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Sample records for confirmatory latent class

  1. Estimation of sensitivity and specificity of bacteriology, histopathology and PCR for the confirmatory diagnosis of bovine tuberculosis using latent class analysis.

    Science.gov (United States)

    Courcoul, Aurélie; Moyen, Jean-Louis; Brugère, Laure; Faye, Sandy; Hénault, Sylvie; Gares, Hélène; Boschiroli, Maria-Laura

    2014-01-01

    Bacteriology and histopathology are the most commonly used tests used for official confirmatory diagnosis of bovine tuberculosis (bTB) in cattle in most countries. PCR is also being used increasingly because it allows a fast diagnosis. This test could be applied as a supplement to or replacement for current bTB confirmatory diagnostic tests but its characteristics have first to be evaluated. The aim of this study was to estimate and compare sensitivities and specificities of bacteriology, histopathology and PCR under French field conditions, in the absence of a gold standard using latent class analysis. The studied population consisted of 5,211 animals from which samples were subjected to bacteriology and PCR (LSI VetMAX™ Mycobacterium tuberculosis Complex PCR Kit, Life Technologies) as their herd of origin was either suspected or confirmed infected with bTB or because bTB-like lesions were detected during slaughterhouse inspection. Samples from 697 of these animals (all with bTB-like lesions) were subjected to histopathology. Bayesian models were developed, allowing for dependence between bacteriology and PCR, while assuming independence from histopathology. The sensitivity of PCR was higher than that of bacteriology (on average 87.7% [82.5-92.3%] versus 78.1% [72.9-82.8%]) while specificity of both tests was very good (on average 97.0% for PCR [94.3-99.0%] and 99.1% for bacteriology [97.1-100.0%]). Histopathology was at least as sensitive as PCR (on average 93.6% [89.9-96.9%]) but less specific than the two other tests (on average 83.3% [78.7-87.6%]). These results suggest that PCR has the potential to replace bacteriology to confirm bTB in samples submitted from suspect cattle.

  2. A Latent Class Model for Rating Data.

    Science.gov (United States)

    Rost, Jurgen

    1985-01-01

    A latent class model for rating data is presented which provides an alternative to the latent trait approach of analyzing test data. It is the analog of Andrich's binomial Rasch model for Lazarsfeld's latent class analysis (LCA). Response probabilities for rating categories follow a binomial distribution and depend on class-specific item…

  3. Introduction to Latent Class Analysis with Applications

    Science.gov (United States)

    Porcu, Mariano; Giambona, Francesca

    2017-01-01

    Latent class analysis (LCA) is a statistical method used to group individuals (cases, units) into classes (categories) of an unobserved (latent) variable on the basis of the responses made on a set of nominal, ordinal, or continuous observed variables. In this article, we introduce LCA in order to demonstrate its usefulness to early adolescence…

  4. Stability of latent class segments over time

    DEFF Research Database (Denmark)

    Mueller, Simone

    2011-01-01

    logit model suggests significant changes in the price sensitivity and the utility from environmental claims between both experimental waves. A pooled scale adjusted latent class model is estimated jointly over both waves and the relative size of latent classes is compared across waves, resulting...

  5. On identifiability of certain latent class models.

    NARCIS (Netherlands)

    van Wieringen, W.N.

    2005-01-01

    Blischke [1962. Moment estimators for the parameters of a mixture of two binomial distributions. Ann. Math. Statist. 33, 444-454] studies a mixture of two binomials, a latent class model. In this article we generalize this model to a mixture of two products of binomials. We show when this

  6. Saharan Africa: A Latent Class Analysis

    African Journals Online (AJOL)

    AJRH Managing Editor

    1University of Southern California School of Social Work, 669 W. 34th Street, Los Angeles, CA 90089, USA; 2University of ... Abstract. While studies have examined factors associated with condom use behaviors, few have assessed risk perception and condom use among SSA .... approach (latent class analysis) to identify.

  7. Optimization-Based Model Fitting for Latent Class and Latent Profile Analyses

    Science.gov (United States)

    Huang, Guan-Hua; Wang, Su-Mei; Hsu, Chung-Chu

    2011-01-01

    Statisticians typically estimate the parameters of latent class and latent profile models using the Expectation-Maximization algorithm. This paper proposes an alternative two-stage approach to model fitting. The first stage uses the modified k-means and hierarchical clustering algorithms to identify the latent classes that best satisfy the…

  8. Latent Class and Latent Transition Analysis With Applications in the Social, Behavioral, and Health Sciences

    CERN Document Server

    Collins, Linda M

    2010-01-01

    One of the few books on latent class analysis (LCA) and latent transition analysis (LTA) with a comprehensive treatment of longitudinal latent class models, Latent Class and Latent Transition Analysis reflects improvements in statistical computing as the most up-to-date reference for theoretical, technical, and practical issues in cross-sectional and longitudinal data. Plentiful examples enable the reader to acquire a thorough conceptual and technical understanding and to apply techniques to address empirical research questions. Researchers seeking an advanced introduction to LCA and LTA and g

  9. Multilevel Latent Class Models with Dirichlet Mixing Distribution

    OpenAIRE

    Di, Chong-Zhi; Bandeen-Roche, Karen

    2011-01-01

    Latent class analysis (LCA) and latent class regression (LCR) are widely used for modeling multivariate categorical outcomes in social science and biomedical studies. Standard analyses assume data of different respondents to be mutually independent, excluding application of the methods to familial and other designs in which participants are clustered. In this paper, we consider multilevel latent class models, in which subpopulation mixing probabilities are treated as random effects that vary ...

  10. 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....... The resulting subgroups were descriptively compared using statistical measures and clinical interpretability. RESULTS: For each health domain, the preferred model solution ranged from five to seven subgroups for the summary-score strategy and seven to eight subgroups for the single-item strategy...

  11. Assessment of handedness using latent class factor analysis.

    Science.gov (United States)

    Merni, Franco; Di Michele, Rocco; Soffritti, Gabriele

    2014-01-01

    Recently several studies in which handedness was evaluated as a latent construct have been performed. In those studies, handedness was modelled using a qualitative latent variable (latent class models), a continuous latent variable (factor models), or both a qualitative latent variable and a continuous latent trait (mixed Rasch models). The aim of this study was to explore the usefulness and effectiveness of an approach in which handedness is treated as a qualitatively scaled latent variable with ordered categories (latent class factor models). This aim was pursued through an exploratory analysis of a dataset containing information on the hand used by 2236 young Italian sportspeople to perform 10 tasks. For comparison purposes, a latent class analysis was carried out. A cross-validation procedure was implemented. The results of all the analyses revealed that the best fit to the observed handedness patterns was obtained using a latent class factor model. Through this model, individuals were assigned to one of four ordered levels of handedness, and a quantitative index of left-handedness for each individual was computed by taking into account the different effect of the 10 tasks. These results provide support for the use of the latent class factor approach for handedness assessment.

  12. A Latent Class Approach to Estimating Test-Score Reliability

    Science.gov (United States)

    van der Ark, L. Andries; van der Palm, Daniel W.; Sijtsma, Klaas

    2011-01-01

    This study presents a general framework for single-administration reliability methods, such as Cronbach's alpha, Guttman's lambda-2, and method MS. This general framework was used to derive a new approach to estimating test-score reliability by means of the unrestricted latent class model. This new approach is the latent class reliability…

  13. PROC LCA: A SAS Procedure for Latent Class Analysis

    Science.gov (United States)

    Lanza, Stephanie T.; Collins, Linda M.; Lemmon, David R.; Schafer, Joseph L.

    2007-01-01

    Latent class analysis (LCA) is a statistical method used to identify a set of discrete, mutually exclusive latent classes of individuals based on their responses to a set of observed categorical variables. In multiple-group LCA, both the measurement part and structural part of the model can vary across groups, and measurement invariance across…

  14. Spurious Latent Classes in the Mixture Rasch Model

    Science.gov (United States)

    Alexeev, Natalia; Templin, Jonathan; Cohen, Allan S.

    2011-01-01

    Mixture Rasch models have been used to study a number of psychometric issues such as goodness of fit, response strategy differences, strategy shifts, and multidimensionality. Although these models offer the potential for improving understanding of the latent variables being measured, under some conditions overextraction of latent classes may…

  15. Item Response Theory, Latent Classes and Rule Space.

    Science.gov (United States)

    1987-07-15

    1968) and Latent Class ( Lazarsfeld p.M 5 & Henry, 1968) will be discussed with respect to the demands of modern measurement theory and their...Paper presented at the 22nd International Congress of Psychology, Leipzig. Lazarsfeld , P. F. & Henry, N. W. (1968). Latent structure analysis. Boston

  16. A Flexible Latent Class Approach to Estimating Test-Score Reliability

    Science.gov (United States)

    van der Palm, Daniël W.; van der Ark, L. Andries; Sijtsma, Klaas

    2014-01-01

    The latent class reliability coefficient (LCRC) is improved by using the divisive latent class model instead of the unrestricted latent class model. This results in the divisive latent class reliability coefficient (DLCRC), which unlike LCRC avoids making subjective decisions about the best solution and thus avoids judgment error. A computational…

  17. Collinear Latent Variables in Multilevel Confirmatory Factor Analysis : A Comparison of Maximum Likelihood and Bayesian Estimation

    NARCIS (Netherlands)

    Can, Seda; van de Schoot, Rens; Hox, Joop

    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

  18. Collinear Latent Variables in Multilevel Confirmatory Factor Analysis: A Comparison of Maximum Likelihood and Bayesian Estimations

    Science.gov (United States)

    Can, Seda; van de Schoot, Rens; Hox, Joop

    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 influence of the size of the intraclass correlation…

  19. Latent Class Analysis of YBOCS 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.

    2010-01-01

    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 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. Method Latent class analysis (LCA) models using 61 obsessive-compulsive symptoms (OCS) collected from the Yale-Brown Obsessive-Compulsive Scale were fit. Relationships between latent class membership and treatment response, gender, symptom severity and comorbid tic disorders were tested for relationship to class membership. Results LCA models of best fit yielded three classes. Classes differed only in frequency of symptom endorsement. Classes with higher symptom endorsement were associated with earlier age of onset, being male, higher YBOCS symptom severity scores, and comorbid tic disorders. There were no differences in treatment response between classes. Conclusions 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. PMID:21145539

  20. Multilevel latent class models with dirichlet mixing distribution.

    Science.gov (United States)

    Di, Chong-Zhi; Bandeen-Roche, Karen

    2011-03-01

    Latent class analysis (LCA) and latent class regression (LCR) are widely used for modeling multivariate categorical outcomes in social science and biomedical studies. Standard analyses assume data of different respondents to be mutually independent, excluding application of the methods to familial and other designs in which participants are clustered. In this article, we consider multilevel latent class models, in which subpopulation mixing probabilities are treated as random effects that vary among clusters according to a common Dirichlet distribution. We apply the expectation-maximization (EM) algorithm for model fitting by maximum likelihood (ML). This approach works well, but is computationally intensive when either the number of classes or the cluster size is large. We propose a maximum pairwise likelihood (MPL) approach via a modified EM algorithm for this case. We also show that a simple latent class analysis, combined with robust standard errors, provides another consistent, robust, but less-efficient inferential procedure. Simulation studies suggest that the three methods work well in finite samples, and that the MPL estimates often enjoy comparable precision as the ML estimates. We apply our methods to the analysis of comorbid symptoms in the obsessive compulsive disorder study. Our models' random effects structure has more straightforward interpretation than those of competing methods, thus should usefully augment tools available for LCA of multilevel data. © 2010, The International Biometric Society.

  1. 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 ...

  2. A Note on Parameter Estimation For Lazarsfeld's Latent Class Analysis

    Science.gov (United States)

    Formann, Anton K.

    1978-01-01

    As the literature indicates, no method is presently available which takes explicitly into account that the parameters of Lazarsfeld's latent class analysis are defined as probabilities and are therefore restricted to the interval (0,1). An appropriate transform on the parameters is presented in order to satisfy this constraint. (Author/JKS)

  3. Latent Classes of PTSD Symptoms in Vietnam Veterans

    Science.gov (United States)

    Steenkamp, Maria M.; Nickerson, Angela; Maguen, Shira; Dickstein, Benjamin D.; Nash, William P.; Litz, Brett T.

    2012-01-01

    The authors examined heterogeneity in posttraumatic stress disorder (PTSD) symptom presentation among veterans (n = 335) participating in the clinical interview subsample of the National Vietnam Veterans Readjustment Study. Latent class analysis was used to identify clinically homogeneous subgroups of Vietnam War combat veterans. Consistent with…

  4. Predictors of drinking patterns in adolescence: a latent class analysis.

    Science.gov (United States)

    Jackson, Nicki; Denny, Simon; Sheridan, Janie; Fleming, Terry; Clark, Terryann; Teevale, Tasileta; Ameratunga, Shanthi

    2014-02-01

    Uni-dimensional measures of alcohol consumption may be unable to fully capture the complexity of adolescent drinking and experience of alcohol-related harms. Latent class analysis provides an empirical method to understand different adolescent drinking patterns. Latent class analysis was used to create typologies of drinking among the 5018 current drinkers in the national Youth '07 survey. Determinants of drinking patterns were identified using multinomial logistic regression. Four latent classes were identified, demonstrating an overall increase in risk of alcohol-related outcomes from increasing consumption. One class strongly deviated from this pattern, having moderate consumption patterns but disproportionately high levels of alcohol-related problems. Multinomial logistic regression found that the strongest predictors of belonging to high-risk drinking typologies were having a positive attitude to regular alcohol use, buying own alcohol, peers using alcohol, and obtaining alcohol from friends and/or other adults. Other significant predictors included being male, having a strong connection to friends, having parents with a low level of knowledge of their daily activities and poor connection to school. Class membership also varied by ethnicity. The latent class approach demonstrated variability in alcohol-related harms across groups of students with different drinking patterns. Longitudinal studies are necessary to determine the causes of this variability in order to inform the development of targeted policy and preventative interventions. Legislative controls, such as increasing the legal purchase age and reducing the commercial availability of alcohol, will continue to be important strategies for reducing harm in young people. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  5. Latent Class Analysis of college women's Thursday drinking.

    Science.gov (United States)

    Ward, Rose Marie; Cleveland, Michael J; Messman-Moore, Terri L

    2013-01-01

    College students drink in consistent patterns over the course of the academic semester and year (Beets et al., 2009; Del Boca et al., 2004). However, it is unclear if there are naturally occurring groups of female Thursday drinkers who display their own unique patterns of drinking across the semester. In a fall semester 10-week mixed online- and paper-based study of college female drinking, classes of Thursday drinkers were identified using Repeated Measures Latent Class Analysis. The 424 participants were recruited via flyers and advertisements in the student newspaper. It was determined that three latent classes provided optimal fit to the data: 1. Unlikely to report Thursday drinking; 2. Normal probability of Thursday drinkers; and 3. High probability of Thursday drinkers. The proportion of students within the latent classes differed across academic year in school. Seniors were least likely to be in the Unlikely group, and juniors and seniors were not in the Normal group. An additional analysis indicated that women in a sorority were four times more likely to be in the Normal or High groups compared to the Unlikely group. A final set of analyses indicated that women who enrolled in Friday morning classes were more likely to be in the Unlikely or Normal groups compared to the High group. Results indicated that the Unlikely group consumed significantly less alcohol at baseline, had lower levels of negative alcohol-related consequences prior to and during the study, and drank less on the weekends (Friday and Saturday). Female students who report drinking on Thursdays tend to be older, to be part of sororities, to have later classes or no classes on Friday, and to experience more negative alcohol-related consequences. Female students whose "weekends" start early are high-risk drinkers and might be targeted for future prevention and intervention efforts. Copyright © 2012 Elsevier Ltd. All rights reserved.

  6. Examination of polytrauma typologies: A latent class analysis approach.

    Science.gov (United States)

    Sullivan, Erin; Contractor, Ateka A; Gerber, Monica M; Neumann, Craig

    2017-09-01

    Potentially traumatizing events (PTE) are highly prevalent, and are associated with detrimental effects on psychological health, including increased risk of posttraumatic stress disorder (PTSD). Multiple endorsed PTEs (polytraumatization) may have even greater effects on a person's health than the impact of a single index event. To better understand patterns of polytraumatization, person-centered analytic techniques such as Latent class analysis (LCA) are recommended. The current study used LCA to explore latent subgroupings of people based on their endorsement of PTEs, thus defining patterns in PTE exposure. The sample included 850 participants who endorsed at least one PTE on a web-administered Trauma History Questionnaire (THQ). Results indicated a best-fitting 3-class solution: (1) a class with a greater probability of experiencing interpersonal PTEs and other PTEs, (2) a class with moderate PTE exposure and higher probability of mugging and accidents, and (3) a class with low PTE exposure. Differences in age, gender, and PTSD symptom severity accounted for class membership. Results suggest the experience of interpersonal PTEs may be a risk factor for additional lifetime PTE exposure, and is associated with increased PTSD severity. Additional findings underscore the heterogenity of trauma experiences, highlighting the importance of examining such patterns in future research. Copyright © 2017. Published by Elsevier B.V.

  7. Exploring Latent Class Based on Growth Rates in Number Sense Ability

    Science.gov (United States)

    Kim, Dongil; Shin, Jaehyun; Lee, Kijyung

    2013-01-01

    The purpose of this study was to explore latent class based on growth rates in number sense ability by using latent growth class modeling (LGCM). LGCM is one of the noteworthy methods for identifying growth patterns of the progress monitoring within the response to intervention framework in that it enables us to analyze latent sub-groups based not…

  8. A latent class analysis of urban American Indian youth identities.

    Science.gov (United States)

    Kulis, Stephen S; Robbins, Danielle E; Baker, Tahnee M; Denetsosie, Serena; Deschine Parkhurst, Nicholet A

    2016-04-01

    This study examined sources of indigenous identity among urban American Indian youth that map the three theoretical dimensions of a model advanced by Markstrom: identification (tribal and ethnic heritage), connection (through family and reservation ties), and involvement in traditional culture and spirituality. Data came from self-administered questionnaires completed by 208 urban American Indian students from five middle schools in a large metropolitan area in the Southwest. Descriptive statistics showed most youth were connected to multiple indicators on all three dimensions of indigenous identity: native parental heritage, native best friends, past and current reservation connections, involvement with cultural practices, tribal language and spirituality, and alignment with native and mainstream cultural orientations. A latent class analysis identified five classes. There were two larger groups, one with strong native heritage and the highest levels of enculturation, and another that was more bicultural in orientation. The remaining three groups were smaller and about equal in size: a highly acculturated group with mixed parental ethnic heritage, those who had strong native heritage but were culturally disengaged, and a group with some mixed ethnic heritage that was low on indicators of enculturation. Evidence for the validity of the latent classes came from significant variations across the classes in scores on an American Indian ethnic identity (modified Phinney) scale, the students' open-ended descriptions of the main sources of their indigenous identities, and the better academic grades of classes that were more culturally engaged. Despite the challenges of maintaining cultural identities in the urban environment, most youth in this sample expressed a strong sense of indigenous identity, claimed personal and parental tribal heritage, remained connected to reservation communities, and actively engaged in Native cultural and spiritual life. (c) 2016 APA, all

  9. Temporal eating patterns: a latent class analysis approach.

    Science.gov (United States)

    Leech, Rebecca M; Worsley, Anthony; Timperio, Anna; McNaughton, Sarah A

    2017-01-07

    There is some evidence that large energy intakes towards the end of the day are associated with adverse health outcomes, however, studies of temporal eating patterns across the day are rare. This study examines the temporal eating patterns of Australian adults using latent class analysis (LCA), as a novel approach. Dietary data (n = 2402 men and n = 2840 women, ≥19 years) from two 24-h recalls collected during the 2011-12 Australian National Nutrition and Physical Activity Survey were analyzed. LCA was performed to identify distinct temporal eating patterns based on whether or not an eating occasion (EO) occurred within each hour of the day. F and adjusted-chi(2) tests assessed differences in sociodemographic and eating patterns (e.g., meal, snack and EO frequency) between latent classes. Three patterns, labelled "Conventional" (men: 43%, women: 41%), "Later lunch" (men: 34%, women: 34%) and "Grazing" (men: 23%, women: 25%) were identified. Men and women with a "Grazing" pattern were significantly younger (P energy intake from snacks but a lower proportion of total energy intake from meals (P eating patterns in adults that varied by age, EO frequency, snack frequency and energy intake pattern. LCA is a useful approach to capture differences in EO timing across the day. Future research should examine associations between temporal eating patterns and health.

  10. A latent class analysis of brief postpartum psychiatric hospital admissions.

    Science.gov (United States)

    Shlomi Polachek, Inbal; Fung, Kinwah; Putnam, Karen; Brody, Samantha Meltzer; Vigod, Simone N

    2017-09-11

    Almost 40% of postpartum psychiatric hospital admissions are brief, lasting 72h or less. We aimed to identify unique subgroups of women within this group to inform better intervention. All women in Ontario, Canada with a brief postpartum psychiatric admission (≤ 72h) (2007-2012)(N = 631) were studied using latent class analysis. We identified distinct subtypes of women and compared women within each subtype on post-discharge mental health indicators: physician visits, emergency department (ED) visits and readmissions. We identified four clinically distinct classes: (1)women with no diagnosed mental illness (2 years before delivery) (n = 179; 28.4% of the sample); (2)women with pre-existing history of severe mental illness (i.e. psychosis) (n = 161; 25.5%); (3)women with pre-existing history of non-psychotic mental illness (n = 211; 33.4%); and (4)adolescent rural-dwelling women with alcohol and substance use disorders (n = 80; 12.7%). In the 1 year post-discharge, women in classes 1-3 were more likely to have post-discharge physician visit than women in class 4 (p class 2 were most likely to be readmitted (p planning. Copyright © 2017 Elsevier B.V. All rights reserved.

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

    OpenAIRE

    Nouwens, P.J.G.; Lucas, R.; Smulders, N.B.M.; Embregts, P.J.C.M.; Van Nieuwenhuizen, Ch

    2017-01-01

    Background 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. Methods Latent clas...

  12. Latent Classes and Cumulative Impacts of Adverse Childhood Experiences.

    Science.gov (United States)

    Barboza, Gia Elise

    2017-01-01

    Studies of adverse childhood experiences (ACEs) have gauged severity using a cumulative risk (CR) index. Few studies have focused on the nature of the context of adversity and their association with psychosocial outcomes. The objective of this study was to examine the patterning of ACEs and to explore the resultant patterns' association with HIV risk-taking, problem drinking, and depressive symptoms in adulthood. Latent class analysis (LCA) was used to identify homogeneous, mutually exclusive "classes" of 11 of the most commonly used ACEs. The LCA resulted in four high-risk profiles and one low-risk profile, which were labeled: (1) highly abusive and dysfunctional (3.3%; n = 1,983), (2) emotionally abusive alcoholic with parental conflict (6%, n = 3,303), (3) sexual abuse only (4.3%, n = 2,260), (4) emotionally abusive and alcoholic (30.3%, n = 17,460), and (5) normative, low risk (56.3%, n = 32,950). Compared to the low-risk class, each high-risk profile was differentially associated with adult psychosocial outcomes even when the conditional CR within that class was similar. The results further our understanding about the pattern of ACEs and the unique pathways to poor health. Implications for child welfare systems when dealing with individuals who have experienced multiple forms of early childhood maltreatment and/or household dysfunction are discussed.

  13. Identification and Prediction of Latent Classes of Weight-loss Strategies Among Women

    OpenAIRE

    Lanza, Stephanie T.; Savage, Jennifer S.; Birch, Leann L.

    2009-01-01

    We apply latent class analysis (LCA) to quantify multidimensional patterns of weight-loss strategies in a sample of 197 women, and explore the degree to which dietary restraint, disinhibition, and other individual characteristics predict membership in latent classes of weight-loss strategies. Latent class models were fit to a set of 14 healthy and unhealthy weight-loss strategies. BMI, weight concern, body satisfaction, depression, dietary disinhibition and restraint, and the interaction of d...

  14. Validation of Diagnostic Measures Based on Latent Class Analysis: A Step Forward in Response Bias Research

    Science.gov (United States)

    Thomas, Michael L.; Lanyon, Richard I.; Millsap, Roger E.

    2009-01-01

    The use of criterion group validation is hindered by the difficulty of classifying individuals on latent constructs. Latent class analysis (LCA) is a method that can be used for determining the validity of scales meant to assess latent constructs without such a priori classifications. The authors used this method to examine the ability of the L…

  15. 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.

  16. A Latent Class Analysis of Personal Values in Young Adults

    Directory of Open Access Journals (Sweden)

    Avanté J. Smack

    2017-12-01

    Full Text Available Human values and motivations are a powerful predictor of behavior, and Schwartz’s taxonomy offers a meaningful organizational system for robust value dimensions (Schwartz, 1992. Although values clearly represent a meaningful and culturally relevant dimension of individual differences, they remain poorly understood particularly in regards to how values co-occur and manifest within individuals. The purpose of the present study was to examine how values co-occur and manifest within individuals. A racially/ethnically diverse sample of 1, 308 undergraduate students (351 males, 'Mage '= 21.70, SD = 5.22 reported on their personal values and personality traits. Latent class analyses revealed support for two value classes: personal-focused (N = 210 and social-focused ('N' = 1098, which map onto hypotheses of value configurations based on Schwartz’s taxonomy (Schwartz, 1992. The value classes also exhibited differences based on racial/ethnic composition, gender composition, and personality trait association, also consistent with previous research. The current study provides evidence for two value types that manifest across two countries in North America.

  17. 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.

  18. Validating the European Health Literacy Survey Questionnaire in people with type 2 diabetes: Latent trait analyses applying multidimensional Rasch modelling and confirmatory factor analysis.

    Science.gov (United States)

    Finbråten, Hanne Søberg; Pettersen, Kjell Sverre; Wilde-Larsson, Bodil; Nordström, Gun; Trollvik, Anne; Guttersrud, Øystein

    2017-11-01

    To validate the European Health Literacy Survey Questionnaire (HLS-EU-Q47) in people with type 2 diabetes mellitus. The HLS-EU-Q47 latent variable is outlined in a framework with four cognitive domains integrated in three health domains, implying 12 theoretically defined subscales. Valid and reliable health literacy measurers are crucial to effectively adapt health communication and education to individuals and groups of patients. Cross-sectional study applying confirmatory latent trait analyses. Using a paper-and-pencil self-administered approach, 388 adults responded in March 2015. The data were analysed using the Rasch methodology and confirmatory factor analysis. Response violation (response dependency) and trait violation (multidimensionality) of local independence were identified. Fitting the "multidimensional random coefficients multinomial logit" model, 1-, 3- and 12-dimensional Rasch models were applied and compared. Poor model fit and differential item functioning were present in some items, and several subscales suffered from poor targeting and low reliability. Despite multidimensional data, we did not observe any unordered response categories. Interpreting the domains as distinct but related latent dimensions, the data fit a 12-dimensional Rasch model and a 12-factor confirmatory factor model best. Therefore, the analyses did not support the estimation of one overall "health literacy score." To support the plausibility of claims based on the HLS-EU score(s), we suggest: removing the health care aspect to reduce the magnitude of multidimensionality; rejecting redundant items to avoid response dependency; adding "harder" items and applying a six-point rating scale to improve subscale targeting and reliability; and revising items to improve model fit and avoid bias owing to person factors. © 2017 John Wiley & Sons Ltd.

  19. Confirmatory factors analysis of science teacher leadership in the Thailand world-class standard schools

    Science.gov (United States)

    Thawinkarn, Dawruwan

    2018-01-01

    This research aims to analyze factors of science teacher leadership in the Thailand World-Class Standard Schools. The research instrument was a five scale rating questionnaire with reliability 0.986. The sample group included 500 science teachers from World-Class Standard Schools who had been selected by using the stratified random sampling technique. Factor analysis of science teacher leadership in the Thailand World-Class Standard Schools was conducted by using M plus for Windows. The results are as follows: The results of confirmatory factor analysis on science teacher leadership in the Thailand World-Class Standard Schools revealed that the model significantly correlated with the empirical data. The consistency index value was x2 = 105.655, df = 88, P-Value = 0.086, TLI = 0.997, CFI = 0.999, RMSEA = 0.022, and SRMR = 0.019. The value of factor loading of science teacher leadership was positive, with statistical significance at the level of 0.01. The value of six factors was between 0.880-0.996. The highest factor loading was the professional learning community, followed by child-centered instruction, participation in development, the role model in teaching, transformational leaders, and self-development with factor loading at 0.996, 0.928, 0.911, 0.907, 0.901, and 0.871, respectively. The reliability of each factor was 99.1%, 86.0%, 83.0%, 82.2%, 81.0%, and 75.8%, respectively.

  20. Addressing the Problem of Switched Class Labels in Latent Variable Mixture Model Simulation Studies

    Science.gov (United States)

    Tueller, Stephen J.; Drotar, Scott; Lubke, Gitta H.

    2011-01-01

    The discrimination between alternative models and the detection of latent classes in the context of latent variable mixture modeling depends on sample size, class separation, and other aspects that are related to power. Prior to a mixture analysis it is useful to investigate model performance in a simulation study that reflects the research…

  1. 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…

  2. Latent classes of polysubstance use among adolescents-a systematic review.

    Science.gov (United States)

    Tomczyk, Samuel; Isensee, Barbara; Hanewinkel, Reiner

    2016-03-01

    This systematic review aims to summarize latent classes of polysubstance use in adolescents (10-19 years), and to describe predictors of polysubstance use. A systematic literature review was conducted in three databases (PUBMED, PsycINFO, PsycARTICLES) to identify peer-reviewed articles on latent classes of adolescent polysubstance use (published through June 30, 2015), and to assess the comparability of their results. 23 studies (N=450-N=419,698) met the inclusion criteria. The studies showed predominantly (18 studies) average to low risk of bias. 17 studies (74%) identified between three or four latent classes, with "no use" or "low use" classes being the largest and "polysubstance use" being the smallest ones. Intermediate classes included extensive single substance use, such as "alcohol only" classes. Polysubstance use classes were unanimously predicted by higher age, higher parental and peer substance use, and poor academic performance, other predictors were highly heterogeneous. Latent classes deliver solid information on polysubstance use in adolescence. Despite their sample sensitivity, the studies possess manifold similarities, hence, modeling latent classes seems to be an ecologically valid approach to further research, e.g., for subgroup analyses or on substance use trajectories. Finally, latent classes may help to illustrate differential effects and special groups in prevention and treatment that depend on the actual consumption pattern. However, there are certain methodological recommendations to be considered in order to obtain reliable results. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  3. Original article Latent classes of criminal intent associated with criminal behaviour

    Directory of Open Access Journals (Sweden)

    Daniel Boduszek

    2014-07-01

    Full Text Available Background This study aimed to examine the number of latent classes of criminal intent that exist among prisoners and to look at the associations with recidivism, number of police arrests, type of offending (robbery, violent offences, murder, and multiple offences, and age. Participants and procedure Latent class analysis was used to identify homogeneous subgroups of prisoners based on their responses to the 10 questions reflecting criminal intent. Participants were 309 male recidivistic prisoners incarcerated in a maximum security prison. Multinomial logistic regression was used to interpret the nature of the latent classes, or groups, by estimating the association between recidivism and latent classes of criminal intent while controlling for offence type (robbery, violent offences, murder, and multiple offences, number of arrests, and age. Results The best fitting latent class model was a three-class solution: ‘High criminal intent’ (49.3%, ‘Intermediate criminal intent’ (41.3%, and ‘Low criminal intent’ (9.4%. The latent classes were differentially related to the external variables (recidivism, violent offences, and age. Conclusions Criminal intent is best explained by three homogeneous classes that appear to represent an underlying continuum. Future work is needed to identify whether these distinct classes of criminal intent may predict engagement in various types of criminal behaviour.

  4. Estimation of Parameters in Latent Class Models with Constraints on the Parameters.

    Science.gov (United States)

    1986-06-01

    the item parameters. Let us briefly review the elements of latent class models. The reader desiring a thorough introduction can consult Lazarsfeld and...parameters, including most of the models which have been proposed to date. The latent distance model of Lazarsfeld and Henry (1968) and the quasi...Psychometrika, 1964, 29, 115-129. Lazarsfeld , P.F., and Henry, N.W. Latent structure analysis. Boston: Houghton-Mifflin, 1968. L6. - 29 References continued

  5. 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.

  6. 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.

  7. 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

  8. Probit Latent Class Analysis with Dichotomous or Ordered Category Measures: Conditional Independence/Dependence Models.

    Science.gov (United States)

    Uebersax, John S.

    1999-01-01

    Describes flexible measures that relax restrictive conditional independence assumptions of latent class analysis. Dichotomous and ordered category manifest variables are viewed as discretized latent continuous variables. Discusses the relationship between the multivariate probit model proposed and the mixed Rasch model of J. Rost (1991). (SLD)

  9. Diagnostic Performance Tests for Suspected Scaphoid Fractures Differ with Conventional and Latent Class Analysis

    NARCIS (Netherlands)

    Buijze, Geert A.; Mallee, Wouter H.; Beeres, Frank J. P.; Hanson, Timothy E.; Johnson, Wesley O.; Ring, David

    2011-01-01

    Evaluation of the diagnostic performance characteristics of radiographic tests for diagnosing a true fracture among suspected scaphoid fractures is hindered by the lack of a consensus reference standard. Latent class analysis is a statistical method that takes advantage of unobserved, or latent,

  10. Cross-Informant Agreement on Child and Adolescent Withdrawn Behavior: A Latent Class Approach

    Science.gov (United States)

    Rubin, David H.; Althoff, Robert R.; Walkup, John T.; Hudziak, James J.

    2013-01-01

    Withdrawn behavior (WB) relates to many developmental outcomes, including pervasive developmental disorders, anxiety, depression, psychosis, personality disorders and suicide. No study has compared the latent profiles of different informants' reports on WB. This study uses multi-informant latent class analyses (LCA) of the child behavior checklist…

  11. The Latent Class Model as a Measurement Model for Situational Judgment Tests

    Directory of Open Access Journals (Sweden)

    Frank Rijmen

    2011-11-01

    Full Text Available In a situational judgment test, it is often debatable what constitutes a correct answer to a situation. There is currently a multitude of scoring procedures. Establishing a measurement model can guide the selection of a scoring rule. It is argued that the latent class model is a good candidate for a measurement model. Two latent class models are applied to the Managing Emotions subtest of the Mayer, Salovey, Caruso Emotional Intelligence Test: a plain-vanilla latent class model, and a second-order latent class model that takes into account the clustering of several possible reactions within each hypothetical scenario of the situational judgment test. The results for both models indicated that there were three subgroups characterised by the degree to which differentiation occurred between possible reactions in terms of perceived effectiveness. Furthermore, the results for the second-order model indicated a moderate cluster effect.

  12. Reporting guidelines for diagnostic accuracy studies that use Bayesian latent class models (STARD-BLCM)

    DEFF Research Database (Denmark)

    Kostoulas, Polychronis; Nielsen, Søren S.; Branscum, Adam J.

    2017-01-01

    for studies designed to estimate the accuracy of tests when disease status is known. The original STARD statement was initially published in seven journals, while an updated version — STARD2015 — has been recently released. More than 200 biomedical journals encourage its use in their instructions to authors....... An affordable, reliable, and noninvasive reference standard does not always exist as is the case for infectious diseases with a long latent period (e.g., in chronic infections such as tuberculosis). In such situations test accuracy can be estimated using latent class models that do not require knowledge...... to estimate test accuracy. Latent class models, in conjunction with what the tests under evaluation actually detect (e.g., organisms or immune responses to organisms), define the latent status. Thus, a definition/interpretation of the latent disease or infection under consideration from a biological...

  13. Latent Classes in the Developmental Trajectories of Infant Handedness

    Science.gov (United States)

    Michel, George F.; Babik, Iryna; Sheu, Ching-Fan; Campbell, Julie M.

    2014-01-01

    Handedness for acquiring objects was assessed monthly from 6 to 14 months in 328 infants (182 males). A group based trajectory model identified 3 latent groups with different developmental trajectories: those with an identifiable right preference (38%) or left preference (14%) and those without an identifiable preference (48%) but with a…

  14. Personality types in childhood: relations to latent trajectory classes of problem behavior and overreactive parenting across the transition into adolescence

    NARCIS (Netherlands)

    van den Akker, A.L.; Deković, M.; Asscher, J.J.; Shiner, R.L.; Prinzie, P.

    2013-01-01

    This study investigated relations among children's personality types, trajectories of internalizing and externalizing problems, and overreactive parenting across 6 years. Latent Class Analysis of the Big 5 personality dimensions (modeled as latent factors, based on mother, father and teacher

  15. Predictors of Latent Trajectory Classes of Dating Violence Victimization

    Science.gov (United States)

    Brooks-Russell, Ashley; Foshee, Vangie; Ennett, Susan

    2014-01-01

    This study identified classes of developmental trajectories of physical dating violence victimization from grades 8 to 12 and examined theoretically-based risk factors that distinguished among trajectory classes. Data were from a multi-wave longitudinal study spanning 8th through 12th grade (n = 2,566; 51.9% female). Growth mixture models were used to identify trajectory classes of physical dating violence victimization separately for girls and boys. Logistic and multinomial logistic regressions were used to identify situational and target vulnerability factors associated with the trajectory classes. For girls, three trajectory classes were identified: a low/non-involved class; a moderate class where victimization increased slightly until the 10th grade and then decreased through the 12th grade; and a high class where victimization started at a higher level in the 8th grade, increased substantially until the 10th grade, and then decreased until the 12th grade. For males, two classes were identified: a low/non-involved class, and a victimized class where victimization increased slightly until the 9th grade, decreased until the 11th grade, and then increased again through the 12th grade. In bivariate analyses, almost all of the situational and target vulnerability risk factors distinguished the victimization classes from the non-involved classes. However, when all risk factors and control variables were in the model, alcohol use (a situational vulnerability) was the only factor that distinguished membership in the moderate trajectory class from the non-involved class for girls; anxiety and being victimized by peers (target vulnerability factors) were the factors that distinguished the high from the non-involved classes for the girls; and victimization by peers was the only factor distinguishing the victimized from the non-involved class for boys. These findings contribute to our understanding of the heterogeneity in physical dating violence victimization during

  16. Latent structure of cognition in schizophrenia: a confirmatory factor analysis of the MATRICS Consensus Cognitive Battery (MCCB).

    Science.gov (United States)

    McCleery, A; Green, M F; Hellemann, G S; Baade, L E; Gold, J M; Keefe, R S E; Kern, R S; Mesholam-Gately, R I; Seidman, L J; Subotnik, K L; Ventura, J; Nuechterlein, K H

    2015-01-01

    The number of separable cognitive dimensions in schizophrenia has been debated. Guided by the extant factor analytic literature, the NIMH Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) initiative selected seven cognitive domains relevant to treatment studies in schizophrenia: speed of processing, attention/vigilance, working memory, verbal learning, visual learning, reasoning and problem solving, and social cognition. These domains are assessed in the MATRICS Consensus Cognitive Battery (MCCB). The aim of this study was to conduct a confirmatory factor analysis (CFA) of the beta battery of the MCCB to compare the fit of the MATRICS consensus seven-domain model to other models in the current literature on cognition in schizophrenia. Using data from 281 schizophrenia outpatients, we compared the seven correlated factors model with alternative models. Specifically, we compared the 7-factor model to (a) a single-factor model, (b) a three correlated factors model including speed of processing, working memory, and general cognition, and (c) a hierarchical model in which seven first-order factors loaded onto a second-order general cognitive factor. Multiple fit indices indicated the seven correlated factors model was the best fit for the data and provided significant improvement in model fit beyond the comparison models. These results support the assessment of these seven cognitive dimensions in clinical trials of interventions to improve cognition in schizophrenia. Because these cognitive factors are separable to some degree, it is plausible that specific interventions may have differential effects on the domains.

  17. Classifying life course trajectories : a comparison of latent class and sequence analysis

    NARCIS (Netherlands)

    Barban, Nicola; Billari, Francesco C.

    2012-01-01

    . We compare two techniques that are widely used in the analysis of life course trajectories: latent class analysis and sequence analysis. In particular, we focus on the use of these techniques as devices to obtain classes of individual life course trajectories. We first compare the consistency of

  18. Two-Step Estimation of Models Between Latent Classes and External Variables.

    Science.gov (United States)

    Bakk, Zsuzsa; Kuha, Jouni

    2017-11-17

    We consider models which combine latent class measurement models for categorical latent variables with structural regression models for the relationships between the latent classes and observed explanatory and response variables. We propose a two-step method of estimating such models. In its first step, the measurement model is estimated alone, and in the second step the parameters of this measurement model are held fixed when the structural model is estimated. Simulation studies and applied examples suggest that the two-step method is an attractive alternative to existing one-step and three-step methods. We derive estimated standard errors for the two-step estimates of the structural model which account for the uncertainty from both steps of the estimation, and show how the method can be implemented in existing software for latent variable modelling.

  19. Latent class bivariate model for the meta-analysis of diagnostic test accuracy studies.

    Science.gov (United States)

    Eusebi, Paolo; Reitsma, Johannes B; Vermunt, Jeroen K

    2014-07-11

    Several types of statistical methods are currently available for the meta-analysis of studies on diagnostic test accuracy. One of these methods is the Bivariate Model which involves a simultaneous analysis of the sensitivity and specificity from a set of studies. In this paper, we review the characteristics of the Bivariate Model and demonstrate how it can be extended with a discrete latent variable. The resulting clustering of studies yields additional insight into the accuracy of the test of interest. A Latent Class Bivariate Model is proposed. This model captures the between-study variability in sensitivity and specificity by assuming that studies belong to one of a small number of latent classes. This yields both an easier to interpret and a more precise description of the heterogeneity between studies. Latent classes may not only differ with respect to the average sensitivity and specificity, but also with respect to the correlation between sensitivity and specificity. The Latent Class Bivariate Model identifies clusters of studies with their own estimates of sensitivity and specificity. Our simulation study demonstrated excellent parameter recovery and good performance of the model selection statistics typically used in latent class analysis. Application in a real data example on coronary artery disease showed that the inclusion of latent classes yields interesting additional information. Our proposed new meta-analysis method can lead to a better fit of the data set of interest, less biased estimates and more reliable confidence intervals for sensitivities and specificities. But even more important, it may serve as an exploratory tool for subsequent sub-group meta-analyses.

  20. Predictors of Latent Trajectory Classes of Dating Violence Victimization

    OpenAIRE

    Brooks-Russell, Ashley; Foshee, Vangie; Ennett, Susan

    2012-01-01

    This study identified classes of developmental trajectories of physical dating violence victimization from grades 8 to 12 and examined theoretically-based risk factors that distinguished among trajectory classes. Data were from a multi-wave longitudinal study spanning 8th through 12th grade (n = 2,566; 51.9% female). Growth mixture models were used to identify trajectory classes of physical dating violence victimization separately for girls and boys. Logistic and multinomial logistic regressi...

  1. Predictors of Latent Trajectory Classes of Physical Dating Violence Victimization

    Science.gov (United States)

    Brooks-Russell, Ashley; Foshee, Vangie A.; Ennett, Susan T.

    2013-01-01

    This study identified classes of developmental trajectories of physical dating violence victimization from grades 8 to 12 and examined theoretically-based risk factors that distinguished among trajectory classes. Data were from a multi-wave longitudinal study spanning 8th through 12th grade (n = 2,566; 51.9 % female). Growth mixture models were…

  2. The association between latent depression subtypes and remission after treatment with citalopram: A latent class analysis with distal outcome.

    Science.gov (United States)

    Ulbricht, Christine M; Rothschild, Anthony J; Lapane, Kate L

    2015-12-01

    The objectives were to characterize latent depression subtypes by symptoms, evaluate sex differences in and examine correlates of these subtypes, and examine the association between subtype and symptom remission after citalopram treatment. Latent class analysis was applied to baseline data from 2772 participants in the Sequenced Treatment Alternatives to Relieve Depression trial. Indicators were from the Quick Inventory of Depressive Symptomatology. Separate multinomial logistic models identified correlates of subtypes and the association between subtype and the distal outcome of remission. Four latent subtypes were identified: Mild (men: 37%, women: 27%), Moderate (men: 24%, women: 21%), Severe with Increased Appetite (men: 13%, women: 22%), and Severe with Insomnia (men: 26%, women: 31%). Generalized anxiety disorder, bulimia, and social phobia were correlated with Severe with Increased Appetite and generalized anxiety disorder, post-traumatic stress disorder, and social phobia with Severe with Insomnia. Relative to those with the Mild subtype, those with Severe with Increased Appetite (odds ratiomen (OR): 0.48; 95% confidence interval (CI): 0.25-0.92; OR women: 0.59; 95% CI: 0.41-0.86) and those with Severe Depression with Insomnia (ORmen: 0.65; 95% CI: 0.41-1.02; ORwomen: 0.45; 95% CI: 0.32-0.64) were less likely to achieve remission. The sample size limited exploration of higher order interactions. Insomnia and increased appetite distinguished latent subtypes. Sex and psychiatric comorbidities differed between the subtypes. Remission was less likely for those with the severe depression subtypes. Sleep disturbances, appetite changes, and other mental disorders may play a role in the etiology and treatment of depression. Copyright © 2015 Elsevier B.V. All rights reserved.

  3. Cyclist–motorist crash patterns in Denmark: A latent class clustering approach

    DEFF Research Database (Denmark)

    Kaplan, Sigal; Prato, Carlo Giacomo

    2013-01-01

    differentiating the latent classes were speed limit, infrastructure type, road surface conditions, number of lanes, motorized vehicle precrash maneuvers, the availability of a cycle lane, cyclist intoxication, and helmet wearing behavior. After the latent class clustering, the distribution of cyclists’ injury......Objective: The current study aimed at uncovering patterns of cyclist–motorist crashes in Denmark and investigating their prevalence and severity. The importance of implementing clustering techniques for providing a holistic overview of vulnerable road users’ crash patterns derives from the need...

  4. Traumatic Brain Injury and PTSD Screening Efforts Evaluated Using Latent Class Analysis

    Science.gov (United States)

    2014-01-01

    Carolina). For latent class analyses, SAS PROC LCA , version 1.2.5 was used (PROC LCA ; Lanza et al., 2007). Results Analysis yielded four classes with...41, 1284–1292. doi:10.1097/01.MLR.0000093487.78664.3C Lanza, S., Collins, L., Lemmon, D., & Schafer, J. (2007). PROC LCA : A SAS procedure for latent...International Journal of Psychiatry in Clinical Practice, 9, 9 –14. doi:10.1185/ 135525703125002360 PROC LCA , Version 1.2.5. [Computer software]. The

  5. Investigating preferences for mosquito-control technologies in Mozambique with latent class analysis

    Directory of Open Access Journals (Sweden)

    Barclay Victoria C

    2011-07-01

    Full Text Available Abstract Background It is common practice to seek the opinions of future end-users during the development of innovations. Thus, the aim of this study is to investigate latent classes of users in Mozambique based on their preferences for mosquito-control technology attributes and covariates of these classes, as well as to explore which current technologies meet these preferences. Methods Surveys were administered in five rural villages in Mozambique. The data were analysed with latent class analysis. Results This study showed that users' preferences for malaria technologies varied, and people could be categorized into four latent classes based on shared preferences. The largest class, constituting almost half of the respondents, would not avoid a mosquito-control technology because of its cost, heat, odour, potential to make other health issues worse, ease of keeping clean, or inadequate mosquito control. The other three groups are characterized by the attributes which would make them avoid a technology; these groups are labelled as the bites class, by-products class, and multiple-concerns class. Statistically significant covariates included literacy, self-efficacy, willingness to try new technologies, and perceived seriousness of malaria for the household. Conclusions To become widely diffused, best practices suggest that end-users should be included in product development to ensure that preferred attributes or traits are considered. This study demonstrates that end-user preferences can be very different and that one malaria control technology will not satisfy everyone.

  6. Latent-Class Hough Forests for 6 DoF Object Pose Estimation.

    Science.gov (United States)

    Tejani, Alykhan; Kouskouridas, Rigas; Doumanoglou, Andreas; Tang, Danhang; Kim, Tae-Kyun

    2018-01-01

    In this paper we present Latent-Class Hough Forests, a method for object detection and 6 DoF pose estimation in heavily cluttered and occluded scenarios. We adapt a state of the art template matching feature into a scale-invariant patch descriptor and integrate it into a regression forest using a novel template-based split function. We train with positive samples only and we treat class distributions at the leaf nodes as latent variables. During testing we infer by iteratively updating these distributions, providing accurate estimation of background clutter and foreground occlusions and, thus, better detection rate. Furthermore, as a by-product, our Latent-Class Hough Forests can provide accurate occlusion aware segmentation masks, even in the multi-instance scenario. In addition to an existing public dataset, which contains only single-instance sequences with large amounts of clutter, we have collected two, more challenging, datasets for multiple-instance detection containing heavy 2D and 3D clutter as well as foreground occlusions. We provide extensive experiments on the various parameters of the framework such as patch size, number of trees and number of iterations to infer class distributions at test time. We also evaluate the Latent-Class Hough Forests on all datasets where we outperform state of the art methods.

  7. 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.

  8. 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

  9. Psychological distress among victimized women on probation and parole: A latent class analysis.

    Science.gov (United States)

    Golder, Seana; Engstrom, Malitta; Hall, Martin T; Higgins, George E; Logan, T K

    2015-07-01

    Latent class analysis was used to identify subgroups of victimized women (N = 406) on probation and parole differentiated by levels of general psychological distress. The 9 primary symptom dimensions from the Brief Symptom Inventory (BSI) were used individually as latent class indicators (Derogatis, 1993). Results identified 3 classes of women characterized by increasing levels of psychological distress; classes were further differentiated by posttraumatic stress disorder symptoms, cumulative victimization, substance use and other domains of psychosocial functioning (i.e., sociodemographic characteristics; informal social support and formal service utilization; perceived life stress; and resource loss). The present research was effective in uncovering important heterogeneity in psychological distress using a highly reliable and easily accessible measure of general psychological distress. Differentiating levels of psychological distress and associated patterns of psychosocial risk can be used to develop intervention strategies targeting the needs of different subgroups of women. Implications for treatment and future research are presented. (c) 2015 APA, all rights reserved).

  10. 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.…

  11. A Behavioral Approach to Understanding Green Consumerism Using Latent Class Choice Analysis

    DEFF Research Database (Denmark)

    Peschel, Anne Odile; Grebitus, Carola; Steiner, Bodo

    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...

  12. A Latent Class Analysis of Adolescent Gambling: Application of Resilience Theory

    Science.gov (United States)

    Goldstein, Abby L.; Faulkner, Breanne; Cunningham, Rebecca M.; Zimmerman, Marc A.; Chermack, Stephen; Walton, Maureen A.

