WorldWideScience

Sample records for latent structure analysis

  1. The Latent Structure of Autistic Traits: A Taxometric, Latent Class and Latent Profile Analysis of the Adult Autism Spectrum Quotient

    Science.gov (United States)

    James, Richard J.; Dubey, Indu; Smith, Danielle; Ropar, Danielle; Tunney, Richard J.

    2016-01-01

    Autistic traits are widely thought to operate along a continuum. A taxometric analysis of Adult Autism Spectrum Quotient data was conducted to test this assumption, finding little support but identifying a high severity taxon. To understand this further, latent class and latent profile models were estimated that indicated the presence of six…

  2. The structure of posttraumatic stress disorder: latent class analysis in 2 community samples.

    Science.gov (United States)

    Breslau, Naomi; Reboussin, Beth A; Anthony, James C; Storr, Carla L

    2005-12-01

    Latent structure analysis of DSM-IV posttraumatic stress disorder (PTSD) can help clarify how persons who experience traumatic events might be sorted into clusters with respect to their symptom profiles. Classification of persons exposed to traumatic events into clinically homogeneous groups would facilitate further etiologic and treatment research, as well as research on the relationship of trauma and PTSD with other disorders. To examine empirically the structure underlying PTSD criterion symptoms and identify discrete classes with similar symptom profiles. Data on PTSD symptoms from trauma-exposed subsets of 2 community samples were subjected to latent class analysis. The resultant classes were studied in associations with trauma type and indicators of impairment. The first sample is from the Detroit Area Survey of Trauma (1899 trauma-exposed respondents with complete data) and the second is from a mid-Atlantic study of young adults conducted by The Johns Hopkins University Prevention Research Center, Baltimore, Md (1377 trauma-exposed respondents with complete data). Respondents in the 2 community samples who experienced 1 or more qualifying PTSD-level traumatic events. Number, size, and symptom profiles of latent classes. In both samples, analysis yielded 3 classes: no disturbance, intermediate disturbance, and pervasive disturbance. The classes also varied qualitatively, with emotional numbing distinguishing the class of pervasive disturbance, a class that approximates the subset with DSM-IV PTSD. Members of the pervasive disturbance class were far more likely to report use of medical care and disruptions in life or activities. The 3-class structure separates trauma-exposed persons with pervasive disturbance (a class that approximates DSM-IV PTSD) from no disturbance and intermediate disturbance, a distinction that also helps identify population subgroups with low risk for any posttrauma disturbance. The results suggest that the structure of PTSD is ordinal

  3. Does Attention-Deficit/Hyperactivity Disorder Have a Dimensional Latent Structure? A Taxometric Analysis

    Science.gov (United States)

    Marcus, David K.; Barry, Tammy D.

    2010-01-01

    An understanding of the latent structure of attention-deficit/hyperactivity disorder (ADHD) is essential for developing causal models of this disorder. Although some researchers have presumed that ADHD is dimensional and others have assumed that it is taxonic, there has been relatively little research directly examining the latent structure of ADHD. The authors conducted a set of taxometric analyses using data from the NICHD Study of Early Child Care and Youth Development (ns between 667–1078). The results revealed a dimensional latent structure across a variety of different analyses and sets of indicators, for inattention, hyperactivity/impulsivity, and ADHD. Furthermore, analyses of correlations with associated features indicated that dimensional models demonstrated stronger validity coefficients with these criterion measures than dichotomous models. These findings jibe with recent research on the genetic basis of ADHD and with contemporary models of ADHD. PMID:20973595

  4. Does attention-deficit/hyperactivity disorder have a dimensional latent structure? A taxometric analysis.

    Science.gov (United States)

    Marcus, David K; Barry, Tammy D

    2011-05-01

    An understanding of the latent structure of attention-deficit/hyperactivity disorder (ADHD) is essential for developing causal models of this disorder. Although some researchers have presumed that ADHD is dimensional and others have assumed that it is taxonic, there has been relatively little research directly examining the latent structure of ADHD. The authors conducted a set of taxometric analyses using data from the NICHD Study of Early Child Care and Youth Development (ns between 667 and 1,078). The results revealed a dimensional latent structure across a variety of different analyses and sets of indicators for inattention, hyperactivity/impulsivity, and ADHD. Furthermore, analyses of correlations with associated features indicated that dimensional models demonstrated stronger validity coefficients with these criterion measures than dichotomous models. These findings jibe with recent research on the genetic basis of ADHD and with contemporary models of ADHD.

  5. Latent semantic analysis.

    Science.gov (United States)

    Evangelopoulos, Nicholas E

    2013-11-01

    This article reviews latent semantic analysis (LSA), a theory of meaning as well as a method for extracting that meaning from passages of text, based on statistical computations over a collection of documents. LSA as a theory of meaning defines a latent semantic space where documents and individual words are represented as vectors. LSA as a computational technique uses linear algebra to extract dimensions that represent that space. This representation enables the computation of similarity among terms and documents, categorization of terms and documents, and summarization of large collections of documents using automated procedures that mimic the way humans perform similar cognitive tasks. We present some technical details, various illustrative examples, and discuss a number of applications from linguistics, psychology, cognitive science, education, information science, and analysis of textual data in general. WIREs Cogn Sci 2013, 4:683-692. doi: 10.1002/wcs.1254 CONFLICT OF INTEREST: The author has declared no conflicts of interest for this article. For further resources related to this article, please visit the WIREs website. © 2013 John Wiley & Sons, Ltd.

  6. Confirmatory factor analysis reveals a latent cognitive structure common to bipolar disorder, schizophrenia, and normal controls.

    Science.gov (United States)

    Schretlen, David J; Peña, Javier; Aretouli, Eleni; Orue, Izaskun; Cascella, Nicola G; Pearlson, Godfrey D; Ojeda, Natalia

    2013-06-01

    We sought to determine whether a single hypothesized latent factor structure would characterize cognitive functioning in three distinct groups. We assessed 576 adults (340 community controls, 126 adults with bipolar disorder, and 110 adults with schizophrenia) using 15 measures derived from nine cognitive tests. Confirmatory factor analysis (CFA) was conducted to examine the fit of a hypothesized six-factor model. The hypothesized factors included attention, psychomotor speed, verbal memory, visual memory, ideational fluency, and executive functioning. The six-factor model provided an excellent fit for all three groups [for community controls, root mean square error of approximation (RMSEA) schizophrenia, RMSEA = 0.06 and CFI = 0.98]. Alternate models that combined fluency with processing speed or verbal and visual memory reduced the goodness of fit. Multi-group CFA results supported factor invariance across the three groups. Confirmatory factor analysis supported a single six-factor structure of cognitive functioning among patients with schizophrenia or bipolar disorder and community controls. While the three groups clearly differ in level of performance, they share a common underlying architecture of information processing abilities. These cognitive factors could provide useful targets for clinical trials of treatments that aim to enhance information processing in persons with neurological and neuropsychiatric disorders. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  7. Evaluating measurement models in clinical research: covariance structure analysis of latent variable models of self-conception.

    Science.gov (United States)

    Hoyle, R H

    1991-02-01

    Indirect measures of psychological constructs are vital to clinical research. On occasion, however, the meaning of indirect measures of psychological constructs is obfuscated by statistical procedures that do not account for the complex relations between items and latent variables and among latent variables. Covariance structure analysis (CSA) is a statistical procedure for testing hypotheses about the relations among items that indirectly measure a psychological construct and relations among psychological constructs. This article introduces clinical researchers to the strengths and limitations of CSA as a statistical procedure for conceiving and testing structural hypotheses that are not tested adequately with other statistical procedures. The article is organized around two empirical examples that illustrate the use of CSA for evaluating measurement models with correlated error terms, higher-order factors, and measured and latent variables.

  8. Residual Structures in Latent Growth Curve Modeling

    Science.gov (United States)

    Grimm, Kevin J.; Widaman, Keith F.

    2010-01-01

    Several alternatives are available for specifying the residual structure in latent growth curve modeling. Two specifications involve uncorrelated residuals and represent the most commonly used residual structures. The first, building on repeated measures analysis of variance and common specifications in multilevel models, forces residual variances…

  9. Analysis on the public acceptance of nuclear energy using structural equation model with latent variables

    International Nuclear Information System (INIS)

    Lee, Young Eal

    1996-02-01

    Comparison of the effect of education and public information on the public acceptance of nuclear energy is carried out. For the increase of public acceptance, the correct understanding on the nuclear energy via proper regular school education would be the first basis and the appropriate public information services by utility and unbiased mass media would be the second basis. Subjects that which is more effect in education or information and how much effective quantitatively to improve the public acceptance are derived. Structural Equation Model (SEM) with Latent Variables (LVs) in social science to public attitudes towards nuclear energy is developed. Questionnaire is conducted to respondents who took part in the program of visiting the nuclear power plant opened by OKAEA in 1995. As a result of the analysis, effect of education for correct awareness of nuclear energy is more sensitive to public acceptance than that of information. It is shown that the susceptibility in education factor in influence of radiation on human body and that in information factor persons consider nuclear power plant as an environmental polluter. It is concluded that radiation treatment should be a 'Hand on Experience' and general principle of nuclear power generation should be contained in the educational text book. Education and information should not been independently performed but been carried out simultaneously and mutually aided. It is shown that this modeling approach is useful to make the decision for the long-term nuclear energy policy transparent and successful

  10. Multilevel multitrait-multimethod latent analysis of structurally different and interchangeable raters of school climate.

    Science.gov (United States)

    Konold, Timothy; Cornell, Dewey

    2015-09-01

    Informant-based systems of assessment are common platforms for measuring a variety of educational and psychological constructs where the use of multiple informants is considered best practice. In many instances, structurally different informant types (e.g., students and teachers) are solicited on the basis of their unique roles with the target of measurement. The use of multiple informants provides an opportunity to evaluate the degree to which the obtained ratings are influenced by the trait of focus and extraneous sources that can be attributed to the rater. Data from a multilevel multitrait-multimethod design in which students (N = 35,565) and teachers (N = 9,112), from 340 middle schools, responded to items measuring 3 dimensions of school climate were evaluated through a multilevel correlated trait-correlated method latent variable model. Results indicated that ratings of school climate obtained by students and teachers demonstrated high levels of convergent validity, and that school-level ratings obtained by students and teachers were equitable in the assessment of teasing and bullying. Student ratings of support and structure yielded somewhat stronger evidence of convergent validity than ratings obtained by teachers as revealed by their respective trait factor loadings. This was explained in part by the higher levels of common method effects that were observed for teachers. (c) 2015 APA, all rights reserved.

  11. Latent variable models an introduction to factor, path, and structural equation analysis

    CERN Document Server

    Loehlin, John C

    2004-01-01

    This fourth edition introduces multiple-latent variable models by utilizing path diagrams to explain the underlying relationships in the models. The book is intended for advanced students and researchers in the areas of social, educational, clinical, ind

  12. Analysis of heterogeneity and epistasis in physiological mixed populations by combined structural equation modelling and latent class analysis

    DEFF Research Database (Denmark)

    Fenger, Mogens; Linneberg, A.; Werge, Thomas Mears

    2008-01-01

    and genetic variations of such networks. METHODS: In this study on type 2 diabetes mellitus, heterogeneity was resolved in a latent class framework combined with structural equation modelling using phenotypic indicators of distinct physiological processes. We modelled the clinical condition "the metabolic......BACKGROUND: Biological systems are interacting, molecular networks in which genetic variation contributes to phenotypic heterogeneity. This heterogeneity is traditionally modelled as a dichotomous trait (e.g. affected vs. non-affected). This is far too simplistic considering the complexity...

  13. The Latent Structure of Dictionaries.

    Science.gov (United States)

    Vincent-Lamarre, Philippe; Massé, Alexandre Blondin; Lopes, Marcos; Lord, Mélanie; Marcotte, Odile; Harnad, Stevan

    2016-07-01

    How many words-and which ones-are sufficient to define all other words? When dictionaries are analyzed as directed graphs with links from defining words to defined words, they reveal a latent structure. Recursively removing all words that are reachable by definition but that do not define any further words reduces the dictionary to a Kernel of about 10% of its size. This is still not the smallest number of words that can define all the rest. About 75% of the Kernel turns out to be its Core, a "Strongly Connected Subset" of words with a definitional path to and from any pair of its words and no word's definition depending on a word outside the set. But the Core cannot define all the rest of the dictionary. The 25% of the Kernel surrounding the Core consists of small strongly connected subsets of words: the Satellites. The size of the smallest set of words that can define all the rest-the graph's "minimum feedback vertex set" or MinSet-is about 1% of the dictionary, about 15% of the Kernel, and part-Core/part-Satellite. But every dictionary has a huge number of MinSets. The Core words are learned earlier, more frequent, and less concrete than the Satellites, which are in turn learned earlier, more frequent, but more concrete than the rest of the Dictionary. In principle, only one MinSet's words would need to be grounded through the sensorimotor capacity to recognize and categorize their referents. In a dual-code sensorimotor/symbolic model of the mental lexicon, the symbolic code could do all the rest through recombinatory definition. Copyright © 2016 Cognitive Science Society, Inc.

  14. Study on TCM Syndrome Differentiation of Primary Liver Cancer Based on the Analysis of Latent Structural Model

    Directory of Open Access Journals (Sweden)

    Zhan Gu

    2015-01-01

    Full Text Available Primary liver cancer (PLC is one of the most common malignant tumors because of its high incidence and high mortality. Traditional Chinese medicine (TCM plays an active role in the treatment of PLC. As the most important part in the TCM system, syndrome differentiation based on the clinical manifestations from traditional four diagnostic methods has met great challenges and questions with the lack of statistical validation support. In this study, we provided evidences for TCM syndrome differentiation of PLC using the method of analysis of latent structural model from clinic data, thus providing basis for establishing TCM syndrome criteria. And also we obtain the common syndromes of PLC as well as their typical clinical manifestations, respectively.

  15. Study on TCM Syndrome Differentiation of Primary Liver Cancer Based on the Analysis of Latent Structural Model.

    Science.gov (United States)

    Gu, Zhan; Qi, Xiuzhong; Zhai, Xiaofeng; Lang, Qingbo; Lu, Jianying; Ma, Changping; Liu, Long; Yue, Xiaoqiang

    2015-01-01

    Primary liver cancer (PLC) is one of the most common malignant tumors because of its high incidence and high mortality. Traditional Chinese medicine (TCM) plays an active role in the treatment of PLC. As the most important part in the TCM system, syndrome differentiation based on the clinical manifestations from traditional four diagnostic methods has met great challenges and questions with the lack of statistical validation support. In this study, we provided evidences for TCM syndrome differentiation of PLC using the method of analysis of latent structural model from clinic data, thus providing basis for establishing TCM syndrome criteria. And also we obtain the common syndromes of PLC as well as their typical clinical manifestations, respectively.

  16. Evaluating the Latent Structure of the MMPI-2 F(p) Scale in a Forensic Sample: A Taxometric Analysis

    Science.gov (United States)

    Strong, David R.; Glassmire, David M.; Frederick, Richard I.; Greene, Roger L.

    2006-01-01

    P. A. Arbisi and Y. S. Ben-Porath (1995) originally proposed that the Infrequency Psychopathology scale, F(p), be used as the final step in an algorithm to determine the validity of a Minnesota Multiphasic Personality Inventory-2 (MMPI-2) protocol. The current study used taxometric procedures to determine the latent structure of F(p) among…

  17. Learning Latent Structure in Complex Networks

    DEFF Research Database (Denmark)

    Mørup, Morten; Hansen, Lars Kai

    such as the Modularity, it has recently been shown that latent structure in complex networks is learnable by Bayesian generative link distribution models (Airoldi et al., 2008, Hofman and Wiggins, 2008). In this paper we propose a new generative model that allows representation of latent community structure......Latent structure in complex networks, e.g., in the form of community structure, can help understand network dynamics, identify heterogeneities in network properties, and predict ‘missing’ links. While most community detection algorithms are based on optimizing heuristic clustering objectives...... as in the previous Bayesian approaches and in addition allows learning of node specific link properties similar to that in the modularity objective. We employ a new relaxation method for efficient inference in these generative models that allows us to learn the behavior of very large networks. We compare the link...

  18. Sensitivity analysis for linear structural equation models, longitudinal mediation with latent growth models and blended learning in biostatistics education

    Science.gov (United States)

    Sullivan, Adam John

    In chapter 1, we consider the biases that may arise when an unmeasured confounder is omitted from a structural equation model (SEM) and sensitivity analysis techniques to correct for such biases. We give an analysis of which effects in an SEM are and are not biased by an unmeasured confounder. It is shown that a single unmeasured confounder will bias not just one but numerous effects in an SEM. We present sensitivity analysis techniques to correct for biases in total, direct, and indirect effects when using SEM analyses, and illustrate these techniques with a study of aging and cognitive function. In chapter 2, we consider longitudinal mediation with latent growth curves. We define the direct and indirect effects using counterfactuals and consider the assumptions needed for identifiability of those effects. We develop models with a binary treatment/exposure followed by a model where treatment/exposure changes with time allowing for treatment/exposure-mediator interaction. We thus formalize mediation analysis with latent growth curve models using counterfactuals, makes clear the assumptions and extends these methods to allow for exposure mediator interactions. We present and illustrate the techniques with a study on Multiple Sclerosis(MS) and depression. In chapter 3, we report on a pilot study in blended learning that took place during the Fall 2013 and Summer 2014 semesters here at Harvard. We blended the traditional BIO 200: Principles of Biostatistics and created ID 200: Principles of Biostatistics and epidemiology. We used materials from the edX course PH207x: Health in Numbers: Quantitative Methods in Clinical & Public Health Research and used. These materials were used as a video textbook in which students would watch a given number of these videos prior to class. Using surveys as well as exam data we informally assess these blended classes from the student's perspective as well as a comparison of these students with students in another course, BIO 201

  19. The Prospective and Retrospective Memory Questionnaire (PRMQ): latent structure, normative data and discrepancy analysis for proxy-ratings.

    Science.gov (United States)

    Crawford, John R; Henry, Julie D; Ward, Aileen L; Blake, John

    2006-03-01

    To evaluate the proxy-rating version of the Prospective and Retrospective Memory Questionnaire (PRMQ) and provide norms and methods for score interpretation. Cross-sectional and correlational. The PRMQ was administered to a large sample drawn from the general adult population (N=570). Confirmatory factor analysis (CFA) was used to test competing models of its latent structure. Various psychometric methods were applied to provide clinicians with tools for score interpretation. The CFA model with optimal fit specified a general memory factor together with additional prospective and retrospective factors. The reliabilities of the PRMQ were acceptable (.83 to .92), and demographic variables did not influence ratings. Tables are presented for conversion of raw scores on the Total scale and Prospective and Retrospective scales to T scores. In addition, tables are provided to allow users to assess the reliability and abnormality of differences between proxy ratings on the Prospective and Retrospective scales. Finally, tables are also provided to compare proxy-ratings with self-ratings (using data from the present sample and self-rating data from a previous study). The proxy-rating version of the PRMQ provides a useful measure of everyday memory for use in clinical research and practice.

  20. Latent structure and reliability analysis of the measure of body apperception: cross-validation for head and neck cancer patients.

    Science.gov (United States)

    Jean-Pierre, Pascal; Fundakowski, Christopher; Perez, Enrique; Jean-Pierre, Shadae E; Jean-Pierre, Ashley R; Melillo, Angelica B; Libby, Rachel; Sargi, Zoukaa

    2013-02-01

    Cancer and its treatments are associated with psychological distress that can negatively impact self-perception, psychosocial functioning, and quality of life. Patients with head and neck cancers (HNC) are particularly susceptible to psychological distress. This study involved a cross-validation of the Measure of Body Apperception (MBA) for HNC patients. One hundred and twenty-two English-fluent HNC patients between 20 and 88 years of age completed the MBA on a Likert scale ranging from "1 = disagree" to "4 = agree." We assessed the latent structure and internal consistency reliability of the MBA using Principal Components Analysis (PCA) and Cronbach's coefficient alpha (α), respectively. We determined convergent and divergent validities of the MBA using correlations with the Hospital Anxiety and Depression Scale (HADS), observer disfigurement rating, and patients' clinical and demographic variables. The PCA revealed a coherent set of items that explained 38 % of the variance. The Kaiser-Meyer-Olkin measure of sampling adequacy was 0.73 and the Bartlett's test of sphericity was statistically significant (χ (2) (28) = 253.64; p 0.05). The MBA is a valid and reliable screening measure of body apperception for HNC patients.

  1. Evaluation of three 3ABC ELISAs for foot-and-mouth disease non-structural antibodies using latent class analysis

    Directory of Open Access Journals (Sweden)

    Malirat Viviane

    2006-10-01

    Full Text Available Abstract Background Foot-and-mouth disease (FMD is a highly contagious viral disease of even-toed ungulates. Serological diagnosis/surveillance of FMD presents several problems as there are seven serotypes worldwide and in the event of vaccination it may be necessary to be able to identify FMD infected/exposed animals irrespective of their vaccination status. The recent development of non-structural 3ABC protein (NSP ELISA tests has greatly advanced sero-diagnosis/surveillance as these tests detect exposure to live virus for any of the seven serotypes of FMD, even in vaccinated populations. This paper analyses the performance of three NSP tests using a Bayesian formulation of the Hui-Walter latent class model to estimate test sensitivity and specificity in the absence of a "gold-standard" test, using sera from a well described cattle population in Cameroon with endemic FMD. Results The analysis found a high sensitivity and specificity for both the Danish C-ELISA and the World Organisation for Animal Health (O.I.E. recommended South American I-ELISA. However, the commercial CHEKIT kit, though having high specificity, has very low sensitivity. The results of the study suggests that for NSP ELISAs, latent class models are a useful alternative to the traditional approach of evaluating diagnostic tests against a known "gold-standard" test as imperfections in the "gold-standard" may give biased test characteristics. Conclusion This study demonstrates that when applied to naturally infected zebu cattle managed under extensive rangeland conditions, the FMD ELISAs may not give the same parameter estimates as those generated from experimental studies. The Bayesian approach allows for full posterior probabilities and capture of the uncertainty in the estimates. The implications of an imperfect specificity are important for the design and interpretation of sero-surveillance data and may result in excessive numbers of false positives in low prevalence

  2. Latent Growth and Dynamic Structural Equation Models.

    Science.gov (United States)

    Grimm, Kevin J; Ram, Nilam

    2018-05-07

    Latent growth models make up a class of methods to study within-person change-how it progresses, how it differs across individuals, what are its determinants, and what are its consequences. Latent growth methods have been applied in many domains to examine average and differential responses to interventions and treatments. In this review, we introduce the growth modeling approach to studying change by presenting different models of change and interpretations of their model parameters. We then apply these methods to examining sex differences in the development of binge drinking behavior through adolescence and into adulthood. Advances in growth modeling methods are then discussed and include inherently nonlinear growth models, derivative specification of growth models, and latent change score models to study stochastic change processes. We conclude with relevant design issues of longitudinal studies and considerations for the analysis of longitudinal data.

  3. Bayesian Latent Class Analysis Tutorial.

    Science.gov (United States)

    Li, Yuelin; Lord-Bessen, Jennifer; Shiyko, Mariya; Loeb, Rebecca

    2018-01-01

    This article is a how-to guide on Bayesian computation using Gibbs sampling, demonstrated in the context of Latent Class Analysis (LCA). It is written for students in quantitative psychology or related fields who have a working knowledge of Bayes Theorem and conditional probability and have experience in writing computer programs in the statistical language R . The overall goals are to provide an accessible and self-contained tutorial, along with a practical computation tool. We begin with how Bayesian computation is typically described in academic articles. Technical difficulties are addressed by a hypothetical, worked-out example. We show how Bayesian computation can be broken down into a series of simpler calculations, which can then be assembled together to complete a computationally more complex model. The details are described much more explicitly than what is typically available in elementary introductions to Bayesian modeling so that readers are not overwhelmed by the mathematics. Moreover, the provided computer program shows how Bayesian LCA can be implemented with relative ease. The computer program is then applied in a large, real-world data set and explained line-by-line. We outline the general steps in how to extend these considerations to other methodological applications. We conclude with suggestions for further readings.

  4. Generalized latent variable modeling multilevel, longitudinal, and structural equation models

    CERN Document Server

    Skrondal, Anders; Rabe-Hesketh, Sophia

    2004-01-01

    This book unifies and extends latent variable models, including multilevel or generalized linear mixed models, longitudinal or panel models, item response or factor models, latent class or finite mixture models, and structural equation models.

  5. Latent factor structure of a behavioral economic marijuana demand curve.

    Science.gov (United States)

    Aston, Elizabeth R; Farris, Samantha G; MacKillop, James; Metrik, Jane

    2017-08-01

    Drug demand, or relative value, can be assessed via analysis of behavioral economic purchase task performance. Five demand indices are typically obtained from drug purchase tasks. The goal of this research was to determine whether metrics of marijuana reinforcement from a marijuana purchase task (MPT) exhibit a latent factor structure that efficiently characterizes marijuana demand. Participants were regular marijuana users (n = 99; 37.4% female, 71.5% marijuana use days [5 days/week], 15.2% cannabis dependent) who completed study assessments, including the MPT, during a baseline session. Principal component analysis was used to examine the latent structure underlying MPT indices. Concurrent validity was assessed via examination of relationships between latent factors and marijuana use, past quit attempts, and marijuana expectancies. A two-factor solution was confirmed as the best fitting structure, accounting for 88.5% of the overall variance. Factor 1 (65.8% variance) reflected "Persistence," indicating sensitivity to escalating marijuana price, which comprised four MPT indices (elasticity, O max , P max , and breakpoint). Factor 2 (22.7% variance) reflected "Amplitude," indicating the amount consumed at unrestricted price (intensity). Persistence factor scores were associated with fewer past marijuana quit attempts and lower expectancies of negative use outcomes. Amplitude factor scores were associated with more frequent use, dependence symptoms, craving severity, and positive marijuana outcome expectancies. Consistent with research on alcohol and cigarette purchase tasks, the MPT can be characterized with a latent two-factor structure. Thus, demand for marijuana appears to encompass distinct dimensions of price sensitivity and volumetric consumption, with differential relations to other aspects of marijuana motivation.

  6. Latent class models in financial data analysis

    Directory of Open Access Journals (Sweden)

    Attilio Gardini

    2007-10-01

    Full Text Available This paper deals with optimal international portfolio choice by developing a latent class approach based on the distinction between international and non-international investors. On the basis of micro data, we analyze the effects of many social, demographic, economic and financial characteristics on the probability to be an international investor. Traditional measures of equity home bias do not allow for the existence of international investment rationing operators. On the contrary, by resorting to latent class analysis it is possible to detect the unobservable distinction between international investors and investors who are precluded from operating into international financial markets and, therefore, to evaluate the role of these unobservable constraints on equity home bias.

  7. Using existing questionnaires in latent class analysis

    DEFF Research Database (Denmark)

    Nielsen, Anne Molgaard; Vach, Werner; Kent, Peter

    2016-01-01

    BACKGROUND: Latent class analysis (LCA) is increasingly being used in health research, but optimal approaches to handling complex clinical data are unclear. One issue is that commonly used questionnaires are multidimensional, but expressed as summary scores. Using the example of low back pain (LBP......), the aim of this study was to explore and descriptively compare the application of LCA when using questionnaire summary scores and when using single items to subgrouping of patients based on multidimensional data. MATERIALS AND METHODS: Baseline data from 928 LBP patients in an observational study were...

  8. Tweets clustering using latent semantic analysis

    Science.gov (United States)

    Rasidi, Norsuhaili Mahamed; Bakar, Sakhinah Abu; Razak, Fatimah Abdul

    2017-04-01

    Social media are becoming overloaded with information due to the increasing number of information feeds. Unlike other social media, Twitter users are allowed to broadcast a short message called as `tweet". In this study, we extract tweets related to MH370 for certain of time. In this paper, we present overview of our approach for tweets clustering to analyze the users' responses toward tragedy of MH370. The tweets were clustered based on the frequency of terms obtained from the classification process. The method we used for the text classification is Latent Semantic Analysis. As a result, there are two types of tweets that response to MH370 tragedy which is emotional and non-emotional. We show some of our initial results to demonstrate the effectiveness of our approach.

  9. Amatchmethod Based on Latent Semantic Analysis for Earthquakehazard Emergency Plan

    Science.gov (United States)

    Sun, D.; Zhao, S.; Zhang, Z.; Shi, X.

    2017-09-01

    The structure of the emergency plan on earthquake is complex, and it's difficult for decision maker to make a decision in a short time. To solve the problem, this paper presents a match method based on Latent Semantic Analysis (LSA). After the word segmentation preprocessing of emergency plan, we carry out keywords extraction according to the part-of-speech and the frequency of words. Then through LSA, we map the documents and query information to the semantic space, and calculate the correlation of documents and queries by the relation between vectors. The experiments results indicate that the LSA can improve the accuracy of emergency plan retrieval efficiently.

  10. AMATCHMETHOD BASED ON LATENT SEMANTIC ANALYSIS FOR EARTHQUAKEHAZARD EMERGENCY PLAN

    Directory of Open Access Journals (Sweden)

    D. Sun

    2017-09-01

    Full Text Available The structure of the emergency plan on earthquake is complex, and it’s difficult for decision maker to make a decision in a short time. To solve the problem, this paper presents a match method based on Latent Semantic Analysis (LSA. After the word segmentation preprocessing of emergency plan, we carry out keywords extraction according to the part-of-speech and the frequency of words. Then through LSA, we map the documents and query information to the semantic space, and calculate the correlation of documents and queries by the relation between vectors. The experiments results indicate that the LSA can improve the accuracy of emergency plan retrieval efficiently.

  11. Chromatin Structure of Epstein-Barr Virus Latent Episomes.

    Science.gov (United States)

    Lieberman, Paul M

    2015-01-01

    EBV latent infection is characterized by a highly restricted pattern of viral gene expression. EBV can establish latent infections in multiple different tissue types with remarkable variation and plasticity in viral transcription and replication. During latency, the viral genome persists as a multi-copy episome, a non-integrated-closed circular DNA with nucleosome structure similar to cellular chromosomes. Chromatin assembly and histone modifications contribute to the regulation of viral gene expression, DNA replication, and episome persistence during latency. This review focuses on how EBV latency is regulated by chromatin and its associated processes.

  12. The Latent Structure of Secure Base Script Knowledge

    Science.gov (United States)

    Waters, Theodore E. A.; Fraley, R. Chris; Groh, Ashley M.; Steele, Ryan D.; Vaughn, Brian E.; Bost, Kelly K.; Veríssimo, Manuela; Coppola, Gabrielle; Roisman, Glenn I.

    2015-01-01

    There is increasing evidence that attachment representations abstracted from childhood experiences with primary caregivers are organized as a cognitive script describing secure base use and support (i.e., the "secure base script"). To date, however, the latent structure of secure base script knowledge has gone unexamined--this despite…

  13. The Latent Structure of Psychopathy in Youth: A Taxometric Investigation

    Science.gov (United States)

    Vasey, Michael W.; Kotov, Roman; Frick, Paul J.; Loney, Bryan R.

    2005-01-01

    Using taxometric procedures, the latent structure of psychopathy was investigated in two studies of children and adolescents. Prior studies have identified a taxon (i.e., a natural category) associated with antisocial behavior in adults as well as children and adolescents. However, features of this taxon suggest that it is not psychopathy but…

  14. Structuring Latent Consumer Needs using LISREL

    DEFF Research Database (Denmark)

    Poulsen, Carsten Stig; Juhl, H. J.; Kristensen, K.

    1995-01-01

    A LISREL (Linear Structural Relationships) model is formulated according to the hierarchical division of customer needs presented in the literature on Quality Function Deployment (QFD). The purpose is to evaluate the relative importance of first-h impression and taste experience as regards food...

  15. Structuring latent consumer needs using LISREL

    DEFF Research Database (Denmark)

    Juhl, Hans Jørn; Kristensen, Kai; Bech, Anne C.

    1995-01-01

    A LISREL (Linear Structural Relationships) model is formulated according to the hierarchical division of customer needs presented in the literature on Quality Function Deployment (QFD). The purpose is to evaluate the relative importance of first-h impression and taste experience as regards food...

  16. Structuring latent consumer needs using LISREL

    DEFF Research Database (Denmark)

    Juhl, Hans Jørn; Poulsen, Carsten Stig; Kristensen, Kai

    1995-01-01

    Executive summary A LISREL (Linear Structural Relationships) model is formulated according to the hierarchical division of customer needs presented in the literature on Quality Function Deployment (QFD). The purpose is to evaluate the relative importance of first-hand impression and taste...

  17. Standard Errors of Estimated Latent Variable Scores with Estimated Structural Parameters

    Science.gov (United States)

    Hoshino, Takahiro; Shigemasu, Kazuo

    2008-01-01

    The authors propose a concise formula to evaluate the standard error of the estimated latent variable score when the true values of the structural parameters are not known and must be estimated. The formula can be applied to factor scores in factor analysis or ability parameters in item response theory, without bootstrap or Markov chain Monte…

  18. The latent structure of oppositional defiant disorder in children and adults.

    Science.gov (United States)

    Barry, Tammy D; Marcus, David K; Barry, Christopher T; Coccaro, Emil F

    2013-12-01

    An understanding of the latent structure of oppositional defiant disorder (ODD) is essential for better developing causal models, improving diagnostic and assessment procedures, and enhancing treatments for the disorder. Although much research has focused on ODD-including recent studies informing the diagnostic criteria for DSM-5-research examining the latent structure of ODD is sparse, and no known study has specifically undertaken a taxometric analysis to address the issue of whether ODD is a categorical or dimensional construct. To address this gap, the authors conducted two separate studies using a set of taxometric analyses with data from the NICHD Study of Early Child Care and Youth Development (child study; n = 969) and with data from a large mixed sample of adults, which included participants reporting psychiatric difficulties as well as healthy controls (adult study; n = 600). The results of a variety of non-redundant analyses across both studies revealed a dimensional latent structure for ODD symptoms among both children and adults. These findings are consistent with previous studies that have examined latent structure of related constructs (e.g., aggression, antisocial behavior) as well as studies that have examined the dimensional versus categorical structure of ODD using methods other than taxometric analysis. Copyright © 2013 Elsevier Ltd. All rights reserved.

  19. Latent structure and construct validity of the reinforcement sensitivity questionnaire

    Directory of Open Access Journals (Sweden)

    Mitrović Dušanka

    2008-01-01

    Full Text Available The Revised reinforcement sensitivity theory contains three basic systems: Behavioral inhibition system (BAS, Behavioral activation system (BIS and the Fight/ Flight/ Freeze (FFF system. In this model, BIS is a system for detection of potential conflict or threat, and FFFS differs three basic patterns of reaction to actual or perceived danger. In Study 1, which was aimed at the examination of the latent structure of the RSQ, was conducted on a sample of 472 participants of both genders. The best - fitting model suggests that, at the top level of hierarchy, three dimensions exist, which are analogous to the BIS, BAS and FFF. The last dimension contains three subordinate dimensions, which represent the subsystems of the FFF. Study 2, in which 203 subjects participated, was aimed at examination of the relations between the dimensions of the Revised reinforcement sensitivity theory and dimensions of the PEN model. Confirmatory factor analyses of the RSQ and EPQ-R dimensions revealed that the best-fitting model comprised three latent dimensions, the first one being analogous to the BIS - Neuroticism, the second one to the BAS - Extraversion, and the third to the Aggressiveness- Psychoticism. The structure of the latent dimensions is in accordance with the expectations. The results state that fear and anxiety (which neurophysiological distinction is emphasized by Gray, are substantively similar on the behavioral level. Also, the results suggest that the Freeze dimension is probably closer to the BIS system than to the FFF.

  20. Improving knowledge management systems with latent semantic analysis

    International Nuclear Information System (INIS)

    Sebok, A.; Plott, C.; LaVoie, N.

    2006-01-01

    Latent Semantic Analysis (LSA) offers a technique for improving lessons learned and knowledge management systems. These systems are expected to become more widely used in the nuclear industry, as experienced personnel leave and are replaced by younger, less-experienced workers. LSA is a machine learning technology that allows searching of text based on meaning rather than predefined keywords or categories. Users can enter and retrieve data using their own words, rather than relying on constrained language lists or navigating an artificially structured database. LSA-based tools can greatly enhance the usability and usefulness of knowledge management systems and thus provide a valuable tool to assist nuclear industry personnel in gathering and transferring worker expertise. (authors)

  1. Latent Transition Analysis with a Mixture Item Response Theory Measurement Model

    Science.gov (United States)

    Cho, Sun-Joo; Cohen, Allan S.; Kim, Seock-Ho; Bottge, Brian

    2010-01-01

    A latent transition analysis (LTA) model was described with a mixture Rasch model (MRM) as the measurement model. Unlike the LTA, which was developed with a latent class measurement model, the LTA-MRM permits within-class variability on the latent variable, making it more useful for measuring treatment effects within latent classes. A simulation…

  2. Latent cluster analysis of ALS phenotypes identifies prognostically differing groups.

    Directory of Open Access Journals (Sweden)

    Jeban Ganesalingam

    2009-09-01

    Full Text Available Amyotrophic lateral sclerosis (ALS is a degenerative disease predominantly affecting motor neurons and manifesting as several different phenotypes. Whether these phenotypes correspond to different underlying disease processes is unknown. We used latent cluster analysis to identify groupings of clinical variables in an objective and unbiased way to improve phenotyping for clinical and research purposes.Latent class cluster analysis was applied to a large database consisting of 1467 records of people with ALS, using discrete variables which can be readily determined at the first clinic appointment. The model was tested for clinical relevance by survival analysis of the phenotypic groupings using the Kaplan-Meier method.The best model generated five distinct phenotypic classes that strongly predicted survival (p<0.0001. Eight variables were used for the latent class analysis, but a good estimate of the classification could be obtained using just two variables: site of first symptoms (bulbar or limb and time from symptom onset to diagnosis (p<0.00001.The five phenotypic classes identified using latent cluster analysis can predict prognosis. They could be used to stratify patients recruited into clinical trials and generating more homogeneous disease groups for genetic, proteomic and risk factor research.

  3. Multilevel Latent Class Analysis: Parametric and Nonparametric Models

    Science.gov (United States)

    Finch, W. Holmes; French, Brian F.

    2014-01-01

    Latent class analysis is an analytic technique often used in educational and psychological research to identify meaningful groups of individuals within a larger heterogeneous population based on a set of variables. This technique is flexible, encompassing not only a static set of variables but also longitudinal data in the form of growth mixture…

  4. Changes in latent fingerprint examiners' markup between analysis and comparison.

    Science.gov (United States)

    Ulery, Bradford T; Hicklin, R Austin; Roberts, Maria Antonia; Buscaglia, JoAnn

    2015-02-01

    After the initial analysis of a latent print, an examiner will sometimes revise the assessment during comparison with an exemplar. Changes between analysis and comparison may indicate that the initial analysis of the latent was inadequate, or that confirmation bias may have affected the comparison. 170 volunteer latent print examiners, each randomly assigned 22 pairs of prints from a pool of 320 total pairs, provided detailed markup documenting their interpretations of the prints and the bases for their comparison conclusions. We describe changes in value assessments and markup of features and clarity. When examiners individualized, they almost always added or deleted minutiae (90.3% of individualizations); every examiner revised at least some markups. For inconclusive and exclusion determinations, changes were less common, and features were added more frequently when the image pair was mated (same source). Even when individualizations were based on eight or fewer corresponding minutiae, in most cases some of those minutiae had been added during comparison. One erroneous individualization was observed: the markup changes were notably extreme, and almost all of the corresponding minutiae had been added during comparison. Latents assessed to be of value for exclusion only (VEO) during analysis were often individualized when compared to a mated exemplar (26%); in our previous work, where examiners were not required to provide markup of features, VEO individualizations were much less common (1.8%). Published by Elsevier Ireland Ltd.

  5. Preferences, benefits, and park visits: a latent class segmentation analysis

    NARCIS (Netherlands)

    Kemperman, A.D.A.M.; Timmermans, H.J.P.

    2006-01-01

    This study describes and predicts segments of urban park visitors to support park planning and policy making. A latent class analysis is used to identify segments of park users who differ regarding their preferences for park characteristics, benefits sought in park visits, and sociodemographics.

  6. The Latent Class Structure of Chinese Patients with Eating Disorders in Shanghai.

    Science.gov (United States)

    Zheng, Yuchen; Kang, Qing; Huang, Jiabin; Jiang, Wenhui; Liu, Qiang; Chen, Han; Fan, Qing; Wang, Zhen; Chen, Jue; Xiao, Zeping

    2017-08-25

    Eating disorder is culture related, and the clinical symptoms are different between eastern and western patients. So the validity of feeding and eating disorders in the upcoming ICD-11 guide for Chinese patients is unclear. To explore the latent class structure of Chinese patients with eating disorder and the cross-cultural validity of the eating disorder section of the new ICD-11 guide in China. A total of 379 patients with eating disorders at Shanghai Mental Health Center were evaluated using the EDI questionnaire and a questionnaire developed by researchers from 2010 to 2016. SPSS 20.0 was used to enter data and analyze demographic data, and Latent GOLD was employed to conduct latent profile analysis. According to the results of latent profile analysis, patients with eating disorder were divided into five classes: low-weight fasting class (23.1%), non-fat-phobic binge/purge class (21.54%), low-fat-phobic binge class (19.27%), fat-phobic binge class (19.27%), and non-fat-phobic low-weight class (16.76%). Among the clinical symptoms extracted, there were significant differences in Body Mass Index (BMI), binge eating behavior, self-induced vomiting, laxative use and fat-phobic opinion; while there was no significant difference in restrictive food intake. Based on the clinical symptoms, there are five latent classes in Chinese patients with eating disorder, which is in accordance with the diagnostic categories of feeding and eating disorder in ICD-11. However, further work is needed in improving the fat-phobic opinion of patients with eating disorder and clarifying the BMI standard of thinness in the Chinese population.

  7. LATENT STRUCTURE OF MOTOR ABILITIES AND SKILLS OF DEAF CHILDREN

    Directory of Open Access Journals (Sweden)

    Husnija Hasanbegović

    2012-04-01

    Full Text Available In this work surveys of latent motility abilities and skills of school children are shown. The sample for this survey was consisted of two subsamples. First one has consisted of deaf children N=29, and the second one has consisted hearing children of same age N=69. Subsamples of deaf is chosen according to model of applied sample, and subsample is chosen randomly, so two stages group sample N=90 has been created. After quantitative differences have been discovered between subsamples, hearing pupils have shown statistically better results at motility skills and techniques than deaf children and cumulative results have been subjected to inter correlation of variables. The target of using this method was determination of saturation of common variability through saturation of variables and their correlation by Ortoblique rotation for determination of latent information that are going to serve as practical guides at education and deaf children treatment, because of improvement of their motility abilities and skills according to hearing children. Three factors have been singled out as main preview of measurement on manifest variables. According to first review of measuring it has been established that at deaf children is needed to work on improving of physical abilities and mobility and then developed motility abilities and skills. Their information has been gained most probably by non system fluctuations as information about ability of balance maintaining which is most probably non dependable of motility abilities and skills as at deaf and hearing children too. According to this survey by entering the structure of measuring instrument it is possible to create programs for improving motility abilities and skills at deaf children.

  8. Disintermediation and User-generated Content: A Latent Segmentation Analysis

    OpenAIRE

    Del Chiappa, Giacomo; Lorenzo-Romero, Carlota; Constantinides, Efthymios

    2014-01-01

    This research investigates the perceptions of different groups of consumers for and against the disintermediation of travel agencies also considering the relative power in influencing the tourist's choices exerted by user generated-content (UGC). A web-based survey is carried out in Spain and 961 complete questionnaires was obtained. A latent segmentation was applied on factors identified running an exploratory factor analysis on a list of 16 statements, the use and frequency of use of the In...

  9. Latent-Trait Latent-Class Analysis of Self-disclosure in the Work Environment

    NARCIS (Netherlands)

    Maij - de Meij, A.M.; Kelderman, H.; van der Flier, H.

    2005-01-01

    Based on the literature about self-disclosure, it was hypothesized that different groups of subjects differ in their pattern of self-disclosure with respect to different areas of social interaction. An extended latent-trait latent-class model was proposed to describe these general patterns of

  10. Latent-trait latent-class analysis of selfdisclosure in the work environment

    NARCIS (Netherlands)

    Maij - de Meij, A.M.; Kelderman, H.; van der Flier, H.

    2006-01-01

    Based on the literature about self-disclosure, it was hypothesized that different groups of subjects differ in their pattern of self-disclosure with respect to different areas of social interaction. An extended latent-trait latent-class model was proposed to describe these general patterns of

  11. Latent-Trait Latent-Class Analysis of Self-Disclosure in the Work Environment

    Science.gov (United States)

    Maij-de Meij, Annette M.; Kelderman, Henk; van der Flier, Henk

    2005-01-01

    Based on the literature about self-disclosure, it was hypothesized that different groups of subjects differ in their pattern of self-disclosure with respect to different areas of social interaction. An extended latent-trait latent-class model was proposed to describe these general patterns of self-disclosure. The model was used to analyze the data…

  12. Latent-trait latent-class analysis of selfdisclosure in the work environment

    NARCIS (Netherlands)

    Maij - de Meij, A.M.; Kelderman, H.; van der Flier, H.

    2005-01-01

    Based on the literature about self-disclosure, it was hypothesized that different groups of subjects differ in their pattern of self-disclosure with respect to different areas of social interaction. An extended latent-trait latent-class model was proposed to describe these general patterns of

  13. Structural identifiability of cyclic graphical models of biological networks with latent variables.

    Science.gov (United States)

    Wang, Yulin; Lu, Na; Miao, Hongyu

    2016-06-13

    Graphical models have long been used to describe biological networks for a variety of important tasks such as the determination of key biological parameters, and the structure of graphical model ultimately determines whether such unknown parameters can be unambiguously obtained from experimental observations (i.e., the identifiability problem). Limited by resources or technical capacities, complex biological networks are usually partially observed in experiment, which thus introduces latent variables into the corresponding graphical models. A number of previous studies have tackled the parameter identifiability problem for graphical models such as linear structural equation models (SEMs) with or without latent variables. However, the limited resolution and efficiency of existing approaches necessarily calls for further development of novel structural identifiability analysis algorithms. An efficient structural identifiability analysis algorithm is developed in this study for a broad range of network structures. The proposed method adopts the Wright's path coefficient method to generate identifiability equations in forms of symbolic polynomials, and then converts these symbolic equations to binary matrices (called identifiability matrix). Several matrix operations are introduced for identifiability matrix reduction with system equivalency maintained. Based on the reduced identifiability matrices, the structural identifiability of each parameter is determined. A number of benchmark models are used to verify the validity of the proposed approach. Finally, the network module for influenza A virus replication is employed as a real example to illustrate the application of the proposed approach in practice. The proposed approach can deal with cyclic networks with latent variables. The key advantage is that it intentionally avoids symbolic computation and is thus highly efficient. Also, this method is capable of determining the identifiability of each single parameter and

  14. Latent Factor Structure of DSM-5 Posttraumatic Stress Disorder

    Science.gov (United States)

    Gentes, Emily; Dennis, Paul A.; Kimbrel, Nathan A.; Kirby, Angela C.; Hair, Lauren P.; Beckham, Jean C.; Calhoun, Patrick S.

    2015-01-01

    The current study examined the latent factor structure of posttraumatic stress disorder (PTSD) based on DSM-5 criteria in a sample of participants (N = 374) recruited for studies on trauma and health. Confirmatory factor analyses (CFA) were used to compare the fit of the previous 3-factor DSM-IV model of PTSD to the 4-factor model specified in DSM-5 as well as to a competing 4-factor “dysphoria” model (Simms, Watson, & Doebbeling, 2002) and a 5-factor (Elhai et al., 2011) model of PTSD. Results indicated that the Elhai 5-factor model (re-experiencing, active avoidance, emotional numbing, dysphoric arousal, anxious arousal) provided the best fit to the data, although substantial support was demonstrated for the DSM-5 4-factor model. Low factor loadings were noted for two of the symptoms in the DSM-5 model (psychogenic amnesia and reckless/self-destructive behavior), which raises questions regarding the adequacy of fit of these symptoms with other core features of the disorder. Overall, the findings from the present research suggest the DSM-5 model of PTSD is a significant improvement over the previous DSM-IV model of PTSD. PMID:26366290

  15. [Latent Class Analysis of Gambling Activities among Korean Adolescents].

    Science.gov (United States)

    Kang, Kyonghwa; Kim, Hyeongsu; Park, Ae Ran; Kim, Hee Young; Lee, Kunsei

    2018-04-01

    The aim of this study is to identify the types of gambling among adolescents and provide basic prevention information regarding adolescents' gambling problems. Secondary data from representative national survey on 2015 Youth Gambling Problems of Korea Center on Gambling Problems were used. Using latent class analysis (LCA), 13 gambling types such as offline and online games of 14,011 adolescents were classified, and gambling experiences and characteristics were analyzed. The subgroups of adolescent gambling were identified as four latent classes: a rare group (84.5% of the sample), a risk group (1.0%), an offline group (11.9%), and an expanded group (2.6%). The types and characteristics of gambling among the latent classes differed. In the risk group, adolescents participated in online illegal sports betting and internet casino, and gambling time, gambling expenses, and the number of gambling types were higher than other groups. Gambling frequently occur among adolescent, and the subtypes of gambling did not reveal homogeneous characteristics. In order to prevent adolescent gambling problems, it is a necessary to develop tailored prevention intervention in the nursing field, which is appropriate to the characteristics of adolescent gambling group and can help with early identification. © 2018 Korean Society of Nursing Science.

  16. A Taxonomy of Latent Structure Assumptions for Probability Matrix Decomposition Models.

    Science.gov (United States)

    Meulders, Michel; De Boeck, Paul; Van Mechelen, Iven

    2003-01-01

    Proposed a taxonomy of latent structure assumptions for probability matrix decomposition (PMD) that includes the original PMD model and a three-way extension of the multiple classification latent class model. Simulation study results show the usefulness of the taxonomy. (SLD)

  17. Computer assessment of interview data using latent semantic analysis.

    Science.gov (United States)

    Dam, Gregory; Kaufmann, Stefan

    2008-02-01

    Clinical interviews are a powerful method for assessing students' knowledge and conceptualdevelopment. However, the analysis of the resulting data is time-consuming and can create a "bottleneck" in large-scale studies. This article demonstrates the utility of computational methods in supporting such an analysis. Thirty-four 7th-grade student explanations of the causes of Earth's seasons were assessed using latent semantic analysis (LSA). Analyses were performed on transcriptions of student responses during interviews administered, prior to (n = 21) and after (n = 13) receiving earth science instruction. An instrument that uses LSA technology was developed to identify misconceptions and assess conceptual change in students' thinking. Its accuracy, as determined by comparing its classifications to the independent coding performed by four human raters, reached 90%. Techniques for adapting LSA technology to support the analysis of interview data, as well as some limitations, are discussed.

  18. The Latent Structure of Attention Deficit/Hyperactivity Disorder in an Adult Sample

    Science.gov (United States)

    Marcus, David K.; Norris, Alyssa L.; Coccaro, Emil F.

    2012-01-01

    The vast majority of studies that have examined the latent structure of attention deficit/hyperactivity disorder (ADHD) in children and adolescents have concluded that ADHD has a dimensional latent structure. In other words, ADHD symptomatology exists along a continuum and there is no natural boundary or qualitative distinction (i.e., taxon) separating youth with ADHD from those with subclinical inattention or hyperactivity/impulsivity problems. Although adult ADHD appears to be less prevalent than ADHD in youth (which could suggest a more severe adult ADHD taxon), researchers have yet to examine the latent structure of ADHD in adults. The present study used a sample (N = 600) of adults who completed a self-report measure of ADHD symptoms. The taxometric analyses revealed a dimensional latent structure for inattention, hyperactivity/impulsivity, and ADHD. These findings are consistent with previous taxometric studies that examined ADHD in children and adolescents, and with contemporary polygenic and multifactorial models of ADHD. PMID:22480749

  19. Dissociative features in posttraumatic stress disorder: A latent profile analysis.

    Science.gov (United States)

    Műllerová, Jana; Hansen, Maj; Contractor, Ateka A; Elhai, Jon D; Armour, Cherie

    2016-09-01

    The fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) characterizes the dissociative subtype of posttraumatic stress disorder (PTSD) in terms of the individual meeting the criteria for PTSD and additionally reporting symptoms of depersonalization and/or derealization. The current study aimed to examine whether a dissociative PTSD profile may include alternative features of dissociation and whether it could be differentiated from a nondissociative PTSD profile on certain psychopathologies and demographics. Data from 309 trauma-exposed participants, collected through Amazon Mechanical Turk, were subjected to latent profile analysis. Regression analyses were used to examine the predictors of latent classes. Three discrete profiles named Baseline, PTSD, and Dissociative profile were uncovered. All examined features of dissociation were significantly elevated in the Dissociative profile. Anxiety, male sex, being employed, and having a minority racial background significantly predicted the Dissociative profile relative to the PTSD profile. The study points to the importance of alternative symptoms of dissociation in the dissociative PTSD subtype beyond the symptoms of depersonalization and derealization. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  20. Perbandingan Hasil Deteksi Plagiarisme Dokumen dengan Metode Jaro-Winkler Distance dan Metode Latent Semantic Analysis

    Directory of Open Access Journals (Sweden)

    Tinaliah Tinaliah

    2018-01-01

    Full Text Available Various methods are applied in the application of plagiarism detection to help check the similarity of a document. Jaro-Winkler Distance can measure the distance between two strings. However, this method basically depends on the position of the word. Latent Semantic Analysis emphasizes the words contained in the document regardless of its linguistic character. This study compares the results of plagiarism detection using the Jaro-Winkler Distance and the Latent Semantic Analysis method. From comparing results of  Jaro-Winkler Distance method and Latent Semantic Analysis method, Jaro-Winkler Distance method is better than Latent Semantic Analysis method if using the same test data. Jaro-Winkler Distance method will give plagiarism result 100% and Latent Semantic Analysis method will give plagiarism result 97,14%. Beragam metode diterapkan dalam aplikasi deteksi plagiarisme untuk membantu mengecek tingkat kesamaan sebuah dokumen. Metode Jaro-Winkler Distance dapat mengukur kesamaan antara dua buah string dan sangat bergantung pada urutan atau posisi kata. Latent Semantic Analysis mementingkan kata-kata yang terkandung di dalam dokumen tanpa memperhatikan karakter linguistiknya. Penelitian ini melakukan perbandingan hasil deteksi plagiarisme dengan menggunakan metode Jaro-Winkler Distance dan metode Latent Semantic Analysis. Hasil pendeteksian plagiarisme dokumen menggunakan metode Jaro-Winkler Distance memberikan hasil yang lebih baik daripada metode Latent Semantic Analysis, yaitu jika data yang dibandingkan sama persis maka akan menghasilkan nilai plagiat sebesar 100%, sedangkan metode Latent Semantic Analysis menghasilkan nilai plagiat sebesar 97,14%.

  1. Obesogenic family types identified through latent profile analysis.

    Science.gov (United States)

    Martinson, Brian C; VazquezBenitez, Gabriela; Patnode, Carrie D; Hearst, Mary O; Sherwood, Nancy E; Parker, Emily D; Sirard, John; Pasch, Keryn E; Lytle, Leslie

    2011-10-01

    Obesity may cluster in families due to shared physical and social environments. This study aims to identify family typologies of obesity risk based on family environments. Using 2007-2008 data from 706 parent/youth dyads in Minnesota, we applied latent profile analysis and general linear models to evaluate associations between family typologies and body mass index (BMI) of youth and parents. Three typologies described most families with 18.8% "Unenriched/Obesogenic," 16.9% "Risky Consumer," and 64.3% "Healthy Consumer/Salutogenic." After adjustment for demographic and socioeconomic factors, parent BMI and youth BMI Z-scores were higher in unenriched/obesogenic families (BMI difference = 2.7, p typology. In contrast, parent BMI and youth BMI Z-scores were similar in the risky consumer families relative to those in healthy consumer/salutogenic type. We can identify family types differing in obesity risks with implications for public health interventions.

  2. Identifying subgroups of patients using latent class analysis

    DEFF Research Database (Denmark)

    Nielsen, Anne Mølgaard; Kent, Peter; Hestbæk, Lise

    2017-01-01

    BACKGROUND: Heterogeneity in patients with low back pain (LBP) is well recognised and different approaches to subgrouping have been proposed. Latent Class Analysis (LCA) is a statistical technique that is increasingly being used to identify subgroups based on patient characteristics. However......, as LBP is a complex multi-domain condition, the optimal approach when using LCA is unknown. Therefore, this paper describes the exploration of two approaches to LCA that may help improve the identification of clinically relevant and interpretable LBP subgroups. METHODS: From 928 LBP patients consulting...... of statistical performance measures, qualitative evaluation of clinical interpretability (face validity) and a subgroup membership comparison. RESULTS: For the single-stage LCA, a model solution with seven patient subgroups was preferred, and for the two-stage LCA, a nine patient subgroup model. Both approaches...

  3. PTSD's latent structure in Malaysian tsunami victims: assessing the newly proposed Dysphoric Arousal model.

    Science.gov (United States)

    Armour, Cherie; Raudzah Ghazali, Siti; Elklit, Ask

    2013-03-30

    The underlying latent structure of Posttraumatic Stress Disorder (PTSD) is widely researched. However, despite a plethora of factor analytic studies, no single model has consistently been shown as superior to alternative models. The two most often supported models are the Emotional Numbing and the Dysphoria models. However, a recently proposed five-factor Dysphoric Arousal model has been gathering support over and above existing models. Data for the current study were gathered from Malaysian Tsunami survivors (N=250). Three competing models (Emotional Numbing/Dysphoria/Dysphoric Arousal) were specified and estimated using Confirmatory Factor Analysis (CFA). The Dysphoria model provided superior fit to the data compared to the Emotional Numbing model. However, using chi-square difference tests, the Dysphoric Arousal model showed a superior fit compared to both the Emotional Numbing and Dysphoria models. In conclusion, the current results suggest that the Dysphoric Arousal model better represents PTSD's latent structure and that items measuring sleeping difficulties, irritability/anger and concentration difficulties form a separate, unique PTSD factor. These results are discussed in relation to the role of Hyperarousal in PTSD's on-going symptom maintenance and in relation to the DSM-5. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  4. A quantitative analysis on latent heat of an aqueous binary mixture.

    Science.gov (United States)

    Han, Bumsoo; Choi, Jeung Hwan; Dantzig, Jonathan A; Bischof, John C

    2006-02-01

    The latent heat during phase change of water-NaCl binary mixture was measured using a differential scanning calorimeter, and the magnitude for two distinct phase change events, water/ice and eutectic phase change, were analyzed considering the phase change characteristics of a binary mixture. During the analysis, the latent heat associated with each event was calculated by normalizing the amount of each endothermic peak with only the amount of sample participating in each event estimated from the lever rule for the phase diagram. The resulting latent heat of each phase change measured is 303.7 +/- 2.5 J/g for water/ice phase change, and 233.0 +/- 1.6 J/g for eutectic phase change, respectively regardless of the initial concentration of mixture. Although the latent heats of water/ice phase change in water-NaCl mixtures are closely correlated, further study is warranted to investigate the reason for smaller latent heat of water/ice phase change than that in pure water (335 J/g). The analysis using the lever rule was extended to estimate the latent heat of dihydrate as 115 J/g with the measured eutectic and water/ice latent heat values. This new analysis based on the lever rule will be useful to estimate the latent heat of water-NaCl mixtures at various concentrations, and may become a framework for more general analysis of latent heat of various biological solutions.

  5. Do gender and directness of trauma exposure moderate PTSD's latent structure?

    Science.gov (United States)

    Frankfurt, Sheila B; Armour, Cherie; Contractor, Ateka A; Elhai, Jon D

    2016-11-30

    The PTSD diagnosis and latent structure were substantially revised in the transition from DSM-IV to DSM-5. However, three alternative models (i.e., anhedonia model, externalizing behavior model, and hybrid model) of PTSD fit the DSM-5 symptom criteria better than the DSM-5 factor model. Thus, the psychometric performance of the DSM-5 and alternative models' PTSD factor structure needs to be critically evaluated. The current study examined whether gender or trauma directness (i.e., direct or indirect trauma exposure) moderates the PTSD latent structure when using the DSM-5 or alternative models. Model performance was evaluated with measurement invariance testing procedures on a large undergraduate sample (n=455). Gender and trauma directness moderated the DSM-5 PTSD and externalizing behavior model and did not moderate the anhedonia and hybrid models' latent structure. Clinical implications and directions for future research are discussed. Published by Elsevier Ireland Ltd.

  6. Mixture simultaneous factor analysis for capturing differences in latent variables between higher level units of multilevel data

    NARCIS (Netherlands)

    De Roover, K.; Vermunt, J.K.; Timmerman, Marieke E.; Ceulemans, Eva

    2017-01-01

    Given multivariate data, many research questions pertain to the covariance structure: whether and how the variables (for example, personality measures) covary. Exploratory factor analysis (EFA) is often used to look for latent variables that may explain the covariances among variables; for example,

  7. A fully Bayesian latent variable model for integrative clustering analysis of multi-type omics data.

    Science.gov (United States)

    Mo, Qianxing; Shen, Ronglai; Guo, Cui; Vannucci, Marina; Chan, Keith S; Hilsenbeck, Susan G

    2018-01-01

    Identification of clinically relevant tumor subtypes and omics signatures is an important task in cancer translational research for precision medicine. Large-scale genomic profiling studies such as The Cancer Genome Atlas (TCGA) Research Network have generated vast amounts of genomic, transcriptomic, epigenomic, and proteomic data. While these studies have provided great resources for researchers to discover clinically relevant tumor subtypes and driver molecular alterations, there are few computationally efficient methods and tools for integrative clustering analysis of these multi-type omics data. Therefore, the aim of this article is to develop a fully Bayesian latent variable method (called iClusterBayes) that can jointly model omics data of continuous and discrete data types for identification of tumor subtypes and relevant omics features. Specifically, the proposed method uses a few latent variables to capture the inherent structure of multiple omics data sets to achieve joint dimension reduction. As a result, the tumor samples can be clustered in the latent variable space and relevant omics features that drive the sample clustering are identified through Bayesian variable selection. This method significantly improve on the existing integrative clustering method iClusterPlus in terms of statistical inference and computational speed. By analyzing TCGA and simulated data sets, we demonstrate the excellent performance of the proposed method in revealing clinically meaningful tumor subtypes and driver omics features. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  8. A Systematic Approach for Identifying Level-1 Error Covariance Structures in Latent Growth Modeling

    Science.gov (United States)

    Ding, Cherng G.; Jane, Ten-Der; Wu, Chiu-Hui; Lin, Hang-Rung; Shen, Chih-Kang

    2017-01-01

    It has been pointed out in the literature that misspecification of the level-1 error covariance structure in latent growth modeling (LGM) has detrimental impacts on the inferences about growth parameters. Since correct covariance structure is difficult to specify by theory, the identification needs to rely on a specification search, which,…

  9. Latent class analysis of the Yale-Brown Obsessive-Compulsive Scale symptoms in obsessive-compulsive disorder.

    Science.gov (United States)

    Delucchi, Kevin L; Katerberg, Hilga; Stewart, S Evelyn; Denys, Damiaan A J P; Lochner, Christine; Stack, Denise E; den Boer, Johan A; van Balkom, Anton J L M; Jenike, Michael A; Stein, Dan J; Cath, Danielle C; Mathews, Carol A

    2011-01-01

    Obsessive-compulsive disorder (OCD) is phenomenologically heterogeneous, and findings of underlying structure classification based on symptom grouping have been ambiguous to date. Variable-centered approaches, primarily factor analysis, have been used to identify homogeneous groups of symptoms; but person-centered latent methods have seen little use. This study was designed to uncover sets of homogeneous groupings within 1611 individuals with OCD based on symptoms. Latent class analysis models using 61 obsessive-compulsive symptoms collected from the Yale-Brown Obsessive-Compulsive Scale were fit. Relationships between latent class membership and treatment response, sex, symptom severity, and comorbid tic disorders were tested for relationship to class membership. Latent class analysis models of best fit yielded 3 classes. Classes differed only in frequency of symptom endorsement. Classes with higher symptom endorsement were associated with earlier age of onset, being male, higher Yale-Brown Obsessive-Compulsive Scale symptom severity scores, and comorbid tic disorders. There were no differences in treatment response between classes. These results provide support for the validity of a single underlying latent OCD construct, in addition to the distinct symptom factors identified previously via factor analyses. Copyright © 2011 Elsevier Inc. All rights reserved.

  10. Modeling Psychological Attributes in Psychology – An Epistemological Discussion: Network Analysis vs. Latent Variables

    Science.gov (United States)

    Guyon, Hervé; Falissard, Bruno; Kop, Jean-Luc

    2017-01-01

    Network Analysis is considered as a new method that challenges Latent Variable models in inferring psychological attributes. With Network Analysis, psychological attributes are derived from a complex system of components without the need to call on any latent variables. But the ontological status of psychological attributes is not adequately defined with Network Analysis, because a psychological attribute is both a complex system and a property emerging from this complex system. The aim of this article is to reappraise the legitimacy of latent variable models by engaging in an ontological and epistemological discussion on psychological attributes. Psychological attributes relate to the mental equilibrium of individuals embedded in their social interactions, as robust attractors within complex dynamic processes with emergent properties, distinct from physical entities located in precise areas of the brain. Latent variables thus possess legitimacy, because the emergent properties can be conceptualized and analyzed on the sole basis of their manifestations, without exploring the upstream complex system. However, in opposition with the usual Latent Variable models, this article is in favor of the integration of a dynamic system of manifestations. Latent Variables models and Network Analysis thus appear as complementary approaches. New approaches combining Latent Network Models and Network Residuals are certainly a promising new way to infer psychological attributes, placing psychological attributes in an inter-subjective dynamic approach. Pragmatism-realism appears as the epistemological framework required if we are to use latent variables as representations of psychological attributes. PMID:28572780

  11. STRUCTURE RELATION OF VIOLENCE AND PERSONALITY LATENT DIMENSIONS OF PREADOLESCENT BASKETBALL PLAYERS

    Directory of Open Access Journals (Sweden)

    Miroljub Ivanović

    2012-09-01

    Full Text Available The aim of this research was to define structure relations of latent dimension violence among peers structure, characteristics and parent’s educational attitudes. In this research participated 134 basketball players (mini-jam, younger pioneers and pioneers. The research was conducted using the PRONA questionnaire for peers violence evaluation (Maksimovic and collaborators, 2008. Analysing the main components space of peers’ violence, three main components have been determined as dangerous behaviour exposure, announced victim and physiological violence. Mutual relation of these latent personality characteristics examinees dimensions and educational attitudes of their parents has been determined using the Pirson’s correlation coefficien.

  12. Comparing methods of classifying life courses: Sequence analysis and latent class analysis

    NARCIS (Netherlands)

    Elzinga, C.H.; Liefbroer, Aart C.; Han, Sapphire

    2017-01-01

    We compare life course typology solutions generated by sequence analysis (SA) and latent class analysis (LCA). First, we construct an analytic protocol to arrive at typology solutions for both methodologies and present methods to compare the empirical quality of alternative typologies. We apply this

  13. Comparing methods of classifying life courses: sequence analysis and latent class analysis

    NARCIS (Netherlands)

    Han, Y.; Liefbroer, A.C.; Elzinga, C.

    2017-01-01

    We compare life course typology solutions generated by sequence analysis (SA) and latent class analysis (LCA). First, we construct an analytic protocol to arrive at typology solutions for both methodologies and present methods to compare the empirical quality of alternative typologies. We apply this

  14. Enhancing multilingual latent semantic analysis with term alignment information.

    Energy Technology Data Exchange (ETDEWEB)

    Chew, Peter A.; Bader, Brett William

    2008-08-01

    Latent Semantic Analysis (LSA) is based on the Singular Value Decomposition (SVD) of a term-by-document matrix for identifying relationships among terms and documents from co-occurrence patterns. Among the multiple ways of computing the SVD of a rectangular matrix X, one approach is to compute the eigenvalue decomposition (EVD) of a square 2 x 2 composite matrix consisting of four blocks with X and XT in the off-diagonal blocks and zero matrices in the diagonal blocks. We point out that significant value can be added to LSA by filling in some of the values in the diagonal blocks (corresponding to explicit term-to-term or document-to-document associations) and computing a term-by-concept matrix from the EVD. For the case of multilingual LSA, we incorporate information on cross-language term alignments of the same sort used in Statistical Machine Translation (SMT). Since all elements of the proposed EVD-based approach can rely entirely on lexical statistics, hardly any price is paid for the improved empirical results. In particular, the approach, like LSA or SMT, can still be generalized to virtually any language(s); computation of the EVD takes similar resources to that of the SVD since all the blocks are sparse; and the results of EVD are just as economical as those of SVD.

  15. Study The role of latent variables in lost working days by Structural Equation Modeling Approach

    Directory of Open Access Journals (Sweden)

    Meysam Heydari

    2016-12-01

    Full Text Available Background: Based on estimations, each year about 250 million work-related injuries and many temporary or permanent disabilities occur which most are preventable. Oil and Gas industries are among industries with high incidence of injuries in the world. The aim of this study has investigated  the role and effect of different risk management variables on lost working days (LWD in the seismic projects. Methods: This study was a retrospective, cross-sectional and systematic analysis, which was carried out on occupational accidents between 2008-2015(an 8 years period in different seismic projects for oilfield exploration at Dana Energy (Iranian Seismic Company. The preliminary sample size of the study were 487accidents. A systems analysis approach were applied by using root case analysis (RCA and structural equation modeling (SEM. Tools for the data analysis were included, SPSS23 and AMOS23  software. Results: The mean of lost working days (LWD, was calculated 49.57, the final model of structural equation modeling showed that latent variables of, safety and health training factor(-0.33, risk assessment factor(-0.55 and risk control factor (-0.61 as direct causes significantly affected of lost working days (LWD in the seismic industries (p< 0.05. Conclusion: The finding of present study revealed that combination of variables affected in lost working days (LWD. Therefore,the role of these variables in accidents should be investigated and suitable programs should be considered for them.

  16. Probabilistic Latent Semantic Analyses (PLSA in Bibliometric Analysis for Technology Forecasting

    Directory of Open Access Journals (Sweden)

    Wang Zan

    2007-03-01

    Full Text Available Due to the availability of internet-based abstract services and patent databases, bibliometric analysis has become one of key technology forecasting approaches. Recently, latent semantic analysis (LSA has been applied to improve the accuracy in document clustering. In this paper, a new LSA method, probabilistic latent semantic analysis (PLSA which uses probabilistic methods and algebra to search latent space in the corpus is further applied in document clustering. The results show that PLSA is more accurate than LSA and the improved iteration method proposed by authors can simplify the computing process and improve the computing efficiency

  17. A Latent Class Analysis of Heterosexual Young Men's Masculinities.

    Science.gov (United States)

    Casey, Erin A; Masters, N Tatiana; Beadnell, Blair; Wells, Elizabeth A; Morrison, Diane M; Hoppe, Marilyn J

    2016-07-01

    Parallel bodies of research have described the diverse and complex ways that men understand and construct their masculine identities (often termed "masculinities") and, separately, how adherence to traditional notions of masculinity places men at risk for negative sexual and health outcomes. The goal of this analysis was to bring together these two streams of inquiry. Using data from a national, online sample of 555 heterosexually active young men, we employed latent class analysis (LCA) to detect patterns of masculine identities based on men's endorsement of behavioral and attitudinal indicators of "dominant" masculinity, including sexual attitudes and behaviors. LCA identified four conceptually distinct masculine identity profiles. Two groups, termed the Normative and Normative/Male Activities groups, respectively, constituted 88 % of the sample and were characterized by low levels of adherence to attitudes, sexual scripts, and behaviors consistent with "dominant" masculinity, but differed in their levels of engagement in male-oriented activities (e.g., sports teams). Only eight percent of the sample comprised a masculinity profile consistent with "traditional" ideas about masculinity; this group was labeled Misogynistic because of high levels of sexual assault and violence toward female partners. The remaining four percent constituted a Sex-Focused group, characterized by high numbers of sexual partners, but relatively low endorsement of other indicators of traditional masculinity. Follow-up analyses showed a small number of differences across groups on sexual and substance use health indicators. Findings have implications for sexual and behavioral health interventions and suggest that very few young men embody or endorse rigidly traditional forms of masculinity.

  18. Latent Class Analysis of Criminal Social Identity in a Prison Sample

    Directory of Open Access Journals (Sweden)

    Boduszek Daniel

    2014-06-01

    Full Text Available This study aimed to examine the number of latent classes of criminal social identity that exist among male recidivistic prisoners. Latent class analysis was used to identify homogeneous groups of criminal social identity. Multinomial logistic regression was used to interpret the nature of the latent classes, or groups, by estimating the associationsto number of police arrests, recidivism, and violent offending while controlling for current age. The best fitting latent class model was a five-class solution: ‘High criminal social identity’ (17%, ‘High Centrality, Moderate Affect, Low Ties’ (21.7%, ‘Low Centrality, Moderate Affect, High Ties’ (13.3%,‘Low Cognitive, High Affect, Low Ties’ (24.6%, and ‘Low criminal social identity’ (23.4%. Each of the latent classes was predicted by differing external variables. Criminal social identity is best explained by five homogenous classes that display qualitative and quantitative differences.

  19. Environmental Forcing of Supertyphoon Paka's (1997) Latent Heat Structure.

    Science.gov (United States)

    Rodgers, Edward; Olson, William; Halverson, Jeff; Simpson, Joanne; Pierce, Harold

    2000-12-01

    The distribution and intensity of total (i.e., combined stratified and convective processes) rain rate/latent heat release (LHR) were derived for Tropical Cyclone Paka during the period 9-21 December 1997 from the F-10, F-11, F-13, and F-14 Defense Meteorological Satellite Special Sensor Microwave Imager and the Tropical Rainfall Measuring Mission Microwave Imager observations. These observations were frequent enough to capture three episodes of inner-core convective bursts and a convective rainband cycle that preceded periods of rapid intensification. During these periods of convective bursts, satellite sensors revealed that the rain rates/LHR 1) increased within the inner-core region, 2) were mainly convectively generated (nearly a 65% contribution), 3) propagated inward, 4) extended upward within the mid- and upper troposphere, and 5) became electrically charged. These factors may have increased the areal mean ascending motion in the mid- and upper-troposphere eyewall region, creating greater cyclonic angular momentum, and, thereby, warming the center and intensifying the system.Radiosonde measurements from Kwajalein Atoll and Guam, sea surface temperature observations, and the European Centre for Medium-Range Forecasts analyses were used to examine the necessary and sufficient conditions for initiating and maintaining these inner-core convective bursts. For example, the necessary conditions such as the atmospheric thermodynamics [i.e., cold tropopause temperatures, moist troposphere, and warm SSTs (>26°C)] fulfill the necessary conditions and suggested that the atmosphere was ideally suited for Paka's maximum potential intensity to approach supertyphoon strength. Further, Paka encountered moderate vertical wind shear (<15 m s1) before interacting with the westerlies on 21 December. The sufficient conditions that include horizontal moisture and the upper-tropospheric eddy relative angular momentum fluxes, on the other hand, appeared to have some influence on

  20. The latent structure of attention deficit/hyperactivity disorder in an adult sample.

    Science.gov (United States)

    Marcus, David K; Norris, Alyssa L; Coccaro, Emil F

    2012-06-01

    The vast majority of studies that have examined the latent structure of attention deficit/hyperactivity disorder (ADHD) in children and adolescents have concluded that ADHD has a dimensional latent structure. In other words, ADHD symptomatology exists along a continuum and there is no natural boundary or qualitative distinction (i.e., taxon) separating youth with ADHD from those with subclinical inattention or hyperactivity/impulsivity problems. Although adult ADHD appears to be less prevalent than ADHD in youth (which could suggest a more severe adult ADHD taxon), researchers have yet to examine the latent structure of ADHD in adults. The present study used a sample (N = 600) of adults who completed a self-report measure of ADHD symptoms. The taxometric analyses revealed a dimensional latent structure for inattention, hyperactivity/impulsivity, and ADHD. These findings are consistent with previous taxometric studies that examined ADHD in children and adolescents, and with contemporary polygenic and multifactorial models of ADHD. Copyright © 2012 Elsevier Ltd. All rights reserved.

  1. The Latent Factor Structure of Acute Stress Disorder following Bank Robbery

    DEFF Research Database (Denmark)

    Hansen, M.; Lasgaard, M.; Elklit, A.

    2013-01-01

    of the latent structure of ASD were specified and estimated. METHOD: The analyses were based on a national study of bank robbery victims (N = 450) using the acute stress disorder scale. RESULTS: The results of the confirmatory factor analyses showed that the DSM-IV model provided the best fit to the data. Thus...

  2. Automated Communications Analysis System using Latent Semantic Analysis

    National Research Council Canada - National Science Library

    Foltz, Peter W

    2006-01-01

    ... and during the debriefing process to assess knowledge proficiency. In this report, the contractor describes prior research on communication analysis and how it can inform assessment of individual and team cognitive processing...

  3. Comorbidity profiles of psoriasis in Taiwan: A latent class analysis.

    Science.gov (United States)

    Wu, Chen-Yi; Hu, Hsiao-Yun; Li, Chung-Pin; Chou, Yiing-Jeng; Chang, Yun-Ting

    2018-01-01

    Psoriasis is associated with many comorbidities. An understanding of these comorbidity patterns can help foster better care of patients with psoriasis. To identify the heterogeneity of psoriasis comorbidities using latent class analysis (LCA). LCA was used to empirically identify psoriasis comorbidity patterns in a nationwide sample of 110,729 incident cases of psoriasis (2002-2012) from the National Health Insurance database in Taiwan. The mean age of incident psoriasis was 46.1 years. Hypertension (28.8%), dyslipidemia (18.9%), and chronic liver disease/cirrhosis/hepatitis (18.1%) were the top three comorbidities in patients with psoriasis. LCA identified four distinct comorbidity classes among these patients, including 9.9% of patients in the "multi-comorbidity" class, 17.9% in the "metabolic syndrome" class, 11.3% in the "hypertension and chronic obstructive pulmonary disease (COPD)" class, and 60.9% in the "relatively healthy" class. Psoriatic arthritis was evenly distributed among each class. Relative to membership in the "relative healthy" class, an increase of one year of age had a higher probability of membership in the "multi-comorbidity" (odds ratio [OR], 1.25), "metabolic syndrome" (OR, 1.11), or "hypertension and COPD" (OR, 1.34) classes. Relative to membership in the "relative healthy" class, compared to women, men had a higher probability of membership in the "multi-comorbidity" (OR, 1.39), "metabolic syndrome" (OR, 1.77), or "hypertension and COPD" (OR, 1.22) classes. We observed four distinct classes of psoriasis comorbidities, including the "multi-comorbidity", "metabolic syndrome", "hypertension and COPD", and "relatively healthy" classes, as well as the clustering of liver diseases with metabolic syndrome and clustering of COPD with hypertension.

  4. Computerized summary scoring: crowdsourcing-based latent semantic analysis.

    Science.gov (United States)

    Li, Haiying; Cai, Zhiqiang; Graesser, Arthur C

    2017-11-03

    In this study we developed and evaluated a crowdsourcing-based latent semantic analysis (LSA) approach to computerized summary scoring (CSS). LSA is a frequently used mathematical component in CSS, where LSA similarity represents the extent to which the to-be-graded target summary is similar to a model summary or a set of exemplar summaries. Researchers have proposed different formulations of the model summary in previous studies, such as pregraded summaries, expert-generated summaries, or source texts. The former two methods, however, require substantial human time, effort, and costs in order to either grade or generate summaries. Using source texts does not require human effort, but it also does not predict human summary scores well. With human summary scores as the gold standard, in this study we evaluated the crowdsourcing LSA method by comparing it with seven other LSA methods that used sets of summaries from different sources (either experts or crowdsourced) of differing quality, along with source texts. Results showed that crowdsourcing LSA predicted human summary scores as well as expert-good and crowdsourcing-good summaries, and better than the other methods. A series of analyses with different numbers of crowdsourcing summaries demonstrated that the number (from 10 to 100) did not significantly affect performance. These findings imply that crowdsourcing LSA is a promising approach to CSS, because it saves human effort in generating the model summary while still yielding comparable performance. This approach to small-scale CSS provides a practical solution for instructors in courses, and also advances research on automated assessments in which student responses are expected to semantically converge on subject matter content.

  5. Malingering as a Categorical or Dimensional Construct: The Latent Structure of Feigned Psychopathology as Measured by the SIRS and MMPI-2

    Science.gov (United States)

    Walters, Glenn D.; Rogers, Richard; Berry, David T. R.; Miller, Holly A.; Duncan, Scott A.; McCusker, Paul J.; Payne, Joshua W.; Granacher, Robert P., Jr.

    2008-01-01

    The 6 nonoverlapping primary scales of the Structured Interview of Reported Symptoms (SIRS) were subjected to taxometric analysis in a group of 1,211 criminal and civil examinees in order to investigate the latent structure of feigned psychopathology. Both taxometric procedures used in this study, mean above minus below a cut (MAMBAC) and maximum…

  6. Mediation Analysis in a Latent Growth Curve Modeling Framework

    Science.gov (United States)

    von Soest, Tilmann; Hagtvet, Knut A.

    2011-01-01

    This article presents several longitudinal mediation models in the framework of latent growth curve modeling and provides a detailed account of how such models can be constructed. Logical and statistical challenges that might arise when such analyses are conducted are also discussed. Specifically, we discuss how the initial status (intercept) and…

  7. Temporal analysis of text data using latent variable models

    DEFF Research Database (Denmark)

    Mølgaard, Lasse Lohilahti; Larsen, Jan; Goutte, Cyril

    2009-01-01

    Detecting and tracking of temporal data is an important task in multiple applications. In this paper we study temporal text mining methods for Music Information Retrieval. We compare two ways of detecting the temporal latent semantics of a corpus extracted from Wikipedia, using a stepwise...

  8. Bifactor latent structure of attention-deficit/hyperactivity disorder (ADHD)/oppositional defiant disorder (ODD) symptoms and first-order latent structure of sluggish cognitive tempo symptoms.

    Science.gov (United States)

    Lee, SoYean; Burns, G Leonard; Beauchaine, Theodore P; Becker, Stephen P

    2016-08-01

    The objective was to determine if the latent structure of attention-deficit/hyperactivity disorder (ADHD) and oppositional defiant disorder (ODD) symptoms is best explained by a general disruptive behavior factor along with specific inattention (IN), hyperactivity/impulsivity (HI), and ODD factors (a bifactor model) whereas the latent structure of sluggish cognitive tempo (SCT) symptoms is best explained by a first-order factor independent of the bifactor model of ADHD/ODD. Parents' (n = 703) and teachers' (n = 366) ratings of SCT, ADHD-IN, ADHD-HI, and ODD symptoms on the Child and Adolescent Disruptive Behavior Inventory (CADBI) in a community sample of children (ages 5-13; 55% girls) were used to evaluate 4 models of symptom organization. Results indicated that a bifactor model of ADHD/ODD symptoms, in conjunction with a separate first-order SCT factor, was the best model for both parent and teacher ratings. The first-order SCT factor showed discriminant validity with the general disruptive behavior and specific IN factors in the bifactor model. In addition, higher scores on the SCT factor predicted greater academic and social impairment, even after controlling for the general disruptive behavior and 3 specific factors. Consistent with predictions from the trait-impulsivity etiological model of externalizing liability, a single, general disruptive behavior factor accounted for nearly all common variance in ADHD/ODD symptoms, whereas SCT symptoms represented a factor different from the general disruptive behavior and specific IN factor. These results provide additional support for distinguishing between SCT and ADHD-IN. The study also demonstrates how etiological models can be used to predict specific latent structures of symptom organization. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  9. Uncovering a latent multinomial: Analysis of mark-recapture data with misidentification

    Science.gov (United States)

    Link, W.A.; Yoshizaki, J.; Bailey, L.L.; Pollock, K.H.

    2010-01-01

    Natural tags based on DNA fingerprints or natural features of animals are now becoming very widely used in wildlife population biology. However, classic capture-recapture models do not allow for misidentification of animals which is a potentially very serious problem with natural tags. Statistical analysis of misidentification processes is extremely difficult using traditional likelihood methods but is easily handled using Bayesian methods. We present a general framework for Bayesian analysis of categorical data arising from a latent multinomial distribution. Although our work is motivated by a specific model for misidentification in closed population capture-recapture analyses, with crucial assumptions which may not always be appropriate, the methods we develop extend naturally to a variety of other models with similar structure. Suppose that observed frequencies f are a known linear transformation f = A???x of a latent multinomial variable x with cell probability vector ?? = ??(??). Given that full conditional distributions [?? | x] can be sampled, implementation of Gibbs sampling requires only that we can sample from the full conditional distribution [x | f, ??], which is made possible by knowledge of the null space of A???. We illustrate the approach using two data sets with individual misidentification, one simulated, the other summarizing recapture data for salamanders based on natural marks. ?? 2009, The International Biometric Society.

  10. Interferon-gamma release assay for the diagnosis of latent tuberculosis infection: A latent-class analysis.

    Directory of Open Access Journals (Sweden)

    Tan N Doan

    Full Text Available Accurate diagnosis and subsequent treatment of latent tuberculosis infection (LTBI is essential for TB elimination. However, the absence of a gold standard test for diagnosing LTBI makes assessment of the true prevalence of LTBI and the accuracy of diagnostic tests challenging. Bayesian latent class models can be used to make inferences about disease prevalence and the sensitivity and specificity of diagnostic tests using data on the concordance between tests. We performed the largest meta-analysis to date aiming to evaluate the performance of tuberculin skin test (TST and interferon-gamma release assays (IGRAs for LTBI diagnosis in various patient populations using Bayesian latent class modelling.Systematic search of PubMeb, Embase and African Index Medicus was conducted without date and language restrictions on September 11, 2017 to identify studies that compared the performance of TST and IGRAs for LTBI diagnosis. Two IGRA methods were considered: QuantiFERON-TB Gold In Tube (QFT-GIT and T-SPOT.TB. Studies were included if they reported 2x2 agreement data between TST and QFT-GIT or T-SPOT.TB. A Bayesian latent class model was developed to estimate the sensitivity and specificity of TST and IGRAs in various populations, including immune-competent adults, immune-compromised adults and children. A TST cut-off value of 10 mm was used for immune-competent subjects and 5 mm for immune-compromised individuals.A total of 157 studies were included in the analysis. In immune-competent adults, the sensitivity of TST and QFT-GIT were estimated to be 84% (95% credible interval [CrI] 82-85% and 52% (50-53%, respectively. The specificity of QFT-GIT was 97% (96-97% in non-BCG-vaccinated and 93% (92-94% in BCG-vaccinated immune-competent adults. The estimated figures for TST were 100% (99-100% and 79% (76-82%, respectively. T-SPOT.TB has comparable specificity (97% for both tests and better sensitivity (68% versus 52% than QFT-GIT in immune-competent adults

  11. Alexithymia and psychosocial problems among Italian preadolescents. A latent class analysis approach.

    Science.gov (United States)

    Mannarini, Stefania; Balottin, Laura; Toldo, Irene; Gatta, Michela

    2016-10-01

    The study, conducted on Italian preadolscents aged 11 to 13 belonging to the general population, aims to investigate the relationship between the emotional functioning, namely, alexithymia, and the risk of developing behavioral and emotional problems measured using the Strength and Difficulty Questionnaire. The latent class analysis approach allowed to identify two latent variables, accounting for the internalizing (emotional symptoms and difficulties in emotional awareness) and for the externalizing problems (conduct problems and hyperactivity, problematic relationships with peers, poor prosocial behaviors and externally oriented thinking). The two latent variables featured two latent classes: the difficulty in dealing with problems and the strength to face problems that was representative of most of the healthy participants with specific gender differences. Along with the analysis of psychopathological behaviors, the study of resilience and strengths can prove to be a key step in order to develop valuable preventive approaches to tackle psychiatric disorders. © 2016 Scandinavian Psychological Associations and John Wiley & Sons Ltd.

  12. An Evaluation of the Texas Functional Living Scale's Latent Structure and Subscales.

    Science.gov (United States)

    González, David Andrés; Soble, Jason R; Marceaux, Janice C; McCoy, Karin J M

    2017-02-01

    Performance-based functional assessment is a critical component of neuropsychological practice. The Texas Functional Living Scale (TFLS) has promise given its brevity, nationally representative norms, and co-norming with Wechsler scales. However, its subscale structure has not been evaluated. The purpose of this study was to evaluate the TFLS in a mixed clinical sample (n = 197). Reliability and convergent and discriminant validity coefficients were calculated with neurocognitive testing and collateral reports and factor analysis was performed. The Money and Calculation subscale had the best psychometric properties of the subscales. The evidence did not support solitary interpretation of the Time subscale. A three-factor latent structure emerged representing memory and semantic retrieval, performance and visual scanning, and financial calculation. This study added psychometric support for interpretation of the TFLS total score and some of its subscales. Study limitations included sample characteristics (e.g., gender ratio) and low power for collateral report analyses. Published by Oxford University Press 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.

  13. Visualization of pairwise and multilocus linkage disequilibrium structure using latent forests.

    Directory of Open Access Journals (Sweden)

    Raphaël Mourad

    Full Text Available Linkage disequilibrium study represents a major issue in statistical genetics as it plays a fundamental role in gene mapping and helps us to learn more about human history. The linkage disequilibrium complex structure makes its exploratory data analysis essential yet challenging. Visualization methods, such as the triangular heat map implemented in Haploview, provide simple and useful tools to help understand complex genetic patterns, but remain insufficient to fully describe them. Probabilistic graphical models have been widely recognized as a powerful formalism allowing a concise and accurate modeling of dependences between variables. In this paper, we propose a method for short-range, long-range and chromosome-wide linkage disequilibrium visualization using forests of hierarchical latent class models. Thanks to its hierarchical nature, our method is shown to provide a compact view of both pairwise and multilocus linkage disequilibrium spatial structures for the geneticist. Besides, a multilocus linkage disequilibrium measure has been designed to evaluate linkage disequilibrium in hierarchy clusters. To learn the proposed model, a new scalable algorithm is presented. It constrains the dependence scope, relying on physical positions, and is able to deal with more than one hundred thousand single nucleotide polymorphisms. The proposed algorithm is fast and does not require phase genotypic data.

  14. Incorporating Measurement Non-Equivalence in a Cross-Study Latent Growth Curve Analysis.

    Science.gov (United States)

    Flora, David B; Curran, Patrick J; Hussong, Andrea M; Edwards, Michael C

    2008-10-01

    A large literature emphasizes the importance of testing for measurement equivalence in scales that may be used as observed variables in structural equation modeling applications. When the same construct is measured across more than one developmental period, as in a longitudinal study, it can be especially critical to establish measurement equivalence, or invariance, across the developmental periods. Similarly, when data from more than one study are combined into a single analysis, it is again important to assess measurement equivalence across the data sources. Yet, how to incorporate non-equivalence when it is discovered is not well described for applied researchers. Here, we present an item response theory approach that can be used to create scale scores from measures while explicitly accounting for non-equivalence. We demonstrate these methods in the context of a latent curve analysis in which data from two separate studies are combined to create a single longitudinal model spanning several developmental periods.

  15. Prevalence Estimation and Validation of New Instruments in Psychiatric Research: An Application of Latent Class Analysis and Sensitivity Analysis

    Science.gov (United States)

    Pence, Brian Wells; Miller, William C.; Gaynes, Bradley N.

    2009-01-01

    Prevalence and validation studies rely on imperfect reference standard (RS) diagnostic instruments that can bias prevalence and test characteristic estimates. The authors illustrate 2 methods to account for RS misclassification. Latent class analysis (LCA) combines information from multiple imperfect measures of an unmeasurable latent condition to…

  16. Paranoid Personality Has a Dimensional Latent Structure: Taxometric Analyses of Community and Clinical Samples

    OpenAIRE

    Edens, John F.; Marcus, David K.; Morey, Leslie C.

    2009-01-01

    Although paranoid personality is one of the most commonly diagnosed personality disorders and is associated with numerous negative life consequences, relatively little is known about the structural properties of this condition. This study examines whether paranoid personality traits represent a latent dimension or a discrete class (i.e., taxon). In study 1, we conducted taxometric analyses of paranoid personality disorder criteria in a sample of 731 patients participating in the Collaborative...

  17. The Latent Class Structure of Chinese Patients with Eating Disorders in Shanghai

    OpenAIRE

    ,; ,; ,; ,; ,; ,; ,; ,; ,; ,

    2017-01-01

    Background Eating disorder is culture related, and the clinical symptoms are different between eastern and western patients. So the validity of feeding and eating disorders in the upcoming ICD-11 guide for Chinese patients is unclear. Aims To explore the latent class structure of Chinese patients with eating disorder and the cross-cultural validity of the eating disorder section of the new ICD-11 guide in China. Methods A total of 379 patients with eating disorders at Shanghai Mental Health C...

  18. Understanding comorbidity among internalizing problems: Integrating latent structural models of psychopathology and risk mechanisms

    Science.gov (United States)

    Hankin, Benjamin L.; Snyder, Hannah R.; Gulley, Lauren D.; Schweizer, Tina H.; Bijttebier, Patricia; Nelis, Sabine; Toh, Gim; Vasey, Michael W.

    2016-01-01

    It is well known that comorbidity is the rule, not the exception, for categorically defined psychiatric disorders, and this is also the case for internalizing disorders of depression and anxiety. This theoretical review paper addresses the ubiquity of comorbidity among internalizing disorders. Our central thesis is that progress in understanding this co-occurrence can be made by employing latent dimensional structural models that organize both psychopathology as well as vulnerabilities and risk mechanisms and by connecting the multiple levels of risk and psychopathology outcomes together. Different vulnerabilities and risk mechanisms are hypothesized to predict different levels of the structural model of psychopathology. We review the present state of knowledge based on concurrent and developmental sequential comorbidity patterns among common discrete psychiatric disorders in youth, and then we advocate for the use of more recent bifactor dimensional models of psychopathology (e.g., p factor, Caspi et al., 2014) that can help to explain the co-occurrence among internalizing symptoms. In support of this relatively novel conceptual perspective, we review six exemplar vulnerabilities and risk mechanisms, including executive function, information processing biases, cognitive vulnerabilities, positive and negative affectivity aspects of temperament, and autonomic dysregulation, along with the developmental occurrence of stressors in different domains, to show how these vulnerabilities can predict the general latent psychopathology factor, a unique latent internalizing dimension, as well as specific symptom syndrome manifestations. PMID:27739389

  19. The Depression Anxiety Stress Scales (DASS): normative data and latent structure in a large non-clinical sample.

    Science.gov (United States)

    Crawford, John R; Henry, Julie D

    2003-06-01

    To provide UK normative data for the Depression Anxiety and Stress Scale (DASS) and test its convergent, discriminant and construct validity. Cross-sectional, correlational and confirmatory factor analysis (CFA). The DASS was administered to a non-clinical sample, broadly representative of the general adult UK population (N = 1,771) in terms of demographic variables. Competing models of the latent structure of the DASS were derived from theoretical and empirical sources and evaluated using confirmatory factor analysis. Correlational analysis was used to determine the influence of demographic variables on DASS scores. The convergent and discriminant validity of the measure was examined through correlating the measure with two other measures of depression and anxiety (the HADS and the sAD), and a measure of positive and negative affectivity (the PANAS). The best fitting model (CFI =.93) of the latent structure of the DASS consisted of three correlated factors corresponding to the depression, anxiety and stress scales with correlated error permitted between items comprising the DASS subscales. Demographic variables had only very modest influences on DASS scores. The reliability of the DASS was excellent, and the measure possessed adequate convergent and discriminant validity Conclusions: The DASS is a reliable and valid measure of the constructs it was intended to assess. The utility of this measure for UK clinicians is enhanced by the provision of large sample normative data.

  20. Heterogeneity of postpartum depression: a latent class analysis

    Science.gov (United States)

    2016-01-01

    Summary Background Maternal depression in the postpartum period confers substantial morbidity and mortality, but the definition of postpartum depression remains controversial. We investigated the heterogeneity of symptoms with the aim of identifying clinical subtypes of postpartum depression. Methods Data were aggregated from the international perinatal psychiatry consortium Postpartum Depression: Action Towards Causes and Treatment, which represents 19 institutions in seven countries. 17 912 unique subject records with phenotypic data were submitted. We applied latent class analyses in a two-tiered approach to assess the validity of empirically defined subtypes of postpartum depression. Tier one assessed heterogeneity in women with complete data on the Edinburgh postnatal depression scale (EPDS) and tier two in those with postpartum depression case status. Findings 6556 individuals were assessed in tier one and 4245 in tier two. A final model with three latent classes was optimum for both tiers. The most striking characteristics associated with postpartum depression were severity, timing of onset, comorbid anxiety, and suicidal ideation. Women in class 1 had the least severe symptoms (mean EPDS score 10·5), followed by those in class 2 (mean EPDS score 14·8) and those in class 3 (mean EPDS score 20·1). The most severe symptoms of postpartum depression were significantly associated with poor mood (mean EPDS score 20·1), increased anxiety, onset of symptoms during pregnancy, obstetric complications, and suicidal ideation. In class 2, most women (62%) reported symptom onset within 4 weeks postpartum and had more pregnancy complications than in other two classes (69% vs 67% in class 1 and 29% in class 3). Interpretation PPD seems to have several distinct phenotypes. Further assessment of PPD heterogeneity to identify more precise phenotypes will be important for future biological and genetic investigations. Funding Sources of funding are listed at the end of the

  1. Latent human error analysis and efficient improvement strategies by fuzzy TOPSIS in aviation maintenance tasks.

    Science.gov (United States)

    Chiu, Ming-Chuan; Hsieh, Min-Chih

    2016-05-01

    The purposes of this study were to develop a latent human error analysis process, to explore the factors of latent human error in aviation maintenance tasks, and to provide an efficient improvement strategy for addressing those errors. First, we used HFACS and RCA to define the error factors related to aviation maintenance tasks. Fuzzy TOPSIS with four criteria was applied to evaluate the error factors. Results show that 1) adverse physiological states, 2) physical/mental limitations, and 3) coordination, communication, and planning are the factors related to airline maintenance tasks that could be addressed easily and efficiently. This research establishes a new analytic process for investigating latent human error and provides a strategy for analyzing human error using fuzzy TOPSIS. Our analysis process complements shortages in existing methodologies by incorporating improvement efficiency, and it enhances the depth and broadness of human error analysis methodology. Copyright © 2015 Elsevier Ltd and The Ergonomics Society. All rights reserved.

  2. Retrieving latent heating vertical structure from cloud and precipitation Profiles—Part I: Warm rain processes

    International Nuclear Information System (INIS)

    Min, Qilong; Li, Rui; Wu, Xiaoqing; Fu, Yunfei

    2013-01-01

    An exploratory study on physical based latent heat (LH) retrieval algorithm is conducted by parameterizing the physical linkages of hydrometeor profiles of cloud and precipitation to the major processes related to the phase change of atmospheric water. Specifically, rain events are segregated into three rain types: warm, convective, and stratiform, based on their dynamical and thermodynamical characteristics. As the first of the series, only the warm rain LH algorithm is presented and evaluated here. The major microphysical processes of condensation and evaporation for warm rain are parameterized through traditional rain growth theory, with the aid of Cloud Resolving Model (CRM) simulations. The evaluation or the self-consistency tests indicate that the physical based retrievals capture the fundamental LH processes associated with the warm rain life cycle. There is no significant systematic bias in terms of convection strength, illustrated by the month-long CRM simulation as the mesoscale convective systems (MCSs) experience from initial, mature, to decay stages. The overall monthly-mean LH comparison showed that the total LH, as well as condensation heating and evaporation cooling components, agree with the CRM simulation. -- Highlights: ► An exploratory study on physics-based warm rain latent heat retrieval algorithm. ► Utilize the full information of the vertical structures of cloud and rainfall. ► Directly link water mass measurements to latent heat at instantaneous pixel level. ► Applicable at various stages of cloud system life cycle

  3. Examining Combinations of Social Physique Anxiety and Motivation Regulations Using Latent Profile Analysis

    Science.gov (United States)

    Ullrich-French, Sarah; Cox, Anne E.; Cooper, Brittany Rhoades

    2016-01-01

    Previous research has used cluster analysis to examine how social physique anxiety (SPA) combines with motivation in physical education. This study utilized a more advanced analytic approach, latent profile analysis (LPA), to identify profiles of SPA and motivation regulations. Students in grades 9-12 (N = 298) completed questionnaires at two time…

  4. Latent class analysis derived subgroups of low back pain patients - do they have prognostic capacity?

    DEFF Research Database (Denmark)

    Mølgaard Nielsen, Anne; Hestbaek, Lise; Vach, Werner

    2017-01-01

    . Previously, we developed two novel suggestions for subgrouping patients with low back pain based on Latent Class Analysis of patient baseline characteristics (patient history and physical examination), which resulted in 7 subgroups when using a single-stage analysis, and 9 subgroups when using a two...

  5. Latent structure of the social anxiety scale and relations between social anxiety and irrational beliefs

    Directory of Open Access Journals (Sweden)

    Tovilović Snežana

    2004-01-01

    Full Text Available The research which was realized belongs to one of three research fields within framework of rational-emotional-behavioral therapy (REBT - to the theory of emotional disorders. It was undertaken with the aim to establish presence and nature of relations between social anxiety, treated as dimension and the construct of irrational beliefs from REBT theory. The research was carried out on the sample of 261 students of Novi Sad University, both genders, age 18 to 26. First of all, the latent structure of newly constructed Scale of Social Anxiety (SA of the author Tovilović S. was tested. SA scale was proved to be of satisfying reliability (α =0.92. Principal-component factor analysis was conducted under gathered data. Four factors of social anxiety, which explain 44,09% of total variance of the items of SA scale, were named: social-evaluation anxiety, inhibition in social-uncertain situations, low self-respect and hypersensitivity on rejection. The other test that was used is Scale of General Attitudes and Beliefs of the author Marić Z. Reliability of the sub-scale of irrational beliefs that was got on our sample is α =0.91 yet the subscale of rational beliefs is α =0.70. Canonical correlational analysis was conducted under manifest variables of both scales. Three pairs of statistically significant canonical factors were got, with correlations within the span between Rc=0.78 and Rc=0.64. We discussed nature of correlation between social anxiety and irrational beliefs in the light of REBT model of social phobia, REBT theory of emotional disorder, researches and model of social anxiety in wider, cognitive-behavioral framework.

  6. Latent vs. Observed Variables : Analysis of Irrigation Water Efficiency Using SEM and SUR

    NARCIS (Netherlands)

    Tang, Jianjun; Folmer, Henk

    In this paper we compare conceptualising single factor technical and allocative efficiency as indicators of a single latent variable, or as separate observed variables. In the former case, the impacts on both efficiency types are analysed by means of structural equationmodeling (SEM), in the latter

  7. The Stability of Social Desirability: A Latent Change Analysis.

    Science.gov (United States)

    Haberecht, Katja; Schnuerer, Inga; Gaertner, Beate; John, Ulrich; Freyer-Adam, Jennis

    2015-08-01

    Social desirability has been shown to be stable in samples with higher school education. However, little is known about the stability of social desirability in more heterogeneous samples differing in school education. This study aimed to investigate the stability of social desirability and which factors predict interindividual differences in intraindividual change. As part of a randomized controlled trial, 1,243 job seekers with unhealthy alcohol use were systematically recruited at three job agencies. A total of 1,094 individuals (87.8%) participated in at least one of two follow-ups (6 and 15 months after baseline) and constitute this study's sample. The Social Desirability Scale-17 was applied. Two latent change models were conducted: Model 1 tested for interindividual differences in intraindividual change of social desirability between both follow-ups; Model 2 included possible predictors (age, sex, education, current employment status) of interindividual differences in intraindividual change. Model 1 revealed a significant decrease of social desirability over time. Model 2 revealed school education to be the only significant predictor of change. These findings indicate that stability of social desirability may depend on school education. It may not be as stable in individuals with higher school education as in individuals with lower education. © 2014 Wiley Periodicals, Inc.

  8. Parent involvement and science achievement: A latent growth curve analysis

    Science.gov (United States)

    Johnson, Ursula Yvette

    This study examined science achievement growth across elementary and middle school and parent school involvement using the Early Childhood Longitudinal Study - Kindergarten Class of 1998--1999 (ECLS-K). The ECLS-K is a nationally representative kindergarten cohort of students from public and private schools who attended full-day or half-day kindergarten class in 1998--1999. The present study's sample (N = 8,070) was based on students that had a sampling weight available from the public-use data file. Students were assessed in science achievement at third, fifth, and eighth grades and parents of the students were surveyed at the same time points. Analyses using latent growth curve modeling with time invariant and varying covariates in an SEM framework revealed a positive relationship between science achievement and parent involvement at eighth grade. Furthermore, there were gender and racial/ethnic differences in parents' school involvement as a predictor of science achievement. Findings indicated that students with lower initial science achievement scores had a faster rate of growth across time. The achievement gap between low and high achievers in earth, space and life sciences lessened from elementary to middle school. Parents' involvement with school usually tapers off after elementary school, but due to parent school involvement being a significant predictor of eighth grade science achievement, later school involvement may need to be supported and better implemented in secondary schooling.

  9. Longitudinal Physical Activity Patterns Among Older Adults: A Latent Transition Analysis.

    Science.gov (United States)

    Mooney, Stephen J; Joshi, Spruha; Cerdá, Magdalena; Kennedy, Gary J; Beard, John R; Rundle, Andrew G

    2018-05-14

    Most epidemiologic studies of physical activity measure either total energy expenditure or engagement in a single activity type, such as walking. These approaches may gloss over important nuances in activity patterns. We performed a latent transition analysis to identify patterns of activity types as well as neighborhood and individual determinants of changes in those activity patterns over two years in a cohort of 2,023 older adult residents of New York City, NY, surveyed between 2011 and 2013. We identified seven latent classes: 1) Mostly Inactive, 2) Walking, 3) Exercise, 4) Household Activities and Walking, 5) Household Activities and Exercise, 6) Gardening and Household Activities, and 7) Gardening, Household Activities, and Exercise. The majority of subjects retained the same activity patterns between waves (54% unchanged between waves 1 and 2, 66% unchanged between waves 2 and 3).Most latent class transitions were between classes distinguished only by one form of activity, and only neighborhood unemployment was consistently associated with changing between activity latent classes. Future latent transition analyses of physical activity would benefit from larger cohorts and longer follow-up periods to assess predictors of and long-term impacts of changes in activity patterns.

  10. Preparation of fluoropolymer-based ion-track membranes. Structure of latent tracks and pretreatment effect

    International Nuclear Information System (INIS)

    Yamaki, Tetsuya; Nuryanthi, Nuryanthi; Koshikawa, Hiroshi; Sawada, Shinichi; Hakoda, Teruyuki; Hasegawa, Shin; Asano, Masaharu; Maekawa, Yasunari

    2012-01-01

    High-energy heavy-ion induced damage, called latent tracks m organic polymers can sometimes be etched out chemically to give submicro- and nano-sized pores. Our focus is placed on ion-track membranes of poly(vinylidene fluoride) (PVDF), a type of fluoropolymer, which were previously considered as a matrix of polymer electrolyte fuel-cell membranes. There have been no optimized methods of preparing the PVDF-based ion-track membranes. We thus examined chemical structures of the defects created in the track, and accordingly, presented a pretreatment technique for achieving more efficient track etching. A 25 μm-thick PVDF film was bombarded with 1.1 GeV 238 U or 450 MeV 129 Xe ions. In the multi-purpose chamber, degradation processes were monitored in-situ by FT-IR spectroscopy and residual gas analysis as a function of the fluence up to 6.0 x 10 11 ions/cm 2 . The films irradiated at 8 ions/cm 2 were etched in a 9 M KOH aqueous solution at 80degC. We also performed the conductometric etching, which allows monitoring of pore evolution versus etching time by recording the electrical conductance through the membrane. At fluences above 1 x 10 10 ions/cm 2 , the film showed two new absorption bands identified as double-bond stretching vibrations of in-chain unsaturations -CH=CF- and fluorinated vinyl groups -CF 2 CH=CF 2 . These defects would result from the evolution of HF. The knowledge of the solubility in a permanganate alkaline solution and our preliminary experiment suggested the importance of oxidized tracks for the easy introduction of the etching agent. We finally found that the pretreatment with ozone could oxidize the double bonds in the tracks, thereby vigorously promoting track etching before breakthrough. (author)

  11. Internet Gamblers Differ on Social Variables: A Latent Class Analysis.

    Science.gov (United States)

    Khazaal, Yasser; Chatton, Anne; Achab, Sophia; Monney, Gregoire; Thorens, Gabriel; Dufour, Magali; Zullino, Daniele; Rothen, Stephane

    2017-09-01

    Online gambling has gained popularity in the last decade, leading to an important shift in how consumers engage in gambling and in the factors related to problem gambling and prevention. Indebtedness and loneliness have previously been associated with problem gambling. The current study aimed to characterize online gamblers in relation to indebtedness, loneliness, and several in-game social behaviors. The data set was obtained from 584 Internet gamblers recruited online through gambling websites and forums. Of these gamblers, 372 participants completed all study assessments and were included in the analyses. Questionnaires included those on sociodemographics and social variables (indebtedness, loneliness, in-game social behaviors), as well as the Gambling Motives Questionnaire, Gambling Related Cognitions Scale, Internet Addiction Test, Problem Gambling Severity Index, Short Depression-Happiness Scale, and UPPS-P Impulsive Behavior Scale. Social variables were explored with a latent class model. The clusters obtained were compared for psychological measures and three clusters were found: lonely indebted gamblers (cluster 1: 6.5%), not lonely not indebted gamblers (cluster 2: 75.4%), and not lonely indebted gamblers (cluster 3: 18%). Participants in clusters 1 and 3 (particularly in cluster 1) were at higher risk of problem gambling than were those in cluster 2. The three groups differed on most assessed variables, including the Problem Gambling Severity Index, the Short Depression-Happiness Scale, and the UPPS-P subscales (except the sensation seeking subscore). Results highlight significant between-group differences, suggesting that Internet gamblers are not a homogeneous group. Specific intervention strategies could be implemented for groups at risk.

  12. Remote sensing image segmentation using local sparse structure constrained latent low rank representation

    Science.gov (United States)

    Tian, Shu; Zhang, Ye; Yan, Yimin; Su, Nan; Zhang, Junping

    2016-09-01

    Latent low-rank representation (LatLRR) has been attached considerable attention in the field of remote sensing image segmentation, due to its effectiveness in exploring the multiple subspace structures of data. However, the increasingly heterogeneous texture information in the high spatial resolution remote sensing images, leads to more severe interference of pixels in local neighborhood, and the LatLRR fails to capture the local complex structure information. Therefore, we present a local sparse structure constrainted latent low-rank representation (LSSLatLRR) segmentation method, which explicitly imposes the local sparse structure constraint on LatLRR to capture the intrinsic local structure in manifold structure feature subspaces. The whole segmentation framework can be viewed as two stages in cascade. In the first stage, we use the local histogram transform to extract the texture local histogram features (LHOG) at each pixel, which can efficiently capture the complex and micro-texture pattern. In the second stage, a local sparse structure (LSS) formulation is established on LHOG, which aims to preserve the local intrinsic structure and enhance the relationship between pixels having similar local characteristics. Meanwhile, by integrating the LSS and the LatLRR, we can efficiently capture the local sparse and low-rank structure in the mixture of feature subspace, and we adopt the subspace segmentation method to improve the segmentation accuracy. Experimental results on the remote sensing images with different spatial resolution show that, compared with three state-of-the-art image segmentation methods, the proposed method achieves more accurate segmentation results.

  13. Further Examining Berry's Model: The Applicability of Latent Profile Analysis to Acculturation

    Science.gov (United States)

    Fox, Rina S.; Merz, Erin L.; Solórzano, Martha T.; Roesch, Scott C.

    2013-01-01

    This study used latent profile analysis (LPA) to identify acculturation profiles. A three-profile solution fit the data best, and comparisons on demographic and psychosocial outcomes as a function of profile yielded expected results. The findings support using LPA as a parsimonious way to model acculturation without anticipating profiles in…

  14. Occurence of internet addiction in a general population sample: A latent class analysis

    NARCIS (Netherlands)

    Rumpf, H.J.; Vermulst, A.A.; Bischof, A.; Kastirke, N.; Gürtler, D.; Bischof, G.; Meerkerk, G.J.; John, U.; Meyer, C.

    2014-01-01

    Background: Prevalence studies of Internet addiction in the general population are rare. In addition, a lack of approved criteria hampers estimation of its occurrence. Aims: This study conducted a latent class analysis (LCA) in a large general population sample to estimate prevalence. Methods: A

  15. Computational Tools for Probing Interactions in Multiple Linear Regression, Multilevel Modeling, and Latent Curve Analysis

    Science.gov (United States)

    Preacher, Kristopher J.; Curran, Patrick J.; Bauer, Daniel J.

    2006-01-01

    Simple slopes, regions of significance, and confidence bands are commonly used to evaluate interactions in multiple linear regression (MLR) models, and the use of these techniques has recently been extended to multilevel or hierarchical linear modeling (HLM) and latent curve analysis (LCA). However, conducting these tests and plotting the…

  16. A Latent Profile Analysis of Math Achievement, Numerosity, and Math Anxiety in Twins

    Science.gov (United States)

    Hart, Sara A.; Logan, Jessica A. R.; Thompson, Lee; Kovas, Yulia; McLoughlin, Gráinne; Petrill, Stephen A.

    2016-01-01

    Underperformance in math is a problem with increasing prevalence, complex etiology, and severe repercussions. This study examined the etiological heterogeneity of math performance in a sample of 264 pairs of 12-year-old twins assessed on measures of math achievement, numerosity, and math anxiety. Latent profile analysis indicated 5 groupings of…

  17. Refining the Classification of Children with Selective Mutism: A Latent Profile Analysis

    Science.gov (United States)

    Cohan, Sharon L.; Chavira, Denise A.; Shipon-Blum, Elisa; Hitchcock, Carla; Roesch, Scott C.; Stein, Murray B.

    2008-01-01

    The goal of this study was to develop an empirically derived classification system for selective mutism (SM) using parent-report measures of social anxiety, behavior problems, and communication delays. The sample consisted of parents of 130 children (ages 5-12) with SM. Results from latent profile analysis supported a 3-class solution made up of…

  18. Solidarity and conflict between adult children and parents: a latent class analysis

    NARCIS (Netherlands)

    van Gaalen, R.I.A.; Dykstra, P.A.

    2006-01-01

    Using multiple dimensions of solidarity and conflict in a latent class analysis, we develop a typology of adult child–parent relationships. The data (N= 4,990) are from the first wave of the Netherlands Kinship Panel Study. In descending order of relationship quality, the 5 types are harmonious

  19. Identifying Students at Risk: An Examination of Computer-Adaptive Measures and Latent Class Growth Analysis

    Science.gov (United States)

    Keller-Margulis, Milena; McQuillin, Samuel D.; Castañeda, Juan Javier; Ochs, Sarah; Jones, John H.

    2018-01-01

    Multitiered systems of support depend on screening technology to identify students at risk. The purpose of this study was to examine the use of a computer-adaptive test and latent class growth analysis (LCGA) to identify students at risk in reading with focus on the use of this methodology to characterize student performance in screening.…

  20. An examination of generalized anxiety disorder and dysthymic disorder by latent class analysis

    NARCIS (Netherlands)

    Rhebergen, D.; van der Steenstraten, I.M.; Sunderland, M.; de Graaf, R.; ten Have, M.; Lamers, F.; Penninx, B.W.J.H.; Andrews, G.

    2014-01-01

    Background The nosological status of generalized anxiety disorder (GAD) versus dysthymic disorder (DD) has been questioned. The aim of this study was to examine qualitative differences within (co-morbid) GAD and DD symptomatology. Method Latent class analysis was applied to anxious and depressive

  1. Assessing model fit in latent class analysis when asymptotics do not hold

    NARCIS (Netherlands)

    van Kollenburg, Geert H.; Mulder, Joris; Vermunt, Jeroen K.

    2015-01-01

    The application of latent class (LC) analysis involves evaluating the LC model using goodness-of-fit statistics. To assess the misfit of a specified model, say with the Pearson chi-squared statistic, a p-value can be obtained using an asymptotic reference distribution. However, asymptotic p-values

  2. Solidarity and Conflict Between Adult Childrenand Parents : A Latent Class Analysis

    NARCIS (Netherlands)

    Gaalen, Ruben I. van; Dykstra, Pearl A.

    2006-01-01

    Using multiple dimensions of solidarity and conflict in a latent class analysis, we develop a typology of adult child–parent relationships. The data (N ¼ 4,990) are from the first wave of the Netherlands Kinship Panel Study. In descending order of relationship quality, the 5 types are harmonious

  3. Prospective memory in healthy Chinese people: the latent structure of the Comprehensive Assessment of Prospective Memory Questionnaire.

    Science.gov (United States)

    Chan, Raymond C K; Qing, Yonghong; Wu, Qiuping; Shum, David

    2010-06-01

    This study aimed to examine the latent structure of the Chinese version of the Comprehensive Assessment of Prospective Memory (CAPM) using confirmatory factor analysis. A total of 264 healthy Chinese participants (118 men and 146 women) took part in the study and their ages ranged from 17 to 90 years. There was no gender effect upon the frequency of prospective memory (PM) forgetting but age and education were found to be correlated significantly with these frequencies in the current sample. Results of the study also showed that the model with the best fit had a tripartite structure which consisted of a general memory factor (with all items loading on it) plus a basic activities of daily living as well as an instrumental activities of daily living factor. Furthermore, this tripartite model was robust across subgroups with respect to gender, education, and age. These findings provide support for the construct validity of the original CAPM and demonstrate its utility in another culture.

  4. Stability of alcohol use and teen dating violence for female youth: A latent transition analysis.

    Science.gov (United States)

    Choi, Hye Jeong; Elmquist, JoAnna; Shorey, Ryan C; Rothman, Emily F; Stuart, Gregory L; Temple, Jeff R

    2017-01-01

    Alcohol use is one of the most widely accepted and studied risk factors for teen dating violence (TDV). Too little research has explored longitudinally if it is true that an adolescent's alcohol use and TDV involvement simultaneously occur. In the current study, we examined whether there were latent status based on past-year TDV and alcohol use and whether female adolescents changed their statuses of TDV and alcohol use over time. The sample consisted of 583 female youths in seven public high schools in Texas. Three waves of longitudinal data collected from 2011 to 2013 were utilised in this study. Participants completed self-report assessments of alcohol use (past-year alcohol use, number of drinks in the past month and episodic heavy drinking within the past month) and psychological and physical TDV victimisation and perpetration. Latent transition analysis was used to examine if the latent status based on TDV and alcohol use changed over time. Five separate latent statuses were identified: (i) no violence, no alcohol; (ii) alcohol; (iii) psychological violence, no alcohol; (iv) psychological violence, alcohol; and (v) physical and psychological violence, alcohol. Latent transition analysis indicated that adolescents generally remained in the same subgroup across time. This study provides evidence on the co-occurrence of alcohol use and teen dating violence, and whether teens' status based on dating violence and alcohol use are stable over time. Findings from the current study highlight the importance of targeting both TDV and substance use in intervention and prevention programs. [Choi HJ, Elmquist J, Shorey RC, Rothman EF, Stuart GL,Temple JR. Stability of alcohol use and teen dating violence for female youth: Alatent transition analysis. Drug Alcohol Rev 2017;36:80-87]. © 2017 Australasian Professional Society on Alcohol and other Drugs.

  5. A Comparison of Approaches for the Analysis of Interaction Effects between Latent Variables Using Partial Least Squares Path Modeling

    Science.gov (United States)

    Henseler, Jorg; Chin, Wynne W.

    2010-01-01

    In social and business sciences, the importance of the analysis of interaction effects between manifest as well as latent variables steadily increases. Researchers using partial least squares (PLS) to analyze interaction effects between latent variables need an overview of the available approaches as well as their suitability. This article…

  6. Construct Equivalence and Latent Means Analysis of Health Behaviors Between Male and Female Middle School Students

    OpenAIRE

    Park, Jeong Mo; Han, Ae Kyung; Cho, Yoon Hee

    2011-01-01

    Purpose: The purpose of this study was to investigate the construct equivalence of the five general factors (subjective health, eating habits, physical activities, sedentary lifestyle, and sleeping behaviors) and to compare the latent means between male and female middle school students in Incheon, Korea. Methods: The 2008 Korean Youth Risk Behavior Survey data was used for analysis. Multigroup confirmatory factor analysis was performed to test whether the scale has configural, metric, and...

  7. Men and women are from Earth: examining the latent structure of gender.

    Science.gov (United States)

    Carothers, Bobbi J; Reis, Harry T

    2013-02-01

    Taxometric methods enable determination of whether the latent structure of a construct is dimensional or taxonic (nonarbitrary categories). Although sex as a biological category is taxonic, psychological gender differences have not been examined in this way. The taxometric methods of mean above minus below a cut, maximum eigenvalue, and latent mode were used to investigate whether gender is taxonic or dimensional. Behavioral measures of stereotyped hobbies and physiological characteristics (physical strength, anthropometric measurements) were examined for validation purposes, and were taxonic by sex. Psychological indicators included sexuality and mating (sexual attitudes and behaviors, mate selectivity, sociosexual orientation), interpersonal orientation (empathy, relational-interdependent self-construal), gender-related dispositions (masculinity, femininity, care orientation, unmitigated communion, fear of success, science inclination, Big Five personality), and intimacy (intimacy prototypes and stages, social provisions, intimacy with best friend). Constructs were with few exceptions dimensional, speaking to Spence's (1993) gender identity theory. Average differences between men and women are not under dispute, but the dimensionality of gender indicates that these differences are inappropriate for diagnosing gender-typical psychological variables on the basis of sex. (c) 2013 APA, all rights reserved.

  8. Construct equivalence and latent means analysis of health behaviors between male and female middle school students.

    Science.gov (United States)

    Park, Jeong Mo; Han, Ae Kyung; Cho, Yoon Hee

    2011-12-01

    The purpose of this study was to investigate the construct equivalence of the five general factors (subjective health, eating habits, physical activities, sedentary lifestyle, and sleeping behaviors) and to compare the latent means between male and female middle school students in Incheon, Korea. The 2008 Korean Youth Risk Behavior Survey data was used for analysis. Multigroup confirmatory factor analysis was performed to test whether the scale has configural, metric, and scalar invariance across gender. Configural invariance, metric invariance, and factor invariance were satisfied for latent means analysis (LMA) between genders. Male and female students were significantly different in LMA of all factors. Male students reported better subjective health, consumed more fast food and carbonated drinks, participated in more physical activities, showed less sedentary behavior, and enjoyed better quality of sleep than female students. Health providers should consider gender differences when they develop and deliver health promotion programs aimed at adolescents. Copyright © 2011. Published by Elsevier B.V.

  9. Analysis of Trace Elements in South African Clinkers using Latent ...

    African Journals Online (AJOL)

    The trace element content of clinkers (and possibly of cements) can be used to identify the manufacturing factory. The Mg, Sr, Ba, Mn, Ti, Zr, Zn and V content of clinkers give detailed information for the determination of the origin of clinkers produced in different factories. However, for the analysis of such complex data there ...

  10. Response Patterns in Health State Valuation Using Endogenous Attribute Attendance and Latent Class Analysis.

    Science.gov (United States)

    Hole, Arne Risa; Norman, Richard; Viney, Rosalie

    2016-02-01

    Not accounting for simplifying decision-making heuristics when modelling data from discrete choice experiments has been shown potentially to lead to biased inferences. This study considers two ways of exploring the presence of attribute non-attendance (that is, respondents considering only a subset of the attributes that define the choice options) in a health state valuation discrete choice experiment. The methods used include the latent class (LC) and endogenous attribute attendance (EAA) models, which both required adjustment to reflect the structure of the quality-adjusted life year (QALY) framework for valuing health outcomes. We find that explicit consideration of attendance patterns substantially improves model fit. The impact of allowing for non-attendance on the estimated QALY weights is dependent on the assumed source of non-attendance. If non-attendance is interpreted as a form of preference heterogeneity, then the inferences from the LC and EAA models are similar to those from standard models, while if respondents ignore attributes to simplify the choice task, the QALY weights differ from those using the standard approach. Because the cause of non-attendance is unknown in the absence of additional data, a policymaker may use the range of weights implied by the two approaches to conduct a sensitivity analysis. Copyright © 2014 John Wiley & Sons, Ltd.

  11. Application of a latent class analysis to empirically define eating disorder phenotypes.

    Science.gov (United States)

    Keel, Pamela K; Fichter, Manfred; Quadflieg, Norbert; Bulik, Cynthia M; Baxter, Mark G; Thornton, Laura; Halmi, Katherine A; Kaplan, Allan S; Strober, Michael; Woodside, D Blake; Crow, Scott J; Mitchell, James E; Rotondo, Alessandro; Mauri, Mauro; Cassano, Giovanni; Treasure, Janet; Goldman, David; Berrettini, Wade H; Kaye, Walter H

    2004-02-01

    Diagnostic criteria for eating disorders influence how we recognize, research, and treat eating disorders, and empirically valid phenotypes are required for revealing their genetic bases. To empirically define eating disorder phenotypes. Data regarding eating disorder symptoms and features from 1179 individuals with clinically significant eating disorders were submitted to a latent class analysis. The resulting latent classes were compared on non-eating disorder variables in a series of validation analyses. Multinational, collaborative study with cases ascertained through diverse clinical settings (inpatient, outpatient, and community). Members of affected relative pairs recruited for participation in genetic studies of eating disorders in which probands met DSM-IV-TR criteria for anorexia nervosa (AN) or bulimia nervosa and had at least 1 biological relative with a clinically significant eating disorder. Main Outcome Measure Number and clinical characterization of latent classes. A 4-class solution provided the best fit. Latent class 1 (LC1) resembled restricting AN; LC2, AN and bulimia nervosa with the use of multiple methods of purging; LC3, restricting AN without obsessive-compulsive features; and LC4, bulimia nervosa with self-induced vomiting as the sole form of purging. Biological relatives were significantly likely to belong to the same latent class. Across validation analyses, LC2 demonstrated the highest levels of psychological disturbance, and LC3 demonstrated the lowest. The presence of obsessive-compulsive features differentiates among individuals with restricting AN. Similarly, the combination of low weight and multiple methods of purging distinguishes among individuals with binge eating and purging behaviors. These results support some of the distinctions drawn within the DSM-IV-TR among eating disorder subtypes, while introducing new features to define phenotypes.

  12. Multichannel biomedical time series clustering via hierarchical probabilistic latent semantic analysis.

    Science.gov (United States)

    Wang, Jin; Sun, Xiangping; Nahavandi, Saeid; Kouzani, Abbas; Wu, Yuchuan; She, Mary

    2014-11-01

    Biomedical time series clustering that automatically groups a collection of time series according to their internal similarity is of importance for medical record management and inspection such as bio-signals archiving and retrieval. In this paper, a novel framework that automatically groups a set of unlabelled multichannel biomedical time series according to their internal structural similarity is proposed. Specifically, we treat a multichannel biomedical time series as a document and extract local segments from the time series as words. We extend a topic model, i.e., the Hierarchical probabilistic Latent Semantic Analysis (H-pLSA), which was originally developed for visual motion analysis to cluster a set of unlabelled multichannel time series. The H-pLSA models each channel of the multichannel time series using a local pLSA in the first layer. The topics learned in the local pLSA are then fed to a global pLSA in the second layer to discover the categories of multichannel time series. Experiments on a dataset extracted from multichannel Electrocardiography (ECG) signals demonstrate that the proposed method performs better than previous state-of-the-art approaches and is relatively robust to the variations of parameters including length of local segments and dictionary size. Although the experimental evaluation used the multichannel ECG signals in a biometric scenario, the proposed algorithm is a universal framework for multichannel biomedical time series clustering according to their structural similarity, which has many applications in biomedical time series management. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  13. Treatment of Latent Tuberculosis Infection: An Updated Network Meta-analysis

    OpenAIRE

    Zenner, D.; Beer, N.; Harris, R. J.; Lipman, M. C.; Stagg, H. R.; van der Werf, M. J.

    2017-01-01

    Background: Treatment of latent tuberculosis infection (LTBI) is an important component of tuberculosis (TB) control, and this study updates a previous network meta-analysis of the best LTBI treatment options to inform public health action and programmatic management of LTBI. Purpose: To evaluate the comparative efficacy and harms of LTBI treatment regimens aimed at preventing active TB among adults and children. Data Sources: PubMed, Embase, and Web of Science from indexing ...

  14. Latent segmentation based count models: Analysis of bicycle safety in Montreal and Toronto.

    Science.gov (United States)

    Yasmin, Shamsunnahar; Eluru, Naveen

    2016-10-01

    The study contributes to literature on bicycle safety by building on the traditional count regression models to investigate factors affecting bicycle crashes at the Traffic Analysis Zone (TAZ) level. TAZ is a traffic related geographic entity which is most frequently used as spatial unit for macroscopic crash risk analysis. In conventional count models, the impact of exogenous factors is restricted to be the same across the entire region. However, it is possible that the influence of exogenous factors might vary across different TAZs. To accommodate for the potential variation in the impact of exogenous factors we formulate latent segmentation based count models. Specifically, we formulate and estimate latent segmentation based Poisson (LP) and latent segmentation based Negative Binomial (LNB) models to study bicycle crash counts. In our latent segmentation approach, we allow for more than two segments and also consider a large set of variables in segmentation and segment specific models. The formulated models are estimated using bicycle-motor vehicle crash data from the Island of Montreal and City of Toronto for the years 2006 through 2010. The TAZ level variables considered in our analysis include accessibility measures, exposure measures, sociodemographic characteristics, socioeconomic characteristics, road network characteristics and built environment. A policy analysis is also conducted to illustrate the applicability of the proposed model for planning purposes. This macro-level research would assist decision makers, transportation officials and community planners to make informed decisions to proactively improve bicycle safety - a prerequisite to promoting a culture of active transportation. Copyright © 2016 Elsevier Ltd. All rights reserved.

  15. A Latent Profile Analysis of Latino Parenting: The Infusion of Cultural Values on Family Conflict

    OpenAIRE

    Ayón, Cecilia; Williams, Lela Rankin; Marsiglia, Flavio F.; Ayers, Stephanie; Kiehne, Elizabeth

    2015-01-01

    The purpose of the present study was to (a) examine how acculturation and social support inform Latinos’ parenting behaviors, controlling for gender and education; (b) describe parenting styles among Latino immigrants while accounting for cultural elements; and (c) test how these parenting styles are associated with family conflict. A 3 step latent profile analysis with the sample (N = 489) revealed best fit with a 4 profile model (n = 410) of parenting: family parenting (n = 268, 65%), child...

  16. Using Latent Semantic Analysis to Identify Quality in Use (QU) Indicators from User Reviews

    OpenAIRE

    Syn, Wendy Tan Wei; How, Bong Chih; Atoum, Issa

    2015-01-01

    The paper describes a novel approach to categorize users' reviews according to the three Quality in Use (QU) indicators defined in ISO: effectiveness, efficiency and freedom from risk. With the tremendous amount of reviews published each day, there is a need to automatically summarize user reviews to inform us if any of the software able to meet requirement of a company according to the quality requirements. We implemented the method of Latent Semantic Analysis (LSA) and its subspace to predi...

  17. A simple low cost latent fingerprint sensor based on deflectometry and WFT analysis

    Science.gov (United States)

    Dhanotia, Jitendra; Chatterjee, Amit; Bhatia, Vimal; Prakash, Shashi

    2018-02-01

    In criminal investigations, latent fingerprints are one of the most significant forms of evidence and most commonly used forensic investigation tool worldwide. The existing non-contact latent fingerprint detection systems are bulky, expensive and require environment which is shock and vibration resistant, thereby limiting their usability outside the laboratory. In this article, a compact, full field, low cost technique for profiling of fingerprints using deflectometry is proposed. Using inexpensive mobile phone screen based structured illumination, and windowed Fourier transform (WFT) based phase retrieval mechanism, the 2D and 3D phase plots reconstruct the profile information of the fingerprint. The phase information is also used to confirm a match between two fingerprints in real time. Since the proposed technique is non-interferometric, the measurements are least affected by environmental perturbations. Using the proposed technique, a portable sensor capable of field deployment has been realized.

  18. Characteristics of cyclist crashes in Italy using latent class analysis and association rule mining.

    Directory of Open Access Journals (Sweden)

    Gabriele Prati

    Full Text Available The factors associated with severity of the bicycle crashes may differ across different bicycle crash patterns. Therefore, it is important to identify distinct bicycle crash patterns with homogeneous attributes. The current study aimed at identifying subgroups of bicycle crashes in Italy and analyzing separately the different bicycle crash types. The present study focused on bicycle crashes that occurred in Italy during the period between 2011 and 2013. We analyzed categorical indicators corresponding to the characteristics of infrastructure (road type, road signage, and location type, road user (i.e., opponent vehicle and cyclist's maneuver, type of collision, age and gender of the cyclist, vehicle (type of opponent vehicle, and the environmental and time period variables (time of the day, day of the week, season, pavement condition, and weather. To identify homogenous subgroups of bicycle crashes, we used latent class analysis. Using latent class analysis, the bicycle crash data set was segmented into 19 classes, which represents 19 different bicycle crash types. Logistic regression analysis was used to identify the association between class membership and severity of the bicycle crashes. Finally, association rules were conducted for each of the latent classes to uncover the factors associated with an increased likelihood of severity. Association rules highlighted different crash characteristics associated with an increased likelihood of severity for each of the 19 bicycle crash types.

  19. Classification of multiple sclerosis patients by latent class analysis of magnetic resonance imaging characteristics.

    Science.gov (United States)

    Zwemmer, J N P; Berkhof, J; Castelijns, J A; Barkhof, F; Polman, C H; Uitdehaag, B M J

    2006-10-01

    Disease heterogeneity is a major issue in multiple sclerosis (MS). Classification of MS patients is usually based on clinical characteristics. More recently, a pathological classification has been presented. While clinical subtypes differ by magnetic resonance imaging (MRI) signature on a group level, a classification of individual MS patients based purely on MRI characteristics has not been presented so far. To investigate whether a restricted classification of MS patients can be made based on a combination of quantitative and qualitative MRI characteristics and to test whether the resulting subgroups are associated with clinical and laboratory characteristics. MRI examinations of the brain and spinal cord of 50 patients were scored for 21 quantitative and qualitative characteristics. Using latent class analysis, subgroups were identified, for whom disease characteristics and laboratory measures were compared. Latent class analysis revealed two subgroups that mainly differed in the extent of lesion confluency and MRI correlates of neuronal loss in the brain. Demographics and disease characteristics were comparable except for cognitive deficits. No correlations with laboratory measures were found. Latent class analysis offers a feasible approach for classifying subgroups of MS patients based on the presence of MRI characteristics. The reproducibility, longitudinal evolution and further clinical or prognostic relevance of the observed classification will have to be explored in a larger and independent sample of patients.

  20. Discontinuous Patterns of Cigarette Smoking From Ages 18 to 50 in the United States: A Repeated-Measures Latent Class Analysis.

    Science.gov (United States)

    Terry-McElrath, Yvonne M; O'Malley, Patrick M; Johnston, Lloyd D

    2017-12-13

    Effective cigarette smoking prevention and intervention programming is enhanced by accurate understanding of developmental smoking pathways across the life span. This study investigated within-person patterns of cigarette smoking from ages 18 to 50 among a US national sample of high school graduates, focusing on identifying ages of particular importance for smoking involvement change. Using data from approximately 15,000 individuals participating in the longitudinal Monitoring the Future study, trichotomous measures of past 30-day smoking obtained at 11 time points were modeled using repeated-measures latent class analyses. Sex differences in latent class structure and membership were examined. Twelve latent classes were identified: three characterized by consistent smoking patterns across age (no smoking; smoking developing effective smoking prevention and intervention programming. This study examined cigarette smoking among a national longitudinal US sample of high school graduates from ages 18 to 50 and identified distinct latent classes characterized by patterns of movement between no cigarette use, light-to-moderate smoking, and the conventional definition of heavy smoking at 11 time points via repeated-measures latent class analysis. Membership probabilities for each smoking class were estimated, and critical ages of susceptibility to change in smoking behaviors were identified. © The Author 2017. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  1. Symptom Cluster Research With Biomarkers and Genetics Using Latent Class Analysis.

    Science.gov (United States)

    Conley, Samantha

    2017-12-01

    The purpose of this article is to provide an overview of latent class analysis (LCA) and examples from symptom cluster research that includes biomarkers and genetics. A review of LCA with genetics and biomarkers was conducted using Medline, Embase, PubMed, and Google Scholar. LCA is a robust latent variable model used to cluster categorical data and allows for the determination of empirically determined symptom clusters. Researchers should consider using LCA to link empirically determined symptom clusters to biomarkers and genetics to better understand the underlying etiology of symptom clusters. The full potential of LCA in symptom cluster research has not yet been realized because it has been used in limited populations, and researchers have explored limited biologic pathways.

  2. A latent transition analysis of bullying and victimization in Chinese primary school students.

    Directory of Open Access Journals (Sweden)

    Yiqin Pan

    Full Text Available Bullying is a social phenomenon that impacts a large number of children and young people, worldwide. This study aimed to longitudinally examine the development of bullying and victimization in Chinese students in grades 4, 5, and 6. We used latent class analysis to empirically identify groups of youth with different bullying and victimization patterns, and then used latent transition analysis to explore the movement of children between these latent classes over time. Results showed that: (1 across the three time points, students could be classified into four classes: bullies, victims, bully-victims, and non-involved children; and (2 students in the non-involved class tended to remain in that class when moving to higher grades, students in the bully and victims classes tended to transition to the non-involved class, while students in the bully-victims class tended to transition to the bullies class. Thus, future intervention should be implemented to prevent bully-victims from bullying behaviors.

  3. Using multiple biomarkers and determinants to obtain a better measurement of oxidative stress: a latent variable structural equation model approach.

    Science.gov (United States)

    Eldridge, Ronald C; Flanders, W Dana; Bostick, Roberd M; Fedirko, Veronika; Gross, Myron; Thyagarajan, Bharat; Goodman, Michael

    2017-09-01

    Since oxidative stress involves a variety of cellular changes, no single biomarker can serve as a complete measure of this complex biological process. The analytic technique of structural equation modeling (SEM) provides a possible solution to this problem by modelling a latent (unobserved) variable constructed from the covariance of multiple biomarkers. Using three pooled datasets, we modelled a latent oxidative stress variable from five biomarkers related to oxidative stress: F 2 -isoprostanes (FIP), fluorescent oxidation products, mitochondrial DNA copy number, γ-tocopherol (Gtoc) and C-reactive protein (CRP, an inflammation marker closely linked to oxidative stress). We validated the latent variable by assessing its relation to pro- and anti-oxidant exposures. FIP, Gtoc and CRP characterized the latent oxidative stress variable. Obesity, smoking, aspirin use and β-carotene were statistically significantly associated with oxidative stress in the theorized directions; the same exposures were weakly and inconsistently associated with the individual biomarkers. Our results suggest that using SEM with latent variables decreases the biomarker-specific variability, and may produce a better measure of oxidative stress than do single variables. This methodology can be applied to similar areas of research in which a single biomarker is not sufficient to fully describe a complex biological phenomenon.

  4. Taxometric evidence of a dimensional latent structure for depression in an epidemiological sample of children and adolescents.

    Science.gov (United States)

    Liu, R T

    2016-04-01

    A basic phenomenological question of much theoretical and empirical interest is whether the latent structure of depression is dimensional or categorical in nature. Prior taxometric studies of youth depression have yielded mixed findings. In a step towards resolving these contradictory findings, the current taxometric investigation is the first to utilize a recently developed objective index, the comparison curve fit index, to evaluate the latent structure of major depression in an epidemiological sample of children and adolescents. Data were derived from Mental Health of Children and Young People in Great Britain surveys. Participants were administered a structured diagnostic interview to assess for current depression. Parents (n = 683) were interviewed for children aged 5-16 years, and child interviews (n = 605) were conducted for those aged 11-16 years. MAMBAC (mean above minus below a cut), MAXEIG (maximum eigenvalue) and L-Mode (latent mode) analyses provided convergent support for a dimensional latent structure. The current findings suggest that depression in youth is more accurately conceptualized as a continuous syndrome rather than a discrete diagnostic entity.

  5. The Nature of Coping in Treatment for Marijuana Dependence: Latent Structure and Validation of the Coping Strategies Scale

    Science.gov (United States)

    Litt, Mark D.; Kadden, Ronald M; Tennen, Howard

    2012-01-01

    The Coping Strategies Scale (CSS) was designed to assess adaptive changes in substance-use specific coping that result from treatment. The present study sought to examine the latent structure of the CSS in the hope that it might shed light on the coping processes of drug users, and guide the development of a brief version of the CSS. Respondents on the CSS were 751 men and women treated in three clinical trials for marijuana dependence. Posttreatment CSS data were analyzed to determine the nature of coping responses in patients who have been trained to use specific strategies to deal with substance use disorders. Exploratory factor analysis yielded two factors, categorized as problem-focused and emotion-focused coping, but confirmatory factor analysis did not support this structure. When infrequently endorsed items were removed, however, confirmatory factor analysis revealed a good fit to the data. Contrary to expectations, practical strategies that often form the basis for coping skills training, such as avoiding those who smoke, were not frequently endorsed. Problem focused items reflected cognitive commitments to change. Emotion-focused items included cognitive reinterpretations of emotions, to help manage emotional reactions. Brief versions of the CSS based on these factors showed good convergent and discriminant validity. The CSS, and the brief versions of the CSS, may prove useful in future treatment trials to evaluate effects of treatment on coping skills acquisition and utilization in substance dependent individuals. PMID:22082345

  6. Pathways of early fatherhood, marriage, and employment: a latent class growth analysis.

    Science.gov (United States)

    Dariotis, Jacinda K; Pleck, Joseph H; Astone, Nan M; Sonenstein, Freya L

    2011-05-01

    In the National Longitudinal Survey of Youth 1979 (NLSY79), young fathers include heterogeneous subgroups with varying early life pathways in terms of fatherhood timing, the timing of first marriage, and holding full-time employment. Using latent class growth analysis with 10 observations between ages 18 and 37, we derived five latent classes with median ages of first fatherhood below the cohort median (26.4), constituting distinct early fatherhood pathways representing 32.4% of NLSY men: (A) Young Married Fathers, (B) Teen Married Fathers, (C) Young Underemployed Married Fathers, (D) Young Underemployed Single Fathers, and (E) Young Later-Marrying Fathers. A sixth latent class of men who become fathers around the cohort median, following full-time employment and marriage (On-Time On-Sequence Fathers), is the comparison group. With sociodemographic background controlled, all early fatherhood pathways show disadvantage in at least some later-life circumstances (earnings, educational attainment, marital status, and incarceration). The extent of disadvantage is greater when early fatherhood occurs at relatively younger ages (before age 20), occurs outside marriage, or occurs outside full-time employment. The relative disadvantage associated with early fatherhood, unlike early motherhood, increases over the life course.

  7. Towards a typology of business process management professionals: identifying patterns of competences through latent semantic analysis

    DEFF Research Database (Denmark)

    Müller, Oliver; Schmiedel, Theresa; Gorbacheva, Elena

    2014-01-01

    -related job advertisements in order to develop a typology of BPM professionals. This empirical analysis reveals distinct ideal types and profiles of BPM professionals on several levels of abstraction. A closer look at these ideal types and profiles confirms that BPM is a boundary-spanning field that requires......While researchers have analysed the organisational competences that are required for successful Business Process Management (BPM) initiatives, individual BPM competences have not yet been studied in detail. In this study, latent semantic analysis is used to examine a collection of 1507 BPM...

  8. Oral health status in older adults with social security in Mexico City: Latent class analysis.

    Science.gov (United States)

    Sánchez-García, Sergio; Heredia-Ponce, Erika; Cruz-Hervert, Pablo; Juárez-Cedillo, Teresa; Cárdenas-Bahena, Angel; García-Peña, Carmen

    2014-02-01

    To explore the oral health status through a latent class analysis in elderly social security beneficiaries from Southwest Mexico City. Cross-sectional study of beneficiaries of the State Employee Social Security and Social Services Institute (ISSSTE, in Spanish) and the Mexican Institute of Social Security (IMSS, in Spanish) aged 60 years or older. Oral health conditions such as edentulism, coronal and root caries (DMFT and DFT ≥ 75 percentile), clinical attachment loss (≥ 4 mm), and healthy teeth (≤ 25 percentile) were determined. A latent class analysis (LCA) was performed to classify the oral health status of dentate patients. In total, 336 patients were included (47.9% from the ISSSTE and 52.1% from the IMSS), with an average age of 74.4 (SD = 7.1) years. The 75th percentile of the DMFT = 23 and of the DFT = 2. Of the patients, 77.9% had periodontal disease. The 25th percentile of healthy teeth = 4. A three class model is adequate, with a high classification quality (Entropy = 0.915). The patients were classified as "Edentulous" (15.2%), "Class 1 = Unfavorable" (13.7%), "Class 2 = Somewhat favorable" (10.4%), and "Class 3 = Favorable" (60.7%). Using "Class 3 = Favorable" as a reference, there was an association (OR = 3.4; 95% CI = 1.8-6.4) between being edentulous and being 75 years of age and over, compared with the 60- to 74-year age group. The oral health in elderly social security beneficiaries is not optimal. The probability of becoming edentulous increases with age. A three-class model appropriately classifies the oral health dimensions in the elderly population. Key words:Elderly, Latent class analysis (LCA), oral health, social security, Mexico.