    2013-01-01

    The current study examined the application of resilience theory to adolescent gambling using Latent Class Analysis (LCA) to establish subtypes of adolescent gamblers and to explore risk and promotive factors associated with gambling group membership. Participants were a diverse sample of 249 adolescents ages 14 to 18 (30.1 % female, 59.4 % African…

  13. Estimating the Concomitant-Variable Latent-Class Model with the EM Algorithm.

    Science.gov (United States)

    van der Heijden, Peter G. M.; And Others

    1996-01-01

    The concomitant-variable latent-class model is described for situations with continuous explanatory variables, and an EM estimation procedure to estimate the model is presented. The model is applied to the study of crime among ethnic groups in the Netherlands, and its utility is demonstrated. (SLD)

  14. A Mixture Rasch Model-Based Computerized Adaptive Test for Latent Class Identification

    Science.gov (United States)

    Jiao, Hong; Macready, George; Liu, Junhui; Cho, Youngmi

    2012-01-01

    This study explored a computerized adaptive test delivery algorithm for latent class identification based on the mixture Rasch model. Four item selection methods based on the Kullback-Leibler (KL) information were proposed and compared with the reversed and the adaptive KL information under simulated testing conditions. When item separation was…

  15. Bayesian Inference for Growth Mixture Models with Latent Class Dependent Missing Data

    Science.gov (United States)

    Lu, Zhenqiu Laura; Zhang, Zhiyong; Lubke, Gitta

    2011-01-01

    "Growth mixture models" (GMMs) with nonignorable missing data have drawn increasing attention in research communities but have not been fully studied. The goal of this article is to propose and to evaluate a Bayesian method to estimate the GMMs with latent class dependent missing data. An extended GMM is first presented in which class…

  16. 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

  17. 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

  18. Who Benefits Most from Head Start? Using Latent Class Moderation to Examine Differential Treatment Effects

    Science.gov (United States)

    Cooper, Brittany Rhoades; Lanza, Stephanie T.

    2014-01-01

    Head Start (HS) is the largest federally funded preschool program for disadvantaged children. Research has shown relatively small impacts on cognitive and social skills; therefore, some have questioned its effectiveness. Using data from the Head Start Impact Study (3-year-old cohort; N = 2,449), latent class analysis was used to (a) identify…

  19. Statistical power of likelihood ratio and Wald tests in latent class models with covariates

    NARCIS (Netherlands)

    Gudicha, D.W.; Schmittmann, V.D.; Vermunt, J.K.

    2017-01-01

    This paper discusses power and sample-size computation for likelihood ratio and Wald testing of the significance of covariate effects in latent class models. For both tests, asymptotic distributions can be used; that is, the test statistic can be assumed to follow a central Chi-square under the null

  20. Divisive Latent Class Modeling as a Density Estimation Method for Categorical Data

    NARCIS (Netherlands)

    van der Palm, D.W.; van der Ark, L.A.; Vermunt, J.K.

    Traditionally latent class (LC) analysis is used by applied researchers as a tool for identifying substantively meaningful clusters. More recently, LC models have also been used as a density estimation tool for categorical variables. We introduce a divisive LC (DLC) model as a density estimation

  1. Divisive latent class modeling as a density estimation method for categorical data

    NARCIS (Netherlands)

    van der Palm, D.W.; van der Ark, L.A.; Vermunt, J.K.

    2016-01-01

    Traditionally latent class (LC) analysis is used by applied researchers as a tool for identifying substantively meaningful clusters. More recently, LC models have also been used as a density estimation tool for categorical variables. We introduce a divisive LC (DLC) model as a density estimation

  2. 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

    BACKGROUND: 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. Pr...

  3. A Note on Parameter Estimation for Lazarsfeld's Latent Class Model Using the EM Algorithm.

    Science.gov (United States)

    Everitt, B. S.

    1984-01-01

    Latent class analysis is formulated as a problem of estimating parameters in a finite mixture distribution. The EM algorithm is used to find the maximum likelihood estimates, and the case of categorical variables with more than two categories is considered. (Author)

  4. 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 scor...

  5. Latent Class Analysis in Higher Education: An Illustrative Example of Pluralistic Orientation

    Science.gov (United States)

    Denson, Nida; Ing, Marsha

    2014-01-01

    Although used frequently in related fields such as K-12 education research, educational psychology, sociology, and social survey research, latent class analysis (LCA) has been infrequently used in higher education. This article provides higher education researchers with a pedagogical application of LCA to classify entering freshmen based on their…

  6. 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

  7. The Structure of Student Satisfaction with College Services: A Latent Class Model

    Science.gov (United States)

    Adwere-Boamah, Joseph

    2011-01-01

    Latent Class Analysis (LCA) was used to identify distinct groups of Community college students based on their self-ratings of satisfaction with student service programs. The programs were counseling, financial aid, health center, student programs and student government. The best fitting model to describe the data was a two Discrete-Factor model…

  8. 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

  9. Identifying person-fit latent classes, and explanation of categorical and continuous person misfit

    NARCIS (Netherlands)

    Conijn, J.M.; Sijtsma, K.; Emons, W.H.M.

    2016-01-01

    Latent class (LC) cluster analysis of a set of subscale lz person-fit statistics was proposed to explain person misfit on multiscale measures. The proposed explanatory LC person-fit analysis was used to analyze data of students (N = 91,648) on the nine-subscale School Attitude Questionnaire Internet

  10. Inferring the structure of latent class models using a genetic algorithm

    NARCIS (Netherlands)

    van der Maas, H.L.J.; Raijmakers, M.E.J.; Visser, I.

    2005-01-01

    Present optimization techniques in latent class analysis apply the expectation maximization algorithm or the Newton-Raphson algorithm for optimizing the parameter values of a prespecified model. These techniques can be used to find maximum likelihood estimates of the parameters, given the specified

  11. Goodness-of-fit of multilevel latent class models for categorical data

    NARCIS (Netherlands)

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

    2016-01-01

    In the context of multilevel latent class models, the goodness-of-fit depends on multiple aspects, among which are two local independence assumptions. However, because of the lack of local fit statistics, the model and any issues relating to model fit can only be inspected jointly through global fit

  12. 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.

  13. Combined Patterns of Risk for Problem and Obesogenic Behaviors in Adolescents: A Latent Class Analysis Approach

    Science.gov (United States)

    Fleary, Sasha A.

    2017-01-01

    Background: Several studies have used latent class analyses to explore obesogenic behaviors and substance use in adolescents independently. We explored a variety of health risks jointly to identify distinct patterns of risk behaviors among adolescents. Methods: Latent class models were estimated using Youth Risk Behavior Surveillance System…

  14. Tailoring community-based wellness initiatives with latent class analysis--Massachusetts Community Transformation Grant projects.

    Science.gov (United States)

    Arcaya, Mariana; Reardon, Timothy; Vogel, Joshua; Andrews, Bonnie K; Li, Wenjun; Land, Thomas

    2014-02-13

    Community-based approaches to preventing chronic diseases are attractive because of their broad reach and low costs, and as such, are integral components of health care reform efforts. Implementing community-based initiatives across Massachusetts' municipalities presents both programmatic and evaluation challenges. For effective delivery and evaluation of the interventions, establishing a community typology that groups similar municipalities provides a balanced and cost-effective approach. Through a series of key informant interviews and exploratory data analysis, we identified 55 municipal-level indicators of 6 domains for the typology analysis. The domains were health behaviors and health outcomes, housing and land use, transportation, retail environment, socioeconomics, and demographic composition. A latent class analysis was used to identify 10 groups of municipalities based on similar patterns of municipal-level indicators across the domains. Our model with 10 latent classes yielded excellent classification certainty (relative entropy = .995, minimum class probability for any class = .871), and differentiated distinct groups of municipalities based on health-relevant needs and resources. The classes differentiated healthy and racially and ethnically diverse urban areas from cities with similar population densities and diversity but worse health outcomes, affluent communities from lower-income rural communities, and mature suburban areas from rapidly suburbanizing communities with different healthy-living challenges. Latent class analysis is a tool that may aid in the planning, communication, and evaluation of community-based wellness initiatives such as Community Transformation Grants projects administrated by the Centers for Disease Control and Prevention.

  15. Loss of Control as a Discriminating Factor Between Different Latent Classes of Disordered Gambling Severity.

    Science.gov (United States)

    James, Richard J E; O'Malley, Claire; Tunney, Richard J

    2016-12-01

    Analyses of disordered gambling assessment data have indicated that commonly used screens appear to measure latent categories. This stands in contrast to the oft-held assumption that problem gambling is at the extreme of a continuum. To explore this further, we report a series of latent class analyses of a number of prevalent problem gambling assessments (PGSI, SOGS, DSM-IV Pathological Gambling based assessments) in nationally representative British surveys between 1999 and 2012, analysing data from nearly fifty thousand individuals. The analyses converged on a three class model in which the classes differed by problem gambling severity. This identified an initial class of gamblers showing minimal problems, a additional class predominantly endorsing indicators of preoccupation and loss chasing, and a third endorsing a range of disordered gambling criteria. However, there was considerable evidence to suggest that classes of intermediate and high severity disordered gamblers differed systematically in their responses to items related to loss of control, and not simply on the most 'difficult' items. It appeared that these differences were similar between assessments. An important exception to this was one set of DSM-IV criteria based analyses using a specific cutoff, which was also used in an analysis that identified an increase in UK problem gambling prevalence between 2007 and 2010. The results suggest that disordered gambling has a mixed latent structure, and that present assessments of problem gambling appear to converge on a broadly similar construct.

  16. Usage of a Responsible Gambling Tool: A Descriptive Analysis and Latent Class Analysis of User Behavior.

    Science.gov (United States)

    Forsström, David; Hesser, Hugo; Carlbring, Per

    2016-09-01

    Gambling is a common pastime around the world. Most gamblers can engage in gambling activities without negative consequences, but some run the risk of developing an excessive gambling pattern. Excessive gambling has severe negative economic and psychological consequences, which makes the development of responsible gambling strategies vital to protecting individuals from these risks. One such strategy is responsible gambling (RG) tools. These tools track an individual's gambling history and supplies personalized feedback and might be one way to decrease excessive gambling behavior. However, research is lacking in this area and little is known about the usage of these tools. The aim of this article is to describe user behavior and to investigate if there are different subclasses of users by conducting a latent class analysis. The user behaviour of 9528 online gamblers who voluntarily used a RG tool was analysed. Number of visits to the site, self-tests made, and advice used were the observed variables included in the latent class analysis. Descriptive statistics show that overall the functions of the tool had a high initial usage and a low repeated usage. Latent class analysis yielded five distinct classes of users: self-testers, multi-function users, advice users, site visitors, and non-users. Multinomial regression revealed that classes were associated with different risk levels of excessive gambling. The self-testers and multi-function users used the tool to a higher extent and were found to have a greater risk of excessive gambling than the other classes.

  17. Identification and prediction of latent classes of weight-loss strategies among women.

    Science.gov (United States)

    Lanza, Stephanie T; Savage, Jennifer S; Birch, Leann L

    2010-04-01

    We apply latent class analysis (LCA) to quantify multidimensional patterns of weight-loss strategies in a sample of 197 women, and explore the degree to which dietary restraint, disinhibition, and other individual characteristics predict membership in latent classes of weight-loss strategies. Latent class models were fit to a set of 14 healthy and unhealthy weight-loss strategies. BMI, weight concern, body satisfaction, depression, dietary disinhibition and restraint, and the interaction of disinhibition and restraint were included as predictors of latent class membership. All analyses were conducted with PROC LCA, a recently developed SAS procedure available for download. Results revealed four subgroups of women based on their history of weight-loss strategies: No Weight Loss Strategy (10.0%), Dietary Guidelines (26.5%), Guidelines+Macronutrients (39.4%), and Guidelines+Macronutrients+Restrictive (24.2%). BMI, weight concerns, the desire to be thinner, disinhibition, and dietary restraint were all significantly related to weight-control strategy latent class. Among women with low dietary restraint, disinhibition increases the odds of engaging in any set of weight-loss strategies vs. none, whereas among medium- and high-restraint women disinhibition increases the odds of use of unhealthy vs. healthy strategies. LCA was an effective tool for organizing multiple weight-loss strategies in order to identify subgroups of individuals who have engaged in particular sets of strategies over time. This person-centered approach provides a measure weight-control status, where the different statuses are characterized by particular combinations of healthy and unhealthy weight-loss strategies.

  18. Latent classes of alcohol problems in Mauritian men: Results from the Joint Child Health Project.

    Science.gov (United States)

    Luczak, Susan E; Prescott, Carol A; Venables, Peter H

    2017-11-01

    The purpose of this study was to identify latent classes of alcohol problems and their sociodemographic correlates in the east African nation of Mauritius. Participants were from the Joint Child Health Project, a longitudinal study of a 1969-1970 birth cohort of 1795 individuals. In mid-adulthood (M = 37 years), all available participants (n = 1206; 67% of the original cohort) were assessed for demographic characteristics, and lifetime drinkers were assessed for alcohol-related problems. Given the low endorsement of problems by women, only male lifetime drinkers (n = 520) were included in the latent class analyses. Analyses indicated the best-fitting model contained four classes of drinkers: Non-problematic (66%), Moderate (16%), Hazardous (11%) and Severe (6%). Lower education and occupation were associated with Moderate and Severe problem classes, whereas higher education and occupation were associated with the Hazardous class. Being Hindu, Tamil and Creole were differentially predictive of class membership, but being Muslim was not. Our findings provide evidence of a distinct Hazardous drinking class that has unique demographic correlates and may represent a cluster of problems that is more bound by cultural factors. We also found problem classes on a severity continuum from none to moderate to severe problems. This study highlights the importance of examining societal, subgroup and person-level factors to produce a more nuanced understanding of distinct classes of alcohol-related problems. [Luczak SE, Prescott CA, Venables PH. Latent classes of alcohol problems in Mauritian men: Results from the Joint Child Health Project. © 2017 Australasian Professional Society on Alcohol and other Drugs.

  19. 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.

  20. Latent classes of resilience and psychological response among only-child loss parents in China.

    Science.gov (United States)

    Wang, An-Ni; Zhang, Wen; Zhang, Jing-Ping; Huang, Fei-Fei; Ye, Man; Yao, Shu-Yu; Luo, Yuan-Hui; Li, Zhi-Hua; Zhang, Jie; Su, Pan

    2017-10-01

    Only-child loss parents in China recently gained extensive attention as a newly defined social group. Resilience could be a probable solution out of the psychological dilemma. Using a sample of 185 only-child loss people, this study employed latent class analysis (a) to explore whether different classes of resilience could be identified, (b) to determine socio-demographic characteristics of each class, and (c) to compare the depression and the subjective well-being of each class. The results supported a three-class solution, defined as 'high tenacity-strength but moderate optimism class', 'moderate resilience but low self-efficacy class' and 'low tenacity but moderate adaption-dependence class'. Parents with low income and medical insurance of low reimbursement type and without endowment insurance occupied more proportions in the latter two classes. The latter two classes also had a significant higher depression scores and lower subjective well-being scores than high tenacity-strength but moderate optimism class. Future work should care those socio-economically vulnerable bereaved parents, and an elastic economic assistance policy was needed. To develop targeted resilience interventions, the emphasis of high tenacity-strength but moderate optimism class should be the optimism. Moderate resilience but low self-efficacy class should be self-efficacy, and low tenacity but moderate adaption-dependence class should be tenacity. Copyright © 2016 John Wiley & Sons, Ltd.

  1. 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.

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

    Science.gov (United States)

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

    2014-01-01

    Objective: To explore the oral health status through a latent class analysis in elderly social security beneficiaries from Southwest Mexico City. Material and Methods: 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. Results: 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. Conclusion: 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. PMID:24596632

  3. 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.

  4. Examining variation in depressive symptoms over the life course: a latent class analysis.

    Science.gov (United States)

    Mezuk, B; Kendler, K S

    2012-10-01

    Older adults have the lowest prevalence and incidence of major depressive disorder, although it has been hypothesized that this finding is due in part to differences in expression of psychopathology in later life. The aim of this study was to examine variation in depressive symptomatology in the general population across the lifespan. Data came from three sites of the Epidemiologic Catchment Area (ECA) Project (n=10 529). Depressive symptoms during the past 6 months were assessed using the Diagnostic Interview Schedule (DIS). Latent class analysis (LCA) was used to identify homogeneous groups of depressive symptomatology based on 16 individual symptoms, and to examine variation in the prevalence and composition of depression classes across age groups. The DIS symptoms fit a four-class model composed of non-depressed (83.2%), mild depression (11.6%), severe depression (1.9%), and despondent (3.2%) groups. Relative to the non-depressed class, older age was inversely associated with being in the mild or severe depression class. The profile of the latent classes was similar across age groups with the exception of the despondent class, which was not well differentiated among the youngest adults and was not inversely associated with age. The symptom profiles of depression are similar across age with the exception of the despondent class, which is more differentiated from severe depression among older adults. The findings demonstrate the benefit of examining individual symptoms rather than broad symptom groups for understanding the natural history of depression over the lifespan.

  5. Latent trajectory classes of depressive and anxiety disorders from adolescence to adulthood: descriptions of classes and associations with risk factors.

    Science.gov (United States)

    Olino, Thomas M; Klein, Daniel N; Lewinsohn, Peter M; Rohde, Paul; Seeley, John R

    2010-01-01

    This study used person-oriented analyses to identify subgroups of individuals who exhibit different patterns of depressive and anxiety disorders over the course of adolescence and young adulthood. Using latent class growth analysis, six trajectory classes were identified. Two classes were mainly characterized by depressive disorders; one class was mainly characterized by anxiety disorders; two classes were characterized by temporally different patterns of comorbidity; and one class was characterized by the absence of psychopathology. Classes characterized largely by depressive disorders differed in persistence and degree of comorbidity with anxiety disorders. Classes that were characterized by anxiety disorders differed in persistence, age of onset, and constellation of specific anxiety disorders. Female participants were more likely to belong to classes characterized by fluctuations in the course of depressive and anxiety disorders; sex differences were not observed in classes characterized by persistent depressive and anxiety disorders. Offspring of parents with depression were more likely to have a depressive course, whereas offspring of parents with anxiety disorders tended to have a course characterized by anxiety disorder. The findings indicate that several subgroups of adolescents exist with distinct longitudinal trajectories of depressive and anxiety disorders, and these trajectory classes are associated with different risk factors. 2010 Elsevier Inc. All rights reserved.

  6. 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.

  7. Latent Class Analysis of the Child Behavior Checklist Obsessive-Compulsive Scale

    Science.gov (United States)

    Althoff, Robert R.; Rettew, David C.; Boomsma, Dorret I.; Hudziak, James J.

    2009-01-01

    The Obsessive Compulsive Scale (OCS) of the Child Behavior Checklist (CBCL) predicts Obsessive-Compulsive Disorder and is highly heritable. Latent Class Analysis (LCA) of the OCS was used to identify profiles within this 8-item scale and to examine heritability of those profiles. LCA was performed on maternal CBCL reports of their 6–18 year-old children from 2 U.S. nationally representative samples from 1989 (n=2475, 50% male) and 1999 (n=2029, 53% male) and from Dutch Twins in the Netherlands Twin Registry at ages 7 (n=10,194, 49.3% male), 10 (n=6448, 48.1% male), and 12 (n=3674, 48.6% male). The heritability of the resultant classes was estimated using odds ratios of twin membership across classes. A 4-class solution fit all samples best. The resulting classes were a “no or few symptoms” class, a “worries and has to be perfect” class, a “thought problems class, and an “OCS” class. Within class odds ratios were higher than across class odds ratios and were higher for MZ than DZ twins. We conclude that LCA identifies an OCS class and that class is highly heritable using across-twin comparisons. PMID:19840599

  8. Latent classes of childhood trauma exposure predict the development of behavioral health outcomes in adolescence and young adulthood.

    Science.gov (United States)

    Ballard, E D; Van Eck, K; Musci, R J; Hart, S R; Storr, C L; Breslau, N; Wilcox, H C

    2015-11-01

    To develop latent classes of exposure to traumatic experiences before the age of 13 years in an urban community sample and to use these latent classes to predict the development of negative behavioral outcomes in adolescence and young adulthood. A total of 1815 participants in an epidemiologically based, randomized field trial as children completed comprehensive psychiatric assessments as young adults. Reported experiences of nine traumatic experiences before age 13 years were used in a latent class analysis to create latent profiles of traumatic experiences. Latent classes were used to predict psychiatric outcomes at age ⩾13 years, criminal convictions, physical health problems and traumatic experiences reported in young adulthood. Three latent classes of childhood traumatic experiences were supported by the data. One class (8% of sample), primarily female, was characterized by experiences of sexual assault and reported significantly higher rates of a range of psychiatric outcomes by young adulthood. Another class (8%), primarily male, was characterized by experiences of violence exposure and reported higher levels of antisocial personality disorder and post-traumatic stress. The final class (84%) reported low levels of childhood traumatic experiences. Parental psychopathology was related to membership in the sexual assault group. Classes of childhood traumatic experiences predict specific psychiatric and behavioral outcomes in adolescence and young adulthood. The long-term adverse effects of childhood traumas are primarily concentrated in victims of sexual and non-sexual violence. Gender emerged as a key covariate in the classes of trauma exposure and outcomes.

  9. Classification of adults suffering from typical gastroesophageal reflux disease symptoms: contribution of latent class analysis in a European observational study.

    Science.gov (United States)

    Bruley des Varannes, Stanislas; Cestari, Renzo; Usova, Liudmila; Triantafyllou, Konstantinos; Alvarez Sanchez, Angel; Keim, Sofia; Bergmans, Paul; Marelli, Silvia; Grahl, Esther; Ducrotté, Philippe

    2014-06-26

    As illustrated by the Montreal classification, gastroesophageal reflux disease (GERD) is much more than heartburn and patients constitute a heterogeneous group. Understanding if links exist between patients' characteristics and GERD symptoms, and classify subjects based on symptom-profile could help to better understand, diagnose, and treat GERD. The aim of this study was to identify distinct classes of GERD patients according to symptom profiles, using a specific statistical tool: Latent class analysis. An observational single-visit study was conducted in 5 European countries in 7700 adults with typical symptoms. A latent class analysis was performed to identify "latent classes" and was applied to 12 indicator symptoms. On 7434 subjects with non-missing indicators, latent class analysis yielded 5 latent classes. Class 1 grouped the highest severity of typical GERD symptoms during day and night, more digestive and non-digestive GERD symptoms, and bad sleep quality. Class 3 represented less frequent and less severe digestive and non-digestive GERD symptoms, and better sleep quality than in class 1. In class 2, only typical GERD symptoms at night occurred. Classes 4 and 5 represented daytime and nighttime regurgitation. In class 4, heartburn was also identified and more atypical digestive symptoms. Multinomial logistic regression showed that country, age, sex, smoking, alcohol use, low-fat diet, waist circumference, recent weight gain (>5 kg), elevated triglycerides, metabolic syndrome, and medical GERD treatment had a significant effect on latent classes. Latent class analysis classified GERD patients based on symptom profiles which related to patients' characteristics. Although further studies considering these proposed classes have to be conducted to determine the reproducibility of this classification, this new tool might contribute in better management and follow-up of patients with GERD.

  10. Self-regulation and alcohol use involvement: a latent class analysis.

    Science.gov (United States)

    Kuvaas, Nicholas J; Dvorak, Robert D; Pearson, Matthew R; Lamis, Dorian A; Sargent, Emily M

    2014-01-01

    Although alcohol use can be problematic, research suggests considerable heterogeneity in problems across various drinking classes; particularly among the heaviest drinking groups. Differences in self-regulation may differentiate drinking classes. The current study evaluated differences in emotional and behavioral self-regulation across four empirically derived drinking classes. Participants (n=1895 college students) completed online measures of demographics, alcohol involvement, and self-regulation. Using latent class analysis (LCA), four drinking classes were empirically derived. Moderate drinkers were the largest class (38.1%) followed by light drinkers (37.4%), heavy drinkers (17.8%), and problem drinkers (6.8%). Each class was predicted by self-regulation indicators in the LCA. With the exception of urgency, behavioral self-regulation distinguished primarily between light drinkers and the other three classes. Emotional self-regulation and urgency were not associated with use, but did distinguish among the most problematic class. Specifically, emotional instability and urgency were higher in the problem use class than all other classes. Overall, the findings suggest important differences in behavioral and emotional self-regulation across drinking classes that differentially contribute to use and consequences. Further, the results highlight the importance of examining homogenous subpopulations of drinkers that may differ on indices other than consumption. © 2013.

  11. Joint analysis of time-to-event and multiple binary indicators of latent classes

    DEFF Research Database (Denmark)

    Larsen, Klaus

    2004-01-01

    on the profile likelihood, treating the nonparametric baseline hazard as a nuisance parameter. A sampling-based method for model checking is proposed. It allows for graphical investigation of the assumption of proportional hazards across latent classes. It may also be used for checking other model assumptions......Multiple categorical variables are commonly used in medical and epidemiological research to measure specific aspects of human health and functioning. To analyze such data, models have been developed considering these categorical variables as imperfect indicators of an individual's "true" status......, such as no additional effect of the observed indicators given latent class. The usefulness of the model framework and the proposed techniques are illustrated in an analysis of data from the Women's Health and Aging Study concerning the effect of severe mobility disability on time-to-death for elderly women....

  12. Two-Stage maximum likelihood estimation in the misspecified restricted latent class model.

    Science.gov (United States)

    Wang, Shiyu

    2017-10-28

    The maximum likelihood classification rule is a standard method to classify examinee attribute profiles in cognitive diagnosis models (CDMs). Its asymptotic behaviour is well understood when the model is assumed to be correct, but has not been explored in the case of misspecified latent class models. This paper investigates the asymptotic behaviour of a two-stage maximum likelihood classifier under a misspecified CDM. The analysis is conducted in a general restricted latent class model framework addressing all types of CDMs. Sufficient conditions are proposed under which a consistent classification can be obtained by using a misspecified model. Discussions are also provided on the inconsistency of classification under certain model misspecification scenarios. Simulation studies and a real data application are conducted to illustrate these results. Our findings can provide some guidelines as to when a misspecified simple model or a general model can be used to provide a good classification result. © 2017 The British Psychological Society.

  13. Patterns of adolescent sexual behavior predicting young adult sexually transmitted infections: a latent class analysis approach.

    Science.gov (United States)

    Vasilenko, Sara A; Kugler, Kari C; Butera, Nicole M; Lanza, Stephanie T

    2015-04-01

    Adolescent sexual behavior is multidimensional, yet most studies of the topic use variable-oriented methods that reduce behaviors to a single dimension. In this study, we used a person-oriented approach to model adolescent sexual behavior comprehensively, using data from the National Longitudinal Study of Adolescent Health. We identified five latent classes of adolescent sexual behavior: Abstinent (39%), Oral Sex (10%), Low-Risk (25%), Multi-Partner Normative (12%), and Multi-Partner Early (13%). Membership in riskier classes of sexual behavior was predicted by substance use and depressive symptoms. Class membership was also associated with young adult STI outcomes although these associations differed by gender. Male adolescents' STI rates increased with membership in classes with more risky behaviors whereas females' rates were consistent among all sexually active classes. These findings demonstrate the advantages of examining adolescent sexuality in a way that emphasizes its complexity.

  14. Common Mental Disorders among Occupational Groups: Contributions of the Latent Class Model

    Directory of Open Access Journals (Sweden)

    Kionna Oliveira Bernardes Santos

    2016-01-01

    Full Text Available Background. The Self-Reporting Questionnaire (SRQ-20 is widely used for evaluating common mental disorders. However, few studies have evaluated the SRQ-20 measurements performance in occupational groups. This study aimed to describe manifestation patterns of common mental disorders symptoms among workers populations, by using latent class analysis. Methods. Data derived from 9,959 Brazilian workers, obtained from four cross-sectional studies that used similar methodology, among groups of informal workers, teachers, healthcare workers, and urban workers. Common mental disorders were measured by using SRQ-20. Latent class analysis was performed on each database separately. Results. Three classes of symptoms were confirmed in the occupational categories investigated. In all studies, class I met better criteria for suspicion of common mental disorders. Class II discriminated workers with intermediate probability of answers to the items belonging to anxiety, sadness, and energy decrease that configure common mental disorders. Class III was composed of subgroups of workers with low probability to respond positively to questions for screening common mental disorders. Conclusions. Three patterns of symptoms of common mental disorders were identified in the occupational groups investigated, ranging from distinctive features to low probabilities of occurrence. The SRQ-20 measurements showed stability in capturing nonpsychotic symptoms.

  15. Ordering patterns following the implementation of a healthier children's restaurant menu: A latent class analysis.

    Science.gov (United States)

    Mueller, Megan P; Anzman-Frasca, Stephanie; Blakeley, Caitlin E; Folta, Sara C; Wilde, Parke; Economos, Christina D

    2017-01-01

    Identify ordering patterns following implementation of a healthier children's menu. A healthier children's menu was introduced in 2012 at a regional restaurant chain, featuring more meals meeting Kids LiveWell (KLW) nutrition standards, KLW side dishes bundled with meals, and the removal of French fries and soda. Latent class analysis was conducted on child meal orders placed after menu implementation (n = 8,611). The average calorie content and proportion of orders meeting calorie recommendations (≤600 kcal) in each class were evaluated. The best-fitting model contained six latent classes representing different ordering patterns: "healthy meals" (27.0%), "healthy meals, add-ons" (9.6%), "unhealthy sides" (9.2%), "healthy substitutions" (30.9%), "healthy substitutions, add-ons" (1.0%), and "unhealthy substitutions" (22.4%). Classes denoted as "healthy" were likely to contain meals with KLW items. Orders in the healthy meals class contained fewer calories than orders in all other classes (P menu were common and more likely to meet calorie recommendations. Ordering patterns inconsistent with menu changes also emerged and can inform intervention efforts to reach patrons who may reject or compensate for healthier items. © 2016 The Obesity Society.

  16. A new insight into masticatory function and its determinants: a latent class analysis.

    Science.gov (United States)

    Feizi, Awat; Keshteli, Ammar Hassanzadeh; Khazaei, Saber; Adibi, Peyman

    2016-02-01

    Masticatory function is an important factor for preservation of general health. Epidemiologic data on masticatory function and its determinants among Iranian population are sparse, and no study has evaluated masticatory function using latent class analysis (LCA). This study was conducted to investigate the masticatory function and its determinants among a large sample of Iranian adults. In a cross-sectional study among 8691 adults, masticatory function was investigated using a validated questionnaire. LCA and latent class regression (LCR) were applied to identify classes of masticatory function and its potential determinants, respectively. In addition, multigroup LCA was conducted based on gender and age categories. In total, 11.24% and 24.87% of participants had poor and moderate masticatory function, respectively. Males (class size: 14.33%) were more likely to have poor masticatory function than females (class size: 2.35%) (P masticatory function. Nonsmokers had a lower chance of being in poor masticatory function class than heavy smokers (OR: 0.21, 95% CI: 0.11-0.38, P masticatory function is high among Iranian adults. Aging, male gender, low levels of physical activity, and smoking were found to be associated with poor masticatory function. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  17. Behavioral and Mental Health Correlates of Youth Stalking Victimization: A Latent Class Approach.

    Science.gov (United States)

    Reidy, Dennis E; Smith-Darden, Joanne P; Kernsmith, Poco D

    2016-12-01

    Although recognized as a public health problem, little attention has been paid to the problem of stalking among youth. Latent profile analysis was used to identify latent groups of adolescent stalking victims and their behavioral and mental health correlates. A cross-sectional sample of 1,236 youths were randomly selected from 13 schools stratified by community risk level (i.e., low, moderate, and high risk) and gender. Students completed surveys assessing behavioral indicators of stalking victimization, as well as substance use, sexual behavior, dating violence, and psychiatric symptoms. Data were collected in 2013 and data analyses were performed in 2015. Analysis indicated the presence of a non-victim class, a minimal exposure class, and a victim class for boys and girls alike. Approximately 14% of girls and 13% of boys were in the stalking victim class. Adolescents in the victim class reported more symptoms of post-traumatic stress, mood disorder, and hopelessness, as well as more instances of alcohol use, binge drinking, and physical dating violence victimization. Girls in the victim class also reported engaging in sexting behaviors and oral sex with significantly more partners than their non-victim peers. These findings provide valuable knowledge of the prevalence and pertinent health correlates of stalking victimization in adolescence. The data suggest a substantial proportion of adolescents are victims of stalking and are likewise at risk for a number of deleterious health outcomes. As such, this population merits further attention by prevention researchers and practitioners. Published by Elsevier Inc.

  18. A Personality-Based Latent Class Analysis of Emerging Adult Gamblers.

    Science.gov (United States)

    Tackett, Jennifer L; Rodriguez, Lindsey M; Rinker, Dipali V; Neighbors, Clayton

    2015-12-01

    Increases in access to gambling venues have been accompanied by increased gambling behavior among young adults. The present research examined associations among Five Factor Model personality traits, motives for gambling, and gambling behavior and problems using latent class analysis. College students (N = 220) completed online measures of personality and gambling behavior as part of a larger intervention trial. Agreeableness and conscientiousness were negatively associated with indicators of gambling behavior. Low agreeableness and high neuroticism were associated with gambling-specific motives, particularly for less frequently endorsed motives. Personality-based latent class analyses of emerging adult gamblers revealed support for three distinct groups reflecting a resilient personality group, a normative personality group, and a vulnerable personality group, which were further differentiated by gambling behaviors and gambling-specific motives. Associations between personality traits and gambling-specific motives highlight potential heterogeneity among college students who gamble. Together, findings suggest that the correlational and latent class-based analyses, as well as the personality and motivation analyses, present complementary information with respect to the attributes of college student gamblers. Implications and future research directions are discussed.

  19. The search for healthy schools: A multilevel latent class analysis of schools and their students

    Directory of Open Access Journals (Sweden)

    Kenneth R. Allison

    2016-12-01

    Full Text Available The objective of this study was to establish and investigate a taxonomy of school health among high school students in Ontario, Canada. Data analyzed were based on 3358 9th–12th graders attending 103 high schools who participated in the 2011 Ontario Student Drug Use and Health Survey. Based on 10 health-related indicators, multilevel latent class analysis was used to extract 4 student-level latent classes and 3 school-level latent classes. Unhealthy schools (19% of schools had the lowest proportion of healthy students (39% and the highest proportion of substance-using (31% and unhealthy (18% students. Healthy schools (66% contained the highest proportion of healthy students (56% and smaller proportions of substance-using (22% and unhealthy students (8%. Distressed schools (15% were similar to healthy schools in terms of the proportions of healthy and unhealthy students. Distressed schools, however, were characterized by having the largest proportion of distressed students (35% and the lowest proportion of substance-using students (4%. Meaningful categories of schools with respect to healthy environments can be identified and these categories could be used for focusing interventions and evaluating school health programs.

  20. 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

  1. Class Evolution Tree: a graphical tool to support decisions on the number of classes in exploratory categorical latent variable modeling for rehabilitation research.

    Science.gov (United States)

    Kriston, Levente; Melchior, Hanne; Hergert, Anika; Bergelt, Corinna; Watzke, Birgit; Schulz, Holger; von Wolff, Alessa

    2011-06-01

    The aim of our study was to develop a graphical tool that can be used in addition to standard statistical criteria to support decisions on the number of classes in explorative categorical latent variable modeling for rehabilitation research. Data from two rehabilitation research projects were used. In the first study, a latent profile analysis was carried out in patients with cancer receiving an inpatient rehabilitation program to identify prototypical combinations of treatment elements. In the second study, growth mixture modeling was used to identify latent trajectory classes based on weekly symptom severity measurements during inpatient treatment of patients with mental disorders. A graphical tool, the Class Evolution Tree, was developed, and its central components were described. The Class Evolution Tree can be used in addition to statistical criteria to systematically address the issue of number of classes in explorative categorical latent variable modeling.

  2. Patterns of Relationship and Sexual Behaviors in Mexican Adolescents and Associations with Well-being: A Latent Class Approach

    OpenAIRE

    Espinosa-Hern?ndez, Graciela; Vasilenko, Sara A.

    2015-01-01

    To broaden our understanding of romance and sexuality during adolescence in Latin American countries, we used a person-oriented approach (latent class analysis) to examine classes marked by different patterns of romantic and sexual behaviors in Mexican adolescents. We found 5 classes: Inactive, (8.53%), Early stage (37.8%), Waiting class (27.5%), Physical (8.4%) and Committed (17.9%); but no group dating class. We also explored how these classes were associated with adolescents? mental health...

  3. 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…

  4. Indentifying Latent Classes and Testing Their Determinants in Early Adolescents' Use of Computers and Internet for Learning

    Science.gov (United States)

    Heo, Gyun

    2013-01-01

    The purpose of the present study was to identify latent classes resting on early adolescents' change trajectory patterns in using computers and the Internet for learning and to test the effects of gender, self-control, self-esteem, and game use in South Korea. Latent growth mixture modeling (LGMM) was used to identify subpopulations in the Korea…

  5. 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

  6. Class Evolution Tree: A Graphical Tool to Support Decisions on the Number of Classes in Exploratory Categorical Latent Variable Modeling for Rehabilitation Research

    Science.gov (United States)

    Kriston, Levente; Melchior, Hanne; Hergert, Anika; Bergelt, Corinna; Watzke, Birgit; Schulz, Holger; von Wolff, Alessa

    2011-01-01

    The aim of our study was to develop a graphical tool that can be used in addition to standard statistical criteria to support decisions on the number of classes in explorative categorical latent variable modeling for rehabilitation research. Data from two rehabilitation research projects were used. In the first study, a latent profile analysis was…

  7. Adolescent Physical Activity and the Built Environment: A Latent Class Analysis Approach

    Science.gov (United States)

    McDonald, Kelsey; Hearst, Mary; Farbakhsh, Kian; Patnode, Carrie; Forsyth, Ann; Sirard, John; Lytle, Leslie

    2011-01-01

    This study used latent class analysis to classify adolescent home neighborhoods (n=344) according to built environment characteristics, and tested how adolescent physical activity, sedentary behavior, and screen time differ by neighborhood type/class. Four distinct neighborhood classes emerged: 1) low-density retail/transit, low walkability index (WI), further from recreation; 2) high-density retail/transit, high WI, closer to recreation; 3) moderate-high-density retail/transit, moderate WI, further from recreation; and 4) moderate-low-density retail/transit, low WI, closer to recreation. We found no difference in adolescent activity by neighborhood class. These results highlight the difficulty of disentangling the potential effects of the built environment on adolescent physical activity. PMID:21975286

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

    National Research Council Canada - National Science Library

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

    2017-01-01

    ... to encourage and support students' science aspirations. This study uses latent class analysis to describe underlying differences in ability beliefs, task values and links these science-self-perceptions to interest in science...

  9. Latent Class Analysis of DSM-5 Alcohol Use Disorder Criteria Among Heavy-Drinking College Students.

    Science.gov (United States)

    Rinker, Dipali Venkataraman; Neighbors, Clayton

    2015-10-01

    The DSM-5 has created significant changes in the definition of alcohol use disorders (AUDs). Limited work has considered the impact of these changes in specific populations, such as heavy-drinking college students. Latent class analysis (LCA) is a person-centered approach that divides a population into mutually exclusive and exhaustive latent classes, based on observable indicator variables. The present research was designed to examine whether there were distinct classes of heavy-drinking college students who met DSM-5 criteria for an AUD and whether gender, perceived social norms, use of protective behavioral strategies (PBS), drinking refusal self-efficacy (DRSE), self-perceptions of drinking identity, psychological distress, and membership in a fraternity/sorority would be associated with class membership. Three-hundred and ninety-four college students who met DSM-5 criteria for an AUD were recruited from three different universities. Two distinct classes emerged: Less Severe (86%), the majority of whom endorsed both drinking more than intended and tolerance, as well as met criteria for a mild AUD; and More Severe (14%), the majority of whom endorsed at least half of the DSM-5 AUD criteria and met criteria for a severe AUD. Relative to the Less Severe class, membership in the More Severe class was negatively associated with DRSE and positively associated with self-identification as a drinker. There is a distinct class of heavy-drinking college students with a more severe AUD and for whom intervention content needs to be more focused and tailored. Clinical implications are discussed. Copyright © 2015 Elsevier Inc. All rights reserved.

  10. Polydrug use among nightclub patrons in a megacity: A latent class analysis.

    Science.gov (United States)

    Sañudo, Adriana; Andreoni, Solange; Sanchez, Zila M

    2015-12-01

    Nightclubs are places with a high prevalence of binge drinking and illicit drug use. The aim of this study was to evaluate the characteristics of polydrug use, including licit and illicit drugs, among 2420 nightclub patrons in a probabilistic sample in the city of São Paulo, Brazil, The study was conducted in 2013. A latent class analysis (LCA) of polydrug use, accounting for binge drinking (BD) and other drug use (cannabis, cocaine, ecstasy, tobacco, ketamine, inhalants and hallucinogens) in the past 12 months was performed using Mplus. Multinomial logistic regression was used to evaluate latent class associations with sociodemographic characteristics and variables that characterise type of nightclub and frequency of attendance. A three-class LCA model best described polydrug use patterns. We found a "no polydrug use" class (55%), a "moderate polydrug use" class (35%) and a "high level polydrug use" class (10%). Compared to "no polydrug use", patrons in the two "polydrug use classes" were more likely to be men, young adults (<34 years), have attended nightclubs three times or more per month and have attended hip-hop and rock music nightclubs. Patrons in the "high level polydrug use" class were more likely to attend electronic (aOR=9.9, 95% CI: 5.4-8.1, p<0.001) and hip-hop music nightclubs (aOR=10.1, 95% CI: 6.2-16.5, p<0.001). LCA is a useful method to identify groups of polydrug users among nightclub patrons. The three groups identified represented the diversity of patrons of São Paulo nightclubs. Frequency of attendance and the nightclub's musical style were highly correlated with polydrug use. Copyright © 2015 Elsevier B.V. All rights reserved.

  11. Subgrouping High School Students for Substance Abuse-Related Behaviors: A Latent Class Analysis.

    Science.gov (United States)

    Khayyati, Fariba; Mohammadpoorasl, Asghar; Allahverdipour, Hamid; AsghariJafarabadi, Mohammad; Kouzekanani, Kamiar

    2017-07-01

    The aim of the current study was to characterize the prevalence of latent groups in terms of smoking, hookah, and alcohol in a sample of Iranian high school students. In this cross-sectional study, 4,422 high school students were assessed in East Azerbaijan Province, Iran. Latent class analysis was applied to determine the subgroups and prevalence of each class using the procLCA in SAS 9.2 software. The prevalence of hookah smoking was the highest among the other substances and had the greatest abuse among males than females. Nearly 86%, 9.5%, and 4.6% of the participants were low risk, tobacco experimenter, and high risk, respectively. The odds ratio indices of membership in each class, compared with the first class, associated with the independent variables. A fair number of students, males in particular, were identified as high risk-takers. Considering the simultaneous incidence of multiple high-risk behaviors, interventions must cover multiple aspects of the issue at the same time.

  12. 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.

  13. Prolonged grief and posttraumatic stress in bereaved children: A latent class analysis.

    Science.gov (United States)

    Boelen, Paul A; Spuij, Mariken; Reijntjes, Albert H A

    2017-12-01

    Few studies have yet examined subgroups among children (aged 8-18) confronted with the death of a close loved one, characterized by different profiles of symptoms of prolonged grief disorder (PGD) and symptoms of bereavement-related posttraumatic stress disorder (PTSD). This study sought to identify such subgroups and socio-demographic and loss-related variables associated with subgroup membership. We used data from 332 children, most of whom (> 80%) were confronted with the death of a parent, mostly (> 50%) due to illness. Latent class analysis revealed three classes of participants: a resilient class (38.6%), a predominantly PGD class (35.2%), and a combined PGD/PTSD class (26.2%). Class membership was associated with self-rated levels of depression and functional impairment, and parent-rated behavioural problems. No significant between-class differences on demographics or loss-related variables were found. The current findings of distinct classes of PGD, and PGD plus PTSD attest to the construct validity of PGD as a distinct disorder, and can inform theory building and the development of diagnostic instruments relevant to children with pervasive distress following loss. Copyright © 2017 Elsevier B.V. All rights reserved.

  14. 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.

  15. Risk factor profiles among intravenous drug using young adults: a latent class analysis (LCA) approach.

    Science.gov (United States)

    James, Sigrid; McField, Edward S; Montgomery, Susanne B

    2013-03-01

    Using data from a cross-sectional study that examined health risk behaviors among urban intravenous drug-using (IDU) adolescents and young adults, this study investigated risk profiles among a high-risk sample (n=274). Risk profiles were empirically derived through latent class analysis based on indicators of engagement in health-risking behaviors, experience of abuse and violence as well as individual and family risk factors. The best fitting model was a 3-class model. Class 1 (n=95) captured participants with the lowest risk across all indicators. Compared to Class 1, Class 2 (n=128) and Class 3 (n=51) had elevated rates of engagement in health-risking behaviors as well as individual and family risk factors; however, Class 3 had the highest rate of engagement in sexual risk behavior, and backgrounds of substantial abuse and violence as well as familial psychopathology. Class 2 was the group most socioeconomically disadvantaged, with the highest percentage of participants coming from poor backgrounds, spending the longest time homeless and working the fewest months. Identifying subgroups of IDU has the potential to guide the development of more targeted and effective strategies for prevention and treatment of this high-risk population. Copyright © 2012 Elsevier Ltd. All rights reserved.

  16. 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.

  17. 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

  18. 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.

  19. 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

  20. Clustering and combining pattern of metabolic syndrome components among Iranian population with latent class analysis.

    Science.gov (United States)

    Abbasi-Ghahramanloo, Abbas; Soltani, Sepideh; Gholami, Ali; Erfani, Mohammadreza; Yosaee, Somayeh

    2016-01-01

    Background: Metabolic syndrome (MetS), a combination of coronary heart disease and diabetes mellitus risk factor, refer to one of the most challenging public health issues in worldwide. The aim of this study was to identify the subgroups of participants in a study on the basis of MetS components. Methods: The cross-sectional study took place in the districts related to Tehran University of Medical Sciences. The randomly selected sample consists of 415 subjects. All participants provided written informed consent. Latent class analysis was performed to achieve the study's objectives. Analyses were conducted by using proc LCA in SAS 9.2 software. Results: Except systolic and diastolic blood pressure, the prevalence of all MetS components is common in female than male. Four latent classes were identified: (a) non MetS, (b) low risk, (c) high risk, and (d) MetS. Notably, 24.2% and 1.3% of the subjects were in the high risk and MetS classes respectively. Conclusion: Most of the study participants were identified as high risk and MetS. Design and implementation of preventive interventions for this segment of the population are necessary.

  1. Patterns of aggressive behavior and peer victimization from childhood to early adolescence: a latent class analysis.

    Science.gov (United States)

    Williford, Anne Powell; Brisson, Daniel; Bender, Kimberly A; Jenson, Jeffrey M; Forrest-Bank, Shandra

    2011-06-01

    The developmental period characterized by the transition from childhood and elementary school to early adolescence and middle school has been associated with increases in aggressive behavior and peer victimization. Few longitudinal studies, however, have examined the stability of aggression and victimization during this critical transition. This study uses latent class analysis (LCA) to examine patterns of aggressive behavior and victimization during the transition to middle school among urban, public school students (N = 458; Girls = 53%; Latino/a = 53%; M age at t1 = 10.2 years). Independent LCA models were conducted using self-reported data assessing subjects' involvement in aggressive conduct and victimization during the spring semesters of grades four, five, and six. Elementary school students in the fourth grade initially belonged to one of four groups identified as aggressor, victim, aggressor-victim, and uninvolved latent classes. Contrary to prior research, membership in these classes changed significantly by the time students completed their first year of middle school with most youth participating in episodes of aggression and victimization during the transition. Six common paths that describe patterns of aggressive behavior and victimization from the last two years of elementary school to the first year of middle school were found. Findings are discussed in the context of social dominance theory and prior research that has found greater stability in aggression and victimization among early adolescents.

  2. Treatment Strategy Profiles in Substance Use Disorder Treatment Programs: A Latent Class Analysis

    Science.gov (United States)

    Aletraris, Lydia; Paino, Maria; Roman, Paul M.

    2015-01-01

    Background Modern treatment options for substance use disorder are diverse. While studies have analyzed the adoption of individual evidence-based practices in treatment centers, little is known about the specific make-up of treatment strategy profiles in treatment centers throughout the United States. The current study used latent class analysis to profile underlying treatment strategies and to evaluate philosophical and structural supports associated with each profile. Methods Utilizing three aggregated and secondary datasets of nationally representative samples of substance use disorder treatment centers (N=775), we employed latent class analysis to determine treatment strategy profiles. Using multinomial logistic regression, we then examined organizational characteristics associated with each profile. Results We found three distinct treatment strategy profiles: Centers that primarily relied on Motivational Interviewing and Motivational Enhancement Therapy, centers that utilized psychosocial and alternative therapies, and centers that employed comprehensive treatments including pharmacotherapy. The multinomial logistic regression revealed that philosophical and structural center characteristics were associated with membership in the comprehensive class. Centers with philosophical orientations conducive to holistic care and pharmacotherapy-acceptance, resource-rich infrastructures, and an entrepreneurial reliance on insured clients were more likely to offer diverse interventions. All associations were significant at the .05 level. Principle Conclusion The findings from this study help us understand the general strategies of treatment centers. From a practical perspective, practitioners and clients should be aware of the variation in treatment center practices where they may offer or receive treatment. PMID:26105707

  3. Inferring the structure of latent class models using a genetic algorithm.

    Science.gov (United States)

    van der Maas, Han L J; Raijmakers, Maartje E J; Visser, Ingmar

    2005-05-01

    Present optimization techniques in latent class analysis apply the expectation maximization algorithm or the Newton-Raphson algorithm for optimizing the parameter values of a prespecified model. These techniques can be used to find maximum likelihood estimates of the parameters, given the specified structure of the model, which is defined by the number of classes and, possibly, fixation and equality constraints. The model structure is usually chosen on theoretical grounds. A large variety of structurally different latent class models can be compared using goodness-of-fit indices of the chi-square family, Akaike's information criterion, the Bayesian information criterion, and various other statistics. However, finding the optimal structure for a given goodness-of-fit index often requires a lengthy search in which all kinds of model structures are tested. Moreover, solutions may depend on the choice of initial values for the parameters. This article presents a new method by which one can simultaneously infer the model structure from the data and optimize the parameter values. The method consists of a genetic algorithm in which any goodness-of-fit index can be used as a fitness criterion. In a number of test cases in which data sets from the literature were used, it is shown that this method provides models that fit equally well as or better than the models suggested in the original articles.

  4. 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.

  5. Are Informing Knowledge and Supportive Attitude Enough for Tobacco Control? A Latent Class Analysis of Cigarette Smoking Patterns among Medical Teachers in China

    National Research Council Canada - National Science Library

    Niu, Lu; Luo, Dan; Silenzio, Vincent M B; Xiao, Shuiyuan; Tian, Yongquan

    2015-01-01

    .... 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...