  9. Examining the Latent Structure of the Delis-Kaplan Executive Function System.

    Science.gov (United States)

    Karr, Justin E; Hofer, Scott M; Iverson, Grant L; Garcia-Barrera, Mauricio A

    2018-05-04

    The current study aimed to determine whether the Delis-Kaplan Executive Function System (D-KEFS) taps into three executive function factors (inhibition, shifting, fluency) and to assess the relationship between these factors and tests of executive-related constructs less often measured in latent variable research: reasoning, abstraction, and problem solving. Participants included 425 adults from the D-KEFS standardization sample (20-49 years old; 50.1% female; 70.1% White). Eight alternative measurement models were compared based on model fit, with test scores assigned a priori to three factors: inhibition (Color-Word Interference, Tower), shifting (Trail Making, Sorting, Design Fluency), and fluency (Verbal/Design Fluency). The Twenty Questions, Word Context, and Proverb Tests were predicted in separate structural models. The three-factor model fit the data well (CFI = 0.938; RMSEA = 0.047), although a two-factor model, with shifting and fluency merged, fit similarly well (CFI = 0.929; RMSEA = 0.048). A bifactor model fit best (CFI = 0.977; RMSEA = 0.032) and explained the most variance in shifting indicators, but rarely converged among 5,000 bootstrapped samples. When the three first-order factors simultaneously predicted the criterion variables, only shifting was uniquely predictive (p measuring executive-related constructs and provide a framework through which clinicians can interpret D-KEFS results.

  10. Usage of Latent Class Analysis in Diagnostic Microbiology in the Absence of Gold Standard Test

    Directory of Open Access Journals (Sweden)

    Gul Bayram Abiha

    2016-12-01

    Full Text Available The evaluation of performance of various tests diagnostic tests in the absence of gold standard is an important problem. Latent class analysis (LCA is a statistical analysis method known for many years, especially in the absence of a gold standard for evaluation of diagnostic tests so that LCA has found its wide application area. During the last decade, LCA method has widely used in for determining sensivity and specifity of different microbiological tests. It has investigated in the diagnosis of mycobacterium tuberculosis, mycobacterium bovis, human papilloma virus, bordetella pertussis, influenza viruses, hepatitis E virus (HEV, hepatitis C virus (HCV and other various viral infections. Researchers have compared several diagnostic tests for the diagnosis of different pathogens with LCA. We aimed to evaluate performance of latent class analysis method used microbiological diagnosis in various diseases in several researches. When we took into account all of these tests' results, we suppose that LCA is a good statistical analysis method to assess different test performances in the absence of gold standard. [Archives Medical Review Journal 2016; 25(4.000: 467-488

  11. Toward a quantitative typology of burglars: a latent profile analysis of career offenders.

    Science.gov (United States)

    Vaughn, Michael G; DeLisi, Matt; Beaver, Kevin M; Howard, Matthew O

    2008-11-01

    Burglary is a serious, costly, and prevalent crime but prior typologies of burglars are mostly speculative and based on qualitative data. Using a sample of 456 adult career criminals, the current study used latent profile analysis to construct a methodologically rigorous quantitative typology. Four classes of burglars emerged: young versatile, vagrant, drug-oriented, and sexual predators. All groups demonstrated significant involvement in varied forms of crime, but the sexual predator group was the most violent and had the most serious criminal careers. Connections to the criminal career literature are offered and suggestions for further empirical study of offender typologies are discussed.

  12. ltm: An R Package for Latent Variable Modeling and Item Response Analysis

    Directory of Open Access Journals (Sweden)

    Dimitris Rizopoulos

    2006-11-01

    Full Text Available The R package ltm has been developed for the analysis of multivariate dichotomous and polytomous data using latent variable models, under the Item Response Theory approach. For dichotomous data the Rasch, the Two-Parameter Logistic, and Birnbaum's Three-Parameter models have been implemented, whereas for polytomous data Semejima's Graded Response model is available. Parameter estimates are obtained under marginal maximum likelihood using the Gauss-Hermite quadrature rule. The capabilities and features of the package are illustrated using two real data examples.

  13. Using Latent Semantic Analysis to Identify Research Trends in OpenStreetMap

    Directory of Open Access Journals (Sweden)

    Sukhjit Singh Sehra

    2017-07-01

    Full Text Available OpenStreetMap (OSM, based on collaborative mapping, has become a subject of great interest to the academic community, resulting in a considerable body of literature produced by many researchers. In this paper, we use Latent Semantic Analysis (LSA to help identify the emerging research trends in OSM. An extensive corpus of 485 academic abstracts of papers published during the period 2007–2016 was used. Five core research areas and fifty research trends were identified in this study. In addition, potential future research directions have been provided to aid geospatial information scientists, technologists and researchers in undertaking future OSM research.

  14. BayesLCA: An R Package for Bayesian Latent Class Analysis

    Directory of Open Access Journals (Sweden)

    Arthur White

    2014-11-01

    Full Text Available The BayesLCA package for R provides tools for performing latent class analysis within a Bayesian setting. Three methods for fitting the model are provided, incorporating an expectation-maximization algorithm, Gibbs sampling and a variational Bayes approximation. The article briefly outlines the methodology behind each of these techniques and discusses some of the technical difficulties associated with them. Methods to remedy these problems are also described. Visualization methods for each of these techniques are included, as well as criteria to aid model selection.

  15. Variations in Care Quality Outcomes of Dying People: Latent Class Analysis of an Adult National Register Population.

    Science.gov (United States)

    Öhlén, Joakim; Russell, Lara; Håkanson, Cecilia; Alvariza, Anette; Fürst, Carl Johan; Årestedt, Kristofer; Sawatzky, Richard

    2017-01-01

    Symptom relief is a key goal of palliative care. There is a need to consider complexities in symptom relief patterns for groups of people to understand and evaluate symptom relief as an indicator of quality of care at end of life. The aims of this study were to distinguish classes of patients who have different symptom relief patterns during the last week of life and to identify predictors of these classes in an adult register population. In a cross-sectional retrospective design, data were used from 87,026 decedents with expected deaths registered in the Swedish Register of Palliative Care in 2011 and 2012. Study variables were structured into patient characteristics, and processes and outcomes of quality of care. A latent class analysis was used to identify symptom relief patterns. Multivariate multinomial regression analyses were used to identify predictors of class membership. Five latent classes were generated: "relieved pain," "relieved pain and rattles," "relieved pain and anxiety," "partly relieved shortness of breath, rattles and anxiety," and "partly relieved pain, anxiety and confusion." Important predictors of class membership were age, sex, cause of death, and having someone present at death, individual prescriptions as needed (PRN) and expert consultations. Interindividual variability and complexity in symptom relief patterns may inform quality of care and its evaluation for dying people across care settings. Copyright © 2016 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

  16. Substance Use, Violence, and Antiretroviral Adherence: A Latent Class Analysis of Women Living with HIV in Canada.

    Science.gov (United States)

    Carter, Allison; Roth, Eric Abella; Ding, Erin; Milloy, M-J; Kestler, Mary; Jabbari, Shahab; Webster, Kath; de Pokomandy, Alexandra; Loutfy, Mona; Kaida, Angela

    2018-03-01

    We used latent class analysis to identify substance use patterns for 1363 women living with HIV in Canada and assessed associations with socio-economic marginalization, violence, and sub-optimal adherence to combination antiretroviral therapy (cART). A six-class model was identified consisting of: abstainers (26.3%), Tobacco Users (8.81%), Alcohol Users (31.9%), 'Socially Acceptable' Poly-substance Users (13.9%), Illicit Poly-substance Users (9.81%) and Illicit Poly-substance Users of All Types (9.27%). Multinomial logistic regression showed that women experiencing recent violence had significantly higher odds of membership in all substance use latent classes, relative to Abstainers, while those reporting sub-optimal cART adherence had higher odds of being members of the poly-substance use classes only. Factors significantly associated with Illicit Poly-substance Users of All Types were sexual minority status, lower income, and lower resiliency. Findings underline a need for increased social and structural supports for women who use substances to support them in leading safe and healthy lives with HIV.

  17. Comprehensive thermodynamic analysis of a renewable energy sourced hybrid heating system combined with latent heat storage

    International Nuclear Information System (INIS)

    Utlu, Zafer; Aydın, Devrim; Kıncay, Olcay

    2014-01-01

    Highlights: • An experimental thermal investigation of hybrid renewable heating system is presented. • Analyses were done by using real data obtained from a prototype structure. • Exergy efficiency of system components investigated during discharging period are close to each other as 32%. • The average input energy and exergy rates to the LHS were 0.770 and 0.027 kW. • Overall total energy and exergy efficiencies of LHS calculated as 72% and 28.4%. - Abstract: In this study an experimental thermal investigation of hybrid renewable heating system is presented. Latent heat storage stores energy, gained by solar collectors and supplies medium temperature heat to heat pump both day time also night time while solar energy is unavailable. In addition to this an accumulation tank exists in the system as sensible heat storage. It provides supply–demand balance with storing excess high temperature heat. Analyses were done according to thermodynamic’s first and second laws by using real data obtained from a prototype structure, built as part of a project. Results show that high percent of heat loses took place in heat pump with 1.83 kW where accumulator-wall heating cycle followed it with 0.42 kW. Contrarily highest break-down of exergy loses occur accumulator-wall heating cycle with 0.28 kW. Averagely 2.42 kW exergy destruction took place in whole system during the experiment. Solar collectors and heat pump are the promising components in terms of exergy destruction with 1.15 kW and 1.09 kW respectively. Exergy efficiency of system components, investigated during discharging period are in a close approximately of 32%. However, efficiency of solar collectors and charging of latent heat storage are 2.3% and 7% which are relatively low. Average overall total energy and exergy efficiencies of latent heat storage calculated as 72% and 28.4% respectively. Discharging energy efficiency of latent heat storage is the highest through all system components. Also heat

  18. Is there a nonadherent subtype of hypertensive patient? A latent class analysis approach

    Directory of Open Access Journals (Sweden)

    Ranak B Trivedi

    2010-07-01

    Full Text Available Ranak B Trivedi1, Brian J Ayotte2, Carolyn T Thorpe3, David Edelman4, Hayden B Bosworth51Northwest Health Services Research and Development Service Center of Excellence, VA Puget Sound Health Care System, Seattle, Washington; 2Boston VA Health Care System, Boston, Massachusetts; 3Department of Population Health Sciences, University of Wisconsin, Madison, Wisconsin; 4Department of Medicine, Duke University Medical Center, Durham, North Carolina; 5Research Professor, Department of Medicine, Duke University Medical Center, Durham, North Carolina, USAAbstract: To determine subtypes of adherence, 636 hypertensive patients (48% White, 34% male reported adherence to medications, diet, exercise, smoking, and home blood pressure monitoring. A latent class analysis approach was used to identify subgroups that adhere to these five self-management behaviors. Fit statistics suggested two latent classes. The first class (labeled “more adherent” included patients with greater probability of adhering to ­recommendations compared with the second class (labeled “less adherent” with regard to nonsmoking (97.7% versus 76.3%, medications (75.5% versus 49.5%, diet (70.7% versus 46.9%, exercise (63.4% versus 27.2%, and blood pressure monitoring (32% versus 3.4%. Logistic regression analyses used to characterize the two classes showed that “more adherent” participants were more likely to report full-time employment, adequate income, and better emotional and physical well-being. Results suggest the presence of a less adherent subtype of hypertensive patients. Behavioral interventions designed to improve adherence might best target these at-risk patients for greater treatment efficiency.Keywords: adherence, hypertension, latent class analysis, self-management

  19. Organizational Supports for Research Evidence Use in State Public Health Agencies: A Latent Class Analysis.

    Science.gov (United States)

    Hu, Hengrui; Allen, Peg; Yan, Yan; Reis, Rodrigo S; Jacob, Rebekah R; Brownson, Ross C

    2018-05-30

    Use of research evidence in public health decision making can be affected by organizational supports. Study objectives are to identify patterns of organizational supports and explore associations with research evidence use for job tasks among public health practitioners. In this longitudinal study, we used latent class analysis to identify organizational support patterns, followed by mixed logistic regression analysis to quantify associations with research evidence use. The setting included 12 state public health department chronic disease prevention units and their external partnering organizations involved in chronic disease prevention. Chronic disease prevention staff from 12 US state public health departments and partnering organizations completed self-report surveys at 2 time points, in 2014 and 2016 (N = 872). Latent class analysis was employed to identify subgroups of survey participants with distinct patterns of perceived organizational supports. Two classify-analyze approaches (maximum probability assignment and multiple pseudo-class draws) were used in 2017 to investigate the association between latent class membership and research evidence use. The optimal model identified 4 latent classes, labeled as "unsupportive workplace," "low agency leadership support," "high agency leadership support," and "supportive workplace." With maximum probability assignment, participants in "high agency leadership support" (odds ratio = 2.08; 95% CI, 1.35-3.23) and "supportive workplace" (odds ratio = 1.74; 95% CI, 1.10-2.74) were more likely to use research evidence in job tasks than "unsupportive workplace." The multiple pseudo-class draws produced comparable results with odds ratio = 2.09 (95% CI, 1.31-3.30) for "high agency leadership support" and odds ratio = 1.74 (95% CI, 1.07-2.82) for "supportive workplace." Findings suggest that leadership support may be a crucial element of organizational supports to encourage research evidence use. Organizational supports such

  20. Structure and function of the latent F0-F1-ATPase complex of Micrococcus lysodeikticus

    International Nuclear Information System (INIS)

    Chung, Y.S.

    1988-01-01

    The latent F 0 F 1 -ATPase from Micrococcus luteus (lysodeikticus) has been purified to homogeneity, and nine distinct subunit bands were observed on SDS-PAGE. Five of nine bands corresponded to the F 1 subunits and the other four bands are likely to be subunits a, a', b, and c of the F 0 segment of the complex. The subunit designated as a' probably arises from proteolytic cleavage of the 25,5000 Mr subunit a. The F 0 F 1 -ATPase complex has a molecular weight of approximately 1,060,000, as determined by Fast Protein Liquid Chromatography (FPLC). It is assumed that the F 0 F 1 -ATPase peak obtained by FPLC was a dimer and that molecular weight of the F 0 F 1 -ATPase monomer was accordingly 530,000. The stoichiometry of the subunits was determined with 14 C-labeled F 0 F 1 -ATPase prepared from cells grown on medium containing 14 C-amino acids. Antibodies to the native and SDS-denatured F 1 and F 0 F 1 -ATPase as well as to individual SDS-dissociated subunits have been generated for immunochemical analysis. The arrangement of the subunits in F 1 and F 0 F 1 -ATPase have been investigated using bifunctional chemical cross-linking agents

  1. Latent transition analysis of pre-service teachers' efficacy in mathematics and science

    Science.gov (United States)

    Ward, Elizabeth Kennedy

    This study modeled changes in pre-service teacher efficacy in mathematics and science over the course of the final year of teacher preparation using latent transition analysis (LTA), a longitudinal form of analysis that builds on two modeling traditions (latent class analysis (LCA) and auto-regressive modeling). Data were collected using the STEBI-B, MTEBI-r, and the ABNTMS instruments. The findings suggest that LTA is a viable technique for use in teacher efficacy research. Teacher efficacy is modeled as a construct with two dimensions: personal teaching efficacy (PTE) and outcome expectancy (OE). Findings suggest that the mathematics and science teaching efficacy (PTE) of pre-service teachers is a multi-class phenomena. The analyses revealed a four-class model of PTE at the beginning and end of the final year of teacher training. Results indicate that when pre-service teachers transition between classes, they tend to move from a lower efficacy class into a higher efficacy class. In addition, the findings suggest that time-varying variables (attitudes and beliefs) and time-invariant variables (previous coursework, previous experiences, and teacher perceptions) are statistically significant predictors of efficacy class membership. Further, analyses suggest that the measures used to assess outcome expectancy are not suitable for LCA and LTA procedures.

  2. Examining the latent structure mechanisms for comorbid posttraumatic stress disorder and major depressive disorder.

    Science.gov (United States)

    Hurlocker, Margo C; Vidaurri, Desirae N; Cuccurullo, Lisa-Ann J; Maieritsch, Kelly; Franklin, C Laurel

    2018-03-15

    Posttraumatic stress disorder (PTSD) is a complex psychiatric illness that can be difficult to diagnose, due in part to its comorbidity with major depressive disorder (MDD). Given that researchers have found no difference in prevalence rates of PTSD and MDD after accounting for overlapping symptoms, the latent structures of PTSD and MDD may account for the high comorbidity. In particular, the PTSD Negative Alterations in Cognition and Mood (NACM) and Hyperarousal factors have been characterized as non-specific to PTSD. Therefore, we compared the factor structures of the Diagnostic and Statistical Manual of Mental Disorders, 5 th edition (DSM-5) PTSD and MDD and examined the mediating role of the PTSD NACM and Hyperarousal factors on the relationship between MDD and PTSD symptom severity. Participants included 598 trauma-exposed veterans (M age = 48.39, 89% male) who completed symptom self-report measures of DSM-5 PTSD and MDD. Confirmatory factor analyses indicated an adequate-fitting four-factor DSM-5 PTSD model and two-factor MDD model. Compared to other PTSD factors, the PTSD NACM factor had the strongest relationship with the MDD Affective factor, and the PTSD NACM and Hyperarousal factors had the strongest association with the MDD Somatic factor. Further, the PTSD NACM factor explained the relationship between MDD factors and PTSD symptom severity. More Affective and Somatic depression was related to more NACM symptoms, which in turn were related to increased severity of PTSD. Limitations include the reliance on self-report measures and the use of a treatment-seeking, trauma-exposed veteran sample which may not generalize to other populations. Implications concerning the shared somatic complaints and psychological distress in the comorbidity of PTSD and MDD are discussed. Published by Elsevier B.V.

  3. Are depression and frailty overlapping syndromes in mid- and late-life? A latent variable analysis.

    Science.gov (United States)

    Mezuk, Briana; Lohman, Matthew; Dumenci, Levent; Lapane, Kate L

    2013-06-01

    Depression and frailty both predict disability and morbidity in later life. However, it is unclear to what extent these common geriatric syndromes represent overlapping constructs. To examine the joint relationship between the constructs of depression and frailty. Data come from 2004-2005 wave of the Baltimore Epidemiologic Catchment Area Study, and the analysis is limited to participants 40 years and older, with complete data on frailty and depression indicators (N = 683). Depression was measured using the Diagnostic Interview Schedule, and frailty was indexed by modified Fried criteria. A series of confirmatory latent class analyses were used to assess the degree to which depression and frailty syndromes identify the same populations. A latent kappa coefficient (κl) was also estimated between the constructs. Confirmatory latent class analyses indicated that depression and frailty represent distinct syndromes rather than a single construct. The joint modeling of the two constructs supported a three-class solution for depression and two-class solution for frailty, with 2.9% categorized as severely depressed, 19.4% as mildly depressed, and 77.7% as not depressed, and 21.1% categorized as frail and 78.9% as not frail. The chance-corrected agreement statistic indicated moderate correspondence between the depression and frailty constructs (κl: 66, 95% confidence interval: 0.58-0.74). Results suggest that depression and frailty are interrelated concepts, yet their operational criteria identify substantively overlapping subpopulations. These findings have implications for understanding factors that contribute to the etiology and prognosis of depression and frailty in later life. Copyright © 2013 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.

  4. Latent class analysis of early developmental trajectory in baby siblings of children with autism.

    Science.gov (United States)

    Landa, Rebecca J; Gross, Alden L; Stuart, Elizabeth A; Bauman, Margaret

    2012-09-01

    Siblings of children with autism (sibs-A) are at increased genetic risk for autism spectrum disorders (ASD) and milder impairments. To elucidate diversity and contour of early developmental trajectories exhibited by sibs-A, regardless of diagnostic classification, latent class modeling was used. Sibs-A (N = 204) were assessed with the Mullen Scales of Early Learning from age 6 to 36 months. Mullen T scores served as dependent variables. Outcome classifications at age 36 months included: ASD (N = 52); non-ASD social/communication delay (broader autism phenotype; BAP; N = 31); and unaffected (N = 121). Child-specific patterns of performance were studied using latent class growth analysis. Latent class membership was then related to diagnostic outcome through estimation of within-class proportions of children assigned to each diagnostic classification. A 4-class model was favored. Class 1 represented accelerated development and consisted of 25.7% of the sample, primarily unaffected children. Class 2 (40.0% of the sample), was characterized by normative development with above-average nonverbal cognitive outcome. Class 3 (22.3% of the sample) was characterized by receptive language, and gross and fine motor delay. Class 4 (12.0% of the sample), was characterized by widespread delayed skill acquisition, reflected by declining trajectories. Children with an outcome diagnosis of ASD were spread across Classes 2, 3, and 4. Results support a category of ASD that involves slowing in early non-social development. Receptive language and motor development is vulnerable to early delay in sibs-A with and without ASD outcomes. Non-ASD sibs-A are largely distributed across classes depicting average or accelerated development. Developmental trajectories of motor, language, and cognition appear independent of communication and social delays in non-ASD sibs-A. © 2012 The Authors. Journal of Child Psychology and Psychiatry © 2012 Association for Child and Adolescent Mental Health.

  5. Illustration of Step-Wise Latent Class Modeling With Covariates and Taxometric Analysis in Research Probing Children's Mental Models in Learning Sciences.

    Science.gov (United States)

    Stamovlasis, Dimitrios; Papageorgiou, George; Tsitsipis, Georgios; Tsikalas, Themistoklis; Vaiopoulou, Julie

    2018-01-01

    This paper illustrates two psychometric methods, latent class analysis (LCA) and taxometric analysis (TA) using empirical data from research probing children's mental representation in science learning. LCA is used to obtain a typology based on observed variables and to further investigate how the encountered classes might be related to external variables, where the effectiveness of classification process and the unbiased estimations of parameters become the main concern. In the step-wise LCA, the class membership is assigned and subsequently its relationship with covariates is established. This leading-edge modeling approach suffers from severe downward-biased estimations. The illustration of LCA is focused on alternative bias correction approaches and demonstrates the effect of modal and proportional class-membership assignment along with BCH and ML correction procedures. The illustration of LCA is presented with three covariates, which are psychometric variables operationalizing formal reasoning, divergent thinking and field dependence-independence, respectively. Moreover, taxometric analysis, a method designed to detect the type of the latent structural model, categorical or dimensional, is introduced, along with the relevant basic concepts and tools. TA was applied complementarily in the same data sets to answer the fundamental hypothesis about children's naïve knowledge on the matters under study and it comprises an additional asset in building theory which is fundamental for educational practices. Taxometric analysis provided results that were ambiguous as far as the type of the latent structure. This finding initiates further discussion and sets a problematization within this framework rethinking fundamental assumptions and epistemological issues.

  6. Substance Use Patterns Among Adolescents in Europe: A Latent Class Analysis.

    Science.gov (United States)

    Göbel, Kristin; Scheithauer, Herbert; Bräker, Astrid-Britta; Jonkman, Harrie; Soellner, Renate

    2016-07-28

    Several researchers have investigated substance use patterns using a latent class analysis; however, hardly no studies exist on substance use patterns across countries. Adolescent substance use patterns, demographic factors, and international differences in the prevalence of substance use patterns were explored. Data from 25 European countries were used to identify patterns of adolescent (12-16 years, 50.6% female) substance use (N = 33,566). Latent class analysis revealed four substance use classes: nonusers (68%), low-alcohol users (recent use of beer, wine, and alcopops; 16.1%), alcohol users (recent use of alcohol and lifetime use of marijuana; 11.2%), and polysubstance users (recent use of alcohol, marijuana, and other illicit drugs; 4.7%). Results support a general pattern of adolescent substance use across all countries; however, the prevalence rates of use patterns vary for each country. The present research provides insight into substance use patterns across Europe by using a large international adolescent sample, multidimensional indicators and a variety of substances. Substance use patterns are helpful when targeting policy and prevention strategies.

  7. Latent profile analysis and comorbidity in a sample of individuals with compulsive buying disorder.

    Science.gov (United States)

    Mueller, Astrid; Mitchell, James E; Black, Donald W; Crosby, Ross D; Berg, Kelly; de Zwaan, Martina

    2010-07-30

    The aims of this study were to perform a latent profile analysis in a sample of individuals with compulsive buying, to explore the psychiatric comorbidity, and to examine whether or not more severe compulsive buying is associated with greater comorbidity. Compulsive buying measures and SCID data obtained from 171 patients with compulsive buying behavior who had participated in treatment trials at different clinical centers in the U.S. and Germany were analyzed. Latent profile analysis produced two clusters. Overall, cluster 2, included subjects with more severe compulsive buying, and was characterized by higher lifetime as well as current prevalence rates for Axis I and impulse control disorders. Nearly 90% of the total sample reported at least one lifetime Axis I diagnosis, particularly mood (74%) and anxiety (57%) disorders. Twenty-one percent had a comorbid impulse control disorder, most commonly intermittent explosive disorder (11%). Half of the sample presented with at least one current Axis I disorder, most commonly anxiety disorders (44%). Given the substantial psychiatric comorbidity, it is reasonable to question whether or not compulsive buying represents a distinct psychiatric entity vs. an epiphenomenon of other psychiatric disorders. Copyright 2010 Elsevier Ltd. All rights reserved.

  8. Latent profile analysis of neuropsychological measures to determine preschoolers' risk for ADHD.

    Science.gov (United States)

    Rajendran, Khushmand; O'Neill, Sarah; Marks, David J; Halperin, Jeffrey M

    2015-09-01

    Hyperactive/Inattentive preschool children show clear evidence of neuropsychological dysfunction. We examined whether patterns and severity of test scores could reliably identify subgroups of preschoolers with differential risk for ADHD during school-age. Typically developing (TD: n = 76) and Hyperactive/Inattentive (HI: n = 138) 3-4 year olds were assessed annually for 6 years (T1-T6). Latent profile analysis (LPA) was used to form subgroups among the HI group based on objective/neuropsychological measures (NEPSY, Actigraph and Continuous Performance Test). Logistic regression assessed the predictive validity of empirically formed subgroups at risk for ADHD diagnosis relative to the TD group and to each other from T2 to T6. Latent profile analysis yielded two subgroups of HI preschoolers: (a) selectively weak Attention/Executive functions, and (b) pervasive neuropsychological dysfunction across all measures. Both subgroups were more likely to have ADHD at all follow-up time-points relative to the TD group (OR range: 11.29-86.32), but there were no significant differences between the LPA-formed subgroups of HI children at any time-point. Objective/neuropsychological measures distinguish HI preschoolers from their TD peers, but patterns and severity of neuropsychological dysfunction do not predict risk for ADHD during school-age. We hypothesize that trajectories in at-risk children are influenced by subsequent environmental and neurodevelopmental factors, raising the possibility that they are amenable to early intervention. © 2015 Association for Child and Adolescent Mental Health.

  9. Bayesian Analysis for Dynamic Generalized Linear Latent Model with Application to Tree Survival Rate

    Directory of Open Access Journals (Sweden)

    Yu-sheng Cheng

    2014-01-01

    Full Text Available Logistic regression model is the most popular regression technique, available for modeling categorical data especially for dichotomous variables. Classic logistic regression model is typically used to interpret relationship between response variables and explanatory variables. However, in real applications, most data sets are collected in follow-up, which leads to the temporal correlation among the data. In order to characterize the different variables correlations, a new method about the latent variables is introduced in this study. At the same time, the latent variables about AR (1 model are used to depict time dependence. In the framework of Bayesian analysis, parameters estimates and statistical inferences are carried out via Gibbs sampler with Metropolis-Hastings (MH algorithm. Model comparison, based on the Bayes factor, and forecasting/smoothing of the survival rate of the tree are established. A simulation study is conducted to assess the performance of the proposed method and a pika data set is analyzed to illustrate the real application. Since Bayes factor approaches vary significantly, efficiency tests have been performed in order to decide which solution provides a better tool for the analysis of real relational data sets.

  10. Beyond the ridge pattern: multi-informative analysis of latent fingermarks by MALDI mass spectrometry.

    Science.gov (United States)

    Francese, S; Bradshaw, R; Ferguson, L S; Wolstenholme, R; Clench, M R; Bleay, S

    2013-08-07

    After over a century, fingerprints are still one of the most powerful means of biometric identification. The conventional forensic workflow for suspect identification consists of (i) recovering latent marks from crime scenes using the appropriate enhancement technique and (ii) obtaining an image of the mark to compare either against known suspect prints and/or to search in a Fingerprint Database. The suspect is identified through matching the ridge pattern and local characteristics of the ridge pattern (minutiae). However successful, there are a number of scenarios in which this process may fail; they include the recovery of partial, distorted or smudged marks, poor quality of the image resulting from inadequacy of the enhancement technique applied, extensive scarring/abrasion of the fingertips or absence of suspect's fingerprint records in the database. In all of these instances it would be very desirable to have a technology able to provide additional information from a fingermark exploiting its endogenous and exogenous chemical content. This opportunity could potentially provide new investigative leads, especially when the fingermark comparison and match process fails. We have demonstrated that Matrix Assisted Laser Desorption Ionisation Mass Spectrometry and Mass Spectrometry Imaging (MALDI MSI) can provide multiple images of the same fingermark in one analysis simultaneous with additional intelligence. Here, a review on the pioneering use and development of MALDI MSI for the analysis of latent fingermarks is presented along with the latest achievements on the forensic intelligence retrievable.

  11. Perceived stress latent factors and the burnout subtypes: a structural model in dental students.

    Science.gov (United States)

    Montero-Marín, Jesús; Piva Demarzo, Marcelo Marcos; Stapinski, Lexine; Gili, Margarita; García-Campayo, Javier

    2014-01-01

    Students of health-professions suffer high levels of stress and burnout. The aim of the present study was to evaluate the relationship between perceived stress latent factors ('tenseness' and 'frustration') and the features ('overload', 'lack of development' and 'neglect') of the three burnout subtypes ('frenetic', 'under-challenged' and 'worn-out', respectively), in a sample of Spanish dental students. The study employed a cross-sectional design. A sample of Spanish dental students (n = 314) completed the 'Perceived Stress Questionnaire' and the 'Burnout Clinical Subtype Questionnaire Student Survey'. The associations among variables were observed by means of structural equation modelling using the unweighted least squares method from polychoric correlations. Strong associations among perceived stress factors and the burnout characteristics were observed, although a distinct pattern of relations was observed for each burnout subtype. The 'overload' was moderately and positively associated with both 'tenseness' (0.45), and 'frustration' (0.38) dimensions of perceived stress; the 'lack of development' was positively associated with the 'frustration' dimension (0.72), but negatively associated with 'tenseness' (-0.69); the 'neglect' showed a weaker positive associated with 'frustration' (0.41), and a small negative association with 'tenseness' (-0.20). The model was a very good fit to the data (GFI  =  0.96; RSMR  =  0.07; AGFI = 0.96; NFI = 0.95; RFI = 0.95). The stress factors of 'frustration' and 'tenseness' seems to be related in a distinct way to the burnout subtypes in Spanish dental students. This finding suggests that intervention programs specifically tailored to these subtypes may be a promising future direction.

  12. Perceived stress latent factors and the burnout subtypes: a structural model in dental students.

    Directory of Open Access Journals (Sweden)

    Jesús Montero-Marín

    Full Text Available Students of health-professions suffer high levels of stress and burnout. The aim of the present study was to evaluate the relationship between perceived stress latent factors ('tenseness' and 'frustration' and the features ('overload', 'lack of development' and 'neglect' of the three burnout subtypes ('frenetic', 'under-challenged' and 'worn-out', respectively, in a sample of Spanish dental students.The study employed a cross-sectional design. A sample of Spanish dental students (n = 314 completed the 'Perceived Stress Questionnaire' and the 'Burnout Clinical Subtype Questionnaire Student Survey'. The associations among variables were observed by means of structural equation modelling using the unweighted least squares method from polychoric correlations.Strong associations among perceived stress factors and the burnout characteristics were observed, although a distinct pattern of relations was observed for each burnout subtype. The 'overload' was moderately and positively associated with both 'tenseness' (0.45, and 'frustration' (0.38 dimensions of perceived stress; the 'lack of development' was positively associated with the 'frustration' dimension (0.72, but negatively associated with 'tenseness' (-0.69; the 'neglect' showed a weaker positive associated with 'frustration' (0.41, and a small negative association with 'tenseness' (-0.20. The model was a very good fit to the data (GFI  =  0.96; RSMR  =  0.07; AGFI = 0.96; NFI = 0.95; RFI = 0.95.The stress factors of 'frustration' and 'tenseness' seems to be related in a distinct way to the burnout subtypes in Spanish dental students. This finding suggests that intervention programs specifically tailored to these subtypes may be a promising future direction.

  13. Statistical analysis of latent generalized correlation matrix estimation in transelliptical distribution.

    Science.gov (United States)

    Han, Fang; Liu, Han

    2017-02-01

    Correlation matrix plays a key role in many multivariate methods (e.g., graphical model estimation and factor analysis). The current state-of-the-art in estimating large correlation matrices focuses on the use of Pearson's sample correlation matrix. Although Pearson's sample correlation matrix enjoys various good properties under Gaussian models, its not an effective estimator when facing heavy-tail distributions with possible outliers. As a robust alternative, Han and Liu (2013b) advocated the use of a transformed version of the Kendall's tau sample correlation matrix in estimating high dimensional latent generalized correlation matrix under the transelliptical distribution family (or elliptical copula). The transelliptical family assumes that after unspecified marginal monotone transformations, the data follow an elliptical distribution. In this paper, we study the theoretical properties of the Kendall's tau sample correlation matrix and its transformed version proposed in Han and Liu (2013b) for estimating the population Kendall's tau correlation matrix and the latent Pearson's correlation matrix under both spectral and restricted spectral norms. With regard to the spectral norm, we highlight the role of "effective rank" in quantifying the rate of convergence. With regard to the restricted spectral norm, we for the first time present a "sign subgaussian condition" which is sufficient to guarantee that the rank-based correlation matrix estimator attains the optimal rate of convergence. In both cases, we do not need any moment condition.

  14. The intersectionality of discrimination attributes and bullying among youth: an applied latent class analysis.

    Science.gov (United States)

    Garnett, Bernice Raveche; Masyn, Katherine E; Austin, S Bryn; Miller, Matthew; Williams, David R; Viswanath, Kasisomayajula

    2014-08-01

    Discrimination is commonly experienced among adolescents. However, little is known about the intersection of multiple attributes of discrimination and bullying. We used a latent class analysis (LCA) to illustrate the intersections of discrimination attributes and bullying, and to assess the associations of LCA membership to depressive symptoms, deliberate self harm and suicidal ideation among a sample of ethnically diverse adolescents. The data come from the 2006 Boston Youth Survey where students were asked whether they had experienced discrimination based on four attributes: race/ethnicity, immigration status, perceived sexual orientation and weight. They were also asked whether they had been bullied or assaulted for these attributes. A total of 965 (78%) students contributed to the LCA analytic sample (45% Non-Hispanic Black, 29% Hispanic, 58% Female). The LCA revealed that a 4-class solution had adequate relative and absolute fit. The 4-classes were characterized as: low discrimination (51%); racial discrimination (33%); sexual orientation discrimination (7%); racial and weight discrimination with high bullying (intersectional class) (7%). In multivariate models, compared to the low discrimination class, individuals in the sexual orientation discrimination class and the intersectional class had higher odds of engaging in deliberate self-harm. Students in the intersectional class also had higher odds of suicidal ideation. All three discrimination latent classes had significantly higher depressive symptoms compared to the low discrimination class. Multiple attributes of discrimination and bullying co-occur among adolescents. Research should consider the co-occurrence of bullying and discrimination.

  15. Consumption Patterns of Nightlife Attendees in Munich: A Latent-Class Analysis.

    Science.gov (United States)

    Hannemann, Tessa-Virginia; Kraus, Ludwig; Piontek, Daniela

    2017-09-19

    The affinity for substance use among patrons of nightclubs has been well established. With novel psychoactive substances (NPS) quickly emerging on the European drug market, trends, and patterns of use are potentially changing. (1) The detection of subgroups of consumers in the electronic dance music scene of a major German metropolitan city, (2) describing the consumption patterns of these subgroups, (3) exploring the prevalence and type of NPS consumption in this population at nightlife events in Munich. A total of 1571 patrons answered questions regarding their own substance use and the emergence of NPS as well as their experience with these substances. A latent class analysis was employed to detect consumption patterns within the sample. A four class model was determined reflecting different consumption patterns: the conservative class (34.9%) whose substance was limited to cannabis; the traditional class (36.6%) which especially consumed traditional club drugs; the psychedelic class (17.5%) which, in addition to traditional club drugs also consumed psychedelic drugs; and an unselective class (10.9%) which displayed the greatest likelihood of consumption of all assessed drugs. "Smoking mixtures" and methylone were the new substances mentioned most often, the number of substances mentioned differed between latent classes. Specific strategies are needed to reduce harm in those displaying the riskiest substance use. Although NPS use is still a fringe phenomenon its prevalence is greater in this subpopulation than in the general population, especially among users in the high-risk unselective class.

  16. Latent class models for joint analysis of disease prevalence and high-dimensional semicontinuous biomarker data.

    Science.gov (United States)

    Zhang, Bo; Chen, Zhen; Albert, Paul S

    2012-01-01

    High-dimensional biomarker data are often collected in epidemiological studies when assessing the association between biomarkers and human disease is of interest. We develop a latent class modeling approach for joint analysis of high-dimensional semicontinuous biomarker data and a binary disease outcome. To model the relationship between complex biomarker expression patterns and disease risk, we use latent risk classes to link the 2 modeling components. We characterize complex biomarker-specific differences through biomarker-specific random effects, so that different biomarkers can have different baseline (low-risk) values as well as different between-class differences. The proposed approach also accommodates data features that are common in environmental toxicology and other biomarker exposure data, including a large number of biomarkers, numerous zero values, and complex mean-variance relationship in the biomarkers levels. A Monte Carlo EM (MCEM) algorithm is proposed for parameter estimation. Both the MCEM algorithm and model selection procedures are shown to work well in simulations and applications. In applying the proposed approach to an epidemiological study that examined the relationship between environmental polychlorinated biphenyl (PCB) exposure and the risk of endometriosis, we identified a highly significant overall effect of PCB concentrations on the risk of endometriosis.

  17. Job satisfaction among Australian doctors: the use of latent class analysis.

    Science.gov (United States)

    Joyce, Catherine; Wang, Wei Chun

    2015-10-01

    To identify patterns of job satisfaction among Australian doctors using latent class analysis, and to determine the relationships of these patterns to personal and professional characteristics so as to improve satisfaction and minimize medical wastage. MABEL (Medicine in Australia: Balancing Employment and Life) data in 2011 were used. The study collected information on 5764 doctors about their job satisfaction, demographic characteristics, their health, country of medical training, opportunities for professional development and social interaction, taking time off work, views of patients' expectations, unpredictable working hours, hours worked per week, preference to reduce hours and intention to leave the medical workforce. Four latent classes of job satisfaction were identified: 5.8% had high job satisfaction; 19.4% had low satisfaction with working hours; 16.1% had high satisfaction with working hours but felt undervalued; and 6.5% had low job satisfaction. Low job satisfaction was associated with reporting poor health, having trained outside Australia, having poor opportunities for professional development and working longer hours. Low satisfaction was associated with a preference to reduce work hours and an intention to leave the medical workforce. To improve job satisfaction and minimize medical wastage, policies need to address needs of overseas trained doctors, provide continuing professional development and provide good health care for doctors. © The Author(s) 2015.

  18. a Latent Variable Path Analysis Model of Secondary Physics Enrollments in New York State.

    Science.gov (United States)

    Sobolewski, Stanley John

    The Percentage of Enrollment in Physics (PEP) at the secondary level nationally has been approximately 20% for the past few decades. For a more scientifically literate citizenry as well as specialists to continue scientific research and development, it is desirable that more students enroll in physics. Some of the predictor variables for physics enrollment and physics achievement that have been identified previously includes a community's socioeconomic status, the availability of physics, the sex of the student, the curriculum, as well as teacher and student data. This study isolated and identified predictor variables for PEP of secondary schools in New York. Data gathered by the State Education Department for the 1990-1991 school year was used. The source of this data included surveys completed by teachers and administrators on student characteristics and school facilities. A data analysis similar to that done by Bryant (1974) was conducted to determine if the relationships between a set of predictor variables related to physics enrollment had changed in the past 20 years. Variables which were isolated included: community, facilities, teacher experience, number of type of science courses, school size and school science facilities. When these variables were isolated, latent variable path diagrams were proposed and verified by the Linear Structural Relations computer modeling program (LISREL). These diagrams differed from those developed by Bryant in that there were more manifest variables used which included achievement scores in the form of Regents exam results. Two criterion variables were used, percentage of students enrolled in physics (PEP) and percent of students enrolled passing the Regents physics exam (PPP). The first model treated school and community level variables as exogenous while the second model treated only the community level variables as exogenous. The goodness of fit indices for the models was 0.77 for the first model and 0.83 for the second

  19. Towards a typology of business process management professionals: identifying patterns of competences through latent semantic analysis

    Science.gov (United States)

    Müller, Oliver; Schmiedel, Theresa; Gorbacheva, Elena; vom Brocke, Jan

    2016-01-01

    While researchers have analysed the organisational competences that are required for successful Business Process Management (BPM) initiatives, individual BPM competences have not yet been studied in detail. In this study, latent semantic analysis is used to examine a collection of 1507 BPM-related job advertisements in order to develop a typology of BPM professionals. This empirical analysis reveals distinct ideal types and profiles of BPM professionals on several levels of abstraction. A closer look at these ideal types and profiles confirms that BPM is a boundary-spanning field that requires interdisciplinary sets of competence that range from technical competences to business and systems competences. Based on the study's findings, it is posited that individual and organisational alignment with the identified ideal types and profiles is likely to result in high employability and organisational BPM success.

  20. Functional Status, Quality of Life, and Costs Associated With Fibromyalgia Subgroups: A Latent Profile Analysis.

    Science.gov (United States)

    Luciano, Juan V; Forero, Carlos G; Cerdà-Lafont, Marta; Peñarrubia-María, María Teresa; Fernández-Vergel, Rita; Cuesta-Vargas, Antonio I; Ruíz, José M; Rozadilla-Sacanell, Antoni; Sirvent-Alierta, Elena; Santo-Panero, Pilar; García-Campayo, Javier; Serrano-Blanco, Antoni; Pérez-Aranda, Adrián; Rubio-Valera, María

    2016-10-01

    Although fibromyalgia syndrome (FM) is considered a heterogeneous condition, there is no generally accepted subgroup typology. We used hierarchical cluster analysis and latent profile analysis to replicate Giesecke's classification in Spanish FM patients. The second aim was to examine whether the subgroups differed in sociodemographic characteristics, functional status, quality of life, and in direct and indirect costs. A total of 160 FM patients completed the following measures for cluster derivation: the Center for Epidemiological Studies-Depression Scale, the Trait Anxiety Inventory, the Pain Catastrophizing Scale, and the Control over Pain subscale. Pain threshold was measured with a sphygmomanometer. In addition, the Fibromyalgia Impact Questionnaire-Revised, the EuroQoL-5D-3L, and the Client Service Receipt Inventory were administered for cluster validation. Two distinct clusters were identified using hierarchical cluster analysis ("hypersensitive" group, 69.8% and "functional" group, 30.2%). In contrast, the latent profile analysis goodness-of-fit indices supported the existence of 3 FM patient profiles: (1) a "functional" profile (28.1%) defined as moderate tenderness, distress, and pain catastrophizing; (2) a "dysfunctional" profile (45.6%) defined by elevated tenderness, distress, and pain catastrophizing; and (3) a "highly dysfunctional and distressed" profile (26.3%) characterized by elevated tenderness and extremely high distress and catastrophizing. We did not find significant differences in sociodemographic characteristics between the 2 clusters or among the 3 profiles. The functional profile was associated with less impairment, greater quality of life, and lower health care costs. We identified 3 distinct profiles which accounted for the heterogeneity of FM patients. Our findings might help to design tailored interventions for FM patients.

  1. A systematic literature review of PTSD's latent structure in the Diagnostic and Statistical Manual of Mental Disorders: DSM-IV to DSM-5.

    Science.gov (United States)

    Armour, Cherie; Műllerová, Jana; Elhai, Jon D

    2016-03-01

    The factor structure of posttraumatic stress disorder (PTSD) has been widely researched, but consensus regarding the exact number and nature of factors is yet to be reached. The aim of the current study was to systematically review the extant literature on PTSD's latent structure in the Diagnostic and Statistical Manual of Mental Disorders (DSM) in order to identify the best-fitting model. One hundred and twelve research papers published after 1994 using confirmatory factor analysis and DSM-based measures of PTSD were included in the review. In the DSM-IV literature, four-factor models received substantial support, but the five-factor Dysphoric arousal model demonstrated the best fit, regardless of gender, measurement instrument or trauma type. The recently proposed DSM-5 PTSD model was found to be a good representation of PTSD's latent structure, but studies analysing the six- and seven-factor models suggest that the DSM-5 PTSD factor structure may need further alterations. Copyright © 2015 Elsevier Ltd. All rights reserved.

  2. Latent class analysis derived subgroups of low back pain patients - do they have prognostic capacity?

    Science.gov (United States)

    Molgaard Nielsen, Anne; Hestbaek, Lise; Vach, Werner; Kent, Peter; Kongsted, Alice

    2017-08-09

    Heterogeneity in patients with low back pain is well recognised and different approaches to subgrouping have been proposed. One statistical technique that is increasingly being used is Latent Class Analysis as it performs subgrouping based on pattern recognition with high accuracy. Previously, we developed two novel suggestions for subgrouping patients with low back pain based on Latent Class Analysis of patient baseline characteristics (patient history and physical examination), which resulted in 7 subgroups when using a single-stage analysis, and 9 subgroups when using a two-stage approach. However, their prognostic capacity was unexplored. This study (i) determined whether the subgrouping approaches were associated with the future outcomes of pain intensity, pain frequency and disability, (ii) assessed whether one of these two approaches was more strongly or more consistently associated with these outcomes, and (iii) assessed the performance of the novel subgroupings as compared to the following variables: two existing subgrouping tools (STarT Back Tool and Quebec Task Force classification), four baseline characteristics and a group of previously identified domain-specific patient categorisations (collectively, the 'comparator variables'). This was a longitudinal cohort study of 928 patients consulting for low back pain in primary care. The associations between each subgroup approach and outcomes at 2 weeks, 3 and 12 months, and with weekly SMS responses were tested in linear regression models, and their prognostic capacity (variance explained) was compared to that of the comparator variables listed above. The two previously identified subgroupings were similarly associated with all outcomes. The prognostic capacity of both subgroupings was better than that of the comparator variables, except for participants' recovery beliefs and the domain-specific categorisations, but was still limited. The explained variance ranged from 4.3%-6.9% for pain intensity and

  3. The Latent Structure of Child Depression: A Taxometric Analysis

    Science.gov (United States)

    Richey, J. Anthony; Schmidt, Norman B.; Lonigan, Christopher J.; Phillips, Beth M.; Catanzaro, Salvatore J.; Laurent, Jeff; Gerhardstein, Rebecca R.; Kotov, Roman

    2009-01-01

    Background: The current study examined the categorical versus continuous nature of child and adolescent depression among three samples of children and adolescents ranging from 5 to 19 years. Methods: Depression was measured using the Children's Depression Inventory (CDI). Indicators derived from the CDI were based on factor analytic research on…

  4. Dissociative Experiences are Associated with Obsessive-Compulsive Symptoms in a Non-clinical Sample: A Latent Profile Analysis

    Science.gov (United States)

    BOYSAN, Murat

    2014-01-01

    Introduction There has been a burgeoning literature considering the significant associations between obsessive-compulsive symptoms and dissociative experiences. In this study, the relationsips between dissociative symtomotology and dimensions of obsessive-compulsive symptoms were examined in homogeneous sub-groups obtained with latent class algorithm in an undergraduate Turkish sample. Method Latent profile analysis, a recently developed classification method based on latent class analysis, was applied to the Dissociative Experiences Scale (DES) item-response data from 2976 undergraduates. Differences in severity of obsessive-compulsive symptoms, anxiety and depression across groups were evaluated by running multinomial logistic regression analyses. Associations between latent class probabilities and psychological variables in terms of obsessive-compulsive sub-types, anxiety, and depression were assessed by computing Pearson’s product-moment correlation coefficients. Results The findings of the latent profile analysis supported further evidence for discontinuity model of dissociative experiences. The analysis empirically justified the distinction among three sub-groups based on the DES items. A marked proportion of the sample (42%) was assigned to the high dissociative class. In the further analyses, all sub-types of obsessive-compulsive symptoms significantly differed across latent classes. Regarding the relationships between obsessive-compulsive symptoms and dissociative symptomatology, low dissociation appeared to be a buffering factor dealing with obsessive-compulsive symptoms; whereas high dissociation appeared to be significantly associated with high levels of obsessive-compulsive symptoms. Conclusion It is concluded that the concept of dissociation can be best understood in a typological approach that dissociative symptomatology not only exacerbates obsessive-compulsive symptoms but also serves as an adaptive coping mechanism. PMID:28360635

  5. Automatic Evaluation for E-Learning Using Latent Semantic Analysis: A Use Case

    Directory of Open Access Journals (Sweden)

    Mireia Farrús

    2013-03-01

    Full Text Available Assessment in education allows for obtaining, organizing, and presenting information about how much and how well the student is learning. The current paper aims at analysing and discussing some of the most state-of-the-art assessment systems in education. Later, this work presents a specific use case developed for the Universitat Oberta de Catalunya, which is an online university. An automatic evaluation tool is proposed that allows the student to evaluate himself anytime and receive instant feedback. This tool is a web-based platform, and it has been designed for engineering subjects (i.e., with math symbols and formulas in Catalan and Spanish. Particularly, the technique used for automatic assessment is latent semantic analysis. Although the experimental framework from the use case is quite challenging, results are promising.

  6. Identifying classes of persons with mild intellectual disability or borderline intellectual functioning: a latent class analysis.

    Science.gov (United States)

    Nouwens, Peter J G; Lucas, Rosanne; Smulders, Nienke B M; Embregts, Petri J C M; van Nieuwenhuizen, Chijs

    2017-07-17

    Persons with mild intellectual disability or borderline intellectual functioning are often studied as a single group with similar characteristics. However, there are indications that differences exist within this population. Therefore, the aim of this study was to identify classes of persons with mild intellectual disability or borderline intellectual functioning and to examine whether these classes are related to individual and/or environmental characteristics. Latent class analysis was performed using file data of 250 eligible participants with a mean age of 26.1 (SD 13.8, range 3-70) years. Five distinct classes of persons with mild intellectual disability or borderline intellectual functioning were found. These classes significantly differed in individual and environmental characteristics. For example, persons with a mild intellectual disability experienced fewer problems than those with borderline intellectual disability. The identification of five classes implies that a differentiated approach is required towards persons with mild intellectual disability or borderline intellectual functioning.

  7. Discrete response patterns in the upper range of hypnotic suggestibility: A latent profile analysis.

    Science.gov (United States)

    Terhune, Devin Blair

    2015-05-01

    High hypnotic suggestibility is a heterogeneous condition and there is accumulating evidence that highly suggestible individuals may be comprised of discrete subtypes with dissimilar cognitive and phenomenological profiles. This study applied latent profile analysis to response patterns on a diverse battery of difficult hypnotic suggestions in a sample of individuals in the upper range of hypnotic suggestibility. Comparisons among models indicated that a four-class model was optimal. One class was comprised of very highly suggestible (virtuoso) participants, two classes included highly suggestible participants who were alternately more responsive to inhibitory cognitive suggestions or posthypnotic amnesia suggestions, and the fourth class consisted primarily of medium suggestible participants. These results indicate that there are discrete response profiles in high hypnotic suggestibility. They further provide a number of insights regarding the optimization of hypnotic suggestibility measurement and have implications for the instrumental use of hypnosis for the modeling of different psychological conditions. Copyright © 2015 Elsevier Inc. All rights reserved.

  8. Multiple murder and criminal careers: a latent class analysis of multiple homicide offenders.

    Science.gov (United States)

    Vaughn, Michael G; DeLisi, Matt; Beaver, Kevin M; Howard, Matthew O

    2009-01-10

    To construct an empirically rigorous typology of multiple homicide offenders (MHOs). The current study conducted latent class analysis of the official records of 160 MHOs sampled from eight states to evaluate their criminal careers. A 3-class solution best fit the data (-2LL=-1123.61, Bayesian Information Criterion (BIC)=2648.15, df=81, L(2)=1179.77). Class 1 (n=64, class assignment probability=.999) was the low-offending group marked by little criminal record and delayed arrest onset. Class 2 (n=51, class assignment probability=.957) was the severe group that represents the most violent and habitual criminals. Class 3 (n=45, class assignment probability=.959) was the moderate group whose offending careers were similar to Class 2. A sustained criminal career with involvement in versatile forms of crime was observed for two of three classes of MHOs. Linkages to extant typologies and recommendations for additional research that incorporates clinical constructs are proffered.

  9. A Latent Profile Analysis of Latino Parenting: The Infusion of Cultural Values on Family Conflict.

    Science.gov (United States)

    Ayón, Cecilia; Williams, Lela Rankin; Marsiglia, Flavio F; Ayers, Stephanie; Kiehne, Elizabeth

    The purpose of the present study was to (a) examine how acculturation and social support inform Latinos' parenting behaviors, controlling for gender and education; (b) describe parenting styles among Latino immigrants while accounting for cultural elements; and (c) test how these parenting styles are associated with family conflict. A 3 step latent profile analysis with the sample ( N = 489) revealed best fit with a 4 profile model ( n = 410) of parenting: family parenting ( n = 268, 65%), child-centered parenting ( n = 68, 17%), moderate parenting ( n = 60, 15%), and disciplinarian parenting ( n = 14, 3%). Parents' gender, acculturation, and social support significantly predicted profile membership. Disciplinarian and moderate parenting were associated with more family conflict. Recommendations include integrating culturally based parenting practices as a critical element to family interventions to minimize conflict and promote positive youth development.

  10. Discrete subgroups of adolescents diagnosed with borderline personality disorder: a latent class analysis of personality features.

    Science.gov (United States)

    Ramos, Vera; Canta, Guilherme; de Castro, Filipa; Leal, Isabel

    2014-08-01

    Research suggests that borderline personality disorder (BPD) can be diagnosed in adolescents and is marked by considerable heterogeneity. This study aimed to identify personality features characterizing adolescents with BPD and possible meaningful patterns of heterogeneity that could lead to personality subgroups. The authors analyzed data on 60 adolescents, ages 15 to 18 years, who met DSM criteria for a BPD diagnosis. The authors used latent class analysis (LCA) to identify subgroups based on the personality pattern scales from the Millon Adolescent Clinical Inventory (MACI). LCA indicated that the best-fitting solution was a two-class model, identifying two discrete subgroups of BPD adolescents that were described as internalizing and externalizing. The subgroups were then compared on clinical and sociodemographic variables, measures of personality dimensions, DSM BPD criteria, and perception of attachment styles. Adolescents with a BPD diagnosis constitute a heterogeneous group and vary meaningfully on personality features that can have clinical implications for treatment.

  11. Differences in environmental preferences towards cycling for transport among adults: a latent class analysis

    Directory of Open Access Journals (Sweden)

    Lieze Mertens

    2016-08-01

    Full Text Available Abstract Background Increasing cycling for transport can contribute to improve public health among adults. Micro-environmental factors (i.e. small-scaled street-setting features may play an important role in affecting the street’s appeal to cycle for transport. Understanding about the interplay between individuals and their physical environment is important to establish tailored environmental interventions. Therefore, the current study aimed to examine whether specific subgroups exist based on similarities in micro-environmental preferences to cycle for transport. Methods Responses of 1950 middle-aged adults (45–65 years on a series of choice tasks depicting potential cycling routes with manipulated photographs yielded three subgroups with different micro-environmental preferences using latent class analysis. Results Although latent class analysis revealed three different subgroups in the middle-aged adult population based on their environmental preferences, results indicated that cycle path type (i.e. a good separated cycle path is the most important environmental factor for all participants and certainly for individuals who did not cycle for transport. Furthermore, only negligible differences were found between the importances of the other micro-environmental factors (i.e. traffic density, evenness of the cycle path, maintenance, vegetation and speed limits regarding the two at risk subgroups and that providing a speed bump obviously has the least impact on the street’s appeal to cycle for transport. Conclusions Results from the current study indicate that only negligible differences were found between the three subgroups. Therefore, it might be suggested that tailored environmental interventions are not required in this research context.

  12. Differences in environmental preferences towards cycling for transport among adults: a latent class analysis.

    Science.gov (United States)

    Mertens, Lieze; Van Cauwenberg, Jelle; Ghekiere, Ariane; De Bourdeaudhuij, Ilse; Deforche, Benedicte; Van de Weghe, Nico; Van Dyck, Delfien

    2016-08-12

    Increasing cycling for transport can contribute to improve public health among adults. Micro-environmental factors (i.e. small-scaled street-setting features) may play an important role in affecting the street's appeal to cycle for transport. Understanding about the interplay between individuals and their physical environment is important to establish tailored environmental interventions. Therefore, the current study aimed to examine whether specific subgroups exist based on similarities in micro-environmental preferences to cycle for transport. Responses of 1950 middle-aged adults (45-65 years) on a series of choice tasks depicting potential cycling routes with manipulated photographs yielded three subgroups with different micro-environmental preferences using latent class analysis. Although latent class analysis revealed three different subgroups in the middle-aged adult population based on their environmental preferences, results indicated that cycle path type (i.e. a good separated cycle path) is the most important environmental factor for all participants and certainly for individuals who did not cycle for transport. Furthermore, only negligible differences were found between the importances of the other micro-environmental factors (i.e. traffic density, evenness of the cycle path, maintenance, vegetation and speed limits) regarding the two at risk subgroups and that providing a speed bump obviously has the least impact on the street's appeal to cycle for transport. Results from the current study indicate that only negligible differences were found between the three subgroups. Therefore, it might be suggested that tailored environmental interventions are not required in this research context.

  13. Parental attitudes towards measles vaccination in the canton of Aargau, Switzerland: a latent class analysis.

    Science.gov (United States)

    Weiss, Carine; Schröpfer, Daniel; Merten, Sonja

    2016-08-11

    Despite the successes of routine national childhood vaccination programmes, measles remains a public health concern. The purpose of this paper is to investigate how patterns of parental attitudes are linked to the decision-making process for or against MMR vaccination. This exploratory study was designed to identify distinct patterns of attitudes towards or against measles vaccination through Latent Class Analysis (LCA) in a sub-sample of mothers living in the canton of Aargau in Switzerland. Parents of young children below 36 months of age were randomly selected through parents' counsellors' registries. Among other questions, respondents were asked to state their agreement in response to 14 belief statements regarding measles vaccination on a 5-point Likert scale. To identify groups of parents showing distinct patterns of attitudes and beliefs regarding measles vaccination, we used Latent Class Analysis (LCA). The LCA showed three classes of parents with different attitudes and believes towards measles vaccination: The biggest group (class 1) are those having positive attitudes towards immunisation, followed by the second biggest group (class 2) which is characterised by having fearful attitudes and by showing uncertainty about immunisation. The third group (class 3) shows distinct patterns of critical attitudes against immunisation. Within this group over 90 % agree or totally agree that immunisation is an artificial intrusion into the natural immune system and therefore want to vaccinate their children only if necessary. We find that parents in the Canton Aargau who hesitate to vaccinate their children against measles, mumps and rubella show distinct opinions and attitudes. Health professionals should be aware of these perceptions to tailor their messages accordingly and positively influence these parents to vaccinate their children. Special attention needs to be given to those parents who are planning to vaccinate their children but are not following the

  14. Enhanced Thermal Properties of Novel Latent Heat Thermal Storage Material Through Confinement of Stearic Acid in Meso-Structured Onion-Like Silica

    Science.gov (United States)

    Gao, Junkai; Lv, Mengjiao; Lu, Jinshu; Chen, Yan; Zhang, Zijun; Zhang, Xiongjie; Zhu, Yingying

    2017-12-01

    Meso-structured onion-like silica (MOS), which had a highly ordered, onion-like multilayer; large surface area and pore volume; and highly curved mesopores, were synthesized as a support for stearic acid (SA) to develop a novel shape-stabilized phase change material (SA/MOS). The characterizations of SA/MOS were studied by the analysis technique of scanning electron microscope, infrared spectroscopy, x-ray diffraction, differential scanning calorimeter (DSC), and thermal gravimetry analysis (TGA). The results showed that the interaction between the SA and the MOS was physical adsorption and that the MOS had no effect on the crystal structure of the SA. The DSC results suggested that the melting and solidifying temperature of the SA/MOS were 72.7°C and 63.9°C with a melting latent heat of 108.0 J/g and a solidifying latent heat of 126.0 J/g, respectively, and the TGA results indicated that the SA/MOS had a good thermal stability. All of the results demonstrated that the SA/MOS was a promising thermal energy storage material candidate for practical applications.

  15. Profiles of adolescent religiousness using latent profile analysis: Implications for psychopathology.

    Science.gov (United States)

    Longo, Gregory S; Bray, Bethany C; Kim-Spoon, Jungmeen

    2017-03-01

    Prior research has documented robust associations between adolescent religiousness/spirituality (R/S) and psychopathology outcomes including externalizing and internalizing symptomatology, yet no previous studies have examined these associations with adolescent R/S profiles using a person-centred approach. We examined whether there are identifiable subgroups characterized by unique multidimensional patterns of R/S experiences and how these experiences may be related to externalizing and internalizing symptomatology. The sample consisted of 220 Appalachian adolescents between 12 and 18 years old who were primarily White and primarily Christian. Latent profile analysis revealed three profiles of adolescent R/S: high religiousness (28.4%), introjectors (47.6%), and low religiousness (24.0%). These profiles were differentially related to internalizing and externalizing symptomatology such that the high religiousness group was significantly lower than the introjectors with respect to internalizing and externalizing symptomatology and lower than the low religiousness group in externalizing symptomatology. Implications and suggestions for future research using person-centred approaches to better understand differential developmental trajectories of religious development are provided. Statement of contribution What is already known Prior research has demonstrated a negative relationship between adolescent religiousness and spirituality (R/S) and psychopathology. Numerous studies document the differential relationships between aspects of R/S and psychopathology; however, few have done so from a person-centred perspective. There are several theories that outline how R/S to study R/S when paying specific attention to culture. Saroglou's Big Four dimensions of religion (believing, bonding, behaving, and belonging) posits that these four dimensions (1) are able to delimit religion from proximal constructs; (2) translate major distinct dimensions of religiousness; (3) can be

  16. A Latent Class Regression Analysis of Men's Conformity to Masculine Norms and Psychological Distress

    Science.gov (United States)

    Wong, Y. Joel; Owen, Jesse; Shea, Munyi

    2012-01-01

    How are specific dimensions of masculinity related to psychological distress in specific groups of men? To address this question, the authors used latent class regression to assess the optimal number of latent classes that explained differential relationships between conformity to masculine norms and psychological distress in a racially diverse…

  17. Extending dynamic segmentation with lead generation : A latent class Markov analysis of financial product portfolios

    NARCIS (Netherlands)

    Paas, L.J.; Bijmolt, T.H.A.; Vermunt, J.K.

    2004-01-01

    A recent development in marketing research concerns the incorporation of dynamics in consumer segmentation.This paper extends the latent class Markov model, a suitable technique for conducting dynamic segmentation, in order to facilitate lead generation.We demonstrate the application of the latent

  18. Job Satisfaction among Health-Care Staff in Township Health Centers in Rural China: Results from a Latent Class Analysis

    OpenAIRE

    Haipeng Wang; Chengxiang Tang; Shichao Zhao; Qingyue Meng; Xiaoyun Liu

    2017-01-01

    Background: The lower job satisfaction of health-care staff will lead to more brain drain, worse work performance, and poorer health-care outcomes. The aim of this study was to identify patterns of job satisfaction among health-care staff in rural China, and to investigate the association between the latent clusters and health-care staff’s personal and professional features; Methods: We selected 12 items of five-point Likert scale questions to measure job satisfaction. A latent-class analysis...

  19. Latent class analysis of diagnostic science assessment data using Bayesian networks

    Science.gov (United States)

    Steedle, Jeffrey Thomas

    2008-10-01

    Diagnostic science assessments seek to draw inferences about student understanding by eliciting evidence about the mental models that underlie students' reasoning about physical systems. Measurement techniques for analyzing data from such assessments embody one of two contrasting assessment programs: learning progressions and facet-based assessments. Learning progressions assume that students have coherent theories that they apply systematically across different problem contexts. In contrast, the facet approach makes no such assumption, so students should not be expected to reason systematically across different problem contexts. A systematic comparison of these two approaches is of great practical value to assessment programs such as the National Assessment of Educational Progress as they seek to incorporate small clusters of related items in their tests for the purpose of measuring depth of understanding. This dissertation describes an investigation comparing learning progression and facet models. Data comprised student responses to small clusters of multiple-choice diagnostic science items focusing on narrow aspects of understanding of Newtonian mechanics. Latent class analysis was employed using Bayesian networks in order to model the relationship between students' science understanding and item responses. Separate models reflecting the assumptions of the learning progression and facet approaches were fit to the data. The technical qualities of inferences about student understanding resulting from the two models were compared in order to determine if either modeling approach was more appropriate. Specifically, models were compared on model-data fit, diagnostic reliability, diagnostic certainty, and predictive accuracy. In addition, the effects of test length were evaluated for both models in order to inform the number of items required to obtain adequately reliable latent class diagnoses. Lastly, changes in student understanding over time were studied with a

  20. poLCA: An R Package for Polytomous Variable Latent Class Analysis

    Directory of Open Access Journals (Sweden)

    Drew A. Linzer

    2011-08-01

    Full Text Available poLCA is a software package for the estimation of latent class and latent class regression models for polytomous outcome variables, implemented in the R statistical computing environment. Both models can be called using a single simple command line. The basic latent class model is a finite mixture model in which the component distributions are assumed to be multi-way cross-classification tables with all variables mutually independent. The latent class regression model further enables the researcher to estimate the effects of covariates on predicting latent class membership. poLCA uses expectation-maximization and Newton-Raphson algorithms to find maximum likelihood estimates of the model parameters.

  1. Patterns of victimization, suicide attempt, and posttraumatic stress disorder in Greenlandic adolescents: a latent class analysis.

    Science.gov (United States)

    Karsberg, Sidsel; Armour, Cherie; Elklit, Ask

    2014-09-01

    The current study had two main aims. The first was to identify groups of adolescents based on their similarity of responding across a number of victimizing and potentially traumatic events (PTEs). In doing so, we employed the statistical technique of Latent Class Analysis (LCA). The second aim was to assess the relationship between our resultant classes and the covariates of gender, suicide attempt, and PTSD. Two hundred and sixty-nine Greenlandic school students, aged 12-18 (M = 15.4, SD = 1.84) were assessed for their level of exposure to PTEs. In addition, adolescents were assessed for the psychological impact of these events. A LCA was performed on seven binary indicators representing PTEs. Logistic regression was subsequently implemented to ascertain the relationships between latent classes and covariates. Three distinct classes were uncovered: a violence, neglect, and bullying class (class 1), a wide-ranging multiple PTE class (class 2), and a normative/baseline class (class 3). Notably, classes 1 and 2 were largely separated by the presence or absence of sexual PTEs. Individuals who reported having previously attempted suicide were almost six times more likely to be members of class 1 (OR = 5.97) and almost four times more likely to be members of class 2 (OR = 3.87) compared to the baseline class (class 3). Individuals who met the diagnostic criteria for PTSD were five times as likely to be members of class 1 and class 2 (OR = 5.09) compared to the baseline class. No significant associations were found between classes and gender. The results underline the complexity of the interplay between multiple victimization experiences, traumatization, and suicide attempts.

  2. Latent class analysis of eating and impulsive behavioral symptoms in Taiwanese women with bulimia nervosa.

    Science.gov (United States)

    Tseng, Mei-Chih Meg; Hu, Fu-Chang

    2012-01-01

    The implications of impulsivity in its relationship with binge-eating or purging behaviors remain unclear. This study examined the patterns of eating behaviors and co-morbid impulsive behaviors in individuals with bulimia nervosa n optimally homogeneous classes using latent class analysis (LCA). All participants (n=180) were asked to complete a series of self-reported inventories of impulsive behaviors and other psychological measures. Information regarding the lifetime presence of symptoms of eating disorder was assessed by clinical interviews. LCA was conducted using eating disorder symptoms, impulsive behaviors, and the number of purging methods. Three latent classes of bulimic women were identified. These were women who exhibited relatively higher rates of purging, symptoms of impulsive behavior, and multiple purging methods (17.8%), women who used no more than one purging method with a low occurrence of impulsive behavior (41.7%), and women who showed higher rates of purging behaviors and the use of multiple purging methods with a low rate of impulsive behavior (41.7%). The impulsive sub-group had comparable severity of eating-related measures, frequency of binge-eating, and higher levels of general psychopathology than that of the other two sub-groups. This study provides empirical support for the existence of an impulsive subgroup with distinctive features among a non-Western group of BN patients. This study also suggests that mechanisms other than impulse dysregulation may exist for the development of binge-eating and purging behaviors in bulimia nervosa patients, or the mechanisms contributing to binge-eating and impulsive behaviors may be different. Copyright © 2011 Elsevier Inc. All rights reserved.

  3. Cost and performance analysis of concentrating solar power systems with integrated latent thermal energy storage

    International Nuclear Information System (INIS)

    Nithyanandam, K.; Pitchumani, R.

    2014-01-01

    Integrating TES (thermal energy storage) in a CSP (concentrating solar power) plant allows for continuous operation even during times when solar irradiation is not available, thus providing a reliable output to the grid. In the present study, the cost and performance models of an EPCM-TES (encapsulated phase change material thermal energy storage) system and HP-TES (latent thermal storage system with embedded heat pipes) are integrated with a CSP power tower system model utilizing Rankine and s-CO 2 (supercritical carbon-dioxide) power conversion cycles, to investigate the dynamic TES-integrated plant performance. The influence of design parameters of the storage system on the performance of a 200 MW e capacity power tower CSP plant is studied to establish design envelopes that satisfy the U.S. Department of Energy SunShot Initiative requirements, which include a round-trip annualized exergetic efficiency greater than 95%, storage cost less than $15/kWh t and LCE (levelized cost of electricity) less than 6 ¢/kWh. From the design windows, optimum designs of the storage system based on minimum LCE, maximum exergetic efficiency, and maximum capacity factor are reported and compared with the results of two-tank molten salt storage system. Overall, the study presents the first effort to construct and analyze LTES (latent thermal energy storage) integrated CSP plant performance that can help assess the impact, cost and performance of LTES systems on power generation from molten salt power tower CSP plant. - Highlights: • Presents technoeconomic analysis of thermal energy storage integrated concentrating solar power plants. • Presents a comparison of different storage options. • Presents optimum design of thermal energy storage system for steam Rankine and supercritical carbon dioxide cycles. • Presents designs for maximizing exergetic efficiency while minimizing storage cost and levelized cost of energy

  4. Subgrouping of risky behaviors among Iranian college students: a latent class analysis

    Science.gov (United States)

    Safiri, Saeid; Rahimi-Movaghar, Afarin; Yunesian, Masud; Sadeghi-Bazargani, Homayoun; Shamsipour, Mansour; Mansournia, Mohammad Ali; Fotouhi, Akbar

    2016-01-01

    Background Risky behaviors may interrupt development or cause considerable morbidity or mortality. This study’s purpose was to determine subgroups of students based on risky behaviors and assess the prevalence of risky behaviors in each of the subgroups. Participants and methods This anonymous cross-sectional study was carried out in October 2015 and November 2015, with 1,777 students from Tabriz University of Medical Sciences, through multistage random sampling method. The data were analyzed by latent class analysis. Results The prevalence rates of cigarette smoking (more than or equal to ten cigarettes), hookah use (≥1 time/month), and alcohol consumption (≥1 time/month) during the last year were 12.4% (95% confidence interval [CI]: 10.9–14.0), 11.6% (95% CI: 10.0–13.1), and 4.9% (95% CI: 3.8–5.9), respectively. The prevalence rates of illicit opioids (1.8%, 95% CI: 1.2–2.5), cannabis (1.2%, 95% CI: 0.7–1.7), methamphetamine (1.1%, 95% CI: 0.6–1.6), methylphenidate (2.5%, 95% CI: 1.7–3.2), and extramarital sex (5.5%, 95% CI: 4.5–6.6) over the last year were also estimated. Three latent classes were determined: 1) low risk; 2) cigarette and hookah smoker; and 3) high risk. It is worth mentioning that 3.7% of males and 0.4% of females were in the high risk group. Conclusion Subgrouping of college students showed that a considerable percentage of them, especially males, were classified into the high risk and cigarette and hookah smoker groups. Appropriate preventive measures that consider multiple different risky behaviors simultaneously are needed for this part of the population. PMID:27524898

  5. Latent profile analysis of sixth graders based on teacher ratings: Association with school dropout.

    Science.gov (United States)

    Orpinas, Pamela; Raczynski, Katherine; Peters, Jaclyn Wetherington; Colman, Laura; Bandalos, Deborah

    2015-12-01

    The goal of this study was to identify meaningful groups of sixth graders with common characteristics based on teacher ratings of assets and maladaptive behaviors, describe dropout rates for each group, and examine the validity of these groups using students' self-reports. The sample consisted of racially diverse students (n = 675) attending sixth grade in public schools in Northeast Georgia. The majority of the sample was randomly selected; a smaller group was identified by teachers as high risk for aggression. Based on teacher ratings of externalizing behaviors, internalizing problems, academic skills, leadership, and social assets, latent profile analysis yielded 7 classes that can be displayed along a continuum: Well-Adapted, Average, Average-Social Skills Deficit, Internalizing, Externalizing, Disruptive Behavior with School Problems, and Severe Problems. Dropout rate was lowest for the Well-adapted class (4%) and highest for the Severe Problems class (58%). However, students in the Average-Social Skills Deficit class did not follow the continuum, with a large proportion of students who abandoned high school (29%). The proportion of students identified by teachers as high in aggression consistently increased across the continuum from none in the Well-Adapted class to 84% in the Severe Problems class. Students' self-reports were generally consistent with the latent profile classes. Students in the Well-Adapted class reported low aggression, drug use, and delinquency, and high life satisfaction; self-reports went in the opposite direction for the Disruptive Behaviors with School Problems class. Results highlight the importance of early interventions to improve academic performance, reduce externalizing behaviors, and enhance social assets. (c) 2015 APA, all rights reserved).