  6. 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

    2016-01-01

    Objective To explore patterns of physical, emotional and sexual violence against Ugandan children. Design Latent class and multinomial logistic regression analysis of cross-sectional data. Setting Luwero District, Uganda. Participants In all, 3706 primary 5, 6 and 7 students attending 42 primary schools. Main outcome and measure 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. Results 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. Conclusions 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

  7. Latent growth classes of alcohol-related blackouts over the first 2 years of college.

    Science.gov (United States)

    Merrill, Jennifer E; Treloar, Hayley; Fernandez, Anne C; Monnig, Mollie A; Jackson, Kristina M; Barnett, Nancy P

    2016-12-01

    Alcohol-related blackouts are common among college student drinkers. The present study extends prior work by examining latent growth classes of blackouts and several predictors of class membership. Participants (N = 709 college drinkers) completed a baseline survey at college entry and biweekly online assessments throughout freshman and sophomore years. Results revealed 5 latent growth class trajectories, reflecting varying experiences of blackouts at the beginning of college and differential change in blackouts over time. The largest class represented a relatively low-risk group (low decrease; 47.3%) characterized by endorsement of no or very low likelihood of blackouts, and decreasing likelihood of blackouts over time. Another decreasing risk group (high decrease; 11.1%) initially reported a high proportion of blackouts and had the steepest decrease in blackout risk over time. A small percentage showed consistently high likelihood of blackouts over time (high stable; 4.1%). The remaining 2 groups were distinguished by relatively moderate (moderate stable; 14.9%) and lower (low stable; 22.6%) likelihood of blackouts, which remained stable over time. Comparisons between classes revealed that students with greater perceived peer drinking, perceived peer approval of drinking, and enhancement motives upon entry to college tended to be in higher risk groups with consistent experiences of blackouts over time, whereas blackout likelihood decreased over time for students with greater conformity motives. Findings suggest that precollege preventive interventions may be strengthened by considering not only factors related to current risk for blackouts and other alcohol-related consequences, but also those factors related to persistence of these behaviors over time. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  8. Examining Patterns of Exposure to Family Violence in Preschool Children: A Latent Class Approach.

    Science.gov (United States)

    Grasso, Damion J; Petitclerc, Amélie; Henry, David B; McCarthy, Kimberly J; Wakschlag, Lauren S; Briggs-Gowan, Margaret J

    2016-12-01

    Young children can experience violence directly or indirectly in the home, with some children exposed to multiple forms of violence. These polyvictims often experience violence that is severe, chronic, and multifaceted. The current study used latent class analysis to identify and examine the pattern of profiles of exposure to family violence (i.e., violence directed towards the child and between caregivers) among a sample of 474 children ages 3-6 year who were drawn from the Multidimensional Assessment of Preschoolers Study (Wakschlag et al., 2014). The data yielded 3 classes: a polyvictimized class (n = 72; 15.2%) with high probability of exposure to all forms of violence, a harsh parenting class (n = 235; 49.5%), distinguished mainly by child-directed physical discipline in the absence of more severe forms of violence, and a low-exposure class (n = 167; 35.2%). Classes were differentiated by contextual factors, maternal characteristics, and mother-reported and observational indicators of parenting and child functioning with most effect sizes between medium and large. These findings add to emerging evidence linking polyvictimization to impaired caregiving and adverse psychological outcomes for children and offer important insight for prevention and intervention for this vulnerable population. Copyright © 2016 International Society for Traumatic Stress Studies.

  9. The Four U's: Latent Classes of Hookup Motivations Among College Students.

    Science.gov (United States)

    Uecker, Jeremy E; Pearce, Lisa D; Andercheck, Brita

    2015-06-01

    College students' "hookups" have been the subject of a great deal of research in recent years. Motivations for hooking up have been linked to differences in well-being after the hookup, but studies detailing college students' motivations for engaging in hookups focus on single motivations. Using data from the 2010 Duke Hookup Survey, we consider how motivations for hooking up cluster to produce different classes, or profiles, of students who hook up, and how these classes are related to hookup regret. Four distinct classes of motivations emerged from our latent class analysis: Utilitarians (50%), Uninhibiteds (27%), Uninspireds (19%), and Unreflectives (4%). We find a number of differences in hookup motivation classes across social characteristics, including gender, year in school, race-ethnicity, self-esteem, and attitudes about sexual behavior outside committed relationships. Additionally, Uninspireds regret hookups more frequently than members of the other classes, and Uninhibiteds report regret less frequently than Utilitarians and Uninspireds. These findings reveal the complexity of motivations for hooking up and the link between motivations and regret.

  10. Exploring the Latent Structure of the Luria Model for the KABC-II at School Age: Further Insights from Confirmatory Factor Analysis

    Science.gov (United States)

    McGill, Ryan J.

    2017-01-01

    The present study examined the factor structure of the Luria interpretive model for the Kaufman Assessment Battery for Children-Second Edition (KABC-II) with normative sample participants aged 7-18 (N = 2,025) using confirmatory factor analysis with maximum-likelihood estimation. For the eight subtest Luria configuration, an alternative…

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

    NARCIS (Netherlands)

    Nouwens, P.J.G.; Lucas, R.; Smulders, N.B.M.; Embregts, P.J.C.M.; van Nieuwenhuizen, Ch.

    2017-01-01

    Background 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

  12. A joint latent class model for classifying severely hemorrhaging trauma patients.

    Science.gov (United States)

    Rahbar, Mohammad H; Ning, Jing; Choi, Sangbum; Piao, Jin; Hong, Chuan; Huang, Hanwen; Del Junco, Deborah J; Fox, Erin E; Rahbar, Elaheh; Holcomb, John B

    2015-10-24

    In trauma research, "massive transfusion" (MT), historically defined as receiving ≥10 units of red blood cells (RBCs) within 24 h of admission, has been routinely used as a "gold standard" for quantifying bleeding severity. Due to early in-hospital mortality, however, MT is subject to survivor bias and thus a poorly defined criterion to classify bleeding trauma patients. Using the data from a retrospective trauma transfusion study, we applied a latent-class (LC) mixture model to identify severely hemorrhaging (SH) patients. Based on the joint distribution of cumulative units of RBCs and binary survival outcome at 24 h of admission, we applied an expectation-maximization (EM) algorithm to obtain model parameters. Estimated posterior probabilities were used for patients' classification and compared with the MT rule. To evaluate predictive performance of the LC-based classification, we examined the role of six clinical variables as predictors using two separate logistic regression models. Out of 471 trauma patients, 211 (45 %) were MT, while our latent SH classifier identified only 127 (27 %) of patients as SH. The agreement between the two classification methods was 73 %. A non-ignorable portion of patients (17 out of 68, 25 %) who died within 24 h were not classified as MT but the SH group included 62 patients (91 %) who died during the same period. Our comparison of the predictive models based on MT and SH revealed significant differences between the coefficients of potential predictors of patients who may be in need of activation of the massive transfusion protocol. The traditional MT classification does not adequately reflect transfusion practices and outcomes during the trauma reception and initial resuscitation phase. Although we have demonstrated that joint latent class modeling could be used to correct for potential bias caused by misclassification of severely bleeding patients, improvement in this approach could be made in the presence of time to event

  13. ADVERSE CHILDHOOD EXPERIENCES AMONG YOUTH AGING OUT OF FOSTER CARE: A LATENT CLASS ANALYSIS.

    Science.gov (United States)

    Rebbe, Rebecca; Nurius, Paula S; Ahrens, Kym R; Courtney, Mark E

    2017-03-01

    Research has demonstrated that youth who age out, or emancipate, from foster care face deleterious outcomes across a variety of domains in early adulthood. This article builds on this knowledge base by investigating the role of adverse childhood experience accumulation and composition on these outcomes. A latent class analysis was performed to identify three subgroups: Complex Adversity, Environmental Adversity, and Lower Adversity. Differences are found amongst the classes in terms of young adult outcomes in terms of socio-economic outcomes, psychosocial problems, and criminal behaviors. The results indicate that not only does the accumulation of adversity matter, but so does the composition of the adversity. These results have implications for policymakers, the numerous service providers and systems that interact with foster youth, and for future research.

  14. 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.

  15. Profiles of Depression Help Seeking Among Black Americans: A Latent Class Approach.

    Science.gov (United States)

    Hays, Krystal; Gilreath, Tamika

    2017-08-01

    Although Black Americans have lower prevalence of depression compared to non-Hispanic Whites (10% vs. 17%), they are nearly twice as likely to have worse outcomes. One contributor to poor depression outcomes involves the ways in which Black Americans seek help for depression. However, little is known about depression help-seeking behavior, and the use of multiple sources of help, among Black Americans. This study used latent class analysis to identify unique constellations of depression help seeking, from multiple sources, among African American and Black Caribbeans. Results indicated four profiles of depression help seeking including Informal/Primary Care Utilizers (41.4%), Formal Mental Health Utilizers (40.6%), All Support Utilizers (9.8%), and Mixed Source Utilizers (8.2%). The constellation of each profile and demographic differences in class assignment are discussed. Results have implications for tailored depression interventions for Black Americans including community-based psychoeducation and cultural competence training for mental health providers.

  16. Clinical assessment of infection in nonhealing ulcers analyzed by latent class analysis.

    Science.gov (United States)

    Lorentzen, Henrik F; Gottrup, Finn

    2006-01-01

    The distinction between bacterial colonization and infection relies on clinical judgement. Determining sensitivity and specificity of this judgement are problematic as no gold standard exists. Six specialists in wound management independently assessed 120 nonhealing chronic wounds. Sixty-five (54.2%) patients had venous ulcer, 18 (15%) arterial ulcers, 15 (12.5%) ulcerative pyoderma gangraenosum, 12 (10%) neuropathic or pressure ulcers, six (5%) vasculitis ulcers, and four patients had ulcers caused by a primary or metastatic cancer disease. Unrestricted latent class analysis was used for determining sensitivity and specificity in the observer's assessment of hypergranulation, redness, and overall impression of infection. Interrater agreement among observers was determined by restricted latent class analysis. The observers used the diagnoses (redness, hypergranulation, and overall impression of infection with different frequencies (phypergranulation ranged from 3 to 82%, for redness from 34 to 91% and for overall impression of infection from 37 to 90%. None of the observers were interchangeable. These results indicate that clinical assessment of chronic wounds for the presence of infection are difficult tasks accompanied by great variability and low reliability.

  17. A probit latent class model with general correlation structures for evaluating accuracy of diagnostic tests.

    Science.gov (United States)

    Xu, Huiping; Craig, Bruce A

    2009-12-01

    Traditional latent class modeling has been widely applied to assess the accuracy of dichotomous diagnostic tests. These models, however, assume that the tests are independent conditional on the true disease status, which is rarely valid in practice. Alternative models using probit analysis have been proposed to incorporate dependence among tests, but these models consider restricted correlation structures. In this article, we propose a probit latent class model that allows a general correlation structure. When combined with some helpful diagnostics, this model provides a more flexible framework from which to evaluate the correlation structure and model fit. Our model encompasses several other PLC models but uses a parameter-expanded Monte Carlo EM algorithm to obtain the maximum-likelihood estimates. The parameter-expanded EM algorithm was designed to accelerate the convergence rate of the EM algorithm by expanding the complete-data model to include a larger set of parameters and it ensures a simple solution in fitting the PLC model. We demonstrate our estimation and model selection methods using a simulation study and two published medical studies.

  18. A Hybrid Latent Class Analysis Modeling Approach to Analyze Urban Expressway Crash Risk.

    Science.gov (United States)

    Yu, Rongjie; Wang, Xuesong; Abdel-Aty, Mohamed

    2017-04-01

    Crash risk analysis is rising as a hot research topic as it could reveal the relationships between traffic flow characteristics and crash occurrence risk, which is beneficial to understand crash mechanisms which would further refine the design of Active Traffic Management System (ATMS). However, the majority of the current crash risk analysis studies have ignored the impact of geometric characteristics on crash risk estimation while recent studies proved that crash occurrence risk was affected by the various alignment features. In this study, a hybrid Latent Class Analysis (LCA) modeling approach was proposed to account for the heterogeneous effects of geometric characteristics. Crashes were first segmented into homogenous subgroups, where the optimal number of latent classes was identified based on bootstrap likelihood ratio tests. Then, separate crash risk analysis models were developed using Bayesian random parameter logistic regression technique; data from Shanghai urban expressway system were employed to conduct the empirical study. Different crash risk contributing factors were unveiled by the hybrid LCA approach and better model goodness-of-fit was obtained while comparing to an overall total crash model. Finally, benefits of the proposed hybrid LCA approach were discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. Latent class models in diagnostic studies when there is no reference standard--a systematic review.

    Science.gov (United States)

    van Smeden, Maarten; Naaktgeboren, Christiana A; Reitsma, Johannes B; Moons, Karel G M; de Groot, Joris A H

    2014-02-15

    Latent class models (LCMs) combine the results of multiple diagnostic tests through a statistical model to obtain estimates of disease prevalence and diagnostic test accuracy in situations where there is no single, accurate reference standard. We performed a systematic review of the methodology and reporting of LCMs in diagnostic accuracy studies. This review shows that the use of LCMs in such studies increased sharply in the past decade, notably in the domain of infectious diseases (overall contribution: 59%). The 64 reviewed studies used a range of differently specified parametric latent variable models, applying Bayesian and frequentist methods. The critical assumption underlying the majority of LCM applications (61%) is that the test observations must be independent within 2 classes. Because violations of this assumption can lead to biased estimates of accuracy and prevalence, performing and reporting checks of whether assumptions are met is essential. Unfortunately, our review shows that 28% of the included studies failed to report any information that enables verification of model assumptions or performance. Because of the lack of information on model fit and adequate evidence "external" to the LCMs, it is often difficult for readers to judge the validity of LCM-based inferences and conclusions reached.

  20. 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

  1. A Person-Centered Examination of Adolescent Religiosity Using Latent Class Analysis.

    Science.gov (United States)

    Pearce, Lisa D; Foster, E Michael; Hardie, Jessica Halliday

    2013-03-01

    Empirical studies of religion's role in society, especially those focused on individuals and analyzing survey data, conceptualize and measure religiosity on a single measure or a summary index of multiple measures. Other concepts, such as "lived religion," "believing without belonging," or "fuzzy fidelity," emphasize what scholars have noted for decades: humans are rarely consistently low, medium, or high across dimensions of religiosity including institutional involvement, private practice, salience, or belief. A method with great promise for identifying population patterns in how individuals combine types and levels of belief, practice, and personal religious salience is latent class analysis. In this paper, we use data from the first wave of the National Study of Youth and Religion's telephone survey to discuss how to select indicators of religiosity in an informed manner, as well as the implications of the number and types of indicators used for model fit. We identify five latent classes of religiosity among adolescents in the United States and their socio-demographic correlates. Our findings highlight the value of a person-centered approach to understanding how religion is lived by American adolescents.

  2. Stages of health behavior change and mindsets: a latent class approach.

    Science.gov (United States)

    Richert, Jana; Schüz, Natalie; Schüz, Benjamin

    2013-03-01

    Stage theories of health behavior are popular and of high practical relevance. Tests of the validity of these theories provide limited evidence because of validity and reliability problems. This study provides a bottom-up approach to identify behavioral stages from examining differences in underlying mindsets. We examine the concurrent validity of a latent-class-based approach and a commonly used stage-algorithm based on self-reports about intentions and behavior in order to identify possible strengths and shortcomings of previously used approaches. Social-cognitive variables and individuals' stages were assessed in a sample of 2,219 internet users. Latent class analysis (LCA) was used to identify distinct groups with similar patterns of social-cognitive predictors. Convergent validity of the LCA solution and stage algorithms was tested by examining adjusted standardized residuals. The LCA identified four distinct profiles-not intending to change, intending to change (no action), intending to change with action, and maintaining. Convergent validity with a stage algorithm was low, in particular in the nonintending and maintaining stages. Stages as assigned by the stage-algorithm did not correspond well with the extracted mindsets: This indicates that commonly used stage-algorithms might not be effective in assigning individuals to stages that represent mindsets, undermining the possibility for stage-matched interventions. PsycINFO Database Record (c) 2013 APA, all rights reserved.

  3. 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.

  4. Drinking patterns of alcohol intoxicated adolescents in the emergency department: A latent class analysis.

    Science.gov (United States)

    Diestelkamp, Silke; Kriston, Levente; Arnaud, Nicolas; Wartberg, Lutz; Sack, Peter-Michael; Härter, Martin; Thomasius, Rainer

    2015-11-01

    The increasing number of children and adolescents in need of emergency medical treatment following acute alcohol intoxication has been a major public health concern in Europe in recent years. However, little is known about drinking habits and associated risks in this population. To our knowledge, this is the first study to examine drinking patterns and associated risks in adolescent emergency department patients following alcohol intoxication. The aim of this study is to establish a classification system for admitted adolescents Latent class analysis was used to identify subgroups of adolescents with distinct patterns of habitual drinking as defined by the quantity of consumed alcohol on a typical drinking occasion, frequency of binge drinking and drunkenness, alcohol-related problems, prior alcohol-related hospitalizations and alcohol-related risk behaviors. Subgroup characteristics were examined with regard to sociodemographics, other substance use and psychosocial problems using analysis of variance (ANOVA) and chi-square tests. A total of 316 adolescents aged 12-17 treated in 6 urban emergency departments in Germany were analyzed. Five classes of drinking patterns were identified: one class representing low-risk drinking (class 1 "low-risk" (61.2%)), two classes representing risky drinking (class 2 "moderate-risk" (5.7%) and class 3 "frequent drunk" (15.8%)), as well as two classes representing high-risk drinking (class 4 "alcohol-related problems" (11.4%) and class 5 "excessive drinking" (5.1%)). Membership of classes 4 and 5 was associated with the most severe psychosocial problems, especially with regard to aggressive-dissocial behaviors. The CRAFFT-d and brief RAPI screening tools allowed identifying the two risky drinking classes and two high-risk drinking classes. Our findings provide the first in-depth analysis of habitual drinking in this study population and may help practitioners to better tailor interventions to patients' needs by using the

  5. Using Latent Class Analysis to Model Preference Heterogeneity in Health: A Systematic Review.

    Science.gov (United States)

    Zhou, Mo; Thayer, Winter Maxwell; Bridges, John F P

    2017-10-03

    Latent class analysis (LCA) has been increasingly used to explore preference heterogeneity, but the literature has not been systematically explored and hence best practices are not understood. We sought to document all applications of LCA in the stated-preference literature in health and to inform future studies by identifying current norms in published applications. We conducted a systematic review of the MEDLINE, EMBASE, EconLit, Web of Science, and PsycINFO databases. We included stated-preference studies that used LCA to explore preference heterogeneity in healthcare or public health. Two co-authors independently evaluated titles, abstracts, and full-text articles. Abstracted key outcomes included segmentation methods, preference elicitation methods, number of attributes and levels, sample size, model selection criteria, number of classes reported, and hypotheses tests. Study data quality and validity were assessed with the Purpose, Respondents, Explanation, Findings, and Significance (PREFS) quality checklist. We identified 2560 titles, 99 of which met the inclusion criteria for the review. Two-thirds of the studies focused on the preferences of patients and the general population. In total, 80% of the studies used discrete choice experiments. Studies used between three and 20 attributes, most commonly four to six. Sample size in LCAs ranged from 47 to 2068, with one-third between 100 and 300. Over 90% of the studies used latent class logit models for segmentation. Bayesian information criterion (BIC), Akaike information criterion (AIC), and log-likelihood (LL) were commonly used for model selection, and class size and interpretability were also considered in some studies. About 80% of studies reported two to three classes. The number of classes reported was not correlated with any study characteristics or study population characteristics (p > 0.05). Only 30% of the studies reported using statistical tests to detect significant variations in preferences

  6. 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.

  7. Identifying symptom profiles of depression and anxiety in patients with an acute coronary syndrome using latent class and latent transition analysis.

    Science.gov (United States)

    Tisminetzky, Mayra; Bray, Bethany C; Miozzo, Ruben; Aupont, Onesky; McLaughlin, Thomas J

    2011-01-01

    To identify symptom profiles of depression and anxiety in patients with an acute coronary syndrome (ACS), to examine changes in symptom profiles over time, and finally, to examine the effects of age and sex on patients' symptom profiles. One hundred ACS patients with mild to severe symptoms of depression and/or anxiety at 1 month post-hospital discharge were enrolled in a randomized trial of cognitive behavioral therapy. Latent class and latent transition analyses were used to identify symptom profiles and describe change over the time in profile membership. A two-class solution was selected to describe depression and anxiety symptom profiles. Class I (76% of patients at baseline) was labeled "depression and some anxiety symptoms." Class II (24% of patients at baseline) was labeled "anxiety and some depression symptoms." Approximately 25% of patients in the treatment condition transitioned from the depression and some anxiety symptoms class to the anxiety and some depression symptoms class at follow-up compared to 10% of patients in the control condition at follow-up; nearly 50% of patients in the control condition showed worsening of symptoms as compared to 28% in the treatment condition. Results suggested age differences in the probabilities of transitioning between the classes; older patients were more likely to continue having depression and some anxiety symptoms at the time of follow-up. Identifying symptom profiles of depression and anxiety in patients with an ACS may improve diagnostic practices and help to design tailored interventions.

  8. Latent classes of young adults based on use of multiple types of tobacco and nicotine products.

    Science.gov (United States)

    Erickson, Darin J; Lenk, Kathleen M; Forster, Jean L

    2014-08-01

    New tobacco and nicotine products such as snus, hookah, and electronic cigarettes have risen in popularity in recent years. Use of these products among young adults is of particular interest given that experimentation with new products is common in young adulthood. We conducted latent class analysis among a population-based sample of young adults to identify separate classes based on use of 6 types of tobacco or nicotine products: snus, hookah, electronic cigarettes, cigarillos, snuff, and cigarettes. We then examined how identified classes differed on demographic characteristics and marijuana and alcohol use. We identified 5 classes: the largest group (60%) was characterized as reporting no or limited use of any of the products, while the smallest group (7%) was characterized by use of many types of products (poly-users). Of the 3 middle classes, 2 were the same size (10%) and were characterized by primarily using 2 of the products: one class used snus and snuff, and the other used cigarillos and hookah; the third class (13%) was characterized by primarily cigarette smoking. Numerous differences were seen across classes, including the poly-users being less likely to be college students/graduates and more likely to be male and use marijuana and alcohol. We found that young adults can be grouped into 5 subgroups based on types of tobacco/nicotine products they do and do not use. A poly-use group that uses all types of tobacco products is concerning, particularly given high levels of marijuana and alcohol use reported in this group. © The Author 2014. 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.

  9. Risk of re-report: A latent class analysis of infants reported for maltreatment.

    Science.gov (United States)

    Eastman, Andrea Lane; Mitchell, Michael N; Putnam-Hornstein, Emily

    2016-05-01

    A key challenge facing child protective services (CPS) is identifying children who are at greatest risk of future maltreatment. This analysis examined a cohort of children with a first report to CPS during infancy, a vulnerable population at high risk of future CPS reports. Birth records of all infants born in California in 2006 were linked to CPS records; 23,871 infants remaining in the home following an initial report were followed for 5 years to determine if another maltreatment report occurred. Latent class analysis (LCA) was used to identify subpopulations of infants based on varying risks of re-report. LCA model fit was examined using the Bayesian information criterion, a likelihood ratio test, and entropy. Statistical indicators and interpretability suggested the four-class model best fit the data. A second LCA included infant re-report as a distal outcome to examine the association between class membership and the likelihood of re-report. In Class 1 and Class 2 (lowest risk), the probability of a re-report was 44%; in contrast, the probability in Class 4 (highest risk) was 78%. Two birth characteristics clustered in the medium- and highest-risk classes: lack of established paternity and delayed or absent prenatal care. Two risk factors from the initial report of maltreatment emerged as predictors of re-report in the highest-risk class: an initial allegation of neglect and a family history of CPS involvement involving older siblings. Findings suggest that statistical techniques can be used to identify families with a heightened risk of experiencing later CPS contact. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. 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

  11. Certain subphenotypes of aspirin-exacerbated respiratory disease distinguished by latent class analysis.

    Science.gov (United States)

    Bochenek, Grazyna; Kuschill-Dziurda, Joanna; Szafraniec, Krystyna; Plutecka, Hanna; Szczeklik, Andrzej; Nizankowska-Mogilnicka, Ewa

    2014-01-01

    Aspirin-exacerbated respiratory disease (AERD) is recognized as a distinct asthma phenotype. It usually has a severe course accompanied by chronic hyperplastic eosinophilic sinusitis with nasal polyps, blood eosinophilia, and increased concentrations of urinary leukotriene E4 (LTE4). More insightful analysis of individual patients shows this group to be nonhomogeneous. We sought to identify any likely subphenotypes in a cohort of patients with AERD through the application of latent class analysis (LCA). Clinical data from 201 patients with AERD (134 women) were collected from questionnaires. Standard spirometry, atopy traits, blood eosinophilia, and urinary LTE4 concentrations were evaluated. LCA was applied to identify possible AERD subphenotypes. Four classes (subphenotypes) within the AERD phenotype were identified as follows: class 1, asthma with a moderate course, intensive upper airway symptoms, and blood eosinophilia (18.9% of patients); class 2, asthma with a mild course, relatively well controlled, and with low health care use (34.8% of patients); class 3, asthma with a severe course, poorly controlled, and with severe exacerbations and airway obstruction (41.3% of patients); and class 4, poorly controlled asthma with frequent and severe exacerbations in female subjects (5.0% of patients). Atopic status did not affect class membership. Patients with particularly intensive upper airway symptoms had the highest levels of blood eosinophilia and the highest concentrations of urinary LTE4. LCA revealed unique AERD subphenotypes, thus corroborating the heterogeneity of this population. Such discrimination might facilitate more individualized treatment in difficult-to-treat patients. Copyright © 2013 American Academy of Allergy, Asthma & Immunology. Published by Mosby, Inc. All rights reserved.

  12. 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

  13. 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.

  14. Patterns of Relationship and Sexual Behaviors in Mexican Adolescents and Associations with Well-being: A Latent Class Approach

    Science.gov (United States)

    Vasilenko, Sara A.

    2017-01-01

    To broaden our understanding of romance and sexuality during adolescence in Latin American countries, we used a person-oriented approach (latent class analysis) to examine classes marked by different patterns of romantic and sexual behaviors in Mexican adolescents. We found 5 classes: Inactive, (8.53%), Early stage (37.8%), Waiting class (27.5%), Physical (8.4%) and Committed (17.9%); but no group dating class. We also explored how these classes were associated with adolescents’ mental health and school performance. Middle school adolescents in the Committed class (high in romantic and sexual behaviors) had the highest level of depressive symptoms. Girls in the Inactive class and boys in the Physical class had the lowest level of symptoms. Adolescents in the Committed class also reported less academic motivation and achievement, whereas adolescents in the Inactive class reported higher motivation. This study expands our knowledge of adolescent romantic and sexual development in Mexico. PMID:26340166

  15. Sexual Initiation Patterns of U.S. Sexual Minority Youth: A Latent Class Analysis.

    Science.gov (United States)

    Goldberg, Shoshana K; Halpern, Carolyn T

    2017-03-01

    The typical understanding of sexual debut as first vaginal intercourse is often irrelevant to sexual minority youth. Better understanding of sexual initiation patterns among these youth is necessary to inform efforts to safeguard their sexual and reproductive health. Early sexual experiences were examined among 1,628 female and 526 male sexual minority participants in Waves 1 (1994-1995) and 4 (2008) of the National Longitudinal Study of Adolescent to Adult Health. Latent class analyses identified initiation patterns distinguished by the timing, sequence and spacing of first experiences of sexual behaviors. Multinomial logistic regression analyses assessed correlates of various patterns. Initiation classes for females were categorized as typical debut (representing 41% of the sample, characterized by vaginal intercourse and short spacing between first two behaviors); dual behavior debut (35%, characterized by vaginal and oral sex in the same year); early sexual debut (17%, characterized by average debut at 13, vaginal intercourse, and anal sex before 18); and delayed debut with oral sex (6%). Male classes were single behavior (50%, characterized by oral sex and longer spacing); multiple behavior (32%, characterized by vaginal and oral sex); early anal sex (11%, characterized by anal intercourse before 18); and very early debut (6%, characterized by oral sex and average debut at 10). Class membership was associated with socioeconomic status for females; age and sexual victimization for males; and race, ethnicity and religiosity for both. Initiation patterns of sexual minority youth differ between genders and involve noncoital behaviors and characteristics beyond timing. Copyright © 2017 by the Guttmacher Institute.

  16. 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."

  17. Health status transitions in community-living elderly with complex care needs: a latent class approach

    Directory of Open Access Journals (Sweden)

    Béland François

    2009-02-01

    Full Text Available Abstract Background For older persons with complex care needs, accounting for the variability and interdependency in how health dimensions manifest themselves is necessary to understand the dynamic of health status. Our objective is to test the hypothesis that a latent classification can capture this heterogeneity in a population of frail elderly persons living in the community. Based on a person-centered approach, the classification corresponds to substantively meaningful groups of individuals who present with a comparable constellation of health problems. Methods Using data collected for the SIPA project, a system of integrated care for frail older people (n = 1164, we performed latent class analyses to identify homogenous categories of health status (i.e. health profiles based on 17 indicators of prevalent health problems (chronic conditions; depression; cognition; functional and sensory limitations; instrumental, mobility and personal care disability Then, we conducted latent transition analyses to study change in profile membership over 2 consecutive periods of 12 and 10 months, respectively. We modeled competing risks for mortality and lost to follow-up as absorbing states to avoid attrition biases. Results We identified four health profiles that distinguish the physical and cognitive dimensions of health and capture severity along the disability dimension. The profiles are stable over time and robust to mortality and lost to follow-up attrition. The differentiated and gender-specific patterns of transition probabilities demonstrate the profiles' sensitivity to change in health status and unmasked the differential relationship of physical and cognitive domains with progression in disability. Conclusion Our approach may prove useful at organization and policy levels where many issues call for classification of individuals into pragmatically meaningful groups. In dealing with attrition biases, our analytical strategy could provide critical

  18. Personality types in childhood: relations to latent trajectory classes of problem behavior and overreactive parenting across the transition into adolescence.

    Science.gov (United States)

    Van den Akker, Alithe L; Deković, Maja; Asscher, Jessica J; Shiner, Rebecca L; Prinzie, Peter

    2013-04-01

    This study investigated relations among children's personality types, trajectories of internalizing and externalizing problems, and overreactive parenting across 6 years. Latent Class Analysis of the Big 5 personality dimensions (modeled as latent factors, based on mother, father and teacher reports) for 429 children (mean age 8 years at Time 1) replicated the Resilient, Under-, and Overcontroller types. Latent Class Growth Analysis of externalizing and internalizing problems (modeled as latent factors, based on mother and father reports), revealed that Undercontrollers were at greater risk of belonging to a high/decreasing externalizing problem class and a high/stable co-occurring problem class than were Resilients. Overcontrollers were more likely to be in a high/stable internalizing class and less likely to be in the externalizing problem class, but only at low levels of parental overreactivity. Undercontrollers appeared at double risk as they were at risk for high overreactive parenting, which was an independent risk-factor for the elevated problem trajectories. Because childhood personality types were a risk factor for adjustment problems that persisted into adolescence, Under- and Overcontrollers might be considered as a target for early intervention, with a focus on overreactive parenting for Undercontrollers specifically.

  19. Application of Latent Class Analysis to Identify Behavioral Patterns of Response to Behavioral Lifestyle Interventions in Overweight and Obese Adults.

    Science.gov (United States)

    Fitzpatrick, Stephanie L; Coughlin, Janelle W; Appel, Lawrence J; Tyson, Crystal; Stevens, Victor J; Jerome, Gerald J; Dalcin, Arlene; Brantley, Phillip J; Hill-Briggs, Felicia

    2015-08-01

    Examining responders and non-responders to behavioral lifestyle interventions among overweight/obese adults with additional comorbidities may aid in refining and tailoring obesity treatment. The purpose of this study is to demonstrate the use of latent class analysis to identify patterns of response to behavioral lifestyle interventions based on adherence to diet and exercise recommendations. Repeated measures latent class analysis was applied to two clinical trial datasets, combination of two active interventions in the PREMIER Trial (n = 501) and phase 1 of the Weight Loss Maintenance Trial (WLM; n = 1685), to identify patterns of response to behavioral lifestyle interventions. Treatment response was based on adherence to daily recommendations for fruit/vegetable, fat, saturated fat, sodium, and exercise at baseline and 6 months. In PREMIER, three distinct latent classes emerged: responders (45.9%), non-responders (23.6%), and early adherers (30.5%). Responders and Early Adherers had greater weight loss at 6 and 18 months and were more likely to meet behavioral recommendations at 18 months than Non-responders. For WLM, there were four latent classes: partial responders (16%), non-responders (40%), early adherers (2%), and fruit/veggie only responders (41%). Non-responders in WLM had significantly less weight loss at 6 months compared to that of the other three latent classes. Latent class analysis is a useful method to apply to clinical trial data to identify distinct patterns of response to behavioral interventions. Overweight/ obese participants who respond to behavioral lifestyle treatment (i.e., meet behavioral recommendations) have significantly greater weight loss than that of participants who do not make behavioral changes.

  20. Multimorbidity Profiles in German Centenarians: A Latent Class Analysis of Health Insurance Data.

    Science.gov (United States)

    Gellert, Paul; von Berenberg, Petra; Zahn, Thomas; Neuwirth, Julia; Kuhlmey, Adelheid; Dräger, Dagmar

    2017-10-01

    Multimorbidity in centenarians is common; although investigations of the prevalence of morbidity in centenarians are accumulating, research on profiles of co-occurrence of morbidities is still sparse. Our aim was to explore profiles of comorbidities in centenarians. Health insurance data from 1,121 centenarians comprising inpatient and outpatient diagnoses from the past 5 years (2009-2013) were analyzed using latent class analysis with adjustments for sex, age, hospitalization, and long-term care. Four distinct comorbidity profiles emerged from the data: 36% of centenarians were categorized as "age-associated"; 18% had a variety of comorbidities but were not diabetic were labeled "multimorbid without diabetes"; 9% were labeled "multimorbid with diabetes"; and 36% "low morbidity." Patterns of comorbidities describe the complexity of geriatric multimorbidity more appropriately than an approach focused on a single disease. The profiles described by this specific research may inform clinicians and health care planners for the oldest old.

  1. Identifying victims of workplace bullying by integrating traditional estimation approaches into a latent class cluster model.

    Science.gov (United States)

    Leon-Perez, Jose M; Notelaers, Guy; Arenas, Alicia; Munduate, Lourdes; Medina, Francisco J

    2014-05-01

    Research findings underline the negative effects of exposure to bullying behaviors and document the detrimental health effects of being a victim of workplace bullying. While no one disputes its negative consequences, debate continues about the magnitude of this phenomenon since very different prevalence rates of workplace bullying have been reported. Methodological aspects may explain these findings. Our contribution to this debate integrates behavioral and self-labeling estimation methods of workplace bullying into a measurement model that constitutes a bullying typology. Results in the present sample (n = 1,619) revealed that six different groups can be distinguished according to the nature and intensity of reported bullying behaviors. These clusters portray different paths for the workplace bullying process, where negative work-related and person-degrading behaviors are strongly intertwined. The analysis of the external validity showed that integrating previous estimation methods into a single measurement latent class model provides a reliable estimation method of workplace bullying, which may overcome previous flaws.

  2. Victims' routine activities and sex offenders' target selection scripts: a latent class analysis.

    Science.gov (United States)

    Deslauriers-Varin, Nadine; Beauregard, Eric

    2010-09-01

    This study investigates target selection scripts of 72 serial sex offenders who have committed a total of 361 sex crimes on stranger victims. Using latent class analysis, three target selection scripts were identified based on the victim's activities prior to the crime, each presenting two different tracks: (1) the Home script, which includes the (a) intrusion track and the (b) invited track, (2) the Outdoor script, which includes the (a) noncoercive track and the (b) coercive track, and (3) the Social script, which includes the (a) onsite track and the (b) off-site track. The scripts identified appeared to be used by both sexual aggressors of children and sexual aggressors of adults. In addition, a high proportion of crime switching was found among the identified scripts, with half of the 72 offenders switching scripts at least once. The theoretical relevance of these target selection scripts and their practical implications for situational crime prevention strategies are discussed.

  3. 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

  4. Latent class analysis of gambling subtypes and impulsive/compulsive associations

    DEFF Research Database (Denmark)

    Chamberlain, Samuel R.; Stochl, Jan; Redden, Sarah A.

    2017-01-01

    Background: 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. Methods: 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...

  5. 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.

  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 <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 neurotic personality traits increased with addiction severity levels (all P<0.001). However, Lie dimension was inversely related to the addiction severity levels (all P<0.01). Through the latent classification process, 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.

  7. Suicidal ideation and behavior in institutions of higher learning: A latent class analysis.

    Science.gov (United States)

    Bernanke, Joel; Galfalvy, Hanga C; Mortali, Maggie G; Hoffman, Laura A; Moutier, Christine; Nemeroff, Charles B; Stanley, Barbara H; Clayton, Paula; Harkavy-Friedman, Jill; Oquendo, Maria A

    2017-12-01

    Suicide is the second leading cause of death among undergraduate students, with an annual rate of 7.5 per 100,000. Suicidal behavior (SB) is complex and heterogeneous, which might be explained by there being multiple etiologies of SB. Data-driven identification of distinct at-risk subgroups among undergraduates would bolster this argument. We conducted a latent class analysis (LCA) on survey data from a large convenience sample of undergraduates to identify subgroups, and validated the resulting latent class model on a sample of graduate students. Data were collected through the Interactive Screening Program deployed by the American Foundation for Suicide Prevention. LCA identified 6 subgroups from the undergraduate sample (N = 5654). In the group with the most students reporting current suicidal thoughts (N = 623, 66% suicidal), 22.5% reported a prior suicide attempt, and 97.6% endorsed moderately severe or worse depressive symptoms. Notably, LCA identified a second at-risk group (N = 662, 27% suicidal), in which only 1.5% of respondents noted moderately severe or worse depressive symptoms. When graduate students (N = 1138) were classified using the model, a similar frequency distribution of groups was found. Finding multiple replicable groups at-risk for suicidal behavior, each with a distinct prevalence of risk factors, including a group of students who would not be classified as high risk with depression-based screening, is consistent with previous studies that identified multiple potential etiologies of SB. Copyright © 2017 Elsevier Ltd. All rights reserved.

  8. Fatal and serious road crashes involving young New Zealand drivers: a latent class clustering approach.

    Science.gov (United States)

    Weiss, Harold B; Kaplan, Sigal; Prato, Carlo Giacomo

    2016-12-01

    The over-representation of young drivers in road crashes remains an important concern worldwide. Cluster analysis has been applied to young driver sub-groups, but its application by analysing crash occurrence is just emerging. We present a classification analysis that advances the field through a holistic overview of crash patterns useful for designing youth-targeted road safety programmes. We compiled a database of 8644 New Zealand crashes from 2002 to 2011 involving at least one 15-24-year-old driver and a fatal or serious injury for at least one road user. We considered crash location, infrastructure characteristics, environmental conditions, demographic characteristics, driving behaviour, and pre-crash manoeuvres. The analysis yielded 15 and 8 latent classes of, respectively, single-vehicle and multi-vehicle crashes, and average posterior probabilities measured the odds of correct classification that revealed how the identified clusters contain mostly crashes of a particular class and all the crashes of that class. The results raised three major safety concerns for young drivers that should be addressed: (1) reckless driving and traffic law violations; (2) inattention, error, and hazard perception problems; and (3) interaction with road geometry and lighting conditions, especially on high-speed open roads and state highways.

  9. 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

    2011-12-01

    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 have 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. As part of a larger study, 1007 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. 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. 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. Copyright © 2011 Elsevier Ltd. All rights reserved.

  10. Sociodemographic predictors of latent class membership of problematic and disordered gamblers

    Directory of Open Access Journals (Sweden)

    Richard J.E. James

    2016-06-01

    Full Text Available This paper reports a series of analyses examining the predictors of gambling subtypes identified from a latent class analysis of problem gambling assessment data, pooled from four health and gambling surveys conducted in Britain between 2007 and 2012. Previous analyses have indicated that gambling assessments have a consistent three class structure showing quantitative and potentially qualitative differences. Bringing this data together is useful for studying more severe problem gamblers, where the small number of respondents has been a chronic limitation of gambling prevalence research. Predictors were drawn from sociodemographic indicators and engagement with other legal addictive behaviours, namely smoking and alcohol consumption. The pooled data was entered into a multinomial logistic regression model in which class membership was regressed along a series of demographic variables and survey year, based on previous analyses of gambling prevalence data. The results identified multiple demographic differences (age, general health, SES, being single, membership of ethnic minority groups between the non-problem and two classes endorsing some problem gambling indicators. Although these two groups tended to share a sociodemographic profile, the odds of being male, British Asian and a smoker increased between the three groups in line with problem gambling severity. Being widowed was also found to be associated with the most severe gambling class. A number of associations were also observed with other addictive behaviours. However these should be taken as indicative as these were limited subsamples of a single dataset. These findings identify specific groups in which gambling problems are more prevalent, and highlight the importance of the interaction between acute and determinant aspects of impulsivity, suggesting that a more complex account of impulsivity should be considered than is currently present in the gambling literature.

  11. Nonsuicidal self-injury and suicidal behavior: a latent class analysis among young adults.

    Directory of Open Access Journals (Sweden)

    Chloe A Hamza

    Full Text Available 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.

  12. 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.

  13. Multilevel latent class casemix modelling: a novel approach to accommodate patient casemix

    Directory of Open Access Journals (Sweden)

    Forman David

    2011-03-01

    Full Text Available Abstract Background Using routinely collected patient data we explore the utility of multilevel latent class (MLLC models to adjust for patient casemix and rank Trust performance. We contrast this with ranks derived from Trust standardised mortality ratios (SMRs. Methods Patients with colorectal cancer diagnosed between 1998 and 2004 and resident in Northern and Yorkshire regions were identified from the cancer registry database (n = 24,640. Patient age, sex, stage-at-diagnosis (Dukes, and Trust of diagnosis/treatment were extracted. Socioeconomic background was derived using the Townsend Index. Outcome was survival at 3 years after diagnosis. MLLC-modelled and SMR-generated Trust ranks were compared. Results Patients were assigned to two classes of similar size: one with reasonable prognosis (63.0% died within 3 years, and one with better prognosis (39.3% died within 3 years. In patient class one, all patients diagnosed at stage B or C died within 3 years; in patient class two, all patients diagnosed at stage A, B or C survived. Trusts were assigned two classes with 51.3% and 53.2% of patients respectively dying within 3 years. Differences in the ranked Trust performance between the MLLC model and SMRs were all within estimated 95% CIs. Conclusions A novel approach to casemix adjustment is illustrated, ranking Trust performance whilst facilitating the evaluation of factors associated with the patient journey (e.g. treatments and factors associated with the processes of healthcare delivery (e.g. delays. Further research can demonstrate the value of modelling patient pathways and evaluating healthcare processes across provider institutions.

  14. Original article Exploring somatization types among patients in Indonesia: latent class analysis using the Adult Symptom Inventory

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    Wahyu Widhiarso

    2014-12-01

    Full Text Available Background The aim of this study was to explore somatization types by reducing patient complaints to their most basic and parsimonious characteristics. We hypothesized that there were latent groups representing distinct types of somatization. Participants and procedure Data were collected from patients undergoing both inpatient and outpatient treatment at two hospitals in Yogyakarta, Indonesia (N = 212. Results Results from latent class analysis revealed four classes of somatization: two classes (Classes 1 and 2 referring to levels of somatization and two classes (Classes 3 and 4 referring to unique types of somatization. The first two classes (Classes 1 and 2; low and high levels of somatization, respectively corresponded to the number of different symptoms that patients reported out of the list of physical symptoms in the Adult Symptom Inventory. The second two classes (Classes 3 and 4; non-serious and critical complaints, respectively corresponded to two different sets of symptoms. Patients in Class 3 tended to report temporary mild complaints that are common in daily life, such as dizziness, nausea, and stomach pain. Patients in Class 4 tended to report severe complaints and medical problems that require serious treatment or medication, such as deafness or blindness. Conclusions The present study do confirm somatization as a unidimensional experience reflecting a general tendency to report somatic symptoms, but rather support the understanding of somatization as a multidimensional construct.

  15. Psychometric properties and a latent class analysis of the 12-item World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) in a pooled dataset of community samples.

    Science.gov (United States)

    MacLeod, Melissa A; Tremblay, Paul F; Graham, Kathryn; Bernards, Sharon; Rehm, Jürgen; Wells, Samantha

    2016-12-01

    The 12-item World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) is a brief measurement tool used cross-culturally to capture the multi-dimensional nature of disablement through six domains, including: understanding and interacting with the world; moving and getting around; self-care; getting on with people; life activities; and participation in society. Previous psychometric research supports that the WHODAS 2.0 functions as a general factor of disablement. In a pooled dataset from community samples of adults (N = 447) we used confirmatory factor analysis to confirm a one-factor structure. Latent class analysis was used to identify subgroups of individuals based on their patterns of responses. We identified four distinct classes, or patterns of disablement: (1) pervasive disability; (2) physical disability; (3) emotional, cognitive, or interpersonal disability; (4) no/low disability. Convergent validity of the latent class subgroups was found with respect to socio-demographic characteristics, number of days affected by disabilities, stress, mental health, and substance use. These classes offer a simple and meaningful way to classify people with disabilities based on the 12-item WHODAS 2.0. Focusing on individuals with a high probability of being in the first three classes may help guide interventions. Copyright © 2016 John Wiley & Sons, Ltd.

  16. 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

  17. Risk behaviors and drug use: a latent class analysis of heavy episodic drinking in first-year college students.

    Science.gov (United States)

    Chiauzzi, Emil; Dasmahapatra, Pronabesh; Black, Ryan A

    2013-12-01

    Examining individual characteristics may not yield an understanding of the complex array of factors that affect college student alcohol use. Utilizing a latent class analysis, the present study investigated an alcohol and drug use database of first-year college students at 89 U.S. colleges and universities (N = 21,945). These data were collected between December, 2010 and September, 2011. This study identified: (1) classes based on alcohol consumption, alcohol-related behaviors, and past-year use of illegal drugs and nonmedical use of prescriptions medications (NMUPM); (2) demographic covariates of these classes; and (3) differential social norms awareness, perceived harmfulness of illegal drugs and NMUPM, and protective strategies. Four classes were identified: (1) Low Risk Drinking/Low Prevalence Drug Use (Class 1); (2) Lower Intake Drinking/Moderate Prevalence Drug Use (Class 2); (3) Moderate Risk Drinking/Moderate Prevalence Drug Use (Class 3); and (4) High Risk Drinking/High Prevalence Drug Use (Class 4). Classes differed in self-reported typical week drinking, estimated peak blood alcohol content over the past 2 weeks, high-risk alcohol use, negative alcohol-related consequences, driving under the influence or riding with drinking drivers, alcohol-related protective behaviors, and past-year substance use. Of particular interest was the identification of a latent class (Class 2) composed primarily of females with a relatively low alcohol intake, but with a high probability of past-year other substance use. This group reported negative alcohol-related consequences despite their relatively low intake. To our knowledge, this is the first latent class analysis of college student alcohol use that includes a drug use indicator and compares social norms awareness, harmfulness perceptions, and alcohol-related protective behaviors between classes. PsycINFO Database Record (c) 2013 APA, all rights reserved.

  18. 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.

  19. 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.

  20. 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.

  1. 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

  2. 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.

  3. 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

  4. 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

  5. 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

  6. 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%),…

  7. 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…

  8. Stress, Mental Health, and Substance Abuse Problems in a Sample of Diversion Program Youths: An Exploratory Latent Class Analysis

    Science.gov (United States)

    Dembo, Richard; Briones, Rhissa; Gulledge, Laura; Karas, Lora; Winters, Ken C.; Belenko, Steven; Greenbaum, Paul E.

    2012-01-01

    Reflective of interest in mental health and substance abuse issues among youths involved with the justice system, we performed a latent class analysis on baseline information collected on 100 youths involved in two diversion programs. Results identified two groups of youths: Group 1: a majority of the youths, who had high levels of delinquency,…

  9. 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

  10. Impacts of fast food and food retail environment on overweight and obesity in China: a multilevel latent class cluster approach

    NARCIS (Netherlands)

    Zhang XiaoYong, Xiaoyong; Lans, van der I.A.; Dagevos, H.

    2012-01-01

    Objective To simultaneously identify consumer segments based on individual-level consumption and community-level food retail environment data and to investigate whether the segments are associated with BMI and dietary knowledge in China. Design A multilevel latent class cluster model was applied to

  11. THE IMPACT OF PROMOTION AND ADVERTISING ON CHOICE OF FRUIT CATEGORY AND APPLE VARIETY: A LATENT-CLASS APPROACH

    OpenAIRE

    Richards, Timothy J.; Patterson, Paul M.

    1999-01-01

    This study applies a latent class estimation technique to a panel of A.C. Nielsen fruit-consuming households to define price, advertising, and promotion responsiveness segments. Ex post analysis of these segments finds significant demographic differences among them, suggesting that fruit-marketers should target their marketing activities in order to improve their efficiency.

  12. Psychopathy and self-injurious thoughts and behaviour: application of latent class analysis.

    Science.gov (United States)

    Dhingra, Katie; Boduszek, Daniel; Palmer, Derrol; Shevlin, Mark

    2015-02-01

    Although early conceptualisations posited an inverse relationship between psychopathy and self-injury, little research has tested this. To examine the self-injurious thoughts and behaviours associated with psychopathy. Data from the MacArthur Violence Risk Assessment Project (N = 871) were used to examine homogenous subtypes of participants based on their responses to six self-injury items. A binary logistic regression model was used to interpret the nature of the latent classes by estimating the associations with the four psychopathy factors, mixed anxiety-depression, violence victimisation, and gender. A 2-class solution provided the best fit to the data. Most participants (86.2%) were assigned to the baseline ("low self-injury risk") group. "The high-risk self-injury group" was characterised by a higher probability of endorsing all self-injury items, particularly "thoughts of hurting self" and "attempts to hurt self". The four psychopathy factors showed differential associations with self-injury group membership. Participant's scorings, higher on the affective component and lower on interpersonal component of psychopathy, were significantly more likely to be assigned to the high risk group. Significant associations were also found between mixed anxiety/depression and gender, and "high-risk self-injury group" membership. These findings have important implications for the identification of individuals at risk of self-injury.

  13. Latent Class Analysis of Intimate Partner Violence Perpetration and Victimization among Latino Emerging Adults.

    Science.gov (United States)

    Grest, Carolina Villamil; Lee, Jungeun Olivia; Gilreath, Tamika; Unger, Jennifer B

    2018-03-01

    While there are known developmental consequences and correlates of intimate partner violence perpetration and victimization, research focused on bidirectional and multiple forms of partner violence among Latino emerging adults is needed. This longitudinal study identified latent classes of intimate partner violence perpetration and victimization patterns among emerging adult Latinos (N = 1060; 60.6% female). A second aim examined acculturation and cumulative substance use correlates in high school, as predictors of intimate partner violence perpetration and victimization classes in emerging adulthood. Average age of participants was 15.5 years in 10th grade and 22.7 years in emerging adulthood. We identified four distinct subgroups of intimate partner violence perpetration and victimization, with 22% of individuals identified in a violence perpetration and victimization subgroup. Cumulative heavy episodic drinking and marijuana use in high school predicted belonging to the psychological bidirectional intimate partner violence group rather than the group with no violence. Cumulative marijuana use in high school, predicted belonging to the sexual bidirectional partner violence group compared to the no violence group. Our study extends the literature across developmental periods among Latino youth. The findings have implications for early adolescent prevention strategies and promotion of healthy intimate relationships.

  14. 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 internet usage, males were more addicted than females (Pinternet 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 (Pinternet 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

  15. Frictions as barriers to perioperative alignment: results from a latent class analysis.

    Science.gov (United States)

    Shewchuk, Richard M; Carlson, Greg L; Klosterman, Matt; Cullen, Stephen; Qu, Haiyan

    2014-01-01

    The quality of the relationship between the sterile processing department (SPD) and the operating room (OR) is an important determinant of OR safety and performance. In this article, the concept of "friction" refers to the SPD behaviors and attributes that can negatively affect OR performance. Panels of SPD professionals initially were asked to identify and operationally define different ways in which behaviors of a hospital's SPD could compromise OR performance. A national convenience sample of OR nurses (N=291) rated 14 frictions in terms of their agreement or disagreement that each had a negative effect on OR performance in their hospital. Overall, more than 50% of the entire sample agreed that 2 frictions, "SPD does not communicate effectively with the OR" (55%) and "SPD inventories are insufficient for surgical volume" (52%), had negative effect on OR performance. However, a latent class analysis revealed 3 distinct classes of nurses who varied with respect to their level of agreement that SPD-OR frictions negatively affected OR performance. The observed heterogeneity in how different groups of nurses viewed different frictions suggests that effective efforts aimed at reducing performance-limiting frictions should be customized so that resources can be used where they are most needed.

  16. Latent class analysis of reading, decoding, and writing performance using the Academic Performance Test: concurrent and discriminating validity.

    Science.gov (United States)

    Cogo-Moreira, Hugo; Carvalho, Carolina Alves Ferreira; de Souza Batista Kida, Adriana; de Avila, Clara Regina Brandão; Salum, Giovanni Abrahão; Moriyama, Tais Silveira; Gadelha, Ary; Rohde, Luis Augusto; de Moura, Luciana Monteiro; Jackowski, Andrea Parolin; de Jesus Mari, Jair

    2013-01-01

    To explore and validate the best returned latent class solution for reading and writing subtests from the Academic Performance Test (TDE). 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). 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. A three-class solution was found to be the best model solution, revealing classes of children with good, not-so-good, or poor performance on TDE reading and writing tasks. The three-class solution has been shown to be correlated with estimated IQ and to ADHD diagnosis. No association was observed between the latent class and major depression. The three-class solution showed both concurrent and discriminant validity. This work provides initial evidence of validity for an empirically derived categorical classification of reading, decoding, and writing performance using the TDE. A valid classification encourages further research investing correlates of reading and writing performance using the TDE.

  17. Further victimization of child sexual abuse victims: A latent class typology of re-victimization trajectories.

    Science.gov (United States)

    Papalia, Nina L; Luebbers, Stefan; Ogloff, James R P; Cutajar, Margaret; Mullen, Paul E; Mann, Emily

    2017-04-01

    The association between child sexual abuse (CSA) and risk for re-victimization is well-documented; however, less is known about the temporal progression of re-victimization experiences over the early life-course among CSA survivors, and whether this differs from that of those without known sexual abuse histories. This study investigated whether there are distinct temporal pathways of interpersonal re-victimization between the ages of 10-25 years among medically confirmed CSA cases, and considered whether abuse variables, re-victimization variables, and the presence of other adverse outcomes, were associated with heterogeneity in re-victimization pathways. The data were collected as part of a large-scale data-linkage study in which the medical records of 2759 cases of contact-CSA between 1964 and 1995 were linked, between 13 and 44 years following abuse, to police and public psychiatric databases; cases were compared to a matched community sample (n=2677). Using a subsample of 510 (401 victims; 109 comparisons) individuals with an interpersonal (re)victimization history, we examined the aggregate 'age-(re)victimization' curves for CSA victims and comparisons, respectively. Further, we applied longitudinal latent class analysis to explore heterogeneity in re-victimization trajectories among abuse survivors across their early life-course. Four latent pathways were identified, labeled: Normative; Childhood-Limited; Emerging-Adulthood; and Chronic re-victimization trajectories. Older age at abuse, a criminal history, and mental health problems were uniquely predictive of membership to the more problematic and persistent re-victimization trajectories. Findings indicate that individuals exposed to CSA during adolescence may be particularly vulnerable to poorer re-victimization trajectories, characterized by multiple risk indices, and thus may warrant increased service provision. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. A LATENT CLASS BINOMIAL LOGIT METHODOLOGY FOR THE ANALYSIS OF PAIRED-COMPARISON CHOICE DATA - AN APPLICATION REINVESTIGATING THE DETERMINANTS OF PERCEIVED RISK

    NARCIS (Netherlands)

    WEDEL, M; DESARBO, WS

    1993-01-01

    A latent class model for identifying classes of subjects in paired comparison choice experiments is developed. The model simultaneously estimates a probabilistic classification of subjects and the logit models' coefficients relating characteristics of objects to choices for each respective group

  19. Uncovering Substantive Patterns in Student Responses in International Large-Scale Assessments--Comparing a Latent Class to a Manifest DIF Approach

    Science.gov (United States)

    Oliveri, María Elena; Ercikan, Kadriye; Zumbo, Bruno D.; Lawless, René

    2014-01-01

    In this study, we contrast results from two differential item functioning (DIF) approaches (manifest and latent class) by the number of items and sources of items identified as DIF using data from an international reading assessment. The latter approach yielded three latent classes, presenting evidence of heterogeneity in examinee response…

  20. Characterizing longitudinal patterns of physical activity in mid-adulthood using latent class analysis: results from a prospective cohort study.

    Science.gov (United States)

    Silverwood, Richard J; Nitsch, Dorothea; Pierce, Mary; Kuh, Diana; Mishra, Gita D

    2011-12-15

    The authors aimed to describe how longitudinal patterns of physical activity during mid-adulthood (ages 31-53 years) can be characterized using latent class analysis in a population-based birth cohort study, the Medical Research Council's 1946 National Survey of Health and Development. Three different types of physical activity-walking, cycling, and leisure-time physical activity-were analyzed separately using self-reported data collected from questionnaires between 1977 and 1999; 3,847 study members were included in the analysis for one or more types of activity. Patterns of activity differed by sex, so stratified analyses were conducted. Two walking latent classes were identified representing low (52.8% of males in the cohort, 33.5% of females) and high (47.2%, 66.5%) levels of activity. Similar low (91.4%, 82.1%) and high (8.6%, 17.9%) classes were found for cycling, while 3 classes were identified for leisure-time physical activity: "low activity" (46.2%, 48.2%), "sports and leisure activity" (31.0%, 35.3%), and "gardening and do-it-yourself activities" (22.8%, 16.5%). The classes were reasonably or very well separated, with the exception of walking in females. Latent class analysis was found to be a useful tool for characterizing longitudinal patterns of physical activity, even when the measurement instrument differs slightly across ages, which added value in comparison with observed activity at a single age.

  1. Classifying Patients with Chronic Pelvic Pain into Levels of Biopsychosocial Dysfunction Using Latent Class Modeling of Patient Reported Outcome Measures

    Science.gov (United States)

    Fenton, Bradford W.; Grey, Scott F.; Tossone, Krystel; McCarroll, Michele; Von Gruenigen, Vivian E.

    2015-01-01

    Chronic pelvic pain affects multiple aspects of a patient's physical, social, and emotional functioning. Latent class analysis (LCA) of Patient Reported Outcome Measures Information System (PROMIS) domains has the potential to improve clinical insight into these patients' pain. Based on the 11 PROMIS domains applied to n=613 patients referred for evaluation in a chronic pelvic pain specialty center, exploratory factor analysis (EFA) was used to identify unidimensional superdomains. Latent profile analysis (LPA) was performed to identify the number of homogeneous classes present and to further define the pain classification system. The EFA combined the 11 PROMIS domains into four unidimensional superdomains of biopsychosocial dysfunction: Pain, Negative Affect, Fatigue, and Social Function. Based on multiple fit criteria, a latent class model revealed four distinct classes of CPP: No dysfunction (3.2%); Low Dysfunction (17.8%); Moderate Dysfunction (53.2%); and High Dysfunction (25.8%). This study is the first description of a novel approach to the complex disease process such as chronic pelvic pain and was validated by demographic, medical, and psychosocial variables. In addition to an essentially normal class, three classes of increasing biopsychosocial dysfunction were identified. The LCA approach has the potential for application to other complex multifactorial disease processes. PMID:26355825

  2. Examining the Latent Class Structure of CO2 Hypersensitivity using Time Course Trajectories of Panic Response Systems

    Science.gov (United States)

    Roberson-Nay, Roxann; Beadel, Jessica R.; Gorlin, Eugenia I.; Latendresse, Shawn J.; Teachman, Bethany A.

    2014-01-01

    Background and Objectives Carbon dioxide (CO2) hypersensitivity is hypothesized to be a robust endophenotypic marker of panic spectrum vulnerability. The goal of the current study was to explore the latent class trajectories of three primary response systems theoretically associated with CO2 hypersensitivity: subjective anxiety, panic symptoms, and respiratory rate (fR). Methods Participants (n=376; 56% female) underwent a maintained 7.5% CO2 breathing task that included three phases: baseline, CO2 air breathing, and recovery. Growth mixture modeling was used to compare response classes (1..n) to identify the best-fit model for each marker. Panic correlates also were examined to determine class differences in panic vulnerability. Results For subjective anxiety ratings, a three-class model was selected, with individuals in one class reporting an acute increase in anxiety during 7.5% CO2 breathing and a return to pre-CO2 levels during recovery. A second, smaller latent class was distinguished by elevated anxiety across all three phases. The third class reported low anxiety reported during room air, a mild increase in anxiety during 7.5% CO2 breathing, and a return to baseline during recovery. Latent class trajectories for fR yielded one class whereas panic symptom response yielded two classes. Limitations This study examined CO2 hypersensitivity in one of the largest samples to date, but did not ascertain a general population sample thereby limiting generalizability. Moreover, a true resting baseline measure of fR was not measured. Conclusions Two classes potentially representing different risk pathways were observed. Implications of results will be discussed in the context of panic risk research. PMID:25496936

  3. 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

  4. Characterizing High School Students Who Play Drinking Games Using Latent Class Analysis

    Science.gov (United States)

    Borsari, Brian; Zamboanga, Byron L.; Correia, Christopher; Olthuis, Janine V.; Van Tyne, Kathryne; Zadworny, Zoe; Grossbard, Joel R.; Horton, Nicholas J.

    2013-01-01

    Heavy alcohol use and its associated negative consequences continue to be an important health issue among adolescents. Of particular concern are risky drinking practices such as playing drinking games. Although retrospective accounts indicate that drinking game participation is common among high school students, it has yet to be assessed in current high school students. Utilizing data from high school students who reported current drinking game participation (n = 178), we used latent class analysis to investigate the negative consequences resulting from gaming and examined underlying demographic and alcohol-related behavioral characteristics of students as a function of the resultant classes. Three classes of “gamers” emerged: (1) a “lower-risk” group who had a lower probability of endorsing negative consequences compared to the other groups, (2) a “higher-risk” group who reported that they experienced hangovers and difficulties limiting their drinking, got physically sick, and became rude, obnoxious, or insulting, and (3) a “sexual regret” group who reported that they experienced poor recall and unplanned sexual activity that they later regretted. Although the frequency of participating in drinking games did not differ between these three groups, results indicated that the “lower-risk” group consumed fewer drinks in a typical gaming session compared to the other two groups. The present findings suggest that drinking games are common among high school students, but that mere participation and frequency of play is not necessarily the best indicator of risk. Instead, examination of other constructs such as game-related alcohol consumption, consequences, or psychosocial variables such as impulsivity may be more useful. PMID:23778317

  5. 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.

  6. Patterns of high-intensity drinking among young adults in the United States: A repeated measures latent class analysis.

    Science.gov (United States)

    Patrick, Megan E; Terry-McElrath, Yvonne M; Schulenberg, John E; Bray, Bethany C

    2017-11-01

    Using a national sample of young adults, this study identified latent classes of alcohol use including high-intensity drinking (10+ drinks) from ages 18 to 25/26, and explored associations between time-invariant covariates measured at age 18 and class membership. Longitudinal data from the national Monitoring the Future study were available for 1078 individuals (51% female) first surveyed as 12th grade students in 2005-2008, and followed through modal age 25/26. Repeated measures latent class analysis was used to identify latent classes based on self-reported alcohol use: no past 30-day drinking, 1-9 drinks per occasion in the past 2weeks, and 10+ drinks per occasion. Four latent classes of alcohol use from ages 18 to 25/26 were identified: (1) Non-Drinkers (21%); (2) Legal Non-High-Intensity Drinkers (23%); (3) Persistent Non-High-Intensity Drinkers (40%); and (4) High-Intensity Drinkers (16%). Membership in the High-Intensity Drinkers class was characterized by higher than average probabilities of high-intensity drinking at all ages, with the probability of high-intensity drinking increasing between ages 18 and 21/22. Both gender and race/ethnicity significantly differentiated class membership, whereas neither parental education (a proxy for socioeconomic status) nor college plans at 12th grade showed significant associations. More than one in seven individuals who were seniors in high school experienced a long-term pattern of high-intensity drinking lasting into middle young adulthood. Young adult high-intensity drinking is often preceded by high-intensity drinking in high school, suggesting the importance of screening and prevention for high-intensity drinking during adolescence. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. Latent Classes of Adolescent Sexual and Romantic Relationship Experiences: Implications for Adult Sexual Health and Relationship Outcomes

    Science.gov (United States)

    Vasilenko, Sara A.; Kugler, Kari C.; Lanza, Stephanie T.

    2015-01-01

    Adolescents’ sexual and romantic relationship experiences are multidimensional, but often studied as single constructs. Thus, it is not clear how different patterns of sexual and relationship experience may interact to differentially predict later outcomes. In this study we used latent class analysis to model patterns (latent classes) of adolescent sexual and romantic experiences, and then examined how these classes are associated with young adult sexual health and relationship outcomes in data from the National Longitudinal Study of Adolescent to Adult Health. We identified six adolescent relationship classes: No Relationship (33%), Waiting (22%), Intimate (38%), Private (3%), Low Involvement (3%), and Physical (2%). Adolescents in the Waiting and Intimate classes were more likely to have married by young adulthood than those in other classes, and those in the Physical class had a greater number of sexual partners and higher rates of STIs. Some gender differences were found; for example, women in the Low-involvement and Physical classes in adolescence had average or high odds of marriage, whereas men in these classes had relatively low odds of marriage. Our findings identify more and less normative patterns of romantic and sexual experiences in late adolescence, and elucidate associations between adolescent experiences and adult outcomes. PMID:26445133

  8. 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

  9. 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.

  10. Heterogeneity in multidimensional health trajectories of late old years and socioeconomic stratification: a latent trajectory class analysis.

    Science.gov (United States)

    Wickrama, Kandauda K A S; Mancini, Jay A; Kwag, Kyunghwa; Kwon, Josephine

    2013-03-01

    This study examines (a) the heterogeneity in individual multidimensional health trajectories and (b) the socioeconomic stratification of individual multidimensional health trajectories during the late older years. This study used prospective data from 1,945 adults, 75 to 85 years old, collected over an 8-year period from the Health and Retirement Study. To examine inconsistent findings in the research literature, a latent trajectory class analysis was performed. Multidimensional overall health trajectories showed three heterogeneous latent classes (maintaining, persistently high, and deteriorating), and profiles of ascribed and achieved socioeconomic characteristics of multidimensional health trajectory classes showed a significant social and racial/ethnic stratification in late older years. Past adverse socioeconomic circumstances, including childhood and adulthood adversity, are potential sources of unobserved heterogeneity of multidimensional health trajectories even in late older years. The identification of members of latent trajectory health classes and the associated antecedents linked to health class membership are consistent with a life-course conceptual framework. Thus, multidimensional health capturing the full range of health problems needs to be investigated for proper examination of socioeconomic correlates of health. This facilitates the understanding of the associations between life-course experiences and health in late old age that ultimately have implications for prevention and intervention.

  11. 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.

  12. 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.

  13. 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.

  14. Exploring differential health effects of work stress: a latent class cluster approach.

    Science.gov (United States)

    Mayerl, Hannes; Stolz, Erwin; Waxenegger, Anja; Freidl, Wolfgang

    2017-01-01

    While evidence highlights the detrimental health consequences of adverse working conditions, effect sizes vary by the stressor examined. In this study, we aimed to explore the differential effects various constellations of job demands have on prevalent symptom clusters. We analysed self-reported data from a nationwide Austrian survey (N = 16,466), based on a cross-sectional design. By means of latent class analysis, a set of items was used to assess the burden from several job demands as well as the frequency of occurrence of mental and physical symptoms in order to identify stress profiles and symptom clusters, respectively. Analysis revealed four subgroups that each demonstrated a typological response pattern regarding job demands and health symptoms, respectively. The revealed stress profiles were found to be strongly related to the symptom clusters, while the effects differed considerably depending on the types of demands experienced. The current study presents an alternative method of examining the stress-health link by using a combined person- and variable-centred approach. The findings suggest a hierarchy in stress exposure with the most pronounced health consequences found for a synchronous burden from physical, psychosocial and organizational demands.

  15. A latent class approach to the external validation of respiratory and non-respiratory panic subtypes

    Science.gov (United States)

    Roberson-Nay, R.; Latendresse, S. J.; Kendler, K. S.

    2013-01-01

    Background The phenotypic variance observed in panic disorder (PD) appears to be best captured by a respiratory and non-respiratory panic subtype. We compared respiratory and non-respiratory panic subtypes across a series of external validators (temporal stability, psychiatric co-morbidity, treatment response) to determine whether subtypes are best conceptualized as differing: (1) only on their symptom profiles with no other differences between them; (2) on a quantitative (i.e. severity) dimension only; or (3) qualitatively from one another. Method Data from a large epidemiological survey (National Epidemiologic Survey on Alcohol and Related Conditions) and a clinical trial (Cross-National Collaborative Panic Study) were used. All analytic comparisons were examined within a latent class framework. Results High temporal stability of panic subtypes was observed, particularly among females. Respiratory panic was associated with greater odds of lifetime major depression and a range of anxiety disorders as well as increased treatment utilization, but no demographic differences. Treatment outcome data did not suggest that the two PD subtypes were associated with differential response to either imipramine or alprazolam. Conclusions These data suggest that respiratory and non-respiratory panic represent valid subtypes along the PD continuum, with the respiratory variant representing a more severe form of the disorder. PMID:21846423

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. Optimization of a class of latent thermal energy storage systems with multiple phase-change materials

    Energy Technology Data Exchange (ETDEWEB)

    Aceves, S.M. [Lawrence Livermore National Lab., CA (United States); Nakamura, H. [Daido Inst. of Tech., Nagoya (Japan). Dept. of Mechanical Engineering; Reistad, G.M. [Oregon State Univ., Corvallis, OR (United States). Dept. of Mechanical Engineering; Martinez-Frias, J. [Centro de Ingenieria y Desarollo Industrial, Queretaro (Mexico)

    1998-02-01

    This paper presents an analysis of a class of latent thermal energy storage (LTES) system. The analysis is based on a simplified model that allows the system performance to be evaluated in terms of a small set of parameters, while still retaining the main thermodynamic aspects associated with their operation. This analysis therefore permits the broad-based application potential of these systems to be viewed. The paper also discusses the applicability of the model to practical systems. This paper analyzes LTES with multiple energy storage cells and multiple phase-change materials (PCMs). The most general case of infinite energy storage cells and PCMs is solved, for the charge process only, as well as for the overall charge-discharge process. The results yield the optimum phase change temperature, expressed as a continuous function of position along the LTES. The method is equally applicable to the case of a finite number of storage cells. An example of the application of the method to this case is also included. The results show the optimum phase change temperatures for each of the problems being considered, along with the corresponding optimum exergetic efficiencies. The solutions to the optimization problems are surprisingly simple to express, considering the difficulty of the problems, and indicate the potential advantages of using LTES with multiple PCMs.

  1. 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.

  2. Self-reported sleep problems among the elderly: A latent class analysis.

    Science.gov (United States)

    Yu, Junhong; Mahendran, Rathi; Abdullah, Fadzillah Nur Mohd; Kua, Ee-Heok; Feng, Lei

    2017-12-01

    The present study utilized a person-centered approach to examine the different profiles of problem sleepers in a community sample of elderly. In addition, this study also explores how demographic and psychiatric variables may be related to these different profiles of sleep problems. A total of 515 participants (Mean age = 67 years, SD = 5) were administered self-report measures of sleep problems, depression and anxiety. Among them, 230 who reported significant problems in any of five selected sleep components were entered into a latent class analysis. The remaining 285 participants were assigned to a comparison control group. The profiles of 'inadequate sleep', 'disturbed sleep', 'trouble falling asleep' and 'multiple problems' were identified. The 'multiple problems' group had significantly higher levels of depression and anxiety relative to the control group. Regression analyses indicated that these different profiles had contributed to a significant increase in variance explained in anxiety but not depression levels, on top of the severity of sleep problems and demographic variables. Although sleep problems occur among the elderly with considerable heterogeneity, they can generally be classified into four different profiles. Furthermore, the inclusion of sleep problem profiles can significantly enhance the prediction of anxiety symptoms. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. 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.

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

    Science.gov (United States)

    2012-01-01

    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. PMID:22863369

  5. 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.

  6. Three subgroups of pain profiles identified in 227 women with arthritis: a latent class analysis.

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    de Luca, Katie; Parkinson, Lynne; Downie, Aron; Blyth, Fiona; Byles, Julie

    2017-03-01

    The objectives were to identify subgroups of women with arthritis based upon the multi-dimensional nature of their pain experience and to compare health and socio-demographic variables between subgroups. A latent class analysis of 227 women with self-reported arthritis was used to identify clusters of women based upon the sensory, affective, and cognitive dimensions of the pain experience. Multivariate multinomial logistic regression analysis was used to determine the relationship between cluster membership and health and sociodemographic characteristics. A three-class cluster model was most parsimonious. 39.5 % of women had a unidimensional pain profile; 38.6 % of women had moderate multidimensional pain profile that included additional pain symptomatology such as sensory qualities and pain catastrophizing; and 21.9 % of women had severe multidimensional pain profile that included prominent pain symptomatology such as sensory and affective qualities of pain, pain catastrophizing, and neuropathic pain. Women with severe multidimensional pain profile have a 30.5 % higher risk of poorer quality of life and a 7.3 % higher risk of suffering depression, and women with moderate multidimensional pain profile have a 6.4 % higher risk of poorer quality of life when compared to women with unidimensional pain. This study identified three distinct subgroups of pain profiles in older women with arthritis. Women had very different experiences of pain, and cluster membership impacted significantly on health-related quality of life. These preliminary findings provide a stronger understanding of profiles of pain and may contribute to the development of tailored treatment options in arthritis.

  7. Predictors and outcomes of somatization in bipolar I disorder: A latent class mixture modeling approach.

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    Edgcomb, Juliet Beni; Kerner, Berit

    2017-11-16

    Mood disorders are often associated with somatic symptoms. The role of somatic symptoms on disease progression in unipolar depression is substantially better characterized than that role in bipolar disorder. Moreover, the contribution of comorbid anxiety disorders and medical illness is not well understood. We investigated 527 patients with bipolar I disorder clustered within 102 families using a latent class approach. Predictors were added stepwise into the model. Anxiety and commonly associated medical illnesses were added as covariates. The rate of somatic symptoms in this sample was 73% (mean 1.7 symptoms), and 27.3% had a comorbid anxiety disorder. A two-class model, with a subgroup at high-risk for somatization, gave the best fit to the data. Multilevel mixture modeling accounted for family clusters. Somatic symptoms were independently associated with disease severity, defined as earlier age of first seeking psychiatric help (x = 21.7 vs x = 24.7, p = 0.005) and first psychiatric hospitalization (x = 25.7 vs x = 28.2, p = 0.03), greater probability of attempting suicide (x = 0.41 vs x = 0.32, p = 0.047), and rapid-cycling disease course (x = 0.57 vs x = 0.36, p somatic symptoms were more likely to be hospitalized for severe mania (x = 0.63 vs x = 0.51; p = 0.013), but did not significantly differ in hospitalization for severe depression. The study is correlational. Information on pharmacologic interventions and comorbid diseases was limited. Somatic symptoms in bipolar disorder could be an independent indicator for disease severity, suicidality, and rapid-cycling disease course. In severe mental illness, somatic and psychological symptoms must be jointly addressed. Copyright © 2017 Elsevier B.V. All rights reserved.

  8. Food shopping profiles and their association with dietary patterns: A latent class analysis

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    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

  9. Service use of older people who participate in primary care health promotion: a latent class analysis.

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    Ford, John A; Kharicha, Kalpa; Clarke, Caroline S; Clark, Allan; Iliffe, Steve; Goodman, Claire; Manthorpe, Jill; Steel, Nick; Walters, Kate

    2017-03-06

    Recruiting patients to health promotion programmes who will benefit is crucial to success. A key policy driver for health promotion in older people is to reduce health and social care use. Our aim was to describe service use among older people taking part in the Multi-dimensional Risk Appraisal for Older people primary care health promotion programme. A random sample of 1 in 3 older people (≥65 years old) was invited to participate in the Multi-dimensional Risk Appraisal for Older people project across five general practices in London and Hertfordshire. Data collected included socio-demographic characteristics, well-being and functional ability, lifestyle factors and service use. Latent class analysis (LCA) was used to identify groups based on use of the following: secondary health care, primary health care, community health care, paid care, unpaid care, leisure and local authority resources. Differences in group characteristics were assessed using univariate logistic regression, weighted by probability of class assignation and clustered by GP practice. Response rate was 34% (526/1550) with 447 participants presenting sufficient data for analysis. LCA using three groups gave the most meaningful interpretation and best model fit. About a third (active well) were fit and active with low service use. Just under a third (high NHS users) had high impairments with high primary, secondary and community health care contact, but low non-health services use. Just over a third (community service users) with high impairments used community health and other services without much hospital use. Older people taking part in the Multi-dimensional Risk Appraisal for Older people primary care health promotion can be described as three groups: active well, high NHS users, and community service users.

  10. Characterizing long-term patterns of weight change in China using latent class trajectory modeling.

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    Lauren Paynter

    Full Text Available Over the past three decades, obesity-related diseases have increased tremendously in China, and are now the leading causes of morbidity and mortality. Patterns of weight change can be used to predict risk of obesity-related diseases, increase understanding of etiology of disease risk, identify groups at particularly high risk, and shape prevention strategies.Latent class trajectory modeling was used to compute weight change trajectories for adults aged 18 to 66 using the China Health and Nutrition Survey (CHNS data (n = 12,611. Weight change trajectories were computed separately for males and females by age group at baseline due to differential age-related patterns of weight gain in China with urbanization. Generalized linear mixed effects models examined the association between weight change trajectories and baseline characteristics including urbanicity, BMI category, age, and year of study entry.Trajectory classes were identified for each of six age-sex subgroups corresponding to various degrees of weight loss, maintenance and weight gain. Baseline BMI status was a significant predictor of trajectory membership for all age-sex subgroups. Baseline overweight/obesity increased odds of following 'initial loss with maintenance' trajectories. We found no significant association between baseline urbanization and trajectory membership after controlling for other covariates.Trajectory analysis identified patterns of weight change for age by gender groups. Lack of association between baseline urbanization status and trajectory membership suggests that living in a rural environment at baseline was not protective. Analyses identified age-specific nuances in weight change patterns, pointing to the importance of subgroup analyses in future research.

  11. Syndemic Risk Classes and Substance Use Problems among Adults in High-Risk Urban Areas: A Latent Class Analysis

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    Charles M. Cleland

    2017-09-01

    Full Text Available Substance use problems tend to co-occur with risk factors that are especially prevalent in urban communities with high rates of poverty. The present study draws on Syndemics Theory to understand profiles of risk and resilience and their associations with substance use problems in a population at risk for adverse outcomes. African-American/Black and Hispanic heterosexual adults (N = 2,853 were recruited by respondent-driven sampling from an urban area with elevated poverty rates, and completed a structured assessment battery covering sociodemographics, syndemic factors (that is, multiple, co-occurring risk factors, and substance use. More than one-third of participants (36% met criteria for either an alcohol or a drug problem in the past year. Latent class analysis identified profiles of risk and resilience, separately for women and men, which were associated with the probability of a substance use problem. Almost a third of women (27% and 38% of men had lower risk profiles—patterns of resilience not apparent in other types of analyses. Profiles with more risk and fewer resilience factors were associated with an increased probability of substance use problems, but profiles with fewer risk and more resilience factors had rates of substance use problems that were very similar to the general adult population. Relative to the lowest risk profile, profiles with the most risk and fewest resilience factors were associated with increased odds of a substance use problem for both women [adjusted odds ratio (aOR = 8.50; 95% CI: 3.85–18.74] and men (aOR = 11.68; 95% CI: 6.91–19.74. Addressing syndemic factors in substance use treatment and prevention may yield improved outcomes.

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

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    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.

  13. What Constitutes High-Quality Implementation of SEL Programs? A Latent Class Analysis of Second Step® Implementation.

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    Low, Sabina; Smolkowski, Keith; Cook, Clay

    2016-11-01

    With the increased number of schools adopting social-emotional learning (SEL) programming, there is increased emphasis on the role of implementation in obtaining desired outcomes. Despite this, the current knowledge of the active ingredients of SEL programming is lacking, and there is a need to move from a focus on "whether" implementation matters to "what" aspects of implementation matter. To address this gap, the current study utilizes a latent class approach with data from year 1 of a randomized controlled trial of Second Step® (61 schools, 321 teachers, over 7300 students). Latent classes of implementation were identified, then used to predict student outcomes. Teachers reported on multiple dimensions of implementation (adherence, dosage, competency), as well as student outcomes. Observational data were also used to assess classroom behavior (academic engagement and disruptive behavior). Results suggest that a three-class model fits the data best, labeled as high-quality, low-engagement, and low-adherence classes. Only the low-engagement class showed significant associations with poorer outcomes, when compared to the high-quality class (not the low-adherence class). Findings are discussed in terms of implications for program development and implementation science more broadly.

  14. Family Functioning and Parent Support Trajectories and Substance Use and Misuse among Minority Urban Adolescents: A Latent Class Growth Analysis

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    Cordova, David; Heinze, Justin; Mistry, Ritesh; Hsieh, Hsing-Fang; Stoddard, Sarah; Salas-Wright, Christopher P.; Zimmerman, Marc A

    2014-01-01

    We sought to examine latent classes of family functioning and parent support trajectories during high school and whether these trajectories are associated with an increased risk of substance use and misuse among urban youth. A total of 850 adolescents (Mage = 15.1 years) were included in this study, assessed at baseline, 12-, 24-, and 36-months postbaseline, and completed self-report measures on past 30-day alcohol and marijuana use, binge drinking, and measures of family functioning and parent support. Latent class growth analysis revealed that trajectories of high family functioning and parent support are associated with a decreased risk of marijuana use. Findings may be helpful to inform family-based preventive interventions. PMID:25033377

  15. Patterns of relationship and sexual behaviors in Mexican adolescents and associations with well-being: A latent class approach.

    Science.gov (United States)

    Espinosa-Hernández, Graciela; Vasilenko, Sara A

    2015-10-01

    To broaden our understanding of romance and sexuality during adolescence in Latin American countries, we used a person-oriented approach (latent class analysis) to examine classes marked by different patterns of romantic and sexual behaviors in Mexican adolescents. We found 5 classes: Inactive (8.53%), Early stage (37.8%), Waiting class (27.5%), Physical (8.4%) and Committed (17.9%); but no group dating class. We also explored how these classes were associated with adolescents' mental health and school performance. Middle school adolescents in the Committed class (high in romantic and sexual behaviors) had the highest level of depressive symptoms. Girls in the Inactive class and boys in the Physical class had the lowest level of symptoms. Adolescents in the Committed class also reported less academic motivation and achievement, whereas adolescents in the Inactive class reported higher motivation. This study expands our knowledge of adolescent romantic and sexual development in Mexico. Copyright © 2015 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

  16. Implicit and explicit drinking identity predict latent classes that differ on the basis of college students' drinking behaviors.

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    Ramirez, Jason J; Fairlie, Anne M; Olin, Cecilia C; Lindgren, Kristen P

    2017-09-01

    The purpose of this study was to identify distinct classes of college students on the basis of recent and past drinking behaviors and evaluate how implicit and explicit measures of drinking identity predict membership in these classes. US undergraduate students (N=456) completed online implicit (Implicit Association Test) and explicit (self-report) measures of drinking identity and assessments of drinking behaviors, including past month drinking, at-risk drinking in the past year, and lifetime history of intoxication. Latent class analysis (LCA) was used to identify classes of college students based on their drinking behaviors. LCA identified five classes: (1) Lifetime Nondrinker, (2) Recent Nondrinker/Past Risk, (3) Light Drinker, (4) Moderate Drinker, and (5) Heavy Drinker. Overall, stronger implicit and explicit drinking identities were uniquely associated with greater odds of belonging to classes with greater alcohol consumption and related consequences relative to those classes characterized by lower alcohol consumption and consequences. Notably, explicit drinking identity was positively associated with odds of membership to the Recent Nondrinker/Past Risk class relative to the Lifetime Nondrinker and Light Drinker classes, and implicit and explicit drinking identities were positively associated with odds of membership to the Heavy Drinker class relative to all other classes. Findings suggest that drinking identity is sensitive to risky drinking experiences in the past, is especially strong among the highest-risk group of college student drinkers, and may be an important cognitive factor to consider as a target for intervention. Copyright © 2017 Elsevier B.V. All rights reserved.

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

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    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 (P<.001). Fluctuating fall risk (posterior probability <0.8 of belonging to any trajectory) was found in only 22.6% of the sample, most commonly among individuals who were transitioning to PIGD predominance. Regardless of their baseline characteristics, most participants had clear and stable 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.

  18. Latent class analysis of diagnostic tests for visceral leishmaniasis in Brazil.

    Science.gov (United States)

    Machado de Assis, Tália Santana; Rabello, Ana; Werneck, Guilherme Loureiro

    2012-10-01

    To estimate the sensitivities and specificities of different diagnostic tests for visceral leishmaniasis (VL) using latent class analysis (LCA).   This study was performed using data from a prospective study conducted in four Brazilian states from May 2004 to May 2007. Five diagnostic tests for VL were evaluated in 285 VL cases and 119 non-cases: microscopy, indirect fluorescence antibody test (IFAT), enzyme-linked immunosorbent assay using recombinant K39 antigen (rK39-ELISA), direct agglutination test (DAT) and the rK39 rapid test. Microscopy showed sensitivity of 77.0% (CI: 71.5-81.5) and specificity of 99.0% (CI: 94.0-99.7). The IFAT and the DAT showed similar sensitivities, 88.3% (CI: 84.0-92.0) and 88.5% (CI: 84.1-92.0), respectively, but the DAT had a higher specificity (95.4%, CI: 89.2-98.1) than did the IFAT (83.0%, CI: 75.0-88.2). The rK39-ELISA and the rK39 rapid test showed sensitivities of 99.0% (CI: 96.3-99.6) and 94.0% (CI: 90.1-96.3), and specificities of 82.5% (CI: 75.0-88.3) and 100% (CI: 97.0-100.0%), respectively. Considering the lack of an adequate reference standard, LCA proved to be a useful tool in validating diagnostic methods for VL. The DAT and the rK39 rapid test showed better performance. Thus, clinically suspected cases of VL in a Brazilian endemic area could be treated based on the positivity of one of these tests. © 2012 Blackwell Publishing Ltd.

  19. Defining the true sensitivity of culture for the diagnosis of melioidosis using Bayesian latent class models.

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    Direk Limmathurotsakul

    Full Text Available BACKGROUND: Culture remains the diagnostic gold standard for many bacterial infections, and the method against which other tests are often evaluated. Specificity of culture is 100% if the pathogenic organism is not found in healthy subjects, but the sensitivity of culture is more difficult to determine and may be low. Here, we apply Bayesian latent class models (LCMs to data from patients with a single Gram-negative bacterial infection and define the true sensitivity of culture together with the impact of misclassification by culture on the reported accuracy of alternative diagnostic tests. METHODS/PRINCIPAL FINDINGS: Data from published studies describing the application of five diagnostic tests (culture and four serological tests to a patient cohort with suspected melioidosis were re-analysed using several Bayesian LCMs. Sensitivities, specificities, and positive and negative predictive values (PPVs and NPVs were calculated. Of 320 patients with suspected melioidosis, 119 (37% had culture confirmed melioidosis. Using the final model (Bayesian LCM with conditional dependence between serological tests, the sensitivity of culture was estimated to be 60.2%. Prediction accuracy of the final model was assessed using a classification tool to grade patients according to the likelihood of melioidosis, which indicated that an estimated disease prevalence of 61.6% was credible. Estimates of sensitivities, specificities, PPVs and NPVs of four serological tests were significantly different from previously published values in which culture was used as the gold standard. CONCLUSIONS/SIGNIFICANCE: Culture has low sensitivity and low NPV for the diagnosis of melioidosis and is an imperfect gold standard against which to evaluate alternative tests. Models should be used to support the evaluation of diagnostic tests with an imperfect gold standard. It is likely that the poor sensitivity/specificity of culture is not specific for melioidosis, but rather a generic

  20. Estimating the true accuracy of diagnostic tests for dengue infection using bayesian latent class models.

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    Wirichada Pan-ngum

    Full Text Available Accuracy of rapid diagnostic tests for dengue infection has been repeatedly estimated by comparing those tests with reference assays. We hypothesized that those estimates might be inaccurate if the accuracy of the reference assays is not perfect. Here, we investigated this using statistical modeling.Data from a cohort study of 549 patients suspected of dengue infection presenting at Colombo North Teaching Hospital, Ragama, Sri Lanka, that described the application of our reference assay (a combination of Dengue IgM antibody capture ELISA and IgG antibody capture ELISA and of three rapid diagnostic tests (Panbio NS1 antigen, IgM antibody and IgG antibody rapid immunochromatographic cassette tests were re-evaluated using bayesian latent class models (LCMs. The estimated sensitivity and specificity of the reference assay were 62.0% and 99.6%, respectively. Prevalence of dengue infection (24.3%, and sensitivities and specificities of the Panbio NS1 (45.9% and 97.9%, IgM (54.5% and 95.5% and IgG (62.1% and 84.5% estimated by bayesian LCMs were significantly different from those estimated by assuming that the reference assay was perfect. Sensitivity, specificity, PPV and NPV for a combination of NS1, IgM and IgG cassette tests on admission samples were 87.0%, 82.8%, 62.0% and 95.2%, respectively.Our reference assay is an imperfect gold standard. In our setting, the combination of NS1, IgM and IgG rapid diagnostic tests could be used on admission to rule out dengue infection with a high level of accuracy (NPV 95.2%. Further evaluation of rapid diagnostic tests for dengue infection should include the use of appropriate statistical models.

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

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    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.

  2. Neuropsychological syndromes associated with Alzheimer's/vascular dementia: a latent class analysis.

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    Libon, David J; Drabick, Deborah A G; Giovannetti, Tania; Price, Catherine C; Bondi, Mark W; Eppig, Joel; Devlin, Kathryn; Nieves, Christine; Lamar, Melissa; Delano-Wood, Lisa; Nation, Daniel A; Brennan, Laura; Au, Rhoda; Swenson, Rod

    2014-01-01

    Epidemiologic autopsy studies show mixed Alzheimer's disease (AD)/vascular pathology in many patients. Moreover, clinical research shows that it is not uncommon for AD and vascular dementia (VaD) patients to be equally impaired on memory, executive, or other neurocognitive tests. However, this clinical heterogeneity has not been incorporated into the new diagnostic criteria for AD (Dubois et al., 2010; McKhann et al., 2011). The current research applied Latent Class Analysis (LCA) to a protocol of six neuropsychological parameters to identify phenotypic subtypes from a large group of AD/VaD participants. Follow-up analyses examined difference between groups on neuroradiological parameters and neuropsychological measures of process and errors. 223 AD/VaD patients were administered a comprehensive neuropsychological protocol. Measures of whole brain and hippocampal volume were available for a portion of the sample (n = 76). LCA identified four distinct groups: moderate/mixed dementia (n = 54; 24.21%), mild/mixed dementia (n = 91; 40.80%); dysexecutive (n = 49, 21.97%), and amnestic (n = 29, 13.00%). Follow-up analyses comparing the groups on neuropsychological process and error scores showed that the dysexecutive group exhibited difficulty sustaining mental set. The moderate/mixed group evidenced pronounced impairment on tests of lexical retrieval/naming along with significant amnesia. Amnestic patients also presented with gross amnesia, but showed relative sparing on other neuropsychological measures. Mild/mixed patients exhibited milder memory deficits that were intermediary between the amnestic and moderate/mixed groups. There are distinct neuropsychological profiles in patients independent of clinical diagnosis, suggesting that the two are not wholly separate and that this information should be integrated into new AD diagnostic paradigms.

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

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    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

  4. Diagnostic performance of various tests and criteria employed in allergic bronchopulmonary aspergillosis: a latent class analysis.

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    Ritesh Agarwal

    Full Text Available AIM: The efficiency of various investigations and diagnostic criteria used in diagnosis of allergic bronchopulmonary aspergillosis (ABPA remain unknown, primarily because of the lack of a gold standard. Latent class analysis (LCA can provide estimates of sensitivity and specificity in absence of gold standard. Herein, we report the performance of various investigations and criteria employed in diagnosis of ABPA. METHODS: Consecutive subjects with asthma underwent all the following investigations Aspergillus skin test, IgE levels (total and A.fumigatus specific, Aspergillus precipitins, eosinophil count, chest radiograph, and high-resolution computed tomography (HRCT of the chest. We used LCA to estimate the performance of various diagnostic tests and criteria in identification of ABPA. RESULTS: There were 372 asthmatics with a mean age of 35.9 years. The prevalence of Aspergillus sensitization was 53.2%. The sensitivity and specificity of various tests were Aspergillus skin test positivity (94.7%, 79.7%; IgE levels>1000 IU/mL (97.1%, 37.7%; A.fumigatus specific IgE levels>0.35 kUA/L (100%, 69.3%; Aspergillus precipitins (42.7%, 97.1%; eosinophil count>1000 cells/µL (29.5%, 93.1%; chest radiographic opacities (36.1%, 92.5%; bronchiectasis (91.9%, 80.9%; and, high-attenuation mucus (39.7%, 100%. The most accurate criteria was the Patterson criteria using six components followed by the Agarwal criteria. However, there was substantial decline in accuracy of the Patterson criteria if components of the criteria were either increased or decreased from six. CONCLUSIONS: A.fumigatus specific IgE levels and high-attenuation mucus were found to be the most sensitive and specific test respectively in diagnosis of ABPA. The Patterson criteria remain the best diagnostic criteria however they have good veridicality only if six criteria are used.

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

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    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

  6. Patterns of HIV Risks and Related Factors among People Who Inject Drugs in Kermanshah, Iran: A Latent Class Analysis.

    Science.gov (United States)

    Sharifi, Hamid; Mirzazadeh, Ali; Noroozi, Alireza; Marshall, Brandon D L; Farhoudian, Ali; Higgs, Peter; Vameghi, Meroe; Mohhamadi Shahboulaghi, Farahnaz; Qorbani, Mostafa; Massah, Omid; Armoon, Bahram; Noroozi, Mehdi

    2017-01-01

    The objective of this study was to explore patterns of drug use and sexual risk behaviors among people who inject drugs (PWID) in Iran. We surveyed 500 PWID in Kermanshah concerning demographic characteristics, sexual risk behaviors, and drug-related risk behaviors in the month prior to study. We used latent class analysis (LCA) to establish a baseline model of risk profiles and to identify the optimal number of latent classes, and we used ordinal regression to identify factors associated with class membership. Three classes of multiple HIV risk were identified. The probability of membership in the high-risk class was 0.33, compared to 0.26 and 0.40 for the low- and moderate-risk classes, respectively. Compared to members in the lowest-risk class (reference group), the highest-risk class members had higher odds of being homeless (OR = 4.5, CI: 1.44-8.22; p = 0.001) in the past 12 months. Members of the high-risk class had lower odds of regularly visiting a needle and syringe exchange program as compared to the lowest-risk class members (AOR = 0.42, CI: 0.2-0.81; p = 0.01). Findings show the sexual and drug-related HIV risk clusters among PWID in Iran, and emphasize the importance of developing targeted prevention and harm reduction programs for all domains of risk behaviors, both sexual and drug use related.

  7. Exploring symptoms of somatization in chronic widespread pain: latent class analysis and the role of personality

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    Burri A

    2017-07-01

    Full Text Available Andrea Burri,1,2 Peter Hilpert,3 Peter McNair,1 Frances M Williams4 1Health and Rehabilitation Research Institute, School of Clinical Sciences, Faculty of Health and Environmental Sciences, Auckland University of Technology, 2Waitemata Pain Service, Department of Anaesthesiology and Perioperative Medicine, North Shore Hospital, Auckland, New Zealand; 3Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, USA; 4Department of Twin Research and Genetic Epidemiology, King’s College London, London, UK Abstract: Chronic widespread musculoskeletal pain (CWP is a condition manifesting varied co-symptomatology and considerable heterogeneity in symptom profiles. This poses an obstacle for disease definition and effective treatment. Latent class analysis (LCA provides an opportunity to find subtypes of cases in multivariate data. In this study, LCA was used to investigate whether and how individuals with CWP could be classified according to 12 additional somatic symptoms (migraine headaches, insomnia, stiffness, etc.. In a second step, the role of psychological and coping factors for the severity of these co-symptoms was investigated. Data were available for a total of N = 3,057 individuals (mean age = 56.6 years, with 15.4% suffering from CWP. In the latter group, LCA resulted in a three-class solution (ngroup1 = 123; ngroup2 = 306; ngroup3 = 43 with groups differing in a graded fashion (i.e., severity rather than qualitatively for somatic co-symptom endorsements. A consistent picture emerged, with individuals in the first group reporting the lowest scores and individuals in group 3 reporting the highest. Additionally, more co-symptomatology was associated with higher rates of anxiety sensitivity and depression, as well as more extraversion and emotional instability. No group differences for any of the coping strategies could be identified. The findings suggest that CWP has several detectable subtypes with distinct

  8. Diversity of users in banking agencies: An analysis of latent classes, Libertador municipality, Mérida state, Venezuela

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    Marysela Morillo Moreno

    2015-09-01

    Full Text Available To determine the existence of different groups of users of personal services of the banking agencies, based on demographic, psychographic and behavioral characteristics, field research was designed, based on random sampling, in the Libertador municipality of Merida state, Venezuela. As finding, a statistical analysis of latent classes highlights the existence of three classes of users; the kind that brings the largest number of users is characterized by a moderate frequency of use and perception over quality. The identification of such groups precedes the design of marketing practices for each segment, particulary for handling waiting times, service quality recovery.

  9. Predicting healthy lifestyle patterns among retirement age older adults in the WELL study: a latent class analysis of sex differences.

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    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.

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

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    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.

  11. Latent classes of childhood poly-victimization and associations with suicidal behavior among adult trauma victims: Moderating role of anger.

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    Charak, Ruby; Byllesby, Brianna M; Roley, Michelle E; Claycomb, Meredith A; Durham, Tory A; Ross, Jana; Armour, Cherie; Elhai, Jon D

    2016-12-01

    The aims of the present study were first to identify discrete patterns of childhood victimization experiences including crime, child maltreatment, peer/sibling victimization, sexual violence, and witnessing violence among adult trauma victims using latent class analysis; second, to examine the association between class-membership and suicidal behavior, and third to investigate the differential role of dispositional anger on the association between class-membership and suicidal behavior. We hypothesized that those classes with accumulating exposure to different types of childhood victimization (e.g., poly-victimization) would endorse higher suicidal behavior, than the other less severe classes, and those in the most severe class with higher anger trait would have stronger association with suicidal behavior. Respondents were 346 adults (N=346; Mage=35.0years; 55.9% female) who had experienced a lifetime traumatic event. Sixty four percent had experienced poly-victimization (four or more victimization experiences) and 38.8% met the cut-off score for suicidal behavior. Three distinct classes emerged namely, the Least victimization (Class 1), the Predominantly crime and sibling/peer victimization (Class 2), and the Poly-victimization (Class 3) classes. Regression analysis controlling for age and gender indicated that only the main effect of anger was significantly associated with suicidal behavior. The interaction term suggested that those in the Poly-victimization class were higher on suicidal behavior as a result of a stronger association between anger and suicidal behavior in contrast to the association found in Class 2. Clinical implications of findings entail imparting anger management skills to facilitate wellbeing among adult with childhood poly-victimization experiences. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

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    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

  13. Evaluating diagnostic tests for bovine tuberculosis in the southern part of Germany: A latent class analysis

    Science.gov (United States)

    Knubben-Schweizer, Gabriela; Döpfer, Dörte; Groll, Andreas; Hafner-Marx, Angela; Hörmansdorfer, Stefan; Sauter-Louis, Carola; Straubinger, Reinhard K.; Zimmermann, Pia; Hartnack, Sonja

    2017-01-01

    Germany has been officially free of bovine tuberculosis since 1996. However, in the last years there has been an increase of bovine tuberculosis cases, particularly in the southern part of Germany, in the Allgäu region. As a consequence a one-time tuberculosis surveillance program was revisited with different premortal and postmortal tests. The aim of this paper was to estimate diagnostic sensitivities and specificities of the different tests used within this surveillance program. In the absence of a perfect test with 100% sensitivity and 100% specificity, thus in the absence of a gold standard, a Bayesian latent class approach with two different datasets was performed. The first dataset included 389 animals, tested with single intra-dermal comparative cervical tuberculin (SICCT) test, PCR and pathology; the second dataset contained 175 animals, tested with single intra-dermal cervical tuberculin (SICT) test, Bovigam® assay, pathology and culture. Two-way conditional dependencies were considered within the models. Additionally, inter-laboratory agreement (five officially approved laboratories) of the Bovigam® assay was assessed with Cohen's kappa test (21 blood samples). The results are given in posterior means and 95% credibility intervals. The specificities of the SICT test, SICCT test, PCR and pathology ranged between 75.8% [68.8–82.2%] and 99.0% [96.8–100%]. The Bovigam® assay stood out with a very low specificity (6.9% [3.6–11.1%]), though it had the highest sensitivity (95.7% [91.3–99.2%]). The sensitivities of the SICCT test, PCR, SICT test, pathology and culture varied from 57.8% [48.0–67.6%] to 88.9% [65.5–99.7%]. The prevalences were 19.8% [14.6–26.5%] (three-test dataset) and 7.7% [4.2–12.3%] (four-test dataset). Among all pairwise comparisons the highest agreement was 0.62 [0.15–1]). In conclusion, the specificity of the Bovigam® assay and the inter-laboratory agreement were lower than expected. PMID:28640908

  14. Distinct Classes of Negative Alcohol-Related Consequences in a National Sample of Incoming First-Year College Students: A Latent Class Analysis.