  6. Identification of Chinese medicine syndromes in persistent insomnia associated with major depressive disorder: a latent tree analysis.

    Science.gov (United States)

    Yeung, Wing-Fai; Chung, Ka-Fai; Zhang, Nevin Lian-Wen; Zhang, Shi Ping; Yung, Kam-Ping; Chen, Pei-Xian; Ho, Yan-Yee

    2016-01-01

    Chinese medicine (CM) syndrome (zheng) differentiation is based on the co-occurrence of CM manifestation profiles, such as signs and symptoms, and pulse and tongue features. Insomnia is a symptom that frequently occurs in major depressive disorder despite adequate antidepressant treatment. This study aims to identify co-occurrence patterns in participants with persistent insomnia and major depressive disorder from clinical feature data using latent tree analysis, and to compare the latent variables with relevant CM syndromes. One hundred and forty-two participants with persistent insomnia and a history of major depressive disorder completed a standardized checklist (the Chinese Medicine Insomnia Symptom Checklist) specially developed for CM syndrome classification of insomnia. The checklist covers symptoms and signs, including tongue and pulse features. The clinical features assessed by the checklist were analyzed using Lantern software. CM practitioners with relevant experience compared the clinical feature variables under each latent variable with reference to relevant CM syndromes, based on a previous review of CM syndromes. The symptom data were analyzed to build the latent tree model and the model with the highest Bayes information criterion score was regarded as the best model. This model contained 18 latent variables, each of which divided participants into two clusters. Six clusters represented more than 50 % of the sample. The clinical feature co-occurrence patterns of these six clusters were interpreted as the CM syndromes Liver qi stagnation transforming into fire, Liver fire flaming upward, Stomach disharmony, Hyperactivity of fire due to yin deficiency, Heart-kidney noninteraction, and Qi deficiency of the heart and gallbladder. The clinical feature variables that contributed significant cumulative information coverage (at least 95 %) were identified. Latent tree model analysis on a sample of depressed participants with insomnia revealed 13 clinical

  7. Presentations and recorded keynotes of the First European Workshop on Latent Semantic Analysis in Technology Enhanced Learning

    NARCIS (Netherlands)

    Several

    2007-01-01

    Presentations and recorded keynotes at the 1st European Workshop on Latent Semantic Analysis in Technology-Enhanced Learning, March, 29-30, 2007. Heerlen, The Netherlands: The Open University of the Netherlands. Please see the conference website for more information:

  8. Disentangling women's responses on complex dietary intake patterns from an Indian cross-sectional survey : a latent class analysis

    NARCIS (Netherlands)

    Padmadas, SS; Dias, JG; Willekens, FJ

    Objective To investigate the degree of individual heterogeneity related to complex dietary behaviour and to further examine the associations of different dietary compositions with selected characteristics. Design Latent class analysis was applied to data from the recent cross-sectional National

  9. A Latent Class Growth Analysis of School Bullying and Its Social Context: The Self-Determination Theory Perspective

    Science.gov (United States)

    Lam, Shui-fong; Law, Wilbert; Chan, Chi-Keung; Wong, Bernard P. H.; Zhang, Xiao

    2015-01-01

    The contribution of social context to school bullying was examined from the self-determination theory perspective in this longitudinal study of 536 adolescents from 3 secondary schools in Hong Kong. Latent class growth analysis of the student-reported data at 5 time points from grade 7 to grade 9 identified 4 groups of students: bullies (9.8%),…

  10. Disentangling women's responses on complex dietary intake patterns from an Indian cross-sectional survey: a latent class analysis

    NARCIS (Netherlands)

    Padmadas, S.; Dias, J.; Willekens, F.J.C.

    2006-01-01

    Objective To investigate the degree of individual heterogeneity related to complex dietary behaviour and to further examine the associations of different dietary compositions with selected characteristics. Design Latent class analysis was applied to data from the recent cross-sectional National

  11. Identifying Students' Expectancy-Value Beliefs: A Latent Class Analysis Approach to Analyzing Middle School Students' Science Self-Perceptions

    Science.gov (United States)

    Phelan, Julia; Ing, Marsha; Nylund-Gibson, Karen; Brown, Richard S.

    2017-01-01

    This study extends current research by organizing information about students' expectancy-value achievement motivation, in a way that helps parents and teachers identify specific entry points to encourage and support students' science aspirations. This study uses latent class analysis to describe underlying differences in ability beliefs, task…

  12. Clustering Educational Digital Library Usage Data: A Comparison of Latent Class Analysis and K-Means Algorithms

    Science.gov (United States)

    Xu, Beijie; Recker, Mimi; Qi, Xiaojun; Flann, Nicholas; Ye, Lei

    2013-01-01

    This article examines clustering as an educational data mining method. In particular, two clustering algorithms, the widely used K-means and the model-based Latent Class Analysis, are compared, using usage data from an educational digital library service, the Instructional Architect (IA.usu.edu). Using a multi-faceted approach and multiple data…

  13. Spatial Bayesian latent factor regression modeling of coordinate-based meta-analysis data.

    Science.gov (United States)

    Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D; Nichols, Thomas E

    2018-03-01

    Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the article are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to (i) identify areas of consistent activation; and (ii) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterized as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. © 2017, The International Biometric Society.

  14. Spatial Bayesian Latent Factor Regression Modeling of Coordinate-based Meta-analysis Data

    Science.gov (United States)

    Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D.; Nichols, Thomas E.

    2017-01-01

    Summary Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the paper are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to 1) identify areas of consistent activation; and 2) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterised as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. PMID:28498564

  15. Longitudinal burnout-collaboration patterns in Japanese medical care workers at special needs schools: a latent class growth analysis

    Directory of Open Access Journals (Sweden)

    Kanayama M

    2016-06-01

    Full Text Available Mieko Kanayama,1 Machiko Suzuki,1 Yoshikazu Yuma2 1Department of Human Health Sciences, Kyoto University Graduate School of Medicine, Kyoto, Japan; 2Department of Human Development Education, Graduate School of Education, Hyogo University of Teacher Education, Kato, Hyogo, Japan Abstract: The present study aimed to identify and characterize potential burnout types and the relationship between burnout and collaboration over time. Latent class growth analysis and the growth mixture model were used to identify and characterize heterogeneous patterns of longitudinal stability and change in burnout, and the relationship between burnout and collaboration. We collected longitudinal data at three time points based on Japanese academic terms. The 396 study participants included academic teachers, yogo teachers, and registered nurses in Japanese special needs schools. The best model included four types of both burnout and collaboration in latent class growth analysis with intercept, slope, and quadratic terms. The four types of burnout were as follows: low stable, moderate unstable, high unstable, and high decreasing. They were identified as involving inverse collaboration function. The results indicated that there could be dynamic burnout types, namely moderate unstable, high unstable, and high decreasing, when focusing on growth trajectories in latent class analyses. The finding that collaboration was dynamic for dynamic burnout types and stable for stable burnout types is of great interest. This was probably related to the inverse relationship between the two constructs. Keywords: burnout, collaboration, latent class growth analysis, interprofessional care, special needs schools

  16. Latent Profile Analysis of Schizotypy and Paranormal Belief: Associations with Probabilistic Reasoning Performance

    Directory of Open Access Journals (Sweden)

    Andrew Denovan

    2018-01-01

    Full Text Available This study assessed the extent to which within-individual variation in schizotypy and paranormal belief influenced performance on probabilistic reasoning tasks. A convenience sample of 725 non-clinical adults completed measures assessing schizotypy (Oxford-Liverpool Inventory of Feelings and Experiences; O-Life brief, belief in the paranormal (Revised Paranormal Belief Scale; RPBS and probabilistic reasoning (perception of randomness, conjunction fallacy, paranormal perception of randomness, and paranormal conjunction fallacy. Latent profile analysis (LPA identified four distinct groups: class 1, low schizotypy and low paranormal belief (43.9% of sample; class 2, moderate schizotypy and moderate paranormal belief (18.2%; class 3, moderate schizotypy (high cognitive disorganization and low paranormal belief (29%; and class 4, moderate schizotypy and high paranormal belief (8.9%. Identification of homogeneous classes provided a nuanced understanding of the relative contribution of schizotypy and paranormal belief to differences in probabilistic reasoning performance. Multivariate analysis of covariance revealed that groups with lower levels of paranormal belief (classes 1 and 3 performed significantly better on perception of randomness, but not conjunction problems. Schizotypy had only a negligible effect on performance. Further analysis indicated that framing perception of randomness and conjunction problems in a paranormal context facilitated performance for all groups but class 4.

  17. Latent Profile Analysis of Schizotypy and Paranormal Belief: Associations with Probabilistic Reasoning Performance.

    Science.gov (United States)

    Denovan, Andrew; Dagnall, Neil; Drinkwater, Kenneth; Parker, Andrew

    2018-01-01

    This study assessed the extent to which within-individual variation in schizotypy and paranormal belief influenced performance on probabilistic reasoning tasks. A convenience sample of 725 non-clinical adults completed measures assessing schizotypy (Oxford-Liverpool Inventory of Feelings and Experiences; O-Life brief), belief in the paranormal (Revised Paranormal Belief Scale; RPBS) and probabilistic reasoning (perception of randomness, conjunction fallacy, paranormal perception of randomness, and paranormal conjunction fallacy). Latent profile analysis (LPA) identified four distinct groups: class 1, low schizotypy and low paranormal belief (43.9% of sample); class 2, moderate schizotypy and moderate paranormal belief (18.2%); class 3, moderate schizotypy (high cognitive disorganization) and low paranormal belief (29%); and class 4, moderate schizotypy and high paranormal belief (8.9%). Identification of homogeneous classes provided a nuanced understanding of the relative contribution of schizotypy and paranormal belief to differences in probabilistic reasoning performance. Multivariate analysis of covariance revealed that groups with lower levels of paranormal belief (classes 1 and 3) performed significantly better on perception of randomness, but not conjunction problems. Schizotypy had only a negligible effect on performance. Further analysis indicated that framing perception of randomness and conjunction problems in a paranormal context facilitated performance for all groups but class 4.

  18. Māori identity signatures: A latent profile analysis of the types of Māori identity.

    Science.gov (United States)

    Greaves, Lara M; Houkamau, Carla; Sibley, Chris G

    2015-10-01

    Māori are the indigenous peoples of New Zealand. However, the term 'Māori' can refer to a wide range of people of varying ethnic compositions and cultural identity. We present a statistical model identifying 6 distinct types, or 'Māori Identity Signatures,' and estimate their proportion in the Māori population. The model is tested using a Latent Profile Analysis of a national probability sample of 686 Māori drawn from the New Zealand Attitudes and Values Study. We identify 6 distinct signatures: Traditional Essentialists (22.6%), Traditional Inclusives (16%), High Moderates (31.7%), Low Moderates (18.7%), Spiritually Orientated (4.1%), and Disassociated (6.9%). These distinct Identity Signatures predicted variation in deprivation, age, mixed-ethnic affiliation, and religion. This research presents the first formal statistical model assessing how people's identity as Māori is psychologically structured, documents the relative proportion of these different patterns of structures, and shows that these patterns reliably predict differences in core demographics. We identify a range of patterns of Māori identity far more diverse than has been previously proposed based on qualitative data, and also show that the majority of Māori fit a moderate or traditional identity pattern. The application of our model for studying Māori health and identity development is discussed. (c) 2015 APA, all rights reserved).

  19. Subgrouping of risky behaviors among Iranian college students: a latent class analysis

    Directory of Open Access Journals (Sweden)

    Safiri S

    2016-07-01

    Full Text Available Saeid Safiri,1,2 Afarin Rahimi-Movaghar,3 Masud Yunesian,4,5 Homayoun Sadeghi-Bazargani,6 Mansour Shamsipour,5 Mohammad Ali Mansournia,1 Akbar Fotouhi1 1Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, 2Department of Public Health, School of Nursing and Midwifery, Maragheh University of Medical Sciences, Maragheh, 3Iranian National Center for Addiction Studies (INCAS, Iranian Institute for Reduction of High-Risk Behaviors, Tehran University of Medical Sciences, Tehran, 4Department of Environmental Health Engineering, School of Public Health, 5Department of Research Methodology and Data Analysis, Institute for Environmental Research, Tehran University of Medical Sciences, Tehran, 6Road Traffic Injury Research Center, Department of Statistics & Epidemiology, Tabriz University of Medical Sciences, Tabriz, Iran Background: Risky behaviors may interrupt development or cause considerable morbidity or mortality. This study’s purpose was to determine subgroups of students based on risky behaviors and assess the prevalence of risky behaviors in each of the subgroups.Participants and methods: This anonymous cross-sectional study was carried out in October 2015 and November 2015, with 1,777 students from Tabriz University of Medical Sciences, through multistage random sampling method. The data were analyzed by latent class analysis.Results: The prevalence rates of cigarette smoking (more than or equal to ten cigarettes, hookah use (≥1 time/month, and alcohol consumption (≥1 time/month during the last year were 12.4% (95% confidence interval [CI]: 10.9–14.0, 11.6% (95% CI: 10.0–13.1, and 4.9% (95% CI: 3.8–5.9, respectively. The prevalence rates of illicit opioids (1.8%, 95% CI: 1.2–2.5, cannabis (1.2%, 95% CI: 0.7–1.7, methamphetamine (1.1%, 95% CI: 0.6–1.6, methylphenidate (2.5%, 95% CI: 1.7–3.2, and extramarital sex (5.5%, 95% CI: 4.5–6.6 over the last year were

  20. Adolescent substance use behavior and suicidal behavior for boys and girls: a cross-sectional study by latent analysis approach.

    Science.gov (United States)

    Wang, Peng-Wei; Yen, Cheng-Fang

    2017-12-08

    Adolescent suicidal behavior may consist of different symptoms, including suicidal ideation, suicidal planning and suicidal attempts. Adolescent substance use behavior may contribute to adolescent suicidal behavior. However, research on the relationships between specific substance use and individual suicidal behavior is insufficient, as adolescents may not use only one substance or develop only one facet of suicidal behavior. Latent variables permit us to describe the relationships between clusters of related behaviors more accurately than studying the relationships between specific behaviors. Thus, the aim of this study was to explore how adolescent substance use behavior contributes to suicidal behavior using latent variables representing adolescent suicidal and substance use behaviors. A total of 13,985 adolescents were recruited using a stratified random sampling strategy. The participants indicated whether they had experienced suicidal ideation, planning and attempts and reported their cigarette, alcohol, ketamine and MDMA use during the past year. Latent analysis was used to examine the relationship between substance use and suicidal behavior. Adolescents who used any one of the above substances exhibited more suicidal behavior. The results of latent variables analysis revealed that adolescent substance use contributed to suicidal behavior and that boys exhibited more severe substance use behavior than girls. However, there was no gender difference in the association between substance use and suicidal behavior. Substance use behavior in adolescents is related to more suicidal behavior. In addition, the contribution of substance use to suicidal behavior does not differ between genders.

  1. Latent Dirichlet Allocation (LDA) for Sentiment Analysis Toward Tourism Review in Indonesia

    Science.gov (United States)

    Putri, IR; Kusumaningrum, R.

    2017-01-01

    The tourism industry is one of foreign exchange sector, which has considerable potential development in Indonesia. Compared to other Southeast Asia countries such as Malaysia with 18 million tourists and Singapore 20 million tourists, Indonesia which is the largest Southeast Asia’s country have failed to attract higher tourist numbers compared to its regional peers. Indonesia only managed to attract 8,8 million foreign tourists in 2013, with the value of foreign tourists each year which is likely to decrease. Apart from the infrastructure problems, marketing and managing also form of obstacles for tourism growth. An evaluation and self-analysis should be done by the stakeholder to respond toward this problem and capture opportunities that related to tourism satisfaction from tourists review. Recently, one of technology to answer this problem only relying on the subjective of statistical data which collected by voting or grading from user randomly. So the result is still not to be accountable. Thus, we proposed sentiment analysis with probabilistic topic model using Latent Dirichlet Allocation (LDA) method to be applied for reading general tendency from tourist review into certain topics that can be classified toward positive and negative sentiment.

  2. Two distinct phenotypes of asthma in elite athletes identified by latent class analysis.

    Science.gov (United States)

    Couto, Mariana; Stang, Julie; Horta, Luís; Stensrud, Trine; Severo, Milton; Mowinckel, Petter; Silva, Diana; Delgado, Luís; Moreira, André; Carlsen, Kai-Håkon

    2015-01-01

    Clusters of asthma in athletes have been insufficiently studied. Therefore, the present study aimed to characterize asthma phenotypes in elite athletes using latent class analysis (LCA) and to evaluate its association with the type of sport practiced. In the present cross-sectional study, an analysis of athletes' records was carried out in databases of the Portuguese National Anti-Doping Committee and the Norwegian School of Sport Sciences. Athletes with asthma, diagnosed according to criteria given by the International Olympic Committee, were included for LCA. Sports practiced were categorized into water, winter and other sports. Of 324 files screened, 150 files belonged to asthmatic athletes (91 Portuguese; 59 Norwegian). LCA retrieved two clusters: "atopic asthma" defined by allergic sensitization, rhinitis and allergic co-morbidities and increased exhaled nitric oxide levels; and "sports asthma", defined by exercise-induced respiratory symptoms and airway hyperesponsiveness without allergic features. The risk of developing the phenotype "sports asthma" was significantly increased in athletes practicing water (OR = 2.87; 95% CI [1.82-4.51]) and winter (OR = 8.65; 95% CI [2.67-28.03]) sports, when compared with other athletes. Two asthma phenotypes were identified in elite athletes: "atopic asthma" and "sports asthma". The type of sport practiced was associated with different phenotypes: water and winter sport athletes had three- and ninefold increased risk of "sports asthma". Recognizing different phenotypes is clinically relevant as it would lead to distinct targeted treatments.

  3. Predicting Raters’ Transparency Judgments of English and Chinese Morphological Constituents using Latent Semantic Analysis

    Science.gov (United States)

    Wang, Hsueh-Cheng; Hsu, Li-Chuan; Tien, Yi-Min; Pomplun, Marc

    2013-01-01

    The morphological constituents of English compounds (e.g., “butter” and “fly” for “butterfly”) and two-character Chinese compounds may differ in meaning from the whole word. Subjective differences and ambiguity of transparency make the judgments difficult, and a computational alternative based on a general model may be a way to average across subjective differences. The current study proposes two approaches based on Latent Semantic Analysis (Landauer & Dumais, 1997): Model 1 compares the semantic similarity between a compound word and each of its constituents, and Model 2 derives the dominant meaning of a constituent based on a clustering analysis of morphological family members (e.g., “butterfingers” or “buttermilk” for “butter”). The proposed models successfully predicted participants’ transparency ratings, and we recommend that experimenters use Model 1 for English compounds and Model 2 for Chinese compounds, due to raters’ morphological processing in different writing systems. The dominance of lexical meaning, semantic transparency, and the average similarity between all pairs within a morphological family are provided, and practical applications for future studies are discussed. PMID:23784009

  4. Trajectories of acute low back pain: a latent class growth analysis.

    Science.gov (United States)

    Downie, Aron S; Hancock, Mark J; Rzewuska, Magdalena; Williams, Christopher M; Lin, Chung-Wei Christine; Maher, Christopher G

    2016-01-01

    Characterising the clinical course of back pain by mean pain scores over time may not adequately reflect the complexity of the clinical course of acute low back pain. We analysed pain scores over 12 weeks for 1585 patients with acute low back pain presenting to primary care to identify distinct pain trajectory groups and baseline patient characteristics associated with membership of each cluster. This was a secondary analysis of the PACE trial that evaluated paracetamol for acute low back pain. Latent class growth analysis determined a 5 cluster model, which comprised 567 (35.8%) patients who recovered by week 2 (cluster 1, rapid pain recovery); 543 (34.3%) patients who recovered by week 12 (cluster 2, pain recovery by week 12); 222 (14.0%) patients whose pain reduced but did not recover (cluster 3, incomplete pain recovery); 167 (10.5%) patients whose pain initially decreased but then increased by week 12 (cluster 4, fluctuating pain); and 86 (5.4%) patients who experienced high-level pain for the whole 12 weeks (cluster 5, persistent high pain). Patients with longer pain duration were more likely to experience delayed recovery or nonrecovery. Belief in greater risk of persistence was associated with nonrecovery, but not delayed recovery. Higher pain intensity, longer duration, and workers' compensation were associated with persistent high pain, whereas older age and increased number of episodes were associated with fluctuating pain. Identification of discrete pain trajectory groups offers the potential to better manage acute low back pain.

  5. Latent class analysis on internet and smartphone addiction in college students

    Science.gov (United States)

    Mok, Jung-Yeon; Choi, Sam-Wook; Kim, Dai-Jin; Choi, Jung-Seok; Lee, Jaewon; Ahn, Heejune; Choi, Eun-Jeung; Song, Won-Young

    2014-01-01

    Purpose This study aimed to classify distinct subgroups of people who use both smartphone and the internet based on addiction severity levels. Additionally, how the classified groups differed in terms of sex and psychosocial traits was examined. Methods A total of 448 university students (178 males and 270 females) in Korea participated. The participants were given a set of questionnaires examining the severity of their internet and smartphone addictions, their mood, their anxiety, and their personality. Latent class analysis and ANOVA (analysis of variance) were the statistical methods used. Results Significant differences between males and females were found for most of the variables (all addicted than females (Psmartphone, this pattern was reversed (Psmartphone addiction were performed separately for each sex. Each sex showed clear patterns with the three-class model based on likelihood level of internet and smartphone addiction (Paddiction severity levels (all Paddiction severity levels (all Pprocess, this study identified three distinct internet and smartphone user groups in each sex. Moreover, psychosocial traits that differed in terms of addiction severity levels were also examined. It is expected that these results should aid the understanding of traits of internet and smartphone addiction and facilitate further study in this field. PMID:24899806

  6. Latent class analysis on internet and smartphone addiction in college students.

    Science.gov (United States)

    Mok, Jung-Yeon; Choi, Sam-Wook; Kim, Dai-Jin; Choi, Jung-Seok; Lee, Jaewon; Ahn, Heejune; Choi, Eun-Jeung; Song, Won-Young

    2014-01-01

    This study aimed to classify distinct subgroups of people who use both smartphone and the internet based on addiction severity levels. Additionally, how the classified groups differed in terms of sex and psychosocial traits was examined. A total of 448 university students (178 males and 270 females) in Korea participated. The participants were given a set of questionnaires examining the severity of their internet and smartphone addictions, their mood, their anxiety, and their personality. Latent class analysis and ANOVA (analysis of variance) were the statistical methods used. Significant differences between males and females were found for most of the variables (all addicted than females (Psmartphone, this pattern was reversed (Psmartphone addiction were performed separately for each sex. Each sex showed clear patterns with the three-class model based on likelihood level of internet and smartphone addiction (Paddiction severity levels (all Paddiction severity levels (all Psmartphone user groups in each sex. Moreover, psychosocial traits that differed in terms of addiction severity levels were also examined. It is expected that these results should aid the understanding of traits of internet and smartphone addiction and facilitate further study in this field.

  7. A latent profile analysis of Asian American men's and women's adherence to cultural values.

    Science.gov (United States)

    Wong, Y Joel; Nguyen, Chi P; Wang, Shu-Yi; Chen, Weilin; Steinfeldt, Jesse A; Kim, Bryan S K

    2012-07-01

    The goal of this study was to identify diverse profiles of Asian American women's and men's adherence to values that are salient in Asian cultures (i.e., conformity to norms, family recognition through achievement, emotional self-control, collectivism, and humility). To this end, the authors conducted a latent profile analysis using the 5 subscales of the Asian American Values Scale-Multidimensional in a sample of 214 Asian Americans. The analysis uncovered a four-cluster solution. In general, Clusters 1 and 2 were characterized by relatively low and moderate levels of adherence to the 5 dimensions of cultural values, respectively. Cluster 3 was characterized by the highest level of adherence to the cultural value of family recognition through achievement, whereas Cluster 4 was typified by the highest levels of adherence to collectivism, emotional self-control, and humility. Clusters 3 and 4 were associated with higher levels of depressive symptoms than Cluster 1. Furthermore, Asian American women and Asian American men had lower odds of being in Cluster 4 and Cluster 3, respectively. These findings attest to the importance of identifying specific patterns of adherence to cultural values when examining the relationship between Asian Americans' cultural orientation and mental health status.

  8. Psychological features of North Korean female refugees on the MMPI-2: latent profile analysis.

    Science.gov (United States)

    Kim, Seong-Hyeon; Kim, Hee Kyung; Lee, Narae

    2013-12-01

    This study examined the heterogeneity in the Minnesota Multiphasic Personality Inventory-2nd Edition (MMPI-2; Butcher, Dahlstrom, Graham, Tellegen, & Kaemmer, 1989) profiles of North Korean female refugee population (N = 2,163) using latent profile analysis (LPA). The North Korean female refugee sample arrived at Hanawon, South Korea's resettlement center for North Korean refugees in 2008 and 2009 and took the MMPI-2 as part of an initial psychological screen. The analysis, which included the T scores of the 6 validity scales and the 10 standard clinical scales, identified 4 classes with distinctive psychological features: Class 1 (nonclinical), Class 2 (demoralized), Class 3 (somatized), and Class 4 (detached). The 4 covariates entered into the model (age, education, affiliation with a religion, and the number of forced repatriations) impacted the likelihood of belonging to certain classes. As hypothesized, older age, fewer years of education, and more incidents of forced repatriation predicted higher proneness to psychopathology. However, contrary to our expectation, having a religious faith did not emerge as a salient protective factor. The current LPA results revealed distinct heterogeneous subgroups that previous research on the MMPI and MMPI-2 profiles of refugee populations overlooked with the assumption of a homogeneous sample. Clinical implications for the treatment of North Korean female refugees and the limitations of the study are discussed. (c) 2013 APA, all rights reserved.

  9. Variations in adolescents’ motivational characteristics across gender and physical activity patterns: A latent class analysis approach

    Directory of Open Access Journals (Sweden)

    Margaret Lawler

    2017-08-01

    Full Text Available Abstract Background Neglecting to take account of the underlying context or type of physical activity (PA that underpins overall involvement has resulted in a limited understanding of adolescents’ PA participation. The purpose of the present research was to identify male and female adolescents’ leisure time PA patterns and examine whether psychological processes derived from self-determination theory differ as a function of the pattern of PA undertaken. Methods Nine hundred ninety-five students (61.2% females, 38.8% males; M age = 13.72 years, SD = 1.25 from eight secondary schools in Dublin, Ireland completed a physical activity recall 7 day diary and measures of intrinsic motivation, competence, relatedness, autonomy and autonomy support. Based on the diary five binary indicators of physical activity were derived reflecting recommended levels of MVPA on a minimum of 3 days, at least three sessions of non-organized physical activity (e.g. jog, team sport, individual sport, and organized non-sport physical activity (e.g. dance. Latent class analysis was used to identify subgroups of adolescents that engaged in similar patterns of physical activity. Profiles of physical activity participation were subsequently compared on motivational characteristics using Kruskal-Wallis tests. Results Latent class analysis revealed six distinct classes for girls (Organized Run/Swim & Dance/Gym; Organized Dance; Leisure Active Team Sport; Active Individual Sport; Walk/Run/Outdoor games; Non-Participation and five for boys (Leisure Active Gym; Leisure Active Individual Sport; Active Team Sport; Active Mixed Type; Non-Participation. Significant differences were found between the classes. Girls characterized by participation in team or individual sport, and boys represented by team sport participation demonstrated significantly higher self-determined motivational characteristics relative to other profiles of physical activity. Conclusion This research

  10. Variations in adolescents' motivational characteristics across gender and physical activity patterns: A latent class analysis approach.

    Science.gov (United States)

    Lawler, Margaret; Heary, Caroline; Nixon, Elizabeth

    2017-08-17

    Neglecting to take account of the underlying context or type of physical activity (PA) that underpins overall involvement has resulted in a limited understanding of adolescents' PA participation. The purpose of the present research was to identify male and female adolescents' leisure time PA patterns and examine whether psychological processes derived from self-determination theory differ as a function of the pattern of PA undertaken. Nine hundred ninety-five students (61.2% females, 38.8% males; M age = 13.72 years, SD = 1.25) from eight secondary schools in Dublin, Ireland completed a physical activity recall 7 day diary and measures of intrinsic motivation, competence, relatedness, autonomy and autonomy support. Based on the diary five binary indicators of physical activity were derived reflecting recommended levels of MVPA on a minimum of 3 days, at least three sessions of non-organized physical activity (e.g. jog), team sport, individual sport, and organized non-sport physical activity (e.g. dance). Latent class analysis was used to identify subgroups of adolescents that engaged in similar patterns of physical activity. Profiles of physical activity participation were subsequently compared on motivational characteristics using Kruskal-Wallis tests. Latent class analysis revealed six distinct classes for girls (Organized Run/Swim & Dance/Gym; Organized Dance; Leisure Active Team Sport; Active Individual Sport; Walk/Run/Outdoor games; Non-Participation) and five for boys (Leisure Active Gym; Leisure Active Individual Sport; Active Team Sport; Active Mixed Type; Non-Participation). Significant differences were found between the classes. Girls characterized by participation in team or individual sport, and boys represented by team sport participation demonstrated significantly higher self-determined motivational characteristics relative to other profiles of physical activity. This research offers a nuanced insight into the underlying type of activities that

  11. Latent class analysis on internet and smartphone addiction in college students

    Directory of Open Access Journals (Sweden)

    Mok JY

    2014-05-01

    Full Text Available Jung-Yeon Mok,1 Sam-Wook Choi,1,2 Dai-Jin Kim,3 Jung-Seok Choi,4 Jaewon Lee,2 Heejune Ahn,5 Eun-Jeung Choi,6 Won-Young Song7 1Eulji Addiction Institute, Eulji University, Seoul, South Korea; 2Department of Psychiatry, Gangnam Eulji Hospital, Eulji University, Seoul, South Korea; 3Department of Psychiatry, Seoul St Mary's Hospital, College of Medicine, Catholic University of Korea, Seoul, South Korea; 4Department of Psychiatry, SMG-SNU Boramae Medical Center, Seoul, South Korea; 5Department of Electrical and Information Engineering, SeoulTech, Seoul, South Korea; 6Department of Social Welfare, Dongshin University, Naju, South Korea; 7Department of Counseling and Psychotherapy, Konyang University, Nonsan, South Korea Purpose: This study aimed to classify distinct subgroups of people who use both smartphone and the internet based on addiction severity levels. Additionally, how the classified groups differed in terms of sex and psychosocial traits was examined. Methods: A total of 448 university students (178 males and 270 females in Korea participated. The participants were given a set of questionnaires examining the severity of their internet and smartphone addictions, their mood, their anxiety, and their personality. Latent class analysis and ANOVA (analysis of variance were the statistical methods used. Results: Significant differences between males and females were found for most of the variables (all P<0.05. Specifically, in terms of internet usage, males were more addicted than females (P<0.05; however, regarding smartphone, this pattern was reversed (P<0.001. Due to these observed differences, classifications of the subjects into subgroups based on internet and smartphone addiction were performed separately for each sex. Each sex showed clear patterns with the three-class model based on likelihood level of internet and smartphone addiction (P<0.001. A common trend for psychosocial trait factors was found for both sexes: anxiety levels and

  12. Retrieving latent heating vertical structure from cloud and precipitation profiles—Part II: Deep convective and stratiform rain processes

    International Nuclear Information System (INIS)

    Li, Rui; Min, Qilong; Wu, Xiaoqing; Fu, Yunfei

    2013-01-01

    An exploratory study on physical based latent heat (LH) retrieval algorithm is conducted by parameterizing the physical linkages between observed cloud and precipitation profiles to the major processes of phase change of atmospheric water. Specifically, rain is segregated into three rain types: warm, convective, and stratiform rain, based on their dynamical and thermodynamical characteristics. As the second of series, both convective and stratiform rain LH algorithms are presented and evaluated here. For convective and stratiform rain, the major LH-related microphysical processes including condensation, deposition, evaporation, sublimation, and freezing–melting are parameterized with the aid of Cloud Resolving Model (CRM) simulations. The condensation and deposition processes are parameterized in terms of rain formation processes through the precipitation formation theory. LH associated with the freezing–melting process is relatively small and is assumed to be a fraction of total condensation and deposition LH. The evaporation and sublimation processes are parameterized for three unsaturated scenarios: rain out of the cloud body, clouds at cloud boundary and clouds and rain in downdraft region. The evaluation or self-consistency test indicates the retrievals capture the major features of LH profiles and reproduce the double peaks at right altitudes. The LH products are applicable at various stages of cloud system life cycle for high-resolution models, as well as for large-scale climate models. -- Highlights: ► An exploratory study on physics-based cold rain latent heat retrieval algorithm. ► Utilize the full information of the vertical structures of cloud and rainfall. ► Include all major LH-related microphysical processes (in ice and liquid phase). ► Directly link water mass measurements to latent heat at instantaneous pixel level. ► Applicable at various stages of cloud system life cycle

  13. Illustration of Step-Wise Latent Class Modeling With Covariates and Taxometric Analysis in Research Probing Children's Mental Models in Learning Sciences

    Directory of Open Access Journals (Sweden)

    Dimitrios Stamovlasis

    2018-04-01

    Full Text Available This paper illustrates two psychometric methods, latent class analysis (LCA and taxometric analysis (TA using empirical data from research probing children's mental representation in science learning. LCA is used to obtain a typology based on observed variables and to further investigate how the encountered classes might be related to external variables, where the effectiveness of classification process and the unbiased estimations of parameters become the main concern. In the step-wise LCA, the class membership is assigned and subsequently its relationship with covariates is established. This leading-edge modeling approach suffers from severe downward-biased estimations. The illustration of LCA is focused on alternative bias correction approaches and demonstrates the effect of modal and proportional class-membership assignment along with BCH and ML correction procedures. The illustration of LCA is presented with three covariates, which are psychometric variables operationalizing formal reasoning, divergent thinking and field dependence-independence, respectively. Moreover, taxometric analysis, a method designed to detect the type of the latent structural model, categorical or dimensional, is introduced, along with the relevant basic concepts and tools. TA was applied complementarily in the same data sets to answer the fundamental hypothesis about children's naïve knowledge on the matters under study and it comprises an additional asset in building theory which is fundamental for educational practices. Taxometric analysis provided results that were ambiguous as far as the type of the latent structure. This finding initiates further discussion and sets a problematization within this framework rethinking fundamental assumptions and epistemological issues.

  14. An Optimized DNA Analysis Workflow for the Sampling, Extraction, and Concentration of DNA obtained from Archived Latent Fingerprints.

    Science.gov (United States)

    Solomon, April D; Hytinen, Madison E; McClain, Aryn M; Miller, Marilyn T; Dawson Cruz, Tracey

    2018-01-01

    DNA profiles have been obtained from fingerprints, but there is limited knowledge regarding DNA analysis from archived latent fingerprints-touch DNA "sandwiched" between adhesive and paper. Thus, this study sought to comparatively analyze a variety of collection and analytical methods in an effort to seek an optimized workflow for this specific sample type. Untreated and treated archived latent fingerprints were utilized to compare different biological sampling techniques, swab diluents, DNA extraction systems, DNA concentration practices, and post-amplification purification methods. Archived latent fingerprints disassembled and sampled via direct cutting, followed by DNA extracted using the QIAamp® DNA Investigator Kit, and concentration with Centri-Sep™ columns increased the odds of obtaining an STR profile. Using the recommended DNA workflow, 9 of the 10 samples provided STR profiles, which included 7-100% of the expected STR alleles and two full profiles. Thus, with carefully selected procedures, archived latent fingerprints can be a viable DNA source for criminal investigations including cold/postconviction cases. © 2017 American Academy of Forensic Sciences.

  15. Evaluating the accuracy of molecular diagnostic testing for canine visceral leishmaniasis using latent class analysis.

    Directory of Open Access Journals (Sweden)

    Manuela da Silva Solcà

    Full Text Available Host tissues affected by Leishmania infantum have differing degrees of parasitism. Previously, the use of different biological tissues to detect L. infantum DNA in dogs has provided variable results. The present study was conducted to evaluate the accuracy of molecular diagnostic testing (qPCR in dogs from an endemic area for canine visceral leishmaniasis (CVL by determining which tissue type provided the highest rate of parasite DNA detection. Fifty-one symptomatic dogs were tested for CVL using serological, parasitological and molecular methods. Latent class analysis (LCA was performed for accuracy evaluation of these methods. qPCR detected parasite DNA in 100% of these animals from at least one of the following tissues: splenic and bone marrow aspirates, lymph node and skin fragments, blood and conjunctival swabs. Using latent variable as gold standard, the qPCR achieved a sensitivity of 95.8% (CI 90.4-100 in splenic aspirate; 79.2% (CI 68-90.3 in lymph nodes; 77.3% (CI 64.5-90.1 in skin; 75% (CI 63.1-86.9 in blood; 50% (CI 30-70 in bone marrow; 37.5% (CI 24.2-50.8 in left-eye; and 29.2% (CI 16.7-41.6 in right-eye conjunctival swabs. The accuracy of qPCR using splenic aspirates was further evaluated in a random larger sample (n = 800, collected from dogs during a prevalence study. The specificity achieved by qPCR was 76.7% (CI 73.7-79.6 for splenic aspirates obtained from the greater sample. The sensitivity accomplished by this technique was 95% (CI 93.5-96.5 that was higher than those obtained for the other diagnostic tests and was similar to that observed in the smaller sampling study. This confirms that the splenic aspirate is the most effective type of tissue for detecting L. infantum infection. Additionally, we demonstrated that LCA could be used to generate a suitable gold standard for comparative CVL testing.

  16. Predominant typologies of psychopathology in the United States: a latent class analysis.

    Science.gov (United States)

    El-Gabalawy, Renée; Tsai, Jack; Harpaz-Rotem, Ilan; Hoff, Rani; Sareen, Jitender; Pietrzak, Robert H

    2013-11-01

    Latent class analysis (LCA) offers a parsimonious way of classifying common typologies of psychiatric comorbidity. We used LCA to identify the nature and correlates of predominant typologies of Axis I and II disorders in a large and comprehensive population-based sample of U.S. adults. We analyzed data from Wave 2 of the National Epidemiologic Survey on Alcohol and Related Conditions (2004-2005; n = 34,653), a population-based sample of U.S. adults. We derived latent classes based on all assessed Axis I and II disorders and examined the relationship between the identified Axis I classes and lifetime psychiatric disorders and suicide attempts, and physical and mental health-related quality of life. A four-class solution was optimal in characterizing predominant typologies of both Axis I and II disorders. For Axis I disorders, these included low psychopathology (n = 28,935, 84.0%), internalizing (n = 3693, 9.9%), externalizing (n = 1426, 4.5%), and high psychopathology (n = 599, 1.6%) classes. For Axis II disorders, these included no/low personality disorders (n = 31,265, 90.9%), obsessive/paranoid (n = 1635, 4.6%), borderline/dysregulated (n = 1319, 3.4%), and highly comorbid (n = 434, 1.1%) classes. Compared to the low psychopathology class, all other Axis I classes had significantly increased odds of mental disorders, elevated Axis II classes, suicide attempts and poorer quality of life, with the high psychopathology class having the overall highest rates of these correlates, with the exception of substance use disorders. Compared to the low psychopathology class, the internalizing and externalizing classes had increased rates of mood and anxiety disorders, and substance use disorders, respectively. Axis I and II psychopathology among U.S. adults may be best represented by four predominant typologies. Characterizing co-occurring patterns of psychopathology using person-based typologies represents a higher-order classification system that may be useful in clinical

  17. National youth sedentary behavior and physical activity daily patterns using latent class analysis applied to accelerometry.

    Science.gov (United States)

    Evenson, Kelly R; Wen, Fang; Hales, Derek; Herring, Amy H

    2016-05-03

    Applying latent class analysis (LCA) to accelerometry can help elucidated underlying patterns. This study described the patterns of accelerometer-determined sedentary behavior and physical activity among youth by applying LCA to a nationally representative United States (US) sample. Using 2003-2006 National Health and Nutrition Examination Survey data, 3998 youths 6-17 years wore an ActiGraph 7164 accelerometer for one week, providing > =3 days of wear for > =8 h/day from 6:00 am-midnight. Cutpoints defined sedentary behavior ( = 2296 counts/minute), and vigorous activity (> = 4012 counts/minute). To account for wear time differences, outcomes were expressed as percent of day in a given intensity. LCA was used to classify daily (Monday through Sunday) patterns of average counts/minute, sedentary behavior, light activity, MVPA, and vigorous activity separately. The latent classes were explored overall and by age (6-11, 12-14, 15-17 years), gender, and whether or not youth attended school during measurement. Estimates were weighted to account for the sampling frame. For average counts/minute/day, four classes emerged from least to most active: 40.9% of population (mean 323.5 counts/minute/day), 40.3% (559.6 counts/minute/day), 16.5% (810.0 counts/minute/day), and 2.3% (1132.9 counts/minute/day). For percent of sedentary behavior, four classes emerged: 13.5% of population (mean 544.6 min/day), 30.1% (455.1 min/day), 38.5% (357.7 min/day), and 18.0% (259.2 min/day). For percent of light activity, four classes emerged: 12.3% of population (mean 222.6 min/day), 29.3% (301.7 min/day), 41.8% (384.0 min/day), and 16.6% (455.5 min/day). For percent of MVPA, four classes emerged: 59.9% of population (mean 25.0 min/day), 33.3% (60.9 min/day), 3.1% (89.0 min/day), and 3.6% (109.3 min/day). For percent of vigorous activity, three classes emerged: 76.8% of population (mean 7.1 min/day), 18.5% (23.9 min/day), and 4.7% (47.4 min/day). Classes were developed by age

  18. Effect of intrinsic motivation on affective responses during and after exercise: latent curve model analysis.

    Science.gov (United States)

    Shin, Myoungjin; Kim, Inwoo; Kwon, Sungho

    2014-12-01

    Understanding the relationship between affect and exercise is helpful in predicting human behavior with respect to exercise participation. The goals of the present study were to investigate individual differences in affective response during and after exercise and to identify the role of intrinsic motivation in affective changes. 30 active male college students (M age = 21.4 yr.) who regularly participated in sports activities volunteered to answer a questionnaire measuring intrinsic motivation toward running activities and performed a 20-min. straight running protocol at heavy intensity (about 70% of VO2max). Participants' affective responses were measured every 5 min. from the beginning of the run to 10 min. after completing the run. Latent curve model analysis indicated that individuals experienced different changes in affective state during exercise, moderated by intrinsic motivation. Higher intrinsic motivation was associated with more positive affect during exercise. There were no significant individual differences in the positive tendency of the participants' affective responses after exercise over time. Intrinsic motivation seems to facilitate positive feelings during exercise and encourages participation in exercise.

  19. Age onset of offending and serious mental illness among forensic psychiatric patients: A latent profile analysis.

    Science.gov (United States)

    Penney, Stephanie R; Prosser, Aaron; Simpson, Alexander I F

    2018-01-16

    Developmental typologies regarding age of onset of violence and offending have not routinely taken account of the role of serious mental illness (SMI), and whether age of onset of offending in relation to onset of illness impacts on the manifestation of offending over the life course. To test whether forensic psychiatric patients can be classified according to age of onset of SMI and offending, and, if so, whether subtypes differ by sex. Details of all 511 patients enrolled into a large forensic mental health service in Ontario, Canada, in 2011 or 2012 were collected from records. A latent profile analysis supported a 2-class solution in both men and women. External validation of the classes demonstrated that those with a younger age onset of serious mental illness and offending were characterised by higher levels of static risk factors and criminogenic need than those whose involvement in both mental health and criminal justice systems was delayed to later life. Our findings present a new perspective on life course trajectories of offenders with SMI. While analyses identified just two distinct age-of-onset groups, in both the illness preceded the offending. The fact that our sample was entirely drawn from those hospitalised may have introduced a selection bias for those whose illness precedes offending, but findings underscore the complexity and level of need among those with a younger age of onset. Copyright © 2018 John Wiley & Sons, Ltd. Copyright © 2018 John Wiley & Sons, Ltd.

  20. Prevalence and characteristics of addictive behaviors in a community sample: A latent class analysis.

    Science.gov (United States)

    Deleuze, Jory; Rochat, Lucien; Romo, Lucia; Van der Linden, Martial; Achab, Sophia; Thorens, Gabriel; Khazaal, Yasser; Zullino, Daniele; Maurage, Pierre; Rothen, Stéphane; Billieux, Joël

    2015-06-01

    While addictions to substances such as alcohol, tobacco, and other drugs have been extensively investigated, interest has been growing in potential non-substance-related addictive behaviors (e.g., excessive gambling, buying or playing video games). In the current study, we sought to determine the prevalence and characteristics of a wide range of addictive behaviors in a general population sample and to identify reliable subgroups of individuals displaying addictive behaviors. Seven hundred seventy participants completed an online survey. The survey screened for the presence and characteristics of the main recognized substance and behavioral addictions (alcohol, tobacco, cannabis, other drugs, gambling, compulsive shopping, intensive exercise, Internet and mobile phone overuse, intensive work involvement, and overeating) in a three-month period. Key aspects of addiction were measured for each reported behavior, including negative outcomes, emotional triggers (positive and negative emotional contexts), search for stimulation or pleasure, loss of control, and cognitive salience. Latent class analysis allowed us to identify three theoretically and clinically relevant subgroups of individuals. The first class groups problematic users, i.e., addiction-prone individuals. The second class groups at-risk users who frequently engage in potentially addictive behaviors to regulate emotional states (especially overinvolvement in common behaviors such as eating, working, or buying). The third class groups individuals who are not prone to addictive behaviors. The existence of different groups in the population sheds new light on the distinction between problematic and non-problematic addiction-like behaviors.

  1. Longitudinal Model Building Using Latent Transition Analysis: An Example Using School Bullying Data

    Directory of Open Access Journals (Sweden)

    Ji Hoon Ryoo

    2018-05-01

    Full Text Available Applications of latent transition analysis (LTA have emerged since the early 1990s, with numerous scientific findings being published in many areas, including social and behavioral sciences, education, and public health. Although LTA is effective as a statistical analytic tool for a person-centered model using longitudinal data, model building in LTA has often been subjective and confusing for applied researchers. To fill this gap in the literature, we review the components of LTA, recommend a framework of fitting LTA, and summarize what acceptable model evaluation tools should be used in practice. The proposed framework of fitting LTA consists of six steps depicted in Figure 1 from step 0 (exploring data to step 5 (fitting distal variables. We also illustrate the framework of fitting LTA with data on concerns about school bullying from a sample of 1,180 students ranging from 5th to 9th grade (mean age = 12.2 years, SD = 1.29 years at Time 1 over three semesters. We identified four groups of students with distinct patterns of bullying concerns, and found that their concerns about bullying decreased and narrowed to specific concerns about rumors, gossip, and social exclusion over time. The data and command (syntax files needed for reproducing the results using SAS PROC LCA and PROC LTA (Version 1.3.2 (2015 and Mplus 7.4 (Muthén and Muthén, 1998–2015 are provided as online supplementary materials.

  2. Emotional labor actors: a latent profile analysis of emotional labor strategies.

    Science.gov (United States)

    Gabriel, Allison S; Daniels, Michael A; Diefendorff, James M; Greguras, Gary J

    2015-05-01

    Research on emotional labor focuses on how employees utilize 2 main regulation strategies-surface acting (i.e., faking one's felt emotions) and deep acting (i.e., attempting to feel required emotions)-to adhere to emotional expectations of their jobs. To date, researchers largely have considered how each strategy functions to predict outcomes in isolation. However, this variable-centered perspective ignores the possibility that there are subpopulations of employees who may differ in their combined use of surface and deep acting. To address this issue, we conducted 2 studies that examined surface acting and deep acting from a person-centered perspective. Using latent profile analysis, we identified 5 emotional labor profiles-non-actors, low actors, surface actors, deep actors, and regulators-and found that these actor profiles were distinguished by several emotional labor antecedents (positive affectivity, negative affectivity, display rules, customer orientation, and emotion demands-abilities fit) and differentially predicted employee outcomes (emotional exhaustion, job satisfaction, and felt inauthenticity). Our results reveal new insights into the nature of emotion regulation in emotional labor contexts and how different employees may characteristically use distinct combinations of emotion regulation strategies to manage their emotional expressions at work. (c) 2015 APA, all rights reserved.

  3. Latent profile analysis and principal axis factoring of the DSM-5 dissociative subtype

    Science.gov (United States)

    Frewen, Paul A.; Brown, Matthew F. D.; Steuwe, Carolin; Lanius, Ruth A.

    2015-01-01

    Objective A dissociative subtype has been recognized based on the presence of experiences of depersonalization and derealization in relation to DSM-IV posttraumatic stress disorder (PTSD). However, the dissociative subtype has not been assessed in a community sample in relation to the revised DSM-5 PTSD criteria. Moreover, the 20-item PTSD Checklist for DSM-5 (PCL-5) currently does not assess depersonalization and derealization. Method We therefore evaluated two items for assessing depersonalization and derealization in 557 participants recruited online who endorsed PTSD symptoms of at least moderate severity on the PCL-5. Results A five-class solution identified two PTSD classes who endorsed dissociative experiences associated with either 1) severe or 2) moderate PTSD symptom severity (D-PTSD classes). Those in the severe dissociative class were particularly likely to endorse histories of childhood physical and sexual abuse. A principal axis factor analysis of the symptom list identified six latent variables: 1) Reexperiencing, 2) Emotional Numbing/Anhedonia, 3) Dissociation, 4) Negative Alterations in Cognition & Mood, 5) Avoidance, and 6) Hyperarousal. Conclusions The present results further support the presence of a dissociative subtype within the DSM-5 criteria for PTSD. PMID:25854673

  4. Patterns of Brucellosis Infection Symptoms in Azerbaijan: A Latent Class Cluster Analysis

    Directory of Open Access Journals (Sweden)

    Rita Ismayilova

    2014-01-01

    Full Text Available Brucellosis infection is a multisystem disease, with a broad spectrum of symptoms. We investigated the existence of clusters of infected patients according to their clinical presentation. Using national surveillance data from the Electronic-Integrated Disease Surveillance System, we applied a latent class cluster (LCC analysis on symptoms to determine clusters of brucellosis cases. A total of 454 cases reported between July 2011 and July 2013 were analyzed. LCC identified a two-cluster model and the Vuong-Lo-Mendell-Rubin likelihood ratio supported the cluster model. Brucellosis cases in the second cluster (19% reported higher percentages of poly-lymphadenopathy, hepatomegaly, arthritis, myositis, and neuritis and changes in liver function tests compared to cases of the first cluster. Patients in the second cluster had a severe brucellosis disease course and were associated with longer delay in seeking medical attention. Moreover, most of them were from Beylagan, a region focused on sheep and goat livestock production in south-central Azerbaijan. Patients in cluster 2 accounted for one-quarter of brucellosis cases and had a more severe clinical presentation. Delay in seeking medical care may explain severe illness. Future work needs to determine the factors that influence brucellosis case seeking and identify brucellosis species, particularly among cases from Beylagan.

  5. The application of latent curve analysis to testing developmental theories in intervention research.

    Science.gov (United States)

    Curran, P J; Muthén, B O

    1999-08-01

    The effectiveness of a prevention or intervention program has traditionally been assessed using time-specific comparisons of mean levels between the treatment and the control groups. However, many times the behavior targeted by the intervention is naturally developing over time, and the goal of the treatment is to alter this natural or normative developmental trajectory. Examining time-specific mean levels can be both limiting and potentially misleading when the behavior of interest is developing systematically over time. It is argued here that there are both theoretical and statistical advantages associated with recasting intervention treatment effects in terms of normative and altered developmental trajectories. The recently developed technique of latent curve (LC) analysis is reviewed and extended to a true experimental design setting in which subjects are randomly assigned to a treatment intervention or a control condition. LC models are applied to both artificially generated and real intervention data sets to evaluate the efficacy of an intervention program. Not only do the LC models provide a more comprehensive understanding of the treatment and control group developmental processes compared to more traditional fixed-effects models, but LC models have greater statistical power to detect a given treatment effect. Finally, the LC models are modified to allow for the computation of specific power estimates under a variety of conditions and assumptions that can provide much needed information for the planning and design of more powerful but cost-efficient intervention programs for the future.

  6. Distinguishing PTSD, Complex PTSD, and Borderline Personality Disorder: A latent class analysis

    Directory of Open Access Journals (Sweden)

    Marylène Cloitre

    2014-09-01

    Full Text Available Background: There has been debate regarding whether Complex Posttraumatic Stress Disorder (Complex PTSD is distinct from Borderline Personality Disorder (BPD when the latter is comorbid with PTSD. Objective: To determine whether the patterns of symptoms endorsed by women seeking treatment for childhood abuse form classes that are consistent with diagnostic criteria for PTSD, Complex PTSD, and BPD. Method: A latent class analysis (LCA was conducted on an archival dataset of 280 women with histories of childhood abuse assessed for enrollment in a clinical trial for PTSD. Results: The LCA revealed four distinct classes of individuals: a Low Symptom class characterized by low endorsements on all symptoms; a PTSD class characterized by elevated symptoms of PTSD but low endorsement of symptoms that define the Complex PTSD and BPD diagnoses; a Complex PTSD class characterized by elevated symptoms of PTSD and self-organization symptoms that defined the Complex PTSD diagnosis but low on the symptoms of BPD; and a BPD class characterized by symptoms of BPD. Four BPD symptoms were found to greatly increase the odds of being in the BPD compared to the Complex PTSD class: frantic efforts to avoid abandonment, unstable sense of self, unstable and intense interpersonal relationships, and impulsiveness. Conclusions: Findings supported the construct validity of Complex PTSD as distinguishable from BPD. Key symptoms that distinguished between the disorders were identified, which may aid in differential diagnosis and treatment planning.

  7. Perceived risk associated with ecstasy use: a latent class analysis approach

    Science.gov (United States)

    Martins, SS; Carlson, RG; Alexandre, PK; Falck, RS

    2011-01-01

    This study aims to define categories of perceived health problems among ecstasy users based on observed clustering of their perceptions of ecstasy-related health problems. Data from a community sample of ecstasy users (n=402) aged 18 to 30, in Ohio, was used in this study. Data was analyzed via Latent Class Analysis (LCA) and Regression. This study identified five different subgroups of ecstasy users based on their perceptions of health problems they associated with their ecstasy use. Almost one third of the sample (28.9%) belonged to a class with “low level of perceived problems” (Class 4). About one fourth (25.6%) of the sample (Class 2), had high probabilities of “perceiving problems on sexual-related items”, but generally low or moderate probabilities of perceiving problems in other areas. Roughly one-fifth of the sample (21.1%, Class 1) had moderate probabilities of perceiving ecstasy health-related problems in all areas. A small proportion of respondents (11.9%, Class 5) had high probabilities of reporting “perceived memory and cognitive problems, and of perceiving “ecstasy related-problems in all areas” (12.4%, Class 3). A large proportion of ecstasy users perceive either low or moderate risk associated with their ecstasy use. It is important to further investigate whether lower levels of risk perception are associated with persistence of ecstasy use. PMID:21296504

  8. Semi-supervised learning based probabilistic latent semantic analysis for automatic image annotation

    Institute of Scientific and Technical Information of China (English)

    Tian Dongping

    2017-01-01

    In recent years, multimedia annotation problem has been attracting significant research attention in multimedia and computer vision areas, especially for automatic image annotation, whose purpose is to provide an efficient and effective searching environment for users to query their images more easily.In this paper, a semi-supervised learning based probabilistic latent semantic analysis ( PL-SA) model for automatic image annotation is presenred.Since it' s often hard to obtain or create la-beled images in large quantities while unlabeled ones are easier to collect, a transductive support vector machine ( TSVM) is exploited to enhance the quality of the training image data.Then, differ-ent image features with different magnitudes will result in different performance for automatic image annotation.To this end, a Gaussian normalization method is utilized to normalize different features extracted from effective image regions segmented by the normalized cuts algorithm so as to reserve the intrinsic content of images as complete as possible.Finally, a PLSA model with asymmetric mo-dalities is constructed based on the expectation maximization( EM) algorithm to predict a candidate set of annotations with confidence scores.Extensive experiments on the general-purpose Corel5k dataset demonstrate that the proposed model can significantly improve performance of traditional PL-SA for the task of automatic image annotation.

  9. How school climate relates to chronic absence: A multi-level latent profile analysis.

    Science.gov (United States)

    Van Eck, Kathryn; Johnson, Stacy R; Bettencourt, Amie; Johnson, Sarah Lindstrom

    2017-04-01

    Chronic absence is a significant problem in schools. School climate may play an important role in influencing chronic absence rates among schools, yet little research has evaluated how school climate constructs relate to chronic absence. Using multilevel latent profile analysis, we evaluated how profiles of student perceptions of school climate at both the student and school level differentiated school-level rates of chronic absence. Participants included 25,776 middle and high school students from 106 schools who completed a district administered school climate survey. Students attended schools in a large urban school district where 89% of 6th through 12th grade students were African-American and 61% were eligible for the federally subsidized school meals program. Three student-level profiles of perceptions of school climate emerged that corresponded to "positive," "moderate," and "negative" climate. Two predominant patterns regarding the distribution of these profiles within schools emerged that corresponded to the two school-level profiles of "marginal climate" and "climate challenged" schools. Students reporting "moderate" and "negative" climate in their schools were more likely to attend schools with higher chronic absence rates than students reporting that their school had "positive" climate. Likewise, "climate challenged" schools had significantly higher chronic absence rates than "marginal climate" schools. These results suggest that school climate shares an important relation with chronic absence among adolescent students attending urban schools. Implications for prevention and intervention programs are discussed. Copyright © 2016 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

  10. Mental Health and Educational Experiences Among Black Youth: A Latent Class Analysis.

    Science.gov (United States)

    Rose, Theda; Lindsey, Michael A; Xiao, Yunyu; Finigan-Carr, Nadine M; Joe, Sean

    2017-11-01

    Disproportionately lower educational achievement, coupled with higher grade retention, suspensions, expulsions, and lower school bonding make educational success among Black adolescents a major public health concern. Mental health is a key developmental factor related to educational outcomes among adolescents; however, traditional models of mental health focus on absence of dysfunction as a way to conceptualize mental health. The dual-factor model of mental health incorporates indicators of both subjective wellbeing and psychopathology, supporting more recent research that both are needed to comprehensively assess mental health. This study applied the dual-factor model to measure mental health using the National Survey of American Life-Adolescent Supplement (NSAL-A), a representative cross-sectional survey. The sample included 1170 Black adolescents (52% female; mean age 15). Latent class analysis was conducted with positive indicators of subjective wellbeing (emotional, psychological, and social) as well as measures of psychopathology. Four mental health groups were identified, based on having high or low subjective wellbeing and high or low psychopathology. Accordingly, associations between mental health groups and educational outcomes were investigated. Significant associations were observed in school bonding, suspensions, and grade retention, with the positive mental health group (high subjective wellbeing, low psychopathology) experiencing more beneficial outcomes. The results support a strong association between school bonding and better mental health and have implications for a more comprehensive view of mental health in interventions targeting improved educational experiences and mental health among Black adolescents.

  11. Two-Year Trajectory of Fall Risk in People With Parkinson Disease: A Latent Class Analysis.

    Science.gov (United States)

    Paul, Serene S; Thackeray, Anne; Duncan, Ryan P; Cavanaugh, James T; Ellis, Theresa D; Earhart, Gammon M; Ford, Matthew P; Foreman, K Bo; Dibble, Leland E

    2016-03-01

    To examine fall risk trajectories occurring naturally in a sample of individuals with early to middle stage Parkinson disease (PD). Latent class analysis, specifically growth mixture modeling (GMM), of longitudinal fall risk trajectories. Assessments were conducted at 1 of 4 universities. Community-dwelling participants with PD of a longitudinal cohort study who attended at least 2 of 5 assessments over a 2-year follow-up period (N=230). Not applicable. Fall risk trajectory (low, medium, or high risk) and stability of fall risk trajectory (stable or fluctuating). Fall risk was determined at 6 monthly intervals using a simple clinical tool based on fall history, freezing of gait, and gait speed. The GMM optimally grouped participants into 3 fall risk trajectories that closely mirrored baseline fall risk status (P=.001). The high fall risk trajectory was most common (42.6%) and included participants with longer and more severe disease and with higher postural instability and gait disability (PIGD) scores than the low and medium fall risk trajectories (Pfall risk (posterior probability fall risk trajectories over 2 years. Further investigation is required to determine whether interventions to improve gait and balance may improve fall risk trajectories in people with PD. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

  12. Patterns of stigma toward schizophrenia among the general population: a latent profile analysis.

    Science.gov (United States)

    Loch, Alexandre A; Wang, Yuan-Pang; Guarniero, Francisco B; Lawson, Fabio L; Hengartner, Michael P; Rössler, Wulf; Gattaz, Wagner F

    2014-09-01

    Our purpose was to assess stigma toward schizophrenia in a representative sample of the Brazilian general population. The sample consisted of 1015 individuals interviewed by telephone. A vignette describing someone with schizophrenia was read, and four stigma aspects regarding this hypothetical individual were assessed: stereotypes, restrictions, perceived prejudice and social distance. Latent profile analysis searched for stigma profiles among the sample. Multinomial logistic regression was used to find correlates of each class. Four stigma profiles were found; 'no stigma' individuals (n = 251) mostly displayed positive opinions. 'Labelers' (n = 222) scored high on social distance; they more often had familial contact with mental illness and more often labeled the vignette's disorder as schizophrenia. 'Discriminators', the group with the majority of individuals (n = 302), showed high levels of stigmatizing beliefs in all dimensions; discriminators were significantly older. 'Unobtrusive stigma' individuals (n = 240) seemed to demonstrate uncertainty or low commitment since they mostly answered items with the middle/impartial option. Some findings from the international literature were replicated; however, familial contact increased stigma, possibly denoting a locally modulated determinant. Hereby, our study also adds important cross-cultural data by showing that stigma toward schizophrenia is high in a Latin-American setting. We highlight the importance of analyzing the general population as a heterogeneous group, aiming to better elaborate anti-stigma campaigns. © The Author(s) 2013.

  13. Cross-Language Plagiarism Detection System Using Latent Semantic Analysis and Learning Vector Quantization

    Directory of Open Access Journals (Sweden)

    Anak Agung Putri Ratna

    2017-06-01

    Full Text Available Computerized cross-language plagiarism detection has recently become essential. With the scarcity of scientific publications in Bahasa Indonesia, many Indonesian authors frequently consult publications in English in order to boost the quantity of scientific publications in Bahasa Indonesia (which is currently rising. Due to the syntax disparity between Bahasa Indonesia and English, most of the existing methods for automated cross-language plagiarism detection do not provide satisfactory results. This paper analyses the probability of developing Latent Semantic Analysis (LSA for a computerized cross-language plagiarism detector for two languages with different syntax. To improve performance, various alterations in LSA are suggested. By using a linear vector quantization (LVQ classifier in the LSA and taking into account the Frobenius norm, output has reached up to 65.98% in accuracy. The results of the experiments showed that the best accuracy achieved is 87% with a document size of 6 words, and the document definition size must be kept below 10 words in order to maintain high accuracy. Additionally, based on experimental results, this paper suggests utilizing the frequency occurrence method as opposed to the binary method for the term–document matrix construction.

  14. Patterns of client behavior with their most recent male escort: an application of latent class analysis.

    Science.gov (United States)

    Grov, Christian; Starks, Tyrel J; Wolff, Margaret; Smith, Michael D; Koken, Juline A; Parsons, Jeffrey T

    2015-05-01

    Research examining interactions between male escorts and clients has relied heavily on data from escorts, men working on the street, and behavioral data aggregated over time. In the current study, 495 clients of male escorts answered questions about sexual behavior with their last hire. Latent class analysis identified four client sets based on these variables. The largest (n = 200, 40.4 %, labeled Typical Escort Encounter) included men endorsing behavior prior research found typical of paid encounters (e.g., oral sex and kissing). The second largest class (n = 157, 31.7 %, Typical Escort Encounter + Erotic Touching) included men reporting similar behaviors, but with greater variety along a spectrum of touching (e.g., mutual masturbation and body worship). Those classed BD/SM and Kink (n = 76, 15.4 %) reported activity along the kink spectrum (BD/SM and role play). Finally, men classed Erotic Massage Encounters (n = 58, 11.7 %) primarily engaged in erotic touch. Clients reporting condomless anal sex were in the minority (12.2 % overall). Escorts who engage in anal sex with clients might be appropriate to train in HIV prevention and other harm reduction practices-adopting the perspective of "sex workers as sex educators."

  15. PTSD symptom severity and psychiatric comorbidity in recent motor vehicle accident victims: a latent class analysis.

    Science.gov (United States)

    Hruska, Bryce; Irish, Leah A; Pacella, Maria L; Sledjeski, Eve M; Delahanty, Douglas L

    2014-10-01

    We conducted a latent class analysis (LCA) on 249 recent motor vehicle accident (MVA) victims to examine subgroups that differed in posttraumatic stress disorder (PTSD) symptom severity, current major depressive disorder and alcohol/other drug use disorders (MDD/AoDs), gender, and interpersonal trauma history 6-weeks post-MVA. A 4-class model best fit the data with a resilient class displaying asymptomatic PTSD symptom levels/low levels of comorbid disorders; a mild psychopathology class displaying mild PTSD symptom severity and current MDD; a moderate psychopathology class displaying severe PTSD symptom severity and current MDD/AoDs; and a severe psychopathology class displaying extreme PTSD symptom severity and current MDD. Classes also differed with respect to gender composition and history of interpersonal trauma experience. These findings may aid in the development of targeted interventions for recent MVA victims through the identification of subgroups distinguished by different patterns of psychiatric problems experienced 6-weeks post-MVA. Copyright © 2014 Elsevier Ltd. All rights reserved.

  16. Thermal Analysis of Fluidized Bed and Fixed Bed Latent Heat Thermal Storage System

    Science.gov (United States)

    Beemkumar, N.; Karthikeyan, A.; Shiva Keshava Reddy, Kota; Rajesh, Kona; Anderson, A.

    2017-05-01

    Thermal energy storage technology is essential because its stores available energy at low cost. Objective of the work is to store the thermal energy in a most efficient method. This work is deal with thermal analysis of fluidized bed and fixed bed latent heat thermal storage (LHTS) system with different encapsulation materials (aluminium, brass and copper). D-Mannitol has been used as phase change material (PCM). Encapsulation material which is in orbicular shape with 4 inch diameter and 2 mm thickness orbicular shaped product is used. Therminol-66 is used as a heat transfer fluid (HTF). Arrangement of encapsulation material is done in two ways namely fluidized bed and fixed bed thermal storage system. Comparison was made between the performance of fixed bed and fluidized bed with different encapsulation material. It is observed that from the economical point of view aluminium in fluidized bed LHTS System has highest efficiency than copper and brass. The thermal energy storage system can be analyzed with fixed bed by varying mass flow rate of oil paves a way to find effective heat energy transfer.

  17. Latent profile analysis and principal axis factoring of the DSM-5 dissociative subtype

    Directory of Open Access Journals (Sweden)

    Paul A. Frewen

    2015-04-01

    Full Text Available Objective: A dissociative subtype has been recognized based on the presence of experiences of depersonalization and derealization in relation to DSM-IV posttraumatic stress disorder (PTSD. However, the dissociative subtype has not been assessed in a community sample in relation to the revised DSM-5 PTSD criteria. Moreover, the 20-item PTSD Checklist for DSM-5 (PCL-5 currently does not assess depersonalization and derealization. Method: We therefore evaluated two items for assessing depersonalization and derealization in 557 participants recruited online who endorsed PTSD symptoms of at least moderate severity on the PCL-5. Results: A five-class solution identified two PTSD classes who endorsed dissociative experiences associated with either 1 severe or 2 moderate PTSD symptom severity (D-PTSD classes. Those in the severe dissociative class were particularly likely to endorse histories of childhood physical and sexual abuse. A principal axis factor analysis of the symptom list identified six latent variables: 1 Reexperiencing, 2 Emotional Numbing/Anhedonia, 3 Dissociation, 4 Negative Alterations in Cognition & Mood, 5 Avoidance, and 6 Hyperarousal. Conclusions: The present results further support the presence of a dissociative subtype within the DSM-5 criteria for PTSD.

  18. Latent profile analysis and principal axis factoring of the DSM-5 dissociative subtype.

    Science.gov (United States)

    Frewen, Paul A; Brown, Matthew F D; Steuwe, Carolin; Lanius, Ruth A

    2015-01-01

    A dissociative subtype has been recognized based on the presence of experiences of depersonalization and derealization in relation to DSM-IV posttraumatic stress disorder (PTSD). However, the dissociative subtype has not been assessed in a community sample in relation to the revised DSM-5 PTSD criteria. Moreover, the 20-item PTSD Checklist for DSM-5 (PCL-5) currently does not assess depersonalization and derealization. We therefore evaluated two items for assessing depersonalization and derealization in 557 participants recruited online who endorsed PTSD symptoms of at least moderate severity on the PCL-5. A five-class solution identified two PTSD classes who endorsed dissociative experiences associated with either 1) severe or 2) moderate PTSD symptom severity (D-PTSD classes). Those in the severe dissociative class were particularly likely to endorse histories of childhood physical and sexual abuse. A principal axis factor analysis of the symptom list identified six latent variables: 1) Reexperiencing, 2) Emotional Numbing/Anhedonia, 3) Dissociation, 4) Negative Alterations in Cognition & Mood, 5) Avoidance, and 6) Hyperarousal. The present results further support the presence of a dissociative subtype within the DSM-5 criteria for PTSD.

  19. A latent class analysis of cancer risk behaviors among U.S. college students.

    Science.gov (United States)

    Kang, Joseph; Ciecierski, Christina Czart; Malin, Emily L; Carroll, Allison J; Gidea, Marian; Craft, Lynette L; Spring, Bonnie; Hitsman, Brian

    2014-07-01

    The purpose of this study is to understand how cancer risk behaviors cluster in U.S. college students and vary by race and ethnicity. Using the fall 2010 wave of the National College Health Assessment (NCHA), we conducted a latent class analysis (LCA) to evaluate the clustering of cancer risk behaviors/conditions: tobacco use, physical inactivity, unhealthy diet, alcohol binge drinking, and overweight/obesity. The identified clusters were then examined separately by students' self-reported race and ethnicity. Among 30,093 college students surveyed, results show a high prevalence of unhealthy diet as defined by insufficient fruit and vegetable intake (>95%) and physical inactivity (>60%). The LCA identified behavioral clustering for the entire sample and distinct clustering among Black and American Indian students. Cancer risk behaviors/conditions appear to cluster among college students differentially by race. Understanding how risk behaviors cluster in young adults can lend insight to racial disparities in cancer through adulthood. Health behavior interventions focused on modifying multiple risk behaviors and tailored to students' racial group could potentially have a much larger effect on cancer prevention than those targeting any single behavior. Copyright © 2014 Elsevier Inc. All rights reserved.