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    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.

  15. Gradient of association between parenting styles and patterns of drug use in adolescence: A latent class analysis.

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    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.

  16. The co-occurrence of adverse childhood experiences among children investigated for child maltreatment: A latent class analysis.

    Science.gov (United States)

    Brown, Samantha M; Rienks, Shauna; McCrae, Julie S; Watamura, Sarah E

    2017-11-22

    Children investigated for maltreatment are particularly vulnerable to experiencing multiple adversities. Few studies have examined the extent to which experiences of adversity and different types of maltreatment co-occur in this most vulnerable population of children. Understanding the complex nature of childhood adversity may inform the enhanced tailoring of practices to better meet the needs of maltreated children. Using cross-sectional data from the National Survey of Child and Adolescent Well-Being II (N=5870), this study employed latent class analysis to identify subgroups of children who had experienced multiple forms of maltreatment and associated adversities among four developmental stages: birth to 23 months (infants), 2-5 (preschool age), 6-10 (school age), and 11-18 years-old (adolescents). Three latent classes were identified for infants, preschool-aged children, and adolescents, and four latent classes were identified for school-aged children. Among infants, the groups were characterized by experiences of (1) physical neglect/emotional abuse/caregiver treated violently, (2) physical neglect/household dysfunction, and (3) caregiver divorce. For preschool-aged children, the groups included (1) physical neglect/emotional abuse/caregiver treated violently, (2) physical neglect/household dysfunction, and (3) emotional abuse. Children in the school-age group clustered based on experiencing (1) physical neglect/emotional neglect and abuse/caregiver treated violently, (2) physical neglect/household dysfunction, (3) emotional abuse, and (4) emotional abuse/caregiver divorce. Finally, adolescents were grouped based on (1) physical neglect/emotional abuse/household dysfunction, (2) physical abuse/emotional abuse/household dysfunction, and (3) emotional abuse/caregiver divorce. The results indicate distinct classes of adversity experienced among children investigated for child maltreatment, with both stability across developmental periods and unique age

  17. Heterogeneity of alcohol, tobacco, and other substance use behaviors in U.S. college students: A latent class analysis.

    Science.gov (United States)

    Evans-Polce, Rebecca; Lanza, Stephanie; Maggs, Jennifer

    2016-02-01

    To identify subgroups of college students with distinct profiles of traditional and alternative types of tobacco, alcohol, and other substance use and to examine how demographic characteristics and academic and social activities are associated with subgroup membership. We used latent class analysis to characterize subgroups of individuals in their fourth-year of college based on their patterns of seven substance use behaviors: extreme heavy episodic drinking (HED), cigarette use, cigar/cigarillo/little cigar use, smokeless tobacco use, hookah use, marijuana use, and non-medical prescription drug use. Demographic characteristics and academic and social activities were then incorporated as predictors of these latent classes. We identified five classes defined by unique behavior patterns: (1) Non/Low Users, (2) Non-Hookah Tobacco Users, (3) Extreme HED & Marijuana Users, (4) Hookah and Marijuana Users, and (5) Poly-Substance Users. Being male, older, and involved in sports were associated with greater odds of being in the Poly-Substance User class compared to the Low/No User class, and participating in an honors society and reporting more positive peer relationships were associated with being in the Hookah and Marijuana User class compared to the Low/No User class. Our findings of unique characteristics in the subgroups identified suggest that college substance users are a heterogeneous population requiring different targeted interventions. Of particular concern are subgroups with high rates of alternative tobacco products, as perceived risks of use may be inaccurate and this is not currently a focus of college substance use prevention interventions. Copyright © 2015 Elsevier Ltd. All rights reserved.

  18. Longitudinal Patterns of Stages of Change for Exercise and Lifestyle Intervention Outcomes: An Application of Latent Class Analysis with Distal Outcomes.

    Science.gov (United States)

    Jiang, Luohua; Chen, Shuai; Zhang, Ben; Beals, Janette; Mitchell, Christina M; Manson, Spero M; Roubideaux, Yvette

    2016-04-01

    Stages of change measure an individual's readiness to alter a health behavior. This study examined the latent longitudinal patterns of stages of change (SoC) for regular exercise over time among individuals participating in a lifestyle intervention project. It also investigated the association between the longitudinal patterns of SoC and intervention outcomes using a new statistical method to assess the relationship between latent class membership and distal outcomes. We analyzed data from the Special Diabetes Program for Indians Diabetes Prevention Program, a lifestyle intervention program to prevent diabetes among American Indians and Alaska Natives. Latent class analysis (LCA) was conducted to identify the longitudinal patterns of SoC for regular exercise reported at three time points. LCA with distal outcomes was performed to investigate the associations between latent class membership and behavioral changes after the intervention. The parameters and standard errors of the LCA with distal outcomes models were estimated using an improved three-step approach. Three latent classes were identified: Pre-action, Transition, and Maintenance classes. The Transition class, where stage progression occurred, had the greatest improvements in physical activity and weight outcomes at both time points post-baseline among female participants. It also had the largest improvements in weight outcomes among male participants. Furthermore, the Pre-action class had more attenuation in the improvements they had achieved initially than the other two classes. These findings suggest the potential importance of motivating participants to modify their readiness for behavioral change in future lifestyle interventions.

  19. A latent class analysis of DSM-IV alcohol use disorder criteria and binge drinking in undergraduates.

    Science.gov (United States)

    Beseler, Cheryl L; Taylor, Laura A; Kraemer, Deborah T; Leeman, Robert F

    2012-01-01

    Adolescent and adult samples have shown that the Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV) abuse and dependence criteria lie on a continuum of alcohol problem severity, but information on criteria functioning in college students is lacking. Prior factor analyses in a college sample (Beseler et al., 2010) indicated that a 2-factor solution fit the data better than a single-factor solution after a binge drinking criterion was included. The second dimension may indicate a clustering of criteria related to excessive alcohol use in this college sample. The present study was an analysis of data from an anonymous, online survey of undergraduates (N = 361) that included items pertaining to the DSM-IV alcohol use disorder (AUD) diagnostic criteria and binge drinking. Latent class analysis (LCA) was used to determine whether the criteria best fit a categorical model, with and without a binge drinking criterion. In an LCA including the AUD criteria only, a 3-class solution was the best fit. Binge drinking worsened the fit of the models. The largest class (class 1, n = 217) primarily endorsed tolerance (18.4%); none were alcohol dependent. The middle class (class 2, n = 114) endorsed primarily tolerance (81.6%) and drinking more than intended (74.6%); 34.2% met criteria for dependence. The smallest class (class 3, n = 30) endorsed all criteria with high probabilities (30 to 100%); all met criteria for dependence. Alcohol consumption patterns did not differ significantly between classes 2 and 3. Class 3 was characterized by higher levels on several variables thought to predict risk of alcohol-related problems (e.g., enhancement motives for drinking, impulsivity, and aggression). Two classes of heavy-drinking college students were identified, one of which appeared to be at higher risk than the other. The highest risk group may be less likely to "mature out" of high-risk drinking after college. Copyright © 2011 by the Research Society on Alcoholism.

  20. 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.

  1. Violence against Congolese refugee women in Rwanda and mental health: a cross-sectional study using latent class analysis

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    Sipsma, Heather L; Falb, Kathryn L; Willie, Tiara; Bradley, Elizabeth H; Bienkowski, Lauren; Meerdink, Ned; Gupta, Jhumka

    2015-01-01

    Objective To examine patterns of conflict-related violence and intimate partner violence (IPV) and their associations with emotional distress among Congolese refugee women living in Rwanda. Design Cross-sectional study. Setting Two Congolese refugee camps in Rwanda. Participants 548 ever-married Congolese refugee women of reproductive age (15–49 years) residing in Rwanda. Primary outcome measure Our primary outcome was emotional distress as measured using the Self-Report Questionnaire-20 (SRQ-20). For analysis, we considered participants with scores greater than 10 to be experiencing emotional distress and participants with scores of 10 or less not to be experiencing emotional distress. Results Almost half of women (49%) reported experiencing physical, emotional or sexual violence during the conflict, and less than 10% of women reported experiencing of any type of violence after fleeing the conflict. Lifetime IPV was reported by approximately 22% of women. Latent class analysis derived four distinct classes of violence experiences, including the Low All Violence class, the High Violence During Conflict class, the High IPV class and the High Violence During and After Conflict class. In multivariate regression models, latent class was strongly associated with emotional distress. Compared with women in the Low All Violence class, women in the High Violence During and After Conflict class and women in the High Violence During Conflict had 2.7 times (95% CI 1.11 to 6.74) and 2.3 times (95% CI 1.30 to 4.07) the odds of experiencing emotional distress in the past 4 weeks, respectively. Furthermore, women in the High IPV class had a 4.7 times (95% CI 2.53 to 8.59) greater odds of experiencing emotional distress compared with women in the Low All Violence class. Conclusions Experiences of IPV do not consistently correlate with experiences of conflict-related violence, and women who experience high levels of IPV may have the greatest likelihood for poor mental health

  2. Knowledge and Attitudes towards Antibiotic Use and Resistance - A Latent Class Analysis of a Swedish Population-Based Sample

    Science.gov (United States)

    Rosales-Klintz, Senia; Tegmark Wisell, Karin; Stålsby Lundborg, Cecilia

    2016-01-01

    Background 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. Objective (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. Methods 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. Results 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. Conclusion 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. PMID:27096751

  3. 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.

  4. Marijuana Use Patterns among African-American Middle-School Students: A Longitudinal Latent Class Regression Analysis

    OpenAIRE

    Reboussin, Beth A.; Hubbard, Scott; Ialongo, Nicholas S.

    2007-01-01

    The aim of this paper was to describe patterns of marijuana involvement during the middle-school years from the first chance to try marijuana down through the early stages of experiencing health and social problems from marijuana use in a sample of African-American adolescents. A total of 488 urban-dwelling African-American middle-school students were interviewed in sixth, seventh and eighth grades as part of a longitudinal field study. Longitudinal latent class models were used to identify s...

  5. 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.

  6. 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.

  7. 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

  8. Application of Fractal theory for crash rate prediction: Insights from random parameters and latent class tobit models.

    Science.gov (United States)

    Chand, Sai; Dixit, Vinayak V

    2018-01-04

    The repercussions from congestion and accidents on major highways can have significant negative impacts on the economy and environment. It is a primary objective of transport authorities to minimize the likelihood of these phenomena taking place, to improve safety and overall network performance. In this study, we use the Hurst Exponent metric from Fractal Theory, as a congestion indicator for crash-rate modeling. We analyze one month of traffic speed data at several monitor sites along the M4 motorway in Sydney, Australia and assess congestion patterns with the Hurst Exponent of speed (Hspeed). Random Parameters and Latent Class Tobit models were estimated, to examine the effect of congestion on historical crash rates, while accounting for unobserved heterogeneity. Using a latent class modeling approach, the motorway sections were probabilistically classified into two segments, based on the presence of entry and exit ramps. This will allow transportation agencies to implement appropriate safety/traffic countermeasures when addressing accident hotspots or inadequately managed sections of motorway. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. A latent class analysis of stigmatizing attitudes and knowledge of HIV risk among youth in South Africa.

    Directory of Open Access Journals (Sweden)

    Lauren Brinkley-Rubinstein

    Full Text Available BACKGROUND: The current study aims to investigate how the ability to accurately gauge risk factors associated with contracting HIV while taking into consideration various individual and community level socio-demographic characteristics (e.g., race and poverty predicts the nature of stigmatizing attitudes toward persons with HIV. METHODS: Data from a sample of 1,347 Cape Town area youth who participated in the Cape Area Panel Study (CAPS Wave 2a were used. Latent Class Analysis was conducted to ascertain whether response patterns regarding knowledge of HIV contraction suggest the presence of subgroups within the sample. RESULTS: Findings indicate that there are four latent classes representing unique response pattern profiles regarding knowledge of HIV contraction. Additionally, our results suggest that those in South Africa who are classified as "white," live in more affluent communities, and have more phobic perceptions of HIV risk are also more likely to have the most stigmatizing attitudes toward those who are HIV positive. CONCLUSION: Implications of these findings include extending HIV knowledge, education, and awareness programs to those who are not traditionally targeted in an attempt to increase levels of knowledge about HIV and, consequently, decrease stigma.

  10. A latent class analysis of stigmatizing attitudes and knowledge of HIV risk among youth in South Africa.

    Science.gov (United States)

    Brinkley-Rubinstein, Lauren; Craven, Krista

    2014-01-01

    The current study aims to investigate how the ability to accurately gauge risk factors associated with contracting HIV while taking into consideration various individual and community level socio-demographic characteristics (e.g., race and poverty) predicts the nature of stigmatizing attitudes toward persons with HIV. Data from a sample of 1,347 Cape Town area youth who participated in the Cape Area Panel Study (CAPS) Wave 2a were used. Latent Class Analysis was conducted to ascertain whether response patterns regarding knowledge of HIV contraction suggest the presence of subgroups within the sample. Findings indicate that there are four latent classes representing unique response pattern profiles regarding knowledge of HIV contraction. Additionally, our results suggest that those in South Africa who are classified as "white," live in more affluent communities, and have more phobic perceptions of HIV risk are also more likely to have the most stigmatizing attitudes toward those who are HIV positive. Implications of these findings include extending HIV knowledge, education, and awareness programs to those who are not traditionally targeted in an attempt to increase levels of knowledge about HIV and, consequently, decrease stigma.

  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. Maltreatment and Mental Health Outcomes among Ultra-Poor Children in Burkina Faso: A Latent Class Analysis.

    Directory of Open Access Journals (Sweden)

    Leyla Ismayilova

    Full Text Available 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

  13. 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

  14. Taking an intersectional approach to define latent classes of socioeconomic status, ethnicity and migration status for psychiatric epidemiological research.

    Science.gov (United States)

    Goodwin, L; Gazard, B; Aschan, L; MacCrimmon, S; Hotopf, M; Hatch, S L

    2017-04-09

    Inequalities in mental health are well documented using individual social statuses such as socioeconomic status (SES), ethnicity and migration status. However, few studies have taken an intersectional approach to investigate inequalities in mental health using latent class analysis (LCA). This study will examine the association between multiple indicator classes of social identity with common mental disorder (CMD). Data on CMD symptoms were assessed in a diverse inner London sample of 1052 participants in the second wave of the South East London Community Health study. LCA was used to define classes of social identity using multiple indicators of SES, ethnicity and migration status. Adjusted associations between CMD and both individual indicators and multiple indicators of social identity are presented. LCA identified six groups that were differentiated by varying levels of privilege and disadvantage based on multiple SES indicators. This intersectional approach highlighted nuanced differences in odds of CMD, with the economically inactive group with multiple levels of disadvantage most likely to have a CMD. Adding ethnicity and migration status further differentiated between groups. The migrant, economically inactive and White British, economically inactive classes both had increased odds of CMD. This is the first study to examine the intersections of SES, ethnicity and migration status with CMD using LCA. Results showed that both the migrant, economically inactive and the White British, economically inactive classes had a similarly high prevalence of CMD. Findings suggest that LCA is a useful methodology for investigating health inequalities by intersectional identities.

  15. Polysubstance Use Among Adolescents in a Low Income, Rural Community: Latent Classes for Middle- and High-School Students.

    Science.gov (United States)

    Rose, Roderick A; Evans, Caroline B R; Smokowski, Paul R; Howard, Matthew O; Stalker, Katie L

    2017-09-18

    Rural communities are currently being impacted by a nationwide epidemic of prescription opioid misuse. Rural adolescent substance users may be at substantial risk for later addiction to these and other drugs. This study uses Latent Class Analysis to identify subtypes of polysubstance users among a sample of 7,074 rural adolescents. Separate models were estimated for middle- and high-school youth. Predictive validity was estimated using cumulative ordinal logistic regression of the classes on a set of youth and family characteristics. We identified a 4-class solution for both middle- and high-school students marked by initiation of an increasing number of substances used at greater frequency. These classes included Substance Nonusers, Primarily Alcohol Users, Initiators-Low Frequency Users, and Initiators-Moderate-to-High Lifetime Frequency Users. About 6%-10% of youth reported using prescription drugs at least once, and in the moderate-to-high frequency class, middle-school youth were more likely to use prescription drugs and inhalants compared to high-school youth in the same class. The 4 classes were associated with race/ethnicity, and in high school with receiving free/reduced price lunch. In general, younger adolescents have lower overall use rates, but within certain classes identified by this analysis, the observed pattern suggests that younger cohorts are turning to prescription drugs and inhalants. These findings support the implementation of universal substance use prevention programs, targeted programs for youth experiencing risk factors associated with substance use, and improved rural substance abuse treatment options. © 2017 National Rural Health Association.

  16. Longitudinal patterns of stages of change for exercise and lifestyle intervention outcomes: an application of latent class analysis with distal outcomes

    OpenAIRE

    Jiang, Luohua; Chen, Shuai; Zhang, Ben; Beals, Janette; Mitchell, Christina M.; Manson, Spero M.; Roubideaux, Yvette

    2016-01-01

    Stages of change measure an individual's readiness to alter a health behavior. This study examined the latent longitudinal patterns of stages of change (SoC) for regular exercise over time among individuals participating in a lifestyle intervention project. It also investigated the association between the longitudinal patterns of SoC and intervention outcomes using a new statistical method to assess the relationship between latent class membership and distal outcomes. We analyzed data from th...

  17. Longitudinal Patterns of Stages of Change for Exercise and Lifestyle Intervention Outcomes: An Application of Latent Class Analysis with Distal Outcomes

    OpenAIRE

    Jiang, L; Chen, S; Zhang, B; Beals, J; Mitchell, CM; Manson, SM; Roubideaux, Y; The, SDPFIDPDP

    2015-01-01

    © 2015 Society for Prevention Research Stages of change measure an individual’s readiness to alter a health behavior. This study examined the latent longitudinal patterns of stages of change (SoC) for regular exercise over time among individuals participating in a lifestyle intervention project. It also investigated the association between the longitudinal patterns of SoC and intervention outcomes using a new statistical method to assess the relationship between latent class membership and di...

  18. A comparison of the latent class structure of cannabis problems among adult men and women who have used cannabis repeatedly.

    Science.gov (United States)

    Grant, Julia D; Scherrer, Jeffrey F; Neuman, Rosalind J; Todorov, Alexandre A; Price, Rumi K; Bucholz, Kathleen K

    2006-08-01

    Little empirical evidence exists to determine if there are alternative classification schemes for cannabis abuse and dependence beyond the definitions provided by Diagnostic and Statistical Manual (DSM) criteria. Current evidence is not conclusive regarding gender differences for cannabis use, abuse and dependence. It is not known if symptom profiles differ by gender. Latent class analysis (LCA) was used to assess whether cannabis abuse and dependence symptom patterns suggest a severity spectrum or distinct subtypes and to test whether symptom patterns differ by gender. Data from 3312 men and 2509 women in the National Longitudinal Alcohol Epidemiologic Survey (NLAES) who had used cannabis 12 + times life-time were included in the present analyses. The comparability of the solutions for men and women was examined through likelihood ratio chi(2) tests. Based on the Bayesian information criterion and interpretability, a four-class solution was selected, and the classes were labeled as 'unaffected/mild hazardous use', 'hazardous use/abuse', 'abuse/moderate dependence' and 'severe abuse/dependence'. The solutions were generally suggestive of a severity spectrum. Compared to men, women were more likely to be in the 'unaffected/mild hazardous use' class and less likely to be in the 'abuse/moderate dependence' or 'severe abuse/dependence' classes. The results were generally similar for men and women. However, men had consistently and substantially higher endorsements of hazardous use than women, women in the 'abuse/moderate dependence' class had moderately higher rates for four dependence symptoms, and women in two of the classes were more likely to endorse withdrawal. Our findings generally support the severity dimension for DSM-IV cannabis abuse and dependence symptomatology for both men and women. While our results indicate that public health messages may have generic and not gender-specific content, treatment providers should focus more effort on reducing hazardous

  19. Assessment of Differential Rater Functioning in Latent Classes with New Mixture Facets Models.

    Science.gov (United States)

    Jin, Kuan-Yu; Wang, Wen-Chung

    2017-01-01

    Multifaceted data are very common in the human sciences. For example, test takers' responses to essay items are marked by raters. If multifaceted data are analyzed with standard facets models, it is assumed there is no interaction between facets. In reality, an interaction between facets can occur, referred to as differential facet functioning. A special case of differential facet functioning is the interaction between ratees and raters, referred to as differential rater functioning (DRF). In existing DRF studies, the group membership of ratees is known, such as gender or ethnicity. However, DRF may occur when the group membership is unknown (latent) and thus has to be estimated from data. To solve this problem, in this study, we developed a new mixture facets model to assess DRF when the group membership is latent and we provided two empirical examples to demonstrate its applications. A series of simulations were also conducted to evaluate the performance of the new model in the DRF assessment in the Bayesian framework. Results supported the use of the mixture facets model because all parameters were recovered fairly well, and the more data there were, the better the parameter recovery.

  20. 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.

  1. Polydrug Use and Heterogeneity in HIV Risk Among People Who Inject Drugs in Estonia and Russia: A Latent Class Analysis.

    Science.gov (United States)

    Tavitian-Exley, Isabel; Boily, Marie-Claude; Heimer, Robert; Uusküla, Anneli; Levina, Olga; Maheu-Giroux, Mathieu

    2017-07-11

    Non-medical drug injection is a major risk factor for HIV infection in Russia and Estonia. Multiple drug use (polydrug) has further been associated with increased harms. We compared HIV, injecting and sexual risk associated with polydrug use among people who injected drugs (PWID) in 2012-2013 in Kohtla-Järve (Estonia, n = 591) and St Petersburg (Russia, n = 811). Using latent class analysis, we identified five (poly)drug classes, the largest consisting of single-drug injectors among whom an opioid was the sole drug injected (56% of PWID). The four remaining polydrug classes included polydrug-polyroute injectors who injected and used opiates and stimulants (9%), opiate-stimulant poly-injectors who injected amphetamine-type-stimulants with a primary opiate (7%) and opiate-opioid poly-injectors who injected opioids and opiates (16%). Non-injection stimulant co-users were injectors who also used non-injection stimulants (12%). In multivariable multinomial regressions, all four polydrug classes were associated with greater injection risks than single-drug injection, while opiate-stimulant and opiate-opioid poly-injection were also associated with having multiple sex partners. Riskier behaviours among polydrug-injectors suggest increased potential for transmission of blood-borne and sexually-transmitted infections. In addition to needles/syringes provision, services tailored to PWID drug and risk profiles, could consider drug-appropriate treatment and sexual risk reduction strategies to curb HIV transmission.

  2. Applying Health Locus of Control and Latent Class Modelling to food and physical activity choices affecting CVD risk.

    Science.gov (United States)

    Grisolía, José M; Longo, Alberto; Hutchinson, George; Kee, Frank

    2015-05-01

    Health Locus of Control (HLC) classifies our beliefs about the connection between our actions and health outcomes (Skinner, 1996) into three categories: "internal control", corresponding to health being the result of an individual's effort and habits; "control by powerful others", whereby health depends on others, such as doctors; and "chance control", according to which health depends on fate and chance. Using Choice Experiments we investigate the relationship between HLC and willingness to change lifestyle, in terms of eating habits, physical activity and associated cardiovascular disease risk, in a 384 person sample representative of the 40-65 aged population of Northern Ireland administered between February and July 2011. Using latent class analysis we identify three discrete classes of people based on their HLC: the first class is sceptical about their capacity to control their health and certain unhealthy habits. Despite being unsatisfied with their situation, they are reluctant to accept behaviour changes. The second is a group of individuals unhappy with their current situation but willing to change through exercise and diet. Finally, a group of healthy optimists is identified, who are satisfied with their current situation but happy to take more physical activity and improve their diet. Our findings show that any policy designed to modify people's health related behaviour should consider the needs of this sceptical class which represents a considerable proportion of the population in the region. Copyright © 2015 Elsevier Ltd. All rights reserved.

  3. Can Latent Class Analysis Be Used to Improve the Diagnostic Process in Pediatric Patients with Chronic Ataxia?

    Science.gov (United States)

    Klassen, Samantha; Dufault, Brenden; Salman, Michael S

    2017-04-01

    Chronic ataxia is a relatively common symptom in children. There are numerous causes of chronic ataxia, making it difficult to derive a diagnosis in a timely manner. We hypothesized that the efficiency of the diagnostic process can be improved with systematic analysis of clinical features in pediatric patients with chronic ataxia. Our aim was to improve the efficiency of the diagnostic process in pediatric patients with chronic ataxia. A cohort of 184 patients, aged 0-16 years with chronic ataxia who received medical care at Winnipeg Children's Hospital during 1991-2008, was ascertained retrospectively from several hospital databases. Clinical details were extracted from hospital charts. The data were compared among the more common diseases using univariate analysis to identify pertinent clinical features that could potentially improve the efficiency of the diagnostic process. Latent class analysis was then conducted to detect unique patterns of clinical features and to determine whether these patterns could be associated with chronic ataxia diagnoses. Two models each with three classes were chosen based on statistical criteria and clinical knowledge for best fit. Each class represented a specific pattern of presenting symptoms or other clinical features. The three classes corresponded to a plausible and shorter list of possible diagnoses. For example, developmental delay and hypotonia correlated best with Angelman syndrome. Specific patterns of presenting symptoms or other clinical features can potentially aid in the initial assessment and diagnosis of pediatric patients with chronic ataxia. This will likely improve the efficiency of the diagnostic process.

  4. A Latent Class Analysis of Depressive and Externalizing Symptoms in Nonreferred Adolescents

    Science.gov (United States)

    Mezulis, Amy; Vander Stoep, Ann; Stone, Andrea L.; McCauley, Elizabeth

    2011-01-01

    Both depressive and externalizing symptoms are common in adolescence and often co-occur. The purpose of this study was to examine whether adolescents' patterns of depressive and externalizing symptoms can be differentiated into discrete classes and whether these classes are best distinguished by the number or type of symptoms. We examined whether…

  5. Identification of subgroups of patients with low back pain using Latent Class Analysis

    DEFF Research Database (Denmark)

    Nielsen, Anne Mølgaard

    Low back pain (LBP) is a major global health problem but the evidence base available to inform clinical decision making and to provide prognostic information to patients, is less than ideal. Therefore, there is a need for further knowledge about this largely non‐specific condition. Within...... 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...... in the outcomes, their prognostic capacity was as high or higher than two existing subgrouping tools (STarT Back Tool and Quebec Task Force Classification), and three baseline characteristics (LBP intensity, leg pain intensity and pain‐related disability). In contrast, the novel subgroupings had a lower...

  6. 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.

  7. Types of Non-kin Networks and Their Association With Survival in Late Adulthood: A Latent Class Approach.

    Science.gov (United States)

    Ellwardt, Lea; Aartsen, Marja; van Tilburg, Theo

    2017-07-01

    Integration into social networks is an important determinant of health and survival in late adulthood. We first identify different types of non-kin networks among older adults and second, investigate the association of these types with survival rates. Official register information on mortality is combined with data from the Longitudinal Aging Study Amsterdam (LASA). The sample includes 2,440 Dutch respondents aged 54-85 at baseline in 1992 and six follow-ups covering a time span of 20 years. Using latent class analysis, respondents are classified into distinct types of non-kin networks, based on differences in number and variation of non-kin relations, social support received from non-kin, and contact frequency with non-kin. Next, membership in network types is related to mortality in a Cox proportional hazard regression model. There are four latent types of non-kin networks that vary in network size and support. These types differ in their associations with mortality, independent of sociodemographic and health confounders. Older adults integrated into networks high in both number and variation of supportive non-kin contacts have higher chances of survival than older adults embedded in networks low in either amount or variation of support or both. A combination of structural and functional network characteristics should be taken into account when developing intervention programs aiming at increasing social integration outside the family network.

  8. The Four U's: Latent Classes of Hookup Motivations Among College Students

    OpenAIRE

    Uecker, Jeremy E.; Pearce, Lisa D.; Andercheck, Brita

    2015-01-01

    College students’ “hookups” have been the subject of a great deal of research in recent years. Motivations for hooking up have been linked to differences in well-being after the hookup, but studies detailing college students’ motivations for engaging in hookups focus on single motivations. Using data from the 2010 Duke Hookup Survey, we consider how motivations for hooking up cluster to produce different classes, or profiles, of students who hook up, and how these classes are related to hooku...

  9. Identification of a Syndrome Class of Neuropsychiatric Adverse Reactions to Mefloquine from Latent Class Modeling of FDA Adverse Event Reporting System Data.

    Science.gov (United States)

    Nevin, Remington L; Leoutsakos, Jeannie-Marie

    2017-03-01

    Although mefloquine use is known to be associated with a risk of severe neuropsychiatric adverse reactions that are often preceded by prodromal symptoms, specific combinations of neurologic or psychiatric reactions associated with mefloquine use are not well described in the literature. This study sought to identify a distinct neuropsychiatric syndrome class associated with mefloquine use in reports of adverse events. Latent class modeling of US Food and Drug Administration Adverse Event Reporting System (FAERS) data was performed using indicators defined by the Medical Dictionary for Regulatory Activities neurologic and psychiatric high-level group terms, in a study dataset of FAERS reports (n = 5332) of reactions to common antimalarial drugs. A distinct neuropsychiatric syndrome class was identified that was strongly and significantly associated with reports of mefloquine use (odds ratio = 3.92, 95% confidence interval 2.91-5.28), defined by a very high probability of symptoms of deliria (82.7%) including confusion and disorientation, and a moderate probability of other severe psychiatric and neurologic symptoms including dementia and amnesia (18.6%) and seizures (18.1%). The syndrome class was also associated with symptoms that are considered prodromal including anxiety, depression, sleep disturbance, and abnormal dreams, and neurological symptoms such as dizziness, vertigo, and paresthesias. This study confirms in FAERS reports the existence of a severe mefloquine neuropsychiatric syndrome class associated with common symptoms that may be considered prodromal. Clinical identification of the characteristic symptoms of this syndrome class may aid in improving case finding in pharmacovigilance studies of more serious adverse reactions to the drug.

  10. Heterogeneous body composition trajectories in infancy are associated with blood pressure in childhood: A latent class analysis

    DEFF Research Database (Denmark)

    Christensen, Rasmus Wibæk; Kæstel, Pernille; Girma, Tsinuel

    infants. BP was assessed at 4 years of age. Data driven latent class trajectory models were used to establish distinct FM and FFM trajectories, and multiple linear regression to examine their associations with BP at 4 years of age adjusted for sex, weight and length at birth, 3 and 6 months of age...... had a 3.8 mmHg (95%CI, 0.3; 7.4) higher SBP and 5.3 mmHg (95%CI, 1.1; 9.5) higher DBP. SBP was also significantly lower in the “Quadratic FFM” group compared to the “Linear FFM” reference group (figure 2). Conclusions: Heterogeneous FM and FFM accretion patterns in infancy were identified...

  11. 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

    : The major conclusions from this study are that the likelihood of detecting true association between genetic variants and complex traits increases tremendously when studied in physiological homogenous subpopulations and on inclusion of epistasis in the analysis, whereas epistasis (i.e. genetic networks...... 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...... population on genetic interaction was demonstrated by analysis of several genes previously associated with the metabolic syndrome and type 2 diabetes mellitus. RESULTS: The analysis revealed the existence of 19 distinct subpopulations with a different propensity to develop diabetes mellitus within a large...

  12. AN ALTERNATIVE TO CLASSICAL LATENT CLASS MODELS SELECTION METHODS FOR SPARSE BINARY DATA: AN ILLUSTRATION WITH SIMULATED DATA

    Directory of Open Access Journals (Sweden)

    Carlomagno Araya Alpizar

    2017-04-01

    Full Text Available Within the context of a latent class model with manifest binary variables, we propose an alternative method that solves the problem of estimating empirical distribution with sparse contingency tables and the chi-square approximation for goodness-of-fit will not be valid. We analyze sparse binary data, where there are many response patterns with very small expected frequencies in several data sets varying in degree of sparseness from 1 to 5 defined d = n/2p = n/R is a factor that is mentioned in almost all prior literature as being an important determinant of how well the distribution is represented by the chi-squared.The proposed approach produced results that were valid and reliable under the mentioned problematic data conditions. Results from the proposal presented compare the rates of Type I for traditional goodness-of-fit tests. We also show that with data density d ≤ 5, Pearson’s statistic

  13. Investigating trajectories of social recovery in individuals with first-episode psychosis: a latent class growth analysis.

    Science.gov (United States)

    Hodgekins, Jo; Birchwood, Max; Christopher, Rose; Marshall, Max; Coker, Sian; Everard, Linda; Lester, Helen; Jones, Peter; Amos, Tim; Singh, Swaran; Sharma, Vimal; Freemantle, Nick; Fowler, David

    2015-12-01

    Social disability is a hallmark of severe mental illness yet individual differences and factors predicting outcome are largely unknown. To explore trajectories and predictors of social recovery following a first episode of psychosis (FEP). A sample of 764 individuals with FEP were assessed on entry into early intervention in psychosis (EIP) services and followed up over 12 months. Social recovery profiles were examined using latent class growth analysis. Three types of social recovery profile were identified: Low Stable (66%), Moderate-Increasing (27%), and High-Decreasing (7%). Poor social recovery was predicted by male gender, ethnic minority status, younger age at onset of psychosis, increased negative symptoms, and poor premorbid adjustment. Social disability is prevalent in FEP, although distinct recovery profiles are evident. Where social disability is present on entry into EIP services it can remain stable, highlighting a need for targeted intervention. © The Royal College of Psychiatrists 2015.

  14. 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...

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. Latent class analysis of stages of change for multiple health behaviors: results from the Special Diabetes Program for Indians Diabetes Prevention Program.

    Science.gov (United States)

    Jiang, Luohua; Beals, Janette; Zhang, Lijing; Mitchell, Christina M; Manson, Spero M; Acton, Kelly J; Roubideaux, Yvette

    2012-10-01

    This study sought to identify latent subgroups among American Indian and Alaska Native (AI/AN) patients with pre-diabetes based on their stages of change for multiple health behaviors. We analyzed baseline data from participants of the Special Diabetes Program for Indians Diabetes Prevention (SDPI-DP) Program, a lifestyle intervention program to prevent diabetes among AI/ANs. A total of 3,135 participants completed baseline questionnaires assessing stages of change for multiple health behaviors, specifically exercise, healthy eating, and weight loss. Latent class analysis was used to identify subgroups of people based on their answers to stages of change questions. Covariates were added to the latent class analyses to investigate how class membership was related to sociodemographic, behavioral, and psychosocial factors. Three classes were identified based on the distributions of the stages of change variables: Contemplation, Preparation, and Action/Maintenance classes. Male and retired participants were more likely to be in more advanced stages. Those who exercised more, ate healthier diets, and weighed less were significantly more likely to be in the Action/Maintenance class. Further, the participants who had higher self-efficacy, stronger family support, and better health-related quality of life had higher odds of being in the Action/Maintenance class. In conclusion, we found that stages of change for multiple behaviors can be summarized by a three-class model in this sample. Investigating the relationships between latent classes and intervention outcomes represents important next steps to extend the findings of the current study.

  20. DSM-5 latent classes of alcohol users in a population-based sample: results from the São Paulo Megacity Mental Health Survey, Brazil.

    Science.gov (United States)

    Castaldelli-Maia, João Mauricio; Silveira, Camila M; Siu, Erica R; Wang, Yuan-Pang; Milhorança, Igor A; Alexandrino-Silva, Clóvis; Borges, Guilherme; Viana, Maria C; Andrade, Arthur G; Andrade, Laura H; Martins, Silvia S

    2014-03-01

    We aimed to identify different categorical phenotypes based upon the DSM-V criteria of alcohol use disorders (AUD) among alcohol users who had at least one drink per week in the past year (n=948). Data are from the São Paulo Megacity Mental Health Survey collected in 2005-2007, as part of the World Mental Health Survey Initiative. A latent class analysis of the 11 DSM-5-AUD criteria was performed using Mplus, taking into account complex survey design features. Weighted logistic regression models were used to examine demographic correlates of the DSM-5-AUD latent classes. The best latent-class model was a three-class model. We found a "non-symptomatic class" (69.7%), a "use in larger amounts class" (23.2%), defined by high probability (>70%) of the "use in larger amounts" criterion only, and a "high-moderate symptomatic class" (7.1%), defined by high-moderate probability of all the 11 AUD criteria. Compared to those in the non-symptomatic class, individuals in the "high-moderate symptomatic class" were more likely to have been married, have lower educational attainment and to be unemployed or in non-regular/informal employment. Those on the "use in larger amounts class" were more likely to have been married or never married. The two symptomatic classes clearly represented the dimensionality of the new proposed AUD criteria, and could be more specifically targeted by different prevention or treatment strategies. DSM-5-AUD has the advantage of shedding light on risky drinkers included in the "use in larger amounts class", allowing for preventive interventions, which will reach a large number of individuals. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  1. Differential patterns of planning impairments in Parkinson's disease and sub-clinical signs of dementia? A latent-class model-based approach.

    Science.gov (United States)

    Köstering, Lena; McKinlay, Audrey; Stahl, Christoph; Kaller, Christoph P

    2012-01-01

    Planning impairments mark a well-documented consequence of neurodegenerative diseases such as Parkinson's disease (PD). Recently, using the Tower of London task we demonstrated that, rather than being generally impaired, PD patients selectively fail when planning requires flexible in-breadth search strategies. For a better understanding of the interindividual patterns underlying specific planning impairments, here we performed an explorative re-analysis of the original data using a latent-class model-based approach. Data-driven classification according to subjects' performance was based on a multinomial processing tree (MPT) model accommodating the impact of increased breadth versus depth of looking ahead during planning. In order to assess interindividual variability in coping with these different task demands, an extension of MPT models was used in which sample-immanent heterogeneity is accounted for by identifying different latent classes of individuals. Two latent classes were identified that differed considerably in performance for problems placing high demands on the depth of anticipatory search processes. In addition, these impairments were independent of PD diagnosis. However, latent-class mediated search depth-related deficits in planning performance were associated with poorer outcomes in dementia screenings, albeit sub-clinical. PD patients exhibited additional deficits related to the breadth of searching ahead. Taken together, results revealed dissociable impairments in specific planning processes within a single task of visuospatial problem solving. Present analyses put forward the hypothesis that cognitive sequelae of PD and sub-clinical signs of dementia may be related to differential patterns of planning impairments.

  2. A Latent Class Analysis of Maternal Responsiveness and Autonomy-Granting in Early Adolescence: Prediction to Later Adolescent Sexual Risk-Taking

    Science.gov (United States)

    Lanza, H. Isabella; Huang, David Y. C.; Murphy, Debra A.; Hser, Yih-Ing

    2013-01-01

    The present study sought to extend empirical inquiry related to the role of parenting on adolescent sexual risk-taking by using latent class analysis (LCA) to identify patterns of adolescent-reported mother responsiveness and autonomy-granting in early adolescence and examine associations with sexual risk-taking in mid- and late-adolescence.…

  3. Latent class analysis of anxiety and depressive symptoms of the Youth Self-Report in a general population sample of young adolescents

    NARCIS (Netherlands)

    van Lang, Natasja D. J.; Ferdinand, Robert F.; Ormel, Johan; Verhulst, Frank C.

    This study examined whether distinct groups of young adolescents with mainly anxiety or mainly depression could be identified in a general population sample. Latent class analysis was used on self-report ratings of DSM-IV symptoms of anxiety and depressive disorders, because it was hypothesized that

  4. University and student segmentation: multilevel latent-class analysis of students' attitudes towards research methods and statistics.

    Science.gov (United States)

    Mutz, Rüdiger; Daniel, Hans-Dieter

    2013-06-01

    It is often claimed that psychology students' attitudes towards research methods and statistics affect course enrollment, persistence, achievement, and course climate. However, the inter-institutional variability has been widely neglected in the research on students' attitudes towards research methods and statistics, but it is important for didactic purposes (heterogeneity of the student population). The paper presents a scale based on findings of the social psychology of attitudes (polar and emotion-based concept) in conjunction with a method for capturing beginning university students' attitudes towards research methods and statistics and identifying the proportion of students having positive attitudes at the institutional level. The study based on a re-analysis of a nationwide survey in Germany in August 2000 of all psychology students that enrolled in fall 1999/2000 (N= 1,490) and N= 44 universities. Using multilevel latent-class analysis (MLLCA), the aim was to group students in different student attitude types and at the same time to obtain university segments based on the incidences of the different student attitude types. Four student latent clusters were found that can be ranked on a bipolar attitude dimension. Membership in a cluster was predicted by age, grade point average (GPA) on school-leaving exam, and personality traits. In addition, two university segments were found: universities with an average proportion of students with positive attitudes and universities with a high proportion of students with positive attitudes (excellent segment). As psychology students make up a very heterogeneous group, the use of multiple learning activities as opposed to the classical lecture course is required. © 2011 The British Psychological Society.

  5. Patterns of Gambling Activities and Gambling Problems Among Italian High School Students: Results from a Latent Class Analysis.

    Science.gov (United States)

    De Luigi, Nicola; Gibertoni, Dino; Randon, Emanuela; Scorcu, Antonello E

    2017-04-22

    This study aims to provide an estimate of the prevalence of gambling among Italian adolescents and a description of their patterns of gambling activities (PGAs) using a latent class analysis on 13 different types of games. A nationwide sample of 10,959 Italian high school students was recruited in 2013. We assessed problem gambling using the South Oaks Gambling Screen: Revisited for Adolescent (SOGS-RA) scale. Approximately half (50.6%) of students reported gambling at least once in the previous year; 5.0% of them were problem gamblers and 9.1% were at-risk gamblers according to their SOGS-RA scores. Eight PGAs were identified, among which heavy players (1.7% of students) could be classified as problem gamblers and broad skill players (2.0%) and lotteries & sports players (2.4%) as "at-risk" players. These high-risk classes were consistently associated with risky behaviours in terms of substance use, school performance, money spent on gambling and family environment; the other five classes identified low-risk players associated with safe behaviours. To the best of our knowledge, this is the first study to identify PGAs among Italian adolescents. Problem gamblers are not a homogeneous group in terms of patterns of gambling activities and are associated with different risk factors, among which environmental factors, such as parents' gambling attitude and behaviour, deserve special attention. The acknowledgment of such patterns and risk factors could be useful in developing sensible public policies addressing prevention strategies and regulatory instruments.

  6. Marijuana use patterns among African-American middle-school students: a longitudinal latent class regression analysis.

    Science.gov (United States)

    Reboussin, Beth A; Hubbard, Scott; Ialongo, Nicholas S

    2007-09-06

    The aim of this paper was to describe patterns of marijuana involvement during the middle-school years from the first chance to try marijuana down through the early stages of experiencing health and social problems from marijuana use in a sample of African-American adolescents. A total of 488 urban-dwelling African-American middle-school students were interviewed in sixth, seventh and eighth grades as part of a longitudinal field study. Longitudinal latent class models were used to identify subgroups (classes) of adolescents with similar patterns of marijuana involvement. Three classes were identified; little or no involvement (prevalence 85%, 71%, 55% in sixth, seventh and eighth grade, respectively), marijuana exposure opportunity (12%, 19% and 26%), and marijuana use and problems (2%, 9% and 19%). High levels of aggressive/disruptive behavior exhibited as early as first grade and moderate to high levels of deviant peer affiliation were associated with an increased risk of marijuana exposure opportunities in middle-school. Moderate to high levels of aggressive/disruptive behavior and deviant peer affiliation, moderate to low levels of parent monitoring and high levels of perceived neighborhood disadvantage were associated with an increased risk of marijuana use and problems. Significant interactions with grade provided evidence that the influences of parent monitoring and neighborhood disadvantage decrease through the middle-school years. Although not statistically significant, the magnitude of the effects of deviant peer affiliation on marijuana use and problems increased two-fold from sixth to eighth grade. These findings highlight the importance of marijuana exposure opportunities in the pathway to marijuana use and problems and the potential to intervene on behaviors exhibited as early as first grade. It also underscores the importance of developing interventions that are sensitive to the strong influence of parents at entry into middle-school and the shift

  7. Latent tree models

    OpenAIRE

    Zwiernik, Piotr

    2017-01-01

    Latent tree models are graphical models defined on trees, in which only a subset of variables is observed. They were first discussed by Judea Pearl as tree-decomposable distributions to generalise star-decomposable distributions such as the latent class model. Latent tree models, or their submodels, are widely used in: phylogenetic analysis, network tomography, computer vision, causal modeling, and data clustering. They also contain other well-known classes of models like hidden Markov models...

  8. 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.

  9. Heterogeneity in Drinking Practices in England and Wales and Its Association With Violent Behavior: A Latent Class Analysis.

    Science.gov (United States)

    Lightowlers, Carly

    2017-11-10

    Crude single-item consumption metrics, such as "binge drinking" measures, mask the complexity and heterogeneity in young people's drinking; thus limiting our understanding of young people's drinking patterns as well as how alcohol drinking is associated with violent outcomes. The current study employed a range of consumption and contextual indicators to explore heterogeneity in young people's (16-29 years) drinking practices, giving due consideration to their social nature. It also assessed to what extent heterogeneity in drinking practices was associated with violent outcomes. Employing data from the 2006 Offending Crime and Justice Survey, three measures of alcohol consumption and nine drinking context indicators were utilized within latent class analysis to create typologies of drinking practices among current drinkers in England and Wales (n = 2711) and examine their association with violent outcomes. The validity of the typologies was also assessed on age, sex, and socio-economic status. Three discernible drinking profiles were identified: "regular social drinkers" (48%), "regular pub binge drinkers" (32%), and "moderate drinkers" (20%). The "regular pub binge drinkers" were found to be more than twice as likely to commit an assault offence (odds ratio = 2.8 95% CI [1.3, 6.2]) when compared to "moderate drinkers" and "regular social drinkers" (odds ratio = 2.2 95% CI [1.4, 3.4]). Interventions aimed at reducing alcohol-related violence ought to give due consideration to the social context of drinking as well as levels of consumption.

  10. A latent class analysis of bullies, victims and aggressive victims in Chinese adolescence: relations with social and school adjustments.

    Science.gov (United States)

    Shao, Aihui; Liang, Lichan; Yuan, Chunyong; Bian, Yufang

    2014-01-01

    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.

  11. 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.

  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 (p<.001). Fluctuating fall risk (posterior probability <0.8 of belonging to any trajectory) was found in only 22.6% of the sample, most commonly among individuals who were transitioning to PIGD predominance. Conclusions Regardless of their baseline characteristics, most participants had clear and stable 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. 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.

  14. Suicide Risk across Latent Class Subgroups: A Test of the Generalizability of the Interpersonal Psychological Theory of Suicide.

    Science.gov (United States)

    Ma, Jennifer S; Batterham, Philip J; Calear, Alison L; Han, Jin

    2018-01-06

    It remains unclear whether the Interpersonal Psychological Theory of Suicide (IPTS; Joiner, ) is generalizable to the population or holds more explanatory power for certain subgroups compared to others. The aim of this study was to (1) identify subgroups of individuals who endorsed suicide ideation in the past month based on a range of mental health and demographic variables, (2) compare levels of the IPTS constructs within these subgroups, and (3) test the IPTS predictions for suicide ideation and suicide attempt for each group. Latent class, negative binomial, linear, and logistic regression analyses were conducted on population-based data obtained from 1,321 adults recruited from Facebook. Among participants reporting suicide ideation, four distinct patterns of risk factors emerged based on age and severity of mental health symptoms. Groups with highly elevated mental health symptoms reported the highest levels of thwarted belongingness and perceived burdensomeness. Tests of the IPTS interactions provided partial support for the theory, primarily in young adults with elevated mental health symptoms. Lack of support found for the IPTS predictions across the subgroups and full sample in this study raise some questions around the broad applicability of the theory. © 2018 The American Association of Suicidology.

  15. Latent class analysis of bulk tank milk PCR and ELISA testing for herd level diagnosis of Mycoplasma bovis

    DEFF Research Database (Denmark)

    Nielsen, Per Kantsø; Petersen, Mette Bisgaard; Nielsen, Liza Rosenbaum

    2015-01-01

    of this study was to evaluate the herd-level diagnostic performance of an indirect ELISA test by comparison to a real-time PCR test when diagnosing M. bovis in cattle herds of bulk tank milk. Bulk tank milk samples from Danish dairy herds (N=3437) were analysed with both the antibody detecting BIO K 302 M....... bovis ELISA kit and the antigen detecting PathoProof Mastitis Major-3 kit. As none of these are considered a gold standard test for herd-level diagnostics we applied a series of Bayesian latent class analyses for a range of ELISA cut-off values. The negative and positive predictive values were...... calculated for hypothetical true national prevalences (1, 5, 10, 15 and 20%) of infected herds. We estimated that the ELISA test had a median sensitivity and specificity of 60.4 [37.5-96.2 95% Posterior Credibility Interval] and 97.3 [94.0-99.8 95% PCI] at the currently recommended cut-off (37% Optical...

  16. Latent classes of polydrug and polyroute use and associations with human immunodeficiency virus risk behaviours and overdose among people who inject drugs in Tijuana, Baja California, Mexico.

    Science.gov (United States)

    Meacham, Meredith C; Roesch, Scott C; Strathdee, Steffanie A; Lindsay, Suzanne; Gonzalez-Zuniga, Patricia; Gaines, Tommi L

    2017-03-24

    Patterns of polydrug use among people who inject drugs (PWID) may be differentially associated with overdose and unique human immunodeficiency virus (HIV) risk factors. Subgroups of PWID in Tijuana, Mexico, were identified based on substances used, route of administration, frequency of use and co-injection indicators. Participants were PWID residing in Tijuana age ≥18 years sampled from 2011 to 2012 who reported injecting an illicit substance in the past month (n = 735). Latent class analysis identified discrete classes of polydrug use characterised by 11 indicators of past 6 months substance use. Multinomial logistic regression examined class membership association with HIV risk behaviours, overdose and other covariates using an automated three-step procedure in mplus to account for classification error. Participants were classified into five subgroups. Two polydrug and polyroute classes were defined by use of multiple substances through several routes of administration and were primarily distinguished from each other by cocaine use (class 1: 5%) or no cocaine use (class 2: 29%). The other classes consisted primarily of injectors: cocaine, methamphetamine and heroin injection (class 3: 4%); methamphetamine and heroin injection (class 4: 10%); and heroin injection (class 5: 52%). Compared with the heroin-only injection class, memberships in the two polydrug and polyroute use classes were independently associated with both HIV injection and sexual risk behaviours. Substance use patterns among PWID in Tijuana are highly heterogeneous, and polydrug and polyroute users are a high-risk subgroup who may require more tailored prevention and treatment interventions. [Meacham MC, Roesch SC, Strathdee SA, Lindsay S, Gonzalez-Zuniga P, Gaines TL. Latent classes of polydrug and polyroute use and associations with human immunodeficiency virus risk behaviours and overdose among people who inject drugs in Tijuana, Baja California, Mexico. Drug Alcohol Rev 2017

  17. Identifying individuals engaging in risky sexual behaviour for chlamydia infection in the UK: a latent class approach.