  20. Service Usage Typologies in a Clinical Sample of Trauma-Exposed Adolescents: A Latent Class Analysis.

    Science.gov (United States)

    Choi, Kristen R; Briggs, Ernestine C; Seng, Julia S; Graham-Bermann, Sandra A; Munro-Kramer, Michelle L; Ford, Julian D

    2017-11-27

    The purpose of this study is to describe typologies of service utilization among trauma-exposed, treatment-seeking adolescents and to examine associations between trauma history, trauma-related symptoms, demographics, and service utilization. Latent class analysis was used to derive a service utilization typologies based on 10 service variables using a sample of 3,081 trauma-exposed adolescents ages 12 to 16 from the National Child Traumatic Stress Network Core Dataset. Services used 30 days prior to the initial assessment from 5 sectors were examined (health care, mental health, school, social services, and juvenile justice). A 5-class model was selected based on statistical fit indices and substantive evaluation of classes: (a) High intensity/multisystem, 9.5%; (b) Justice-involved, 7.2%; (c) Low intensity/multisystem, 19.9%; (d) Social service and mental health, 19.9%; and (e) Low service usage/reference, 43.5%. The classes could be differentiated based on cumulative trauma, maltreatment history, PTSD, externalizing and internalizing symptoms, and age, gender, race/ethnicity and place of residence. This study provides new evidence about patterns of service utilization by trauma exposed, treatment seeking adolescents. Most of these adolescents appear to be involved with at least 2 service systems prior to seeking trauma treatment. Higher cumulative exposure to multiple types of trauma was associated with greater service utilization intensity and complexity, but trauma symptomatology was not. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  1. Latent physiological factors of complex human diseases revealed by independent component analysis of clinarrays

    Directory of Open Access Journals (Sweden)

    Chen David P

    2010-10-01

    Full Text Available Abstract Background Diagnosis and treatment of patients in the clinical setting is often driven by known symptomatic factors that distinguish one particular condition from another. Treatment based on noticeable symptoms, however, is limited to the types of clinical biomarkers collected, and is prone to overlooking dysfunctions in physiological factors not easily evident to medical practitioners. We used a vector-based representation of patient clinical biomarkers, or clinarrays, to search for latent physiological factors that underlie human diseases directly from clinical laboratory data. Knowledge of these factors could be used to improve assessment of disease severity and help to refine strategies for diagnosis and monitoring disease progression. Results Applying Independent Component Analysis on clinarrays built from patient laboratory measurements revealed both known and novel concomitant physiological factors for asthma, types 1 and 2 diabetes, cystic fibrosis, and Duchenne muscular dystrophy. Serum sodium was found to be the most significant factor for both type 1 and type 2 diabetes, and was also significant in asthma. TSH3, a measure of thyroid function, and blood urea nitrogen, indicative of kidney function, were factors unique to type 1 diabetes respective to type 2 diabetes. Platelet count was significant across all the diseases analyzed. Conclusions The results demonstrate that large-scale analyses of clinical biomarkers using unsupervised methods can offer novel insights into the pathophysiological basis of human disease, and suggest novel clinical utility of established laboratory measurements.

  2. Word maturity indices with latent semantic analysis: why, when, and where is Procrustes rotation applied?

    Science.gov (United States)

    Jorge-Botana, Guillermo; Olmos, Ricardo; Luzón, José M

    2018-01-01

    The aim of this paper is to describe and explain one useful computational methodology to model the semantic development of word representation: Word maturity. In particular, the methodology is based on the longitudinal word monitoring created by Kirylev and Landauer using latent semantic analysis for the representation of lexical units. The paper is divided into two parts. First, the steps required to model the development of the meaning of words are explained in detail. We describe the technical and theoretical aspects of each step. Second, we provide a simple example of application of this methodology with some simple tools that can be used by applied researchers. This paper can serve as a user-friendly guide for researchers interested in modeling changes in the semantic representations of words. Some current aspects of the technique and future directions are also discussed. WIREs Cogn Sci 2018, 9:e1457. doi: 10.1002/wcs.1457 This article is categorized under: Computer Science > Natural Language Processing Linguistics > Language Acquisition Psychology > Development and Aging. © 2017 Wiley Periodicals, Inc.

  3. Validating Quantitative Measurement Using Qualitative Data: Combining Rasch Scaling and Latent Semantic Analysis in Psychiatry

    Science.gov (United States)

    Lange, Rense

    2015-02-01

    An extension of concurrent validity is proposed that uses qualitative data for the purpose of validating quantitative measures. The approach relies on Latent Semantic Analysis (LSA) which places verbal (written) statements in a high dimensional semantic space. Using data from a medical / psychiatric domain as a case study - Near Death Experiences, or NDE - we established concurrent validity by connecting NDErs qualitative (written) experiential accounts with their locations on a Rasch scalable measure of NDE intensity. Concurrent validity received strong empirical support since the variance in the Rasch measures could be predicted reliably from the coordinates of their accounts in the LSA derived semantic space (R2 = 0.33). These coordinates also predicted NDErs age with considerable precision (R2 = 0.25). Both estimates are probably artificially low due to the small available data samples (n = 588). It appears that Rasch scalability of NDE intensity is a prerequisite for these findings, as each intensity level is associated (at least probabilistically) with a well- defined pattern of item endorsements.

  4. Content Themes of Alcohol Advertising in U.S. Television-Latent Class Analysis.

    Science.gov (United States)

    Morgenstern, Matthis; Schoeppe, Franziska; Campbell, Julie; Braam, Marloes W G; Stoolmiller, Michael; Sargent, James D

    2015-09-01

    There is little alcohol research that reports on the thematic contents of contemporary alcohol advertisements in U.S. television. Studies of alcohol ads from 2 decades ago did not identify "Partying" as a social theme. Aim of this study was to describe and classify alcohol advertisements aired in national television in terms of contents, airing times, and channel placements and to identify different marketing strategies of alcohol brands. Content analysis of all ads from the top 20 U.S. beer and spirit brands aired between July 2009 and June 2011. These were 581 unique alcohol ads accounting for 272,828 (78%) national television airings. Ads were coded according to predefined definitions of 13 content areas. A latent class analysis (LCA) was conducted to define content cluster themes and determine alcoholic brands that were more likely to exploit these themes. About half of the advertisements (46%) were aired between 3 am and 8 pm, and the majority were placed either in Entertainment (40%) and Sports (38%) channels. Beer ads comprised 64% of the sample, with significant variation in airing times and channels between types of products and brands. LCA revealed 5 content classes that exploited the "Partying," "Quality," "Sports," "Manly," and "Relax" themes. The partying class, indicative of ad messages surrounding partying, love, and sex, was the dominant theme comprising 42% of all advertisements. Ads for alcopops, flavored spirits, and liqueur were more likely to belong to the party class, but there were also some beer brands (Corona, Heineken) where more than 67% of ads exploited this theme. This is the first analysis to identify a partying theme to contemporary alcohol advertising. Future analyses can now determine whether exposure to that or other themes predicts alcohol misuse among youth audiences. Copyright © 2015 by the Research Society on Alcoholism.

  5. Content Themes of Alcohol Advertising in US Television — Latent Class Analysis

    Science.gov (United States)

    Morgenstern, Matthis; Schoeppe, Franziska; Campbell, Julie; Braam, Marloes W.G.; Stoolmiller, Michael; Sargent, James D.

    2015-01-01

    Background There is little alcohol research that reports on the thematic contents of contemporary alcohol advertisements in US television. Studies of alcohol ads from two decades ago did not identify “partying” as a social theme. Aim of the present study was to describe and classify alcohol advertisements aired in national television in terms of contents, airing times, and channel placements and to identify different marketing strategies of alcohol brands. Methods Content analysis of all ads from the top 20 US beer and spirit brands aired between July 2009 and June 2011. These were 581 unique alcohol ads accounting for 272,828 (78%) national television airings. Ads were coded according to predefined definitions of 13 content areas. A latent class analysis (LCA) was conducted to define content cluster themes and determine alcoholic brands that were more likely to exploit these themes. Results About half of the advertisements (46%) were aired between 3am and 8pm, and the majority were placed either in Entertainment (40%) and Sports (38%) channels. Beer ads comprised 64% of the sample, with significant variation in airing times and channels between types of products and brands. LCA revealed five content classes that exploited the “Partying”, “Quality”, “Sports”, “Manly”, and “Relax” themes. The partying class, indicative of ad messages surrounding partying, love and sex, was the dominant theme, comprising 42% of all advertisements. Ads for alcopops, flavored spirits, and liqueur were more likely to belong to the party class, but there were also some beer brands (Corona, Heineken) where more than 67% of ads exploited this theme. Conclusions This is the first analysis to identify a partying theme to contemporary alcohol advertising. Future analyses can now determine whether exposure to that or other themes predicts alcohol misuse among youth audiences. PMID:26207317

  6. A latent profile analysis of childhood trauma in women with bulimia nervosa: Associations with borderline personality disorder psychopathology.

    Science.gov (United States)

    Utzinger, Linsey M; Haukebo, Justine E; Simonich, Heather; Wonderlich, Stephen A; Cao, Li; Lavender, Jason M; Mitchell, James E; Engel, Scott G; Crosby, Ross D

    2016-07-01

    The aim of this study was to empirically examine naturally occurring groups of individuals with bulimia nervosa (BN) based on their childhood trauma (CT) histories and to compare these groups on a clinically relevant external validator, borderline personality disorder (BPD) psychopathology. This study examined the relationship between CT and BPD psychopathology among 133 women with BN using latent profile analysis (LPA) to classify participants based on histories of CT. Participants completed the Structured Clinical Interview for DSM-IV Axis I Disorders (SCID-I/P), the Diagnostic Interview for Borderlines-Revised (DIB-R), and the Childhood Trauma Questionnaire (CTQ). The LPA revealed four trauma profiles: low/no trauma, emotional trauma, sexual trauma, and polytrauma. Results indicated that the sexual and polytrauma profiles displayed significantly elevated scores on the DIB-R and that the low/no and emotional trauma profiles did not differ significantly on the DIB-R. Secondary analyses revealed elevated levels of a composite CT score among those with both BN and BPD psychopathology compared to those with BN only. These findings suggest that both childhood sexual abuse and the additive effects of childhood polytrauma may be linked to BPD psychopathology in BN. © 2016 Wiley Periodicals, Inc. (Int J Eat Disord 2016; 49:689-694). © 2016 Wiley Periodicals, Inc.

  7. A Latent Class Analysis of Heterosexual Young Men’s Masculinities

    Science.gov (United States)

    Masters, N. Tatiana; Beadnell, Blair; Wells, Elizabeth A.; Morrison, Diane M.; Hoppe, Marilyn J.

    2015-01-01

    Parallel bodies of research have described the diverse and complex ways that men understand and construct their masculine identities (often termed“masculinities”) and, separately, how adherence to traditional notions of masculinity places men at risk for negative sexual and health outcomes. The goal of this analysis was to bring together these two streams of inquiry. Using data from a national, online sample of 555 hetero-sexually active young men, we employed latent class analysis (LCA) to detect patterns of masculine identities based on men’s endorsement of behavioral and attitudinal indicators of“dominant” masculinity, including sexual attitudes and behaviors. LCA identified four conceptually distinct masculine identity profiles. Twogroups, termed the Normative and Normative/Male Activities groups, respectively, constituted 88 % of the sample and were characterized by low levels of adherence to attitudes, sexual scripts, and behaviors consistent with“dominant”masculinity, but differed in their levels of engagement in male-oriented activities (e.g., sports teams). Only eight percent of the sample comprised a masculinity profile consistent with “traditional” ideas about masculinity; this group was labeled Misogynistic because of high levels of sexual assault and violence toward female partners. The remaining four percent constituted a Sex-Focused group, characterized by high numbers of sexual partners, but relatively low endorsement of other indicators of traditional masculinity. Follow-up analyses showed a small number of differences across groups on sexual and substance use health indicators. Findings have implications for sexual and behavioral health interventions and suggest that very few young men embody or endorse rigidly traditional forms of masculinity. PMID:26496914

  8. Evidence for proposed ICD-11 PTSD and complex PTSD: a latent profile analysis

    Directory of Open Access Journals (Sweden)

    Marylène Cloitre

    2013-05-01

    Full Text Available Background: The WHO International Classification of Diseases, 11th version (ICD-11, has proposed two related diagnoses, posttraumatic stress disorder (PTSD and complex PTSD within the spectrum of trauma and stress-related disorders. Objective: To use latent profile analysis (LPA to determine whether there are classes of individuals that are distinguishable according to the PTSD and complex PTSD symptom profiles and to identify potential differences in the type of stressor and severity of impairment associated with each profile. Method: An LPA and related analyses were conducted on 302 individuals who had sought treatment for interpersonal traumas ranging from chronic trauma (e.g., childhood abuse to single-incident events (e.g., exposure to 9/11 attacks. Results: The LPA revealed three classes of individuals: (1 a complex PTSD class defined by elevated PTSD symptoms as well as disturbances in three domains of self-organization: affective dysregulation, negative self-concept, and interpersonal problems; (2 a PTSD class defined by elevated PTSD symptoms but low scores on the three self-organization symptom domains; and (3 a low symptom class defined by low scores on all symptoms and problems. Chronic trauma was more strongly predictive of complex PTSD than PTSD and, conversely, single-event trauma was more strongly predictive of PTSD. In addition, complex PTSD was associated with greater impairment than PTSD. The LPA analysis was completed both with and without individuals with borderline personality disorder (BPD yielding identical results, suggesting the stability of these classes regardless of BPD comorbidity. Conclusion: Preliminary data support the proposed ICD-11 distinction between PTSD and complex PTSD and support the value of testing the clinical utility of this distinction in field trials. Replication of results is necessary.For the abstract or full text in other languages, please see Supplementary files under Article Tools online

  9. Alcohol Use as Risk Factors for Older Adults’ Emergency Department Visits: A Latent Class Analysis

    Directory of Open Access Journals (Sweden)

    Namkee G. Choi, PhD

    2015-12-01

    Full Text Available Introduction: Late middle-aged and older adults’ share of emergency department (ED visits is increasing more than other age groups. ED visits by individuals with substance-related problems are also increasing. This paper was intended to identify subgroups of individuals aged 50+ by their risk for ED visits by examining their health/mental health status and alcohol use patterns. Methods: Data came from the 2013 National Health Interview Survey’s Sample Adult file (n=15,713. Following descriptive analysis of sample characteristics by alcohol use patterns, latent class analysis (LCA modeling was fit using alcohol use pattern (lifetime abstainers, ex-drinkers, current infrequent/light/ moderate drinkers, and current heavy drinkers, chronic health and mental health status, and past-year ED visits as indicators. Results: LCA identified a four-class model. All members of Class 1 (35% of the sample; lowest-risk group were infrequent/light/moderate drinkers and exhibited the lowest probabilities of chronic health/ mental health problems; Class 2 (21%; low-risk group consisted entirely of lifetime abstainers and, despite being the oldest group, exhibited low probabilities of health/mental health problems; Class 3 (37%; moderate-risk group was evenly divided between ex-drinkers and heavy drinkers; and Class 4 (7%; high-risk group included all four groups of drinkers but more ex-drinkers. In addition, Class 4 had the highest probabilities of chronic health/mental problems, unhealthy behaviors, and repeat ED visits, with the highest proportion of Blacks and the lowest proportions of college graduates and employed persons, indicating significant roles of these risk factors. Conclusion: Alcohol nonuse/use (and quantity of use and chronic health conditions are significant contributors to varying levels of ED visit risk. Clinicians need to help heavy-drinking older adults reduce unhealthy alcohol consumption and help both heavy drinkers and ex

  10. Latent Cluster Analysis of Instructional Practices Reported by High- and Low-performing Mathematics Teachers in Four Countries

    OpenAIRE

    Cheng, Qiang; Hsu, Hsien-Yuan

    2017-01-01

    Using Trends in International Mathematics and Science Study (TIMSS) 2011 eighth-grade international dataset, this study explored the profiles of instructional practices reported by high- and low-performing mathematics teachers across the US, Finland, Korea, and Russia. Concepts of conceptual teaching and procedural teaching were used to frame the design of the current study. Latent cluster analysis was applied in the investigation of the profiles of mathematics teachers’ instructional practic...

  11. Narcissistic self-esteem or optimal self-esteem? A Latent Profile Analysis of self-esteem and psychological entitlement

    OpenAIRE

    Stronge, Sam; Cichocka, Aleksandra; Sibley, Chris G.

    2016-01-01

    Research into the relationship between self-esteem and narcissism has produced conflicting results, potentially caused by hidden subpopulations that exhibit distinct positive or negative associations. This research uses Latent Profile Analysis to identify profiles within a national panel study (N = 6,471) with differing relationships between psychological entitlement and self-esteem. We identified a narcissistic self-esteem profile (9%) characterised by high entitlement and high self-esteem, ...

  12. Structural equation modeling of latent growth curves of weight gain among treated tuberculosis patients.

    Directory of Open Access Journals (Sweden)

    Mahalingam Vasantha

    Full Text Available Tuberculosis still remains a major public health problem even though it is treatable and curable. Weight gain measurement during anti tuberculosis (TB treatment period is an important component to assess the progress of TB patients. In this study, Latent Growth Models (LGMs were implemented in a longitudinal design to predict the change in weight of TB patients who were given three different regimens under randomized controlled clinical trial for anti-TB treatment. Linear and Quadratic LGMs were fitted using Mplus software. The age, sex and treatment response of the TB patients were used as time invariant independent variables of the growth trajectories. The quadratic trend was found to be better in explaining the changes in weight without grouping than the quadratic model for three group comparisons. A significant increase in the change of weight over time was identified while a significant quadratic effect indicated that weights were sustained over time. The growth rate was similar in both the groups. The treatment response had significant association with the growth rate of weight scores of the patients.

  13. Latent semantics as cognitive components

    DEFF Research Database (Denmark)

    Petersen, Michael Kai; Mørup, Morten; Hansen, Lars Kai

    2010-01-01

    Cognitive component analysis, defined as an unsupervised learning of features resembling human comprehension, suggests that the sensory structures we perceive might often be modeled by reducing dimensionality and treating objects in space and time as linear mixtures incorporating sparsity...... emotional responses can be encoded in words, we propose a simplified cognitive approach to model how we perceive media. Representing song lyrics in a vector space of reduced dimensionality using LSA, we combine bottom-up defined term distances with affective adjectives, that top-down constrain the latent......, which we suggest might function as cognitive components for perceiving the underlying structure in lyrics....

  14. Attachment typologies and posttraumatic stress disorder (PTSD), depression and anxiety: a latent profile analysis approach.

    Science.gov (United States)

    Armour, Cherie; Elklit, Ask; Shevlin, Mark

    2011-01-01

    Bartholomew (1990) proposed a four category adult attachment model based on Bowlby's (1973) proposal that attachment is underpinned by an individual's view of the self and others. Previous cluster analytic techniques have identified four and two attachment styles based on the Revised Adult Attachment Scale (RAAS). In addition, attachment styles have been proposed to meditate the association between stressful life events and subsequent psychiatric status. The current study aimed to empirically test the attachment typology proposed by Collins and Read (1990). Specifically, LPA was used to determine if the proposed four styles can be derived from scores on the dimensions of closeness/dependency and anxiety. In addition, we aimed to test if the resultant attachment styles predicted the severity of psychopathology in response to a whiplash trauma. A large sample of Danish trauma victims (N=1577) participated. A Latent Profile Analysis was conducted, using Mplus 5.1, on scores from the RAAS scale to ascertain if there were underlying homogeneous attachment classes/subgroups. Class membership was used in a series of one-way ANOVA tests to determine if classes were significantly different in terms of mean scores on measures of psychopathology. The three class solution was considered optimal. Class one was termed Fearful (18.6%), Class two Preoccupied (34.5%), and Class three Secure (46.9%). The secure class evidenced significantly lower mean scores on PTSD, depression, and anxiety measures compared to other classes, whereas the fearful class evidenced significantly higher mean scores compared to other classes. The results demonstrated evidence of three discrete classes of attachment styles, which were labelled secure, preoccupied, and fearful. This is in contrast to previous cluster analytic techniques which have identified four and two attachment styles based on the RAAS.In addition, Securely attached individuals display lower levels of psychopathology post whiplash

  15. Latent class analysis of the feared situations of social anxiety disorder: A population-based study.

    Science.gov (United States)

    Peyre, Hugo; Hoertel, Nicolas; Rivollier, Fabrice; Landman, Benjamin; McMahon, Kibby; Chevance, Astrid; Lemogne, Cédric; Delorme, Richard; Blanco, Carlos; Limosin, Frédéric

    2016-12-01

    Little is known about differences in mental health comorbidity and quality of life in individuals with social anxiety disorder (SAD) according to the number and the types of feared situations. Using a US nationally representative sample, the National Epidemiologic Survey on Alcohol and Related Conditions, we performed latent class analysis to compare the prevalence rates of mental disorders and quality of life measures across classes defined by the number and the types of feared social situations among individuals with SAD. Among the 2,448 participants with a lifetime diagnosis of SAD, we identified three classes of individuals who feared most social situations but differed in the number of feared social situations (generalized severe [N = 378], generalized moderate [N = 1,049] and generalized low [N = 443]) and a class of subjects who feared only performance situations [N = 578]. The magnitude of associations between each class and a wide range of mental disorders and quality of life measures were consistent with a continuum model, supporting that the deleterious effects of SAD on mental health may increase with the number of social situations feared. However, we found that individuals with the "performance only" specifier may constitute an exception to this model because these participants had significantly better mental health than other participants with SAD. Our findings give additional support to the recent changes made in the DSM-5, including the introduction of the "performance only" specifier and the removal of the "generalized" specifier to promote the dimensional approach of the number of social fears. © 2016 Wiley Periodicals, Inc.

  16. Parent-Teen Communication and Pre-College Alcohol Involvement: A Latent Class Analysis

    Science.gov (United States)

    Abar, Caitlin C.; Fernandez, Anne C.; Wood, Mark D.

    2011-01-01

    Although parent-adolescent communication has been identified as important in delaying the onset and escalation of alcohol use, both the strength and direction of observed associations has varied in prior research with adolescents and college students. The current study categorizes parents according to alcohol-related communication and relates these categories to other parenting factors and late adolescent alcohol involvement. Method As part of a larger study, 1,007 college-bound teens and their parents were assessed. Teens were asked to report on their drinking behavior, and parents were asked about the occurrence of several specific alcohol-related communications with their teen, as well as additional parenting characteristics. Profiles of parent alcohol-related communication were derived using latent class analysis. Once the best fitting solution was determined, covariates were entered predicting class membership and investigating how classes were associated with additional parenting characteristics and teen alcohol use. Results A five-class solution provided the best fit to the data: Frequent, All Topics (28%); Moderate, All Topics (25%); Frequent, General Topics (25%); Frequent, Consequences and Limits (12%); and Infrequent, All Topics (10%). Covariate analyses demonstrated class differences with regard to parental modeling, monitoring, knowledge, and parent-teen relationship satisfaction, as well as for students’ intentions to join fraternities/sororities and alcohol use. Conclusions Findings from the current study add to a small but growing literature supporting the continuing influence of parents in late adolescence and suggest that the frequency and specificity of parent-teen communication are potentially informative for refined parent-based preventive interventions. PMID:21864983

  17. Mindfulness and Psychological Health Outcomes: A Latent Profile Analysis among Military Personnel and College Students.

    Science.gov (United States)

    Bravo, Adrian J; Pearson, Matthew R; Kelley, Michelle L

    2018-02-01

    Previous research on trait mindfulness facets using person-centered analyses (e.g., latent profile analysis [LPA]) has identified four distinct mindfulness profiles among college students: a high mindfulness group (high on all facets of the Five-Factor Mindfulness Questionnaire [FFMQ]), a judgmentally observing group (highest on observing, but low on non-judging of inner experience and acting with awareness), a non-judgmentally aware group (high on non-judging of inner experience and acting with awareness, but very low on observing), and a low mindfulness group (low on all facets of the FFMQ). In the present study, we used LPA to identify distinct mindfulness profiles in a community based sample of U.S. military personnel (majority veterans; n = 407) and non-military college students ( n = 310) and compare these profiles on symptoms of psychological health outcomes (e.g., suicidality, PTSD, anxiety, rumination) and percentage of participants exceeding clinically significant cut-offs for depressive symptoms, substance use, and alcohol use. In the subsample of college students, we replicated previous research and found four distinct mindfulness profiles; however, in the military subsample we found three distinct mindfulness profiles (a combined low mindfulness/judgmentally observing class). In both subsamples, we found that the most adaptive profile was the "high mindfulness" profile (i.e., demonstrated the lowest scores on all psychological symptoms and the lowest probability of exceeding clinical cut-offs). Based on these findings, we purport that the comprehensive examination of an individual's mindfulness profile could help clinicians tailor interventions/treatments that capitalize on individual's specific strengths and work to address their specific deficits.

  18. Occurence of internet addiction in a general population sample: a latent class analysis.

    Science.gov (United States)

    Rumpf, Hans-Jürgen; Vermulst, Ad A; Bischof, Anja; Kastirke, Nadin; Gürtler, Diana; Bischof, Gallus; Meerkerk, Gert-Jan; John, Ulrich; Meyer, Christian

    2014-01-01

    Prevalence studies of Internet addiction in the general population are rare. In addition, a lack of approved criteria hampers estimation of its occurrence. This study conducted a latent class analysis (LCA) in a large general population sample to estimate prevalence. A telephone survey was conducted based on a random digit dialling procedure including landline telephone (n=14,022) and cell phone numbers (n=1,001) in participants aged 14-64. The Compulsive Internet Use Scale (CIUS) served as the basis for a LCA used to look for subgroups representing participants with Internet addiction or at-risk use. CIUS was given to participants reporting to use the Internet for private purposes at least 1 h on a typical weekday or at least 1 h on a day at the weekend (n=8,130). A 6-class model showed best model fit and included two groups likely to represent Internet addiction and at-risk Internet use. Both groups showed less social participation and the Internet addiction group less general trust in other people. Proportions of probable Internet addiction were 1.0% (CI 0.9-1.2) among the entire sample, 2.4% (CI 1.9-3.1) in the age group 14-24, and 4.0% (CI 2.7-5.7) in the age group 14-16. No difference in estimated proportions between males and females was found. Unemployment (OR 3.13; CI 1.74-5.65) and migration background (OR 3.04; CI 2.12-4.36) were related to Internet addiction. This LCA-based study differentiated groups likely to have Internet addiction and at-risk use in the general population and provides characteristics to further define this rather new disorder. © 2013 S. Karger AG, Basel.

  19. Patterns and predictors of posttraumatic stress disorder in refugees: A latent class analysis.

    Science.gov (United States)

    Minihan, Savannah; Liddell, Belinda J; Byrow, Yulisha; Bryant, Richard A; Nickerson, Angela

    2018-05-01

    Although elevated rates of posttraumatic stress disorder (PTSD) have been well-documented in refugees, no study has investigated the heterogeneity of DSM-5 PTSD symptomatology in such populations. This study aimed to determine whether there are unique patterns of DSM-5 defined PTSD symptomatology in refugees, and investigate whether factors characteristic of the refugee experience, including trauma exposure and post-migration stress, predict symptom profiles. Participants were 246 refugees and asylum-seekers from an Arabic-, English-, Farsi-, or Tamil-speaking background who had been resettled in Australia. Participants completed measures of post-migration living difficulties, trauma exposure, PTSD symptoms and functional disability. Latent class analysis was used to identify PTSD symptom profiles, and predictors of class membership were elucidated via multinomial logistic regression. Four classes were identified: a high-PTSD class (21.3%), a high-re-experiencing/avoidance class (15.3%), a moderate-PTSD class (23%), and a no PTSD class (40.3%). Trauma exposure and post-migration stress significantly predicted class membership and classes differed in degree of functional disability. The current study employed a cross-sectional design, which precluded inferences regarding the stability of classes of PTSD symptomatology. This study provides evidence for distinct patterns of PTSD symptomatology in refugees. We identified a novel class, characterized by high-re-experiencing and avoidance symptoms, as well as classes characterized by pervasive, moderate, and no symptomatology. Trauma exposure and post-migration stress differentially contributed to the emergence of these profiles. Individuals with high and moderate probability of PTSD symptoms evidenced substantial disability. These results support conceptualizations of PTSD as a heterogeneous construct, and highlight the importance of considering sub-clinical symptom presentations, as well as the post

  20. Subtypes of adolescent sedative/anxiolytic misusers: A latent profile analysis.

    Science.gov (United States)

    Hall, Martin T; Howard, Matthew O; McCabe, Sean Esteban

    2010-10-01

    Few empirically-based taxonomies of nonmedical prescription drug misusers have been published. This study used latent profile analysis (LPA) to identify classes of adolescent sedative/anxiolytic misusers. Interviews assessing substance use, psychiatric symptoms, antisocial traits/behavior, and traumatic life experiences were conducted with 723 Missouri youth in residential care for antisocial behavior. Sedative/anxiolytic misusers (N=247) averaged 15.8 (S.D.=1.1) years of age; a majority were male (83.8%), White (70.0%), and resided in rural/small town areas (53.8%). LPA yielded a three-class solution. Class 1 (59.1%) was comprised of youth with significantly lower levels of currently distressing psychiatric symptoms, fewer lifetime traumatic experiences, less problematic substance use histories, less frequent antisocial behavior, and less impulsivity than youth in Classes 2 and 3. Class 2 (11.3%) youth had high levels of currently distressing psychiatric symptoms and more frequent antisocial behavior compared to youth in Classes 1 and 3. Class 3 (29.5%) youth evidenced levels of psychiatric and behavioral problems that were intermediate to those of Class 1 and 2 youth. Frequency of sedative/anxiolytic misuse was significantly higher in Classes 2 and 3 compared to Class 1. Members of Class 2 and Class 3 also had the highest levels of psychiatric symptoms for which sedatives/anxiolytics are commonly prescribed. Significant differences between classes were observed across a range of health, mental health, personality, and behavioral variables. Adolescents who misused prescription sedatives/anxiolytics evidenced significant heterogeneity across measures of psychiatric and behavioral dysfunction. Youth with comparatively high levels of anxiety and depression reported significantly more intensive sedative/anxiolytic misuse than their counterparts and may be at high risk for sedative/anxiolytic abuse and dependence. 2010 Elsevier Ltd. All rights reserved.

  1. Voluntary climate change mitigation actions of young adults: a classification of mitigators through latent class analysis.

    Science.gov (United States)

    Korkala, Essi A E; Hugg, Timo T; Jaakkola, Jouni J K

    2014-01-01

    Encouraging individuals to take action is important for the overall success of climate change mitigation. Campaigns promoting climate change mitigation could address particular groups of the population on the basis of what kind of mitigation actions the group is already taking. To increase the knowledge of such groups performing similar mitigation actions we conducted a population-based cross-sectional study in Finland. The study population comprised 1623 young adults who returned a self-administered questionnaire (response rate 64%). Our aims were to identify groups of people engaged in similar climate change mitigation actions and to study the gender differences in the grouping. We also determined if socio-demographic characteristics can predict group membership. We performed latent class analysis using 14 mitigation actions as manifest variables. Three classes were identified among men: the Inactive (26%), the Semi-active (63%) and the Active (11%) and two classes among women: the Semi-active (72%) and the Active (28%). The Active among both genders were likely to have mitigated climate change through several actions, such as recycling, using environmentally friendly products, preferring public transport, and conserving energy. The Semi-Active had most probably recycled and preferred public transport because of climate change. The Inactive, a class identified among men only, had very probably done nothing to mitigate climate change. Among males, being single or divorced predicted little involvement in climate change mitigation. Among females, those without tertiary degree and those with annual income €≥16801 were less involved in climate change mitigation. Our results illustrate to what extent young adults are engaged in climate change mitigation, which factors predict little involvement in mitigation and give insight to which segments of the public could be the audiences of targeted mitigation campaigns.

  2. Voluntary climate change mitigation actions of young adults: a classification of mitigators through latent class analysis.

    Directory of Open Access Journals (Sweden)

    Essi A E Korkala

    Full Text Available Encouraging individuals to take action is important for the overall success of climate change mitigation. Campaigns promoting climate change mitigation could address particular groups of the population on the basis of what kind of mitigation actions the group is already taking. To increase the knowledge of such groups performing similar mitigation actions we conducted a population-based cross-sectional study in Finland. The study population comprised 1623 young adults who returned a self-administered questionnaire (response rate 64%. Our aims were to identify groups of people engaged in similar climate change mitigation actions and to study the gender differences in the grouping. We also determined if socio-demographic characteristics can predict group membership. We performed latent class analysis using 14 mitigation actions as manifest variables. Three classes were identified among men: the Inactive (26%, the Semi-active (63% and the Active (11% and two classes among women: the Semi-active (72% and the Active (28%. The Active among both genders were likely to have mitigated climate change through several actions, such as recycling, using environmentally friendly products, preferring public transport, and conserving energy. The Semi-Active had most probably recycled and preferred public transport because of climate change. The Inactive, a class identified among men only, had very probably done nothing to mitigate climate change. Among males, being single or divorced predicted little involvement in climate change mitigation. Among females, those without tertiary degree and those with annual income €≥16801 were less involved in climate change mitigation. Our results illustrate to what extent young adults are engaged in climate change mitigation, which factors predict little involvement in mitigation and give insight to which segments of the public could be the audiences of targeted mitigation campaigns.

  3. Distinct patterns of Internet and smartphone-related problems among adolescents by gender: Latent class analysis.

    Science.gov (United States)

    Lee, Seung-Yup; Lee, Donghwan; Nam, Cho Rong; Kim, Da Yea; Park, Sera; Kwon, Jun-Gun; Kweon, Yong-Sil; Lee, Youngjo; Kim, Dai Jin; Choi, Jung-Seok

    2018-05-23

    Background and objectives The ubiquitous Internet connections by smartphones weakened the traditional boundaries between computers and mobile phones. We sought to explore whether smartphone-related problems differ from those of computer use according to gender using latent class analysis (LCA). Methods After informed consents, 555 Korean middle-school students completed surveys on gaming, Internet use, and smartphone usage patterns. They also completed various psychosocial instruments. LCA was performed for the whole group and by gender. In addition to ANOVA and χ 2 tests, post-hoc tests were conducted to examine differences among the LCA subgroups. Results In the whole group (n = 555), four subtypes were identified: dual-problem users (49.5%), problematic Internet users (7.7%), problematic smartphone users (32.1%), and "healthy" users (10.6%). Dual-problem users scored highest for addictive behaviors and other psychopathologies. The gender-stratified LCA revealed three subtypes for each gender. With dual-problem and healthy subgroup as common, problematic Internet subgroup was classified in the males, whereas problematic smartphone subgroup was classified in the females in the gender-stratified LCA. Thus, distinct patterns were observed according to gender with higher proportion of dual-problem present in males. While gaming was associated with problematic Internet use in males, aggression and impulsivity demonstrated associations with problematic smartphone use in females. Conclusions An increase in the number of digital media-related problems was associated with worse outcomes in various psychosocial scales. Gaming may play a crucial role in males solely displaying Internet-related problems. The heightened impulsivity and aggression seen in our female problematic smartphone users requires further research.

  4. Attachment typologies and posttraumatic stress disorder (PTSD), depression and anxiety: a latent profile analysis approach

    Science.gov (United States)

    Armour, Cherie; Elklit, Ask; Shevlin, Mark

    2011-01-01

    Background Bartholomew (1990) proposed a four category adult attachment model based on Bowlby's (1973) proposal that attachment is underpinned by an individual's view of the self and others. Previous cluster analytic techniques have identified four and two attachment styles based on the Revised Adult Attachment Scale (RAAS). In addition, attachment styles have been proposed to meditate the association between stressful life events and subsequent psychiatric status. Objective The current study aimed to empirically test the attachment typology proposed by Collins and Read (1990). Specifically, LPA was used to determine if the proposed four styles can be derived from scores on the dimensions of closeness/dependency and anxiety. In addition, we aimed to test if the resultant attachment styles predicted the severity of psychopathology in response to a whiplash trauma. Method A large sample of Danish trauma victims (N=1577) participated. A Latent Profile Analysis was conducted, using Mplus 5.1, on scores from the RAAS scale to ascertain if there were underlying homogeneous attachment classes/subgroups. Class membership was used in a series of one-way ANOVA tests to determine if classes were significantly different in terms of mean scores on measures of psychopathology. Results The three class solution was considered optimal. Class one was termed Fearful (18.6%), Class two Preoccupied (34.5%), and Class three Secure (46.9%). The secure class evidenced significantly lower mean scores on PTSD, depression, and anxiety measures compared to other classes, whereas the fearful class evidenced significantly higher mean scores compared to other classes. Conclusions The results demonstrated evidence of three discrete classes of attachment styles, which were labelled secure, preoccupied, and fearful. This is in contrast to previous cluster analytic techniques which have identified four and two attachment styles based on the RAAS.In addition, Securely attached individuals display

  5. Attachment typologies and posttraumatic stress disorder (PTSD, depression and anxiety: a latent profile analysis approach

    Directory of Open Access Journals (Sweden)

    Cherie Armour

    2011-12-01

    Full Text Available Bartholomew (1990 proposed a four category adult attachment model based on Bowlby's (1973 proposal that attachment is underpinned by an individual's view of the self and others. Previous cluster analytic techniques have identified four and two attachment styles based on the Revised Adult Attachment Scale (RAAS. In addition, attachment styles have been proposed to meditate the association between stressful life events and subsequent psychiatric status. The current study aimed to empirically test the attachment typology proposed by Collins and Read (1990. Specifically, LPA was used to determine if the proposed four styles can be derived from scores on the dimensions of closeness/dependency and anxiety. In addition, we aimed to test if the resultant attachment styles predicted the severity of psychopathology in response to a whiplash trauma. A large sample of Danish trauma victims (N=1577 participated. A Latent Profile Analysis was conducted, using Mplus 5.1, on scores from the RAAS scale to ascertain if there were underlying homogeneous attachment classes/subgroups. Class membership was used in a series of one-way ANOVA tests to determine if classes were significantly different in terms of mean scores on measures of psychopathology. The three class solution was considered optimal. Class one was termed Fearful (18.6%, Class two Preoccupied (34.5%, and Class three Secure (46.9%. The secure class evidenced significantly lower mean scores on PTSD, depression, and anxiety measures compared to other classes, whereas the fearful class evidenced significantly higher mean scores compared to other classes. The results demonstrated evidence of three discrete classes of attachment styles, which were labelled secure, preoccupied, and fearful. This is in contrast to previous cluster analytic techniques which have identified four and two attachment styles based on the RAAS.In addition, Securely attached individuals display lower levels of psychopathology post

  6. A latent class analysis of poly-marijuana use among young adults.

    Science.gov (United States)

    Krauss, Melissa J; Rajbhandari, Biva; Sowles, Shaina J; Spitznagel, Edward L; Cavazos-Rehg, Patricia

    2017-12-01

    With more states legalizing marijuana use, the marijuana industry has grown, introducing a variety of marijuana products. Our study explores the use of multiple marijuana products (poly-marijuana use) and the characteristics associated with this behavior. Past-month marijuana users aged 18-34years were surveyed online via an existing online panel (n=2444). Participants answered questions about past-month use of three types of marijuana (plant-based, concentrates, edibles), marijuana use patterns, and driving after use. Latent class analysis was used to identify subgroups of marijuana users. Four classes of marijuana users were identified: Light plant users, who used only plant-based products infrequently and were unlikely to drive after use (32%); Heavy plant users, who used mainly plant-based products frequently, multiple times per day, and were likely to drive after use (37%); Plant and concentrates users, who used plant-based products heavily and concentrates at least infrequently, used multiple times per day, and were likely to drive after use (20%); Light plant and edibles users, who used both products infrequently and were unlikely to drive after use (10%). Those in legal marijuana states were more likely to belong to the poly-marijuana groups. Our findings reflect the increase in popularity of new marijuana products in legal states and suggest that heavy user groups, including concentrates users, are associated with driving after use. As various forms of marijuana use increases, monitoring and surveillance of the use of multiple types of marijuana will be important for determining potential varying impacts on physiological and social consequences. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. Time course of neck-shoulder pain among workers: A longitudinal latent class growth analysis.

    Science.gov (United States)

    Hallman, David M; Rasmussen, Charlotte D Nørregaard; Jørgensen, Marie Birk; Holtermann, Andreas

    2018-01-01

    Objectives The aims of this study were to (i) identify trajectories of neck-shoulder pain (NSP) over one year in an occupational population and (ii) determine whether these trajectories are predicted by NSP characteristics as well as personal and occupational factors at baseline. Methods This longitudinal study was conducted among Danish workers (N=748) from 2012-2014. Text messages were used to collect frequent data on NSP over one year (14 waves in total). Peak NSP intensity in the past month was rated on a 0-10 numeric scale. A baseline questionnaire covered NSP characteristics (pain intensity, duration, comorbidity, pain medication, and pain interference) as well as personal (age, gender, body mass index) and occupational (seniority, work type, physical strain at work) factors. Latent class growth analysis was used to distinguish trajectories of NSP. Multivariate regression models with odds ratios (OR) were constructed to predict trajectories of NSP. Results Six distinct trajectories of NSP were identified (asymptomatic 11%, very low NSP 10%, low recovering NSP 18%, moderate recovering NSP 28%, strong fluctuating NSP 24% and severe persistent NSP 9% of the workers). Female gender, age, physical strain at work, NSP intensity and duration, pain medication, and pain interference in daily work at baseline were positively associated with severe persistent NSP and strong fluctuating NSP (all P<0.05). Altogether, personal and occupational factors accounted for 14% of the variance, while NSP characteristics accounted for 54%. Conclusions In an occupational sample, six distinct trajectories of NSP were identified. Physical strain at work appears to be a pertinent occupational factor predicting strong fluctuating and severe persistent NSP.

  8. Nonsuicidal Self-Injury and Suicidal Behavior: A Latent Class Analysis among Young Adults

    Science.gov (United States)

    Hamza, Chloe A.; Willoughby, Teena

    2013-01-01

    Although there is a general consensus among researchers that engagement in nonsuicidal self-injury (NSSI) is associated with increased risk for suicidal behavior, little attention has been given to whether suicidal risk varies among individuals engaging in NSSI. To identify individuals with a history of NSSI who are most at risk for suicidal behavior, we examined individual variability in both NSSI and suicidal behavior among a sample of young adults with a history of NSSI (N = 439, Mage = 19.1). Participants completed self-report measures assessing NSSI, suicidal behavior, and psychosocial adjustment (e.g., depressive symptoms, daily hassles). We conducted a latent class analysis using several characteristics of NSSI and suicidal behaviors as class indicators. Three subgroups of individuals were identified: 1) an infrequent NSSI/not high risk for suicidal behavior group, 2) a frequent NSSI/not high risk for suicidal behavior group, and 3) a frequent NSSI/high risk for suicidal behavior group. Follow-up analyses indicated that individuals in the ‘frequent NSSI/high risk for suicidal behavior’ group met the clinical-cut off score for high suicidal risk and reported significantly greater levels of suicidal ideation, attempts, and risk for future suicidal behavior as compared to the other two classes. Thus, this study is the first to identity variability in suicidal risk among individuals engaging in frequent and multiple methods of NSSI. Class 3 was also differentiated by higher levels of psychosocial impairment relative to the other two classes, as well as a comparison group of non-injuring young adults. Results underscore the importance of assessing individual differences in NSSI characteristics, as well as psychosocial impairment, when assessing risk for suicidal behavior. PMID:23544113

  9. Family income trajectory during childhood is associated with adiposity in adolescence: a latent class growth analysis.

    Science.gov (United States)

    Kendzor, Darla E; Caughy, Margaret O; Owen, Margaret Tresch

    2012-08-05

    Childhood socioeconomic disadvantage has been linked with obesity in cross-sectional research, although less is known about how changes in socioeconomic status influence the development of obesity. Researchers have hypothesized that upward socioeconomic mobility may attenuate the health effects of earlier socioeconomic disadvantage; while downward socioeconomic mobility might have a negative influence on health despite relative socioeconomic advantages at earlier stages. The purpose of the current study was to characterize trajectories of family income during childhood, and to evaluate the influence of these trajectories on adiposity at age 15. Data were collected as part of the Study of Early Child Care and Youth Development (SECCYD) between 1991 and 2007 at 10 sites across the United States. A latent class growth analysis (LCGA) was conducted to identify trajectories of family income from birth to 15 years of age. Analyses of covariance (ANCOVAs) were conducted to determine whether measures of adiposity differed by trajectory, while controlling for relevant covariates. The LCGA supported a 5-class trajectory model, which included two stable, one downward, and two upward trajectories. ANCOVAs indicated that BMI percentile, waist circumference, and skinfold thicknesses at age 15 differed significantly by trajectory, such that those who experienced downward mobility or stable low income had greater adiposity relative to the more advantaged trajectories. Conversely, upwardly mobile children and those with consistently adequate incomes had similar and more positive outcomes relative to the most disadvantaged trajectories. Findings suggest that promoting upward socioeconomic mobility among disadvantaged families may have a positive impact on obesity-related outcomes in adolescence.

  10. Family income trajectory during childhood is associated with adiposity in adolescence: a latent class growth analysis

    Directory of Open Access Journals (Sweden)

    Kendzor Darla E

    2012-08-01

    Full Text Available Abstract Background Childhood socioeconomic disadvantage has been linked with obesity in cross-sectional research, although less is known about how changes in socioeconomic status influence the development of obesity. Researchers have hypothesized that upward socioeconomic mobility may attenuate the health effects of earlier socioeconomic disadvantage; while downward socioeconomic mobility might have a negative influence on health despite relative socioeconomic advantages at earlier stages. The purpose of the current study was to characterize trajectories of family income during childhood, and to evaluate the influence of these trajectories on adiposity at age 15. Methods Data were collected as part of the Study of Early Child Care and Youth Development (SECCYD between 1991 and 2007 at 10 sites across the United States. A latent class growth analysis (LCGA was conducted to identify trajectories of family income from birth to 15 years of age. Analyses of covariance (ANCOVAs were conducted to determine whether measures of adiposity differed by trajectory, while controlling for relevant covariates. Results The LCGA supported a 5-class trajectory model, which included two stable, one downward, and two upward trajectories. ANCOVAs indicated that BMI percentile, waist circumference, and skinfold thicknesses at age 15 differed significantly by trajectory, such that those who experienced downward mobility or stable low income had greater adiposity relative to the more advantaged trajectories. Conversely, upwardly mobile children and those with consistently adequate incomes had similar and more positive outcomes relative to the most disadvantaged trajectories. Conclusions Findings suggest that promoting upward socioeconomic mobility among disadvantaged families may have a positive impact on obesity-related outcomes in adolescence.

  11. Longitudinal burnout-collaboration patterns in Japanese medical care workers at special needs schools: a latent class growth analysis

    Science.gov (United States)

    Kanayama, Mieko; Suzuki, Machiko; Yuma, Yoshikazu

    2016-01-01

    The present study aimed to identify and characterize potential burnout types and the relationship between burnout and collaboration over time. Latent class growth analysis and the growth mixture model were used to identify and characterize heterogeneous patterns of longitudinal stability and change in burnout, and the relationship between burnout and collaboration. We collected longitudinal data at three time points based on Japanese academic terms. The 396 study participants included academic teachers, yogo teachers, and registered nurses in Japanese special needs schools. The best model included four types of both burnout and collaboration in latent class growth analysis with intercept, slope, and quadratic terms. The four types of burnout were as follows: low stable, moderate unstable, high unstable, and high decreasing. They were identified as involving inverse collaboration function. The results indicated that there could be dynamic burnout types, namely moderate unstable, high unstable, and high decreasing, when focusing on growth trajectories in latent class analyses. The finding that collaboration was dynamic for dynamic burnout types and stable for stable burnout types is of great interest. This was probably related to the inverse relationship between the two constructs. PMID:27366107

  12. The Latent Curve ARMA (P, Q) Panel Model: Longitudinal Data Analysis in Educational Research and Evaluation

    Science.gov (United States)

    Sivo, Stephen; Fan, Xitao

    2008-01-01

    Autocorrelated residuals in longitudinal data are widely reported as common to longitudinal data. Yet few, if any, researchers modeling growth processes evaluate a priori whether their data have this feature. Sivo, Fan, and Witta (2005) found that not modeling autocorrelated residuals present in longitudinal data severely biases latent curve…

  13. Capitalism and Crime in the Classroom: An Analysis of Academic Dishonesty and Latent Student Attitudes

    Science.gov (United States)

    Burrus, Robert T.; Jones, Adam T.; Schuhmann, Peter W.

    2016-01-01

    University students' latent attitudes toward capitalism were quantified and used to predict self-reported cheating behaviors. Results suggest that the relationship between student academic dishonesty and attitudes toward capitalism are complex. Students indicating a strong degree of risk aversion are less likely to report cheating behaviors.…

  14. Progression to dementia in memory clinic patients without dementia: a latent profile analysis

    NARCIS (Netherlands)

    Kohler, S.; Hamel, R.; Sistermans, N.; Koene, T.; Pijnenburg, Y.A.L.; van der Flier, W.M.; Scheltens, P.; Visser, P.J.; Aalten, P.; Verhey, F. R. J.; Ramakers, I.

    2013-01-01

    Objective: To identify the existence of discrete cognitive subtypes among memory clinic patients without dementia and test their prognostic values. Methods: In a retrospective cohort study of 635 patients without dementia visiting the Alzheimer centers in Maastricht or Amsterdam, latent profile

  15. Latent Profile Analysis of Good Citizenship of Rajabhat Universities' Students in the Northeast of Thailand

    Science.gov (United States)

    Siphai, Sunan; Srisa-ard, Boonchoom

    2015-01-01

    The purpose of this study was 1) to develop good citizenship indicators of Rajabhat Universities' Students in the Northeast of Thailand. 2) to classify latent profile of good citizenship of Rajabhat University's students in the northeast of Thailand. The sample was 800 Rajabhat University's students in the northeast of Thailand. Findings 1) there…

  16. Power and type I error of local fit statistics in multilevel latent class analysis

    NARCIS (Netherlands)

    Nagelkerke, E.; Oberski, D.L.; Vermunt, J.K.

    2017-01-01

    In the social and behavioral sciences, variables are often categorical and people are often nested in groups. Models for such data, such as multilevel logistic regression or the multilevel latent class model, should account for not only the categorical nature of the variables, but also the nested

  17. Parent Involvement and Science Achievement: A Cross-Classified Multilevel Latent Growth Curve Analysis

    Science.gov (United States)

    Johnson, Ursula Y.; Hull, Darrell M.

    2014-01-01

    The authors examined science achievement growth at Grades 3, 5, and 8 and parent school involvement at the same time points using the Early Childhood Longitudinal Study-Kindergarten Class of 1998-1999. Data were analyzed using cross-classified multilevel latent growth curve modeling with time invariant and varying covariates. School-based…

  18. Concurrent Associations of Physical Activity and Screen-Based Sedentary Behavior on Obesity Among US Adolescents: A Latent Class Analysis.

    Science.gov (United States)

    Kim, Youngdeok; Barreira, Tiago V; Kang, Minsoo

    2016-01-01

    Independent associations of physical activity (PA) and sedentary behavior (SB) with obesity are well documented. However, little is known about the combined associations of these behaviors with obesity in adolescents. The present study examines the prevalence of concurrent levels of PA and SB, and their associations with obesity among US adolescents. Data from a total of 12 081 adolescents who participated in the Youth Risk Behaviors Survey during 2012-2013 were analyzed. A latent class analysis was performed to identify latent subgroups with varying combined levels of subjectively measured PA and screen-based SB. Follow-up analysis examined the changes in the likelihood of being obese as determined by the Center for Disease Control and Prevention Growth Chart between latent subgroups. Four latent subgroups with varying combined levels of PA and SB were identified across gender. The likelihood of being obese was significantly greater for the subgroups featuring either or both Low PA or High SB when compared with High PA/Low SB across genders (odds ratio [OR] ranges, 2.1-2.7 for males and 9.6-23.5 for females). Low PA/High SB showed the greater likelihood of being obese compared to subgroups featuring either or both High PA and Low SB (OR ranges, 2.2-23.5) for female adolescents only. The findings imply that promoting sufficient levels of PA while reducing SB should be encouraged in order to reduce obesity risk among adolescents, particularly for males. The risk of obesity for female adolescents can be reduced by engaging in either high levels of PA or low levels of SB.

  19. Concurrent Associations of Physical Activity and Screen-Based Sedentary Behavior on Obesity Among US Adolescents: A Latent Class Analysis

    Directory of Open Access Journals (Sweden)

    Youngdeok Kim

    2016-04-01

    Full Text Available Background: Independent associations of physical activity (PA and sedentary behavior (SB with obesity are well documented. However, little is known about the combined associations of these behaviors with obesity in adolescents. The present study examines the prevalence of concurrent levels of PA and SB, and their associations with obesity among US adolescents. Methods: Data from a total of 12 081 adolescents who participated in the Youth Risk Behaviors Survey during 2012–2013 were analyzed. A latent class analysis was performed to identify latent subgroups with varying combined levels of subjectively measured PA and screen-based SB. Follow-up analysis examined the changes in the likelihood of being obese as determined by the Center for Disease Control and Prevention Growth Chart between latent subgroups. Results: Four latent subgroups with varying combined levels of PA and SB were identified across gender. The likelihood of being obese was significantly greater for the subgroups featuring either or both Low PA or High SB when compared with High PA/Low SB across genders (odds ratio [OR] ranges, 2.1–2.7 for males and 9.6–23.5 for females. Low PA/High SB showed the greater likelihood of being obese compared to subgroups featuring either or both High PA and Low SB (OR ranges, 2.2–23.5 for female adolescents only. Conclusions: The findings imply that promoting sufficient levels of PA while reducing SB should be encouraged in order to reduce obesity risk among adolescents, particularly for males. The risk of obesity for female adolescents can be reduced by engaging in either high levels of PA or low levels of SB.

  20. Maternal anaemia at delivery and haemoglobin evolution in children during their first 18 months of life using latent class analysis.

    Directory of Open Access Journals (Sweden)

    Kobto G Koura

    Full Text Available BACKGROUND: Anaemia during pregnancy and at delivery is an important public health problem in low- and middle-income countries. Its association with the children's haemoglobin level over time remains unclear. Our goals were to identify distinct haemoglobin level trajectories using latent class analysis and to assess the association between these trajectories and maternal anaemia and other risk factors. METHOD: A prospective study of children from birth to 18 months of life was conducted in a rural setting in Tori-Bossito, Benin. The main outcome measure was the haemoglobin levels repeatedly measured at 3, 6, 9, 12, 15 and 18 months. Variables were collected from the mothers at delivery and from their children at birth and during the follow-up. The analyses were performed by means of Latent Class Analysis which has never been used for this kind of data. All the analyses were performed with Stata software, version 11.0, using the generalized linear latent and mixed model (GLLAMM framework. RESULTS: We showed that 33.7% of children followed a low haemoglobin trajectory and 66.3% a high trajectory during the first 18 months of life. Newborn anaemia, placental malaria, malaria attack, sickle cell trait and male gender were significantly associated with a lower children's haemoglobin level over time, whereas maternal age, children living in a polygamous family and with good feeding practices had a higher Hb level in the first18 months. We also showed that maternal anaemia was a predictor for 'low haemoglobin level trajectory' group membership but have no significant effect on children haemoglobin level over time. CONCLUSION: Latent Class Analyses framework seems well suited to analyse longitudinal data under the hypothesis that different subpopulations of subjects are present in the data, each with its own set of parameters, with distinctive evolutions that themselves may reflect distinctive aetiologies.

  1. Alternative approaches for econometric analysis of panel count data using dynamic latent class models (with application to doctor visits data).

    Science.gov (United States)

    Hyppolite, Judex; Trivedi, Pravin

    2012-06-01

    Cross-sectional latent class regression models, also known as switching regressions or hidden Markov models, cannot identify transitions between classes that may occur over time. This limitation can potentially be overcome when panel data are available. For such data, we develop a sequence of models that combine features of the static cross-sectional latent class (finite mixture) models with those of hidden Markov models. We model the probability of movement between categories in terms of a Markovian structure, which links the current state with a previous state, where state may refer to the category of an individual. This article presents a suite of mixture models of varying degree of complexity and flexibility for use in a panel count data setting, beginning with a baseline model which is a two-component mixture of Poisson distribution in which latent classes are fixed and permanent. Sequentially, we extend this framework (i) to allow the mixing proportions to be smoothly varying continuous functions of time-varying covariates, (ii) to add time dependence to the benchmark model by modeling the class-indicator variable as a first-order Markov chain and (iii) to extend item (i) by making it dynamic and introducing covariate dependence in the transition probabilities. We develop and implement estimation algorithms for these models and provide an empirical illustration using 1995-1999 panel data on the number of doctor visits derived from the German Socio-Economic Panel. Copyright © 2012 John Wiley & Sons, Ltd.

  2. SAXS investigation of latent track structure in HDPE irradiated with high energy Fe ions

    Energy Technology Data Exchange (ETDEWEB)

    Hai, Yang; Huang, Can [Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800 (China); University of Chinese Academy of Sciences, Beijing 100049 (China); Ma, Mingwang [Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800 (China); Institute of Electronic Engineering, CAEP, Mianyang 621900 (China); Liu, Qi; Wang, Yuzhu; Liu, Yi; Tian, Feng; Lin, Jun [Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800 (China); Zhu, Zhiyong, E-mail: zhuzhiyong@sinap.ac.cn [Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800 (China)

    2015-08-01

    Semi-crystalline high density polyethylene (HDPE) samples were irradiated with 1.157 GeV {sup 56}Fe ion beams to fluences ranging from 1 × 10{sup 11} to 6 × 10{sup 12} ions/cm{sup 2}. The radiation induced changes in nano/microstructure were investigated with small angle X-ray scattering (SAXS) technique. The scattering contributions from HDPE matrix and ion tracks are successfully separated and analyzed through tilted SAXS measurements with respect to the X-ray beam direction. Lorentz correction, one-dimensional correlation function calculation, fractal nature analysis of the isotropic scattering pattern reveal that HDPE long period polymeric structures are damaged and new materials, possibly clusters of carbon-rich materials, are formed inside the ion tracks. Least square curve fitting of the scattering contribution from the ion track reveals that the track is composed of a core of about 5.3 nm in radius, characterized by a significant density deficit compared to the virgin HDPE, surrounded by a shell of about 4.3 nm in thickness with less density reduction.

  3. Latent class analysis of gambling subtypes and impulsive/compulsive associations: Time to rethink diagnostic boundaries for gambling disorder?

    Science.gov (United States)

    Chamberlain, Samuel R; Stochl, Jan; Redden, Sarah A; Odlaug, Brian L; Grant, Jon E

    2017-09-01

    Gambling disorder has been associated with cognitive dysfunction and impaired quality of life. The current definition of non-pathological, problem, and pathological types of gambling is based on total symptom scores, which may overlook nuanced underlying presentations of gambling symptoms. The aims of the current study were (i) to identify subtypes of gambling in young adults, using latent class analysis, based on individual responses from the Structured Clinical Interview for Gambling Disorder (SCI-GD); and (ii) to explore relationships between these gambling subtypes, and clinical/cognitive measures. Total 582 non-treatment seeking young adults were recruited from two US cities, on the basis of gambling five or more times per year. Participants undertook clinical and neurocognitive assessment, including stop-signal, decision-making, and set-shifting tasks. Data from individual items of the Structured Clinical Interview for Gambling Disorder (SCI-GD) were entered into latent class analysis. Optimal number of classes representing gambling subtypes was identified using Bayesian Information Criterion and differences between them were explored using multivariate analysis of variance. Three subtypes of gambling were identified, termed recreational gamblers (60.2% of the sample; reference group), problem gamblers (29.2%), and pathological gamblers (10.5%). Common quality of life impairment, elevated Barratt Impulsivity scores, occurrence of mainstream mental disorders, having a first degree relative with an addiction, and impaired decision-making were evident in both problem and pathological gambling groups. The diagnostic item 'chasing losses' most discriminated recreational from problem gamblers, while endorsement of 'social, financial, or occupational losses due to gambling' most discriminated pathological gambling from both other groups. Significantly higher rates of impulse control disorders occurred in the pathological group, versus the problem group, who in turn

  4. Diversity in Older Adults’ Use of the Internet: Identifying Subgroups Through Latent Class Analysis

    Science.gov (United States)

    van Boekel, Leonieke C; Peek, Sebastiaan TM; Luijkx, Katrien G

    2017-01-01

    Background As for all individuals, the Internet is important in the everyday life of older adults. Research on older adults’ use of the Internet has merely focused on users versus nonusers and consequences of Internet use and nonuse. Older adults are a heterogeneous group, which may implicate that their use of the Internet is diverse as well. Older adults can use the Internet for different activities, and this usage can be of influence on benefits the Internet can have for them. Objective The aim of this paper was to describe the diversity or heterogeneity in the activities for which older adults use the Internet and determine whether diversity is related to social or health-related variables. Methods We used data of a national representative Internet panel in the Netherlands. Panel members aged 65 years and older and who have access to and use the Internet were selected (N=1418). We conducted a latent class analysis based on the Internet activities that panel members reported to spend time on. Second, we described the identified clusters with descriptive statistics and compared the clusters using analysis of variance (ANOVA) and chi-square tests. Results Four clusters were distinguished. Cluster 1 was labeled as the “practical users” (36.88%, n=523). These respondents mainly used the Internet for practical and financial purposes such as searching for information, comparing products, and banking. Respondents in Cluster 2, the “minimizers” (32.23%, n=457), reported lowest frequency on most Internet activities, are older (mean age 73 years), and spent the smallest time on the Internet. Cluster 3 was labeled as the “maximizers” (17.77%, n=252); these respondents used the Internet for various activities, spent most time on the Internet, and were relatively younger (mean age below 70 years). Respondents in Cluster 4, the “social users,” mainly used the Internet for social and leisure-related activities such as gaming and social network sites. The

  5. Diversity in Older Adults' Use of the Internet: Identifying Subgroups Through Latent Class Analysis.

    Science.gov (United States)

    van Boekel, Leonieke C; Peek, Sebastiaan Tm; Luijkx, Katrien G

    2017-05-24

    As for all individuals, the Internet is important in the everyday life of older adults. Research on older adults' use of the Internet has merely focused on users versus nonusers and consequences of Internet use and nonuse. Older adults are a heterogeneous group, which may implicate that their use of the Internet is diverse as well. Older adults can use the Internet for different activities, and this usage can be of influence on benefits the Internet can have for them. The aim of this paper was to describe the diversity or heterogeneity in the activities for which older adults use the Internet and determine whether diversity is related to social or health-related variables. We used data of a national representative Internet panel in the Netherlands. Panel members aged 65 years and older and who have access to and use the Internet were selected (N=1418). We conducted a latent class analysis based on the Internet activities that panel members reported to spend time on. Second, we described the identified clusters with descriptive statistics and compared the clusters using analysis of variance (ANOVA) and chi-square tests. Four clusters were distinguished. Cluster 1 was labeled as the "practical users" (36.88%, n=523). These respondents mainly used the Internet for practical and financial purposes such as searching for information, comparing products, and banking. Respondents in Cluster 2, the "minimizers" (32.23%, n=457), reported lowest frequency on most Internet activities, are older (mean age 73 years), and spent the smallest time on the Internet. Cluster 3 was labeled as the "maximizers" (17.77%, n=252); these respondents used the Internet for various activities, spent most time on the Internet, and were relatively younger (mean age below 70 years). Respondents in Cluster 4, the "social users," mainly used the Internet for social and leisure-related activities such as gaming and social network sites. The identified clusters significantly differed in age (PInternet

  6. Treatment of Latent Tuberculosis Infection: An Updated Network Meta-analysis.

    Science.gov (United States)

    Zenner, Dominik; Beer, Netta; Harris, Ross J; Lipman, Marc C; Stagg, Helen R; van der Werf, Marieke J

    2017-08-15

    Treatment of latent tuberculosis infection (LTBI) is an important component of tuberculosis (TB) control, and this study updates a previous network meta-analysis of the best LTBI treatment options to inform public health action and programmatic management of LTBI. To evaluate the comparative efficacy and harms of LTBI treatment regimens aimed at preventing active TB among adults and children. PubMed, Embase, and Web of Science from indexing to 8 May 2017; clinical trial registries; and conference abstracts. No language restrictions were applied. Randomized controlled trials that evaluated human LTBI treatments and recorded at least 1 of 2 prespecified end points (hepatotoxicity and prevention of active TB). 2 investigators independently extracted data from eligible studies and assessed study quality according to a standard protocol. The network meta-analysis of 8 new and 53 previously included studies showed that isoniazid regimens of 6 months (odds ratio [OR], 0.65 [95% credible interval {CrI}, 0.50 to 0.83]) or 12 to 72 months (OR, 0.50 [CrI, 0.41 to 0.62]), rifampicin-only regimens (OR, 0.41 [CrI, 0.19 to 0.85]), rifampicin-isoniazid regimens of 3 to 4 months (OR, 0.53 [CrI, 0.36 to 0.78]), rifampicin-isoniazid-pyrazinamide regimens (OR, 0.35 [CrI, 0.19 to 0.61]), and rifampicin-pyrazinamide regimens (OR, 0.53 [CrI, 0.33 to 0.84]) were efficacious compared with placebo. Evidence existed for efficacy of weekly rifapentine-isoniazid regimens compared with no treatment (OR, 0.36 [CrI, 0.18 to 0.73]). No conclusive evidence showed that HIV status altered treatment efficacy. Evidence was sparse for many comparisons and hepatotoxicity outcomes, and risk of bias was high or unknown for many studies. Evidence exists for the efficacy and safety of 6-month isoniazid monotherapy, rifampicin monotherapy, and combination therapies with 3 to 4 months of isoniazid and rifampicin. U.K. National Institute for Health Research. (PROSPERO: CRD42016037871).

  7. Job Satisfaction among Health-Care Staff in Township Health Centers in Rural China: Results from a Latent Class Analysis

    Directory of Open Access Journals (Sweden)

    Haipeng Wang

    2017-09-01

    Full Text Available Background: The lower job satisfaction of health-care staff will lead to more brain drain, worse work performance, and poorer health-care outcomes. The aim of this study was to identify patterns of job satisfaction among health-care staff in rural China, and to investigate the association between the latent clusters and health-care staff’s personal and professional features; Methods: We selected 12 items of five-point Likert scale questions to measure job satisfaction. A latent-class analysis was performed to identify subgroups based on the items of job satisfaction; Results: Four latent classes of job satisfaction were identified: 8.9% had high job satisfaction, belonging to “satisfied class”; 38.2% had low job satisfaction, named as “unsatisfied class”; 30.5% were categorized into “unsatisfied class with the exception of interpersonal relationships”; 22.4% were identified as “pseudo-satisfied class”, only satisfied with management-oriented items. Low job satisfaction was associated with specialty, training opportunity, and income inequality. Conclusions: The minority of health-care staff belong to the “satisfied class”. Three among four subgroups are not satisfied with income, benefit, training, and career development. Targeting policy interventions should be implemented to improve the items of job satisfaction based on the patterns and health-care staff’s features.

  8. Job Satisfaction among Health-Care Staff in Township Health Centers in Rural China: Results from a Latent Class Analysis.

    Science.gov (United States)

    Wang, Haipeng; Tang, Chengxiang; Zhao, Shichao; Meng, Qingyue; Liu, Xiaoyun

    2017-09-22

    Background : The lower job satisfaction of health-care staff will lead to more brain drain, worse work performance, and poorer health-care outcomes. The aim of this study was to identify patterns of job satisfaction among health-care staff in rural China, and to investigate the association between the latent clusters and health-care staff's personal and professional features; Methods : We selected 12 items of five-point Likert scale questions to measure job satisfaction. A latent-class analysis was performed to identify subgroups based on the items of job satisfaction; Results : Four latent classes of job satisfaction were identified: 8.9% had high job satisfaction, belonging to "satisfied class"; 38.2% had low job satisfaction, named as "unsatisfied class"; 30.5% were categorized into "unsatisfied class with the exception of interpersonal relationships"; 22.4% were identified as "pseudo-satisfied class", only satisfied with management-oriented items. Low job satisfaction was associated with specialty, training opportunity, and income inequality. Conclusions : The minority of health-care staff belong to the "satisfied class". Three among four subgroups are not satisfied with income, benefit, training, and career development. Targeting policy interventions should be implemented to improve the items of job satisfaction based on the patterns and health-care staff's features.

  9. The NEO Five-Factor Inventory: Latent Structure and Relationships with Dimensions of Anxiety and Depressive Disorders in a Large Clinical Sample

    Science.gov (United States)

    Rosellini, Anthony J.; Brown, Timothy A.

    2011-01-01

    The present study evaluated the latent structure of the NEO Five-Factor Inventory (NEO FFI) and relations between the five-factor model (FFM) of personality and dimensions of "DSM-IV" anxiety and depressive disorders (panic disorder, generalized anxiety disorder [GAD], obsessive-compulsive disorder, social phobia [SOC], major depressive disorder…

  10. Anxiety, bulimia, drug and alcohol addiction, depression, and schizophrenia: what do you think about their aetiology, dangerousness, social distance, and treatment? A latent class analysis approach.

    Science.gov (United States)

    Mannarini, Stefania; Boffo, Marilisa

    2015-01-01

    Mental illness stigma is a serious societal problem and a critical impediment to treatment seeking for mentally ill people. To improve the understanding of mental illness stigma, this study focuses on the simultaneous analysis of people's aetiological beliefs, attitudes (i.e. perceived dangerousness and social distance), and recommended treatments related to several mental disorders by devising an over-arching latent structure that could explain the relations among these variables. Three hundred and sixty university students randomly received an unlabelled vignette depicting one of six mental disorders to be evaluated on the four variables on a Likert-type scale. A one-factor Latent Class Analysis (LCA) model was hypothesized, which comprised the four manifest variables as indicators and the mental disorder as external variable. The main findings were the following: (a) a one-factor LCA model was retrieved; (b) alcohol and drug addictions are the most strongly stigmatized; (c) a realistic opinion about the causes and treatment of schizophrenia, anxiety, bulimia, and depression was associated to lower prejudicial attitudes and social rejection. Beyond the general appraisal of mental illness an individual might have, the results generally point to the acknowledgement of the specific features of different diagnostic categories. The implications of the present results are discussed in the framework of a better understanding of mental illness stigma.

  11. Latent class analysis of comorbidity patterns among women with generalized and localized vulvodynia: preliminary findings

    Directory of Open Access Journals (Sweden)

    Nguyen RHN

    2013-04-01

    Full Text Available Ruby HN Nguyen,1 Christin Veasley,2 Derek Smolenski1,3 1Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, 2National Vulvodynia Association, Silver Spring, MD, 3National Center for Telehealth and Technology, Defense Centers of Excellence, Department of Defense, Tacoma, WA, USA Background: The pattern and extent of clustering of comorbid pain conditions with vulvodynia is largely unknown. However, elucidating such patterns may improve our understanding of the underlying mechanisms involved in these common causes of chronic pain. We sought to describe the pattern of comorbid pain clustering in a population-based sample of women with diagnosed vulvodynia. Methods: A total of 1457 women with diagnosed vulvodynia self-reported their type of vulvar pain as localized, generalized, or both. Respondents were also surveyed about the presence of comorbid pain conditions, including temporomandibular joint and muscle disorders, interstitial cystitis, fibromyalgia, chronic fatigue syndrome, irritable bowel syndrome, endometriosis, and chronic headache. Age-adjusted latent class analysis modeled extant patterns of comorbidity by vulvar pain type, and a multigroup model was used to test for the equality of comorbidity patterns using a comparison of prevalence. A two-class model (no/single comorbidity versus multiple comorbidities had the best fit in individual and multigroup models. Results: For the no/single comorbidity class, the posterior probability prevalence of item endorsement ranged from 0.9% to 24.4%, indicating a low probability of presence. Conversely, the multiple comorbidity class showed that at least two comorbid conditions were likely to be endorsed by at least 50% of women in that class, and irritable bowel syndrome and fibromyalgia were the most common comorbidities regardless of type of vulvar pain. Prevalence of the multiple comorbidity class differed by type of vulvar pain: both

  12. Patterns and predictors of violence against children in Uganda: a latent class analysis.

    Science.gov (United States)

    Clarke, Kelly; Patalay, Praveetha; Allen, Elizabeth; Knight, Louise; Naker, Dipak; Devries, Karen

    2016-05-24

    To explore patterns of physical, emotional and sexual violence against Ugandan children. Latent class and multinomial logistic regression analysis of cross-sectional data. Luwero District, Uganda. In all, 3706 primary 5, 6 and 7 students attending 42 primary schools. To measure violence, we used the International Society for the Prevention of Child Abuse and Neglect Child Abuse Screening Tool-Child Institutional. We used the Strengths and Difficulties Questionnaire to assess mental health and administered reading, spelling and maths tests. We identified three violence classes. Class 1 (N=696 18.8%) was characterised by emotional and physical violence by parents and relatives, and sexual and emotional abuse by boyfriends, girlfriends and unrelated adults outside school. Class 2 (N=975 26.3%) was characterised by physical, emotional and sexual violence by peers (male and female students). Children in Classes 1 and 2 also had a high probability of exposure to emotional and physical violence by school staff. Class 3 (N=2035 54.9%) was characterised by physical violence by school staff and a lower probability of all other forms of violence compared to Classes 1 and 2. Children in Classes 1 and 2 were more likely to have worked for money (Class 1 Relative Risk Ratio 1.97, 95% CI 1.54 to 2.51; Class 2 1.55, 1.29 to 1.86), been absent from school in the previous week (Class 1 1.31, 1.02 to 1.67; Class 2 1.34, 1.10 to 1.63) and to have more mental health difficulties (Class 1 1.09, 1.07 to 1.11; Class 2 1.11, 1.09 to 1.13) compared to children in Class 3. Female sex (3.44, 2.48 to 4.78) and number of children sharing a sleeping area predicted being in Class 1. Childhood violence in Uganda forms distinct patterns, clustered by perpetrator and setting. Research is needed to understand experiences of victimised children, and to develop mental health interventions for those with severe violence exposures. NCT01678846; Results. Published by the BMJ Publishing Group Limited. For

  13. Clustering of modifiable biobehavioral risk factors for chronic disease in US adults: a latent class analysis.

    Science.gov (United States)

    Leventhal, Adam M; Huh, Jimi; Dunton, Genevieve F

    2014-11-01

    Examining the co-occurrence patterns of modifiable biobehavioral risk factors for deadly chronic diseases (e.g. cancer, cardiovascular disease, diabetes) can elucidate the etiology of risk factors and guide disease-prevention programming. The aims of this study were to (1) identify latent classes based on the clustering of five key biobehavioral risk factors among US adults who reported at least one risk factor and (2) explore the demographic correlates of the identified latent classes. Participants were respondents of the National Epidemiologic Survey of Alcohol and Related Conditions (2004-2005) with at least one of the following disease risk factors in the past year (N = 22,789), which were also the latent class indicators: (1) alcohol abuse/dependence, (2) drug abuse/dependence, (3) nicotine dependence, (4) obesity, and (5) physical inactivity. Housing sample units were selected to match the US National Census in location and demographic characteristics, with young adults oversampled. Participants were administered surveys by trained interviewers. Five latent classes were yielded: 'obese, active non-substance abusers' (23%); 'nicotine-dependent, active, and non-obese' (19%); 'active, non-obese alcohol abusers' (6%); 'inactive, non-substance abusers' (50%); and 'active, polysubstance abusers' (3.7%). Four classes were characterized by a 100% likelihood of having one risk factor coupled with a low or moderate likelihood of having the other four risk factors. The five classes exhibited unique demographic profiles. Risk factors may cluster together in a non-monotonic fashion, with the majority of the at-risk population of US adults expected to have a high likelihood of endorsing only one of these five risk factors. © Royal Society for Public Health 2013.

  14. A Behavioral Approach to Understanding Green Consumerism Using Latent Class Choice Analysis

    DEFF Research Database (Denmark)

    Peschel, Anne Odile; Grebitus, Carola; Steiner, Bodo

    on individuals' environmental attitudes and values. Consumer involvement and environmental attitudes contribute significantly toward explaining sustainable choices, suggesting that greater consumer involvement may be targeted by policy makers and firms to more effectively nudge consumers toward green consumerism......To better understand motivations of consumers making choices among sustainability-labeled food products, this paper analyzes drivers of stated choices for a dietary staple labeled with carbon and water foodprints. Latent class modeling of survey responses reveals distinct consumer segments based...

  15. Math Anxiety Questionnaire: Similar Latent Structure in Brazilian and German School Children

    Directory of Open Access Journals (Sweden)

    Guilherme Wood

    2012-01-01

    Full Text Available Math anxiety is a relatively frequent phenomenon often related to low mathematics achievement and dyscalculia. In the present study, the German and the Brazilian versions of the Mathematics Anxiety Questionnaire (MAQ were examined. The two-dimensional structure originally reported for the German MAQ, that includes both affective and cognitive components of math anxiety was reproduced in the Brazilian version. Moreover, mathematics anxiety also was found to increase with age in both populations and was particularly associated with basic numeric competencies and more complex arithmetics. The present results suggest that mathematics anxiety as measured by the MAQ presents the same internal structure in culturally very different populations.

  16. Interferon-γ release assays for the diagnosis of latent Mycobacterium tuberculosis infection: a systematic review and meta-analysis

    DEFF Research Database (Denmark)

    Diel, R; Goletti, D; Ferrara, G

    2011-01-01

    We conducted a systematic review and meta-analysis to compare the accuracy of the QuantiFERON-TB® Gold In-Tube (QFT-G-IT) and the T-SPOT®.TB assays with the tuberculin skin test (TST) for the diagnosis of latent Mycobacterium tuberculosis infection (LTBI). The Medline, Embase and Cochrane databases...... of IGRAs varied 98-100%. In immunocompetent adults, NPV for progression to tuberculosis within 2 yrs were 97.8% for T-SPOT®.TB and 99.8% for QFT-G-IT. When test performance of an immunodiagnostic test was not restricted to prior positivity of another test, progression rates to tuberculosis among IGRA...

  17. Visualizing Confidence Bands for Semiparametrically Estimated Nonlinear Relations among Latent Variables

    Science.gov (United States)

    Pek, Jolynn; Chalmers, R. Philip; Kok, Bethany E.; Losardo, Diane

    2015-01-01

    Structural equation mixture models (SEMMs), when applied as a semiparametric model (SPM), can adequately recover potentially nonlinear latent relationships without their specification. This SPM is useful for exploratory analysis when the form of the latent regression is unknown. The purpose of this article is to help users familiar with structural…

  18. The Latent Symptom Structure of the Beck Depression Inventory-II in Outpatients with Major Depression

    Science.gov (United States)

    Quilty, Lena C.; Zhang, K. Anne; Bagby, R. Michael

    2010-01-01

    The Beck Depression Inventory-II (BDI-II) is a self-report instrument frequently used in clinical and research settings to assess depression severity. Although investigators have examined the factor structure of the BDI-II, a clear consensus on the best fitting model has not yet emerged, resulting in different recommendations regarding how to best…

  19. Psychometrics and latent structure of the IDS and QIDS with young adult students.

    Science.gov (United States)

    González, David Andrés; Boals, Adriel; Jenkins, Sharon Rae; Schuler, Eric R; Taylor, Daniel

    2013-07-01

    Students and young adults have high rates of suicide and depression, thus are a population of interest. To date, there is no normative psychometric information on the IDS and QIDS in these populations. Furthermore, there is equivocal evidence on the factor structure and subscales of the IDS. Two samples of young adult students (ns=475 and 1681) were given multiple measures to test the psychometrics and dimensionality of the IDS and QIDS. The IDS, its subscales, and QIDS had acceptable internal consistencies (αs=.79-90) and favorable convergent and divergent validity correlations. A three-factor structure and two Rasch-derived subscales best fit the IDS. The samples were collected from one university, which may influence generalizability. The IDS and QIDS are desirable measures of depressive symptoms when studying young adult students. Copyright © 2013 Elsevier B.V. All rights reserved.

  20. What Do Test Scores Really Mean? A Latent Class Analysis of Danish Test Score Performance

    DEFF Research Database (Denmark)

    Munk, Martin D.; McIntosh, James

    2014-01-01

    Latent class Poisson count models are used to analyze a sample of Danish test score results from a cohort of individuals born in 1954-55, tested in 1968, and followed until 2011. The procedure takes account of unobservable effects as well as excessive zeros in the data. We show that the test scores...... of intelligence explain a significant proportion of the variation in test scores. This adds to the complexity of interpreting test scores and suggests that school culture and possible incentive problems make it more di¢ cult to understand what the tests measure....

  1. Geertz versus Levi-Strauss: latent structural dispositions in Geertz "theory of culture"?

    Directory of Open Access Journals (Sweden)

    Gordana Gorunović

    2016-02-01

    Full Text Available These are two authors, in Foucauldian terms that certainly belong to the most influential individuals in socio-cultural anthropology, as well as in the social sciences and interdisciplinary research more broadly. Claude Levi- Strauss became some kind of an "intellectual hero" during the domination of structuralism in the mid-twentieth century and during the 1960s, while Clifford Geertz was an ‘icon and ambassador’ of anthropology in the second half of the twentieth century. They are both one of the founders of the discourse theory. They not only established a distinct theoretical approaches and methods – structural (Levi-Strauss and interpretative anthropology (Clifford Geertz, but through their intellectual authority they also inspired paradigms and intellectual movements making structuralism and "interpretation of culture" more than some passing episodes in the history of social though (in terms of "trendy ideas". My aim is to make some parallels between these two authors, who despite all the differences that are evident in their epistemological discourses, theoretical approaches and methods (as well as in their ethnographic and anthropological writings itself still have some similarities in their theorisation and interpretation of culture, which I would like to stress in this paper.

  2. Exploratory market structure analysis. Topology-sensitive methodology.

    OpenAIRE

    Mazanec, Josef

    1999-01-01

    Given the recent abundance of brand choice data from scanner panels market researchers have neglected the measurement and analysis of perceptions. Heterogeneity of perceptions is still a largely unexplored issue in market structure and segmentation studies. Over the last decade various parametric approaches toward modelling segmented perception-preference structures such as combined MDS and Latent Class procedures have been introduced. These methods, however, are not taylored for qualitative ...

  3. Structure of health-enhancing behavior in adolescence: a latent-variable approach.

    Science.gov (United States)

    Donovan, J E; Jessor, R; Costa, F M

    1993-12-01

    The structure of the interrelations among a variety of health-enhancing behaviors was examined using structural equation modeling analyses of questionnaire data from 1,280 middle school students and 2,219 high school students. The health-enhancing behaviors included seat belt use, adequate hours of sleep, attention to healthy diet, adequate exercise, low sedentary behavior, and regular toothbrushing. In the middle school sample, all of the health-enhancing behaviors correlated significantly but modestly with each other, except for sleep with toothbrushing. In the high school sample, all but three of the 15 correlations among the behaviors were significant. The results further show that a single underlying factor can account for the modest correlations among these health-enhancing behaviors in both samples. The generality of the single-factor model was also established for male, female, White, Hispanic, and Black students at each school level. These findings provide some support for the existence of health-related lifestyles in adolescence.

  4. Latent structure of the Wisconsin Card Sorting Test: a confirmatory factor analytic study.

    Science.gov (United States)

    Greve, Kevin W; Stickle, Timothy R; Love, Jeffrey M; Bianchini, Kevin J; Stanford, Matthew S

    2005-05-01

    The present study represents the first large scale confirmatory factor analysis of the Wisconsin Card Sorting Test (WCST). The results generally support the three factor solutions reported in the exploratory factor analysis literature. However, only the first factor, which reflects general executive functioning, is statistically sound. The secondary factors, while likely reflecting meaningful cognitive abilities, are less stable except when all subjects complete all 128 cards. It is likely that having two discontinuation rules for the WCST has contributed to the varied factor analytic solutions reported in the literature and early discontinuation may result in some loss of useful information. Continued multivariate research will be necessary to better clarify the processes underlying WCST performance and their relationships to one another.

  5. Gradient of association between parenting styles and patterns of drug use in adolescence: A latent class analysis.

    Science.gov (United States)

    Valente, Juliana Y; Cogo-Moreira, Hugo; Sanchez, Zila M

    2017-11-01

    To identify different patterns of drug use in adolescence and determine if these are associated with parenting styles and other sociodemographic factors. A latent class analysis was conducted using baseline data collected in a sample (n=6381) from a randomized controlled trial conducted to evaluate the effectiveness of the #Tamojunto drug-use prevention program, carried out with 7th- and 8th-grade public school students in six Brazilian cities. Three latent classes were identified among the students: 1) abstainers/low users (81.54%), 2) alcohol users/binge drinkers (16.65%), and 3) polydrug users (1.80%). A gradient of inverse association was found between parenting styles (authoritative, authoritarian, and indulgent, with the neglectful style as a reference point) and the classes "alcohol users/binge drinkers" (aOR=0.36, 95%CI=0.27-0.47; aOR=0.56, 95%CI=0.43-0.72; and aOR=0.64, 95%CI=0.51-0.80, respectively) and "polydrug users" (aOR=0.09, 95%CI=0.03-0.24; aOR=0.23, 95%CI=0.11-0.52; and aOR=0.24, 95%CI=0.08-0.74, respectively). Associations were also revealed between the latent classes and the adolescent's age and socioeconomic status. The results suggest that activities to develop parenting skills should be included in school programs aimed at the prevention of drug use among adolescents in order to reduce neglectful practices and thereby possibly reduce drug use among the children. Copyright © 2017. Published by Elsevier B.V.

  6. Polydrug Use and HIV Risk Among People Who Inject Heroin in Tijuana, Mexico: A Latent Class Analysis.

    Science.gov (United States)

    Meacham, Meredith C; Rudolph, Abby E; Strathdee, Steffanie A; Rusch, Melanie L; Brouwer, Kimberly C; Patterson, Thomas L; Vera, Alicia; Rangel, Gudelia; Roesch, Scott C

    2015-01-01

    Although most people who inject drugs (PWID) in Tijuana, Mexico, primarily inject heroin, injection and non-injection use of methamphetamine and cocaine is common. We examined patterns of polydrug use among heroin injectors to inform prevention and treatment of drug use and its health and social consequences. Participants were PWID residing in Tijuana, aged ≥18 years who reported heroin injection in the past six months and were recruited through respondent-driven sampling (n = 1,025). Latent class analysis was conducted to assign individuals to classes on a probabilistic basis, using four indicators of past six-month polydrug and polyroute use: cocaine injecting, cocaine smoking or snorting, methamphetamine injecting, and methamphetamine smoking or snorting. Latent class membership was regressed onto covariates in a multinomial logistic regression. Latent class analyses testing 1, 2, 3, and 4 classes were fit, with the 3-class solution fitting best. Class 1 was defined by predominantly heroin use (50.2%, n = 515); class 2 by methamphetamine and heroin use (43.7%, n = 448), and class 3 by methamphetamine, cocaine, and heroin use (6.0%, n = 62). Bivariate and multivariate analyses indicated a group of methamphetamine and cocaine users that exhibited higher-risk sexual practices and lower heroin injecting frequency, and a group of methamphetamine users who were younger and more likely to be female. Discrete subtypes of heroin PWID were identified based on methamphetamine and cocaine use patterns. These findings have identified subtypes of heroin injectors who require more tailored interventions to reduce the health and social harms of injecting drug use.

  7. Latent class analysis of multimorbidity patterns and associated outcomes in Spanish older adults: a prospective cohort study.

    Science.gov (United States)

    Olaya, Beatriz; Moneta, Maria Victoria; Caballero, Francisco Félix; Tyrovolas, Stefanos; Bayes, Ivet; Ayuso-Mateos, José Luis; Haro, Josep Maria

    2017-08-18

    This study sought to identify multimorbidity patterns and determine the association between these latent classes with several outcomes, including health, functioning, disability, quality of life and use of services, at baseline and after 3 years of follow-up. We analyzed data from a representative Spanish cohort of 3541 non-institutionalized people aged 50 years old and over. Measures were taken at baseline and after 3 years of follow-up. Latent Class Analysis (LCA) was conducted using eleven common chronic conditions. Generalized linear models were conducted to determine the adjusted association of multimorbidity latent classes with several outcomes. 63.8% of participants were assigned to the "healthy" class, with minimum disease, 30% were classified under the "metabolic/stroke" class and 6% were assigned to the "cardiorespiratory/mental/arthritis" class. Significant cross-sectional associations were found between membership of both multimorbidity classes and poorer memory, quality of life, greater burden and more use of services. After 3 years of follow-up, the "metabolic/stroke" class was a significant predictor of lower levels of verbal fluency while the two multimorbidity classes predicted poor quality of life, problems in independent living, higher risk of hospitalization and greater use of health services. Common chronic conditions in older people cluster together in broad categories. These broad clusters are qualitatively distinct and are important predictors of several health and functioning outcomes. Future studies are needed to understand underlying mechanisms and common risk factors for patterns of multimorbidity and to propose more effective treatments.

  8. Victimization and Human Immunodeficiency Virus-Related Risk Among Transgender Women in India: A Latent Profile Analysis.

    Science.gov (United States)

    Willie, Tiara C; Chakrapani, Venkatesan; White Hughto, Jaclyn M; Kershaw, Trace S

    2017-12-01

    Globally, transgender women (TGW) experience multiple forms of victimization such as violence and discrimination that can place them at risk for poor sexual health. To date, research overlooks the heterogeneity in experiences of victimization among TGW. Furthermore, few studies have examined the association between victimization and sexual risk among TGW in India, despite the high burden of HIV and victimization in this community. Latent profile analysis was performed to identify patterns of victimization in a convenience sample of 299 TGW recruited from nongovernmental organizations across four states in India. Analysis of covariance was performed to examine differences in sexual risk (i.e., alcohol use before sex; inconsistent condom use with a male regular partner, a male causal partner, and a male paying partner; and having multiple sexual partners) between latent profiles. Five distinct profiles of Indian TGW were identified based on the type and severity of victimization: (1) Low victimization, (2) High verbal police victimization, (3) High verbal and physical police victimization, (4) Moderate victimization, and (5) High victimization. While controlling for age, education, income, HIV status, and marital status, results revealed that TGW in the moderate victimization and high victimization profiles had higher sexual risk than TGW in the low victimization and high verbal police victimization profiles. In addition, TGW in high verbal and physical police victimization profile had higher sexual risk than TGW in low victimization profile. These findings underscore the importance of tailoring sexual risk reduction interventions to the specific needs of TGW based on patterns of victimization.

  9. Maltreatment histories of foster youth exiting out-of-home care through emancipation: a latent class analysis.

    Science.gov (United States)

    Havlicek, Judy

    2014-01-01

    Little is known about maltreatment among foster youth transitioning to adulthood. Multiple entries into out-of-home care and unsuccessful attempts at reunification may nevertheless reflect extended exposure to chronic maltreatment and multiple types of victimization. This study used administrative data from the Illinois Department of Children and Family Services to identify all unduplicated allegations of maltreatment in a cohort of 801 foster youth transitioning to adulthood in the state of Illinois. A latent variable modeling approach generated profiles of maltreatment based on substantiated and unsubstantiated reports of maltreatment taken from state administrative data. Four indicators of maltreatment were included in the latent class analysis: multiple types of maltreatment, predominant type of maltreatment, chronicity, and number of different perpetrators. The analysis identified four subpopulations of foster youth in relation to maltreatment. Study findings highlight the heterogeneity of maltreatment in the lives of foster youth transitioning to adulthood and draw attention to a need to raise awareness among service providers to screen for chronic maltreatment and multiple types of victimization. © The Author(s) 2014.

  10. Latent constructs of adjustment to aging and subjective age in Portugal and Romania: a comparative multiple correspondence analysis

    Directory of Open Access Journals (Sweden)

    Sofia von Humboldt

    Full Text Available Objective: To analyze the determinants of adjustment to aging (AtA and subjective age (SA identified by older adults and to investigate the differences of latent constructs that can work as major determinants in AtA and SA in an older Portuguese and Romanian population. Method: Measures were completed, including demographics and interviews. Complete data were available for 38 older adults aged between 74-90 years (M=80.6; SD = 5.4, from Portugal and Romenia. Data was subjected to content analysis. Representation of the associations and latent constructs were analyzed by a Multiple Correspondence Analysis (MCA. Results: The most prevalent response of the interviewed participants for determinants to AtA was ‘health status, physical and intellectual functioning’ (18.1%. ‘With apprehension’ and ‘good enough’ (both 27.0% were identified as the most frequent SA responses. Findings showed a model for each nationality. AtA and SA for Portuguese elderly were explained by a three-factor model: ‘regardful’, ‘engaged’ and ‘conciliated’. A three-dimension model formed by ‘perseverant’, ‘congruent’ and ‘enjoyers’ was indicated as a best-fit solution for Romanian elderly. Conclusion: AtA and SA are strongly explained by increased likelihood of specific constructs in its definition. AtA is related to SA in older adults in both countries, although in different degree.

  11. Personal and Financial Risk Typologies Among Women Who Engage in Sex Work in Mongolia: A Latent Class Analysis.

    Science.gov (United States)

    Offringa, Reid; Tsai, Laura Cordisco; Aira, Toivgoo; Riedel, Marion; Witte, Susan S

    2017-08-01

    Women engaged in sex work bear a disproportionate burden of HIV infection worldwide, particularly in low- to middle-income countries. Stakeholders interested in promoting prevention and treatment programs are challenged to efficiently and effectively target heterogeneous groups of women. This problem is particularly difficult because it is nearly impossible to know how those groups are composed a priori. Although grouping based on individual variables (e.g., age or place of solicitation) can describe a sample of women engaged in sex work, selecting these variables requires a strong intuitive understanding of the population. Furthermore, this approach is difficult to quantify and has the potential to reinforce preconceived notions, rather than generate new information. We aimed to investigate groupings of women engaged in sex work. The data were collected from a sample of 204 women who were referred to an HIV prevention intervention in Ulaanbaatar, Mongolia. Latent class analysis was used to create subgroups of women engaged in sex work, based on personal and financial risk factors. This analysis found three latent classes, representing unique response pattern profiles of personal and financial risk. The current study approached typology research in a novel, more empirical way and provided a description of different subgroups, which may respond differently to HIV risk interventions.

  12. Motivation, emotion regulation, and the latent structure of psychopathology: An integrative and convergent historical perspective.

    Science.gov (United States)

    Beauchaine, Theodore P; Zisner, Aimee

    2017-09-01

    Motivational models of psychopathology have long been advanced by psychophysiologists, and have provided key insights into neurobiological mechanisms of a wide range of psychiatric disorders. These accounts emphasize individual differences in activity and reactivity of bottom-up, subcortical neural systems of approach and avoidance in affecting behavior. Largely independent literatures emphasize the roles of top-down, cortical deficits in emotion regulation and executive function in conferring vulnerability to psychopathology. To date however, few models effectively integrate functions performed by bottom-up emotion generation system with those performed by top-down emotion regulation systems in accounting for alternative expressions of psychopathology. In this article, we present such a model, and describe how it accommodates the well replicated bifactor structure of psychopathology. We describe how excessive approach motivation maps directly into externalizing liability, how excessive passive avoidance motivation maps directly into internalizing liability, and how emotion dysregulation and executive function map onto general liability. This approach is consistent with the Research Domain Criteria initiative, which assumes that a limited number of brain systems interact to confer vulnerability to many if not most forms of psychopathology. Copyright © 2017 Elsevier B.V. All rights reserved.

  13. Brief Sensation Seeking Scale: Latent structure of 8-item and 4-item versions in Peruvian adolescents.

    Science.gov (United States)

    Merino-Soto, Cesar; Salas Blas, Edwin

    2018-01-01

    This research intended to validate two brief scales of sensations seeking with Peruvian adolescents: the eight item scale (BSSS8; Hoyle, Stephenson, Palmgreen, Lorch, y Donohew, 2002) and the four item scale (BSSS4; Stephenson, Hoyle, Slater, y Palmgreen, 2003). Questionnaires were administered to 618 voluntary participants, with an average age of 13.6 years, from different levels of high school, state and private school in a district in the south of Lima. It analyzed the internal structure of both short versions using three models: a) unidimensional (M1), b) oblique or related dimensions (M2), and c) the bifactor model (M3). Results show that both instruments have a single dimension which best represents the variability of the items; a fact that can be explained both by the complexity of the concept and by the small number of items representing each factor, which is more noticeable in the BSSS4. Reliability is within levels found by previous studies: alpha: .745 = BSSS8 and BSSS4 =. 643; omega coefficient: .747 in BSSS8 and .651 in BSSS4. These are considered suitable for the type of instruments studied. Based on the correlation between the two instruments, it was found that there are satisfactory levels of equivalence between the BSSS8 and BSSS4. However, it is recommended that the BSSS4 is mainly used for research and for the purpose of describing populations.

  14. Performance modeling and techno-economic analysis of a modular concentrated solar power tower with latent heat storage

    Energy Technology Data Exchange (ETDEWEB)

    Rea, Jonathan E.; Oshman, Christopher J.; Olsen, Michele L.; Hardin, Corey L.; Glatzmaier, Greg C.; Siegel, Nathan P.; Parilla, Philip A.; Ginley, David S.; Toberer, Eric S.

    2018-05-01

    In this paper, we present performance simulations and techno-economic analysis of a modular dispatchable solar power tower. Using a heliostat field and power block three orders of magnitude smaller than conventional solar power towers, our unique configuration locates thermal storage and a power block directly on a tower receiver. To make the system dispatchable, a valved thermosyphon controls heat flow from a latent heat thermal storage tank to a Stirling engine. The modular design results in minimal balance of system costs and enables high deployment rates with a rapid realization of economies of scale. In this new analysis, we combine performance simulations with techno-economic analysis to evaluate levelized cost of electricity, and find that the system has potential for cost-competitiveness with natural gas peaking plants and alternative dispatchable renewables.

  15. The Different Facets of Work Stress: A Latent Profile Analysis of Nurses' Work Demands.

    Science.gov (United States)

    Jenull, Brigitte B; Wiedermann, Wolfgang

    2015-10-01

    Work-related stress has been identified as a relevant problem leading to negative effects on health and quality of life. Using data from 844 nurses, latent profile analyses (LPA) were applied to identify distinct patterns of work stress. Several sociodemographic variables, including nurses' working and living conditions, as well as nurses' reactions to workload, were considered to predict respondents' profile membership. LPA revealed three distinct profiles that can be distinguished by a low, moderate, and higher stress level. Being financially secure is positively related to the low stress profile, whereas working in an urban area and having low job satisfaction increases the chance of belonging to the higher stress profile. Our results can be used as a basis to develop interventions to create a healthy nursing home environment by supporting the balance between family and work, providing access to job resources and optimizing recovery opportunities. © The Author(s) 2013.

  16. Identification of subgroups of patients with low back pain using Latent Class Analysis

    DEFF Research Database (Denmark)

    Nielsen, Anne Mølgaard

    questionnaire and the clinicians’ findings on a standardised examination of the low back. By using pattern recognition, subgroups of patients were identified within which their responses and scores are similar, and therefore the patients are more alike within the subgroups than across the subgroups. Latent......, the optimal application of the LCA method in this context is unknown and therefore, two methodological considerations were addressed during the process. Firstly, when using existing questionnaire data, whether using each single item or the summary scores would provide better subgroup information. Secondly...... the questionnaires was preferred, due to the more nuanced description available within the resulting subgroups. Therefore, the single‐item strategy was used in the subsequent single‐stage and two‐stage LCA, which identified seven and nine patient subgroups, respectively, with similar face validity and adequate...

  17. Parent Prevention Communication Profiles and Adolescent Substance Use: A Latent Profile Analysis and Growth Curve Model

    Science.gov (United States)

    Choi, Hye Jeong; Miller-Day, Michelle; Shin, YoungJu; Hecht, Michael L.; Pettigrew, Jonathan; Krieger, Janice L.; Lee, JeongKyu; Graham, John W.

    2017-01-01

    This current study identifies distinct parent prevention communication profiles and examines whether youth with different parental communication profiles have varying substance use trajectories over time. Eleven schools in two rural school districts in the Midwestern United States were selected, and 784 students were surveyed at three time points from the beginning of 7th grade to the end of 8th grade. A series of latent profile analyses were performed to identify discrete profiles/subgroups of substance-specific prevention communication (SSPC). The results revealed a 4-profile model of SSPC: Active-Open, Passive-Open, Active-Silent, and Passive-Silent. A growth curve model revealed different rates of lifetime substance use depending on the youth’s SSPC profile. These findings have implications for parenting interventions and tailoring messages for parents to fit specific SSPC profiles. PMID:29056872

  18. Physicians' perception of demand-induced supply in the information age: a latent class model analysis.

    Science.gov (United States)

    Shih, Ya-Chen Tina; Tai-Seale, Ming

    2012-03-01

    This paper introduces a concept called 'demand-induced supply' that reflects the excess supply of services due to an increase in demand initiated by patients. We examine its association with the proportion of information-savvy patients in physicians' practice. Using data from a national representative physician survey, we apply latent class models to analyze this association. Our analyses categorize physicians into three 'types' according to the frequency with which they provided additional medical services at their patients' requests: frequent, occasional, and rare. The proportion of information-savvy patients is significantly and positively correlated with demand-induced supply for the frequent or occasional type, but not among physicians in the rare type. Efforts to contain healthcare costs through utilization control need to recognize the pattern of responses from physicians who treat an increasing number of information-savvy patients. Copyright © 2011 John Wiley & Sons, Ltd.

  19. Separate sensible and latent cooling system: A preliminary analysis of a novel approach

    Energy Technology Data Exchange (ETDEWEB)

    Nawaz, Kashif [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2017-10-01

    Separate sensible and latent cooling systems offer significant increases in the overall performance of cooling/dehumidification systems compared with conventional vapor-compression air-conditioning systems. Key to the energy efficiency of such systems is the performance of the heat and mass exchangers that provide sensible cooling and dehumidification. A novel design is proposed for dehumidification applications, deploying metal foam as a substrate coated with solid desiccants. The current report provides some preliminary information regarding the development of the technology and discusses factors such as manufacturing of desiccants, characterization of desiccants, and development of the metal foam heat exchanger. All three aspects provide the necessary infrastructure for further development and validation of the proposed concept.

  20. Gender roles and binge drinking among Latino emerging adults: a latent class regression analysis.

    Science.gov (United States)

    Vaughan, Ellen L; Wong, Y Joel; Middendorf, Katharine G

    2014-09-01

    Gender roles are often cited as a culturally specific predictor of drinking among Latino populations. This study used latent class regression to test the relationships between gender roles and binge drinking in a sample of Latino emerging adults. Participants were Latino emerging adults who participated in Wave III of the National Longitudinal Study of Adolescent Health (N = 2,442). A subsample of these participants (n = 660) completed the Bem Sex Role Inventory--Short. We conducted latent class regression using 3 dimensions of gender roles (femininity, social masculinity, and personal masculinity) to predict binge drinking. Results indicated a 3-class solution. In Class 1, the protective personal masculinity class, personal masculinity (e.g., being a leader, defending one's own beliefs) was associated with a reduction in the odds of binge drinking. In Class 2, the nonsignificant class, gender roles were not related to binge drinking. In Class 3, the mixed masculinity class, personal masculinity was associated with a reduction in the odds of binge drinking, whereas social masculinity (e.g., forceful, dominant) was associated with an increase in the odds of binge drinking. Post hoc analyses found that females, those born outside the United States, and those with greater English language usage were at greater odds of being in Class 1 (vs. Class 2). Males, those born outside the United States, and those with greater Spanish language usage were at greater odds of being in Class 3 (vs. Class 2). Directions for future research and implications for practice with Latino emerging adults are discussed.

  1. Religiousness and Levels of Hazardous Alcohol Use: A Latent Profile Analysis.

    Science.gov (United States)

    Jankowski, Peter J; Hardy, Sam A; Zamboanga, Byron L; Ham, Lindsay S; Schwartz, Seth J; Kim, Su Yeong; Forthun, Larry F; Bersamin, Melina M; Donovan, Roxanne A; Whitbourne, Susan Krauss; Hurley, Eric A; Cano, Miguel Ángel

    2015-10-01

    Prior person-centered research has consistently identified a subgroup of highly religious participants that uses significantly less alcohol when compared to the other subgroups. The construct of religious motivation is absent from existing examinations of the nuanced combinations of religiousness dimensions within persons, and alcohol expectancy valuations have yet to be included as outcome variables. Variable-centered approaches have found religious motivation and alcohol expectancy valuations to play a protective role against individuals' hazardous alcohol use. The current study examined latent religiousness profiles and hazardous alcohol use in a large, multisite sample of ethnically diverse college students. The sample consisted of 7412 college students aged 18-25 (M age = 19.77, SD age = 1.61; 75% female; 61% European American). Three latent profiles were derived from measures of religious involvement, salience, and religious motivations: Quest-Intrinsic Religiousness (highest levels of salience, involvement, and quest and intrinsic motivations; lowest level of extrinsic motivation), Moderate Religiousness (intermediate levels of salience, involvement, and motivations) and Extrinsic Religiousness (lowest levels of salience, involvement, and quest and intrinsic motivations; highest level of extrinsic motivation). The Quest-Intrinsic Religiousness profile scored significantly lower on hazardous alcohol use, positive expectancy outcomes, positive expectancy valuations, and negative expectancy valuations, and significantly higher on negative expectancy outcomes, compared to the other two profiles. The Extrinsic and Moderate Religiousness profiles did not differ significantly on positive expectancy outcomes, negative expectancy outcomes, negative expectancy valuations, or hazardous alcohol use. The results advance existing research by demonstrating that the protective influence of religiousness on college students' hazardous alcohol use may involve high levels on

  2. Students' Perceptions of Motivational Climate and Enjoyment in Finnish Physical Education: A Latent Profile Analysis.

    Science.gov (United States)

    Jaakkola, Timo; Wang, C K John; Soini, Markus; Liukkonen, Jarmo

    2015-09-01

    The purpose of this study was to identify student clusters with homogenous profiles in perceptions of task- and ego-involving, autonomy, and social relatedness supporting motivational climate in school physical education. Additionally, we investigated whether different motivational climate groups differed in their enjoyment in PE. Participants of the study were 2 594 girls and 1 803 boys, aged 14-15 years. Students responded to questionnaires assessing their perception of motivational climate and enjoyment in physical education. Latent profile analyses produced a five-cluster solution labeled 1) 'low autonomy, relatedness, task, and moderate ego climate' group', 2) 'low autonomy, relatedness, and high task and ego climate, 3) 'moderate autonomy, relatedness, task and ego climate' group 4) 'high autonomy, relatedness, task, and moderate ego climate' group, and 5) 'high relatedness and task but moderate autonomy and ego climate' group. Analyses of variance showed that students in clusters 4 and 5 perceived the highest level of enjoyment whereas students in cluster 1 experienced the lowest level of enjoyment. The results showed that the students' perceptions of various motivational climates created differential levels of enjoyment in PE classes. Key pointsLatent profile analyses produced a five-cluster solution labeled 1) 'low autonomy, relatedness, task, and moderate ego climate' group', 2) 'low autonomy, relatedness, and high task and ego climate, 3) 'moderate autonomy, relatedness, task and ego climate' group 4) 'high autonomy, relatedness, task, and moderate ego climate' group, and 5) 'high relatedness and task but moderate autonomy and ego climate' group.Analyses of variance showed that clusters 4 and 5 perceived the highest level of enjoyment whereas cluster 1 experienced the lowest level of enjoyment. The results showed that the students' perceptions of motivational climate create differential levels of enjoyment in PE classes.

  3. Risk-taking behaviors and subgrouping of suicide in Iran: A latent class analysis of national registries data.

    Science.gov (United States)

    Hajebi, Ahmad; Abbasi-Ghahramanloo, Abbas; Hashemian, Seyed Sepehr; Khatibi, Seyed Reza; Ghasemzade, Masomeh; Khodadost, Mahmoud

    2017-09-01

    Suicide is one the most important public health problem which is rapidly growing concerns. The aim of this study was to subgroup suicide using LCA method. This cross-sectional study was conducted in Iran based on 66990 records registered in Ministry of Health in 2014. A case report questionnaire in the form of software was used for case registries. Latent class analysis was used to achieve the research objectives. Four latent classes were identified; (a) Non-lethal attempters without a history of psychiatric disorders, (b) Non-lethal attempters with a history of psychiatric disorders, (c) Lethal attempters without a history of psychiatric disorders, (d) Lethal attempters with a history of psychiatric disorders. The probability of completed/an achieved suicide is high in lethal attempter classes. Being male increases the risk of inclusion in lethal attempters' classes (OR = 4.93). Also, being single (OR = 1.16), having an age lower than 25 years (OR = 1.14) and being a rural citizen (OR = 2.36) associate with lethal attempters classes. The males tend to use more violent methods and have more completed suicide. Majority of the individuals are non-lethal attempters who need to be addressed by implementing preventive interventions and mental support provision. Copyright © 2017. Published by Elsevier B.V.

  4. Predicting healthy lifestyle patterns among retirement age older adults in the WELL study: a latent class analysis of sex differences.

    Science.gov (United States)

    Södergren, Marita; Wang, Wei Chun; Salmon, Jo; Ball, Kylie; Crawford, David; McNaughton, Sarah A

    2014-01-01

    The aim of this study was to identify subgroups of retirement age older adults with respect to their lifestyle patterns of eating, drinking, smoking, physical activity and TV viewing behaviors, and to examine the association between these patterns and socio-demographic covariates. The sample consisted of 3133 older adults aged 55-65 years from the Wellbeing, Eating and Exercise for a Long Life (WELL) study, 2010. This study used latent class analysis (stratified by sex), with a set of lifestyle indicators and including socio-demographic covariates. Statistical analyses were performed by generalized linear latent and mixed models in Stata. Two classes of lifestyle patterns were identified: Healthy (53% men and 72% women) and less healthy lifestyles. Physical activity, TV-viewing time, and fruit intake were good indicators distinguishing the "Healthier" class, whereas consumption of vegetables, alcohol (men) and fast food (women) could not clearly discriminate older adults in the two classes. Class membership was associated with education, body mass index, and self-rated health. This study contributes to the literature on lifestyle behaviors among older adults, and provides evidence that there are meaningful sex differences in lifestyle behaviors between subgroups of older adults. From a policy perspective, understanding indicators or "markers" of healthy and less healthy lifestyle patterns is important for identifying target groups for interventions. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  5. Latent profile analysis of lifestyle characteristics and health risk behaviors among Koreans who have completed industrial accident care.

    Science.gov (United States)

    Choi, Wan-Suk; Moon, Ok-Kon; Yeum, Dong-Moon

    2017-10-07

    This study investigated the characteristics and health behavior profiles of 1,803 workers who had experienced industrial accidents. Average weekly exercise days, average number of cigarettes smoked per day, average daily sleep duration, and number of days of alcohol consumption were selected to investigate health behavior profiles. Specifically, latent profile analysis was applied to identify the health behavior profiles of people who had completed industrial accident care; the latent classes were the health-conscious type (n=240), the potential-risk type (n=850), and the high-risk type (n=713). Comparison of the health-conscious and potential-risk types indicated that younger subjects, the employed, and those with lower social status and life satisfaction were more likely to be the potential-risk type. Comparison of the health-conscious and high-risk types revealed that males, younger subjects, the employed, those without chronic illnesses, and those with lower social status and life satisfaction were more likely to be the high-risk type. The results suggest that industrial accident victims who have completed accident care have different health behaviors and it is necessary to improve health promotion based on health type characteristics.

  6. Knowledge, Skills and Competence Modelling in Nuclear Engineering Domain using Singular Value Decomposition (SVD) and Latent Semantic Analysis (LSA)

    International Nuclear Information System (INIS)

    Kuo, V.

    2016-01-01

    Full text: The European Qualifications Framework categorizes learning objectives into three qualifiers “knowledge”, “skills”, and “competences” (KSCs) to help improve the comparability between different fields and disciplines. However, the management of KSCs remains a great challenge given their semantic fuzziness. Similar texts may describe different concepts and different texts may describe similar concepts among different domains. This is difficult for the indexing, searching and matching of semantically similar KSCs within an information system, to facilitate transfer and mobility of KSCs. We present a working example using a semantic inference method known as Latent Semantic Analysis, employing a matrix operation called Singular Value Decomposition, which have been shown to infer semantic associations within unstructured textual data comparable to that of human interpretations. In our example, a few natural language text passages representing KSCs in the nuclear sector are used to demonstrate the capabilities of the system. It can be shown that LSA is able to infer latent semantic associations between texts, and cluster and match separate text passages semantically based on these associations. We propose this methodology for modelling existing natural language KSCs in the nuclear domain so they can be semantically queried, retrieved and filtered upon request. (author

  7. Functional Impairment and Changes in Depression Subtypes for Women in STAR*D: A Latent Transition Analysis

    Science.gov (United States)

    Rothschild, Anthony J.; Lapane, Kate L.

    2016-01-01

    Abstract Objective: To characterize the association between functional impairment and major depression subtypes at baseline and to characterize changes in subtypes by functional impairment level in women receiving citalopram in level 1 of the Sequenced Treatment Alternatives to Relieve Depression trial. Method: Women who completed baseline and week 12 study visits were included. Items from the self-reported Quick Inventory of Depressive Symptomatology were used to define the latent depression subtypes. The Work and Social Adjustment Scale was used to classify baseline functional impairment. A latent transition analysis model provided estimates of the prevalence of subtype membership and transition probabilities by functional impairment level. Results: Of the 755 women included, 69% had major functional impairment at baseline. Regardless of functional impairment level, the subtypes were differentiated by depression severity, appetite changes, psychomotor disturbances, and insomnia. Sixty-seven percent of women with normal/significant functional impairment and 60% of women with major impairment were likely to transition to a symptom resolution subtype at week 12. Women with baseline major impairment who were in the severe with psychomotor agitation subtype at the beginning of the study were least likely to transition to the symptom resolution subtype (4% chance). Conclusions: Functional impairment level was related to both the baseline depression subtype and the likelihood of moving to a different subtype. These results underscore the need to incorporate not only depression symptoms but also functioning in the assessment and treatment of depression. PMID:26488110

  8. Outcomes of empirical eating disorder phenotypes in a clinical female sample: results from a latent class analysis.

    Science.gov (United States)

    Dechartres, Agnes; Huas, Caroline; Godart, Nathalie; Pousset, Maud; Pham, Alexandra; Divac, Snezana M; Rouillon, Frederic; Falissard, Bruno

    2011-01-01

    To empirically classify phenotypes of eating disorders (ED) using latent class analysis (LCA), and to validate this classification based on clinical outcomes. LCA was applied to 968 inpatients. The resultant classes were validated by clinical outcomes including mortality. A 5-class solution showed the best fit. The symptoms of latent class 1 (LC1; 26% of the sample) resembled anorexia nervosa (AN), bingeing-purging (AN-B/P) subtype; those of LC2 (23%) resembled bulimia nervosa; those of LC3 (11%) were close to AN-B/P without weight and body concerns; those of LC4 resembled restrictive anorexia nervosa (RAN) without weight and body concerns, and those of LC5 RAN. A history of hospitalization for ED was significantly more frequent for LC3 and LC4. The lowest BMI at admission were presented in LC4. LC1 showed the highest level of psychological disturbances and LC4 the lowest. LC3 and LC4 differed from LC1 and LC5 by higher percentages of treatment dropout (64.9 vs. 57.2 and 55.7 vs. 47.5%, respectively; overall p = 0.001). Survival rates tended to be different between the LC (p = 0.09). Subgroups of AN patients with low weight and body concerns seem more severe at hospitalization and more difficult to manage, with a higher rate of treatment dropout than the 'typical' AN patients. Copyright © 2010 S. Karger AG, Basel.

  9. Microaggressions, Discrimination, and Phenotype among African Americans: A Latent Class Analysis of the Impact of Skin Tone and BMI.

    Science.gov (United States)

    Keith, Verna M; Nguyen, Ann W; Taylor, Robert Joseph; Mouzon, Dawne M; Chatters, Linda M

    2017-05-01

    Data from the 2001-2003National Survey of American Life are used to investigate the effects of phenotype on everyday experiences with discrimination among African Americans (N=3343). Latent class analysis is used to identify four classes of discriminatory treatment: 1) low levels of discrimination, 2) disrespect and condescension, 3) character-based discrimination, and 4) high levels of discrimination. We then employ latent class multinomial logistic regression to evaluate the association between skin tone and body weight and these four classes of discrimination. Designating the low level discrimination class as the reference group, findings revealed that respondents with darker skin were more likely to be classified into the disrespect/condescension and the high level microaggression types. BMI was unrelated to the discrimination type, although there was a significant interaction effect between gender and BMI. BMI was strongly and positively associated with membership in the disrespect and condescension type among men but not among women. These findings indicate that skin tone and body weight are two phenotypic characteristics that influence the type and frequency of discrimination experienced by African Americans.

  10. The latent factor structure of acute stress disorder following bank robbery: testing alternative models in light of the pending DSM-5.

    Science.gov (United States)

    Hansen, Maj; Lasgaard, Mathias; Elklit, Ask

    2013-03-01

    Acute stress disorder (ASD) was introduced into the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV; American Psychiatric Association, 1994) to identify posttraumatic stress reactions occurring within the first month after a trauma and thus help to identify victims at risk of developing posttraumatic stress disorder (PTSD). Since its introduction, research into ASD has focused on the prediction of PTSD, whereas only a few studies have investigated the latent structure of ASD. Results of the latter have been mixed. In light of the current proposal for the ASD diagnosis in the pending DSM-5, there is a profound need for empirical studies that investigate the latent structure of ASD prior to the DSM-5 being finalized. Based on previous factor analytic research, the DSM-IV, and the proposed DSM-5 formulation of ASD, four different models of the latent structure of ASD were specified and estimated. The analyses were based on a national study of bank robbery victims (N = 450) using the acute stress disorder scale. The results of the confirmatory factor analyses showed that the DSM-IV model provided the best fit to the data. Thus, the present study suggests that the latent structure of ASD may best be characterized according to the four-factor DSM-IV model of ASD (i.e., dissociation, re-experiencing, avoidance, and arousal) following exposure to bank robbery. The results are pertinent in light of the pending DSM-5 and add to the debate about the conceptualization of ASD. . © 2012 The British Psychological Society.

  11. A framework for estimating causal effects in latent class analysis: is there a causal link between early sex and subsequent profiles of delinquency?

    Science.gov (United States)

    Butera, Nicole M; Lanza, Stephanie T; Coffman, Donna L

    2014-06-01

    Prevention scientists use latent class analysis (LCA) with increasing frequency to characterize complex behavior patterns and profiles of risk. Often, the most important research questions in these studies involve establishing characteristics that predict membership in the latent classes, thus describing the composition of the subgroups and suggesting possible points of intervention. More recently, prevention scientists have begun to adopt modern methods for drawing causal inference from observational data because of the bias that can be introduced by confounders. This same issue of confounding exists in any analysis of observational data, including prediction of latent class membership. This study demonstrates a straightforward approach to causal inference in LCA that builds on propensity score methods. We demonstrate this approach by examining the causal effect of early sex on subsequent delinquency latent classes using data from 1,890 adolescents in 11th and 12th grade from wave I of the National Longitudinal Study of Adolescent Health. Prior to the statistical adjustment for potential confounders, early sex was significantly associated with delinquency latent class membership for both genders (p = 0.02). However, the propensity score adjusted analysis indicated no evidence for a causal effect of early sex on delinquency class membership (p = 0.76) for either gender. Sample R and SAS code is included in an Appendix in the ESM so that prevention scientists may adopt this approach to causal inference in LCA in their own work.

  12. Complexity in action: Untangling latent relationships between land quality, economic structures and socio-spatial patterns in Italy.

    Directory of Open Access Journals (Sweden)

    Luca Salvati

    Full Text Available Land quality, a key economic capital supporting local development, is affected by biophysical and anthropogenic factors. Taken as a relevant attribute of economic systems, land quality has shaped the territorial organization of any given region influencing localization of agriculture, industry and settlements. In regions with long-established human-landscape interactions, such as the Mediterranean basin, land quality has determined social disparities and polarization in the use of land, reflecting the action of geographical gradients based on elevation and population density. The present study investigates latent relationships within a large set of indicators profiling local communities and land quality on a fine-grained resolution scale in Italy with the aim to assess the potential impact of land quality on the regional socioeconomic structure. The importance of land quality gradients in the socioeconomic configuration of urban and rural regions was verified analyzing the distribution of 149 socioeconomic and environmental indicators organized in 5 themes and 17 research dimensions. Agriculture, income, education and labour market variables discriminate areas with high land quality from areas with low land quality. While differential land quality in peri-urban areas may reflect conflicts between competing actors, moderate (or low quality of land in rural districts is associated with depopulation, land abandonment, subsidence agriculture, unemployment and low educational levels. We conclude that the socioeconomic profile of local communities has been influenced by land quality in a different way along urban-rural gradients. Policies integrating environmental and socioeconomic measures are required to consider land quality as a pivotal target for sustainable development. Regional planning will benefit from an in-depth understanding of place-specific relationships between local communities and the environment.

  13. Complexity in action: Untangling latent relationships between land quality, economic structures and socio-spatial patterns in Italy.

    Science.gov (United States)

    Salvati, Luca; Tombolini, Ilaria; Gemmiti, Roberta; Carlucci, Margherita; Bajocco, Sofia; Perini, Luigi; Ferrara, Agostino; Colantoni, Andrea

    2017-01-01

    Land quality, a key economic capital supporting local development, is affected by biophysical and anthropogenic factors. Taken as a relevant attribute of economic systems, land quality has shaped the territorial organization of any given region influencing localization of agriculture, industry and settlements. In regions with long-established human-landscape interactions, such as the Mediterranean basin, land quality has determined social disparities and polarization in the use of land, reflecting the action of geographical gradients based on elevation and population density. The present study investigates latent relationships within a large set of indicators profiling local communities and land quality on a fine-grained resolution scale in Italy with the aim to assess the potential impact of land quality on the regional socioeconomic structure. The importance of land quality gradients in the socioeconomic configuration of urban and rural regions was verified analyzing the distribution of 149 socioeconomic and environmental indicators organized in 5 themes and 17 research dimensions. Agriculture, income, education and labour market variables discriminate areas with high land quality from areas with low land quality. While differential land quality in peri-urban areas may reflect conflicts between competing actors, moderate (or low) quality of land in rural districts is associated with depopulation, land abandonment, subsidence agriculture, unemployment and low educational levels. We conclude that the socioeconomic profile of local communities has been influenced by land quality in a different way along urban-rural gradients. Policies integrating environmental and socioeconomic measures are required to consider land quality as a pivotal target for sustainable development. Regional planning will benefit from an in-depth understanding of place-specific relationships between local communities and the environment.

  14. Application of core–shell-structured CdTe-SiO2 quantum dots synthesized via a facile solution method for improving latent fingerprint detection

    International Nuclear Information System (INIS)

    Gao Feng; Han Jiaxing; Lv Caifeng; Wang Qin; Zhang Jun; Li Qun; Bao Liru; Li Xin

    2012-01-01

    Fingerprint detection is important in criminal investigation. This paper reports a facile powder brushing technique for improving latent fingerprint detection using core–shell-structured CdTe-SiO 2 quantum dots (QDs) as fluorescent labeling marks. Core–shell-structured CdTe-SiO 2 QDs are prepared via a simple solution-based approach using NH 2 NH 2 ·H 2 O as pH adjustor and stabilizer, and their application for improving latent fingerprint detection is explored. The obtained CdTe-SiO 2 QDs show spherical shapes with well-defined core–shell structures encapsulating different amounts of QDs depending on the type of the pH adjustor and stabilizer. Moreover, the fluorescence of CdTe-SiO 2 QDs is largely enhanced by surface modification of the SiO 2 shell. The CdTe-SiO 2 QDs overcome the oxidation problem of pure CdTe QDs in air, thus affording better variability with strong adhesive ability, better resolution, and bright emission colors for practical application in latent fingerprint detection. In comparison with the conventional fluorescence powders, silver powders, and others, the effectiveness of CdTe-SiO 2 QD powders for detection of latent fingerprints present on a large variety of object surfaces is greatly improved. The synthesis method for CdTe-SiO 2 QDs is simple, cheap, and easy for large-scale production, and thus offers many advantages in the practical application of fingerprint detection.

  15. Space-time latent component Modeling of Geo-referenced health data

    OpenAIRE

    Lawson, Andrew B.; Song, Hae-Ryoung; Cai, Bo; Hossain, Md Monir; Huang, Kun

    2010-01-01

    Latent structure models have been proposed in many applications. For space time health data it is often important to be able to find underlying trends in time which are supported by subsets of small areas. Latent structure modeling is one approach to this analysis. This paper presents a mixture-based approach that can be appied to component selction. The analysis of a Georgia ambulatory asthma county level data set is presented and a simulation-based evaluation is made.

  16. Longitudinal Research with Latent Variables

    CERN Document Server

    van Montfort, Kees; Satorra, Albert

    2010-01-01

    This book combines longitudinal research and latent variable research, i.e. it explains how longitudinal studies with objectives formulated in terms of latent variables should be carried out, with an emphasis on detailing how the methods are applied. Because longitudinal research with latent variables currently utilizes different approaches with different histories, different types of research questions, and different computer programs to perform the analysis, the book is divided into nine chapters. Starting from some background information about the specific approach, short history and the ma

  17. Two-Year Predictive Validity of Conduct Disorder Subtypes in Early Adolescence: A Latent Class Analysis of a Canadian Longitudinal Sample

    Science.gov (United States)

    Lacourse, Eric; Baillargeon, Raymond; Dupere, Veronique; Vitaro, Frank; Romano, Elisa; Tremblay, Richard

    2010-01-01

    Background: Investigating the latent structure of conduct disorder (CD) can help clarify how symptoms related to aggression, property destruction, theft, and serious violations of rules cluster in individuals with this disorder. Discovering homogeneous subtypes can be useful for etiologic, treatment, and prevention purposes depending on the…

  18. Latent profile analysis of students’ motivation and outcomes in mathematics: an organismic integration theory perspective

    Directory of Open Access Journals (Sweden)

    Chee Keng John Wang

    2017-05-01

    Full Text Available The purpose of the current study was to identify the motivation profiles at the intraindividual level using a latent profile analyses (LPA approach. A total of 1151 secondary school students aged 13 to 17 years old from Singapore took part in the study. Using LPA, four distinct motivational profiles were identified based on four motivation regulations. Profile 1 has very low introjected and low autonomous motivation (6% of sample. Profile 2 had high external and identified regulations and very low intrinsic regulation (10%. Profile 3 consisted of students with high identified and intrinsic regulations (51%. Profile 4 had moderately low identified and intrinsic regulations (33%. The results showed that the four profiles differed significantly in terms of effort, competence, value, and time spent on math beyond homework. The best profile (Profile 3 reported highest scores in effort, value, competence and time spent on Math beyond homework. The worst profile (Profile 1 reported lowest scores in all the four outcome variables. Keywords: Education

  19. Identification of children with mathematics learning disabilities (MLDs) using latent class growth analysis.

    Science.gov (United States)

    Wong, Terry T-Y; Ho, Connie S-H; Tang, Joey

    2014-11-01

    The traditional way of identifying children with mathematics learning disabilities (MLDs) using the low-achievement method with one-off assessment suffers from several limitations (e.g., arbitrary cutoff, measurement error, lacking consideration of growth). The present study attempted to identify children with MLD using the latent growth modelling approach, which minimizes the above potential problems. Two hundred and ten Chinese-speaking children were classified into five classes based on their arithmetic performance over 3 years. Their performance on various number-related cognitive measures was also assessed. A potential MLD class was identified, which demonstrated poor achievement over the 3 years and showed smaller improvement over time compared with the average-achieving class. This class had deficits in all number-related cognitive skills, hence supporting the number sense deficit hypothesis. On the other hand, another low-achieving class, which showed little improvement in arithmetic skills over time, was also identified. This class had an average cognitive profile but a low SES. Interventions should be provided to both low-achieving classes according to their needs. Copyright © 2014 Elsevier Ltd. All rights reserved.

  20. School climate and bullying victimization: a latent class growth model analysis.

    Science.gov (United States)

    Gage, Nicholas A; Prykanowski, Debra A; Larson, Alvin

    2014-09-01

    Researchers investigating school-level approaches for bullying prevention are beginning to discuss and target school climate as a construct that (a) may predict prevalence and (b) be an avenue for school-wide intervention efforts (i.e., increasing positive school climate). Although promising, research has not fully examined and established the social-ecological link between school climate factors and bullying/peer aggression. To address this gap, we examined the association between school climate factors and bullying victimization for 4,742 students in Grades 3-12 across 3 school years in a large, very diverse urban school district using latent class growth modeling. Across 3 different models (elementary, secondary, and transition to middle school), a 3-class model was identified, which included students at high-risk for bullying victimization. Results indicated that, for all students, respect for diversity and student differences (e.g., racial diversity) predicted within-class decreases in reports of bullying. High-risk elementary students reported that adult support in school was a significant predictor of within-class reduction of bullying, and high-risk secondary students report peer support as a significant predictor of within-class reduction of bullying. PsycINFO Database Record (c) 2014 APA, all rights reserved.

  1. Parenting characteristics in the home environment and adolescent overweight: a latent class analysis.

    Science.gov (United States)

    Berge, Jerica M; Wall, Melanie; Bauer, Katherine W; Neumark-Sztainer, Dianne

    2010-04-01

    Parenting style and parental support and modeling of physical activity and healthy dietary intake have been linked to youth weight status, although findings have been inconsistent across studies. Furthermore, little is known about how these factors co-occur, and the influence of the coexistence of these factors on adolescents' weight. This article examines the relationship between the co-occurrence of various parenting characteristics and adolescents' weight status. Data are from Project EAT (eating among teens), a population-based study of 4,746 diverse adolescents. Theoretical and latent class groupings of parenting styles and parenting practices were created. Regression analyses examined the relationship between the created variables and adolescents' BMI. Having an authoritarian mother was associated with higher BMI in sons. The co-occurrence of an authoritarian mother and neglectful father was associated with higher BMI for sons. Daughters' whose fathers did not model or encourage healthy behaviors reported higher BMIs. The co-occurrence of neither parent modeling healthy behaviors was associated with higher BMIs for sons, and incongruent parental modeling and encouraging of healthy behaviors was associated with higher BMIs in daughters. Although, further research into the complex dynamics of the home environment is needed, findings indicate that authoritarian parenting style is associated with higher adolescent weight status and incongruent parenting styles and practices between mothers and fathers are associated with higher adolescent weight status.

  2. Next generation sequencing and molecular analysis of artichoke Italian latent virus.

    Science.gov (United States)

    Elbeaino, Toufic; Belghacem, Imen; Mascia, Tiziana; Gallitelli, Donato; Digiaro, Michele

    2017-06-01

    Next-generation sequencing (NGS) allowed the assembly of the complete RNA-1 and RNA-2 sequences of a grapevine isolate of artichoke Italian latent virus (AILV). RNA-1 and RNA-2 are 7,338 and 4,630 nucleotides in length excluding the 3' terminal poly(A) tail, and encode two putative polyproteins of 255.8 kDa (p1) and 149.6 kDa (p2), respectively. All conserved motifs and predicted cleavage sites, typical for nepovirus polyproteins, were found in p1 and p2. AILV p1 and p2 share high amino acid identity with their homologues in beet ringspot virus (p1, 81% and p2, 71%), tomato black ring virus (p1, 79% and p2, 63%), grapevine Anatolian ringspot virus (p1, 65% and p2, 63%), and grapevine chrome mosaic virus (p1, 60% and p2, 54%), and to a lesser extent with other grapevine nepoviruses of subgroup A and C. Phylogenetic and sequence analyses, all confirmed the strict relationship of AILV with members classified in subgroup B of genus Nepovirus.

  3. Examination of the heterogeneity in PTSD and impulsivity facets: A latent profile analysis.

    Science.gov (United States)

    Contractor, Ateka A; Caldas, Stephanie; Weiss, Nicole H; Armour, Cherie

    2018-04-15

    The experience of traumatizing events and resulting posttraumatic stress disorder (PTSD) symptomology relates to a range of impulsive behaviors. While both PTSD and impulsivity are heterogeneous and multidimensional constructs, no research has used person-centered approaches to examine subgroups of individuals based on these response endorsements. Hence, our study examined PTSD-impulsivity typologies and their construct validity in two samples: university students ( n = 412) and community participants recruited through Amazon's MTurk ( n = 346). Measures included the Stressful Life Events Screening Questionnaire (PTEs), PTSD Checklist for DSM-5 (PTSD severity), UPPS Impulsive Behavior Scale (negative urgency, lack of premeditation, lack of perseverance, sensation seeking). Dimensions of Anger Reaction Scale (anger), and the Patient Health Questionnaire-9 (depression). For both samples, results of latent profile analyses indicated a best-fitting 3-class solution: High, Moderate, and Low PTSD-Negative Urgency. Negative urgency was the most distinguishing impulsivity facet. Anger and depression severity significantly predicted membership in the more severe symptomatology classes. Thus, individuals can be meaningfully categorized into three subgroups based on PTSD and impulsivity item endorsements. We provide some preliminary evidence for a negative urgency subtype of PTSD characterized by greater depression and anger regulation difficulties; and underscore addressing emotional regulation skills for these subgroup members.

  4. Analysis of Immunogenicity of Intracellular CTAR Fragments of Epstein-Barr Virus Latent Phase Protein LMP1.

    Science.gov (United States)

    Lomakin, Ya A; Shmidt, A A; Bobik, T V; Chernov, A S; Pyrkov, A Yu; Aleksandrova, N M; Okunola, D O; Vaskina, M I; Ponomarenko, N A; Telegin, G B; Dubina, M V; Belogurov, A A

    2017-10-01

    Intracellular fragments of latent phase protein LMP1 of Epstein-Barr virus, denoted as CTAR1/2/3, can trigger a variety of cell cascades and contribute to the transforming potential of the virus. Generation of recombinant proteins CTAR1/2/3 is expected to yield more ample data on functional and immunogenic characteristics of LMP1. We created genetic constructs for prokaryotic expression of LMP1 CTAR fragments and selected optimal conditions for their production and purification. Using a new library of LMP1 CTAR fragments, we carried out epitope mapping of a diagnostic anti-LMP1 antibody S12. Analysis of polyclonal serum antibodies from mice immunized with full-length LMP1 confirmed immunogenicity of CTAR elements comparable with that of full-length protein.

  5. Effect of prenatal mindfulness training on depressive symptom severity through 18-months postpartum: A latent profile analysis.

    Science.gov (United States)

    Felder, Jennifer N; Roubinov, Danielle; Bush, Nicole R; Coleman-Phox, Kimberly; Vieten, Cassandra; Laraia, Barbara; Adler, Nancy E; Epel, Elissa

    2018-02-28

    We examined whether prenatal mindfulness training was associated with lower depressive symptoms through 18-months postpartum compared to treatment as usual (TAU). A controlled, quasi-experimental trial compared prenatal mindfulness training (MMT) to TAU. We collected depressive symptom data at post-intervention, 6-, and 18-months postpartum. Latent profile analysis identified depressive symptom profiles, and multinomial logistic regression examined whether treatment condition predicted profile. Three depressive symptom severity profiles emerged: none/minimal, mild, and moderate. Adjusting for relevant covariates, MMT participants were less likely than TAU participants to be in the moderate profile than the none/minimal profile (OR = 0.13, 95% CI = 0.03-0.54, p = .005). Prenatal mindfulness training may have benefits for depressive symptoms during the transition to parenthood. © 2018 Wiley Periodicals, Inc.

  6. A latent class analysis of social activities and health among community-dwelling older adults in Korea.

    Science.gov (United States)

    Park, Mi Jin; Park, Nan Sook; Chiriboga, David A

    2018-05-01

    This study presents an empirical typology of social activity and its association with the depressive symptoms and self-rated health of community-dwelling older adults (n = 464) in South Korea. Latent class analysis (LCA) was used to classify the types of social activities. Data analyses were conducted using Mplus 7.2 program for LCA and SPSS 22.0 for multiple regression analyses. LCA identified people who fell into one of the four activity groups: Diverse, Community Center/Disengaged, Religion Plus, and Friendship/Leisure. Membership in these four groups predicted differences in depressive symptoms and self-rated health. Results indicate that typologies of social activity could enhance practitioners' understanding of activity patterns and their associations with health and well-being.

  7. Examination of emotion-induced changes in eating: A latent profile analysis of the Emotional Appetite Questionnaire.

    Science.gov (United States)

    Bourdier, L; Morvan, Y; Kotbagi, G; Kern, L; Romo, L; Berthoz, S

    2018-04-01

    It is now recognized that emotions can influence food intake. While some people report eating less when distressed, others report either no change of eating or eating more in the same condition. The question whether this interindividual variability also occurs in response to positive emotions has been overlooked in most studies on Emotional Eating (EE). Using the Emotional Appetite Questionnaire (EMAQ) and Latent Profile Analysis, this study aimed to examine the existence of latent emotion-induced changes in eating profiles, and explore how these profiles differ by testing their relations with 1) age and sex, 2) BMI and risk for eating disorders (ED) and 3) factors that are known to be associated with EE such as perceived positive/negative feelings, depression, anxiety, stress symptoms and impulsivity. Among 401 university students (245 females) who completed the EMAQ, 3 profiles emerged (P1:11.2%, P2:60.1%, P3:28.7%), with distinct patterns of eating behaviors in response to negative emotions and situations but few differences regarding positive ones. Negative emotional overeaters (P1) and negative emotional undereaters (P3) reported similar levels of emotional distress and positive feelings, and were at greater risk for ED. However, the people in the former profile i) reported decreasing their food intake in a positive context, ii) were in majority females, iii) had higher BMI and iv) were more prone to report acting rashly when experiencing negative emotions. Our findings suggest that a person-centred analysis of the EMAQ scores offers a promising way to capture the inter-individual variability of emotionally-driven eating behaviors. These observations also add to the growing literature underscoring the importance of further investigating the role of different facets of impulsivity in triggering overeating and to develop more targeted interventions of EE. Copyright © 2017 Elsevier Ltd. All rights reserved.

  8. Work Disability among Employees with Diabetes: Latent Class Analysis of Risk Factors in Three Prospective Cohort Studies.

    Directory of Open Access Journals (Sweden)

    Marianna Virtanen

    Full Text Available Studies of work disability in diabetes have examined diabetes as a homogeneous disease. We sought to identify subgroups among persons with diabetes based on potential risk factors for work disability.Participants were 2,445 employees with diabetes from three prospective cohorts (the Finnish Public Sector study, the GAZEL study, and the Whitehall II study. Work disability was ascertained via linkage to registers of sickness absence and disability pensions during a follow-up of 4 years. Study-specific latent class analysis was used to identify subgroups according to prevalent comorbid disease and health-risk behaviours. Study-specific associations with work disability at follow-up were pooled using fixed-effects meta-analysis.Separate latent class analyses for men and women in each cohort supported a two-class solution with one subgroup (total n = 1,086; 44.4% having high prevalence of chronic somatic diseases, psychological symptoms, obesity, physical inactivity and abstinence from alcohol and the other subgroup (total n = 1,359; 55.6% low prevalence of these factors. In the adjusted meta-analyses, participants in the 'high-risk' group had more work disability days (pooled rate ratio = 1.66, 95% CI 1.38-1.99 and more work disability episodes (pooled rate ratio = 1.33, 95% CI 1.21-1.46. These associations were similar in men and women, younger and older participants, and across occupational groups.Diabetes is not a homogeneous disease in terms of work disability risk. Approximately half of people with diabetes are assigned to a subgroup characterised by clustering of comorbid health conditions, obesity, physical inactivity, abstinence of alcohol, and associated high risk of work disability; the other half to a subgroup characterised by a more favourable risk profile.

  9. Environmental, morphological, and productive characterization of Sardinian goats and use of latent explanatory factors for population analysis.

    Science.gov (United States)

    Vacca, G M; Paschino, P; Dettori, M L; Bergamaschi, M; Cipolat-Gotet, C; Bittante, G; Pazzola, M

    2016-09-01

    Dairy goat farming is practiced worldwide, within a range of different farming systems. Here we investigated the effects of environmental factors and morphology on milk traits of the Sardinian goat population. Sardinian goats are currently reared in Sardinia (Italy) in a low-input context, similar to many goat farming systems, especially in developing countries. Milk and morphological traits from 1,050 Sardinian goats from 42 farms were recorded. We observed a high variability regarding morphological traits, such as coat color, ear length and direction, horn presence, and udder shape. Such variability derived partly from the unplanned repeated crossbreeding of the native Sardinian goats with exotic breeds, especially Maltese goats. The farms located in the mountains were characterized by the traditional farming system and the lowest percentage of crossbred goats. Explanatory factors analysis was used to summarize the interrelated measured milk variables. The explanatory factor related to fat, protein, and energy content of milk (the "Quality" latent variable) explained about 30% of the variance of the whole data set of measured milk traits followed by the "Hygiene" (19%), "Production" (19%), and "Acidity" (11%) factors. The "Quality" and "Hygiene" factors were not affected by any of the farm classification items, whereas "Production" and "Acidity" were affected only by altitude and size of herds, respectively, indicating the adaptation of the local goat population to different environmental conditions. The use of latent explanatory factor analysis allowed us to clearly explain the large variability of milk traits, revealing that the Sardinian goat population cannot be divided into subpopulations based on milk attitude The factors, properly integrated with genetic data, may be useful tools in future selection programs.

  10. Distinct Classes of Negative Alcohol-Related Consequences in a National Sample of Incoming First-Year College Students: A Latent Class Analysis.

    Science.gov (United States)

    Rinker, Dipali Venkataraman; Diamond, Pamela M; Walters, Scott T; Wyatt, Todd M; DeJong, William

    2016-09-01

    : First-year college students are at particular risk for experiencing negative alcohol-related consequences that may set the stage for experiencing such consequences in later life. Latent class analysis is a person-centered approach that, based on observable indicator variables, divides a population into mutually exclusive and exhaustive groups ('classes'). To date, no studies have examined the latent class structure of negative alcohol-related consequences experienced by first-year college students just before entering college. The aims of this study were to (a) identify classes of first-year college students based on the patterns of negative alcohol-related consequences they experienced just before entering college, and (b) determine whether specific covariates were associated with class membership. Incoming freshmen from 148 colleges and universities (N = 54,435) completed a baseline questionnaire as part of an alcohol education program they completed just prior to their first year of college. Participants answered questions regarding demographics and other personal characteristics, their alcohol use in the past 2 weeks, and the negative alcohol-related consequences they had experienced during that time. Four distinct classes of students emerged: (a) No Problems, (b) Academic Problems, (c) Injured Self and (d) Severe Problems. Average number of drinks per drinking day, total number of drinking days, age of drinking initiation, intention to join a fraternity or sorority and family history of alcohol problems were associated with membership in all of the problem classes relative to the No Problems class. These results can inform future campus-based prevention efforts. © The Author 2016. Medical Council on Alcohol and Oxford University Press. All rights reserved.

  11. Food shopping profiles and their association with dietary patterns: A latent class analysis

    Science.gov (United States)

    Erickson, Darin J.; Laska, Melissa N.

    2015-01-01

    Background Food shopping is a complex behavior that consists of multiple dimensions. Little research has explored multiple dimensions of food shopping or examined how it relates to dietary intake. Objective To identify patterns (or ‘classes’) of food shopping across four domains (fresh food purchasing, “conscientious” food shopping, food shopping locations, and food/beverage purchasing on or near campus) and explore how these patterns relate to dietary intake among college students. Design A cross-sectional online survey was administered. Participants/setting Students attending a public 4-year university and a 2-year community college in the Twin Cities metropolitan area (n=1,201) participated in this study. Main outcome measures Fast food and soda consumption; meeting fruit and vegetable, fiber, added sugar, calcium, dairy, and fat recommendations. Statistical analyses Crude and adjusted latent class models and adjusted logistic regression models were fit. Results An eight-class solution was identified: “traditional shopper (14.9%),” “fresh food and supermarket shopper (14.1%),” “convenience shopper (18.8%),” “conscientious convenience shopper (13.8%),” “conscientious, fresh food, convenience shopper (11.8%),” “conscientious fresh food shopper (6.6%),” “conscientious non-shopper (10.2%)”, and “non-shopper (9.8%).” “Fresh food and supermarket shoppers” and “conscientious fresh food shopper” had better dietary intake (for fast food, calcium, dairy, and added sugar) while “convenience shoppers” and “conscientious convenience shoppers,” and “non-shoppers” had worse dietary intake (for soda, calcium, dairy, fiber, and fat) than “traditional shoppers.” Conclusions These findings highlight unique patterns in food shopping and associated dietary patterns that could inform tailoring of nutrition interventions for college students. Additional research is needed to understand modifiable contextual influences of

  12. Latent class analysis of accident risks in usage-based insurance: Evidence from Beijing.

    Science.gov (United States)

    Jin, Wen; Deng, Yinglu; Jiang, Hai; Xie, Qianyan; Shen, Wei; Han, Weijian

    2018-06-01

    Car insurance is quickly becoming a big data industry, with usage-based insurance (UBI) poised to potentially change the business of insurance. Telematics data, which are transmitted from wireless devices in car, are widely used in UBI to obtain individual-level travel and driving characteristics. While most existing studies have introduced telematics data into car insurance pricing, the telematics-related characteristics are directly obtained from the raw data. In this study, we propose to quantify drivers' familiarity with their driving routes and develop models to quantify drivers' accident risks using the telematics data. In addition, we build a latent class model to study the heterogeneity in travel and driving styles based on the telematics data, which has not been investigated in literature. Our main results include: (1) the improvement to the model fit is statistically significant by adding telematics-related characteristics; (2) drivers' familiarity with their driving trips is critical to identify high risk drivers, and the relationship between drivers' familiarity and accident risks is non-linear; (3) the drivers can be classified into two classes, where the first class is the low risk class with 0.54% of its drivers reporting accidents, and the second class is the high risk class with 20.66% of its drivers reporting accidents; and (4) for the low risk class, drivers with high probability of reporting accidents can be identified by travel-behavior-related characteristics, while for the high risk class, they can be identified by driving-behavior-related characteristics. The driver's familiarity will affect the probability of reporting accidents for both classes. Copyright © 2018 Elsevier Ltd. All rights reserved.