    Science.gov (United States)

    Stuart, Beth; Hinde, Andrew

    2010-01-01

    Chlamydia trachomitis is the most common sexually transmitted infection in the UK and the number of cases diagnosed each year continues to rise. Although much is known about the risk factors for chlamydia from previous observational studies, less is known about how individuals put themselves at risk. Do they engage in just one risky type of behaviour or are certain individuals 'risky', engaging in multiple risky behaviours? This paper uses latent class analysis, applied to the National Survey of Sexual Attitudes and Lifestyles II (2000-2001), to determine whether a subgroup of high-risk individuals can be identified and explores which features of their behaviour distinguish them from other groups of lower risk individuals. A 3-class solution was obtained, splitting the sample on the basis of the number of sexual partners in the past year. Those with no sexual partners in the past year (8%) and one sexual partner in the past year (71%) were much less likely to have engaged in any of the other behaviours known to increase chlamydia risk. However, the group who had two or more sexual partners in the past year (21%) were much more likely to have also engaged in other risky behaviours. The number of partners in the past year is therefore a useful marker for identifying those at increased risk of chlamydia infection. Individuals under 25 years old, males and those who were single or previously married were more likely to be allocated to the risky group. However, in spite of observed higher incidence of chlamydia infection, individuals in the black ethnic minority groups did not show an increased prevalence of risky behaviour, after controlling for age, sex and marital status.

  18. Drug use and phylogenetic clustering of hepatitis C virus infection among people who use drugs in Vancouver, Canada: A latent class analysis approach.

    Science.gov (United States)

    Jacka, B; Bray, B C; Applegate, T L; Marshall, B D L; Lima, V D; Hayashi, K; DeBeck, K; Raghwani, J; Harrigan, P R; Krajden, M; Montaner, J S G; Grebely, J

    2018-01-01

    This study estimated latent classes (ie, unobserved subgroups in a population) of people who use drugs in Vancouver, Canada, and examined how these classes relate to phylogenetic clustering of hepatitis C virus (HCV) infection. HCV antibody-positive people who use drugs from two cohorts in Vancouver, Canada (1996-2012), with a Core-E2 sequence were included. Time-stamped phylogenetic trees were inferred, and phylogenetic clustering was determined by time to most common recent ancestor. Latent classes were estimated, and the association with the phylogenetic clustering outcome was assessed using an inclusive classify/analyse approach. Among 699 HCV RNA-positive participants (26% female, 24% HIV+), recent drug use included injecting cocaine (80%), injecting heroin (70%), injecting cocaine/heroin (ie, speedball, 38%) and crack cocaine smoking (28%). Latent class analysis identified four distinct subgroups of drug use typologies: (i) cocaine injecting, (ii) opioid and cocaine injecting, (iii) crack cocaine smoking and (iv) heroin injecting and currently receiving opioid substitution therapy. After adjusting for age and HIV infection, compared to the group defined by heroin injecting and currently receiving opioid substitution therapy, the odds of phylogenetic cluster membership was greater in the cocaine injecting group (adjusted OR [aOR]: 3.06; 95% CI: 1.73, 5.42) and lower in the crack cocaine smoking group (aOR: 0.06; 95% CI: 0.01, 0.48). Combining latent class and phylogenetic clustering analyses provides novel insights into the complex dynamics of HCV transmission. Incorporating differing risk profiles associated with drug use may provide opportunities to further optimize and target HCV treatment and prevention strategies. © 2017 John Wiley & Sons Ltd.

  19. 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

  20. 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.

  1. Evaluation of antiphospholipid antibody assays using latent class analysis to address the lack of a reference standard.

    Science.gov (United States)

    Thaler, Markus A; Bietenbeck, Andreas; Yin, Meng-Xin; Steigerwald, Udo; Holmes, Andrew B; Lindhoff-Last, Edelgard; Luppa, Peter B

    2016-12-01

    Method evaluation of new assays for the detection of antiphospholipid antibodies (aPL) such as anti-cardiolipin (aCL) or anti-β2-glycoprotein I (aβ2-GPI) is challenging, as no internationally accepted reference material is available yet. Besides a lack of standardization, unacceptable inter-laboratory comparability of established tests is regularly observed. Owing to the absence of a commonly accepted reference standard, the evaluation of two research surface plasmon resonance (SPR) biosensor assays was performed using statistical methods from latent class analysis (LCA). aCL and aβ2-GPI IgG and IgM were measured in sera from 63 antiphospholipid syndrome patients, fulfilling the Sydney criteria, and in 34 healthy controls with four commercial assays. LCA was performed on the results and sera were assigned to the antibody-positive or antibody-negative group. Sera were subsequently evaluated in the SPR assays for aCL and aβ2-GPI. Optimal cutoffs and diagnostic performances of the research systems were established employing the LCA-derived gold standard. With area under the curve results of 0.96 and 0.89 for the detection of aCL and aβ2-GPI, the research SPR assays discriminated well between antibody-positive and antibody-negative sera. Their sensitivities and specificities were comparable to the investigated commercial immunoassays. SPR assays are a suitable tool for the detection of aCL and aβ2-GPI with diagnostic performances not different from currently available commercial tests. LCA enabled the calculation of sensitivities and specificities for aPL assays in absence of a reference standard.

  2. The Neighbourhood Built Environment and Trajectories of Depression Symptom Episodes in Adults: A Latent Class Growth Analysis.

    Directory of Open Access Journals (Sweden)

    Genevieve Gariepy

    Full Text Available To investigate the effect of the neighbourhood built environment on trajectories of depression symptom episodes in adults from the general Canadian population.We used 10 years of data collection (2000/01-2010/11 from the Canadian National Population Health Study (n = 7114. Episodes of depression symptoms were identified using the Composite International Diagnostic Interview Short-Form. We assessed the presence of local parks, healthy food stores, fast food restaurants, health services and cultural services using geospatial data. We used latent class growth modelling to identify different trajectories of depression symptom episodes in the sample and tested for the effect of neighbourhood variables on the trajectories over time.We uncovered three distinct trajectories of depression symptom episodes: low prevalence (76.2% of the sample, moderate prevalence (19.2% and high prevalence of depression symptom episodes (2.8%. The presence of any neighbourhood service (healthy food store, fast-food restaurant, health service, except for cultural service was significantly associated with a lower probability of a depression symptom episode for those following a trajectory of low prevalence of depression symptom episodes. The presence of a local park was also a significant protective factor in trajectory groups with both low and moderate prevalence of depression symptom episodes. Neighbourhood characteristics did not significantly affect the trajectory of high prevalence of depression symptom episodes.For individuals following a trajectory of low and moderate prevalence of depression symptom episodes, the neighbourhood built environment was associated with a shift in the trajectory of depression symptom episodes. Future intervention studies are recommended to make policy recommendations.

  3. Adolescent loneliness and psychiatric morbidity in the general population: Identifying "at risk" groups using latent class analysis.

    Science.gov (United States)

    Shevlin, Mark; Murphy, Siobhan; Murphy, Jamie

    2014-11-01

    Previous research has shown that loneliness is strongly associated with both physical and psychological ill health, particularly among adolescents. Factor analytic research has also shown that loneliness is a multi-dimensional construct, characterized by e.g. feelings of isolation, and relational and collective connectedness. While factor analytic representations of the phenomenon effectively illustrate the structure and form of the loneliness construct, they may not adequately capture its expression in the population within, among and across individuals. The current study modelled the expression of loneliness among a population sample of Northern Irish adolescents using latent class analysis. Data from the Young Life and Times Survey (2011) was used to identify the fewest groups of adolescents in the population characterized by discrete and shared loneliness profiles based on their responses to the UCLA Loneliness Scale (UCLA-LS). Individual "at risk" status for psychiatric morbidity was then assessed on the basis of LCA-group membership. Four groups of adolescents were identified: 1) high loneliness, characterized predominantly by feelings of isolation, 2) intermediate loneliness (two groups), and a baseline group with low levels of loneliness. While all groups were more likely to screen positive for psychiatric morbidity compared with the baseline group, notable risk, however, was attributable to specific isolation experiences or disconnectedness, that characterized both the profiles of the high loneliness group and the similar, but less severe, intermediate loneliness group. Loneliness is distributed throughout the adolescent population; however, among a significant minority, loneliness is predominantly characterized by feelings of isolation and is strongly indicative of psychological ill health.

  4. Use of latent class models to accommodate inter-laboratory variation in assessing genetic polymorphisms associated with disease risk

    Directory of Open Access Journals (Sweden)

    Walter Stephen D

    2008-08-01

    Full Text Available Abstract Background Researchers wanting to study the association of genetic factors with disease may encounter variability in the laboratory methods used to establish genotypes or other traits. Such variability leads to uncertainty in determining the strength of a genotype as a risk factor. This problem is illustrated using data from a case-control study of cervical cancer in which some subjects were independently assessed by different laboratories for the presence of a genetic polymorphism. Inter-laboratory agreement was only moderate, which led to a very wide range of empirical odds ratios (ORs with the disease, depending on how disagreements were treated. This paper illustrates the use of latent class models (LCMs and to estimate OR while taking laboratory accuracy into account. Possible LCMs are characterised in terms of the number of laboratory measurements available, and if their error rates are assumed to be differential or non-differential by disease status and/or laboratory. Results The LCM results give maximum likelihood estimates of laboratory accuracy rates and the OR of the genetic variable and disease, and avoid the ambiguities of the empirical results. Having allowed for possible measurement error in the expure, the LCM estimates of exposure – disease associations are typically stronger than their empirical equivalents. Also the LCM estimates exploit all the available data, and hence have relatively low standard errors. Conclusion Our approach provides a way to evaluate the association of a polymorphism with disease, while taking laboratory measurement error into account. Ambiguities in the empirical data arising from disagreements between laboratories are avoided, and the estimated polymorphism-disease association is typically enhanced.

  5. 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.

  6. Negative psychotic symptoms and impaired role functioning predict transition outcomes in the at-risk mental state: a latent class cluster analysis study.

    Science.gov (United States)

    Valmaggia, L R; Stahl, D; Yung, A R; Nelson, B; Fusar-Poli, P; McGorry, P D; McGuire, P K

    2013-11-01

    Many research groups have attempted to predict which individuals with an at-risk mental state (ARMS) for psychosis will later develop a psychotic disorder. However, it is difficult to predict the course and outcome based on individual symptoms scores. Data from 318 ARMS individuals from two specialized services for ARMS subjects were analysed using latent class cluster analysis (LCCA). The score on the Comprehensive Assessment of At-Risk Mental States (CAARMS) was used to explore the number, size and symptom profiles of latent classes. LCCA produced four high-risk classes, censored after 2 years of follow-up: class 1 (mild) had the lowest transition risk (4.9%). Subjects in this group had the lowest scores on all the CAARMS items, they were younger, more likely to be students and had the highest Global Assessment of Functioning (GAF) score. Subjects in class 2 (moderate) had a transition risk of 10.9%, scored moderately on all CAARMS items and were more likely to be in employment. Those in class 3 (moderate-severe) had a transition risk of 11.4% and scored moderately severe on the CAARMS. Subjects in class 4 (severe) had the highest transition risk (41.2%), they scored highest on the CAARMS, had the lowest GAF score and were more likely to be unemployed. Overall, class 4 was best distinguished from the other classes on the alogia, avolition/apathy, anhedonia, social isolation and impaired role functioning. The different classes of symptoms were associated with significant differences in the risk of transition at 2 years of follow-up. Symptomatic clustering predicts prognosis better than individual symptoms.

  7. DSM-5 latent classes of alcohol users in a population-based sample: Results from the São Paulo Megacity Mental Health Survey, Brazil✩

    Science.gov (United States)

    Castaldelli-Maia, João Mauricio; Silveira, Camila M.; Siu, Erica R.; Wang, Yuan-Pang; Milhorança, Igor A.; Alexandrino-Silva, Clóvis; Borges, Guilherme; Viana, Maria C.; Andrade, Arthur G.; Andrade, Laura H.; Martins, Silvia S.

    2016-01-01

    Background We aimed to identify different categorical phenotypes based upon the DSM-V criteria of alcohol use disorders (AUD) among alcohol users who had at least one drink per week in the past year (n = 948). Methods Data are from the São Paulo Megacity Mental Health Survey collected in 2005–2007, as part of the World Mental Health Survey Initiative. A latent class analysis of the 11 DSM-5-AUD criteria was performed using Mplus, taking into account complex survey design features. Weighted logistic regression models were used to examine demographic correlates of the DSM-5-AUD latent classes. Results The best latent-class model was a three-class model. We found a “non-symptomatic class” (69.7%), a “use in larger amounts class” (23.2%), defined by high probability (>70%) of the “use in larger amounts” criterion only, and a “high-moderate symptomatic class” (7.1%), defined by high-moderate probability of all the 11 AUD criteria. Compared to those in the non-symptomatic class, individuals in the “high-moderate symptomatic class” were more likely to have been married, have lower educational attainment and to be unemployed or in non-regular/informal employment. Those on the “use in larger amounts class” were more likely to have been married or never married. Conclusion The two symptomatic classes clearly represented the dimensionality of the new proposed AUD criteria, and could be more specifically targeted by different prevention or treatment strategies. DSM-5-AUD has the advantage of shedding light on risky drinkers included in the “use in larger amounts class”, allowing for preventive interventions, which will reach a large number of individuals. PMID:24440273

  8. Three-year latent class trajectories of attention-deficit/hyperactivity disorder (ADHD) symptoms in a clinical sample not selected for ADHD.

    Science.gov (United States)

    Arnold, L Eugene; Ganocy, Stephen J; Mount, Katherine; Youngstrom, Eric A; Frazier, Thomas; Fristad, Mary; Horwitz, Sarah M; Birmaher, Boris; Findling, Robert; Kowatch, Robert A; Demeter, Christine; Axelson, David; Gill, Mary Kay; Marsh, Linda

    2014-07-01

    This study aims to examine trajectories of attention-deficit/hyperactivity disorder (ADHD) symptoms in the Longitudinal Assessment of Manic Symptoms (LAMS) sample. The LAMS study assessed 684 children aged 6 to 12 years with the Kiddie-Schedule for Affective Disorders and Schizophrenia (K-SADS) and rating scales semi-annually for 3 years. Although they were selected for elevated manic symptoms, 526 children had baseline ADHD diagnoses. With growth mixture modeling (GMM), we separately analyzed inattentive and hyperactive/impulsive symptoms, covarying baseline age. Multiple standard methods determined optimal fit. The χ(2) and Kruskal-Wallis analysis of variance compared resulting latent classes/trajectories on clinical characteristics and medication. Three latent class trajectories best described inattentive symptoms, and 4 classes best described hyperactive/impulsive symptoms. Inattentive trajectories maintained their relative position over time. Hyperactive/impulsive symptoms had 2 consistent trajectories (least and most severe). A third trajectory (4.5%) started mild, then escalated; and a fourth (14%) started severe but improved dramatically. The improving trajectory was associated with the highest rate of ADHD and lowest rate of bipolar diagnoses. Three-fourths of the mildest inattention class were also in the mildest hyperactive/impulsive class; 72% of the severest inattentive class were in the severest hyperactive/impulsive class, but the severest inattention class also included 62% of the improving hyperactive-impulsive class. An ADHD rather than bipolar diagnosis prognosticates a better course of hyperactive/impulsive, but not inattentive, symptoms. High overlap of relative severity between inattention and hyperactivity/impulsivity confirms the link between these symptom clusters. Hyperactive/impulsive symptoms wane more over time. Group means are insufficient to understand individual ADHD prognosis. A small subgroup deteriorates over time in

  9. Substance use, mental illness, and familial conflict non-negotiation among HIV-positive African-Americans: latent class regression and a new syndemic framework.

    Science.gov (United States)

    Robinson, Allysha C; Knowlton, Amy R; Gielen, Andrea C; Gallo, Joseph J

    2016-02-01

    We evaluated a synergistic epidemic (syndemic) of substance use, mental illness, and familial conflict non-negotiation among HIV-positive injection drug users (IDU). Baseline BEACON study data was utilized. Latent class analyses identified syndemic classes. These classes were regressed on sex, viral suppression, and acute care non-utilization. Females were hypothesized to have higher syndemic burden, and worse health outcomes than males. Nine percent of participants had high substance use/mental illness prevalence (Class 4); 23 % had moderate levels of all factors (Class 3); 25 % had high mental illness (Class 2); 43 % had moderate substance use/mental illness (Class 1; N = 331). Compared to Classes 1-3, Class 4 was mostly female (p < .05), less likely to achieve viral suppression, and more likely to utilize acute care (p < .05). Interventions should target African-American IDU females to improve their risk of negative medical outcomes. Findings support comprehensive syndemic approaches to HIV interventions, rather than singular treatment methods.

  10. 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

    2014-12-01

    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 behaviors that represent multiple theoretically/clinically relevant dimensions of obesity risk among 2- versus 4-year college students using cross-sectional statewide surveillance data (N = 17,584). Additionally, differences in class membership on selected sociodemographic characteristics were examined using a model-based approach. Analysis was conducted separately for both college groups, and five and four classes were identified for 2- and 4-year college students, respectively. Four classes were similar across 2- and 4-year college groups and were characterized as "mostly healthy dietary habits, active"; "moderately high screen time, active"; "moderately healthy dietary habits, inactive"; and "moderately high screen time, inactive." "Moderately healthy dietary habits, high screen time" was the additional class unique to 2-year college students. These classes differed on a number of sociodemographic characteristics, including the proportion in each class who were classified as obese. Implications for prevention scientists and future intervention programs are considered. © 2014 Society for Public Health Education.

  11. 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

  12. 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

  13. 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 9th or 10th grade at seven public high schools in Texas participated in the survey (56 % female, White: 30 %, Hispanic: 32 %, African American: 29 %, others: 9 %). A three-step latent class analysis was employed. Five latent teen dating violence classes were identified: (1) nonviolence; (2) emotional/verbal abuse; (3) forced sexual contact; (4) psychological + physical violence; and (5) psychological abuse. Females, African Americans, and youth who had higher acceptance of couple violence scores and whose parents had less education were more likely to members of dating violence classes compared with the nonviolence class. Adolescents who experienced multiple types of dating violence reported greater mental health concerns. Prevention programs may benefit by identifying the homogenous subgroups of teen dating violence and targeting adolescent teen dating violence accordingly.

  14. Latent class modelling of the association between socioeconomic background and breast cancer survival status at 5 years incorporating stage of disease.

    Science.gov (United States)

    Downing, Amy; Harrison, Wendy J; West, Robert M; Forman, David; Gilthorpe, Mark S

    2010-09-01

    Stage of disease and socioeconomic background (SEB) are often used to 'explain' differences in breast cancer outcomes. There are challenges for all types of analysis (eg, survival analysis, logistic regression), including missing data, measurement error and the 'reversal paradox'. This study investigates the association between SEB and survival status within 5 years of breast cancer diagnosis using (1) logistic regression with and without adjustment for stage and (2) logistic latent class analysis (LCA) excluding stage as a covariate but with and without stage as a latent class predictor. Women diagnosed with invasive breast cancer between 1998 and 2000 in one UK region were identified (n=11 781). Multilevel logistic regression was performed using standard regression and LCA. Models included SEB (2001 Townsend Index), age and stage ('missing' stage (8.0%) modelled as a separate category). The association of SEB with stage was also assessed. Using standard regression, there was a substantial association between SEB and death within 5 years, with and without adjustment for stage. Using LCA, patients were assigned to a large good prognosis group and a small poor prognosis group. The association between SEB and survival was substantive in both classes for the model without stage, but only in the larger class for the model with stage. Increasing deprivation was associated with more advanced stage at diagnosis. LCA categorises patients into prognostic groups according to patient and tumour characteristics, providing an alternative strategy to the usual statistical adjustment for stage.

  15. Joint model-based clustering of nonlinear longitudinal trajectories and associated time-to-event data analysis, linked by latent class membership: with application to AIDS clinical studies.

    Science.gov (United States)

    Huang, Yangxin; Lu, Xiaosun; Chen, Jiaqing; Liang, Juan; Zangmeister, Miriam

    2017-10-27

    Longitudinal and time-to-event data are often observed together. Finite mixture models are currently used to analyze nonlinear heterogeneous longitudinal data, which, by releasing the homogeneity restriction of nonlinear mixed-effects (NLME) models, can cluster individuals into one of the pre-specified classes with class membership probabilities. This clustering may have clinical significance, and be associated with clinically important time-to-event data. This article develops a joint modeling approach to a finite mixture of NLME models for longitudinal data and proportional hazard Cox model for time-to-event data, linked by individual latent class indicators, under a Bayesian framework. The proposed joint models and method are applied to a real AIDS clinical trial data set, followed by simulation studies to assess the performance of the proposed joint model and a naive two-step model, in which finite mixture model and Cox model are fitted separately.

  16. Academic and Social Functioning Associated with Attention-Deficit/Hyperactivity Disorder: Latent Class Analyses of Trajectories from Kindergarten to Fifth Grade.

    Science.gov (United States)

    DuPaul, George J; Morgan, Paul L; Farkas, George; Hillemeier, Marianne M; Maczuga, Steve

    2016-10-01

    Children with attention-deficit/hyperactivity disorder (ADHD) are known to exhibit significantly lower academic and social functioning than other children. Yet the field currently lacks knowledge about specific impairment trajectories experienced by children with ADHD, which may constrain early screening and intervention effectiveness. Data were analyzed from a nationally representative U.S. cohort in the Early Childhood Longitudinal Study, Kindergarten Class of 1998-1999 (ECLS-K) for 590 children (72.7 % male) whose parents reported a formal diagnosis of ADHD. Children's math, reading, and interpersonal skills were assessed at 5 time points between kindergarten and fifth grade. Growth mixture model analyses indicated 4 latent trajectory classes for reading, 8 classes for math, and 4 classes for interpersonal skills. Membership in reading and math trajectory classes was strongly related; overlaps with interpersonal skills classes were weaker. Trajectory class membership was correlated with demographic characteristics and behavioral functioning. Children with ADHD display substantial heterogeneity in their reading, math, and interpersonal growth trajectories, with some groups of children especially likely to display relatively severe levels of academic and social impairment over time. Early screening and intervention to address impairment, particularly reading difficulties, among kindergarten students with ADHD is warranted.

  17. A social network-informed latent class analysis of patterns of substance use, sexual behavior, and mental health: Social Network Study III, Winnipeg, Manitoba, Canada.

    Science.gov (United States)

    Hopfer, Suellen; Tan, Xianming; Wylie, John L

    2014-05-01

    We assessed whether a meaningful set of latent risk profiles could be identified in an inner-city population through individual and network characteristics of substance use, sexual behaviors, and mental health status. Data came from 600 participants in Social Network Study III, conducted in 2009 in Winnipeg, Manitoba, Canada. We used latent class analysis (LCA) to identify risk profiles and, with covariates, to identify predictors of class. A 4-class model of risk profiles fit the data best: (1) solitary users reported polydrug use at the individual level, but low probabilities of substance use or concurrent sexual partners with network members; (2) social-all-substance users reported polydrug use at the individual and network levels; (3) social-noninjection drug users reported less likelihood of injection drug and solvent use; (4) low-risk users reported low probabilities across substances. Unstable housing, preadolescent substance use, age, and hepatitis C status predicted risk profiles. Incorporation of social network variables into LCA can distinguish important subgroups with varying patterns of risk behaviors that can lead to sexually transmitted and bloodborne infections.

  18. Latent Structure Agreement Analysis

    Science.gov (United States)

    1989-11-01

    general approach of Lazarsfeld and Henry [2]. More recently, we have used an EM algorithm 130] related to that described by Goodman [3] and Dawid and...inverting the information matrix [2]. Identifiability Lazarsfeld and Henry [2], Goodman [3], and others discuss identifiability of latent class models...and Irwig [43]. The fixed panel agreement model corresponds closely to traditional latent class analysis applications as described by Lazarsfeld and

  19. Bayesian Adaptive Lasso for Ordinal Regression with Latent Variables

    Science.gov (United States)

    Feng, Xiang-Nan; Wu, Hao-Tian; Song, Xin-Yuan

    2017-01-01

    We consider an ordinal regression model with latent variables to investigate the effects of observable and latent explanatory variables on the ordinal responses of interest. Each latent variable is characterized by correlated observed variables through a confirmatory factor analysis model. We develop a Bayesian adaptive lasso procedure to conduct…

  20. Using latent class analysis to estimate the test characteristics of the γ-interferon test, the single intradermal comparative tuberculin test and a multiplex immunoassay under Irish conditions

    DEFF Research Database (Denmark)

    Clegg, Tracy A.; Duignan, Anthony; Whelan, Clare

    2011-01-01

    estimated in populations with defined infection status. However, these approaches can be problematic as there may be few herds in Ireland where freedom from infection is guaranteed. We used latent class models to estimate the diagnostic characteristics of existing (SICTT and ¿-IFN) and new (multiplex...... of sensitivity and specificity under field conditions in Ireland and suggest that the Enferplex-TB test has the potential to improve on current diagnostics for TB infection in cattle. The extent of that potential will be assessed in further studies....

  1. Screening to Identify Groups of Pediatric Emergency Department Patients Using Latent Class Analysis of Reported Suicidal Ideation and Behavior and Non-Suicidal Self-Injury.

    Science.gov (United States)

    Herres, Joanna; Kodish, Tamar; Fein, Joel; Diamond, Guy

    2017-01-25

    Latent class analysis of medical records data from 3,523 emergency department (ED) patients (ages 14-24; 31% Caucasian; 67% female) distinguished 6 groups with varying histories of suicidal ideation and behavior based on items endorsed on the Behavioral Health Screen, a web based, nurse-initiated screening tool. As expected, the more severe suicidality groups reported higher levels of depressive symptoms, traumatic distress, and substance abuse symptoms. Findings support the validity of the BHS and its utility as a medical decision tool to help ED staff evaluate the severity of patients' suicidality.

  2. A latent class analysis of pathological-gambling criteria among high school students: associations with gambling, risk and health/functioning characteristics.

    Science.gov (United States)

    Kong, Grace; Tsai, Jack; Krishnan-Sarin, Suchitra; Cavallo, Dana A; Hoff, Rani A; Steinberg, Marvin A; Rugle, Loreen; Potenza, Marc N

    2014-01-01

    To identify subtypes of adolescent gamblers based on the 10 Diagnostic and Statistical Manual of Mental Disorders, fourth edition criteria for pathological gambling and the 9 Diagnostic and Statistical Manual of Mental Disorders, fifth edition criteria for gambling disorder and to examine associations between identified subtypes with gambling, other risk behaviors, and health/functioning characteristics. Using cross-sectional survey data from 10 high schools in Connecticut (N = 3901), we conducted latent class analysis to classify adolescents who reported past-year gambling into gambling groups on the basis of items from the Massachusetts Gambling Screen. Adolescents also completed questions assessing demographic information, substance use (cigarette, marijuana, alcohol, and other drugs), gambling behaviors (relating to gambling formats, locations, motivations, and urges), and health/functioning characteristics (eg, extracurricular activities, mood, aggression, and body mass index). The optimal solution consisted of 4 classes that we termed low-risk gambling (86.4%), at-risk chasing gambling (7.6%), at-risk negative consequences gambling (3.7%), and problem gambling (PrG) (2.3%). At-risk and PrG classes were associated with greater negative functioning and more gambling behaviors. Different patterns of associations between at-risk and PrG classes were also identified. Adolescent gambling classifies into 4 classes, which are differentially associated with demographic, gambling patterns, risk behaviors, and health/functioning characteristics. Early identification and interventions for adolescent gamblers should be sensitive to the heterogeneity of gambling subtypes.

  3. A Latent Class Analysis of Pathological-Gambling Criteria Among High School Students: Associations With Gambling, Risk and Health/Functioning Characteristics

    Science.gov (United States)

    Kong, Grace; Tsai, Jack; Krishnan-Sarin, Suchitra; Cavallo, Dana A.; Hoff, Rani A.; Steinberg, Marvin A.; Rugle, Loreen; Potenza, Marc N.

    2015-01-01

    Objectives To identify subtypes of adolescent gamblers based on the 10 Diagnostic and Statistical Manual of Mental Disorders, fourth edition criteria for pathological gambling and the 9 Diagnostic and Statistical Manual of Mental Disorders, fifth edition criteria for gambling disorder and to examine associations between identified subtypes with gambling, other risk behaviors, and health/functioning characteristics. Methods Using cross-sectional survey data from 10 high schools in Connecticut (N = 3901), we conducted latent class analysis to classify adolescents who reported past-year gambling into gambling groups on the basis of items from the Massachusetts Gambling Screen. Adolescents also completed questions assessing demographic information, substance use (cigarette, marijuana, alcohol, and other drugs), gambling behaviors (relating to gambling formats, locations, motivations, and urges), and health/functioning characteristics (eg, extracurricular activities, mood, aggression, and body mass index). Results The optimal solution consisted of 4 classes that we termed low-risk gambling (86.4%), at-risk chasing gambling (7.6%), at-risk negative consequences gambling (3.7%), and problem gambling (PrG) (2.3%). At-risk and PrG classes were associated with greater negative functioning and more gambling behaviors. Different patterns of associations between at-risk and PrG classes were also identified. Conclusions Adolescent gambling classifies into 4 classes, which are differentially associated with demographic, gambling patterns, risk behaviors, and health/functioning characteristics. Early identification and interventions for adolescent gamblers should be sensitive to the heterogeneity of gambling subtypes. PMID:25275877

  4. Profiles of language development in pre-school children: a longitudinal latent class analysis of data from the Early Language in Victoria Study.

    Science.gov (United States)

    Ukoumunne, O C; Wake, M; Carlin, J; Bavin, E L; Lum, J; Skeat, J; Williams, J; Conway, L; Cini, E; Reilly, S

    2012-05-01

    Pre-school language impairment is common and greatly reduces educational performance. Population attempts to identify children who would benefit from appropriately timed intervention might be improved by greater knowledge about the typical profiles of language development. Specifically, this could be used to help with the early identification of children who will be impaired on school entry.   This study applied longitudinal latent class analysis to assessments at 8, 12, 24, 36 and 48 months on 1113 children from a population-based study, in order to identify classes exhibiting distinct communicative developmental profiles. Five substantive classes were identified: Typical, i.e. development in the typical range at each age; Precocious (late), i.e. typical development in infancy followed by high probabilities of precocity from 24 months onwards; Impaired (early), i.e. high probabilities of impairment up to 12 months followed by typical language development thereafter; Impaired (late), i.e. typical development in infancy but impairment from 24 months onwards; Precocious (early), i.e. high probabilities of precocity in early life followed by typical language by 48 months. The entropy statistic (0.84) suggested classes were fairly well defined, although there was a non-trivial degree of uncertainty in classification of children. That half of the Impaired (late) class was expected to have typical language at 4 years and 6% of the numerically large Typical class was expected to be impaired at 4 years illustrates this. Characteristics indicative of social advantage were more commonly found in the classes with improving profiles. Developmental profiles show that some pre-schoolers' language is characterized by periods of accelerated development, slow development and catch-up growth. Given the uncertainty in classifying children into these profiles, use of this knowledge for identifying children who will be impaired on school entry is not straightforward. The findings do

  5. Country and Gender-Specific Achievement of Healthy Nutrition and Physical Activity Guidelines: Latent Class Analysis of 6266 University Students in Egypt, Libya, and Palestine

    Directory of Open Access Journals (Sweden)

    Walid El Ansari

    2017-07-01

    Full Text Available Research on healthy behaviour such as physical activity and healthy nutrition and their combination is lacking among university students in Arab countries. The current survey assessed healthy nutrition, and moderate/vigorous physical activity (PA of 6266 students in Egypt, Libya, and Palestine. We computed a nutrition guideline achievement index using WHO recommendation, as well as the achievement of PA recommendations using guidelines for adults of the American Heart Association guidelines. Latent class regression analysis identified homogenous groups of male and female students, based on their achievements of both guidelines. We examined associations between group membership and achievement of guidelines. A three-class solution model best fitted the data, generating three student Groups: “Healthy Eaters” (7.7% of females, 10.8% of males, “Physically Active” (21.7% of females, 25.8% of males, and “Low Healthy Behaviour” (70.6% of females, 63.4% of males. We did not observe a latent class that exhibited combined healthy behaviours (physically active and healthy eaters, and there were no major differences between countries. We observed a very low rate of healthy nutrition (≈10% of students achieved greater than four of the eight nutrition guidelines, with little gender differences across the countries. About 18–47% of students achieved the PA guidelines, depending on country and gender, more often among males. Few females achieved the PA guidelines, particularly in Libya and Palestine. Culturally adapted multi-behavioural interventions need to encourage healthy lifestyles, nutrition and PA behaviours. National policies need to promote active living while addressing cultural, geographic, and other barriers to young adults’ engagement in PA.

  6. Country and Gender-Specific Achievement of Healthy Nutrition and Physical Activity Guidelines: Latent Class Analysis of 6266 University Students in Egypt, Libya, and Palestine.

    Science.gov (United States)

    El Ansari, Walid; Berg-Beckhoff, Gabriele

    2017-07-11

    Research on healthy behaviour such as physical activity and healthy nutrition and their combination is lacking among university students in Arab countries. The current survey assessed healthy nutrition, and moderate/vigorous physical activity (PA) of 6266 students in Egypt, Libya, and Palestine. We computed a nutrition guideline achievement index using WHO recommendation, as well as the achievement of PA recommendations using guidelines for adults of the American Heart Association guidelines. Latent class regression analysis identified homogenous groups of male and female students, based on their achievements of both guidelines. We examined associations between group membership and achievement of guidelines. A three-class solution model best fitted the data, generating three student Groups: "Healthy Eaters" (7.7% of females, 10.8% of males), "Physically Active" (21.7% of females, 25.8% of males), and "Low Healthy Behaviour" (70.6% of females, 63.4% of males). We did not observe a latent class that exhibited combined healthy behaviours (physically active and healthy eaters), and there were no major differences between countries. We observed a very low rate of healthy nutrition (≈10% of students achieved greater than four of the eight nutrition guidelines), with little gender differences across the countries. About 18-47% of students achieved the PA guidelines, depending on country and gender, more often among males. Few females achieved the PA guidelines, particularly in Libya and Palestine. Culturally adapted multi-behavioural interventions need to encourage healthy lifestyles, nutrition and PA behaviours. National policies need to promote active living while addressing cultural, geographic, and other barriers to young adults' engagement in PA.

  7. A latent profile analysis of intimate partner victimization and aggression and examination of between-class differences in psychopathology symptoms and risky behaviors.

    Science.gov (United States)

    Weiss, Nicole H; Dixon-Gordon, Katherine L; Peasant, Courtney; Jaquier, Véronique; Johnson, Clinesha; Sullivan, Tami P

    2017-05-01

    Intimate partner violence (IPV) is associated with heightened psychopathology symptoms and risky behaviors. However, extant investigations are limited by their focus on IPV victimization, despite evidence to suggest that victimization and aggression frequently co-occur. Further, research on these correlates often has not accounted for the heterogeneity of women who experience victimization. The present study utilized latent profile analysis to identify patterns of physical, psychological, and sexual victimization and aggression in a convenience sample of 212 community women experiencing victimization (Mage = 36.63, 70.8% African American), as well as examined differences in psychopathology symptoms (i.e., posttraumatic stress symptoms [PTSS] and depressive symptoms) and risky behaviors (i.e., drug problems, alcohol problems, deliberate self-harm (DSH), HIV-risk behaviors) across these classes. Four classes of women differentiated by severities of victimization and aggression were identified. Greater psychopathology symptoms were found among classes defined by greater victimization and aggression, regardless of IPV type. Risky behaviors were more prevalent among classes defined by greater sexual victimization and aggression in particular. Findings highlight the importance of developing interventions that target the particular needs of subgroups of women who experience victimization. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  8. Assessing measurement error in surveys using latent class analysis: application to self-reported illicit drug use in data from the Iranian Mental Health Survey

    Directory of Open Access Journals (Sweden)

    Kazem Khalagi

    2016-04-01

    Full Text Available Latent class analysis (LCA is a method of assessing and correcting measurement error in surveys. The local independence assumption in LCA assumes that indicators are independent from each other condition on the latent variable. Violation of this assumption leads to unreliable results. We explored this issue by using LCA to estimate the prevalence of illicit drug use in the Iranian Mental Health Survey. The following three indicators were included in the LCA models: five or more instances of using any illicit drug in the past 12 months (indicator A, any use of any illicit drug in the past 12 months (indicator B, and the self-perceived need of treatment services or having received treatment for a substance use disorder in the past 12 months (indicator C. Gender was also used in all LCA models as a grouping variable. One LCA model using indicators A and B, as well as 10 different LCA models using indicators A, B, and C, were fitted to the data. The three models that had the best fit to the data included the following correlations between indicators: (AC and AB, (AC, and (AC, BC, and AB. The estimated prevalence of illicit drug use based on these three models was 28.9%, 6.2% and 42.2%, respectively. None of these models completely controlled for violation of the local independence assumption. In order to perform unbiased estimations using the LCA approach, the factors violating the local independence assumption (behaviorally correlated error, bivocality, and latent heterogeneity should be completely taken into account in all models using well-known methods.

  9. 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.

  10. Accuracy of cerebrospinal leucocyte count, protein and culture for the diagnosis of acute bacterial meningitis: a comparative study using Bayesian latent class analysis.

    Science.gov (United States)

    Manning, Laurens; Laman, Moses; Mare, Trevor; Hwaiwhanje, Ilomo; Siba, Peter; Davis, Timothy M E

    2014-12-01

    To examine the utility of laboratory methods other than bacterial culture in diagnosing acute bacterial meningitis (ABM). Bayesian latent class analysis was used to estimate diagnostic precision of cerebrospinal fluid (CSF) culture, leucocyte counts and protein concentrations for ABM in Melanesian children. With a cut-off of ≥20 leucocytes/mm(3) , the area under the receiver operating characteristic curve (AUC ROC) was >97.5% for leucocyte counts. A lower (93%) AUC ROC was observed for CSF protein concentrations ≥1 g/l. CSF culture had poor sensitivity and high specificity. Leucocyte counts provide sufficient diagnostic precision to aid clinical decision-making in ABM. © 2014 John Wiley & Sons Ltd.

  11. Socioeconomic inequality in clusters of health-related behaviours in Europe: latent class analysis of a cross-sectional European survey.

    Science.gov (United States)

    Kino, Shiho; Bernabé, Eduardo; Sabbah, Wael

    2017-05-23

    Modifiable health-related behaviours tend to cluster among most vulnerable sectors of the population, particularly those at the bottom of the social hierarchy. This study aimed to identify the clusters of health-related behaviours in 27 European countries and to examine the socioeconomic inequalities in these clusters. Data were from Eurobarometer 72.3-2009, a cross-sectional survey of 27 European countries. The analyses were conducted in 2016. The main sections of the survey included questions pertaining to sociodemographic factors, health-related behaviours, and use of services. In this study, those aged 18 years and older were included. We selected five health-related behaviours, namely smoking, excessive alcohol consumption, frequent fresh fruit consumption, physical activity and dental check-ups. Socioeconomic position was indicated by education, subjective social status and difficulty in paying bills. Latent class analysis was conducted to explore the clusters of these five behaviours. Multinomial logistic regression model was used to examine the relationships between the clusters and socioeconomic positions adjusting for age, gender, marital status and urbanisation. The eligible total population was 23,842. Latent class analysis identified three clusters; healthy, moderate and risky clusters in this European population. Individuals with the lowest socioeconomic position were more likely to have risky and moderate clusters than healthy cluster compared to those with the highest socioeconomic position. There were clear socioeconomic gradients in clusters of health-related behaviours. The findings highlight the importance of adopting interventions that address multiple health risk behaviours and policies that tackle the social determinants of health-related behaviours.

  12. Depression symptoms are persistent in Type 2 diabetes: risk factors and outcomes of 5-year depression trajectories using latent class growth analysis.

    Science.gov (United States)

    Whitworth, S R; Bruce, D G; Starkstein, S E; Davis, W A; Davis, T M E; Skinner, T C; Bucks, R S

    2017-08-01

    To describe the long-term trajectories of depression symptom severity in people with Type 2 diabetes, and to identify predictors and associates of these trajectories. A community-dwelling cohort of 1201 individuals with Type 2 diabetes from the Fremantle Diabetes Study Phase II was followed for 5 years. The nine-item version of the Patient Health Questionnaire was administered annually to assess depression symptoms, and biomedical and psychosocial measures were assessed at baseline and biennially. Latent class growth analysis was used to identify classes of depression severity trajectories and associated outcomes, and logistic regression models were used to determine predictors of class membership. Three trajectories of depression symptoms were identified: continuously low depression symptoms (85.2%); gradually worsening symptoms that then began to improve (persistent depression - low-start; 7.3%); and gradually improving symptoms which later worsened (persistent depression - high-start; 7.5%). Younger age, being a woman, and a lifetime history of major depressive disorder, were associated with greater risk of persistent depression symptoms. Persistent depression was associated with consistently higher BMI over time, but not with changes in HbA1c or self-monitoring of blood glucose. A subset of individuals with Type 2 diabetes is at risk of depression symptoms that remain elevated over time. Younger, overweight individuals with a history of depression may benefit from early and intensive depression management and ongoing follow-up as part of routine Type 2 diabetes care. © 2017 Diabetes UK.

  13. Estimation of test characteristics of real-time PCR and bacterial culture for diagnosis of subclinical intramammary infections with Streptococcus agalactiae in Danish dairy cattle in 2012 using latent class analysis

    DEFF Research Database (Denmark)

    Mahmmod, Yasser; Toft, Nils; Katholm, Jørgen

    2013-01-01

    definition of infection may reflect a more general condition of cows being positive for S. agalactiae. Our findings indicate that PCR Ct-value cut-offs should be chosen according to the underlying latent infection definition of interest. Latent class analysis proposes a useful alternative to classic test......The misdiagnosis of intramammary infections (IMI) with Streptococcus agalactiae (S. agalactiae) could lead farmers to treat or cull animals unnecessarily. The objective of this field study was to estimate the sensitivity (Se) and specificity (Sp) of real-time PCR at different cut-offs for cycle...... threshold (Ct) values against bacterial culture (BC) for diagnosis of S. agalactiae IMI using latent class analysis to avoid the assumption of a perfect reference test. A total of 614 dairy cows were randomly selected from 6 herds with bulk tank PCR Ct value ≤ 39 for S. agalactiae and S. aureus. At milk...

  14. Classifying Married Adults Diagnosed with Alpha-1 Antitrypsin Deficiency Based on Spousal Communication Patterns Using Latent Class Analysis: Insights for Intervention

    Science.gov (United States)

    Smith, Rachel A.; Wienke, Sara E.; Baker, Michelle K.

    2013-01-01

    Married adults are increasingly exposed to test results that indicate an increased genetic risk for adult-onset conditions. For example, a SERPINA1 mutation, associated with alpha-1 antitrypsin deficiency (AATD), predisposes affected individuals to diseases such as chronic obstructive pulmonary disease (COPD) and cancer, which are often detected in adulthood. Married adults are likely to discuss genetic test results with their spouses, and interpersonal research suggests that spouses’ communication patterns differ. Latent class analysis was used to identify subgroups of spousal communication patterns about AATD results from a sample of married adults in the Alpha-1 Research Registry (N = 130). A five-class model was identified, and the subgroups were consistent with existing spousal-communication typologies. This study also showed that genetic beliefs (e.g., genetic stigma), emotions, and experiences (e.g., insurance difficulties) covaried with membership in particular subgroups. Understanding these differences can serve as the foundation for the creation of effective, targeted communications interventions to address the specific needs and conversational patterns of different kinds of couples. PMID:24177906

  15. Long-term trajectories of patients with neck pain and low back pain presenting to chiropractic care: A latent class growth analysis.

    Science.gov (United States)

    Ailliet, L; Rubinstein, S M; Hoekstra, T; van Tulder, M W; de Vet, H C W

    2018-01-01

    Information on the course of neck pain (NP) and low back pain (LBP) typically relies on data collected at few time intervals during a period of up to 1 year. In this prospective, multicentre practice-based cohort study, patients consulting a chiropractor responded weekly for 52 weeks to text messages on their cell phones. Data from 448 patients (153 NP, 295 LBP) who had returned at least one set of answers in the first 26 weeks were used. Outcome measures were pain intensity (VAS) and functional outcome, assessed using four different questions: pain intensity, limitation in activities of daily living (ADL), number of days with pain in the previous week and number of days limited in ADL. Distinct patterns of pain were analysed with quadratic latent class growth analysis. The final model was a 4-class model for NP and LBP. The 'recovering from mild baseline pain' is most common (76.3% of NP patients/58.3% of LBP patients) followed by the 'recovering from severe baseline pain' class (16.3% NP/29.8% LBP). They follow similar trajectories when considered over a period of 6 months. Pain at baseline, duration of complaints, functional status, limitations in ADL and the score on psychosocial scales were the variables that most contributed to distinguish between groups. Most patients with NP or LBP presenting in chiropractic care show a trajectory of symptoms characterized by persistent or fluctuating pain of low or medium intensity. Only a minority either experience a rapid complete recovery or develop chronic severe pain. Ninety percentage of patients with neck pain or low back pain presenting to chiropractors have a 30% improvement within 6 weeks and then show a trajectory of symptoms characterized by persistent or fluctuating pain of low or medium intensity. Only a minority either experience a rapid complete recovery or develop chronic severe pain. © 2017 European Pain Federation - EFIC®.

  16. Latent class analysis of substance use among men who have sex with men in Malaysia: Findings from the Asian Internet MSM Sex Survey.

    Science.gov (United States)

    Lim, Sin How; Cheung, Doug H; Guadamuz, Thomas E; Wei, Chongyi; Koe, Stuart; Altice, Frederick L

    2015-06-01

    High prevalence of substance use among men who have sex with men (MSM) may drive the HIV epidemic in Malaysia but patterns of substance use among Malaysian MSM have not been examined. Our study investigated specific Malaysian MSM risk groups to determine the association between their substance use and sexual risk behaviors. Data from Malaysian respondents (n=1235) in a large, multinational online survey of Asian MSM in 2010 were used to identify latent classes of substance use. Subsequent covariates were included in a joint model to predict class membership. The 3-class model was identified as the best fitting model, which included: (1) 'negligible substance use' for those reporting none or using any substance sparingly; (2) 'soft substance use' for those using poppers, ecstasy and drinking before sex; and (3) 'amphetamine-type stimulant (ATS) use' for those using stimulants (methamphetamine, ecstasy), erectile dysfunction drugs and recreational drug use before sex. Men in the 'ATS use' category were significantly less likely to not know their HIV status (AOR: 0.30, 95%CI: 0.14,0.66), more likely to have had more than 6 male sex partners (AOR: 4.83, 95% CI: 1.92-12.2), to have group sex (AOR:4.07, 95% CI: 2.31-7.15), to report inconsistent condom use (AOR:2.01, 95% CI: 1.12-3.60), to be HIV-infected (AOR:3.92, 95% CI: 1.63-8.42) and to have had any sexually transmitted infections (AOR:3.92, 95% CI:1.70, 9.08), compared to men in the 'negligible substance use' category. Our study identified subgroups of Malaysian MSM with distinct substance use patterns and HIV-related risk profiles, which provides implication for targeting HIV prevention in this subpopulation. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  17. Pooled PCR testing strategy and prevalence estimation of submicroscopic infections using Bayesian latent class models in pregnant women receiving intermittent preventive treatment at Machinga District Hospital, Malawi, 2010.

    Science.gov (United States)

    Zhou, Zhiyong; Mitchell, Rebecca Mans; Gutman, Julie; Wiegand, Ryan E; Mwandama, Dyson A; Mathanga, Don P; Skarbinski, Jacek; Shi, Ya Ping

    2014-12-18

    Low malaria parasite densities in pregnancy are a diagnostic challenge. PCR provides high sensitivity and specificity in detecting low density of parasites, but cost and technical requirements limit its application in resources-limited settings. Pooling samples for PCR detection was explored to estimate prevalence of submicroscopic malaria infection in pregnant women at delivery. Previous work uses gold-standard based methods to calculate sensitivity and specificity of tests, creating a challenge when newer methodologies are substantially more sensitive than the gold standard. Thus prevalence was estimated using Bayesian latent class models (LCMs) in this study. Nested PCR (nPCR) for the 18S rRNA gene subunit of Plasmodium falciparum was conducted to detect malaria infection in microscopy-negative Malawian women on IPTp. Two-step sample pooling used dried blood spot samples (DBSs) collected from placenta or periphery at delivery. Results from nPCR and histology as well as previously published data were used to construct LCMs to estimate assay sensitivity and specificity. Theoretical confidence intervals for prevalence of infection were calculated for two-step and one-step pooling strategies. Of 617 microscopy-negative Malawian women, 39 (6.3%) were identified as actively infected by histology while 52 (8.4%) were positive by nPCR. One hundred forty (22.7%) individuals had past infection assessed by histology. With histology as a reference, 72% of women in the active infection group, 7.1% in the past infection group and 3.2% in histology-negative group were nPCR positive. Using latent class models without a gold standard, histology had a median sensitivity of 49.7% and specificity of 97.6% for active infection while PCR had a median sensitivity of 96.0% and specificity of 99.1%. The true prevalence of active infection was estimated at 8.0% (CI: 5.8-10.5%) from PCR. PCR also had similar sensitivity for detecting either peripheral or placental malaria for

  18. Confirmatory test of two factors and four subtypes of bipolar disorder based on lifetime psychiatric co-morbidity.

    Science.gov (United States)

    Monahan, P O; Stump, T; Coryell, W H; Harezlak, J; Marcoulides, G A; Liu, H; Steeger, C M; Mitchell, P B; Wilcox, H C; Hulvershorn, L A; Glowinski, A L; Iyer-Eimerbrink, P A; McInnis, M; Nurnberger, J I

    2015-07-01

    The first aim was to use confirmatory factor analysis (CFA) to test a hypothesis that two factors (internalizing and externalizing) account for lifetime co-morbid DSM-IV diagnoses among adults with bipolar I (BPI) disorder. The second aim was to use confirmatory latent class analysis (CLCA) to test the hypothesis that four clinical subtypes are detectible: pure BPI; BPI plus internalizing disorders only; BPI plus externalizing disorders only; and BPI plus internalizing and externalizing disorders. A cohort of 699 multiplex BPI families was studied, ascertained and assessed (1998-2003) by the National Institute of Mental Health Genetics Initiative Bipolar Consortium: 1156 with BPI disorder (504 adult probands; 594 first-degree relatives; and 58 more distant relatives) and 563 first-degree relatives without BPI. Best-estimate consensus DSM-IV diagnoses were based on structured interviews, family history and medical records. MPLUS software was used for CFA and CLCA. The two-factor CFA model fit the data very well, and could not be improved by adding or removing paths. The four-class CLCA model fit better than exploratory LCA models or post-hoc-modified CLCA models. The two factors and four classes were associated with distinctive clinical course and severity variables, adjusted for proband gender. Co-morbidity, especially more than one internalizing and/or externalizing disorder, was associated with a more severe and complicated course of illness. The four classes demonstrated significant familial aggregation, adjusted for gender and age of relatives. The BPI two-factor and four-cluster hypotheses demonstrated substantial confirmatory support. These models may be useful for subtyping BPI disorders, predicting course of illness and refining the phenotype in genetic studies.