  13. Serodiagnosis of tuberculosis in Asian elephants (Elephas maximus in Southern India: a latent class analysis.

    Directory of Open Access Journals (Sweden)

    Shalu Verma-Kumar

    Full Text Available BACKGROUND: Mycobacterium tuberculosis, a causative agent of chronic tuberculosis disease, is widespread among some animal species too. There is paucity of information on the distribution, prevalence and true disease status of tuberculosis in Asian elephants (Elephas maximus. The aim of this study was to estimate the sensitivity and specificity of serological tests to diagnose M. tuberculosis infection in captive elephants in southern India while simultaneously estimating sero-prevalence. METHODOLOGY/PRINCIPAL FINDINGS: Health assessment of 600 elephants was carried out and their sera screened with a commercially available rapid serum test. Trunk wash culture of select rapid serum test positive animals yielded no animal positive for M. tuberculosis isolation. Under Indian field conditions where the true disease status is unknown, we used a latent class model to estimate the diagnostic characteristics of an existing (rapid serum test and new (four in-house ELISA tests. One hundred and seventy nine sera were randomly selected for screening in the five tests. Diagnostic sensitivities of the four ELISAs were 91.3-97.6% (95% Credible Interval (CI: 74.8-99.9 and diagnostic specificity were 89.6-98.5% (95% CI: 79.4-99.9 based on the model we assumed. We estimate that 53.6% (95% CI: 44.6-62.8 of the samples tested were free from infection with M. tuberculosis and 15.9% (97.5% CI: 9.8 - to 24.0 tested positive on all five tests. CONCLUSIONS/SIGNIFICANCE: Our results provide evidence for high prevalence of asymptomatic M. tuberculosis infection in Asian elephants in a captive Indian setting. Further validation of these tests would be important in formulating area-specific effective surveillance and control measures.

  14. Food shopping profiles and their association with dietary patterns: a latent class analysis.

    Science.gov (United States)

    VanKim, Nicole A; Erickson, Darin J; Laska, Melissa N

    2015-07-01

    Food shopping is a complex behavior that consists of multiple dimensions. Little research has explored multiple dimensions of food shopping or examined how it relates to dietary intake. To identify patterns (or classes) of food shopping across four domains (fresh food purchasing, conscientious food shopping, food shopping locations, and food/beverage purchasing on or near campus) and explore how these patterns relate to dietary intake among college students. A cross-sectional online survey was administered. Students attending a public 4-year university and a 2-year community college in the Twin Cities (Minnesota) metropolitan area (N=1,201) participated in this study. Fast-food and soda consumption as well as meeting fruit and vegetable, fiber, added sugar, calcium, dairy, and fat recommendations. Crude and adjusted latent class models and adjusted logistic regression models were fit. An eight-class solution was identified: "traditional shopper" (14.9%), "fresh food and supermarket shopper" (14.1%), "convenience shopper" (18.8%), "conscientious convenience shopper" (13.8%), "conscientious, fresh food, convenience shopper" (11.8%), "conscientious fresh food shopper" (6.6%), "conscientious nonshopper" (10.2%), and "nonshopper" (9.8%). "Fresh food and supermarket shoppers" and "conscientious fresh food shoppers" had better dietary intake (for fast food, calcium, dairy, and added sugar), whereas "convenience shoppers" and "conscientious convenience shoppers," and "nonshoppers" had worse dietary intake (for soda, calcium, dairy, fiber, and fat) than "traditional shoppers." These findings highlight unique patterns in food shopping and associated dietary patterns that could inform tailoring of nutrition interventions for college students. Additional research is needed to understand modifiable contextual influences of healthy food shopping. Copyright © 2015 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.

  15. The Role of Religiousness/Spirituality in Health-Related Quality of Life Among Adolescents with HIV: A Latent Profile Analysis.

    Science.gov (United States)

    Lyon, Maureen E; Kimmel, Allison L; Cheng, Yao Iris; Wang, Jichuan

    2016-10-01

    The purpose of this study was to determine whether distinct latent profiles of religiousness/spirituality exist for ALWH, and if so, are latent profile memberships associated with health-related quality of life (HRQoL). Latent profile analysis of religiosity identified four profiles/groups. Compared to the other three groups, higher levels of emotional well-being were found among young perinatally infected adolescents who attended religious services, but who did not pray privately, feel God's presence or identify as religious or spiritual. Social HRQoL was significantly higher among the highest overall religious/spiritual group. Understanding adolescent profiles of religiousness/spirituality on HRQoL could inform faith-based interventions. Trial registration NCT01289444.

  16. Probabilistic Structural Analysis Program

    Science.gov (United States)

    Pai, Shantaram S.; Chamis, Christos C.; Murthy, Pappu L. N.; Stefko, George L.; Riha, David S.; Thacker, Ben H.; Nagpal, Vinod K.; Mital, Subodh K.

    2010-01-01

    NASA/NESSUS 6.2c is a general-purpose, probabilistic analysis program that computes probability of failure and probabilistic sensitivity measures of engineered systems. Because NASA/NESSUS uses highly computationally efficient and accurate analysis techniques, probabilistic solutions can be obtained even for extremely large and complex models. Once the probabilistic response is quantified, the results can be used to support risk-informed decisions regarding reliability for safety-critical and one-of-a-kind systems, as well as for maintaining a level of quality while reducing manufacturing costs for larger-quantity products. NASA/NESSUS has been successfully applied to a diverse range of problems in aerospace, gas turbine engines, biomechanics, pipelines, defense, weaponry, and infrastructure. This program combines state-of-the-art probabilistic algorithms with general-purpose structural analysis and lifting methods to compute the probabilistic response and reliability of engineered structures. Uncertainties in load, material properties, geometry, boundary conditions, and initial conditions can be simulated. The structural analysis methods include non-linear finite-element methods, heat-transfer analysis, polymer/ceramic matrix composite analysis, monolithic (conventional metallic) materials life-prediction methodologies, boundary element methods, and user-written subroutines. Several probabilistic algorithms are available such as the advanced mean value method and the adaptive importance sampling method. NASA/NESSUS 6.2c is structured in a modular format with 15 elements.

  17. Identifying differences in early literacy skills across subgroups of language-minority children: A latent profile analysis.

    Science.gov (United States)

    Lonigan, Christopher J; Goodrich, J Marc; Farver, JoAnn M

    2018-04-01

    Despite acknowledgment that language-minority children come from a wide variety of home language backgrounds and have a wide range of proficiency in their first (L1) and second (L2) languages, it is unknown whether differences across language-minority children in relative and absolute levels of proficiency in L1 and L2 predict subsequent development of literacy-related skills. The purpose of this study was to identify subgroups of language-minority children and evaluate whether differences in level and rate of growth of early literacy skills differed across subgroups. Five-hundred and twenty-six children completed measures of Spanish and English language and early literacy skills at the beginning, middle, and end of the preschool year. Latent growth models indicated that children's early literacy skills were increasing over the course of the preschool year. Latent profile analysis indicated that language-minority children could be classified into nine distinct groups, each with unique patterns of absolute and relative levels of proficiency in L1 and L2. Results of three-step mixture models indicated that profiles were closely associated with level of early literacy skills at the beginning of the preschool year. Initial level of early literacy skills was positively associated with growth in code-related skills (i.e., print knowledge, phonological awareness) and inversely associated with growth in language skills. These findings suggest that language-minority children are a diverse group with regard to their L1 and L2 proficiencies and that growth in early literacy skills is most associated with level of proficiency in the same language. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  18. Statistically Derived Subtypes and Associations with Cerebrospinal Fluid and Genetic Biomarkers in Mild Cognitive Impairment: A Latent Profile Analysis.

    Science.gov (United States)

    Eppig, Joel S; Edmonds, Emily C; Campbell, Laura; Sanderson-Cimino, Mark; Delano-Wood, Lisa; Bondi, Mark W

    2017-08-01

    Research demonstrates heterogeneous neuropsychological profiles among individuals with mild cognitive impairment (MCI). However, few studies have included visuoconstructional ability or used latent mixture modeling to statistically identify MCI subtypes. Therefore, we examined whether unique neuropsychological MCI profiles could be ascertained using latent profile analysis (LPA), and subsequently investigated cerebrospinal fluid (CSF) biomarkers, genotype, and longitudinal clinical outcomes between the empirically derived classes. A total of 806 participants diagnosed by means of the Alzheimer's Disease Neuroimaging Initiative (ADNI) MCI criteria received a comprehensive neuropsychological battery assessing visuoconstructional ability, language, attention/executive function, and episodic memory. Test scores were adjusted for demographic characteristics using standardized regression coefficients based on "robust" normal control performance (n=260). Calculated Z-scores were subsequently used in the LPA, and CSF-derived biomarkers, genotype, and longitudinal clinical outcome were evaluated between the LPA-derived MCI classes. Statistical fit indices suggested a 3-class model was the optimal LPA solution. The three-class LPA consisted of a mixed impairment MCI class (n=106), an amnestic MCI class (n=455), and an LPA-derived normal class (n=245). Additionally, the amnestic and mixed classes were more likely to be apolipoprotein e4+ and have worse Alzheimer's disease CSF biomarkers than LPA-derived normal subjects. Our study supports significant heterogeneity in MCI neuropsychological profiles using LPA and extends prior work (Edmonds et al., 2015) by demonstrating a lower rate of progression in the approximately one-third of ADNI MCI individuals who may represent "false-positive" diagnoses. Our results underscore the importance of using sensitive, actuarial methods for diagnosing MCI, as current diagnostic methods may be over-inclusive. (JINS, 2017, 23, 564-576).

  19. Identification of subgroups of inflammatory and degenerative MRI findings in the spine and sacroiliac joints: a latent class analysis of 1037 patients with persistent low back pain

    DEFF Research Database (Denmark)

    Arnbak, Bodil; Jensen, Rikke Krüger; Manniche, Claus

    2016-01-01

    BACKGROUND: The aim of this study was to investigate subgroups of magnetic resonance imaging (MRI) findings for the spine and sacroiliac joints (SIJs) using latent class analysis (LCA), and to investigate whether these subgroups differ in their demographic and clinical characteristics. METHODS...

  20. Multilevel Latent Class Analysis for Large-Scale Educational Assessment Data: Exploring the Relation between the Curriculum and Students' Mathematical Strategies

    Science.gov (United States)

    Fagginger Auer, Marije F.; Hickendorff, Marian; Van Putten, Cornelis M.; Béguin, Anton A.; Heiser, Willem J.

    2016-01-01

    A first application of multilevel latent class analysis (MLCA) to educational large-scale assessment data is demonstrated. This statistical technique addresses several of the challenges that assessment data offers. Importantly, MLCA allows modeling of the often ignored teacher effects and of the joint influence of teacher and student variables.…

  1. A Latent Class Analysis of Weight-Related Health Behaviors among 2-and 4-Year College Students and Associated Risk of Obesity

    Science.gov (United States)

    Mathur, Charu; Stigler, Melissa; Lust, Katherine; Laska, Melissa

    2014-01-01

    Little is known about the complex patterning of weight-related health behaviors in 2-and 4-year college students. The objective of this study was to identify and describe unique classes of weight-related health behaviors among college students. Latent class analysis was used to identify homogenous, mutually exclusive classes of nine health…

  2. Latent class analysis of reading, decoding, and writing performance using the Academic Performance Test: concurrent and discriminating validity

    Directory of Open Access Journals (Sweden)

    Cogo-Moreira H

    2013-08-01

    Full Text Available Hugo Cogo-Moreira,1 Carolina Alves Ferreira Carvalho,2 Adriana de Souza Batista Kida,2 Clara Regina Brandão de Avila,2 Giovanni Abrahão Salum,3,5 Tais Silveira Moriyama,1,4 Ary Gadelha,1,5 Luis Augusto Rohde,3,5 Luciana Monteiro de Moura,1 Andrea Parolin Jackowski,1 Jair de Jesus Mari11Department of Psychiatry, Federal University of São Paulo, São Paulo, 2Department of Hearing and Speech Pathology, Federal University of São Paulo, São Paulo, 3Department of Psychiatry, Federal University of Rio Grande do Sul, Rio Grande do Sul, 4Department of Psychiatry, University of São Paulo, São Paulo, 5National Institute for Developmental Psychiatry for Children and Adolescent, (National Counsel of Technological and Scientific Development, BrazilAim: To explore and validate the best returned latent class solution for reading and writing subtests from the Academic Performance Test (TDE.Sample: A total of 1,945 children (6–14 years of age, who answered the TDE, the Development and Well-Being Assessment (DAWBA, and had an estimated intelligence quotient (IQ higher than 70, came from public schools in São Paulo (35 schools and Porto Alegre (22 schools that participated in the ‘High Risk Cohort Study for Childhood Psychiatric Disorders’ project. They were on average 9.52 years old (standard deviation = 1.856, from the 1st to 9th grades, and 53.3% male. The mean estimated IQ was 102.70 (standard deviation = 16.44.Methods: Via Item Response Theory (IRT, the highest discriminating items (‘a’>1.7 were selected from the TDE subtests of reading and writing. A latent class analysis was run based on these subtests. The statistically and empirically best latent class solutions were validated through concurrent (IQ and combined attention deficit hyperactivity disorder [ADHD] diagnoses and discriminant (major depression diagnoses measures.Results: A three-class solution was found to be the best model solution, revealing classes of children with good, not

  3. Psychobehavioral Profiles to Assist Tailoring of Interventions for Patients With Hypertension: Latent Profile Analysis.

    Science.gov (United States)

    Tanaka, Rika; Nolan, Robert P

    2018-05-11

    Practice guidelines advocate combining pharmacotherapy with lifestyle counseling for patients with hypertension. To allow for appropriate tailoring of interventions to meet individual patient needs, a comprehensive understanding of baseline patient characteristics is essential. However, few studies have empirically assessed behavioral profiles of hypertensive patients in Web-based lifestyle counseling programs. The objectives of this study were to (1) specify baseline psychobehavioral profiles of patients with hypertension who were enrolled in a Web-based lifestyle counseling trial, and (2) examine mean differences among the identified profile groups in demographics, psychological distress, self-reported self-care behaviors, physiological outcomes, and program engagement to determine prognostic implications. Participants (N=264; mean age 57.5 years; 154/264, 58.3% female; 193/264, 73.1% white) were recruited into a longitudinal, double-blind, randomized controlled trial, designed to evaluate an online lifestyle intervention for hypertensive patients. A series of latent profile analyses identified psychobehavioral profiles, indicated by baseline measures of mood, motivation, and health behaviors. Mean differences between profile groups were then explored. A 2-class solution provided the best model fit (the Bayesian information criterion (BIC) is 10,133.11; sample-size adjusted BIC is 10,006.54; Lo-Mendell-Rubin likelihood ratio test is 65.56, P=.001). The 2 profile groups were (1) adaptive adjustment, marked by low distress, high motivation, and somewhat satisfactory engagement in health behaviors and (2) affectively distressed, marked by clinically significant distress. At baseline, on average, affectively distressed patients had lower income, higher body mass index, and endorsed higher stress compared with their adaptive adjustment counterparts. At 12-months post intervention, treatment effects were sustained for systolic blood pressure and Framingham risk index

  4. 1842676957299765Latent class cluster analysis to understand heterogeneity in prostate cancer treatment utilities

    Directory of Open Access Journals (Sweden)

    Meghani Salimah

    2009-01-01

    Full Text Available Abstract Background Men with prostate cancer are often challenged to choose between conservative management and a range of available treatment options each carrying varying risks and benefits. The trade-offs are between an improved life-expectancy with treatment accompanied by important risks such as urinary incontinence and erectile dysfunction. Previous studies of preference elicitation for prostate cancer treatment have found considerable heterogeneity in individuals' preferences for health states given similar treatments and clinical risks. Methods Using latent class mixture model (LCA, we first sought to understand if there are unique patterns of heterogeneity or subgroups of individuals based on their prostate cancer treatment utilities (calculated time trade-off utilities for various health states and if such unique subgroups exist, what demographic and urological variables may predict membership in these subgroups. Results The sample (N = 244 included men with prostate cancer (n = 188 and men at-risk for disease (n = 56. The sample was predominantly white (77%, with mean age of 60 years (SD ± 9.5. Most (85.9% were married or living with a significant other. Using LCA, a three class solution yielded the best model evidenced by the smallest Bayesian Information Criterion (BIC, substantial reduction in BIC from a 2-class solution, and Lo-Mendell-Rubin significance of < .001. The three identified clusters were named high-traders (n = 31, low-traders (n = 116, and no-traders (n = 97. High-traders were more likely to trade survival time associated with treatment to avoid potential risks of treatment. Low-traders were less likely to trade survival time and accepted risks of treatment. The no-traders were likely to make no trade-offs in any direction favouring the status quo. There was significant difference among the clusters in the importance of sexual activity (Pearson's χ2 = 16.55, P = 0.002; Goodman and Kruskal tau = 0.039, P < 0.001. In

  5. Friendship networks of inner-city adults: a latent class analysis and multi-level regression of supporter types and the association of supporter latent class membership with supporter and recipient drug use.

    Science.gov (United States)

    Bohnert, Amy S B; German, Danielle; Knowlton, Amy R; Latkin, Carl A

    2010-03-01

    Social support is a multi-dimensional construct that is important to drug use cessation. The present study identified types of supportive friends among the social network members in a community-based sample and examined the relationship of supporter-type classes with supporter, recipient, and supporter-recipient relationship characteristics. We hypothesized that the most supportive network members and their support recipients would be less likely to be current heroin/cocaine users. Participants (n=1453) were recruited from low-income neighborhoods with a high prevalence of drug use. Participants identified their friends via a network inventory, and all nominated friends were included in a latent class analysis and grouped based on their probability of providing seven types of support. These latent classes were included as the dependent variable in a multi-level regression of supporter drug use, recipient drug use, and other characteristics. The best-fitting latent class model identified five support patterns: friends who provided Little/No Support, Low/Moderate Support, High Support, Socialization Support, and Financial Support. In bivariate models, friends in the High, Low/Moderate, and Financial Support were less likely to use heroin or cocaine and had less conflict with and were more trusted by the support recipient than friends in the Low/No Support class. Individuals with supporters in those same support classes compared to the Low/No Support class were less likely to use heroin or cocaine, or to be homeless or female. Multivariable models suggested similar trends. Those with current heroin/cocaine use were less likely to provide or receive comprehensive support from friends. Published by Elsevier Ireland Ltd.

  6. Clustering of immunological, metabolic and genetic features in latent autoimmune diabetes in adults: evidence from principal component analysis.

    Science.gov (United States)

    Pes, Giovanni Mario; Delitala, Alessandro Palmerio; Errigo, Alessandra; Delitala, Giuseppe; Dore, Maria Pina

    2016-06-01

    Latent autoimmune diabetes in adults (LADA) which accounts for more than 10 % of all cases of diabetes is characterized by onset after age 30, absence of ketoacidosis, insulin independence for at least 6 months, and presence of circulating islet-cell antibodies. Its marked heterogeneity in clinical features and immunological markers suggests the existence of multiple mechanisms underlying its pathogenesis. The principal component (PC) analysis is a statistical approach used for finding patterns in data of high dimension. In this study the PC analysis was applied to a set of variables from a cohort of Sardinian LADA patients to identify a smaller number of latent patterns. A list of 11 variables including clinical (gender, BMI, lipid profile, systolic and diastolic blood pressure and insulin-free time period), immunological (anti-GAD65, anti-IA-2 and anti-TPO antibody titers) and genetic features (predisposing gene variants previously identified as risk factors for autoimmune diabetes) retrieved from clinical records of 238 LADA patients referred to the Internal Medicine Unit of University of Sassari, Italy, were analyzed by PC analysis. The predictive value of each PC on the further development of insulin dependence was evaluated using Kaplan-Meier curves. Overall 4 clusters were identified by PC analysis. In component PC-1, the dominant variables were: BMI, triglycerides, systolic and diastolic blood pressure and duration of insulin-free time period; in PC-2: genetic variables such as Class II HLA, CTLA-4 as well as anti-GAD65, anti-IA-2 and anti-TPO antibody titers, and the insulin-free time period predominated; in PC-3: gender and triglycerides; and in PC-4: total cholesterol. These components explained 18, 15, 12, and 12 %, respectively, of the total variance in the LADA cohort. The predictive power of insulin dependence of the four components was different. PC-2 (characterized mostly by high antibody titers and presence of predisposing genetic markers

  7. Not all experiences of (inauthenticity are created equal: A latent class analysis approach(retitled Identifying Differences in the Experience of (InAuthenticity: A Latent Class Analysis Approach

    Directory of Open Access Journals (Sweden)

    Alison P. Lenton

    2014-07-01

    Full Text Available Generally, psychologists consider state authenticity– that is, the subjective sense of being one’s true self – to be a unitary and unidimensional construct, such that (a the phenomenological experience of authenticity is thought to be similar no matter its trigger, and (b inauthenticity is thought to be simply the opposing pole (on the same underlying construct of authenticity. Using latent class analysis, we put this conceptualization to a test. In order to avoid over-reliance on a Western conceptualization of authenticity, we used a cross-cultural sample (N = 543, comprising participants from Western, South-Asian, East-Asian, and South-East Asian cultures. Participants provided either a narrative in which the described when they felt most like being themselves or one in which they described when they felt least like being themselves. The analysis identified six distinct classes of experiences: two authenticity classes ('everyday' and 'extraordinary', three inauthenticity classes ('self-conscious,' 'deflated,' and 'extraordinary', and a class representing convergence between authenticity and inauthenticity. The classes were phenomenologically distinct, especially with respect to negative affect, private and public self-consciousness, and self-esteem. Furthermore, relatively more interdependent cultures were less likely to report experiences of extraordinary (inauthenticity than relatively more independent cultures. Understanding the many facets of (inauthenticity may enable researchers to connect different findings and explain why the attainment of authenticity can be difficult.

  8. Latent Class Analysis of HIV Risk Behaviors Among Russian Women at Risk for Alcohol-Exposed Pregnancies.

    Science.gov (United States)

    Bohora, Som; Chaffin, Mark; Shaboltas, Alla; Bonner, Barbara; Isurina, Galina; Batluk, Julia; Bard, David; Tsvetkova, Larissa; Skitnevskaya, Larissa; Volkova, Elena; Balachova, Tatiana

    2017-11-01

    The number of HIV cases attributed to heterosexual contact and the proportion of women among HIV positive individuals has increased worldwide. Russia is a country with the highest rates of newly diagnosed HIV infections in the region, and the infection spreads beyond traditional risk groups. While young women are affected disproportionately, knowledge of HIV risk behaviors in women in the general population remains limited. The objectives of this study were to identify patterns of behaviors that place women of childbearing age at high risk for HIV transmission and determine whether socio-demographic characteristics and alcohol use are predictive of the risk pattern. A total of 708 non-pregnant women, aged between 18 and 44 years, who were at risk for an alcohol-exposed pregnancy were enrolled in two regions in Russia. Participants completed a structured interview focused on HIV risk behaviors, including risky sexual behavior and alcohol and drug use. Latent class analysis was utilized to examine associations between HIV risk and other demographic and alcohol use characteristics and to identify patterns of risk among women. Three classes were identified. 34.93% of participants were at high risk, combining their risk behaviors, e.g., having multiple sexual partners, with high partner's risk associated with partner's drug use (class I). Despite reporting self-perceived risk for HIV/STI, this class of participants was unlikely to utilize adequate protection (i.e., condom use). The second high risk class included 13.19% of participants who combined their risky sexual behaviors, i.e., multiple sexual partners and having STDs, with partner's risk that included partner's imprisonment and partner's sex with other women (class II). Participants in this class were likely to utilize protection/condoms. Finally, 51.88% of participants were at lower risk, which was associated primarily with their partners' risk, and these participants utilized protection (class III). The odds

  9. Second law analysis of a diesel engine waste heat recovery with a combined sensible and latent heat storage system

    International Nuclear Information System (INIS)

    Pandiyarajan, V.; Chinnappandian, M.; Raghavan, V.; Velraj, R.

    2011-01-01

    The exhaust gas from an internal combustion engine carries away about 30% of the heat of combustion. The energy available in the exit stream of many energy conversion devices goes as waste. The major technical constraint that prevents successful implementation of waste heat recovery is due to intermittent and time mismatched demand for and availability of energy. The present work deals with the use of exergy as an efficient tool to measure the quantity and quality of energy extracted from a diesel engine and stored in a combined sensible and latent heat storage system. This analysis is utilized to identify the sources of losses in useful energy within the components of the system considered, and provides a more realistic and meaningful assessment than the conventional energy analysis. The energy and exergy balance for the overall system is quantified and illustrated using energy and exergy flow diagrams. In order to study the discharge process in a thermal storage system, an illustrative example with two different cases is considered and analyzed, to quantify the destruction of exergy associated with the discharging process. The need for promoting exergy analysis through policy decision in the context of energy and environment crisis is also emphasized. - Highlights: → WHR with TES system eliminates the mismatch between the supply of energy and demand. → A saving of 15.2% of energy and 1.6% of exergy is achieved with PCM storage. → Use of multiple PCMs with cascaded system increases energy and exergy efficiency.

  10. The interpretation of dream meaning: Resolving ambiguity using Latent Semantic Analysis in a small corpus of text.

    Science.gov (United States)

    Altszyler, Edgar; Ribeiro, Sidarta; Sigman, Mariano; Fernández Slezak, Diego

    2017-11-01

    Computer-based dreams content analysis relies on word frequencies within predefined categories in order to identify different elements in text. As a complementary approach, we explored the capabilities and limitations of word-embedding techniques to identify word usage patterns among dream reports. These tools allow us to quantify words associations in text and to identify the meaning of target words. Word-embeddings have been extensively studied in large datasets, but only a few studies analyze semantic representations in small corpora. To fill this gap, we compared Skip-gram and Latent Semantic Analysis (LSA) capabilities to extract semantic associations from dream reports. LSA showed better performance than Skip-gram in small size corpora in two tests. Furthermore, LSA captured relevant word associations in dream collection, even in cases with low-frequency words or small numbers of dreams. Word associations in dreams reports can thus be quantified by LSA, which opens new avenues for dream interpretation and decoding. Copyright © 2017 Elsevier Inc. All rights reserved.

  11. Systematic Expression Profiling Analysis Identifies Specific MicroRNA-Gene Interactions that May Differentiate between Active and Latent Tuberculosis Infection

    Directory of Open Access Journals (Sweden)

    Lawrence Shih-Hsin Wu

    2014-01-01

    Full Text Available Tuberculosis (TB is the second most common cause of death from infectious diseases. About 90% of those infected are asymptomatic—the so-called latent TB infections (LTBI, with a 10% lifetime chance of progressing to active TB. To further understand the molecular pathogenesis of TB, several molecular studies have attempted to compare the expression profiles between healthy controls and active TB or LTBI patients. However, the results vary due to diverse genetic backgrounds and study designs and the inherent complexity of the disease process. Thus, developing a sensitive and efficient method for the detection of LTBI is both crucial and challenging. For the present study, we performed a systematic analysis of the gene and microRNA profiles of healthy individuals versus those affected with TB or LTBI. Combined with a series of in silico analysis utilizing publicly available microRNA knowledge bases and published literature data, we have uncovered several microRNA-gene interactions that specifically target both the blood and lungs. Some of these molecular interactions are novel and may serve as potential biomarkers of TB and LTBI, facilitating the development for a more sensitive, efficient, and cost-effective diagnostic assay for TB and LTBI for the Taiwanese population.

  12. Systematic expression profiling analysis identifies specific microRNA-gene interactions that may differentiate between active and latent tuberculosis infection.

    Science.gov (United States)

    Wu, Lawrence Shih-Hsin; Lee, Shih-Wei; Huang, Kai-Yao; Lee, Tzong-Yi; Hsu, Paul Wei-Che; Weng, Julia Tzu-Ya

    2014-01-01

    Tuberculosis (TB) is the second most common cause of death from infectious diseases. About 90% of those infected are asymptomatic--the so-called latent TB infections (LTBI), with a 10% lifetime chance of progressing to active TB. To further understand the molecular pathogenesis of TB, several molecular studies have attempted to compare the expression profiles between healthy controls and active TB or LTBI patients. However, the results vary due to diverse genetic backgrounds and study designs and the inherent complexity of the disease process. Thus, developing a sensitive and efficient method for the detection of LTBI is both crucial and challenging. For the present study, we performed a systematic analysis of the gene and microRNA profiles of healthy individuals versus those affected with TB or LTBI. Combined with a series of in silico analysis utilizing publicly available microRNA knowledge bases and published literature data, we have uncovered several microRNA-gene interactions that specifically target both the blood and lungs. Some of these molecular interactions are novel and may serve as potential biomarkers of TB and LTBI, facilitating the development for a more sensitive, efficient, and cost-effective diagnostic assay for TB and LTBI for the Taiwanese population.

  13. A latent class analysis of friendship network types and their predictors in the second half of life.

    Science.gov (United States)

    Miche, Martina; Huxhold, Oliver; Stevens, Nan L

    2013-07-01

    Friendships contribute uniquely to well-being in (late) adulthood. However, studies on friendship often ignore interindividual differences in friendship patterns. The aim of this study was to investigate such differences including their predictors. The study builds on Matthews's qualitative model of friendship styles. Matthews distinguished 3 approaches to friendship differing by number of friends, duration of friendships, and emotional closeness. We used latent class analysis to identify friendship network types in a sample of middle-aged and older adults aged 40-85 years (N = 1,876). Data came from the German Aging Survey (DEAS). Our analysis revealed 4 distinct friendship network types that were in high congruence with Matthews's typology. We identified these as a discerning style, which focuses on few close relationships, an independent style, which refrains from close engagements, and 2 acquisitive styles that both acquire new friends across their whole life course but differ regarding the emotional closeness of their friendships. Socioeconomic status, gender, health, and network-disturbing and network-sustaining variables predicted affiliations with network types. We argue that future studies should consider a holistic view of friendships in order to better understand the association between friendships and well-being in the second half of life.

  14. Changes in Classes of Injury-Related Risks and Consequences of Risk-Level Drinking: a Latent Transition Analysis.

    Science.gov (United States)

    Cochran, Gerald; Field, Craig; Caetano, Raul

    2015-07-01

    Risk-level drinking, drinking and driving, and alcohol-related violence are risk factors that result in injuries. The current study sought to identify which subgroups of patients experience the most behavioral change following a brief intervention. A secondary analysis of data from a brief alcohol intervention study was conducted. The sample (N = 664) includes at-risk drinkers who experienced an injury and were admitted for care to a Level 1 trauma center. Injury-related items from the Short Inventory of Problems+6 were used to perform a latent transition analysis to describe class transitions participants experienced following discharge. Four classes emerged for the year before and after the current injury. Most individuals transitioned from higher-risk classes into those with lower risk. Some participants maintained risky profiles, and others increased risks and consequences. Drinking and driving remained a persistent problem among the study participants. Although a large portion of intervention recipients improved risks and consequences of alcohol use following discharge, more intensive intervention services may be needed for a subset of patients who showed little or no improvement.

  15. Structural analysis for Diagnosis

    DEFF Research Database (Denmark)

    Izadi-Zamanabadi, Roozbeh; Blanke, M.

    2001-01-01

    Aiming at design of algorithms for fault diagnosis, structural analysis of systems offers concise yet easy overall analysis. Graph-based matching, which is the essential technique to obtain redundant information for diagnosis, is re-considered in this paper. Matching is re-formulated as a problem...... of relating faults to known parameters and measurements of a system. Using explicit fault modelling, minimal over-determined subsystems are shown to provide necessary redundancy relations from the matching. Details of the method are presented and a realistic example used to clearly describe individual steps...

  16. Structural analysis for diagnosis

    DEFF Research Database (Denmark)

    Izadi-Zamanabadi, Roozbeh; Blanke, M.

    2002-01-01

    Aiming at design of algorithms for fault diagnosis, structural analysis of systems offers concise yet easy overall analysis. Graph-based matching, which is the essential tech-nique to obtain redundant information for diagnosis, is reconsidered in this paper. Matching is reformulated as a problem...... of relating faults to known parameters and measurements of a system. Using explicit fault modelling, minimal overdetermined subsystems are shown to provide necessary redundancy relations from the matching. Details of the method are presented and a realistic example used to clearly describe individual steps....

  17. Structural analysis of DAEs

    DEFF Research Database (Denmark)

    Poulsen, Mikael Zebbelin

    2002-01-01

    , by the implementation of the Simpy tool box. This is an object oriented system implemented in the Python language. It can be used for analysis of DAEs, ODEs and non-linear equation and uses e.g. symbolic representations of expressions and equations. The presentations of theory and algorithms for structural index......Differential algebraic equations (DAEs) constitute a fundamental model class for many modelling purposes in engineering and other sciences, especially for dynamical simulation of component based systems. This thesis describes a practical methodology and approach for analysing general DAE...... analysis of DAE is original in the sense that it is based on a new matrix representation of the structural information of a general DAE system instead of a graph oriented representation. Also the presentation of the theory is found to be more complete compared to other presentations, since it e.g. proves...

  18. Cationic bis-N-heterocyclic carbene (NHC) ruthenium complex: Structure and application as latent catalyst in olefin metathesis

    KAUST Repository

    Rouen, Mathieu

    2014-09-11

    An unexpected cationic bis-N-heterocyclic carbene (NHC) benzylidene ether based ruthenium complex (2 a) was prepared through the double incorporation of an unsymmetrical unsaturated N-heterocyclic carbene (U2-NHC) ligand that bore an N-substituted cyclododecyl side chain. The isolation and full characterization (including X-ray diffraction studies) of key synthetic intermediates along with theoretical calculations allowed us to understand the mechanism of the overall cationization process. Finally, the newly developed complex 2 a displayed interesting latent behavior during ring-closing metathesis, which could be "switched on" under acidic conditions.

  19. The latent structure of Posttraumatic Stress Disorder among Arabic-speaking refugees receiving psychiatric treatment in Denmark

    DEFF Research Database (Denmark)

    Vindbjerg, Erik; Carlsson, Jessica; Mortensen, Erik Lykke

    2016-01-01

    provided sufficient fit indices. However, a combination of excessively small clusters, and a case of mistranslation in the official Arabic translation of the HTQ, rendered results two of the models inadmissible. A post hoc analysis revealed that a simpler factor structure is supported, once local...... dependence is addressed. Conclusions: Overall, the construct of PTSD is supported in this sample of arabic-speaking refugees. Apart from pursuing maximum fit, future studies may wish to test simpler, potentially more stable models, which allow a more informative analysis of individual items....

  20. Maltreatment and Mental Health Outcomes among Ultra-Poor Children in Burkina Faso: A Latent Class Analysis.

    Science.gov (United States)

    Ismayilova, Leyla; Gaveras, Eleni; Blum, Austin; Tô-Camier, Alexice; Nanema, Rachel

    2016-01-01

    Research about the mental health of children in Francophone West Africa is scarce. This paper examines the relationships between adverse childhood experiences, including exposure to violence and exploitation, and mental health outcomes among children living in ultra-poverty in rural Burkina Faso. This paper utilizes baseline data collected from 360 children ages 10-15 and 360 of their mothers recruited from twelve impoverished villages in the Nord Region of Burkina, located near the Sahel Desert and affected by extreme food insecurity. We used a Latent Class Analysis to identify underlying patterns of maltreatment. Further, the relationships between latent classes and mental health outcomes were tested using mixed effected regression models adjusted for clustering within villages. About 15% of the children in the study scored above the clinical cut-off for depression, 17.8% for posttraumatic stress disorder (PTSD), and 6.4% for low self-esteem. The study identified five distinct sub-groups (or classes) of children based on their exposure to adverse childhood experiences. Children with the highest exposure to violence at home, at work and in the community (Abused and Exploited class) and children not attending school and working for other households, often away from their families (External Laborer class), demonstrated highest symptoms of depression and trauma. Despite living in adverse conditions and working to assist families, the study also identified a class of children who were not exposed to any violence at home or at work (Healthy and Non-abused class). Children in this class demonstrated significantly higher self-esteem (b = 0.92, SE = 0.45, p<0.05) and lower symptoms of trauma (b = -3.90, SE = 1.52, p<0.05). This study offers insight into the psychological well-being of children in the context of ultra-poverty in Burkina Faso and associated context-specific adverse childhood experiences. Identifying specific sub-groups of children with increased exposure to

  1. Latent geometry of bipartite networks

    Science.gov (United States)

    Kitsak, Maksim; Papadopoulos, Fragkiskos; Krioukov, Dmitri

    2017-03-01

    Despite the abundance of bipartite networked systems, their organizing principles are less studied compared to unipartite networks. Bipartite networks are often analyzed after projecting them onto one of the two sets of nodes. As a result of the projection, nodes of the same set are linked together if they have at least one neighbor in common in the bipartite network. Even though these projections allow one to study bipartite networks using tools developed for unipartite networks, one-mode projections lead to significant loss of information and artificial inflation of the projected network with fully connected subgraphs. Here we pursue a different approach for analyzing bipartite systems that is based on the observation that such systems have a latent metric structure: network nodes are points in a latent metric space, while connections are more likely to form between nodes separated by shorter distances. This approach has been developed for unipartite networks, and relatively little is known about its applicability to bipartite systems. Here, we fully analyze a simple latent-geometric model of bipartite networks and show that this model explains the peculiar structural properties of many real bipartite systems, including the distributions of common neighbors and bipartite clustering. We also analyze the geometric information loss in one-mode projections in this model and propose an efficient method to infer the latent pairwise distances between nodes. Uncovering the latent geometry underlying real bipartite networks can find applications in diverse domains, ranging from constructing efficient recommender systems to understanding cell metabolism.

  2. Pathological and non-pathological variants of restrictive eating behaviors in middle childhood: A latent class analysis.

    Science.gov (United States)

    Schmidt, Ricarda; Vogel, Mandy; Hiemisch, Andreas; Kiess, Wieland; Hilbert, Anja

    2018-08-01

    Although restrictive eating behaviors are very common during early childhood, their precise nature and clinical correlates remain unclear. Especially, there is little evidence on restrictive eating behaviors in older children and their associations with children's shape concern. The present population-based study sought to delineate subgroups of restrictive eating patterns in N = 799 7-14 year old children. Using Latent Class Analysis, children were classified based on six restrictive eating behaviors (for example, picky eating, food neophobia, and eating-related anxiety) and shape concern, separately in three age groups. For cluster validation, sociodemographic and objective anthropometric data, parental feeding practices, and general and eating disorder psychopathology were used. The results showed a 3-cluster solution across all age groups: an asymptomatic class (Cluster 1), a class with restrictive eating behaviors without shape concern (Cluster 2), and a class showing restrictive eating behaviors with prominent shape concern (Cluster 3). The clusters differed in all variables used for validation. Particularly, the proportion of children with symptoms of avoidant/restrictive food intake disorder was greater in Cluster 2 than Clusters 1 and 3. The study underlined the importance of considering shape concern to distinguish between different phenotypes of children's restrictive eating patterns. Longitudinal data are needed to evaluate the clusters' predictive effects on children's growth and development of clinical eating disorders. Copyright © 2018 Elsevier Ltd. All rights reserved.

  3. A latent class analysis of bullies, victims and aggressive victims in Chinese adolescence: relations with social and school adjustments.

    Directory of Open Access Journals (Sweden)

    Aihui Shao

    Full Text Available This study used the latent class analysis (LCA to identify and classify Chinese adolescent children's aggressive behaviors. It was found that (1 Adolescent children could be divided into four categories: general children, aggressive children, victimized children and aggressive victimized children. (2 There were significant gender differences among the aggressive victimized children, the aggressive children and the general children. Specifically, aggressive victimized children and aggressive children had greater probabilities of being boys; victimized children had equal probabilities of being boys or girls. (3 Significant differences in loneliness, depression, anxiety and academic achievement existed among the aggressive victims, the aggressor, the victims and the general children, in which the aggressive victims scored the worst in all questionnaires. (4 As protective factors, peer and teacher supports had important influences on children's aggressive and victimized behaviors. Relative to general children, aggressive victims, aggressive children and victimized children had lower probabilities of receiving peer supports. On the other hand, compared to general children, aggressive victims had lower probabilities of receiving teacher supports; while significant differences in the probability of receiving teacher supports did not exist between aggressive children and victimized children.

  4. Exposure to Different Types of Violence and Subsequent Sexual Risk Behavior among Female STD Clinic Patients: A Latent Class Analysis

    Science.gov (United States)

    Walsh, Jennifer L.; Senn, Theresa E.; Carey, Michael P.

    2013-01-01

    Objective Diverse forms of violence, including childhood maltreatment (CM), intimate partner violence (IPV), and exposure to community violence (ECV), have been linked separately with sexual risk behaviors. However, few studies have explored multiple experiences of violence simultaneously in relation to sexual risk-taking, especially in women who are most vulnerable to violent experiences. Methods Participants were 481 women (66% African American, Mage = 27 years) attending a publicly-funded STD clinic who reported on their past and current experiences with violence and their current sexual risk behavior. We identified patterns of experience with violence using latent class analysis (LCA) and investigated which combinations of experiences were associated with the riskiest sexual outcomes. Results Four classes of women with different experiences of violence were identified: Low Violence (39%), Predominantly ECV (20%), Predominantly CM (23%), and Multiply Victimized (18%). Women in the Multiply Victimized and Predominantly ECV classes reported the highest levels of sexual risk behavior, including more lifetime sexual partners and a greater likelihood of receiving STD treatment and using substances before sex. Conclusions Women with different patterns of violent experiences differed in their sexual risk behavior. Interventions to reduce sexual risk should address violence against women, focusing on experiences with multiple types of violence and experiences specifically with ECV. Additional research is needed to determine the best ways to address violence in sexual risk reduction interventions. PMID:23626921

  5. Variations in students' perceived reasons for, sources of, and forms of in-school discrimination: A latent class analysis.

    Science.gov (United States)

    Byrd, Christy M; Carter Andrews, Dorinda J

    2016-08-01

    Although there exists a healthy body of literature related to discrimination in schools, this research has primarily focused on racial or ethnic discrimination as perceived and experienced by students of color. Few studies examine students' perceptions of discrimination from a variety of sources, such as adults and peers, their descriptions of the discrimination, or the frequency of discrimination in the learning environment. Middle and high school students in a Midwestern school district (N=1468) completed surveys identifying whether they experienced discrimination from seven sources (e.g., peers, teachers, administrators), for seven reasons (e.g., gender, race/ethnicity, religion), and in eight forms (e.g., punished more frequently, called names, excluded from social groups). The sample was 52% White, 15% Black/African American, 14% Multiracial, and 17% Other. Latent class analysis was used to cluster individuals based on reported sources of, reasons for, and forms of discrimination. Four clusters were found, and ANOVAs were used to test for differences between clusters on perceptions of school climate, relationships with teachers, perceptions that the school was a "good school," and engagement. The Low Discrimination cluster experienced the best outcomes, whereas an intersectional cluster experienced the most discrimination and the worst outcomes. The results confirm existing research on the negative effects of discrimination. Additionally, the paper adds to the literature by highlighting the importance of an intersectional approach to examining students' perceptions of in-school discrimination. Copyright © 2016 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

  6. Anxiety is not enough to drive me away: A latent profile analysis on math anxiety and math motivation.

    Directory of Open Access Journals (Sweden)

    Zhe Wang

    Full Text Available Mathematics anxiety (MA and mathematics motivation (MM are important multi-dimensional non-cognitive factors in mathematics learning. While the negative relation between global MA and MM is well replicated, the relations between specific dimensions of MA and MM are largely unexplored. The present study utilized latent profile analysis to explore profiles of various aspects of MA (including learning MA and exam MA and MM (including importance, self-perceived ability, and interest, to provide a more holistic understanding of the math-specific emotion and motivation experiences. In a sample of 927 high school students (13-21 years old, we found 8 distinct profiles characterized by various combinations of dimensions of MA and MM, revealing the complexity in the math-specific emotion-motivation relation beyond a single negative correlation. Further, these profiles differed on mathematics learning behaviors and mathematics achievement. For example, the highest achieving students reported modest exam MA and high MM, whereas the most engaged students were characterized by a combination of high exam MA and high MM. These results call for the need to move beyond linear relations among global constructs to address the complexity in the emotion-motivation-cognition interplay in mathematics learning, and highlight the importance of customized intervention for these heterogeneous groups.

  7. Acculturation and Self-Rated Mental Health Among Latino and Asian Immigrants in the United States: A Latent Class Analysis.

    Science.gov (United States)

    Bulut, Elif; Gayman, Matthew D

    2016-08-01

    This study assesses variations in acculturation experiences by identifying distinct acculturation classes, and investigates the role of these acculturation classes for self-rated mental health among Latino and Asian immigrants in the United States. Using 2002-2003 the National Latino and Asian American Study, Latent Class Analysis is used to capture variations in immigrant classes (recent arrivals, separated, bicultural and assimilated), and OLS regressions are used to assess the link between acculturation classes and self-rated mental health. For both Latinos and Asians, bicultural immigrants reported the best mental health, and separated immigrants and recent arrivals reported the worst mental health. The findings also reveal group differences in acculturation classes, whereby Latino immigrants were more likely to be in the separated class and recent arrivals class relative to Asian immigrants. While there was not a significant group difference in self-rated mental health at the bivariate level, controlling for acculturation classes revealed that Latinos report better self-rated mental health than Asians. Thus, Latino immigrants would actually have better self-rated mental health than their Asian counterparts if they were not more likely to be represented in less acculturated classes (separated class and recent arrivals) and/or as likely to be in the bicultural class as their Asian counterparts. Together the findings underscore the nuanced and complex nature of the acculturation process, highlighting the importance of race differences in this process, and demonstrate the role of acculturation classes for immigrant group differences in self-rated mental health.

  8. LATENT CLUSTER ANALYSIS OF INSTRUCTIONAL PRACTICES REPORTED BY HIGH- AND LOW-PERFORMING MATHEMATICS TEACHERS IN FOUR COUNTRIES

    Directory of Open Access Journals (Sweden)

    Qiang Cheng

    2017-06-01

    Full Text Available Using Trends in International Mathematics and Science Study (TIMSS 2011 eighth-grade international dataset, this study explored the profiles of instructional practices reported by high- and low-performing mathematics teachers across the US, Finland, Korea, and Russia. Concepts of conceptual teaching and procedural teaching were used to frame the design of the current study. Latent cluster analysis was applied in the investigation of the profiles of mathematics teachers’ instructional practices across the four education systems. It was found that all mathematics teachers in the high- and low-performing groups used procedurally as well as conceptually oriented practices in their teaching. However, one group of high-performing mathematics teachers from the U.S. sample and all the high-performing teachers from Finland, Korea, and Russia showed more frequent use of conceptually oriented practices than their corresponding low-performing teachers. Another group of U.S. high-performing mathematics teachers showed a distinctive procedurally oriented pattern, which presented a rather different picture. Such results provide useful suggestions for practitioners and policy makers in their effort to improve mathematics teaching and learning in the US and in other countries as well.DOI: http://dx.doi.org/10.22342/jme.8.2.4066.115-132

  9. Anxiety is not enough to drive me away: A latent profile analysis on math anxiety and math motivation

    Science.gov (United States)

    Shakeshaft, Nicholas; Schofield, Kerry; Malanchini, Margherita

    2018-01-01

    Mathematics anxiety (MA) and mathematics motivation (MM) are important multi-dimensional non-cognitive factors in mathematics learning. While the negative relation between global MA and MM is well replicated, the relations between specific dimensions of MA and MM are largely unexplored. The present study utilized latent profile analysis to explore profiles of various aspects of MA (including learning MA and exam MA) and MM (including importance, self-perceived ability, and interest), to provide a more holistic understanding of the math-specific emotion and motivation experiences. In a sample of 927 high school students (13–21 years old), we found 8 distinct profiles characterized by various combinations of dimensions of MA and MM, revealing the complexity in the math-specific emotion-motivation relation beyond a single negative correlation. Further, these profiles differed on mathematics learning behaviors and mathematics achievement. For example, the highest achieving students reported modest exam MA and high MM, whereas the most engaged students were characterized by a combination of high exam MA and high MM. These results call for the need to move beyond linear relations among global constructs to address the complexity in the emotion-motivation-cognition interplay in mathematics learning, and highlight the importance of customized intervention for these heterogeneous groups. PMID:29444137

  10. Anxiety is not enough to drive me away: A latent profile analysis on math anxiety and math motivation.

    Science.gov (United States)

    Wang, Zhe; Shakeshaft, Nicholas; Schofield, Kerry; Malanchini, Margherita

    2018-01-01

    Mathematics anxiety (MA) and mathematics motivation (MM) are important multi-dimensional non-cognitive factors in mathematics learning. While the negative relation between global MA and MM is well replicated, the relations between specific dimensions of MA and MM are largely unexplored. The present study utilized latent profile analysis to explore profiles of various aspects of MA (including learning MA and exam MA) and MM (including importance, self-perceived ability, and interest), to provide a more holistic understanding of the math-specific emotion and motivation experiences. In a sample of 927 high school students (13-21 years old), we found 8 distinct profiles characterized by various combinations of dimensions of MA and MM, revealing the complexity in the math-specific emotion-motivation relation beyond a single negative correlation. Further, these profiles differed on mathematics learning behaviors and mathematics achievement. For example, the highest achieving students reported modest exam MA and high MM, whereas the most engaged students were characterized by a combination of high exam MA and high MM. These results call for the need to move beyond linear relations among global constructs to address the complexity in the emotion-motivation-cognition interplay in mathematics learning, and highlight the importance of customized intervention for these heterogeneous groups.

  11. Analysis of culture media screening data by projection to latent pathways: The case of Pichia pastoris X-33.

    Science.gov (United States)

    Isidro, Inês A; Ferreira, Ana R; Clemente, João J; Cunha, António E; Oliveira, Rui

    2016-01-10

    Cell culture media formulations contain hundreds of individual components in water solutions which have complex interactions with metabolic pathways. The currently used statistical design methods are empirical and very limited to explore such a large design space. In a previous work we developed a computational method called projection to latent pathways (PLP), which was conceived to maximize covariance between envirome and fluxome data under the constraint of metabolic network elementary flux modes (EFM). More specifically, PLP identifies a minimal set of EFMs (i.e., pathways) with the highest possible correlation with envirome and fluxome measurements. In this paper we extend the concept for the analysis of culture media screening data to investigate how culture medium components up-regulate or down-regulate key metabolic pathways. A Pichia pastoris X-33 strain was cultivated in 26 shake flask experiments with variations in trace elements concentrations and basal medium dilution, based on the standard BSM+PTM1 medium. PLP identified 3 EFMs (growth, maintenance and by-product formation) describing 98.8% of the variance in observed fluxes. Furthermore, PLP presented an overall predictive power comparable to that of PLS regression. Our results show iron and manganese at concentrations close to the PTM1 standard inhibit overall metabolic activity, while the main salts concentration (BSM) affected mainly energy expenditures for cellular maintenance. Copyright © 2015 Elsevier B.V. All rights reserved.

  12. Two-year trajectory of fall risk in people with Parkinson’s disease: a latent class analysis

    Science.gov (United States)

    Paul, Serene S; Thackeray, Anne; Duncan, Ryan P; Cavanaugh, James T; Ellis, Theresa D; Earhart, Gammon M; Ford, Matthew P; Foreman, K Bo; Dibble, Leland E

    2015-01-01

    Objective To examine fall risk trajectories occurring naturally in a sample of individuals with early to middle stage Parkinson’s disease (PD). Design Latent class analysis, specifically growth mixture modeling (GMM) of longitudinal fall risk trajectories. Setting Not applicable. Participants 230 community-dwelling PD participants of a longitudinal cohort study who attended at least two of five assessments over a two year period. Interventions Not applicable. Main Outcome Measures Fall risk trajectory (low, medium or high risk) and stability of fall risk trajectory (stable or fluctuating). Fall risk was determined at 6-monthly intervals using a simple clinical tool based on fall history, freezing of gait, and gait speed. Results The GMM optimally grouped participants into three fall risk trajectories that closely mirrored baseline fall risk status (p=.001). The high fall risk trajectory was most common (42.6%) and included participants with longer and more severe disease and with higher postural instability and gait disability (PIGD) scores than the low and medium risk trajectories (pfall risk (posterior probability fall risk trajectories over two years. Further investigation is required to determine whether interventions to improve gait and balance may improve fall risk trajectories in people with PD. PMID:26606871

  13. Anxiety and anxious-depression in Parkinson's disease over a 4-year period: a latent transition analysis.

    Science.gov (United States)

    Landau, S; Harris, V; Burn, D J; Hindle, J V; Hurt, C S; Samuel, M; Wilson, K C; Brown, R G

    2016-02-01

    Depression and anxiety in Parkinson's disease are common and frequently co-morbid, with significant impact on health outcome. Nevertheless, management is complex and often suboptimal. The existence of clinical subtypes would support stratified approaches in both research and treatment. Five hundred and thirteen patients with Parkinson's disease were assessed annually for up to 4 years. Latent transition analysis (LTA) was used to identify classes that may conform to clinically meaningful subgroups, transitions between those classes over time, and baseline clinical and demographic features that predict common trajectories. In total, 64.1% of the sample remained in the study at year 4. LTA identified four classes, a 'Psychologically healthy' class (approximately 50%), and three classes associated with psychological distress: one with moderate anxiety alone (approximately 20%), and two with moderate levels of depression plus moderate or severe anxiety. Class membership tended to be stable across years, with only about 15% of individuals transitioning between the healthy class and one of the distress classes. Stable distress was predicted by higher baseline depression and psychiatric history and younger age of onset of Parkinson's disease. Those with younger age of onset were also more likely to become distressed over the course of the study. Psychopathology was characterized by relatively stable anxiety or anxious-depression over the 4-year period. Anxiety, with or without depression, appears to be the prominent psychopathological phenotype in Parkinson's disease suggesting a pressing need to understanding its mechanisms and improve management.

  14. A latent class growth analysis of school bullying and its social context: the self-determination theory perspective.

    Science.gov (United States)

    Lam, Shui-fong; Law, Wilbert; Chan, Chi-Keung; Wong, Bernard P H; Zhang, Xiao

    2015-03-01

    The contribution of social context to school bullying was examined from the self-determination theory perspective in this longitudinal study of 536 adolescents from 3 secondary schools in Hong Kong. Latent class growth analysis of the student-reported data at 5 time points from grade 7 to grade 9 identified 4 groups of students: bullies (9.8%), victims (3.0%), bully-victims (9.4%), and typical students (77.8%). There was a significant association between academic tracking and group membership. Students from the school with the lowest academic performance had a greater chance of being victims and bully-victims. Longitudinal data showed that all 4 groups tended to report less victimization over the years. The victims and the typical students also had a tendency to report less bullying over the years, but this tendency was reversed for bullies and bully-victims. Perceived support from teachers for relatedness significantly predicted membership of the groups of bullies and victims. Students with higher perceived support for relatedness from their teachers had a significantly lower likelihood of being bullies or victims. The findings have implications for the theory and practice of preventive interventions in school bullying.

  15. Concurrent and simultaneous polydrug use: latent class analysis of an Australian nationally representative sample of young adults.

    Directory of Open Access Journals (Sweden)

    Lake-Hui eQuek

    2013-11-01

    Full Text Available Background: Alcohol use and illicit drug use peak during young adulthood (around 18-29 years of age, but comparatively little is known about polydrug use in nationally representative samples of young adults. Drawing on a nationally representative cross-sectional survey (Australian National Drug Strategy Household Survey, this study examines polydrug use patterns and associated psychosocial risk factors among young adults (n = 3,333; age 19-29. Method: The use of a broad range of licit and illicit drugs were examined, including alcohol, tobacco, cannabis, cocaine, hallucinogens, ecstasy, ketamine, GHB, inhalants, steroids, barbiturates, meth/amphetamines, heroin, methadone/buprenorphine, other opiates, painkillers and tranquillizers/sleeping pills. Latent class analysis was employed to identify patterns of polydrug use. Results: Polydrug use in this sample was best described using a 5-class solution. The majority of young adults predominantly used alcohol only (52.3%, alcohol and tobacco (34.18%. The other classes were cannabis, ecstasy, and licit drug use (9.4%, cannabis, amphetamine derivative, and licit drug use (2.8%, and sedative and alcohol use (1.3%. Young adult males with low education and/or high income were most at risk of polydrug use. Conclusion: Almost half of young adults reported polydrug use, highlighting the importance of post-high school screening for key risk factors and polydrug use profiles, and the delivery of early intervention strategies targeting illicit drugs.

  16. How do older adult drivers self-regulate? Characteristics of self-regulation classes defined by latent class analysis.

    Science.gov (United States)

    Bergen, Gwen; West, Bethany A; Luo, Feijun; Bird, Donna C; Freund, Katherine; Fortinsky, Richard H; Staplin, Loren

    2017-06-01

    Motor-vehicle crashes were the second leading cause of injury death for adults aged 65-84years in 2014. Some older drivers choose to self-regulate their driving to maintain mobility while reducing driving risk, yet the process remains poorly understood. Data from 729 older adults (aged ≥60years) who joined an older adult ride service program between April 1, 2010 and November 8, 2013 were analyzed to define and describe classes of driving self-regulation. Latent class analysis was employed to characterize older adult driving self-regulation classes using driving frequency and avoidance of seven driving situations. Logistic regression was used to explore associations between characteristics affecting mobility and self-regulation class. Three classes were identified (low, medium, and high self-regulation). High self-regulating participants reported the highest proportion of always avoiding seven risky driving situations and the lowest driving frequency followed by medium and low self-regulators. Those who were female, aged 80years or older, visually impaired, assistive device users, and those with special health needs were more likely to be high self-regulating compared with low self-regulating. Avoidance of certain driving situations and weekly driving frequency are valid indicators for describing driving self-regulation classes in older adults. Understanding the unique characteristics and mobility limitations of each class can guide optimal transportation strategies for older adults. Published by Elsevier Ltd.

  17. Sensory subtypes in children with autism spectrum disorder: latent profile transition analysis using a national survey of sensory features.

    Science.gov (United States)

    Ausderau, Karla K; Furlong, Melissa; Sideris, John; Bulluck, John; Little, Lauren M; Watson, Linda R; Boyd, Brian A; Belger, Aysenil; Dickie, Virginia A; Baranek, Grace T

    2014-08-01

    Sensory features are highly prevalent and heterogeneous among children with ASD. There is a need to identify homogenous groups of children with ASD based on sensory features (i.e., sensory subtypes) to inform research and treatment. Sensory subtypes and their stability over 1 year were identified through latent profile transition analysis (LPTA) among a national sample of children with ASD. Data were collected from caregivers of children with ASD ages 2-12 years at two time points (Time 1 N = 1294; Time 2 N = 884). Four sensory subtypes (Mild; Sensitive-Distressed; Attenuated-Preoccupied; Extreme-Mixed) were identified, which were supported by fit indices from the LPTA as well as current theoretical models that inform clinical practice. The Mild and Extreme-Mixed subtypes reflected quantitatively different sensory profiles, while the Sensitive-Distressed and Attenuated-Preoccupied subtypes reflected qualitatively different profiles. Further, subtypes reflected differential child (i.e., gender, developmental age, chronological age, autism severity) and family (i.e., income, mother's education) characteristics. Ninety-one percent of participants remained stable in their subtypes over 1 year. Characterizing the nature of homogenous sensory subtypes may facilitate assessment and intervention, as well as potentially inform biological mechanisms. © 2014 The Authors. Journal of Child Psychology and Psychiatry. © 2014 Association for Child and Adolescent Mental Health.

  18. A latent class analysis of substance use and culture among gay, bisexual and other men who have sex with men.

    Science.gov (United States)

    Card, Kiffer G; Armstrong, Heather L; Carter, Allison; Cui, Zishan; Wang, Lu; Zhu, Julia; Lachowsky, Nathan J; Moore, David M; Hogg, Robert S; Roth, Eric A

    2018-03-28

    Assessments of gay and bisexual men's substance use often obscures salient sociocultural and identity-related experiences related to how they use drugs. Latent class analysis was used to examine how patterns of substance use represent the social, economic and identity-related experiences of this population. Participants were sexually active gay and bisexual men (including other men who have sex with men), aged ≥ 16 years, living in Metro Vancouver (n = 774). LCA indicators included all substances used in the past six months self-reported by more than 30 men. Model selection was made with consideration to model parsimony, interpretability and optimisation of statistical criteria. Multinomial regression identified factors associated with class membership. A six-class solution was identified representing: 'assorted drug use' (4.5%); 'club drug use' (9.5%); 'street drug use' (12.1%); 'sex drug use' (11.4%); 'conventional drug use' (i.e. tobacco, alcohol, marijuana; 25.9%); and 'limited drug use' (36.7%). Factors associated with class membership included age, sexual orientation, annual income, occupation, income from drug sales, housing stability, group sex event participation, gay bars/clubs attendance, sensation seeking and escape motivation. These results highlight the need for programmes and policies that seek to lessen social disparities and account for social distinctions among this population.

  19. A Latent Class Analysis of Early Adolescent Peer and Dating Violence: Associations With Symptoms of Depression and Anxiety.

    Science.gov (United States)

    Garthe, Rachel C; Sullivan, Terri N; Behrhorst, Kathryn L

    2018-02-01

    Violence within peer and dating contexts is prevalent among early adolescents. Youth may be victims and/or aggressors and be involved in violence across multiple contexts, resulting in negative outcomes. This study identified patterns of perpetration and victimization for peer and dating violence, using a latent class analysis (LCA), and examined how different patterns of engaging in or experiencing violence among early adolescents were associated with symptoms of depression and anxiety. Participants included a sample of 508 racially and ethnically diverse youth (51% male) who had dated in the past 3 months. Youth were in the seventh grade within 37 schools and were primarily from economically disadvantaged communities across four sites in the United States. LCA identified three classes: (a) a low involvement in violence class, (b) a peer aggression and peer victimization class, and (c) a peer and dating violence class. Youth involved with multiple forms of violence displayed significantly higher levels of depressive and anxious symptoms than those with low involvement in violence. Study findings revealed the importance of understanding how peer and dating violence co-occur, and how different patterns of aggression and victimization were related to internalizing symptoms. Prevention efforts should address the intersection of victimization and perpetration in peer and dating contexts in potentially reducing internalizing symptoms among early adolescents.

  20. Life satisfaction and perceived stress among young offenders in a residential therapeutic community: Latent change score analysis.

    Science.gov (United States)

    Tang, Kristen N S; Chan, Christian S

    2017-06-01

    Recent rehabilitation frameworks underscore the importance of strength-based interventions for young offenders who may lack internal and external resources to manage their stress and plan for their life. This multi-wave longitudinal study investigated the dynamic relationship between perceived stress and life satisfaction among a group of young ex-offenders in a residential therapeutic community. Four waves of data were collected from 117 Hong Kong youths (24.0% female, mean age = 17.7) over one year. Latent change score analysis was employed to examine the univairate and bivariate changes of their perceived stress and life satisfaction. Results suggest a positive growth trajectory in life satisfaction over time. The results of perceived stress were less conclusive. Bivariate models indicated that the previous level of life satisfaction was negatively linked to the subsequent perceived stress level but not vice versa. The findings suggest that improvement in life satisfaction may reduce perceived stress in young ex-offenders. Copyright © 2017 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

  1. Differential factors associated with challenge-proven food allergy phenotypes in a population cohort of infants: a latent class analysis.

    Science.gov (United States)

    Peters, R L; Allen, K J; Dharmage, S C; Lodge, C J; Koplin, J J; Ponsonby, A-L; Wake, M; Lowe, A J; Tang, M L K; Matheson, M C; Gurrin, L C

    2015-05-01

    Food allergy, eczema and wheeze are early manifestations of allergic disease and commonly co-occur in infancy although their interrelationship is not well understood. Data from population studies are essential to determine whether there are differential drivers of multi-allergy phenotypes. We aimed to define phenotypes and risk factors of allergic disease using latent class analysis (LCA). The HealthNuts study is a prospective, population-based cohort of 5276 12-month-old infants in Melbourne, Australia. LCA was performed using the following baseline data collected at age 12 months: food sensitization (skin prick test ≥ 2 mm) and allergy (oral food challenge) to egg, peanut and sesame; early (food-sensitized eczema (16%), single egg allergy (9%), multiple food allergies (predominantly peanut) (3%) and multiple food allergies (predominantly egg) (2%). Compared to the baseline group of no allergic disease, shared risk factors for all allergic phenotypes were parents born overseas (particularly Asia), delayed introduction of egg, male gender (except for single egg allergy) and family history of allergic disease, whilst exposure to pet dogs was protective for all phenotypes. Other factors including filaggrin mutations, vitamin D and the presence of older siblings differed by phenotype. Multiple outcomes in infancy can be used to determine five distinct allergy phenotypes at the population level, which have both shared and separate risk factors suggesting differential mechanisms of disease. © 2014 John Wiley & Sons Ltd.

  2. Information System Hazard Analysis: A Method for Identifying Technology-induced Latent Errors for Safety.

    Science.gov (United States)

    Weber, Jens H; Mason-Blakley, Fieran; Price, Morgan

    2015-01-01

    Many health information and communication technologies (ICT) are safety-critical; moreover, reports of technology-induced adverse events related to them are plentiful in the literature. Despite repeated criticism and calls to action, recent data collected by the Institute of Medicine (IOM) and other organization do not indicate significant improvements with respect to the safety of health ICT systems. A large part of the industry still operates on a reactive "break & patch" model; the application of pro-active, systematic hazard analysis methods for engineering ICT that produce "safe by design" products is sparse. This paper applies one such method: Information System Hazard Analysis (ISHA). ISHA adapts and combines hazard analysis techniques from other safety-critical domains and customizes them for ICT. We provide an overview of the steps involved in ISHA and describe.

  3. Collinear Latent Variables in Multilevel Confirmatory Factor Analysis : A Comparison of Maximum Likelihood and Bayesian Estimation

    NARCIS (Netherlands)

    Can, Seda; van de Schoot, Rens|info:eu-repo/dai/nl/304833207; Hox, Joop|info:eu-repo/dai/nl/073351431

    2015-01-01

    Because variables may be correlated in the social and behavioral sciences, multicollinearity might be problematic. This study investigates the effect of collinearity manipulated in within and between levels of a two-level confirmatory factor analysis by Monte Carlo simulation. Furthermore, the

  4. Patterns of Change in Willingness to Communicate in Public Speaking Contexts: A Latent Growth Modeling Analysis

    Science.gov (United States)

    Hodis, Georgeta M.; Bardhan, Nilanjana R.; Hodis, Flaviu A.

    2010-01-01

    This study offers a comprehensive analysis of change in willingness to communicate (WTC) in public speaking contexts (i.e., PS-WTC). The proposed conceptualization of change was tested using longitudinal data collected from a sample of 706 undergraduate students enrolled in an introductory communication course in a US university. Results of latent…

  5. Impact of a Family Empowerment Intervention on Delinquent Behavior: A Latent Growth Model Analysis.

    Science.gov (United States)

    Dembo, Richard; Schmeidler, James; Wothke, Werner

    2003-01-01

    Analysis indicated that reported frequency of involvement in delinquency declined more over time for families receiving Family Empowerment Intervention (FEI) as opposed to those receiving Extended Services Intervention (ESI). Results provide support for the impact of FEI services on reported frequency of delinquent behavior over a 36-month…

  6. Statistical analysis of latent generalized correlation matrix estimation in transelliptical distribution

    OpenAIRE

    Han, Fang; Liu, Han

    2016-01-01

    Correlation matrices play a key role in many multivariate methods (e.g., graphical model estimation and factor analysis). The current state-of-the-art in estimating large correlation matrices focuses on the use of Pearson's sample correlation matrix. Although Pearson's sample correlation matrix enjoys various good properties under Gaussian models, it is not an effective estimator when facing heavy-tailed distributions. As a robust alternative, Han and Liu [J. Am. Stat. Assoc. 109 (2015) 275-2...

  7. Using hybrid latent class model for city-HUBs´users behaviour analysis

    OpenAIRE

    Di Ciommo, Floridea; Monzón de Cáceres, Andrés; Oña, Rocío de; Oña López, Juan de; Hernández del Olmo, Sara

    2014-01-01

    Data from an attitudinal survey and stated preference ranking experiment conducted in two urban European interchanges (i.e. City-HUBs) in Madrid (Spain) and Thessaloniki (Greece) show that the importance that City-HUBs users attach to the intermodal infrastructure varies strongly as a function of their perceptions of time spent in the interchange (i.e.intermodal transfer and waiting time). A principal components analysis allocates respondents (i.e. city-HUB users) to two classes with substant...

  8. Application of a latent variables model for the medical images analysis

    International Nuclear Information System (INIS)

    Campos S, Y.; Ruiz C, S.

    2008-01-01

    In recent years the technological advance has allowed the significant advance in diverse research fields, the medicine has not been exempt of this technology and the use of this technology has allowed a significant advance in the equipment that are used to obtain medical images. The quantity of information that is generated with this equipment has grown in exponential form and it is a difficult task to carry out a quantitative analysis of the data also the manipulation of big quantities of information makes the medical images analysis a complicated task. It is in fact this complexity what motivates this work where one of the main objectives is the analysis of techniques that allow to work with the complexity of the data generated with medical equipment. Likewise, it is wanted to illustrate an application of the peaceful uses of the nuclear energy to treat a medical problem where the diagnostic it depends essentially on the current medical equipment to give an appropriate treatment to the patients. (Author)

  9. Application of a latent variables model for the medical images analysis; Aplicacion de un modelo de variables latentes para el analisis de imagenes medicas

    Energy Technology Data Exchange (ETDEWEB)

    Campos S, Y.; Ruiz C, S. [Centro de Investigacion en Matematica, A.C. Jalisco s/n, Col. Valenciana, Guanajuato (Mexico)

    2008-07-01

    In recent years the technological advance has allowed the significant advance in diverse research fields, the medicine has not been exempt of this technology and the use of this technology has allowed a significant advance in the equipment that are used to obtain medical images. The quantity of information that is generated with this equipment has grown in exponential form and it is a difficult task to carry out a quantitative analysis of the data also the manipulation of big quantities of information makes the medical images analysis a complicated task. It is in fact this complexity what motivates this work where one of the main objectives is the analysis of techniques that allow to work with the complexity of the data generated with medical equipment. Likewise, it is wanted to illustrate an application of the peaceful uses of the nuclear energy to treat a medical problem where the diagnostic it depends essentially on the current medical equipment to give an appropriate treatment to the patients. (Author)

  10. Measurement and structural relations of an authoritative school climate model: A multi-level latent variable investigation.

    Science.gov (United States)

    Konold, Timothy R; Cornell, Dewey

    2015-12-01

    This study tested a conceptual model of school climate in which two key elements of an authoritative school, structure and support variables, are associated with student engagement in school and lower levels of peer aggression. Multilevel multivariate structural modeling was conducted in a statewide sample of 48,027 students in 323 public high schools who completed the Authoritative School Climate Survey. As hypothesized, two measures of structure (Disciplinary Structure and Academic Expectations) and two measures of support (Respect for Students and Willingness to Seek Help) were associated with higher student engagement (Affective Engagement and Cognitive Engagement) and lower peer aggression (Prevalence of Teasing and Bullying) on both student and school levels of analysis, controlling for the effects of school demographics (school size, percentage of minority students, and percentage of low income students). These results support the extension of authoritative school climate model to high school and guide further research on the conditions for a positive school climate. Copyright © 2015 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

  11. Paternal age related schizophrenia (PARS): Latent subgroups detected by k-means clustering analysis.

    Science.gov (United States)

    Lee, Hyejoo; Malaspina, Dolores; Ahn, Hongshik; Perrin, Mary; Opler, Mark G; Kleinhaus, Karine; Harlap, Susan; Goetz, Raymond; Antonius, Daniel

    2011-05-01

    Paternal age related schizophrenia (PARS) has been proposed as a subgroup of schizophrenia with distinct etiology, pathophysiology and symptoms. This study uses a k-means clustering analysis approach to generate hypotheses about differences between PARS and other cases of schizophrenia. We studied PARS (operationally defined as not having any family history of schizophrenia among first and second-degree relatives and fathers' age at birth ≥ 35 years) in a series of schizophrenia cases recruited from a research unit. Data were available on demographic variables, symptoms (Positive and Negative Syndrome Scale; PANSS), cognitive tests (Wechsler Adult Intelligence Scale-Revised; WAIS-R) and olfaction (University of Pennsylvania Smell Identification Test; UPSIT). We conducted a series of k-means clustering analyses to identify clusters of cases containing high concentrations of PARS. Two analyses generated clusters with high concentrations of PARS cases. The first analysis (N=136; PARS=34) revealed a cluster containing 83% PARS cases, in which the patients showed a significant discrepancy between verbal and performance intelligence. The mean paternal and maternal ages were 41 and 33, respectively. The second analysis (N=123; PARS=30) revealed a cluster containing 71% PARS cases, of which 93% were females; the mean age of onset of psychosis, at 17.2, was significantly early. These results strengthen the evidence that PARS cases differ from other patients with schizophrenia. Hypothesis-generating findings suggest that features of PARS may include a discrepancy between verbal and performance intelligence, and in females, an early age of onset. These findings provide a rationale for separating these phenotypes from others in future clinical, genetic and pathophysiologic studies of schizophrenia and in considering responses to treatment. Copyright © 2011 Elsevier B.V. All rights reserved.