  19. Dimensional, categorical, or dimensional-categories: testing the latent structure of anxiety sensitivity among adults using factor-mixture modeling.

    Science.gov (United States)

    Bernstein, Amit; Stickle, Timothy R; Zvolensky, Michael J; Taylor, Steven; Abramowitz, Jonathan; Stewart, Sherry

    2010-12-01

    The present study tested multiple, competing latent structural models of anxiety sensitivity (AS), as measured by the Anxiety Sensitivity Index-3 (ASI-3; Taylor et al., 2007). Data were collected from 3 sites in North America (N=634). Participants were predominantly university students (M=21.3 years, SD=5.4). ASI-3 data were evaluated using an integration of mixture modeling and confirmatory factor analysis-factor mixture modeling (FMM; Muthén, 2008). Results supported a 2-class 3-factor partially invariant model of AS. Specifically, the FMM analyses indicated that AS is a taxonic (two-class) variable, and that each categorical class has a unique multidimensional factor structure. Consistent with the specific point-prediction regarding the hypothesized parameters of the putative latent class variable, FMM indicated that the putatively "high-risk" subgroup of cases or latent form of AS composed approximately 12% of the studied sample whereas the putatively "normative" subgroup of cases or latent form of AS composed 88% of the sample. In addition, the AS Physical and Psychological Concerns subscales, but not the Social Concerns subscale, most strongly discriminated between the two latent classes. Finally, comparison of continuous levels of AS Physical and Psychological Concerns between FMM-derived AS latent classes and independent clinical samples of patients with anxiety disorders provided empirical support for the theorized taxonic-dimensional model of AS and anxiety psychopathology vulnerability. Findings are discussed in regard to the implications of this and related research into the nature of AS and anxiety psychopathology vulnerability. Copyright © 2010. Published by Elsevier Ltd.

  20. Validation of a new test for Schistosoma haematobium based on detection of Dra1 DNA fragments in urine: evaluation through latent class analysis.

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    Olufunmilola Ibironke

    2012-01-01

    Full Text Available Diagnosis of urogenital schistosomiasis in chronically infected adults is challenging but important, especially because long term infection of the bladder and urinary tract can have dire consequences. We evaluated three tests for viable infection: detection of parasite specific DNA Dra1 fragments, haematuria and presence of parasite eggs for sensitivity (Se and specificity (Sp.Over 400 urine specimens collected from adult volunteers in an endemic area in Western Nigeria were assessed for haematuria then filtered in the field, the filter papers dried and later examined for eggs and DNA. The results were stratified according to sex and age and subjected to Latent Class analysis.Presence of Dra1 in males (Se=100%; Sp=100% exceeded haematuria (Se=87.6%: Sp=34.7% and detection of eggs (Se=70.1%; Sp=100%. In females presence of Dra1 was Se=100%: Sp=100%, exceeding haematuria (Se=86.7%: Sp=77.0% and eggs (Se=70.1%; Sp=100%. Dra1 became undetectable 2 weeks after praziquantel treatment. We conclude detection of Dra1 fragment is a definitive test for the presence of Schistosoma haematobium infection.

  1. Latent Class Analysis of Gambling Activities in a Sample of Young Swiss Men: Association with Gambling Problems, Substance Use Outcomes, Personality Traits and Coping Strategies.

    Science.gov (United States)

    Studer, Joseph; Baggio, Stéphanie; Mohler-Kuo, Meichun; Simon, Olivier; Daeppen, Jean-Bernard; Gmel, Gerhard

    2016-06-01

    The study aimed to identify different patterns of gambling activities (PGAs) and to investigate how PGAs differed in gambling problems, substance use outcomes, personality traits and coping strategies. A representative sample of 4989 young Swiss males completed a questionnaire assessing seven distinct gambling activities, gambling problems, substance use outcomes, personality traits and coping strategies. PGAs were identified using latent class analysis (LCA). Differences between PGAs in gambling and substance use outcomes, personality traits and coping strategies were tested. LCA identified six different PGAs. With regard to gambling and substance use outcomes, the three most problematic PGAs were extensive gamblers, followed by private gamblers, and electronic lottery and casino gamblers, respectively. By contrast, the three least detrimental PGAs were rare or non-gamblers, lottery only gamblers and casino gamblers. With regard to personality traits, compared with rare or non-gamblers, private and casino gamblers reported higher levels of sensation seeking. Electronic lottery and casino gamblers, private gamblers and extensive gamblers had higher levels of aggression-hostility. Extensive and casino gamblers reported higher levels of sociability, whereas casino gamblers reported lower levels of anxiety-neuroticism. Extensive gamblers used more maladaptive and less adaptive coping strategies than other groups. Results suggest that gambling is not a homogeneous activity since different types of gamblers exist according to the PGA they are engaged in. Extensive gamblers, electronic and casino gamblers and private gamblers may have the most problematic PGAs. Personality traits and coping skills may predispose individuals to PGAs associated with more or less negative outcomes.

  2. A General Latent Class Model for Performance Evaluation of Diagnostic Tests in the Absence of a Gold Standard: An Application to Chagas Disease

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    Gilberto de Araujo Pereira

    2012-01-01

    Full Text Available We propose a new general Bayesian latent class model for evaluation of the performance of multiple diagnostic tests in situations in which no gold standard test exists based on a computationally intensive approach. The modeling represents an interesting and suitable alternative to models with complex structures that involve the general case of several conditionally independent diagnostic tests, covariates, and strata with different disease prevalences. The technique of stratifying the population according to different disease prevalence rates does not add further marked complexity to the modeling, but it makes the model more flexible and interpretable. To illustrate the general model proposed, we evaluate the performance of six diagnostic screening tests for Chagas disease considering some epidemiological variables. Serology at the time of donation (negative, positive, inconclusive was considered as a factor of stratification in the model. The general model with stratification of the population performed better in comparison with its concurrents without stratification. The group formed by the testing laboratory Biomanguinhos FIOCRUZ-kit (c-ELISA and rec-ELISA is the best option in the confirmation process by presenting false-negative rate of 0.0002% from the serial scheme. We are 100% sure that the donor is healthy when these two tests have negative results and he is chagasic when they have positive results.

  3. Simple construct evaluation with latent class analysis: An investigation of Facebook addiction and the development of a short form of the Facebook Addiction Test (F-AT).

    Science.gov (United States)

    Dantlgraber, Michael; Wetzel, Eunike; Schützenberger, Petra; Stieger, Stefan; Reips, Ulf-Dietrich

    2016-09-01

    In psychological research, there is a growing interest in using latent class analysis (LCA) for the investigation of quantitative constructs. The aim of this study is to illustrate how LCA can be applied to gain insights on a construct and to select items during test development. We show the added benefits of LCA beyond factor-analytic methods, namely being able (1) to describe groups of participants that differ in their response patterns, (2) to determine appropriate cutoff values, (3) to evaluate items, and (4) to evaluate the relative importance of correlated factors. As an example, we investigated the construct of Facebook addiction using the Facebook Addiction Test (F-AT), an adapted version of the Internet Addiction Test (I-AT). Applying LCA facilitates the development of new tests and short forms of established tests. We present a short form of the F-AT based on the LCA results and validate the LCA approach and the short F-AT with several external criteria, such as chatting, reading newsfeeds, and posting status updates. Finally, we discuss the benefits of LCA for evaluating quantitative constructs in psychological research.

  4. Examining driver behavior at the onset of yellow in a traffic simulator environment: Comparisons between random parameters and latent class logit models.

    Science.gov (United States)

    Savolainen, Peter T

    2016-11-01

    This study involves an examination of driver behavior at the onset of a yellow signal indication. Behavioral data were obtained from a driving simulator study that was conducted through the National Advanced Driving Simulator (NADS) laboratory at the University of Iowa. These data were drawn from a series of events during which study participants drove through a series of intersections where the traffic signals changed from the green to yellow phase. The resulting dataset provides potential insights into how driver behavior is affected by distracted driving through an experimental design that alternated handheld, headset, and hands-free cell phone use with "normal" baseline driving events. The results of the study show that male drivers ages 18-45 were more likely to stop. Participants were also more likely to stop as they became more familiar with the simulator environment. Cell phone use was found to some influence on driver behavior in this setting, though the effects varied significantly across individuals. The study also demonstrates two methodological approaches for dealing with unobserved heterogeneity across drivers. These include random parameters and latent class logit models, each of which analyze the data as a panel. The results show each method to provide significantly better fit than a pooled, fixed parameter model. Differences in terms of the context of these two approaches are discussed, providing important insights as to the differences between these modeling frameworks. Copyright © 2016 Elsevier Ltd. All rights reserved.

  5. Morphological and qualitative characteristics of the quadriceps muscle of community-dwelling older adults based on ultrasound imaging: classification using latent class analysis.

    Science.gov (United States)

    Kawai, Hisashi; Kera, Takeshi; Hirayama, Ryo; Hirano, Hirohiko; Fujiwara, Yoshinori; Ihara, Kazushige; Kojima, Motonaga; Obuchi, Shuichi

    2017-06-02

    Muscle thickness and echo intensity measured using ultrasound imaging represent both increased muscle volume and connective tissue accumulation. In combination, these ultrasound measurements can be utilized for assessing sarcopenia in community-dwelling older adults. This study aimed to determine whether morphological and qualitative characteristics classified by quadriceps muscle thickness and echo intensity measured using ultrasound are associated with muscle strength, physical function, and sarcopenia in community-dwelling older adults. Quadriceps muscle thickness and echo intensity were measured using ultrasound imaging in 1239 community-dwelling older adults. Latent class analyses were conducted to classify participants based on similarity in the subcutaneous fat thickness (FT), quadriceps muscle thickness (MT), subcutaneous fat echo intensity (FEI), and muscle echo intensity (MEI), which were assessed using ultrasound imaging. Morphological and qualitative characteristics were classified into four types as follows: (A) normal, (B) sarcopenic obesity, (C) obesity, and (D) sarcopenia type. Knee extension strength was significantly greater in A than in B and D. FT and percent body fat were greater in C than in the other types. The correlation between the ultrasound measures and knee extension strength differed among the classification types. The classification types were significantly associated with sarcopenia prevalence. Classification of the morphological and qualitative characteristics obtained from ultrasound imaging may be useful for assessing sarcopenia in community-dwelling older adults.

  6. Types of integration and depressive symptoms: A latent class analysis on the resettled population for the Three Gorges dam project, China.

    Science.gov (United States)

    Xi, Juan

    2016-05-01

    Focusing on China's Three Gorges Project (TGP)-Induced Resettlement, the largest scale resettlement induced by a single development project, this study aims to investigate different types of integration patterns among the TGP re-settlers and how modes of integration associate with depressive symptoms. Using Latent Class Analysis, we analyzed survey data on 407 TGP re-settlers. We detected three integration patterns among these re-settlers: the fully integrated (68%), the culturally and economically integrated (21%) and the unintegrated (11%). We found that different integration types were linked to different levels of depressive symptoms. Unless fully integrated and experienced a warm feeling toward new community, re-settlers were vulnerable to elevated depressive symptoms. Our findings that culturally and economically integrated re-settlers had similar levels of depressive symptoms as the unintegrated re-settlers highlighted the importance of subjective dimension of integration and resettlement. We also found that rural re-settlers and those who move with the whole village were more likely to fall into the unintegrated category. Policy implications were discussed. Copyright © 2016 Elsevier Ltd. All rights reserved.

  7. Patterns of multiple health risk-behaviours in university students and their association with mental health: application of latent class analysis.

    Science.gov (United States)

    Kwan, M Y; Arbour-Nicitopoulos, K P; Duku, E; Faulkner, G

    2016-08-01

    University and college campuses may be the last setting where it is possible to comprehensively address the health of a large proportion of the young adult population. It is important that health promoters understand the collective challenges students are facing, and to better understand the broader lifestyle behavioural patterning evident during this life stage. The purpose of this study was to examine the clustering of modifiable health-risk behaviours and to explore the relationship between these identified clusters and mental health outcomes among a large Canadian university sample. Undergraduate students (n = 837; mean age = 21 years) from the University of Toronto completed the National College Health Assessment survey. The survey consists of approximately 300 items, including assessments of student health status, mental health and health-risk behaviours. Latent class analysis was used to identify patterning based on eight salient health-risk behaviours (marijuana use, other illicit drug use, risky sex, smoking, binge drinking, poor diet, physical inactivity, and insufficient sleep). A three-class model based on student behavioural patterns emerged: "typical," "high-risk" and "moderately healthy." Results also found high-risk students reporting significantly higher levels of stress than typical students (χ2(1671) = 7.26, p Students with the highest likelihood of engaging in multiple health-risk behaviours reported poorer mental health, particularly as it relates to stress. Although these findings should be interpreted with caution due to the 28% response rate, they do suggest that interventions targeting specific student groups with similar patterning of multiple health-risk behaviours may be needed.

  8. Patterns of multiple health risk-behaviours in university students and their association with mental health: application of latent class analysis

    Directory of Open Access Journals (Sweden)

    M. Y. Kwan

    2016-08-01

    Full Text Available University and college campuses may be the last setting where it is possible to comprehensively address the health of a large proportion of the young adult population. It is important that health promoters understand the collective challenges students are facing, and to better understand the broader lifestyle behavioural patterning evident during this life stage. The purpose of this study was to examine the clustering of modifiable health-risk behaviours and to explore the relationship between these identified clusters and mental health outcomes among a large Canadian university sample. Methods: Undergraduate students (n = 837; mean age = 21 years from the University of Toronto completed the National College Health Assessment survey. The survey consists of approximately 300 items, including assessments of student health status, mental health and health-risk behaviours. Latent class analysis was used to identify patterning based on eight salient health-risk behaviours (marijuana use, other illicit drug use, risky sex, smoking, binge drinking, poor diet, physical inactivity, and insufficient sleep. Results: A three-class model based on student behavioural patterns emerged: "typical," "high-risk" and "moderately healthy." Results also found high-risk students reporting significantly higher levels of stress than typical students (χ2(1671 = 7.26, p < .01. Conclusion: Students with the highest likelihood of engaging in multiple health-risk behaviours reported poorer mental health, particularly as it relates to stress. Although these findings should be interpreted with caution due to the 28% response rate, they do suggest that interventions targeting specific student groups with similar patterning of multiple health-risk behaviours may be needed.

  9. Impacts of fast food and the food retail environment on overweight and obesity in China: a multilevel latent class cluster approach.

    Science.gov (United States)

    Zhang, Xiaoyong; van der Lans, Ivo; Dagevos, Hans

    2012-01-01

    To simultaneously identify consumer segments based on individual-level consumption and community-level food retail environment data and to investigate whether the segments are associated with BMI and dietary knowledge in China. A multilevel latent class cluster model was applied to identify consumer segments based not only on their individual preferences for fast food, salty snack foods, and soft drinks and sugared fruit drinks, but also on the food retail environment at the community level. The data came from the China Health and Nutrition Survey (CHNS) conducted in 2006 and two questionnaires for adults and communities were used. A total sample of 9788 adults living in 218 communities participated in the CHNS. We successfully identified four consumer segments. These four segments were embedded in two types of food retail environment: the saturated food retail environment and the deprived food retail environment. A three-factor solution was found for consumers' dietary knowledge. The four consumer segments were highly associated with consumers' dietary knowledge and a number of sociodemographic variables. The widespread discussion about the relationships between fast-food consumption and overweight/obesity is irrelevant for Chinese segments that do not have access to fast food. Factors that are most associated with segments with a higher BMI are consumers' (incorrect) dietary knowledge, the food retail environment and sociodemographics. The results provide valuable insight for policy interventions on reducing overweight/obesity in China. This study also indicates that despite the breathtaking changes in modern China, the impact of 'obesogenic' environments should not be assessed too strictly from a 'Western' perspective.

  10. Accuracy of parasitological and immunological tests for the screening of human schistosomiasis in immigrants and refugees from African countries: An approach with Latent Class Analysis.

    Science.gov (United States)

    Beltrame, Anna; Guerriero, Massimo; Angheben, Andrea; Gobbi, Federico; Requena-Mendez, Ana; Zammarchi, Lorenzo; Formenti, Fabio; Perandin, Francesca; Buonfrate, Dora; Bisoffi, Zeno

    2017-06-01

    Schistosomiasis is a neglected infection affecting millions of people, mostly living in sub-Saharan Africa. Morbidity and mortality due to chronic infection are relevant, although schistosomiasis is often clinically silent. Different diagnostic tests have been implemented in order to improve screening and diagnosis, that traditionally rely on parasitological tests with low sensitivity. Aim of this study was to evaluate the accuracy of different tests for the screening of schistosomiasis in African migrants, in a non endemic setting. A retrospective study was conducted on 373 patients screened at the Centre for Tropical Diseases (CTD) in Negrar, Verona, Italy. Biological samples were tested with: stool/urine microscopy, Circulating Cathodic Antigen (CCA) dipstick test, ELISA, Western blot, immune-chromatographic test (ICT). Test accuracy and predictive values of the immunological tests were assessed primarily on the basis of the results of microscopy (primary reference standard): ICT and WB resulted the test with highest sensitivity (94% and 92%, respectively), with a high NPV (98%). CCA showed the highest specificity (93%), but low sensitivity (48%). The analysis was conducted also using a composite reference standard, CRS (patients classified as infected in case of positive microscopy and/or at least 2 concordant positive immunological tests) and Latent Class Analysis (LCA). The latter two models demonstrated excellent agreement (Cohen's kappa: 0.92) for the classification of the results. In fact, they both confirmed ICT as the test with the highest sensitivity (96%) and NPV (97%), moreover PPV was reasonably good (78% and 72% according to CRS and LCA, respectively). ELISA resulted the most specific immunological test (over 99%). The ICT appears to be a suitable screening test, even when used alone. The rapid test ICT was the most sensitive test, with the potential of being used as a single screening test for African migrants.

  11. Latent class evaluation of a milk test, a urine test, and the fat-to-protein percentage ratio in milk to diagnose ketosis in dairy cows.

    Science.gov (United States)

    Krogh, M A; Toft, N; Enevoldsen, C

    2011-05-01

    In this study, 3 commonly used tests to diagnose ketosis were evaluated with a latent class model to avoid the assumption of an available perfect test. The 3 tests were the KetoLac BHB (Sanwa Kagaku Kenkyusho Co. Ltd., Nagoya, Japan) test strip that tests milk for β-hydroxybutyrate, the KetoStix (Bayer Diagnostics Europe Ltd., Dublin, Ireland) test strip that tests urine for acetoacetate, and the fat-to-protein percentage ratio (FPR) in milk. A total of 8,902 cows were included in the analysis. The cows were considered to be a random sample from the population of Danish dairy cattle under intensive management, thus representing a natural spectrum of ketosis as a disease. All cows had a recorded FPR between 7 and 21 d postpartum. The KetoLac BHB recordings were available from 2,257 cows and 6,645 cows had a KetoStix recording. The recordings were analyzed with a modified Hui-Walter model, in a Bayesian framework. The specificity of the KetoLac BHB test and the KetoStix test were both high [0.99 (0.97-0.99)], whereas the specificity of FPR was somewhat lower [0.79 (0.77-0.81)]. The best sensitivity was for the KetoStix test [0.78 (0.55-0.98)], followed by the FPR [0.63 (0.58-0.71)] and KetoLac BHB test [0.58 (0.35-0.93)]. Copyright © 2011 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  12. Accuracy of parasitological and immunological tests for the screening of human schistosomiasis in immigrants and refugees from African countries: An approach with Latent Class Analysis.

    Directory of Open Access Journals (Sweden)

    Anna Beltrame

    2017-06-01

    Full Text Available Schistosomiasis is a neglected infection affecting millions of people, mostly living in sub-Saharan Africa. Morbidity and mortality due to chronic infection are relevant, although schistosomiasis is often clinically silent. Different diagnostic tests have been implemented in order to improve screening and diagnosis, that traditionally rely on parasitological tests with low sensitivity. Aim of this study was to evaluate the accuracy of different tests for the screening of schistosomiasis in African migrants, in a non endemic setting.A retrospective study was conducted on 373 patients screened at the Centre for Tropical Diseases (CTD in Negrar, Verona, Italy. Biological samples were tested with: stool/urine microscopy, Circulating Cathodic Antigen (CCA dipstick test, ELISA, Western blot, immune-chromatographic test (ICT. Test accuracy and predictive values of the immunological tests were assessed primarily on the basis of the results of microscopy (primary reference standard: ICT and WB resulted the test with highest sensitivity (94% and 92%, respectively, with a high NPV (98%. CCA showed the highest specificity (93%, but low sensitivity (48%. The analysis was conducted also using a composite reference standard, CRS (patients classified as infected in case of positive microscopy and/or at least 2 concordant positive immunological tests and Latent Class Analysis (LCA. The latter two models demonstrated excellent agreement (Cohen's kappa: 0.92 for the classification of the results. In fact, they both confirmed ICT as the test with the highest sensitivity (96% and NPV (97%, moreover PPV was reasonably good (78% and 72% according to CRS and LCA, respectively. ELISA resulted the most specific immunological test (over 99%. The ICT appears to be a suitable screening test, even when used alone.The rapid test ICT was the most sensitive test, with the potential of being used as a single screening test for African migrants.

  13. Awareness Levels about Breast Cancer Risk Factors, Early Warning Signs, and Screening and Therapeutic Approaches among Iranian Adult Women: A large Population Based Study Using Latent Class Analysis

    Directory of Open Access Journals (Sweden)

    Mahdi Tazhibi

    2014-01-01

    Full Text Available Background and Objective. Breast cancer (BC continues to be a major cause of morbidity and mortality among women throughout the world and in Iran. Lack of awareness and early detection program in developing country is a main reason for escalating the mortality. The present research was conducted to assess the Iranian women’s level of knowledge about breast cancer risk factors, early warning signs, and therapeutic and screening approaches, and their correlated determinants. Methods. In a cross-sectional study, 2250 women before participating at a community based screening and public educational program in an institute of cancer research in Isfahan, Iran, in 2012 were investigated using a self-administered questionnaire about risk factors, early warning signs, and therapeutic and screening approaches of BC. Latent class regression as a comprehensive statistical method was used for evaluating the level of knowledge and its correlated determinants. Results. Only 33.2%, 31.9%, 26.7%, and 35.8% of study participants had high awareness levels about screening approaches, risk factors, early warning signs and therapeutic modalities of breast cancer, respectively, and majority had poor to moderate knowledge levels. Most effective predictors of high level of awareness were higher educational qualifications, attending in screening and public educational programs, personal problem, and family history of BC, respectively. Conclusion. Results of current study indicated that the levels of awareness among study population about key elements of BC are low. These findings reenforce the continuing need for more BC education through conducting public and professional programs that are intended to raise awareness among younger, single women and those with low educational attainments and without family history.

  14. Rapid antigen detection tests for malaria diagnosis in severely ill Papua New Guinean children: a comparative study using Bayesian latent class models.

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    Laurens Manning

    Full Text Available BACKGROUND: Although rapid diagnostic tests (RDTs have practical advantages over light microscopy (LM and good sensitivity in severe falciparum malaria in Africa, their utility where severe non-falciparum malaria occurs is unknown. LM, RDTs and polymerase chain reaction (PCR-based methods have limitations, and thus conventional comparative malaria diagnostic studies employ imperfect gold standards. We assessed whether, using Bayesian latent class models (LCMs which do not require a reference method, RDTs could safely direct initial anti-infective therapy in severe ill children from an area of hyperendemic transmission of both Plasmodium falciparum and P. vivax. METHODS AND FINDINGS: We studied 797 Papua New Guinean children hospitalized with well-characterized severe illness for whom LM, RDT and nested PCR (nPCR results were available. For any severe malaria, the estimated prevalence was 47.5% with RDTs exhibiting similar sensitivity and negative predictive value (NPV to nPCR (≥96.0%. LM was the least sensitive test (87.4% and had the lowest NPV (89.7%, but had the highest specificity (99.1% and positive predictive value (98.9%. For severe falciparum malaria (prevalence 42.9%, the findings were similar. For non-falciparum severe malaria (prevalence 6.9%, no test had the WHO-recommended sensitivity and specificity of >95% and >90%, respectively. RDTs were the least sensitive (69.6% and had the lowest NPV (96.7%. CONCLUSIONS: RDTs appear a valuable point-of-care test that is at least equivalent to LM in diagnosing severe falciparum malaria in this epidemiologic situation. None of the tests had the required sensitivity/specificity for severe non-falciparum malaria but the number of false-negative RDTs in this group was small.

  15. Comparative Study of Kaposi's Sarcoma-Associated Herpesvirus Serological Assays Using Clinically and Serologically Defined Reference Standards and Latent Class Analysis▿

    Science.gov (United States)

    Nascimento, Maria Claudia; de Souza, Vanda Akico; Sumita, Laura Masami; Freire, Wilton; Munoz, Fernando; Kim, Joseph; Pannuti, Claudio S.; Mayaud, Philippe

    2007-01-01

    Accurate determination of infection with Kaposi's sarcoma-associated herpesvirus (KSHV) has been hindered by the lack of a “gold standard” for comparison of serological assays used to estimate KSHV prevalence in serosurveys conducted in different settings. We have evaluated the performance of five in-house (developed at University College London [UCL], United Kingdom, and at the virology laboratory of the Instituto de Medicine Tropical [IMT] in Sao Paulo, Brazil) and two commercial (ABI and DIAVIR) serological assays to detect antibodies to latency-associated nuclear antigen (LANA) and to lytic KSHV antigens. We used a variety of serum samples assembled to represent populations likely to be at high, intermediate, and low risk of KSHV infection in Brazil. Composite reference standard panels were prepared based on clinical and serological parameters, against which assay performances were assessed using conventional Bayesian statistics and latent class analysis (LCA). Against the clinical reference standard, in-house immunofluorescence assays to detect anti-LANA antibodies (IFA-LANA) produced at UCL and IMT had similar performances, with sensitivities of 61% (95% confidence interval [CI], 48% to 74%) and 72% (95% CI, 58% to 83%) and specificities of 99% (95% CI, 94% to 100%) and 100% (95% CI, 96% to 100%), respectively, and only the IMT IFA-LANA was included in LCA, together with the IMT IFA-lytic and four enzyme-linked immunosorbent assays (ELISAs). The LCA indicated that the IMT whole-virus ELISA performed best (sensitivity, 87% [95% CI, 81% to 91%]; and specificity, 100% [95% CI, 98% to 100%]), confirming the results obtained with the conventional statistical approach. Commercially available ELISA-based tests yielded the lowest specificities using a spectrum of serum samples. The evaluation of KSHV serological assays is warranted before planning serosurveys in various settings. PMID:17182752

  16. A Latent Class Model to discover Household Food Waste Patterns in Lisbon City in Support of Food Security, Public Health and Environmental Protection

    Directory of Open Access Journals (Sweden)

    Jaime R.S. Fonseca

    2013-11-01

    Full Text Available 800x600 In the middle of a great world financial crisis that also affects food security, it is important to characterize the habits of households concerning the buying and wasting food. With this study we intend (1 to uncover the patterns of Portuguese citizens concerning food waste by using a mixed research approach and (2 to identify demographic factors that can influence the production of food waste and that may support initiatives towards the education of society on food waste. We used a random sample of 542 Portuguese citizens to identify consumer profiles and 18 in-depth interviews for better understanding the uncovered profiles in a mixed method research approach. Through a two-latent class model two clusters of consumers were identified: cluster 1, the Non food waste citizens with 65% of respondents, mainly 24 years or more, female and married or divorced and cluster 2, the Food waste citizens  with 35% of respondents, mainly up to 23 years old, male and single. Our findings may impact in two distinct ways: they may be used to educate Portuguese citizens concerning the issue of food waste and they may be useful in contributing to a less polluted world. Normal 0 21 false false false DE X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0pt 5.4pt 0pt 5.4pt; mso-para-margin:0pt; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman","serif";}

  17. Using latent class analysis to develop a model of the relationship between socioeconomic position and ethnicity: cross-sectional analyses from a multi-ethnic birth cohort study.

    Science.gov (United States)

    Fairley, Lesley; Cabieses, Baltica; Small, Neil; Petherick, Emily S; Lawlor, Debbie A; Pickett, Kate E; Wright, John

    2014-08-12

    Almost all studies in health research control or investigate socioeconomic position (SEP) as exposure or confounder. Different measures of SEP capture different aspects of the underlying construct, so efficient methodologies to combine them are needed. SEP and ethnicity are strongly associated, however not all measures of SEP may be appropriate for all ethnic groups. We used latent class analysis (LCA) to define subgroups of women with similar SEP profiles using 19 measures of SEP. Data from 11,326 women were used, from eight different ethnic groups but with the majority from White British (40%) or Pakistani (45%) backgrounds, who were recruited during pregnancy to the Born in Bradford birth cohort study. Five distinct SEP subclasses were identified in the LCA: (i) "Least socioeconomically deprived and most educated" (20%); (ii) "Employed and not materially deprived" (19%); (iii) "Employed and no access to money" (16%); (iv) "Benefits and not materially deprived" (29%) and (v) "Most economically deprived" (16%). Based on the magnitude of the point estimates, the strongest associations were that compared to White British women, Pakistani and Bangladeshi women were more likely to belong to groups: (iv) "benefits and not materially deprived" (relative risk ratio (95% CI): 5.24 (4.44, 6.19) and 3.44 (2.37, 5.00), respectively) or (v) most deprived group (2.36 (1.96, 2.84) and 3.35 (2.21, 5.06) respectively) compared to the least deprived class. White Other women were more than twice as likely to be in the (iv) "benefits and not materially deprived group" compared to White British women and all ethnic groups, other than the Mixed group, were less likely to be in the (iii) "employed and not materially deprived" group than White British women. LCA allows different aspects of an individual's SEP to be considered in one multidimensional indicator, which can then be integrated in epidemiological analyses. Ethnicity is strongly associated with these identified subgroups

  18. Testing and verifying nursing theory by confirmatory factor analysis.

    Science.gov (United States)

    Kääriäinen, Maria; Kanste, Outi; Elo, Satu; Pölkki, Tarja; Miettunen, Jouko; Kyngäs, Helvi

    2011-05-01

    This paper presents a discussion of the use of confirmatory factor analysis to test nursing theory. Theory testing is an important phase in nursing theory development. Testing of theory is intended to give more information about concepts and their usefulness in nursing practice. Confirmatory factor analysis is commonly used in instrument development in nursing science studies, but also in theory testing. However, there has been little discussion of its use in theory testing in nursing science research. Multidisciplinary methodological and research publications from 1990 to 2009 were used. The aim of confirmatory factor analysis is to test nursing theory that has already been established, i.e. researchers have an a priori hypothesis based on theoretical knowledge or empirical indications. Analysis is represented as three phases: preparation, model testing and reporting the results. Preparation involves data screening and preliminary analyses. Model testing is divided into model specification, model identification, model estimation, model evaluation and model modification. The results are reported with standardized regression coefficients of the items related to the latent variables, squared multiple correlations (R²) related to error terms and the model's goodness of fit indexes. Implications for nursing. Testing of theory is intended to give more valid information about the concepts and their usefulness in nursing practice. Confirmatory factor analysis is a good method to test the structure of theory, for example to test the concepts built by concept synthesis or analysis. Tested theories are needed to develop nursing science itself. © 2011 The Authors. Journal of Advanced Nursing © 2011 Blackwell Publishing Ltd.

  19. 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…

  20. Identifying developmental trajectories of body mass index in childhood using latent class growth (mixture modelling: associations with dietary, sedentary and physical activity behaviors: a longitudinal study

    Directory of Open Access Journals (Sweden)

    Maaike Koning

    2016-10-01

    Full Text Available Abstract Background To date, many epidemiologic studies examining associations between obesity and dietary and sedentary/physical activity behaviors have focused on assessing Body Mass Index (BMI at one point in time. Recent developments in statistical techniques make it possible to study the potential heterogeneity in the development of BMI during childhood by identifying distinct subpopulations characterized by distinct developmental trajectories. Using Latent Class Growth (Mixture Modelling (LCGMM techniques we aimed to identify BMI trajectories in childhood and to examine associations between these distinct trajectories and dietary, sedentary and physical activity behaviors. Methods This longitudinal study explored BMI standard deviation score (SDS trajectories in a sample of 613 children from 4 to 12 years of age. In 2006, 2009 and 2012 information on children’s health related behaviors was obtained by parental questionnaires, and children’s height and weight were measured. Associations with behaviors were investigated with logistic regression models. Results We identified two BMI SDS trajectories; a decreasing BMI SDS trajectory (n = 416; 68 % and an increasing BMI SDS trajectory (n = 197; 32 %. The increasing BMI SDS trajectory consisted of more participants of lower socio-economic status (SES and of non-western ethnicity. Maternal overweight status was associated with being in the increasing BMI SDS trajectory at both baseline and follow-up six years later (2006: Odds Ratio (OR, 2.9; 95 % confidence interval (CI 1.9 to 4.3; 2012 OR, 1.8; 95 % CI 1.2 to 2.6. The increasing BMI SDS trajectory was associated with the following behaviors; drinking sugared drinks > 3 glasses per day, participation in organized sports  2 h per day, though participation in organized sports at follow-up was the only significant result. Conclusions Our results indicate the importance of healthy lifestyle behaviors at a young age, and

  1. Estimating sensitivity and specificity of a PCR for boot socks to detect Campylobacter in broiler primary production using Bayesian latent class analysis.

    Science.gov (United States)

    Matt, Monika; Nordentoft, Steen; Kopacka, Ian; Pölzler, Thomas; Lassnig, Heimo; Jelovcan, Sandra; Stüger, Hans Peter

    2016-06-01

    The present study compares three different assays for sample collection and detection of Campylobacter spp. in broiler flocks, based on (i) the collection of faecal samples from intestinal organs (caecum), (ii) individual faecal droppings collected from the bedding and (iii) faecal material collected by socks placed on the outside of a pair of boots (boot socks) and used for walking around in the flock. The two first methods are examined for Campylobacter using a culture method (ISO-10272-2:2006), while the boot socks are tested using PCR. The PCR-assay is a genus specific multiplex PCR with primers targeting 16S rDNA in Campylobacter and primers targeting Yersinia ruckerii. Sixty-seven broiler flocks from Austria and 83 broiler flocks from Denmark were included in this prospective study and 89 of these were found to be positive in at least one method (AT: 49 samples, DK: 40 samples) whereas 61 of these were negative in all assays. In Austria samples for the three assays were collected simultaneously, which facilitates a direct comparison of the diagnostic test performance. In Denmark, however, boot socks and faecal droppings were collected three days before slaughter while caecum samples were collected at slaughter. The results were evaluated in the absence of a gold standard using a Bayesian latent class model. Austrian results showed higher sensitivity for PCR detection in sock samples (0.98; Bayesian credible interval (BCI) [0.93-1]) than for culture of faecal droppings (0.86; BCI [0.76-0.91]) or caecal samples (0.92; BCI [0.85-0.97]). The potential impact of Campylobacter introduction within the final three days before slaughter was observed in Denmark, where four flocks were tested negative three days before slaughter, but were detected positive at the slaughterhouse. Therefore the model results for the PCR sensitivity (0.88; BCI [0.83-0.97]) and cultural ISO-method in faecal samples (0.84; BCI [0.76-0.92]) are lower than for caecal samples (0.93; BCI [0

  2. Evaluation of fecal culture and fecal RT-PCR to detect Mycobacterium avium ssp. paratuberculosis fecal shedding in dairy goats and dairy sheep using latent class Bayesian modeling.

    Science.gov (United States)

    Bauman, Cathy A; Jones-Bitton, Andria; Jansen, Jocelyn; Kelton, David; Menzies, Paula

    2016-09-20

    The study's objective was to evaluate the ability of fecal culture (FCUL) and fecal PCR (FPCR) to identify dairy goat and dairy sheep shedding Mycobacterium avium ssp. paratuberculosis. A cross-sectional study of the small ruminant populations was performed in Ontario, Canada between October 2010 and August 2011. Twenty-nine dairy goat herds and 21 dairy sheep flocks were visited, and 20 lactating females > two years of age were randomly selected from each farm resulting in 580 goats and 397 sheep participating in the study. Feces were collected per rectum and cultured using the BD BACTEC™ MGIT™ 960 system using a standard (49 days) and an extended (240 days) incubation time, and underwent RT-PCR based on the hsp-X gene (Tetracore®). Statistical analysis was performed using a 2-test latent class Bayesian hierarchical model for each species fitted in WinBUGS. Extending the fecal culture incubation time statistically improved FCUL sensitivity from 23.1 % (95 % PI: 15.9-34.1) to 42.7 % (95 % PI: 33.0-54.5) in dairy goats and from 5.8 % (95 % PI: 2.3-12.4) to 19.0 % (95 % PI: 11.9-28.9) in dairy sheep. FPCR demonstrated statistically higher sensitivity than FCUL (49 day incubation) with a sensitivity of 31.9 % (95 % PI: 22.4-43.1) in goats and 42.6 % (95 % PI: 28.8-63.3) in sheep. Fecal culture demonstrates such low sensitivity at the standard incubation time it cannot be recommended as a screening test to detect shedding of MAP in either goats or sheep. Extending the incubation time resulted in improved sensitivity; however, it is still disappointingly low for screening purposes. Fecal PCR should be the screening test of choice in both species; however, it is important to recognize that control programs should not be based on testing alone when they demonstrate such low sensitivity.

  3. Latent class analysis of the diagnostic characteristics of PCR and conventional bacteriological culture in diagnosing intramammary infections caused by Staphylococcus aureus in dairy cows at dry off

    Directory of Open Access Journals (Sweden)

    Cederlöf Sara Ellinor

    2012-11-01

    Full Text Available Abstract Background Staphylococcus aureus is one of the most common causes of intramammary infections in dairy cows at dry off. Reliable identification is important for disease management on herd level and for antimicrobial treatment of infected animals. Our objective was to evaluate the test characteristics of PathoProof ™ Mastitis PCR Assay and bacteriological culture (BC in diagnosing bovine intramammary infections caused by S. aureus at dry off at different PCR cycle threshold (Ct-value cut-offs. Methods Sterile quarter samples and non-sterile composite samples from 140 animals in seven herds were collected in connection with the dairy herd improvement (DHI milk recording. All quarter samples were analyzed using BC whereas all composite samples were analyzed with PathoProof ™ Mastitis PCR Assay. Latent class analysis was used to estimate test properties for PCR and BC in the absence of a perfect reference test. The population was divided into two geographically divided subpopulations and the Hui-Walter 2-test 2-populations model applied to estimate Se, Sp for the two tests, and prevalence for the two subpopulations. Results The Se for PCR increased with increasing Ct-value cut-off, accompanied by a small decrease in Sp. For BC the Se decreased and Sp increased with increasing Ct-value cut-off. Most optimal test estimates for the real-time PCR assay were at a Ct-value cut-off of 37; 0.93 [95% posterior probability interval (PPI 0.60-0.99] for Se and 0.95 [95% PPI 0.95-0.99] for Sp. At the same Ct-value cut-off, Se and Sp for BC were 0.83 [95% PPI 0.66-0.99] and 0.97 [95% PPI 0.91-0.99] respectively. Depending on the chosen PCR Ct-value cut-off, the prevalence in the subpopulations varied; the prevalence increased with increasing PCR Ct-value cut-offs. Conclusion Neither BC nor real-time PCR is a perfect test in detecting IMI in dairy cows at dry off. The changes in sensitivity and prevalence at different Ct-value cut-offs for both PCR and

  4. Latent Class Models in the Assessment of Education: The Case of Students’ Academic Attainment in Elementary Education in Zacatecas Modelos de Clase Latente en la Evaluación de la Educación. El Caso del Aprovechamiento Escolar en la Educación Primaria de Zacatecas.

    Directory of Open Access Journals (Sweden)

    Francisco Muro González

    2008-01-01

    Full Text Available Based on an advanced statistical method (Latent Class Analysis, the author jointly examines two crucial factors in the assessment of students? performance in elementary school: School attainment and teacher education ( based on teachers? results in tests taken to earn their teaching credentials. Data from files in the 2001 Archives for the State of Zacatecas, Mexico are used to make this analysis. The author shows that when working with latent class models, one can make a more significant in depth analysis because by virtue of using this method, it is viable to construct suitable clusters and to segment the data files more efficiently in order to find differentiated effects of parameters in the population. A partir de una metodología de estadística avanzada, la de análisis de clase latente, el autor analiza conjuntamente dos archivos cruciales en la evaluación del desempeño de los estudiantes de primaria: los de factor aprovechamiento escolar y factor preparación profesional (o resultados de los exámenes de carrera magisterial. El autor utiliza para ello los archivos correspondientes al año 2001 del estado de Zacatecas. En el texto se muestra que al trabajar con modelos de clase latente se puede ganar significativamente en profundidad en el análisis, pues mediante este método es viable construir clusters adecuados y segmentar eficientemente el archivo de datos para encontrar efectos diferenciados de los parámetros en la población.


    1En el año del 2003 tuve la oportunidad de realizar un estudio para la Secretaría de Educación y Cultura del gobierno del estado de Zacatecas, México, motivo por el cual se me dio acceso a los datos referidos.

  5. 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…

  6. The overlap of youth violence among aggressive adolescents with past-year alcohol use-A latent class analysis: aggression and victimization in peer and dating violence in an inner city emergency department sample.

    Science.gov (United States)

    Whiteside, Lauren K; Ranney, Megan L; Chermack, Stephen T; Zimmerman, Marc A; Cunningham, Rebecca M; Walton, Maureen A

    2013-01-01

    The purpose of this study was to identify overlap and violence types between peer and dating aggression and victimization using latent class analysis (LCA) among a sample of aggressive adolescents with a history of alcohol use and to identify risk and protective factors associated with each violence class. From September 2006 to September 2009, a systematic sample of patients (14-18 years old) seeking care in an urban emergency department were approached. Adolescents reporting any past-year alcohol use and aggression completed a survey using validated measures including types of violence (severe and moderate aggression, severe and moderate victimization with both peers and dating partners). Using LCA, violence classes were identified; correlates of membership in each LCA class were determined. Among this sample (n = 694), LCA identified three classes described as (a) peer aggression (PA) (52.2%), (b) peer aggression + peer victimization (PAPV) (18.6%), and (c) multiple domains of violence (MDV) (29.3%). Compared with those in the PA class, those in the PAPV class were more likely to be male, report injury in a fight, and have delinquent peers. Compared with the PA class, those in the MDV class were more likely to be female, African American, report injury in a fight, carry a weapon, experience negative consequences from alcohol use, and have delinquent peers and more family conflict. Compared with the PAPV class, those in the MDV class were likely to be female, African American, receive public assistance, carry a weapon, experience negative consequences from alcohol use, and use marijuana. There is extensive overlap of victimization and aggression in both peer and dating relationships. Also, those with high rates of violence across relationships have increased alcohol misuse and marijuana use. Thus, violence-prevention efforts should consider addressing concomitant substance use.

  7. Estimation of sensitivity and specificity of pregnancy diagnosis using transrectal ultrasonography and ELISA for pregnancy-associated glycoprotein in dairy cows using a Bayesian latent class model.

    Science.gov (United States)

    Shephard, R W; Morton, J M

    2018-01-01

    To determine the sensitivity (Se) and specificity (Sp) of pregnancy diagnosis using transrectal ultrasonography and an ELISA for pregnancy-associated glycoprotein (PAG) in milk, in lactating dairy cows in seasonally calving herds approximately 85-100 days after the start of the herd's breeding period. Paired results were used from pregnancy diagnosis using transrectal ultrasonography and ELISA for PAG in milk carried out approximately 85 and 100 days after the start of the breeding period, respectively, from 879 cows from four herds in Victoria, Australia. A Bayesian latent class model was used to estimate the proportion of cows pregnant, the Se and Sp of each test, and covariances between test results in pregnant and non-pregnant cows. Prior probability estimates were defined using beta distributions for the expected proportion of cows pregnant, Se and Sp for each test, and covariances between tests. Markov Chain Monte Carlo iterations identified posterior distributions for each of the unknown variables. Posterior distributions for each parameter were described using medians and 95% probability (i.e. credible) intervals (PrI). The posterior median estimates for Se and Sp for each test were used to estimate positive predictive and negative predictive values across a range of pregnancy proportions. The estimate for proportion pregnant was 0.524 (95% PrI = 0.485-0.562). For pregnancy diagnosis using transrectal ultrasonography, Se and Sp were 0.939 (95% PrI = 0.890-0.974) and 0.943 (95% PrI = 0.885-0.984), respectively; for ELISA, Se and Sp were 0.963 (95% PrI = 0.919-0.990) and 0.870 (95% PrI = 0.806-0.931), respectively. The estimated covariance between test results was 0.033 (95% PrI = 0.008-0.046) and 0.035 (95% PrI = 0.018-0.078) for pregnant and non-pregnant cows, respectively. Pregnancy diagnosis results using transrectal ultrasonography had a higher positive predictive value but lower negative predictive value than results from the

  8. Latent class profiles of internalizing and externalizing psychosocial health indicators are differentially associated with sexual transmission risk: Findings from the CFAR network of integrated clinical systems (CNICS) cohort study of HIV-infected men engaged in primary care in the United States.

    Science.gov (United States)

    Mimiaga, Matthew J; Biello, Katie; Reisner, Sari L; Crane, Heidi M; Wilson, Johannes; Grasso, Chris; Kitahata, Mari M; Mathews, Wm Christopher; Mayer, Kenneth H; Safren, Steven A

    2015-09-01

    To examine whether latent class indicators of negative affect and substance use emerged as distinct psychosocial risk profiles among HIV-infected men, and if these latent classes were associated with high-risk sexual behaviors that may transmit HIV. Data were from HIV-infected men who reported having anal intercourse in the past 6 months and received routine clinical care at 4 U.S. sites in the Centers for AIDS Research Network of Integrated Clinical Systems cohort (n = 1,210). Latent class membership was estimated using binary indicators for anxiety, depression, alcohol and/or drug use during sex, and polydrug use. Generalized estimating equations modeled whether latent class membership was associated with HIV sexual transmission risk in the past 6 months. Three latent classes of psychosocial indicators emerged: (a) internalizing (15.3%; high probability of anxiety and major depression); (b) externalizing (17.8%; high probability of alcohol and/or drug use during sex and polydrug use); (c) low psychosocial distress (67.0%; low probability of all psychosocial factors examined). Internalizing and externalizing latent class membership were associated with HIV sexual transmission risk, compared to low psychosocial class membership; externalizing class membership was also associated with higher sexual transmission risk compared to internalizing class membership. Distinct patterns of psychosocial health characterize this sexually active HIV-infected male patient population and are strongly associated with HIV sexual transmission risk. Public Health intervention efforts targeting HIV sexual risk transmission may benefit from considering symptom clusters that share internalizing or externalizing properties. (c) 2015 APA, all rights reserved).

  9. A confirmatory factor analysis of the General Health Questionnaire-28 in a Black South African sample.

    Science.gov (United States)

    de Kock, Francois S; Görgens-Ekermans, Gina; Dhladhla, Thamsanqla J

    2014-10-01

    This study examined the latent factor structure of the General Health Questionnaire-28 (GHQ-28) in a Black South African sample (N = 523). Results of the single-group confirmatory factor analysis support the universal four-factor structure of general psychological health observed in Western samples. However, multigroup confirmatory factor analyses (i.e. split-sample cross-validation approach, conducted with invariance analyses) for a three-factor structure suggest that psychological health could have a less differentiated dimensional structure in some African populations. Theoretical and practical implications of the study results are discussed. © The Author(s) 2013.

  10. Identifying a combined construct of grief and explosive anger as a response to injustice amongst survivors of mass conflict: A latent class analysis of data from Timor-Leste.

    Directory of Open Access Journals (Sweden)

    Susan J Rees

    Full Text Available Previous studies have identified high rates of explosive anger amongst post-conflict populations including Timor-Leste. We sought to test whether explosive anger was integrally associated with symptoms of grief amongst the Timorese, a society that has experienced extensive conflict-related losses. In 2010 and 2011 we recruited adults (n = 2964, 18-years and older, living in an urban and a rural village in Timor-Leste. We applied latent class analysis to identify subpopulations based on symptoms of explosive anger and grief. The best fitting model comprised three classes: grief (24%, grief-anger (25%, and a low symptom group (51%. There were more women and urban dwellers in the grief and grief-anger classes compared to the reference class. Persons in the grief and grief-anger classes experienced higher rates of witnessing murder and atrocities and traumatic losses, ongoing poverty, and preoccupations with injustice for the two historical periods of conflict (the Indonesian occupation and the later internal conflict. Compared to the reference class, only the grief-anger class reported greater exposure to extreme deprivations during the conflict, ongoing family conflict, and preoccupations with injustice for contemporary times; and compared to the grief class, greater exposure to traumatic losses, poverty, family conflict and preoccupations with injustice for both the internal conflict and contemporary times. A substantial number of adults in this post-conflict country experienced a combined constellation of grief and explosive anger associated with extensive traumatic losses, deprivations, and preoccupations with injustice. Importantly, grief-anger may be linked to family conflict in this post-conflict environment.

  11. Handbook of latent variable and related models

    CERN Document Server

    Lee, Sik-Yum

    2011-01-01

    This Handbook covers latent variable models, which are a flexible class of models for modeling multivariate data to explore relationships among observed and latent variables.- Covers a wide class of important models- Models and statistical methods described provide tools for analyzing a wide spectrum of complicated data- Includes illustrative examples with real data sets from business, education, medicine, public health and sociology.- Demonstrates the use of a wide variety of statistical, computational, and mathematical techniques.

  12. Do gamblers eat more salt? Testing a latent trait model of covariance in consumption.

    Science.gov (United States)

    Goodwin, Belinda C; Browne, Matthew; Rockloff, Matthew; Donaldson, Phillip

    2015-09-01

    A diverse class of stimuli, including certain foods, substances, media, and economic behaviours, may be described as 'reward-oriented' in that they provide immediate reinforcement with little initial investment. Neurophysiological and personality concepts, including dopaminergic dysfunction, reward sensitivity and rash impulsivity, each predict the existence of a latent behavioural trait that leads to increased consumption of all stimuli in this class. Whilst bivariate relationships (co-morbidities) are often reported in the literature, to our knowledge, a multivariate investigation of this possible trait has not been done. We surveyed 1,194 participants (550 male) on their typical weekly consumption of 11 types of reward-oriented stimuli, including fast food, salt, caffeine, television, gambling products, and illicit drugs. Confirmatory factor analysis was used to compare models in a 3×3 structure, based on the definition of a single latent factor (none, fixed loadings, or estimated loadings), and assumed residual covariance structure (none, a-priori / literature based, or post-hoc / data-driven). The inclusion of a single latent behavioural 'consumption' factor significantly improved model fit in all cases. Also confirming theoretical predictions, estimated factor loadings on reward-oriented indicators were uniformly positive, regardless of assumptions regarding residual covariances. Additionally, the latent trait was found to be negatively correlated with the non-reward-oriented indicators of fruit and vegetable consumption. The findings support the notion of a single behavioural trait leading to increased consumption of reward-oriented stimuli across multiple modalities. We discuss implications regarding the concentration of negative lifestyle-related health behaviours.