  12. Structured Analysis - IDEF0

    DEFF Research Database (Denmark)

    Larsen, Michael Holm

    1999-01-01

    This note introduces the IDEF0 modelling language (semantics and syntax), and associated rules and techniques, for developing structured graphical representations of a system or enterprise. Use of this standard for IDEF0 permits the construction of models comprising system functions (activities...... that require a modelling technique for the analysis, development, re-engineering, integration, or acquisition of information systems; and incorporate a systems or enterprise modelling technique into a business process analysis or software engineering methodology.This note is a summary of the Standard...... for Integration Definition for Function Modelling (IDEF0). I.e. the Draft Federal Information Processing Standards Publication 183, 1993, December 21, Announcing the Standard for Integration Definition for Function Modelling (IDEF0)....

  13. Convenient preparation of high molecular weight poly(dimethylsiloxane using thermally latent NHC-catalysis: a structure-activity correlation

    Directory of Open Access Journals (Sweden)

    Stefan Naumann

    2015-11-01

    Full Text Available The polymerization of octamethylcyclotetrasiloxane (D4 is investigated using several five-, six- and seven-membered N-heterocyclic carbenes (NHCs. The catalysts are delivered in situ from thermally susceptible CO2 adducts. It is demonstrated that the polymerization can be triggered from a latent state by mild heating, using the highly nucleophilic 1,3,4,5-tetramethylimidazol-2-ylidene as organocatalyst. This way, high molecular weight PDMS is prepared (up to >400 000 g/mol, 1.6 ÐM 95%, using low catalyst loadings (0.2–0.1 mol %. Furthermore, the results suggest that a nucleophilic, zwitterionic mechanism is in operation, in preference to purely anionic polymerization.

  14. Parametrical analysis of latent heat and cold storage for heating and cooling of rooms

    International Nuclear Information System (INIS)

    Osterman, E.; Hagel, K.; Rathgeber, C.; Butala, V.; Stritih, U.

    2015-01-01

    One of the problems we are facing today is the energy consumption minimization, while maintaining the indoor thermal comfort in buildings. A potential solution to this issue is use of phase change materials (PCMs) in thermal energy storage (TES), where cold gets accumulated during the summer nights in order to reduce cooling load during the day. In winter, on the other hand, heat from solar air collector is stored for evening and morning hours when solar radiation is not available. The main objective of the paper is to examine experimentally whether it is possible to use such a storage unit for heating as well as for cooling. For this purpose 30 plates filled with paraffin (melting point around 22°C) were positioned into TES and applied with the same initial and boundary conditions as they are expected in reality. Experimental work covered flow visualization, measurements of air velocity in the channels between the plates, parametric analysis in conjunction with TES thermal response and measurements of the pressure drops. The results indicate that this type of storage technology could be advantageously used in real conditions. For optimized thermal behavior, only plate thickness should be reduced. - Highlights: • Thermal properties of paraffin RT22HC were measured. • Flow visualization was carried out and velocity between plates was measured. • Thermal and pressure drop analysis were performed. • Melting times are too long however, use of storage tank for heating and cooling looks promising

  15. Change in the manifestations of asthma and asthma-related traits in childhood: a latent transition analysis.

    Science.gov (United States)

    Garden, Frances L; Simpson, Judy M; Mellis, Craig M; Marks, Guy B

    2016-02-01

    It is known that asthma is a heterogeneous entity whose manifestations vary with age. Our objective was to examine changes in the manifestation of asthma and asthma-related traits in childhood by defining empirically derived childhood asthma phenotypes and examining their transitions over time.To define the phenotypes we used data on respiratory symptoms, healthcare utilisation, medications, spirometry, airway hyperresponsiveness (AHR), exhaled nitric oxide concentration and atopy from a birth cohort recruited on the basis of having a first-degree relative with asthma. Data were acquired at ages 1.5-11.5 years and analysed using latent transition analysis.In a study population of 370 participants, we classified subjects into four phenotypes: 1) nonatopic, few symptoms (prevalence range from 1.5 to 5 years: 52-60%), 2) atopic, few symptoms (3-21%), 3) nonatopic, asthma and rhinitis symptoms (13-35%), and 4) atopic, asthma and rhinitis symptoms (2-14%) in early childhood; and 1) nonatopic, no respiratory disease (prevalence range from 8 to 11.5 years: 41-46%), 2) atopic, no respiratory disease (23-33%), 3) nonatopic, asthma symptoms, no AHR or airway inflammation (8-12%) and 4) atopic asthma (19%) in mid-childhood. Transitioning between phenotypes was common in early childhood, but less common in later childhood.This analysis represents the first attempt to incorporate longitudinal patterns of several manifestations of asthma into a single model to simultaneously define phenotypes and examine their transitions over time. It provides quantitative support for the view that asthma is a heterogeneous entity, and that some children with wheeze and other respiratory symptoms in early life progress to asthma in mid-childhood, while others become asymptomatic. Copyright ©ERS 2016.

  16. Clusters of abusive parenting: a latent class analysis of families referred to Child Protective Services in Portugal.

    Science.gov (United States)

    Matos, Ana Luísa; Moleiro, Carla; Dias, José G

    2014-12-01

    From the perspective of ecological models, it is suggested that a thorough behavior analysis of parental mistreatment and neglect is undertaken from a general approach to a more comprehensive and multi-dimensional perspective. Hence, the main goal of the present study was to determine if meaningful groups or clusters of abusive parenting in Portugal could be identified based on the characterization of the children and adolescents, their parents and context variables. An instrument was developed to assess variables of the children or adolescents, the family and the social context, all of which have been shown to be important in the literature. Child and Youth Protection Commissions from the whole of Portugal participated in the study, a total of 504 cases. Latent class analysis was applied in order to identify distinct parenting abusing behavior. The results showed four distinct clusters of families which are clearly defined in light of the types of risk and associated variables. The four groups are probabilistic and propose the composition of clusters with socio-demographic variables related to the types of risk. The significant interrelationships of different profiling characteristics are directly related to parenting abusing behavior. The results of this study confirmed our hypothesis of heterogeneous abusive parenting in Portugal. The findings yield useful policy-oriented results. Meaningfully organizing abusive parenting may be an important step not only in understanding the origins of abuse and neglect, but also in integrating this information into intervention models with children, young people and their families. Copyright © 2014 Elsevier Ltd. All rights reserved.

  17. Identifying patterns of motor performance, executive functioning, and verbal ability in preschool children: A latent profile analysis.

    Science.gov (United States)

    Houwen, Suzanne; Kamphorst, Erica; van der Veer, Gerda; Cantell, Marja

    2018-04-30

    A relationship between motor performance and cognitive functioning is increasingly being recognized. Yet, little is known about the precise nature of the relationship between both domains, especially in early childhood. To identify distinct constellations of motor performance, executive functioning (EF), and verbal ability in preschool aged children; and to explore how individual and contextual variables are related to profile membership. The sample consisted of 119 3- to 4-year old children (62 boys; 52%). The home based assessments consisted of a standardized motor test (Movement Assessment Battery for Children - 2), five performance-based EF tasks measuring inhibition and working memory, and the Receptive Vocabulary subtest from the Wechsler Preschool and Primary Scale of Intelligence Third Edition. Parents filled out the Behavior Rating Inventory of Executive Function - Preschool version. Latent profile analysis (LPA) was used to delineate profiles of motor performance, EF, and verbal ability. Chi-square statistics and multinomial logistic regression analysis were used to examine whether profile membership was predicted by age, gender, risk of motor coordination difficulties, ADHD symptomatology, language problems, and socioeconomic status (SES). LPA yielded three profiles with qualitatively distinct response patterns of motor performance, EF, and verbal ability. Quantitatively, the profiles showed most pronounced differences with regard to parent ratings and performance-based tests of EF, as well as verbal ability. Risk of motor coordination difficulties and ADHD symptomatology were associated with profile membership, whereas age, gender, language problems, and SES were not. Our results indicate that there are distinct subpopulations of children who show differential relations with regard to motor performance, EF, and verbal ability. The fact that we found both quantitative as well as qualitative differences between the three patterns of profiles underscores

  18. Application of Fourier transform infrared spectroscopy and orthogonal projections to latent structures/partial least squares regression for estimation of procyanidins average degree of polymerisation.

    Science.gov (United States)

    Passos, Cláudia P; Cardoso, Susana M; Barros, António S; Silva, Carlos M; Coimbra, Manuel A

    2010-02-28

    Fourier transform infrared (FTIR) spectroscopy has being emphasised as a widespread technique in the quick assess of food components. In this work, procyanidins were extracted with methanol and acetone/water from the seeds of white and red grape varieties. A fractionation by graded methanol/chloroform precipitations allowed to obtain 26 samples that were characterised using thiolysis as pre-treatment followed by HPLC-UV and MS detection. The average degree of polymerisation (DPn) of the procyanidins in the samples ranged from 2 to 11 flavan-3-ol residues. FTIR spectroscopy within the wavenumbers region of 1800-700 cm(-1) allowed to build a partial least squares (PLS1) regression model with 8 latent variables (LVs) for the estimation of the DPn, giving a RMSECV of 11.7%, with a R(2) of 0.91 and a RMSEP of 2.58. The application of orthogonal projection to latent structures (O-PLS1) clarifies the interpretation of the regression model vectors. Moreover, the O-PLS procedure has removed 88% of non-correlated variations with the DPn, allowing to relate the increase of the absorbance peaks at 1203 and 1099 cm(-1) with the increase of the DPn due to the higher proportion of substitutions in the aromatic ring of the polymerised procyanidin molecules. Copyright 2009 Elsevier B.V. All rights reserved.

  19. A Latent Factor Analysis of Working Memory Measures Using Large-Scale Data

    Directory of Open Access Journals (Sweden)

    Otto Waris

    2017-06-01

    Full Text Available Working memory (WM is a key cognitive system that is strongly related to other cognitive domains and relevant for everyday life. However, the structure of WM is yet to be determined. A number of WM models have been put forth especially by factor analytical studies. In broad terms, these models vary by their emphasis on WM contents (e.g., visuospatial, verbal vs. WM processes (e.g., maintenance, updating as critical, dissociable elements. Here we conducted confirmatory and exploratory factor analyses on a broad set of WM tasks, half of them numerical-verbal and half of them visuospatial, representing four commonly used task paradigms: simple span, complex span, running memory, and n-back. The tasks were selected to allow the detection of both content-based (visuospatial, numerical-verbal and process-based (maintenance, updating divisions. The data were collected online which allowed the recruitment of a large and demographically diverse sample of adults (n = 711. Both factor analytical methods pointed to a clear division according to task content for all paradigms except n-back, while there was no indication for a process-based division. Besides the content-based division, confirmatory factor analyses supported a model that also included a general WM factor. The n-back tasks had the highest loadings on the general factor, suggesting that this factor reflected high-level cognitive resources such as executive functioning and fluid intelligence that are engaged with all WM tasks, and possibly even more so with the n-back. Together with earlier findings that indicate high variability of process-based WM divisions, we conclude that the most robust division of WM is along its contents (visuospatial vs. numerical-verbal, rather than along its hypothetical subprocesses.

  20. Crystallization and preliminary crystallographic analysis of latent, active and recombinantly expressed aurone synthase, a polyphenol oxidase, from Coreopsis grandiflora

    Energy Technology Data Exchange (ETDEWEB)

    Molitor, Christian; Mauracher, Stephan Gerhard; Rompel, Annette, E-mail: annette.rompel@univie.ac.at [Universität Wien, Althanstrasse 14, 1090 Wien (Austria)

    2015-05-22

    Latent and active aurone synthase purified from petals of C. grandiflora (cgAUS1) were crystallized. The crystal quality of recombinantly expressed latent cgAUS1 was significantly improved by co-crystallization with the polyoxotungstate Na{sub 6}[TeW{sub 6}O{sub 24}] within the liquid–liquid phase-separation zone. Aurone synthase (AUS), a member of a novel group of plant polyphenol oxidases (PPOs), catalyzes the oxidative conversion of chalcones to aurones. Two active cgAUS1 (41.6 kDa) forms that differed in the level of phosphorylation or sulfation as well as the latent precursor form (58.9 kDa) were purified from the petals of Coreopsis grandiflora. The differing active cgAUS1 forms and the latent cgAUS1 as well as recombinantly expressed latent cgAUS1 were crystallized, resulting in six different crystal forms. The active forms crystallized in space groups P2{sub 1}2{sub 1}2{sub 1} and P12{sub 1}1 and diffracted to ∼1.65 Å resolution. Co-crystallization of active cgAUS1 with 1,4-resorcinol led to crystals belonging to space group P3{sub 1}21. The crystals of latent cgAUS1 belonged to space group P12{sub 1}1 and diffracted to 2.50 Å resolution. Co-crystallization of recombinantly expressed pro-AUS with the hexatungstotellurate(VI) salt Na{sub 6}[TeW{sub 6}O{sub 24}] within the liquid–liquid phase separation zone significantly improved the quality of the crystals compared with crystals obtained without hexatungstotellurate(VI)

  1. Delirium superimposed on dementia: defining disease states and course from longitudinal measurements of a multivariate index using latent class analysis and hidden Markov chains.

    Science.gov (United States)

    Ciampi, Antonio; Dyachenko, Alina; Cole, Martin; McCusker, Jane

    2011-12-01

    The study of mental disorders in the elderly presents substantial challenges due to population heterogeneity, coexistence of different mental disorders, and diagnostic uncertainty. While reliable tools have been developed to collect relevant data, new approaches to study design and analysis are needed. We focus on a new analytic approach. Our framework is based on latent class analysis and hidden Markov chains. From repeated measurements of a multivariate disease index, we extract the notion of underlying state of a patient at a time point. The course of the disorder is then a sequence of transitions among states. States and transitions are not observable; however, the probability of being in a state at a time point, and the transition probabilities from one state to another over time can be estimated. Data from 444 patients with and without diagnosis of delirium and dementia were available from a previous study. The Delirium Index was measured at diagnosis, and at 2 and 6 months from diagnosis. Four latent classes were identified: fairly healthy, moderately ill, clearly sick, and very sick. Dementia and delirium could not be separated on the basis of these data alone. Indeed, as the probability of delirium increased, so did the probability of decline of mental functions. Eight most probable courses were identified, including good and poor stable courses, and courses exhibiting various patterns of improvement. Latent class analysis and hidden Markov chains offer a promising tool for studying mental disorders in the elderly. Its use may show its full potential as new data become available.

  2. Cumulative socioeconomic status risk, allostatic load, and adjustment: a prospective latent profile analysis with contextual and genetic protective factors.

    Science.gov (United States)

    Brody, Gene H; Yu, Tianyi; Chen, Yi-fu; Kogan, Steven M; Evans, Gary W; Beach, Steven R H; Windle, Michael; Simons, Ronald L; Gerrard, Meg; Gibbons, Frederick X; Philibert, Robert A

    2013-05-01

    The health disparities literature has identified a common pattern among middle-aged African Americans that includes high rates of chronic disease along with low rates of psychiatric disorders despite exposure to high levels of cumulative socioeconomic status (SES) risk. The current study was designed to test hypotheses about the developmental precursors to this pattern. Hypotheses were tested with a representative sample of 443 African American youths living in the rural South. Cumulative SES risk and protective processes were assessed at ages 11-13 years; psychological adjustment was assessed at ages 14-18 years; genotyping at the 5-HTTLPR was conducted at age 16 years; and allostatic load (AL) was assessed at age 19 years. A latent profile analysis identified 5 profiles that evinced distinct patterns of SES risk, AL, and psychological adjustment, with 2 relatively large profiles designated as focal profiles: a physical health vulnerability profile characterized by high SES risk/high AL/low adjustment problems, and a resilient profile characterized by high SES risk/low AL/low adjustment problems. The physical health vulnerability profile mirrored the pattern found in the adult health disparities literature. Multinomial logistic regression analyses indicated that carrying an s allele at the 5-HTTLPR and receiving less peer support distinguished the physical health vulnerability profile from the resilient profile. Protective parenting and planful self-regulation distinguished both focal profiles from the other 3 profiles. The results suggest the public health importance of preventive interventions that enhance coping and reduce the effects of stress across childhood and adolescence.

  3. Latent Class Analysis of Polysubstance Use, Sexual Risk Behaviors, and Infectious Disease Among South African Drug Users

    Science.gov (United States)

    Trenz, Rebecca C.; Scherer, Michael; Duncan, Alexandra; Harrell, Paul; Moleko, Anne Gloria; Latimer, William

    2013-01-01

    Background HIV transmission risk among non-injection drug users is high due to the co-occurrence of drug use and sexual risk behaviors. The purpose of the current study was to identify patterns of drug use among polysubstance users within a high HIV prevalence population. Methods The study sample included 409 substance users from the Pretoria region of South Africa. Substances used by 20% or more the sample included: cigarettes, alcohol, marijuana and heroin in combination, marijuana and cigarettes in combination, and crack cocaine. Latent class analysis was used to identify patterns of polysubstance use based on types of drugs used. Multivariate logistic regression analyses compared classes on demographics, sexual risk behavior, and disease status. Results Four classes of substance use were found: MJ+Cig (40.8%), MJ+Her (30.8%), Crack (24.7%), and Low Use (3.7%). The MJ+Cig class was 6.7 times more likely to use alcohol and 3 times more likely to use drugs before/during sex with steady partners than the Crack class. The MJ+Cig class was16 times more likely to use alcohol before/during sex with steady partners than the MJ+Her class. The Crack class was 6.1 times more likely to engage in transactional sex and less likely to use drugs before/during steady sex than the MJ+Her class. Conclusions Findings illustrate patterns of drug use among a polysubstance using population that differ in sexual risk behavior. Intervention strategies should address substance use, particularly smoking as a route of administration (ROA), and sexual risk behaviors that best fit this high-risk population. PMID:23562370

  4. Four Distinct Subgroups of Self-Injurious Behavior among Chinese Adolescents: Findings from a Latent Class Analysis.

    Directory of Open Access Journals (Sweden)

    Xiuhong Xin

    Full Text Available Self-injurious behavior (SIB among adolescents is an important public health issue worldwide. It is still uncertain whether homogeneous subgroups of SIB can be identified and whether constellations of SIBs can co-occur due to the high heterogeneity of these behaviors. In this study, a cross-sectional study was conducted on a large school-based sample and latent class analysis was performed (n = 10,069, mean age = 15 years to identify SIB classes based on 11 indicators falling under direct SIB (DSIB, indirect SIB (ISIB, and suicide attempts (SAs. Social and psychological characteristics of each subgroup were examined after controlling for age and gender. Results showed that a four-class model best fit the data and each class had a distinct pattern of co-occurrence of SIBs and external measures. Class 4 (the baseline/normative group, 65.3% had a low probability of SIB. Class 3 (severe SIB group, 3.9% had a high probability of SIB and the poorest social and psychological status. Class 1 (DSIB+SA group, 14.2% had similar scores for external variables compared to class 3, and included a majority of girls [odds ratio (OR = 1.94]. Class 2 (ISIB group, 16.6% displayed moderate endorsement of ISIB items, and had a majority of boys and older adolescents (OR = 1.51. These findings suggest that SIB is a heterogeneous entity, but it may be best explained by four homogenous subgroups that display quantitative and qualitative differences. Findings in this study will improve our understanding on SIB and may facilitate the prevention and treatment of SIB.

  5. A cost-benefit analysis of a proposed overseas refugee latent tuberculosis infection screening and treatment program.

    Science.gov (United States)

    Wingate, La'Marcus T; Coleman, Margaret S; de la Motte Hurst, Christopher; Semple, Marie; Zhou, Weigong; Cetron, Martin S; Painter, John A

    2015-12-01

    This study explored the effect of screening and treatment of refugees for latent tuberculosis infection (LTBI) before entrance to the United States as a strategy for reducing active tuberculosis (TB). The purpose of this study was to estimate the costs and benefits of LTBI screening and treatment in United States bound refugees prior to arrival. Costs were included for foreign and domestic LTBI screening and treatment and the domestic treatment of active TB. A decision tree with multiple Markov nodes was developed to determine the total costs and number of active TB cases that occurred in refugee populations that tested 55, 35, and 20 % tuberculin skin test positive under two models: no overseas LTBI screening and overseas LTBI screening and treatment. For this analysis, refugees that tested 55, 35, and 20 % tuberculin skin test positive were divided into high, moderate, and low LTBI prevalence categories to denote their prevalence of LTBI relative to other refugee populations. For a hypothetical 1-year cohort of 100,000 refugees arriving in the United States from regions with high, moderate, and low LTBI prevalence, implementation of overseas screening would be expected to prevent 440, 220, and 57 active TB cases in the United States during the first 20 years after arrival. The cost savings associated with treatment of these averted cases would offset the cost of LTBI screening and treatment for refugees from countries with high (net cost-saving: $4.9 million) and moderate (net cost-saving: $1.6 million) LTBI prevalence. For low LTBI prevalence populations, LTBI screening and treatment exceed expected future TB treatment cost savings (net cost of $780,000). Implementing LTBI screening and treatment for United States bound refugees from countries with high or moderate LTBI prevalence would potentially save millions of dollars and contribute to United States TB elimination goals. These estimates are conservative since secondary transmission from tuberculosis cases

  6. Latent class analysis of need descriptors within an Irish youth mental health early intervention program toward a typology of need.

    Science.gov (United States)

    Peiper, Nicholas; Illback, Robert J; O'Reilly, Aileen; Clayton, Richard

    2017-02-01

    Significant overlap and comorbidity has been demonstrated among young people with mental health problems. This paper examined demographic characteristics, heterogeneity of need descriptors and services provided among young people (12-25 years) engaging in brief interventions at Jigsaw in the Republic of Ireland. Between 1 January 2013 and 31 December 2013, a total of 2571 young people sought help from 1 of 10 Jigsaw sites. Of these, 1247 engaged in goal-focused brief interventions, typically consisting of one to six face-to-face sessions. Descriptive statistics were used to summarize social and demographic factors. Latent class analysis was used to cluster young people into relevant typologies of presenting issues. Multinomial logistic regression was then performed to determine significant predictors of class membership. The most common age of young people was 16. More women (59.6%) than men engaged in brief interventions, 56% attended school, 74% lived with their family of origin or with one parent, and 54.2% came from families where parents were married. Using established fit criteria, four relevant typologies emerged: Developmental (26.8%), Comorbid (15.8%), Anxious (42.7%) and Externalising (14.6%). Predictors varied by class membership, but general family problems and lack of adult support emerged as the strongest predictors for all classes. This study demonstrated that the mental health needs of young people in Ireland are significant and diverse. Because Jigsaw favours a more descriptive approach to problem identification, the four typologies suggest a need to determine program capacity in engaging youth with heterogeneous presenting issues and to tailor brief interventions to each group's clinical profiles. © 2015 Wiley Publishing Asia Pty Ltd.

  7. Four Distinct Health Profiles in Older Patients With Cancer: Latent Class Analysis of the Prospective ELCAPA Cohort.

    Science.gov (United States)

    Ferrat, Emilie; Audureau, Etienne; Paillaud, Elena; Liuu, Evelyne; Tournigand, Christophe; Lagrange, Jean-Leon; Canoui-Poitrine, Florence; Caillet, Philippe; Bastuji-Garin, Sylvie

    2016-12-01

    Several studies have evaluated the independent prognostic value of impairments in single geriatric-assessment (GA) components in elderly cancer patients. None identified homogeneous subgroups. Our aims were to identify such subgroups based on combinations of GA components and to assess their associations with treatment decisions, admission, and death. We prospectively included 1,021 patients aged ≥70 years who had solid or hematologic malignancies and who underwent a GA in one of two French teaching hospitals. Two geriatricians independently selected candidate GA parameters for latent class analysis, which was then performed on the 821 cases without missing data. Age, gender, tumor site, metastatic status, and inpatient versus outpatient status were used as active covariates and predictors of class membership. Outcomes were cancer treatment decisions, overall 1-year mortality, and 6-month unscheduled admissions. Sensitivity analyses were performed on the overall population of 1,021 patients and on 375 newly enrolled patients. We identified four classes: relatively healthy (LC1, 28%), malnourished (LC2, 36%), cognitive and mood impaired (LC3, 15%), and globally impaired (LC4, 21%). Tumor site, metastatic status, age, and in/outpatient status independently predicted class membership (p LC4 was associated with 1-year mortality and palliative treatment compared to LC2 and LC3 (p ≤ .05). We identified four health profiles that may help physicians select cancer treatments and geriatric interventions. Researchers may find these profiles useful for stratifying patients in clinical trials. © The Author 2016. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  8. Latent class analysis of the Yale-Brown Obsessive-Compulsive Scale symptoms in obsessive-compulsive disorder

    NARCIS (Netherlands)

    Delucchi, K.L.; Katerberg, H.; Stewart, S.E.; Denys, D.A.; Lochner, C.; Stack, D.E.; den Boer, J.A.; van Balkom, A.J.L.M.; Jenike, M.A.; Stein, D.J.; Cath, D.C.; Mathews, C.A.

    2011-01-01

    Objective: Obsessive-compulsive disorder (OCD) is phenomenologically heterogeneous, and findings of underlying structure classification based on symptom grouping have been ambiguous to date. Variable-centered approaches, primarily factor analysis, have been used to identify homogeneous groups of

  9. The association between school exclusion, delinquency and subtypes of cyber- and F2F-victimizations: identifying and predicting risk profiles and subtypes using latent class analysis.

    Science.gov (United States)

    Barboza, Gia Elise

    2015-01-01

    This purpose of this paper is to identify risk profiles of youth who are victimized by on- and offline harassment and to explore the consequences of victimization on school outcomes. Latent class analysis is used to explore the overlap and co-occurrence of different clusters of victims and to examine the relationship between class membership and school exclusion and delinquency. Participants were a random sample of youth between the ages of 12 and 18 selected for inclusion to participate in the 2011 National Crime Victimization Survey: School Supplement. The latent class analysis resulted in four categories of victims: approximately 3.1% of students were highly victimized by both bullying and cyberbullying behaviors; 11.6% of youth were classified as being victims of relational bullying, verbal bullying and cyberbullying; a third class of students were victims of relational bullying, verbal bullying and physical bullying but were not cyberbullied (8%); the fourth and final class, characteristic of the majority of students (77.3%), was comprised of non-victims. The inclusion of covariates to the latent class model indicated that gender, grade and race were significant predictors of at least one of the four victim classes. School delinquency measures were included as distal outcomes to test for both overall and pairwise associations between classes. With one exception, the results were indicative of a significant relationship between school delinquency and the victim subtypes. Implications for these findings are discussed. Copyright © 2014 Elsevier Ltd. All rights reserved.

  10. Interactions between lower urinary tract symptoms and cardiovascular risk factors determine distinct patterns of erectile dysfunction: a latent class analysis.

    Science.gov (United States)

    Barbosa, João A B A; Muracca, Eduardo; Nakano, Élcio; Assalin, Adriana R; Cordeiro, Paulo; Paranhos, Mario; Cury, José; Srougi, Miguel; Antunes, Alberto A

    2013-12-01

    An epidemiological association between lower urinary tract symptoms and erectile dysfunction is well established. However, interactions among multiple risk factors and the role of each in pathological mechanisms are not fully elucidated We enrolled 898 men undergoing prostate cancer screening for evaluation with the International Prostate Symptom Score (I-PSS) and simplified International Index of Erectile Function-5 (IIEF-5) questionnaires. Age, race, hypertension, diabetes, dyslipidemia, metabolic syndrome, cardiovascular disease, serum hormones and anthropometric parameters were also evaluated. Risk factors for erectile dysfunction were identified by logistic regression. The 333 men with at least mild to moderate erectile dysfunction (IIEF 16 or less) were included in a latent class model to identify relationships across erectile dysfunction risk factors. Age, hypertension, diabetes, lower urinary tract symptoms and cardiovascular event were independent predictors of erectile dysfunction (pclasses of patients with erectile dysfunction (R2 entropy=0.82). Latent class 1 had younger men at low cardiovascular risk and a moderate/high prevalence of lower urinary tract symptoms. Latent class 2 had the oldest patients at moderate cardiovascular risk with an increased prevalence of lower urinary tract symptoms. Latent class 3 had men of intermediate age with the highest prevalence of cardiovascular risk factors and lower urinary tract symptoms. Erectile dysfunction severity and lower urinary tract symptoms increased from latent class 1 to 3. Risk factor interactions determined different severities of lower urinary tract symptoms and erectile dysfunction. The effect of lower urinary tract symptoms and cardiovascular risk outweighed that of age. While in the youngest patients lower urinary tract symptoms acted as a single risk factor for erectile dysfunction, the contribution of vascular disease resulted in significantly more severe dysfunction. Applying a risk factor

  11. The effect of job insecurity on employee health complaints: A within-person analysis of the explanatory role of threats to the manifest and latent benefits of work.

    Science.gov (United States)

    Vander Elst, Tinne; Näswall, Katharina; Bernhard-Oettel, Claudia; De Witte, Hans; Sverke, Magnus

    2016-01-01

    The current study contributes to the literature on job insecurity by highlighting threat to the benefits of work as an explanation of the effect of job insecurity on health complaints. Building on the latent deprivation model, we predicted that threats to both manifest (i.e., financial income) and latent benefits of work (i.e., collective purpose, social contacts, status, time structure, activity) mediate the relationships from job insecurity to subsequent mental and physical health complaints. In addition, in line with the conservation of resources theory, we proposed that financial resources buffer the indirect effect of job insecurity on health complaints through threat to the manifest benefit. Hypotheses were tested using a multilevel design, in which 3 measurements (time lag of 6 months between subsequent measurements) were clustered within 1,994 employees (in Flanders, Belgium). This allowed for the investigation of within-person processes, while controlling for variance at the between-person level. The results demonstrate that job insecurity was related to subsequent threats to both manifest and latent benefits, and that these threats in turn were related to subsequent health complaints (with an exception for threat to the manifest benefit that did not predict mental health complaints). Three significant indirect effects were found: threat to the latent benefits mediated the relationships between job insecurity and both mental and physical health complaints, and threat to the manifest benefit mediated the relationship between job insecurity and physical health complaints. Unexpectedly, the latter indirect effect was exacerbated by financial resources. (c) 2016 APA, all rights reserved).

  12. Modeling Nonlinear Change via Latent Change and Latent Acceleration Frameworks: Examining Velocity and Acceleration of Growth Trajectories

    Science.gov (United States)

    Grimm, Kevin; Zhang, Zhiyong; Hamagami, Fumiaki; Mazzocco, Michele

    2013-01-01

    We propose the use of the latent change and latent acceleration frameworks for modeling nonlinear growth in structural equation models. Moving to these frameworks allows for the direct identification of "rates of change" and "acceleration" in latent growth curves--information available indirectly through traditional growth…

  13. Analysis of the Phenotype of Mycobacterium tuberculosis-Specific CD4+ T Cells to Discriminate Latent from Active Tuberculosis in HIV-Uninfected and HIV-Infected Individuals

    Directory of Open Access Journals (Sweden)

    Catherine Riou

    2017-08-01

    Full Text Available Several immune-based assays have been suggested to differentiate latent from active tuberculosis (TB. However, their relative performance as well as their efficacy in HIV-infected persons, a highly at-risk population, remains unclear. In a study of 81 individuals, divided into four groups based on their HIV-1 status and TB disease activity, we compared the differentiation (CD27 and KLRG1, activation (HLA-DR, homing potential (CCR4, CCR6, CXCR3, and CD161 and functional profiles (IFNγ, IL-2, and TNFα of Mycobacterium tuberculosis (Mtb-specific CD4+ T cells using flow cytometry. Active TB disease induced major changes within the Mtb-responding CD4+ T cell population, promoting memory maturation, elevated activation and increased inflammatory potential when compared to individuals with latent TB infection. Moreover, the functional profile of Mtb-specific CD4+ T cells appeared to be inherently related to their degree of differentiation. While these specific cell features were all capable of discriminating latent from active TB, irrespective of HIV status, HLA-DR expression showed the best performance for TB diagnosis [area-under-the-curve (AUC = 0.92, 95% CI: 0.82–1.01, specificity: 82%, sensitivity: 84% for HIV− and AUC = 0.99, 95% CI: 0.98–1.01, specificity: 94%, sensitivity: 93% for HIV+]. In conclusion, these data support the idea that analysis of T cell phenotype can be diagnostically useful in TB.

  14. The Influence of Static and Dynamic Intrapersonal Factors on Longitudinal Patterns of Peer Victimization through Mid-adolescence: a Latent Transition Analysis.

    Science.gov (United States)

    Haltigan, John D; Vaillancourt, Tracy

    2018-01-01

    Using 6 cycles (grade 5 through grade 10) of data obtained from a large prospective sample of Canadian school children (N = 700; 52.6% girls), we replicated previous findings concerning the empirical definition of peer victimization (i.e., being bullied) and examined static and dynamic intrapersonal factors associated with its emergence and experiential continuity through mid-adolescence. Latent class analyses consistently revealed a low victimization and an elevated victimization class across time, supporting previous work suggesting peer victimization was defined by degree rather than by type (e.g., physical). Using latent transition analyses (LTA), we found that child sex, parent-perceived pubertal development, and internalizing symptoms influenced the probability of transitioning from the low to the elevated victimization class across time. Higher-order extensions within the LTA modeling framework revealed a lasting effect of grade 5 victimization status on grade 10 victimization status and a large effect of chronic victimization on later parent-reported youth internalizing symptoms (net of prior parent-reported internalizing symptoms) in later adolescence (grade 11). Implications of the current findings for the experience of peer victimization, as well as the application of latent transition analysis as a useful approach for peer victimization research, are discussed.

  15. Nonlinear Structural Analysis

    Indian Academy of Sciences (India)

    The Structures Panel of the Aeronautics Research and Development Board of India ... A great variety of topics was covered, including themes such as nonlinear finite ... or shell structures, and three are on the composite form of construction, ...

  16. Somatic symptom profiles in the general population: a latent class analysis in a Danish population-based health survey

    Directory of Open Access Journals (Sweden)

    Eliasen M

    2017-08-01

    Full Text Available Marie Eliasen,1 Torben Jørgensen,1–3 Andreas Schröder,4 Thomas Meinertz Dantoft,1 Per Fink,4 Chalotte Heinsvig Poulsen,1,5 Nanna Borup Johansen,1 Lene Falgaard Eplov,5 Sine Skovbjerg,1 Svend Kreiner2 1Research Centre for Prevention and Health, Centre for Health, The Capital Region of Denmark, Glostrup, 2Department of Public Health, University of Copenhagen, Copenhagen, 3Department of Clinical Medicine, Aalborg University, Aalborg, 4Research Clinic for Functional Disorders and Psychosomatics, Aarhus University Hospital, Aarhus C, 5Mental Health Centre Copenhagen, The Capital Region of Denmark, Hellerup, Denmark Purpose: The aim of this study was to identify and describe somatic symptom profiles in the general adult population in order to enable further epidemiological research within multiple somatic symptoms.Methods: Information on 19 self-reported common somatic symptoms was achieved from a population-based questionnaire survey of 36,163 randomly selected adults in the Capital Region of Denmark (55.4% women. The participants stated whether they had been considerably bothered by each symptom within 14 days prior to answering the questionnaire. We used latent class analysis to identify the somatic symptom profiles. The profiles were further described by their association with age, sex, chronic disease, and self-perceived health.Results: We identified 10 different somatic symptom profiles defined by number, type, and site of the symptoms. The majority of the population (74.0% had a profile characterized by no considerable bothering symptoms, while a minor group of 3.9% had profiles defined by a high risk of multiple somatic symptoms. The remaining profiles were more likely to be characterized by a few specific symptoms. The profiles could further be described by their associations with age, sex, chronic disease, and self-perceived health.Conclusion: The identified somatic symptom profiles could be distinguished by number, type, and site of

  17. Identifying and predicting subgroups of information needs among cancer patients: an initial study using latent class analysis.

    Science.gov (United States)

    Neumann, Melanie; Wirtz, Markus; Ernstmann, Nicole; Ommen, Oliver; Längler, Alfred; Edelhäuser, Friedrich; Scheffer, Christian; Tauschel, Diethard; Pfaff, Holger

    2011-08-01

    Understanding how the information needs of cancer patients (CaPts) vary is important because met information needs affect health outcomes and CaPts' satisfaction. The goals of the study were to identify subgroups of CaPts based on self-reported cancer- and treatment-related information needs and to determine whether subgroups could be predicted on the basis of selected sociodemographic, clinical and clinician-patient relationship variables. Three hundred twenty-three CaPts participated in a survey using the "Cancer Patients Information Needs" scale, which is a new tool for measuring cancer-related information needs. The number of information need subgroups and need profiles within each subgroup was identified using latent class analysis (LCA). Multinomial logistic regression was applied to predict class membership. LCA identified a model of five subgroups exhibiting differences in type and extent of CaPts' unmet information needs: a subgroup with "no unmet needs" (31.4% of the sample), two subgroups with "high level of psychosocial unmet information needs" (27.0% and 12.0%), a subgroup with "high level of purely medical unmet information needs" (16.0%) and a subgroup with "high level of medical and psychosocial unmet information needs" (13.6%). An assessment of sociodemographic and clinical characteristics revealed that younger CaPts and CaPts' requiring psychological support seem to belong to subgroups with a higher level of unmet information needs. However, the most significant predictor for the subgroups with unmet information needs is a good clinician-patient relationship, i.e. subjective perception of high level of trust in and caring attention from nurses together with high degree of physician empathy seems to be predictive for inclusion in the subgroup with no unmet information needs. The results of our study can be used by oncology nurses and physicians to increase their awareness of the complexity and heterogeneity of information needs among CaPts and of

  18. Community patterns of stigma towards persons living with HIV: A population-based latent class analysis from rural Vietnam

    LENUS (Irish Health Repository)

    Pharris, Anastasia

    2011-09-18

    Abstract Background The negative effects of stigma on persons living with HIV (PLHIV) have been documented in many settings and it is thought that stigma against PLHIV leads to more difficulties for those who need to access HIV testing, treatment and care, as well as to limited community uptake of HIV prevention and testing messages. In order to understand and prevent stigma towards PLHIV, it is important to be able to measure stigma within communities and to understand which factors are associated with higher stigma. Methods To analyze patterns of community stigma and determinants to stigma toward PLHIV, we performed an exploratory population-based survey with 1874 randomly sampled adults within a demographic surveillance site (DSS) in rural Vietnam. Participants were interviewed regarding knowledge of HIV and attitudes towards persons living with HIV. Data were linked to socioeconomic and migration data from the DSS and latent class analysis and multinomial logistic regression were conducted to examine stigma group sub-types and factors associated with stigma group membership. Results We found unexpectedly high and complex patterns of stigma against PLHIV in this rural setting. Women had the greatest odds of belong to the highest stigma group (OR 1.84, 95% CI 1.42-2.37), while those with more education had lower odds of highest stigma group membership (OR 0.45, 95% CI 0.32-0.62 for secondary education; OR 0.19, 95% CI 0.10-0.35 for tertiary education). Long-term migration out of the district (OR 0.61, 95% CI 0.4-0.91), feeling at-risk for HIV (OR 0.42, 95% CI 0.27-0.66), having heard of HIV from more sources (OR 0.44, 95% CI 0.3-0.66), and knowing someone with HIV (OR 0.76, 95% CI 0.58-0.99) were all associated with lower odds of highest stigma group membership. Nearly 20% of the population was highly unsure of their attitudes towards PLHIV and persons in this group had significantly lower odds of feeling at-risk for HIV (OR 0.54, 95% CI 0.33-0.90) or of knowing

  19. Racial Discrimination and Racial Socialization as Predictors of African American Adolescents’ Racial Identity Development using Latent Transition Analysis

    Science.gov (United States)

    Seaton, Eleanor K.; Yip, Tiffany; Morgan-Lopez, Antonio; Sellers, Robert M.

    2013-01-01

    The current study examined perceptions of racial discrimination and racial socialization on racial identity development among 566 African American adolescents over three years. Latent class analyses were used to estimate identity statuses (Diffuse, Foreclosed, Moratorium and Achieved). The probabilities of transitioning from one stage to another were examined with latent transition analyses to determine the likelihood of youth progressing, regressing or remaining constant. Racial socialization and perceptions of racial discrimination were examined as covariates to assess the association with changes in racial identity status. The results indicated that perceptions of racial discrimination were not linked to any changes in racial identity. Youth who reported higher levels of racial socialization were less likely to be in Diffuse or Foreclosed compared to the Achieved group. PMID:21875184

  20. Understanding today’s music acquisition mix: a latent class analysis of consumers’ combined use of music platforms

    OpenAIRE

    Weijters, Bert; Goedertier, Frank

    2016-01-01

    In response to diversifying music delivery modes, consumers increasingly combine various music platforms, both online and offline, legal and illegal, and free or paying. Based on survey data (N = 685), the current study segments consumers in terms of the combination of music delivery modes they use. We identify four latent classes based on their usage frequency of purchasing CDs, copying CDs, streaming music, streaming music videos, peer-to-peer file sharing, and purchased downloading. All-ro...

  1. Systematic Expression Profiling Analysis Identifies Specific MicroRNA-Gene Interactions that May Differentiate between Active and Latent Tuberculosis Infection

    OpenAIRE

    Wu, Lawrence Shih-Hsin; Lee, Shih-Wei; Huang, Kai-Yao; Lee, Tzong-Yi; Hsu, Paul Wei-Che; Weng, Julia Tzu-Ya

    2014-01-01

    Tuberculosis (TB) is the second most common cause of death from infectious diseases. About 90% of those infected are asymptomatic—the so-called latent TB infections (LTBI), with a 10% lifetime chance of progressing to active TB. To further understand the molecular pathogenesis of TB, several molecular studies have attempted to compare the expression profiles between healthy controls and active TB or LTBI patients. However, the results vary due to diverse genetic backgrounds and study designs ...

  2. Adolescent substance use behavior and suicidal behavior for boys and girls: a cross-sectional study by latent analysis approach

    OpenAIRE

    Wang, Peng-Wei; Yen, Cheng-Fang

    2017-01-01

    Background Adolescent suicidal behavior may consist of different symptoms, including suicidal ideation, suicidal planning and suicidal attempts. Adolescent substance use behavior may contribute to adolescent suicidal behavior. However, research on the relationships between specific substance use and individual suicidal behavior is insufficient, as adolescents may not use only one substance or develop only one facet of suicidal behavior. Latent variables permit us to describe the relationships...

  3. Evaluating aggregate effects of rare and common variants in the 1000 Genomes Project exon sequencing data using latent variable structural equation modeling.

    Science.gov (United States)

    Nock, Nl; Zhang, Lx

    2011-11-29

    Methods that can evaluate aggregate effects of rare and common variants are limited. Therefore, we applied a two-stage approach to evaluate aggregate gene effects in the 1000 Genomes Project data, which contain 24,487 single-nucleotide polymorphisms (SNPs) in 697 unrelated individuals from 7 populations. In stage 1, we identified potentially interesting genes (PIGs) as those having at least one SNP meeting Bonferroni correction using univariate, multiple regression models. In stage 2, we evaluate aggregate PIG effects on trait, Q1, by modeling each gene as a latent construct, which is defined by multiple common and rare variants, using the multivariate statistical framework of structural equation modeling (SEM). In stage 1, we found that PIGs varied markedly between a randomly selected replicate (replicate 137) and 100 other replicates, with the exception of FLT1. In stage 1, collapsing rare variants decreased false positives but increased false negatives. In stage 2, we developed a good-fitting SEM model that included all nine genes simulated to affect Q1 (FLT1, KDR, ARNT, ELAV4, FLT4, HIF1A, HIF3A, VEGFA, VEGFC) and found that FLT1 had the largest effect on Q1 (βstd = 0.33 ± 0.05). Using replicate 137 estimates as population values, we found that the mean relative bias in the parameters (loadings, paths, residuals) and their standard errors across 100 replicates was on average, less than 5%. Our latent variable SEM approach provides a viable framework for modeling aggregate effects of rare and common variants in multiple genes, but more elegant methods are needed in stage 1 to minimize type I and type II error.

  4. Multiple Skills Underlie Arithmetic Performance: A Large-Scale Structural Equation Modeling Analysis

    Directory of Open Access Journals (Sweden)

    Sarit Ashkenazi

    2017-12-01

    Full Text Available Current theoretical approaches point to the importance of several cognitive skills not specific to mathematics for the etiology of mathematics disorders (MD. In the current study, we examined the role of many of these skills, specifically: rapid automatized naming, attention, reading, and visual perception, on mathematics performance among a large group of college students (N = 1,322 with a wide range of arithmetic proficiency. Using factor analysis, we discovered that our data clustered to four latent variables 1 mathematics, 2 perception speed, 3 attention and 4 reading. In subsequent structural equation modeling, we found that the latent variable perception speed had a strong and meaningful effect on mathematics performance. Moreover, sustained attention, independent from the effect of the latent variable perception speed, had a meaningful, direct effect on arithmetic fact retrieval and procedural knowledge. The latent variable reading had a modest effect on mathematics performance. Specifically, reading comprehension, independent from the effect of the latent variable reading, had a meaningful direct effect on mathematics, and particularly on number line knowledge. Attention, tested by the attention network test, had no effect on mathematics, reading or perception speed. These results indicate that multiple factors can affect mathematics performance supporting a heterogeneous approach to mathematics. These results have meaningful implications for the diagnosis and intervention of pure and comorbid learning disorders.

  5. Data on the interexaminer variation of minutia markup on latent fingerprints.

    Science.gov (United States)

    Ulery, Bradford T; Hicklin, R Austin; Roberts, Maria Antonia; Buscaglia, JoAnn

    2016-09-01

    The data in this article supports the research paper entitled "Interexaminer variation of minutia markup on latent fingerprints" [1]. The data in this article describes the variability in minutia markup during both analysis of the latents and comparison between latents and exemplars. The data was collected in the "White Box Latent Print Examiner Study," in which each of 170 volunteer latent print examiners provided detailed markup documenting their examinations of latent-exemplar pairs of prints randomly assigned from a pool of 320 pairs. Each examiner examined 22 latent-exemplar pairs; an average of 12 examiners marked each latent.

  6. The efficiency of parameter estimation of latent path analysis using summated rating scale (SRS) and method of successive interval (MSI) for transformation of score to scale

    Science.gov (United States)

    Solimun, Fernandes, Adji Achmad Rinaldo; Arisoesilaningsih, Endang

    2017-12-01

    Research in various fields generally investigates systems and involves latent variables. One method to analyze the model representing the system is path analysis. The data of latent variables measured using questionnaires by applying attitude scale model yields data in the form of score, before analyzed should be transformation so that it becomes data of scale. Path coefficient, is parameter estimator, calculated from scale data using method of successive interval (MSI) and summated rating scale (SRS). In this research will be identifying which data transformation method is better. Path coefficients have smaller varieties are said to be more efficient. The transformation method that produces scaled data and used in path analysis capable of producing path coefficients (parameter estimators) with smaller varieties is said to be better. The result of analysis using real data shows that on the influence of Attitude variable to Intention Entrepreneurship, has relative efficiency (ER) = 1, where it shows that the result of analysis using data transformation of MSI and SRS as efficient. On the other hand, for simulation data, at high correlation between items (0.7-0.9), MSI method is more efficient 1.3 times better than SRS method.

  7. Structures and their analysis

    CERN Document Server

    Fuchs, Maurice Bernard

    2016-01-01

    Addressing structures, this book presents a classic discipline in a modern setting by combining illustrated examples with insights into the solutions. It is the fruit of the author’s many years of teaching the subject and of just as many years of research into the design of optimal structures. Although intended for an advanced level of instruction it has an undergraduate course at its core. Further, the book was written with the advantage of having massive computer power in the background, an aspect which changes the entire approach to many engineering disciplines and in particular to structures. This paradigm shift has dislodged the force (flexibility) method from its former prominence and paved the way for the displacement (stiffness) method, despite the multitude of linear equations it spawns. In this book, however, both methods are taught: the force method offers a perfect vehicle for understanding structural behavior, bearing in mind that it is the displacement method which does the heavy number crunch...

  8. Complete nucleotide sequence and genome structure of a Japanese isolate of hibiscus latent Fort Pierce virus, a unique tobamovirus that contains an internal poly(A) region in its 3' end.

    Science.gov (United States)

    Yoshida, Tetsuya; Kitazawa, Yugo; Komatsu, Ken; Neriya, Yutaro; Ishikawa, Kazuya; Fujita, Naoko; Hashimoto, Masayoshi; Maejima, Kensaku; Yamaji, Yasuyuki; Namba, Shigetou

    2014-11-01

    In this study, we detected a Japanese isolate of hibiscus latent Fort Pierce virus (HLFPV-J), a member of the genus Tobamovirus, in a hibiscus plant in Japan and determined the complete sequence and organization of its genome. HLFPV-J has four open reading frames (ORFs), each of which shares more than 98 % nucleotide sequence identity with those of other HLFPV isolates. Moreover, HLFPV-J contains a unique internal poly(A) region of variable length, ranging from 44 to 78 nucleotides, in its 3'-untranslated region (UTR), as is the case with hibiscus latent Singapore virus (HLSV), another hibiscus-infecting tobamovirus. The length of the HLFPV-J genome was 6431 nucleotides, including the shortest internal poly(A) region. The sequence identities of ORFs 1, 2, 3 and 4 of HLFPV-J to other tobamoviruses were 46.6-68.7, 49.9-70.8, 31.0-70.8 and 39.4-70.1 %, respectively, at the nucleotide level and 39.8-75.0, 43.6-77.8, 19.2-70.4 and 31.2-74.2 %, respectively, at the amino acid level. The 5'- and 3'-UTRs of HLFPV-J showed 24.3-58.6 and 13.0-79.8 % identity, respectively, to other tobamoviruses. In particular, when compared to other tobamoviruses, each ORF and UTR of HLFPV-J showed the highest sequence identity to those of HLSV. Phylogenetic analysis showed that HLFPV-J, other HLFPV isolates and HLSV constitute a malvaceous-plant-infecting tobamovirus cluster. These results indicate that the genomic structure of HLFPV-J has unique features similar to those of HLSV. To our knowledge, this is the first report of the complete genome sequence of HLFPV.

  9. Space-time latent component modeling of geo-referenced health data.

    Science.gov (United States)

    Lawson, Andrew B; Song, Hae-Ryoung; Cai, Bo; Hossain, Md Monir; Huang, Kun

    2010-08-30

    Latent structure models have been proposed in many applications. For space-time health data it is often important to be able to find the underlying trends in time, which are supported by subsets of small areas. Latent structure modeling is one such approach to this analysis. This paper presents a mixture-based approach that can be applied to component selection. The analysis of a Georgia ambulatory asthma county-level data set is presented and a simulation-based evaluation is made. Copyright (c) 2010 John Wiley & Sons, Ltd.

  10. Knowledge and Attitudes towards Antibiotic Use and Resistance - A Latent Class Analysis of a Swedish Population-Based Sample.

    Directory of Open Access Journals (Sweden)

    Martina Vallin

    Full Text Available In 2006, a study investigating knowledge and attitudes regarding antibiotic use and resistance in Sweden, indicated high level of knowledge but also areas in need of improvement.(i To provide an update on the knowledge and attitudes to antibiotic use and resistance of the Swedish population, and (ii to identify which groups within the population are in particular need of improved knowledge or attitudes.A questionnaire was sent by post in 2013 to 2,500 randomly-selected individuals aged 18-74, living in Sweden. Latent class analyses were conducted to group respondents based on their responses. The association between socio-demographic characteristics and the probability of belonging to each latent class was assessed.The response rate was 57%. Ninety-four per cent of the responders knew that bacteria could become resistant to antibiotics and the majority answered correctly to the questions regarding antibiotic resistance development. The respondents expressed confidence in doctors who decided not to prescribe antibiotics. Three latent classes related to 'knowledge regarding antibiotic use and resistance', two regarding 'attitudes towards antibiotic accessibility and infection prevention' and three regarding 'attitudes towards antibiotic use and effects' were revealed. Men, younger and more educated people were more knowledgeable but males had a less restrictive attitude. Respondents with high levels of knowledge on antibiotics were more likely to have appropriate restrictive attitudes to antibiotics.Knowledge on antibiotic use and resistance is maintained high and has improved in Sweden compared to 2006. People with lower education and elderly are especially in need of improved knowledge about antibiotic use and resistance.

  11. Mobile phone-based evaluation of latent tuberculosis infection: Proof of concept for an integrated image capture and analysis system.

    Science.gov (United States)

    Naraghi, Safa; Mutsvangwa, Tinashe; Goliath, René; Rangaka, Molebogeng X; Douglas, Tania S

    2018-05-08

    The tuberculin skin test is the most widely used method for detecting latent tuberculosis infection in adults and active tuberculosis in children. We present the development of a mobile-phone based screening tool for measuring the tuberculin skin test induration. The tool makes use of a mobile application developed on the Android platform to capture images of an induration, and photogrammetric reconstruction using Agisoft PhotoScan to reconstruct the induration in 3D, followed by 3D measurement of the induration with the aid of functions from the Python programming language. The system enables capture of images by the person being screened for latent tuberculosis infection. Measurement precision was tested using a 3D printed induration. Real-world use of the tool was simulated by application to a set of mock skin indurations, created by a make-up artist, and the performance of the tool was evaluated. The usability of the application was assessed with the aid of a questionnaire completed by participants. The tool was found to measure the 3D printed induration with greater precision than the current ruler and pen method, as indicated by the lower standard deviation produced (0.3 mm versus 1.1 mm in the literature). There was high correlation between manual and algorithm measurement of mock skin indurations. The height of the skin induration and the definition of its margins were found to influence the accuracy of 3D reconstruction and therefore the measurement error, under simulated real-world conditions. Based on assessment of the user experience in capturing images, a simplified user interface would benefit wide-spread implementation. The mobile application shows good agreement with direct measurement. It provides an alternative method for measuring tuberculin skin test indurations and may remove the need for an in-person follow-up visit after test administration, thus improving latent tuberculosis infection screening throughput. Copyright © 2018 Elsevier Ltd

  12. Avoiding and Correcting Bias in Score-Based Latent Variable Regression with Discrete Manifest Items

    Science.gov (United States)

    Lu, Irene R. R.; Thomas, D. Roland

    2008-01-01

    This article considers models involving a single structural equation with latent explanatory and/or latent dependent variables where discrete items are used to measure the latent variables. Our primary focus is the use of scores as proxies for the latent variables and carrying out ordinary least squares (OLS) regression on such scores to estimate…

  13. Collapse Analysis of Timber Structures

    DEFF Research Database (Denmark)

    Kirkegaard, Poul Henning; Sørensen, John Dalsgaard

    2008-01-01

    of Structures and a probabilistic modelling of the timber material proposed in the Probabilistic Model Code (PMC) of the Joint Committee on Structural Safety (JCSS). Due to the framework in the Danish Code the timber structure has to be evaluated with respect to the following criteria where at least one shall...... to criteria a) and b) the timber frame structure has one column with a reliability index a bit lower than an assumed target level. By removal three columns one by one no significant extensive failure of the entire structure or significant parts of it are obtained. Therefore the structure can be considered......A probabilistic based collapse analysis has been performed for a glulam frame structure supporting the roof over the main court in a Norwegian sports centre. The robustness analysis is based on the framework for robustness analysis introduced in the Danish Code of Practice for the Safety...

  14. Latent variables and route choice behavior

    DEFF Research Database (Denmark)

    Prato, Carlo Giacomo; Bekhor, Shlomo; Pronello, Cristina

    2012-01-01

    In the last decade, a broad array of disciplines has shown a general interest in enhancing discrete choice models by considering the incorporation of psychological factors affecting decision making. This paper provides insight into the comprehension of the determinants of route choice behavior...... and bound algorithm. A hybrid model consists of measurement equations, which relate latent variables to measurement indicators and utilities to choice indicators, and structural equations, which link travelers’ observable characteristics to latent variables and explanatory variables to utilities. Estimation...

  15. Exposing Latent Information in Folksonomies for Reasoning

    Science.gov (United States)

    2010-01-14

    1.73 $.") http://www.w3.org/2006/07/SWD/ SKOS /reference/20081001/ Spiteri, L.F. (2007) "The structure and form of folksonomy tags: The road to the...Exposing Latent Information in Folksonomies for Reasoning January 14, 2010 Sponsored by Defense Advanced Research Projects Agency (DOD...DATES COVERED (From - To! 4/14/2009-12/23/2009 4. TITLE AND SUBTITLE Exposing Latent Information in Folksonomies for Reasoning Sa. CONTRACT

  16. Latent palmprint matching.

    Science.gov (United States)

    Jain, Anil K; Feng, Jianjiang

    2009-06-01

    The evidential value of palmprints in forensic applications is clear as about 30 percent of the latents recovered from crime scenes are from palms. While biometric systems for palmprint-based personal authentication in access control type of applications have been developed, they mostly deal with low-resolution (about 100 ppi) palmprints and only perform full-to-full palmprint matching. We propose a latent-to-full palmprint matching system that is needed in forensic applications. Our system deals with palmprints captured at 500 ppi (the current standard in forensic applications) or higher resolution and uses minutiae as features to be compatible with the methodology used by latent experts. Latent palmprint matching is a challenging problem because latent prints lifted at crime scenes are of poor image quality, cover only a small area of the palm, and have a complex background. Other difficulties include a large number of minutiae in full prints (about 10 times as many as fingerprints), and the presence of many creases in latents and full prints. A robust algorithm to reliably estimate the local ridge direction and frequency in palmprints is developed. This facilitates the extraction of ridge and minutiae features even in poor quality palmprints. A fixed-length minutia descriptor, MinutiaCode, is utilized to capture distinctive information around each minutia and an alignment-based minutiae matching algorithm is used to match two palmprints. Two sets of partial palmprints (150 live-scan partial palmprints and 100 latent palmprints) are matched to a background database of 10,200 full palmprints to test the proposed system. Despite the inherent difficulty of latent-to-full palmprint matching, rank-1 recognition rates of 78.7 and 69 percent, respectively, were achieved in searching live-scan partial palmprints and latent palmprints against the background database.

  17. Structural systems reliability analysis

    International Nuclear Information System (INIS)

    Frangopol, D.

    1975-01-01

    For an exact evaluation of the reliability of a structure it appears necessary to determine the distribution densities of the loads and resistances and to calculate the correlation coefficients between loads and between resistances. These statistical characteristics can be obtained only on the basis of a long activity period. In case that such studies are missing the statistical properties formulated here give upper and lower bounds of the reliability. (orig./HP) [de

  18. Predicting Condom Use Using the Information-Motivation-Behavioral Skills (IMB) Model: A Multivariate Latent Growth Curve Analysis

    Science.gov (United States)

    Senn, Theresa E.; Scott-Sheldon, Lori A. J.; Vanable, Peter A.; Carey, Michael P.

    2011-01-01

    Background The Information-Motivation-Behavioral Skills (IMB) model often guides sexual risk reduction programs even though no studies have examined covariation in the theory’s constructs in a dynamic fashion with longitudinal data. Purpose Using new developments in latent growth modeling, we explore how changes in information, motivation, and behavioral skills over 9 months relate to changes in condom use among STD clinic patients. Methods Participants (N = 1281, 50% female, 66% African American) completed measures of IMB constructs at three time points. We used parallel process latent growth modeling to examine associations among intercepts and slopes of IMB constructs. Results Initial levels of motivation, behavioral skills, and condom use were all positively associated, with behavioral skills partially mediating associations between motivation and condom use. Changes over time in behavioral skills positively related to changes in condom use. Conclusions Results support the key role of behavioral skills in sexual risk reduction, suggesting these skills should be targeted in HIV prevention interventions. PMID:21638196

  19. Using bivariate latent basis growth curve analysis to better understand treatment outcome in youth with anorexia nervosa.

    Science.gov (United States)

    Byrne, Catherine E; Wonderlich, Joseph A; Curby, Timothy; Fischer, Sarah; Lock, James; Le Grange, Daniel

    2018-04-25

    This study explored the relation between eating-related obsessionality and weight restoration utilizing bivariate latent basis growth curve modelling. Eating-related obsessionality is a moderator of treatment outcome for adolescents with anorexia nervosa (AN). This study examined the degree to which the rate of change in eating-related obsessionality was associated with the rate of change in weight over time in family-based treatment (FBT) and individual therapy for AN. Data were drawn from a 2-site randomized controlled trial that compared FBT and adolescent focused therapy for AN. Bivariate latent basis growth curves were used to examine the differences of the relations between trajectories of body weight and symptoms associated with eating and weight obsessionality. In the FBT group, the slope of eating-related obsessionality scores and the slope of weight were significantly (negatively) correlated. This finding indicates that a decrease in overall eating-relating obsessionality is significantly associated with an increase in weight for individuals who received FBT. However, there was no relation between change in obsessionality scores and change in weight in the adolescent focused therapy group. Results suggest that FBT has a specific impact on both weight gain and obsessive compulsive behaviour that is distinct from individual therapy. Copyright © 2018 John Wiley & Sons, Ltd and Eating Disorders Association.

  20. Maternal eating disorder and infant diet. A latent class analysis based on the Norwegian Mother and Child Cohort Study (MoBa).

    Science.gov (United States)

    Torgersen, Leila; Ystrom, Eivind; Siega-Riz, Anna Maria; Berg, Cecilie Knoph; Zerwas, Stephanie C; Reichborn-Kjennerud, Ted; Bulik, Cynthia M

    2015-01-01

    Knowledge of infant diet and feeding practices among children of mothers with eating disorders is essential to promote healthy eating in these children. This study compared the dietary patterns of 6-month-old children of mothers with anorexia nervosa, bulimia nervosa, binge eating disorder, and eating disorder not otherwise specified-purging subtype, to the diet of children of mothers with no eating disorders (reference group). The study was based on 53,879 mothers in the Norwegian Mother and Child Cohort Study (MoBa). Latent class analysis (LCA) was used to identify discrete latent classes of infant diet based on the mothers' responses to questions about 16 food items. LCA identified five classes, characterized by primarily homemade vegetarian food (4% of infants), homemade traditional food (8%), commercial cereals (35%), commercial jarred baby food (39%), and a mix of all food groups (11%). The association between latent dietary classes and maternal eating disorders were estimated by multinomial logistic regression. Infants of mothers with bulimia nervosa had a lower probability of being in the homemade traditional food class compared to the commercial jarred baby food class, than the referent (O.R. 0.59; 95% CI 0.36-0.99). Infants of mothers with binge eating disorder had a lower probability of being in the homemade vegetarian class compared to the commercial jarred baby food class (O.R. 0.77; 95% CI 0.60-0.99), but only before adjusting for relevant confounders. Anorexia nervosa and eating disorder not otherwise specified-purging subtype were not statistically significantly associated with any of the dietary classes. These results suggest that maternal eating disorders may to some extent influence the child's diet at 6 months; however, the extent to which these differences influence child health and development remains an area for further inquiry. Copyright © 2014 Elsevier Ltd. All rights reserved.

  1. Ten-year stability and latent structure of the DSM-IV schizotypal, borderline, avoidant, and obsessive-compulsive personality disorders.

    Science.gov (United States)

    Sanislow, Charles A; Little, Todd D; Ansell, Emily B; Grilo, Carlos M; Daversa, Maria; Markowitz, John C; Pinto, Anthony; Shea, M Tracie; Yen, Shirley; Skodol, Andrew E; Morey, Leslie C; Gunderson, John G; Zanarini, Mary C; McGlashan, Thomas H

    2009-08-01

    Evaluation of the validity of personality disorder (PD) diagnostic constructs is important for the impending revision of the Diagnostic and Statistical Manual of Mental Disorders. Prior factor analytic studies have tested these constructs in cross-sectional studies, and models have been replicated longitudinally, but no study has tested a constrained longitudinal model. The authors examined 4 PDs in the Collaborative Longitudinal Personality Disorders study (schizotypal, borderline, avoidant, and obsessive-compulsive) over 7 time points (baseline, 6 months, 1 year, 2 years, 4 years, 6 years, and 10 years). Data for 2-, 4-, 6- and 10-year assessments were obtained in semistructured interviews by raters blind to prior PD diagnoses at each assessment. The latent structure of the 4 constructs was differentiated during the initial time points but became less differentiated over time as the mean levels of the constructs dropped and stability increased. Obsessive-compulsive PD became more correlated with schizotypal and borderline PD than with avoidant PD. The higher correlation among the constructs in later years may reflect greater shared base of pathology for chronic personality disorders.

  2. Latent classification models

    DEFF Research Database (Denmark)

    Langseth, Helge; Nielsen, Thomas Dyhre

    2005-01-01

    parametric family ofdistributions.  In this paper we propose a new set of models forclassification in continuous domains, termed latent classificationmodels. The latent classification model can roughly be seen ascombining the \\NB model with a mixture of factor analyzers,thereby relaxing the assumptions...... classification model, and wedemonstrate empirically that the accuracy of the proposed model issignificantly higher than the accuracy of other probabilisticclassifiers....

  3. Measuring burnout and work engagement: Factor structure, invariance, and latent mean differences across Greece and the Netherlands

    Directory of Open Access Journals (Sweden)

    Xanthopoulou, D.

    2012-01-01

    Full Text Available This study examines the factor structure and invariance of the instruments measuring burnout (Maslach Burnout Inventory - General Survey / MBI-GS and work engagement (Utrecht Work Engagement Scale / UWES in a sample of Dutch (N = 162 and Greek (N = 206 employees. Confirmatory factor analyses in both samples supported the superiority of the proposed three-factor structure of both the MBI-GS (exhaustion, cynicism, and reduced professional efficacy and the UWES (vigor, dedication, and absorption. Alternative two-factor and one-factor models did not show a better fit to the data. In addition, results of multigroup analyses partly supported the invariance of the three-factor model of the MBI-GS, and fully supported the invariance of the three-factor model of the UWES across the two national samples. These results suggest that the MBI-GS and the UWES are not only valid instruments for testing burnout and engagement but also allow comparisons across countries.

  4. Realist identification of group-level latent variables for perinatal social epidemiology theory building.

    Science.gov (United States)

    Eastwood, John Graeme; Jalaludin, Bin Badrudin; Kemp, Lynn Ann; Phung, Hai Ngoc

    2014-01-01

    We have previously reported in this journal on an ecological study of perinatal depressive symptoms in South Western Sydney. In that article, we briefly reported on a factor analysis that was utilized to identify empirical indicators for analysis. In this article, we report on the mixed method approach that was used to identify those latent variables. Social epidemiology has been slow to embrace a latent variable approach to the study of social, political, economic, and cultural structures and mechanisms, partly for philosophical reasons. Critical realist ontology and epistemology have been advocated as an appropriate methodological approach to both theory building and theory testing in the health sciences. We describe here an emergent mixed method approach that uses qualitative methods to identify latent constructs followed by factor analysis using empirical indicators chosen to measure identified qualitative codes. Comparative analysis of the findings is reported together with a limited description of realist approaches to abstract reasoning.

  5. Sequence analysis of the Epstein-Barr virus (EBV) latent membrane protein-1 gene and promoter region

    DEFF Research Database (Denmark)

    Sandvej, Kristian; Gratama, J W; Munch, M

    1997-01-01

    Sequence variations in the Epstein-Barr virus (EBV) encoded latent membrane protein-1 (LMP-1) gene have been described in a Chinese nasopharyngeal carcinoma-derived isolate (CAO), and in viral isolates from various EBV-associated tumors. It has been suggested that these genetic changes, which...... include loss of a Xho I restriction site (position 169425) and a C-terminal 30-base pair (bp) deletion (position 168287-168256), define EBV genotypes associated with increased tumorigenicity or with disease among particular geographic populations. To determine the frequency of LMP-1 variations in European...... wild-type virus isolates, we sequenced the LMP-1 promoter and gene in EBV from lymphoblastoid cell lines from healthy carriers and patients without EBV-associated disease. Sequence changes were often present, and defined at least four main groups of viral isolates, which we designate Groups A through D...

  6. Evaluation of sensitivity and specificity of routine meat inspection of danish slaughter pigs using latent class analysis

    DEFF Research Database (Denmark)

    Bonde, Marianne; Toft, Nils; Thomsen, Peter

    2010-01-01

    and heart disorders will cause a significant underestimation of the prevalence of diseases reported to the pig producers. Based on our results the true prevalence of diseases (conventional vs. organic slaughter pigs) was (in %): 42 vs. 16, 5 vs. 51, 5 vs. 12 and 9 vs. 5 for RESP, PAR, INT and HEART......Two groups of observers, regular meat inspectors and two veterinary researchers, respectively, conducted independent veterinary meat inspection of organs of slaughter pigs from organic or conventional production systems slaughtered at one abattoir in April 2005. A total of 3054 pigs (899 organic...... and 2155 conventional) were examined. The observed pathological disorders were grouped in four categories; respiratory disorders (RESP), parasitic disorders (PAR), intestinal disorders (INT) and heart disorders (HEART). Using a latent class model, the sensitivity (Se) and specificity (Sp) of meat...

  7. Gender and Facebook motives as predictors of specific types of Facebook use: A latent growth curve analysis in adolescence.

    Science.gov (United States)

    Frison, Eline; Eggermont, Steven

    2016-10-01

    Despite increasing evidence that specific types of Facebook use (i.e., active private, active public, and passive Facebook use) are differently related to adolescents' well-being, little is known how these types function over the course of adolescence and whether gender and Facebook motives may predict the initial level and changes in these types over time. To address these gaps, Flemish adolescents (ages 12-19) were questioned at three different time points, with six months in between (NTime1 = 1866). Latent growth curve models revealed that active private Facebook use increased over the course of adolescence, whereas public Facebook use decreased. Passive Facebook use, however, remained stable. In addition, gender and Facebook motives were related to initial levels of specific types of Facebook use, and predictive of dynamic change in specific types of Facebook use over time. The discussion focuses on the understanding and implications of these findings. Copyright © 2016. Published by Elsevier Ltd.

  8. How does consumer knowledge affect environmentally sustainable choices? Evidence from a cross-country latent class analysis of food labels.

    Science.gov (United States)

    Peschel, Anne O; Grebitus, Carola; Steiner, Bodo; Veeman, Michele

    2016-11-01

    This paper examines consumers' knowledge and lifestyle profiles and preferences regarding two environmentally labeled food staples, potatoes and ground beef. Data from online choice experiments conducted in Canada and Germany are analyzed through latent class choice modeling to identify the influence of consumer knowledge (subjective and objective knowledge as well as usage experience) on environmentally sustainable choices. We find that irrespective of product or country under investigation, high subjective and objective knowledge levels drive environmentally sustainable food choices. Subjective knowledge was found to be more important in this context. Usage experience had relatively little impact on environmentally sustainable choices. Our results suggest that about 20% of consumers in both countries are ready to adopt footprint labels in their food choices. Another 10-20% could be targeted by enhancing subjective knowledge, for example through targeted marketing campaigns. Copyright © 2016 Elsevier Ltd. All rights reserved.

  9. Are Informing Knowledge and Supportive Attitude Enough for Tobacco Control? A Latent Class Analysis of Cigarette Smoking Patterns among Medical Teachers in China.

    Science.gov (United States)

    Niu, Lu; Luo, Dan; Silenzio, Vincent M B; Xiao, Shuiyuan; Tian, Yongquan

    2015-09-25

    This study is one part of a five-year tobacco-control project in China, which aimed to gain insight into the smoking behavior, knowledge, and attitudes among medical teachers in China. In May 2010, a cross-sectional survey was conducted among medical teachers of Xiangya Medical School, Central South University, China. A total number of 682 medical teachers completed the surveys. Latent class analysis indicated the sample of smoking patterns was best represented by three latent subgroups of smoking consumption severity levels. Most respondents were informed of smoking related knowledge, but lack of knowledge on smoking cessation. Most of them held a supportive attitude towards their responsibilities among tobacco control, as well as the social significance of smoking. However, both smoking related knowledge and attitude were not correlated with severity of smoking consumption among medical teachers. The smoking prevalence among medical teachers in China remains high. Programs on smoking cessation training are required. Future study should also develop targeted interventions for subgroups of smokers based on smoking consumption. Persistent and effective anti-tobacco efforts are needed to achieve the goals of creating smoke-free campuses and hospitals.

  10. A Three-Step Latent Class Analysis to Identify How Different Patterns of Teen Dating Violence and Psychosocial Factors Influence Mental Health.

    Science.gov (United States)

    Choi, Hye Jeong; Weston, Rebecca; Temple, Jeff R

    2017-04-01

    Although multiple forms (i.e., physical, threatening, psychological, sexual, and relational abuse) and patterns (i.e., perpetration and victimization) of violence can co-occur, most existing research examines these experiences individually. Thus, the purpose of this study is to investigate: (1) homogenous subgroups based on victimization and perpetration of multiple forms of teen dating violence; (2) predictors of membership in these subgroups; and (3) mental health consequences associated with membership in each subgroup. Nine hundred eighteen adolescents in the 9 th or 10 th grade at seven public high schools in