  13. Confirmatory Factor Analysis of the Dutch Version of the Wechsler Memory Scale-Fourth Edition (WMS-IV-NL)

    NARCIS (Netherlands)

    Bouman, Z.; Hendriks, M.P.; Kerkmeer, M.C.; Kessels, R.P.C.; Aldenkamp, A.P.

    2015-01-01

    The latent factor structure of the Dutch version of the Wechsler Memory Scale-Fourth Edition (WMS-IV-NL) was examined with a series of confirmatory factor analyses. As part of the Dutch standardization, 1,188 healthy participants completed the WMS-IV-NL. Four models were tested for the Adult Battery

  14. Confirmatory linkage study of hypochondroplasia

    Energy Technology Data Exchange (ETDEWEB)

    Hecht, J.T.; Herrera, C.; Greenhaw, G.A. [Univ. of Texas Medical School, Houston, TX (United States)] [and others

    1994-09-01

    Hypochondroplasia is an autosomal dominant form of disproportionate short stature disorder that has clinical and radiographic findings similar to but milder than achondroplasia. Based on these findings it has been suggested that achondroplasia and hypochondroplasia are allelic conditions. We and others have mapped the achondroplasia locus to telomeric region of chromosome 4. Tested linkage to 4p markers in 6 hypochondroplasia families and a maximum LOD score of 1.7 at {theta} = 0 was found for IUDA. Here we report the results of a linkage study in 4 multigenerational families with hypochondroplasia using 7 short tandem repeat markers (D4S127, D4S412, D4S43, D4S115, IUDA, D4S227, D4S169) from the short arm of chromosome 4. These families have been well characterized and show the typical clinical and radiographic features of hypochondroplasia. One family was Afro-American, one Hispanic and two were Caucasian. We found a maximum multipoint LOD score of 2.9 at D4S115. The results of this study provide confirmatory evidence that achondroplasia and hypochondroplasia map to the same chromosomal location and suggests that they are indeed allelic conditions.

  15. Characterization of metabolic syndrome among diverse Hispanics/Latinos living in the United States: Latent class analysis from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL).

    Science.gov (United States)

    Arguelles, William; Llabre, Maria M; Sacco, Ralph L; Penedo, Frank J; Carnethon, Mercedes; Gallo, Linda C; Lee, David J; Catellier, Diane J; González, Hector M; Holub, Christina; Loehr, Laura R; Soliman, Elsayed Z; Schneiderman, Neil

    2015-04-01

    Empirical investigation of the adequacy of metabolic syndrome (MetS) diagnostic criteria, and whether meaningful subtypes of MetS exist, is needed among Hispanics/Latinos. In 15,825 US Hispanics/Latinos from HCHS/SOL, latent class analysis of MetS components (waist circumference, systolic and diastolic blood pressure, HDL cholesterol, triglycerides, glucose, and antihypertensive, lipid- and glucose-lowering medication use) was used to investigate (1) whether distinct subtypes of MetS could be identified, and how component levels differed between them, and (2) how identified subtypes related to covariates and cardiovascular disease (CVD) prevalence. Two latent clusters emerged in both men (n=6317) and women (n=9508): one characterized by relatively healthy mean levels (Non-MetS cluster, 77.1% of men and 67.1% of women) and the other by clinically elevated mean levels (MetS cluster, 22.9% of men and 32.9% of women) across most MetS components. These clusters showed expected associations with covariates and CVD prevalence. Notable results suggest that (1) HDL cholesterol may poorly differentiate between US Hispanics/Latinos with and without MetS (mean=45.4 vs. 44.6 mg/dL for men and 51.3 vs. 52.0 mg/dL for women in the MetS vs. Non-MetS clusters, respectively) and (2) the NCEP-ATP III 88 cm waist circumference cutoff for US females may not optimize diagnosis among Hispanic/Latino women (MetS cluster mean waist circumference=102.5 cm). Beyond classification into having MetS or not, additional subtypes of MetS do not clearly emerge in US Hispanics/Latinos. Current diagnostic cutoffs for some components may not optimize MetS identification among this population. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  16. Perceived consequences of female labor-force participation: a multilevel latent-class analysis across 22 countries (Consecuencias percibidas de la participación femenina en el mercado de trabajo: un análisis multinivel de clases latentes en 22 países

    Directory of Open Access Journals (Sweden)

    Angelika Glöckner-Rist

    2011-12-01

    Full Text Available This paper investigates whether there are different patterns of traditionality in different countries with regard to a perceived negative impact of labor-force participation of mothers on their children and family life. For this purpose, individual-level traditionality subgroups and segments of countries with different traditionality patterns of their nationals were identified simultaneously by means of multilevel latent-class (ML-LC analysis of the answers to three items of the Changing Family and Gender Roles module of the International Social Survey Program (ISSP. This module was fielded in 22 countries in the years 1994 and 2002. Six individual-level subgroups and five country segments can be discerned. The structure of individual-level subgroups is almost identical in both years. Four individual-level subgroups differ only quantitatively in their level of traditionality. Two further subgroups are characterized by a unique tendency to defend working mothers against criticism. From 1994 to 2002 the sizes of traditional subgroups decrease, and there is also some change in the composition of country segments. This paper investigates whether there are different patterns of traditionality in different countries with regard to a perceived negative impact of labor-force participation of mothers on their children and family life. For this purpose, individual-level traditionality subgroups and segments of countries with different traditionality patterns of their nationals were identified simultaneously by means of multilevel latent-class (ML-LC analysis of the answers to three items of the Changing Family and Gender Roles module of the International Social Survey Program (ISSP. This module was fielded in 22 countries in the years 1994 and 2002. Six individual-level subgroups and five country segments can be discerned. The structure of individual-level subgroups is almost identical in both years. Four individual-level subgroups differ only

  17. Learning Harmonium models with infinite latent features.

    Science.gov (United States)

    Chen, Ning; Zhu, Jun; Sun, Fuchun; Zhang, Bo

    2014-03-01

    Undirected latent variable models represent an important class of graphical models that have been successfully developed to deal with various tasks. One common challenge in learning such models is to determine the number of hidden units that are unknown a priori. Although Bayesian nonparametrics have provided promising results in bypassing the model selection problem in learning directed Bayesian Networks, very little effort has been made toward applying Bayesian nonparametrics to learn undirected latent variable models. In this paper, we present the infinite exponential family Harmonium (iEFH), a bipartite undirected latent variable model that automatically determines the number of latent units from an unbounded pool. We also present two important extensions of iEFH to 1) multiview iEFH for dealing with heterogeneous data, and 2) infinite maximum-margin Harmonium (iMMH) for incorporating supervising side information to learn predictive latent features. We develop variational inference algorithms to learn model parameters. Our methods are computationally competitive because of the avoidance of selecting the number of latent units. Our extensive experiments on real image datasets and text datasets appear to demonstrate the benefits of iEFH and iMMH inherited from Bayesian nonparametrics and max-margin learning. Such results were not available until now and contribute to expanding the scope of Bayesian nonparametrics to learn the structures of undirected latent variable models.

  18. Classification criteria of syndromes by latent variable models

    DEFF Research Database (Denmark)

    Petersen, Janne

    2010-01-01

    analyses. Part 1: HALS engages different phenotypic changes of peripheral lipoatrophy and central lipohypertrophy.  There are several different definitions of HALS and no consensus on the number of phenotypes. Many of the definitions consist of counting fulfilled criteria on markers and do not include......, although this is often desired. I have proposed a new method for predicting class membership that, in contrast to methods based on posterior probabilities of class membership, yields consistent estimates when regressed on explanatory variables in a subsequent analysis. There are four different basic models...... within latent variable models: factor analysis, latent class analysis, latent profile analysis and latent trait analysis. I have given a general overview of how to predict scores of latent variables so these can be used in subsequent regression models. Two different principles of predicting scores...

  19. The structure of assertiveness : a confirmatory approach

    NARCIS (Netherlands)

    ARRINDELL, WA; SANDERMAN, R; VANDERMOLEN, H; VANDERENDE, J; MERSCH, PP

    1988-01-01

    By using confirmatory factor analysis, distress and performance factors of assertion identified previously in a sample of predomi- nantly agoraphobic club members (N = 703) employing the Scale for Interpersonal Behavior (SlB) - the factors being (I) Display of negative feelings; (II) Expression of

  20. Extension Procedures for Confirmatory Factor Analysis

    Science.gov (United States)

    Nagy, Gabriel; Brunner, Martin; Lüdtke, Oliver; Greiff, Samuel

    2017-01-01

    We present factor extension procedures for confirmatory factor analysis that provide estimates of the relations of common and unique factors with external variables that do not undergo factor analysis. We present identification strategies that build upon restrictions of the pattern of correlations between unique factors and external variables. The…

  1. Classification criteria of syndromes by latent variable models

    DEFF Research Database (Denmark)

    Petersen, Janne

    2010-01-01

    The thesis has two parts; one clinical part: studying the dimensions of human immunodeficiency virus associated lipodystrophy syndrome (HALS) by latent class models, and a more statistical part: investigating how to predict scores of latent variables so these can be used in subsequent regression...

  2. Higher-Order Item Response Models for Hierarchical Latent Traits

    Science.gov (United States)

    Huang, Hung-Yu; Wang, Wen-Chung; Chen, Po-Hsi; Su, Chi-Ming

    2013-01-01

    Many latent traits in the human sciences have a hierarchical structure. This study aimed to develop a new class of higher order item response theory models for hierarchical latent traits that are flexible in accommodating both dichotomous and polytomous items, to estimate both item and person parameters jointly, to allow users to specify…

  3. Using existing questionnaires in latent class analysis

    DEFF Research Database (Denmark)

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

    2016-01-01

    classified into four health domains (psychology, pain, activity, and participation) using the World Health Organization's International Classification of Functioning, Disability, and Health framework. LCA was performed within each health domain using the strategies of summary-score and single-item analyses...

  4. Using existing questionnaires in latent class analysis

    DEFF Research Database (Denmark)

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

    2016-01-01

    ), 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...... characteristics. CONCLUSION: In these data, application of both the summary-score strategy and the single-item strategy in the LCA subgrouping resulted in clinically interpretable subgroups, but the single-item strategy generally revealed more distinguishing characteristics. These results 1) warrant further...

  5. Latent variable theory

    NARCIS (Netherlands)

    Borsboom, D.

    2008-01-01

    This paper formulates a metatheoretical framework for latent variable modeling. It does so by spelling out the difference between observed and latent variables. This difference is argued to be purely epistemic in nature: We treat a variable as observed when the inference from data structure to

  6. Statistics Related Self-Efficacy A Confirmatory Factor Analysis Demonstrating a Significant Link to Prior Mathematics Experiences for Graduate Level Students

    Directory of Open Access Journals (Sweden)

    Karen Larwin

    2014-02-01

    Full Text Available The present study examined students' statistics-related self-efficacy, as measured with the current statistics self-efficacy (CSSE inventory developed by Finney and Schraw (2003. Structural equation modeling was used to check the confirmatory factor analysis of the one-dimensional factor of CSSE. Once confirmed, this factor was used to test whether a significant link to prior mathematics experiences exists. Additionally a new post-structural equation modeling (SEM application was employed to compute error-free latent variable score for CSSE in an effort to examine the ancillary effects of gender, age, ethnicity, department, degree level, hours completed, expected course grade, number of college-level math classes, current GPA on students' CSSE scores. Results support the one-dimensional construct and as expected, the model demonstrated a significant link between CSSE scores and prior mathematics experiences to CSSE. Additionally the students' department, expected grade, and number of prior math classes were found to have a significant effect on student's CSSE scores.

  7. Latent myofascial trigger points.

    Science.gov (United States)

    Ge, Hong-You; Arendt-Nielsen, Lars

    2011-10-01

    A latent myofascial trigger point (MTP) is defined as a focus of hyperirritability in a muscle taut band that is clinically associated with local twitch response and tenderness and/or referred pain upon manual examination. Current evidence suggests that the temporal profile of the spontaneous electrical activity at an MTP is similar to focal muscle fiber contraction and/or muscle cramp potentials, which contribute significantly to the induction of local tenderness and pain and motor dysfunctions. This review highlights the potential mechanisms underlying the sensory-motor dysfunctions associated with latent MTPs and discusses the contribution of central sensitization associated with latent MTPs and the MTP network to the spatial propagation of pain and motor dysfunctions. Treating latent MTPs in patients with musculoskeletal pain may not only decrease pain sensitivity and improve motor functions, but also prevent latent MTPs from transforming into active MTPs, and hence, prevent the development of myofascial pain syndrome.

  8. Discrete time, discrete state latent Markov modelling for assessing and predicting household acquisitions of financial products

    NARCIS (Netherlands)

    Paas, Leonard J.; Vermunt, Jeroen K.; Bijmolt, Tammo H. A.

    2007-01-01

    The paper demonstrates application of the latent Markov model for assessing developments by individuals through stages of a process. This approach is applied by using a database on ownership of 12 financial products and various demographic variables. The latent Markov model derives latent classes,

  9. On Which Abilities Are Category Fluency and Letter Fluency Grounded? A Confirmatory Factor Analysis of 53 Alzheimer's Dementia Patients

    Science.gov (United States)

    Bizzozero, Ilaria; Scotti, Stefania; Clerici, Francesca; Pomati, Simone; Laiacona, Marcella; Capitani, Erminio

    2013-01-01

    Background/Aims In Alzheimer's dementia (AD), letter fluency is less impaired than category fluency. To check whether category fluency and letter fluency depend differently on semantics and attention, 53 mild AD patients were given animal and letter fluency tasks, two semantic tests (the Verbal Semantic Questionnaire and the BORB Association Match test), and two attentional tests (the Stroop Colour-Word Interference test and the Digit Cancellation test). Methods We conducted a LISREL confirmatory factor analysis to check the extent to which category fluency and letter fluency tasks were related to semantics and attention, viewed as latent variables. Results Both types of fluency tasks were related to the latent variable Semantics but not to the latent variable Attention. Conclusions Our findings warn against interpreting the disproportionate impairment of AD patients on category and letter fluency as a contrast between semantics and attention. PMID:23885263

  10. On Which Abilities Are Category Fluency and Letter Fluency Grounded A Confirmatory Factor Analysis of 53 Alzheimer's Dementia Patients

    Directory of Open Access Journals (Sweden)

    Ilaria Bizzozero

    2013-05-01

    Full Text Available Background/Aims: In Alzheimer's dementia (AD, letter fluency is less impaired than category fluency. To check whether category fluency and letter fluency depend differently on semantics and attention, 53 mild AD patients were given animal and letter fluency tasks, two semantic tests (the Verbal Semantic Questionnaire and the BORB Association Match test, and two attentional tests (the Stroop Colour-Word Interference test and the Digit Cancellation test. Methods: We conducted a LISREL confirmatory factor analysis to check the extent to which category fluency and letter fluency tasks were related to semantics and attention, viewed as latent variables. Results: Both types of fluency tasks were related to the latent variable Semantics but not to the latent variable Attention. Conclusions: Our findings warn against interpreting the disproportionate impairment of AD patients on category and letter fluency as a contrast between semantics and attention.

  11. Using existing questionnaires in latent class analysis: should we use summary scores or single items as input? A methodological study using a cohort of patients with low back pain

    Directory of Open Access Journals (Sweden)

    Nielsen AM

    2016-04-01

    Full Text Available Anne Molgaard Nielsen,1 Werner Vach,2 Peter Kent,1,3 Lise Hestbaek,1,4 Alice Kongsted1,4 1Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark; 2Center for Medical Biometry and Medical Informatics, Medical Center, University of Freiburg, Freiburg, Germany; 3School of Physiotherapy and Exercise Science, Curtin University, Perth, Australia; 4Nordic Institute of Chiropractic and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark 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 classified into four health domains (psychology, pain, activity, and participation using the World Health Organization’s International Classification of Functioning, Disability, and Health framework. LCA was performed within each health domain using the strategies of summary-score and single-item analyses. The resulting subgroups were descriptively compared using statistical measures and clinical interpretability. Results: For each health domain, the preferred model solution ranged from five to seven subgroups for the summary-score strategy and seven to eight subgroups for the single-item strategy. There was considerable overlap between the results of the two strategies, indicating that they were reflecting the same underlying data structure. However, in three of the four health domains, the single-item strategy resulted in a more nuanced description, in terms

  12. 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....

  13. Latent olefin metathesis catalysts

    OpenAIRE

    Monsaert, Stijn; Lozano Vila, Ana; Drozdzak, Renata; Van Der Voort, Pascal; Verpoort, Francis

    2009-01-01

    Olefin metathesis is a versatile synthetic tool for the redistribution of alkylidene fragments at carbon-carbon double bonds. This field, and more specifically the development of task-specific, latent catalysts, attracts emerging industrial and academic interest. This tutorial review aims to provide the reader with a concise overview of early breakthroughs and recent key developments in the endeavor to develop latent olefin metathesis catalysts, and to illustrate their use by prominent exampl...

  14. Testing Group Mean Differences of Latent Variables in Multilevel Data Using Multiple-Group Multilevel CFA and Multilevel MIMIC Modeling.

    Science.gov (United States)

    Kim, Eun Sook; Cao, Chunhua

    2015-01-01

    Considering that group comparisons are common in social science, we examined two latent group mean testing methods when groups of interest were either at the between or within level of multilevel data: multiple-group multilevel confirmatory factor analysis (MG ML CFA) and multilevel multiple-indicators multiple-causes modeling (ML MIMIC). The performance of these methods were investigated through three Monte Carlo studies. In Studies 1 and 2, either factor variances or residual variances were manipulated to be heterogeneous between groups. In Study 3, which focused on within-level multiple-group analysis, six different model specifications were considered depending on how to model the intra-class group correlation (i.e., correlation between random effect factors for groups within cluster). The results of simulations generally supported the adequacy of MG ML CFA and ML MIMIC for multiple-group analysis with multilevel data. The two methods did not show any notable difference in the latent group mean testing across three studies. Finally, a demonstration with real data and guidelines in selecting an appropriate approach to multilevel multiple-group analysis are provided.

  15. Classification criteria of syndromes by latent variable models

    DEFF Research Database (Denmark)

    Petersen, Janne

    2010-01-01

    displaying isolated peripheral lipoatrophy and another displaying both peripheral lipoatrophy and central lipohypertrophy. When patient characteristics were included the results indicated that smoking status is an essential variable in explaining why some patients do not get the central lipohypertrophy part...... of the syndrome. Thus, the results suggested that peripheral lipoatrophy and central lipohypertophy are interrelated phenotypes rather than two independent phenotypes. Part 2: Latent class regression relates explanatory variables to latent classes. In this model no measure of the latent class variable is obtained...... are shown to be superior depending on whether the latent variable is a dependent or an independent variable. Both these types of scores are extended to the situation of differential item functioning. Analytically I have showed that the scores result in consistent estimates when used properly in subsequent...

  16. Profils de multiples comportements à risque pour la santé des étudiants universitaires et leurs liens avec la santé mentale : utilisation de l’analyse des classes latentes

    Directory of Open Access Journals (Sweden)

    M. Y. Kwan

    2016-01-01

    Full Text Available Introduction : Les campus universitaires et collégiaux sont sans doute les derniers milieux au sein desquels il est possible d’aborder de façon globale la question de la santé d’une grande proportion de la population de jeunes adultes. Il est important que les promoteurs de la santé saisissent en quoi consistent les difficultés collectives auxquelles font face les étudiants et qu’ils comprennent mieux les modèles plus larges de comportements liés au mode de vie qui se manifestent au cours de cette période de la vie. L’objectif de notre étude a été de déterminer des catégories de comportements à risque pour la santé modifiables et d’étudier la relation entre ces catégories et divers paramètres relevant de la santé mentale au sein d’un vaste échantillon d’étudiants universitaires canadiens. Méthodologie : Des étudiants de premier cycle (n = 837, âge moyen = 21 ans de l’Université de Toronto ont répondu à l’enquête National College Health Assessment (NCHA (évaluation nationale de la santé dans les collèges qui comprend environ 300 éléments, dont des évaluations de l’état de santé, de la santé mentale et des comportements à risque pour la santé des étudiants. Nous avons réalisé une analyse des classes latentes pour relever des profils en fonction de huit comportements à risque pour la santé connus (consommation de marijuana, consommation d'autres drogues illégales, rapports sexuels à risque, tabagisme, excès occasionnel d’alcool, mauvaise alimentation, inactivité physique, manque de sommeil. Résultats : Nous avons obtenu un modèle à trois catégories axé sur les profils de comportement des étudiants : étudiants « typiques », « à risque élevé » et « relativement en bonne santé ». Nos résultats ont par ailleurs montré que les étudiants à risque élevé ont déclaré souffrir d’un niveau de stress considérablement plus élevé que celui des étudiants typiques

  17. Sustainable manufacturing practices in Malaysian automotive industry: confirmatory factor analysis

    National Research Council Canada - National Science Library

    Habidin, Nurul Fadly; Zubir, Anis Fadzlin Mohd; Fuzi, Nursyazwani Mohd; Latip, Nor Azrin Md; Azman, Mohamed Nor Azhari

    2015-01-01

    .... This reported study was conducted to examine confirmatory factor analysis for SMP such as manufacturing process, supply chain management, social responsibility, and environmental management based...

  18. Phosphor informatics based on confirmatory factor analysis.

    Science.gov (United States)

    Park, Woon Bae; Singh, Satendra Pal; Kim, Minseuk; Sohn, Kee-Sun

    2015-05-11

    The theoretical understanding of phosphor luminescence is far from complete. To accomplish a full understanding of phosphor luminescence, the data mining of existing experimental data should receive equal consideration along with theoretical approaches. We mined the crystallographic and luminescence data of 75 reported Eu(2+)-doped phosphors with a single Wyckoff site for Eu(2+) activator accommodation, and 32 descriptors were extracted. A confirmatory factor analysis (CFA) based on a structural equation model (SEM) was employed since it has been helpful in understanding complex problems in social sciences and in bioinformatics. This first attempt at applying CFA to the data mining of engineering materials provided a better understanding of the structural and luminescent-property relationships for LED phosphors than what we have learnt so far from the conventional theoretical approaches.

  19. Latent Semantic Analysis.

    Science.gov (United States)

    Dumais, Susan T.

    2004-01-01

    Presents a literature review that covers the following topics related to Latent Semantic Analysis (LSA): (1) LSA overview; (2) applications of LSA, including information retrieval (IR), information filtering, cross-language retrieval, and other IR-related LSA applications; (3) modeling human memory, including the relationship of LSA to other…

  20. Dynamic Latent Classification Model

    DEFF Research Database (Denmark)

    Zhong, Shengtong; Martínez, Ana M.; Nielsen, Thomas Dyhre

    as possible. Motivated by this problem setting, we propose a generative model for dynamic classification in continuous domains. At each time point the model can be seen as combining a naive Bayes model with a mixture of factor analyzers (FA). The latent variables of the FA are used to capture the dynamics...

  1. Brief report: A confirmatory approach to the validation of the peer group norm questionnaire.

    Science.gov (United States)

    Marshall-Denton, Rhea; Véronneau, Marie-Hélène; Dishion, Thomas J

    2016-07-01

    This study evaluates the internal validity of the "Perception of Peer Group Norms Questionnaire" (PPGNQ), a 17-item measure that assesses middle school students' perceptions of positive and negative norms among their grade mates. The sample consisted of 1073 Grade 6 students. The factorability of the two hypothesized factors was assessed with Exploratory Factor Analysis and a clear two-factor structure emerged. Using Confirmatory Factor Analysis this two-factor model evidenced good fit once items of similar wording and subject matter were permitted to correlate. Support was found for metric, strict, scalar, construct and latent means invariance between genders, suggesting that boys and girls perceived items similarly. The results indicate that the PPGNQ may be recommended as a research questionnaire that demonstrates high internal validity and measurement invariance, and can be used to study the influence of the perception of both negative and positive norms on adolescent behavior in school settings. Copyright © 2016. Published by Elsevier Ltd.

  2. Dimensionality of the premenstrual syndrome: confirmatory factor analysis of premenstrual dysphoric symptoms among college students

    Directory of Open Access Journals (Sweden)

    Y.-P. Wang

    2007-05-01

    Full Text Available Premenstrual syndrome and premenstrual dysphoric disorder (PMDD seem to form a severity continuum with no clear-cut boundary. However, since the American Psychiatric Association proposed the research criteria for PMDD in 1994, there has been no agreement about the symptomatic constellation that constitutes this syndrome. The objective of the present study was to establish the core latent structure of PMDD symptoms in a non-clinical sample. Data concerning PMDD symptoms were obtained from 632 regularly menstruating college students (mean age 24.4 years, SD 5.9, range 17 to 49. For the first random half (N = 316, we performed principal component analysis (PCA and for the remaining half (N = 316, we tested three theory-derived competing models of PMDD by confirmatory factor analysis. PCA allowed us to extract two correlated factors, i.e., dysphoric-somatic and behavioral-impairment factors. The two-dimensional latent model derived from PCA showed the best overall fit among three models tested by confirmatory factor analysis (c²53 = 64.39, P = 0.13; goodness-of-fit indices = 0.96; adjusted goodness-of-fit indices = 0.95; root mean square residual = 0.05; root mean square error of approximation = 0.03; 90%CI = 0.00 to 0.05; Akaike's information criterion = -41.61. The items "out of control" and "physical symptoms" loaded conspicuously on the first factor and "interpersonal impairment" loaded higher on the second factor. The construct validity for PMDD was accounted for by two highly correlated dimensions. These results support the argument for focusing on the core psychopathological dimension of PMDD in future studies.

  3. A Latent Class Analysis of Multimorbidity and the Relationship to Socio-Demographic Factors and Health-Related Quality of Life. A National Population-Based Study of 162,283 Danish Adults

    DEFF Research Database (Denmark)

    Larsen, Finn Breinholt; Pedersen, Marie Hauge; Friis, Karina

    2017-01-01

    and clinically meaningful disease patterns in a nationally representative sample of Danish adults (N = 162,283) aged 16+ years. The analysis was based on 15 chronic diseases. RESULTS: Seven classes with different disease patterns were identified: a class with no or only a single chronic condition (59...

  4. Development of a Body Image Concern Scale using both exploratory and confirmatory factor analyses in Chinese university students

    Directory of Open Access Journals (Sweden)

    He W

    2017-05-01

    Full Text Available Wenxin He, Qiming Zheng, Yutian Ji, Chanchan Shen, Qisha Zhu, Wei Wang Department of Clinical Psychology and Psychiatry, School of Public Health, Zhejiang University College of Medicine, Hangzhou, People’s Republic of China Background: The body dysmorphic disorder is prevalent in general population and in psychiatric, dermatological, and plastic-surgery patients, but there lacks a structure-validated, comprehensive self-report measure of body image concerns, which is established through both exploratory and confirmatory factor analyses. Methods: We have composed a 34-item matrix targeting the body image concerns and trialed it in 328 male and 365 female Chinese university students. Answers to the matrix dealt with treatments including exploratory factor analyses, reserve of qualified items, and confirmatory factor analyses of latent structures. Results: Six latent factors, namely the Social Avoidance, Appearance Dissatisfaction, Preoccupation with Reassurance, Perceived Distress/Discrimination, Defect Hiding, and Embarrassment in Public, were identified. The factors and their respective items have composed a 24-item questionnaire named as the Body Image Concern Scale. Each factor earned a satisfactory internal reliability, and the intercorrelations between these factors were in a median level. Women scored significantly higher than men did on the Appearance Dissatisfaction, Preoccupation with Reassurance, and Defect Hiding. Conclusion: The Body Image Concern Scale has displayed its structure validation and gender preponderance in Chinese university students. Keywords: body dysmorphic disorder, body image, factor analysis, questionnaire development

  5. Development of a Body Image Concern Scale using both exploratory and confirmatory factor analyses in Chinese university students

    Science.gov (United States)

    He, Wenxin; Zheng, Qiming; Ji, Yutian; Shen, Chanchan; Zhu, Qisha; Wang, Wei

    2017-01-01

    Background The body dysmorphic disorder is prevalent in general population and in psychiatric, dermatological, and plastic-surgery patients, but there lacks a structure-validated, comprehensive self-report measure of body image concerns, which is established through both exploratory and confirmatory factor analyses. Methods We have composed a 34-item matrix targeting the body image concerns and trialed it in 328 male and 365 female Chinese university students. Answers to the matrix dealt with treatments including exploratory factor analyses, reserve of qualified items, and confirmatory factor analyses of latent structures. Results Six latent factors, namely the Social Avoidance, Appearance Dissatisfaction, Preoccupation with Reassurance, Perceived Distress/Discrimination, Defect Hiding, and Embarrassment in Public, were identified. The factors and their respective items have composed a 24-item questionnaire named as the Body Image Concern Scale. Each factor earned a satisfactory internal reliability, and the intercorrelations between these factors were in a median level. Women scored significantly higher than men did on the Appearance Dissatisfaction, Preoccupation with Reassurance, and Defect Hiding. Conclusion The Body Image Concern Scale has displayed its structure validation and gender preponderance in Chinese university students. PMID:28603420

  6. Emotional Intelligence and Nurse Recruitment: Rasch and confirmatory factor analysis of the trait emotional intelligence questionnaire short form.

    Science.gov (United States)

    Snowden, Austyn; Watson, Roger; Stenhouse, Rosie; Hale, Claire

    2015-12-01

    To examine the construct validity of the Trait Emotional Intelligence Questionnaire Short form. Emotional intelligence involves the identification and regulation of our own emotions and the emotions of others. It is therefore a potentially useful construct in the investigation of recruitment and retention in nursing and many questionnaires have been constructed to measure it. Secondary analysis of existing dataset of responses to Trait Emotional Intelligence Questionnaire Short form using concurrent application of Rasch analysis and confirmatory factor analysis. First year undergraduate nursing and computing students completed Trait Emotional Intelligence Questionnaire-Short Form in September 2013. Responses were analysed by synthesising results of Rasch analysis and confirmatory factor analysis. Participants (N = 938) completed Trait Emotional Intelligence Questionnaire Short form. Rasch analysis showed the majority of the Trait Emotional Intelligence Questionnaire-Short Form items made a unique contribution to the latent trait of emotional intelligence. Five items did not fit the model and differential item functioning (gender) accounted for this misfit. Confirmatory factor analysis revealed a four-factor structure consisting of: self-confidence, empathy, uncertainty and social connection. All five misfitting items from the Rasch analysis belonged to the 'social connection' factor. The concurrent use of Rasch and factor analysis allowed for novel interpretation of Trait Emotional Intelligence Questionnaire Short form. Much of the response variation in Trait Emotional Intelligence Questionnaire Short form can be accounted for by the social connection factor. Implications for practice are discussed. © 2015 John Wiley & Sons Ltd.

  7. Learning multimodal latent attributes.

    Science.gov (United States)

    Fu, Yanwei; Hospedales, Timothy M; Xiang, Tao; Gong, Shaogang

    2014-02-01

    The rapid development of social media sharing has created a huge demand for automatic media classification and annotation techniques. Attribute learning has emerged as a promising paradigm for bridging the semantic gap and addressing data sparsity via transferring attribute knowledge in object recognition and relatively simple action classification. In this paper, we address the task of attribute learning for understanding multimedia data with sparse and incomplete labels. In particular, we focus on videos of social group activities, which are particularly challenging and topical examples of this task because of their multimodal content and complex and unstructured nature relative to the density of annotations. To solve this problem, we 1) introduce a concept of semilatent attribute space, expressing user-defined and latent attributes in a unified framework, and 2) propose a novel scalable probabilistic topic model for learning multimodal semilatent attributes, which dramatically reduces requirements for an exhaustive accurate attribute ontology and expensive annotation effort. We show that our framework is able to exploit latent attributes to outperform contemporary approaches for addressing a variety of realistic multimedia sparse data learning tasks including: multitask learning, learning with label noise, N-shot transfer learning, and importantly zero-shot learning.

  8. Medical University admission test: a confirmatory factor analysis of the results.

    Science.gov (United States)

    Luschin-Ebengreuth, Marion; Dimai, Hans P; Ithaler, Daniel; Neges, Heide M; Reibnegger, Gilbert

    2016-05-01

    The Graz Admission Test has been applied since the academic year 2006/2007. The validity of the Test was demonstrated by a significant improvement of study success and a significant reduction of dropout rate. The purpose of this study was a detailed analysis of the internal correlation structure of the various components of the Graz Admission Test. In particular, the question investigated was whether or not the various test parts constitute a suitable construct which might be designated as "Basic Knowledge in Natural Science." This study is an observational investigation, analyzing the results of the Graz Admission Test for the study of human medicine and dentistry. A total of 4741 applicants were included in the analysis. Principal component factor analysis (PCFA) as well as techniques from structural equation modeling, specifically confirmatory factor analysis (CFA), were employed to detect potential underlying latent variables governing the behavior of the measured variables. PCFA showed good clustering of the science test parts, including also text comprehension. A putative latent variable "Basic Knowledge in Natural Science," investigated by CFA, was indeed shown to govern the response behavior of the applicants in biology, chemistry, physics, and mathematics as well as text comprehension. The analysis of the correlation structure of the various test parts confirmed that the science test parts together with text comprehension constitute a satisfactory instrument for measuring a latent construct variable "Basic Knowledge in Natural Science." The present results suggest the fundamental importance of basic science knowledge for results obtained in the framework of the admission process for medical universities.

  9. Latent structure of social fears and social anxiety disorders.

    Science.gov (United States)

    Iza, M; Wall, M M; Heimberg, R G; Rodebaugh, T L; Schneier, F R; Liu, S-M; Blanco, C

    2014-01-01

    Despite its high prevalence and associated levels of impairment, the latent structure of social anxiety disorder (SAD) is not well understood, with published studies reporting inconsistent results. Furthermore, it is unknown whether the latent structure of social fears in individuals with and without SAD is the same. Exploratory factor analysis (EFA) and confirmatory factor analysis followed by multiple indicators multiple causes (MIMIC) analysis were conducted on 13 commonly feared social situations assessed in a nationally representative sample including individuals with SAD and those with social fears but who did not meet DSM-IV criteria for SAD. An EFA conducted in the full sample, including individuals with no social fears (88% of the sample), yielded only one factor. When the sample was restricted to those with at least one social fear, the EFA yielded three factors, in both the subsample with at least one social fear but no SAD and the subsample with SAD. The three factors represented feared situations related to public performance, close scrutiny and social interaction. The MIMIC analyses further indicated that the three-factor structure was able to explain differences in prevalence of social fears across a broad range of sociodemographic covariates. Among individuals with at least one social fear and those with DSM-IV SAD the latent structure of social fears appears to be best described by three factors, although this may partially depend on how the sample is specified. These results may help reconcile the findings of different numbers of factors identified in previous studies.

  10. 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.

  11. Factorial Invariance and Latent Mean Differences of Scores on the Achievement Goal Tendencies Questionnaire across Gender and Age in a Sample of Spanish Students

    Science.gov (United States)

    Ingles, Candido J.; Marzo, Juan C.; Castejon, Juan L.; Nunez, Jose Carlos; Valle, Antonio; Garcia-Fernandez, Jose M.; Delgado, Beatriz

    2011-01-01

    This study examined the factorial invariance and latent mean differences of scores on the Spanish version of the "Achievement Goal Tendencies Questionnaire" (AGTQ) across gender and age groups in 2022 Spanish students (51.1% boys) in grades 7 through 10. The equality of factor structures was compared using multi-group confirmatory factor…

  12. The relationship between CUB and loglinear models with latent variables

    NARCIS (Netherlands)

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

    2015-01-01

    The "combination of uniform and shifted binomial"(cub) model is a distribution for ordinal variables that has received considerable recent attention and specialized development. This article notes that the cub model is a special case of the well-known loglinear latent class model, an observation

  13. The relationship between cub and loglinear models with latent variables

    NARCIS (Netherlands)

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

    2015-01-01

    The "combination of uniform and shifted binomial"(cub) model is a distribution for ordinal variables that has received considerable recent attention and specialized development. This article notes that the cub model is a special case of the well-known loglinear latent class model, an observation

  14. Development of Fraction Comparison Strategies: A Latent Transition Analysis

    Science.gov (United States)

    Rinne, Luke F.; Ye, Ai; Jordan, Nancy C.

    2017-01-01

    The present study investigated the development of fraction comparison strategies through a longitudinal analysis of children's responses to a fraction comparison task in 4th through 6th grades (N = 394). Participants were asked to choose the larger value for 24 fraction pairs blocked by fraction type. Latent class analysis of performance over item…

  15. Classification criteria of syndromes by latent variable models

    DEFF Research Database (Denmark)

    Petersen, Janne

    2010-01-01

    standard exists for diagnosing HALS the normally applied diagnostic models cannot be used. Latent class models, which have never before been used to diagnose HALS, make it possible, under certain assumptions, to: statistically evaluate the number of phenotypes, test for mixing of HALS with other processes...

  16. 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.

  17. Where are children active and does it matter for physical activity?: A latent transition analysis

    Science.gov (United States)

    Colabianchi, Natalie; Griffin, JL; McIver, Kerry L; Dowda, Marsha; Pate, Russell R

    2016-01-01

    Background Numerous studies have focused on the role of environments in promoting physical activity, but few studies have examined the specific locations where children are active and whether being active in these locations is associated with physical activity levels over time. Methods Self-reported locations of where physical activity occurred and physical activity measured via accelerometry were obtained for a cohort of 520 children in 5th and 6th grades. Latent class analysis was used to generate classes of children defined by the variety of locations where they were active (i.e., home, school grounds, gyms, recreational centers, parks or playgrounds, neighborhood, and church). Latent transition analyses were used to characterize how these latent classes change over time and to determine whether the latent transitions were associated with changes in physical activity levels. Results Two latent classes were identified at baseline with the majority of children in the class labeled as ‘limited variety’. Most children maintained their latent status over time. Physical activity levels declined for all groups, but significantly less so for children who maintained their membership in the ‘greater variety’ latent status. Conclusions Supporting and encouraging physical activity in a variety of locations may improve physical activity levels in children. PMID:27633617

  18. A latent transition model of the effects of a teen dating violence prevention initiative.

    Science.gov (United States)

    Williams, Jason; Miller, Shari; Cutbush, Stacey; Gibbs, Deborah; Clinton-Sherrod, Monique; Jones, Sarah

    2015-02-01

    Patterns of physical and psychological teen dating violence (TDV) perpetration, victimization, and related behaviors were examined with data from the evaluation of the Start Strong: Building Healthy Teen Relationships initiative, a dating violence primary prevention program targeting middle school students. Latent class and latent transition models were used to estimate distinct patterns of TDV and related behaviors of bullying and sexual harassment in seventh grade students at baseline and to estimate transition probabilities from one pattern of behavior to another at the 1-year follow-up. Intervention effects were estimated by conditioning transitions on exposure to Start Strong. Latent class analyses suggested four classes best captured patterns of these interrelated behaviors. Classes were characterized by elevated perpetration and victimization on most behaviors (the multiproblem class), bullying perpetration/victimization and sexual harassment victimization (the bully-harassment victimization class), bullying perpetration/victimization and psychological TDV victimization (bully-psychological victimization), and experience of bully victimization (bully victimization). Latent transition models indicated greater stability of class membership in the comparison group. Intervention students were less likely to transition to the most problematic pattern and more likely to transition to the least problem class. Although Start Strong has not been found to significantly change TDV, alternative evaluation models may find important differences. Latent transition analysis models suggest positive intervention impact, especially for the transitions at the most and the least positive end of the spectrum. Copyright © 2015. Published by Elsevier Inc.

  19. Understanding Latent Heat of Vaporization.

    Science.gov (United States)

    Linz, Ed

    1995-01-01

    Presents a simple exercise for students to do in the kitchen at home to determine the latent heat of vaporization of water using typical household materials. Designed to stress understanding by sacrificing precision for simplicity. (JRH)

  20. A confirmatory factor analytic study of a self-leadership measure in South Africa

    Directory of Open Access Journals (Sweden)

    Bright Mahembe

    2013-01-01

    Full Text Available Orientation: Self-leadership is considered to be essential for effective individual functioning in occupational and academic contexts. The revised self-leadership questionnaire (RSLQ is widely utilised for measuring self-leadership, but its psychometric properties have not been established on a South African sample. By implication, important questions also exist about the theoretical structure of self-leadership in the South African context. Research purpose: The research aim of this study was to investigate the reliability and factorial validity of the revised self-leadership questionnaire on a South African sample. In doing so, the results of the research would also provide valuable insights into the latent factor structure of the self-leadership construct. Motivation for the study: On a practical level, the research sought internal validity evidence for the use of the RSLQ in the South African context. On a theoretical level, questions remain about the best conceptual representation of self-leadership as a construct. Research design, approach and method: The revised self-leadership questionnaire was administered to a non-probability sample of 375 South African young adults. The first and second-order factor structure underlying contemporary models of self-leadership using confirmatory factor analytic techniques was tested. Main findings: Results showed that the RSLQ measured self-leadership with suitable reliability and internal validity. All eight subscales had high internal consistency coefficients. Confirmatory factor analysis (CFA of the first and second-order models conclusively demonstrated good factorial validity. Practical/managerial implications: The study found that the RSLQ has good measurement properties for a South African context. Academics, practitioners and managers are urged to use the measure in its present form for applications such as leadership development and promoting self-management. Contribution/value-addition: The

  1. Latent failures on biodiesel plants

    OpenAIRE

    Selva S. Rivera; Jorge E. Nunez Mc Leod; Daniela R. Calvo

    2016-01-01

    The process to obtain biodiesel is simple, however it is a chemical process in which toxic and flammable substances are used or variables like temperature or pressure should be controlled to avoid any kind of incident. Literature report accidents where most human errors are related to the confidence of operators by this simplicity. Much of these accidents are influenced by a number of factors involved constituting latent failures. This paper presents a summary of latent failures identified on...

  2. The Infinite Latent Events Model

    CERN Document Server

    Wingate, David; Roy, Daniel; Tenenbaum, Joshua

    2012-01-01

    We present the Infinite Latent Events Model, a nonparametric hierarchical Bayesian distribution over infinite dimensional Dynamic Bayesian Networks with binary state representations and noisy-OR-like transitions. The distribution can be used to learn structure in discrete timeseries data by simultaneously inferring a set of latent events, which events fired at each timestep, and how those events are causally linked. We illustrate the model on a sound factorization task, a network topology identification task, and a video game task.

  3. La sifilis latente vesical

    Directory of Open Access Journals (Sweden)

    Pablo Gómez Martínez

    1948-01-01

    Full Text Available Con este título me propongo presentar los conocimientos y experiencias sacados de la investigación cistoscópica llevada a cabo sobre un total de 400 enfermos examinados en el Departamento de Endoscopia del Hospital de la Samaritana, durante el año de 1946. El autor, describió y publicó por primera vez en Colombia en el año de 1944, 2 casos de sífilis vesical que se presentaron sobre un total de 3.323 pacientes sifilíticos examinados durante los años de 1939, 1940 Y parte de 1941, o sea una incidencia del 1/2 por mil. El porcentaje encontrado sobre enfermos que se quejaban de su aparato urinario fue de 0,30 (1. Entre la numerosa literatura consultada, figuran dos artículos de autores brasileros que nos llamaron mucho la atención, por la frecuencia con que ellos encontraron lesiones vesicales atribuibles a la sífilis y que denominaron "Sífilis latente de la Vejiga". Como sus idea no estaban de acuerdo con los hechos observados por nosotros, ni con la experiencia adquirida en varios años de continuos exámenes cistoscópicos, nos dimos al trabajo de investigar de una manera minuciosa, serena e imparcial, la presencia o ausencia de las lesiones vesicales descritas, lo mismo que la morfología que pudieran tener en nuestro medio.

  4. Confirmatory factor analysis and invariance testing of the Young Carer of Parents Inventory (YCOPI).

    Science.gov (United States)

    Cox, Stephen D; Pakenham, Kenneth I

    2014-11-01

    Research into youth caregiving in families where a parent experiences a significant medical condition has been hampered by a lack of contextually sensitive measures of the nature and breadth of young caregiving experiences. This study examined the factor structure and measurement invariance of such a measure called the Young Carer of Parents Inventory (YCOPI; Pakenham et al., 2006) using confirmatory factor analysis across 3 groups of youth. The YCOPI has 2 parts: YCOPI-A with 5 factors assessing caregiving experiences that are applicable to all caregiving contexts; YCOPI-B with 4 factors that tap dimensions related to youth caregiving in the context of parent illness. Two samples (ages 9-20 years) were recruited: a community sample of 2,429 youth from which 2 groups were derived ("healthy" family [HF], n = 1760; parental illness [PI], n = 446), and a sample of 130 youth of a parent with multiple sclerosis). With some modification, the YCOPI-A demonstrated a replicable factor structure across 3 groups, and exhibited only partial measurement invariance across the HF and PI groups. The impact of assuming full measurement invariance on latent mean differences appeared small, supporting use of the measure in research and applied settings when estimated using latent factors and controlling for measurement invariance. PI youth reported significantly higher scores than did HF youth on all YCOPI-A subscales. The YCOPI-B requires some modifications, and further development work is recommended. The factor structure that emerged and the addition of new items constitutes the YCOPI-Revised. Findings support the use of the YCOPI-Revised in research and applied settings. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

  5. A confirmatory factor analytical study of a servant leadership measure in South Africa

    Directory of Open Access Journals (Sweden)

    Bright Mahembe

    2013-03-01

    Full Text Available Orientation: Servant leadership is a value-based leadership practice that plays a critical role in team effectiveness and organisational success.Research purpose: The goal of the study was to validate the Servant Leadership Questionnaire(SLQ, which Barbuto and Wheeler developed, on a South African sample.Motivation for the study: The literature is replete with evidence of the role of follower focused leadership practices in improving team effectiveness, employee engagement and organisational success. We need to complement these efforts with psychometrically sound measuring instruments.Research design, approach and method: The authors drew a convenience sample of 288 school teachers from schools in the Western Cape Province of South Africa. They used the SLQ that Barbuto and Wheeler developed to measure servant leadership.Main findings: The authors found high levels of reliability for the sub-scales of the latent variables. They found good fit with the data for the measurement model of the five latent servant leadership dimensions (altruistic calling, persuasive mapping, emotional healing, wisdom and organisational stewardship through confirmatory factor analyses (CFA. They obtained reasonable fit for the first- and second-order servant leadership CFA. The authors concluded that the SLQ shows reasonable fit.Practical/managerial implications: The SLQ showed evidence of reliability and construct validity. It can contribute to the scientific selection and development of education leaders in South African schools.Contribution/value add: Servant leadership incorporates a service ethic that fosters participatory management, teacher development and team building. The department of education should increase team effectiveness in schools by selecting and developing servant leadership.

  6. 40 CFR 86.1835-01 - Confirmatory certification testing.

    Science.gov (United States)

    2010-07-01

    ...) General Compliance Provisions for Control of Air Pollution From New and In-Use Light-Duty Vehicles, Light... 40 Protection of Environment 19 2010-07-01 2010-07-01 false Confirmatory certification testing. 86.1835-01 Section 86.1835-01 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR...

  7. Studying Children's Early Literacy Development: Confirmatory Multidimensional Scaling Growth Modeling

    Science.gov (United States)

    Ding, Cody

    2012-01-01

    There has been considerable debate over the ways in which children's early literacy skills develop over time. Using confirmatory multidimensional scaling (MDS) growth analysis, this paper directly tested the hypothesis of a cumulative trajectory versus a compensatory trajectory of development in early literacy skills among a group of 1233…

  8. Evidence Regarding the Internal Structure: Confirmatory Factor Analysis

    Science.gov (United States)

    Lewis, Todd F.

    2017-01-01

    American Educational Research Association (AERA) standards stipulate that researchers show evidence of the internal structure of instruments. Confirmatory factor analysis (CFA) is one structural equation modeling procedure designed to assess construct validity of assessments that has broad applicability for counselors interested in instrument…

  9. Random Effects Structure for Confirmatory Hypothesis Testing: Keep It Maximal

    Science.gov (United States)

    Barr, Dale J.; Levy, Roger; Scheepers, Christoph; Tily, Harry J.

    2013-01-01

    Linear mixed-effects models (LMEMs) have become increasingly prominent in psycholinguistics and related areas. However, many researchers do not seem to appreciate how random effects structures affect the generalizability of an analysis. Here, we argue that researchers using LMEMs for confirmatory hypothesis testing should minimally adhere to the…

  10. 77 FR 58587 - Mr. James Chaisson; Confirmatory Order (Effective Immediately)

    Science.gov (United States)

    2012-09-21

    ...) mediation session conducted on July 26, 2012, at the Wallace F. Bennett Federal Building, Salt Lake City..., arranged through Cornell University's Institute on Conflict Resolution. This Confirmatory Order is issued... included in a future newsletter issued by the Office of Federal and State Materials and Environmental...

  11. Confirmatory Factor Analysis on the Big 5 Personality Test Inventory

    Science.gov (United States)

    Kamarulzaman, Wirawani; Nordin, Mohamad Sahari

    2012-01-01

    This paper is intended to examine the validity of Big 5 Personality test inventory of 44 questions with 5-Likert Scale measurement. Confirmatory factory analysis (CFA) was conducted to determine the good fit indices of the 5 personality types. Those types are 1) extraversion, 2) agreeableness, 3) conscientiousness, 4) openness and 5) neuroticism.…

  12. HIV Seroprevalence and Confirmatory Rate In Enugu Urban ...

    African Journals Online (AJOL)

    This sentinel study determined the occurrence of HIV infection and confirmation rate of seropositive individuals among diverse Enugu Urban population. A seroprevalcne rate of 25.55 percent was obtained for September - December 1999 and a confirmatory rate of 10.57 percent (P<0.05) while seroprevalence rate for the ...

  13. The Study of Faculty Productivity through Confirmatory Factor Analysis: the case of Psychology in United States of America

    Directory of Open Access Journals (Sweden)

    MARÍA CARIDAD GARCÍA-CEPERO

    2010-03-01

    Full Text Available The article proposes the use of Confirmatory Factor Analysis techniques as a new approach to the measurement problem of faculty productivity. For this purpose, the author uses an analysis of scholarly productivity with data of 513 professors in the field of psychology in North America, between 1997 and 1998. Based on this analysis it is possible to identify three latent variables that describe the productivity of the sample: one factor that captures theinflation of all the observed variables, one factor that measures individual productivity and a factor that measures the joint productivity of faculty members. The findings suggest the need of novel approaches to policies for measurement and support of faculty productivity. These policies should be oriented not only to increase the productivity rates but also to decrease the probability of inflation.