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Sample records for mexico latent class

  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. 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.

  3. 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

    2018-01-01

    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 2018;37:128-136].

  4. Latent class models for classification

    NARCIS (Netherlands)

    Vermunt, J.K.; Magidson, J.

    2003-01-01

    An overview is provided of recent developments in the use of latent class (LC) and other types of finite mixture models for classification purposes. Several extensions of existing models are presented. Two basic types of LC models for classification are defined: supervised and unsupervised

  5. Intimate partner violence against low-income women in Mexico City and associations with work-related disruptions: a latent class analysis using cross-sectional data.

    Science.gov (United States)

    Gupta, Jhumka; Willie, Tiara C; Harris, Courtney; Campos, Paola Abril; Falb, Kathryn L; Garcia Moreno, Claudia; Diaz Olavarrieta, Claudia; Okechukwu, Cassandra A

    2018-03-07

    Disrupting women's employment is a strategy that abusive partners could use to prevent women from maintaining economic independence and stability. Yet, few studies have investigated disruptions in employment among victims of intimate partner violence (IPV) in low-income and middle-income countries. Moreover, even fewer have sought to identify which female victims of IPV are most vulnerable to such disruptions. Using baseline data from 947 women in Mexico City enrolled in a randomised controlled trial, multilevel latent class analysis (LCA) was used to classify women based on their reported IPV experiences. Furthermore, multilevel logistic regression analyses were performed on a subsample of women reporting current work (n=572) to investigate associations between LCA membership and IPV-related employment disruptions. Overall, 40.6% of women who were working at the time of the survey reported some form of work-related disruption due to IPV. LCA identified four distinct classes of IPV experiences: Low Physical and Sexual Violence (39.1%); High Sexual and Low Physical Violence class (9.6%); High Physical and Low Sexual Violence and Injuries (36.5%); High Physical and Sexual Violence and Injuries (14.8%). Compared with women in the Low Physical and Sexual Violence class, women in the High Physical and Sexual Violence and Injuries class and women in the High Physical and Low Sexual Violence and Injuries class were at greater risk of work disruption (adjusted relative risk (ARR) 2.44, 95% CI 1.80 to 3.29; ARR 2.05, 95% CI 1.56 to 2.70, respectively). No other statistically significant associations emerged. IPV, and specific patterns of IPV experiences, must be considered both in work settings and, more broadly, by economic development programmes. NCT01661504. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  6. Stability of latent class segments over time

    DEFF Research Database (Denmark)

    Mueller, Simone

    2011-01-01

    Dynamic stability, as the degree to which identified segments at a given time remain unchanged over time in terms of number, size and profile, is a desirable segment property which has received limited attention so far. This study addresses the question to what degree latent classes identified from...... 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...... in significant differences in the size of two out of seven classes. These differences can largely be accounted for by the changes on the aggregated level. The relative size of latent classes is correlated at 0.52, suggesting a fair robustness. An ex-post characterisation of latent classes by behavioural...

  7. Bayesian Latent Class Analysis Tutorial.

    Science.gov (United States)

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

    2018-01-01

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

  8. Latent class models in financial data analysis

    Directory of Open Access Journals (Sweden)

    Attilio Gardini

    2007-10-01

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

  9. 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...

  10. 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…

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

    Science.gov (United States)

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

    2016-01-01

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

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

    NARCIS (Netherlands)

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

    2005-01-01

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

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

    NARCIS (Netherlands)

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

    2006-01-01

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

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

    Science.gov (United States)

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

    2005-01-01

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

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

    NARCIS (Netherlands)

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

    2005-01-01

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

  16. A flexible latent class approach to estimating test-score reliability

    NARCIS (Netherlands)

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

    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

  17. Multilevel Latent Class Analysis: Parametric and Nonparametric Models

    Science.gov (United States)

    Finch, W. Holmes; French, Brian F.

    2014-01-01

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

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

    NARCIS (Netherlands)

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

    2006-01-01

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

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

    Science.gov (United States)

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

    2018-04-01

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

  20. Heterogeneity of postpartum depression: a latent class analysis

    Science.gov (United States)

    2016-01-01

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

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

    Science.gov (United States)

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

    2018-01-01

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

  2. Building latent class trees, with an application to a study of social capital

    NARCIS (Netherlands)

    van den Bergh, M.; Schmittmann, V.D.; Vermunt, J.K.

    2017-01-01

    Researchers use latent class (LC) analysis to derive meaningful clusters from sets of categorical variables. However, especially when the number of classes required to obtain a good fit is large, interpretation of the latent classes may not be straightforward. To overcome this problem, we propose an

  3. Identifying subgroups of patients using latent class analysis

    DEFF Research Database (Denmark)

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

    2017-01-01

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

  4. Latent Class Models in action: bridging social capital & Internet usage.

    Science.gov (United States)

    Neves, Barbara Barbosa; Fonseca, Jaime R S

    2015-03-01

    This paper explores how Latent Class Models (LCM) can be applied in social research, when the basic assumptions of regression models cannot be validated. We examine the usefulness of this method with data collected from a study on the relationship between bridging social capital and the Internet. Social capital is defined here as the resources that are potentially available in one's social ties. Bridging is a dimension of social capital, usually related to weak ties (acquaintances), and a source of instrumental resources such as information. The study surveyed a stratified random sample of 417 inhabitants of Lisbon, Portugal. We used LCM to create the variable bridging social capital, but also to estimate the relationship between bridging social capital and Internet usage when we encountered convergence problems with the logistic regression analysis. We conclude by showing a positive relationship between bridging and Internet usage, and by discussing the potential of LCM for social science research. Copyright © 2014 Elsevier Inc. All rights reserved.

  5. 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.

  6. 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.

  7. Latent class factor and cluster models, bi-plots and tri-plots and related graphical displays

    NARCIS (Netherlands)

    Magidson, J.; Vermunt, J.K.

    2001-01-01

    We propose an alternative method of conducting exploratory latent class analysis that utilizes latent class factor models, and compare it to the more traditional approach based on latent class cluster models. We show that when formulated in terms of R mutually independent, dichotomous latent

  8. Social Class in English Language Education in Oaxaca, Mexico

    Science.gov (United States)

    López-Gopar, Mario E.; Sughrua, William

    2014-01-01

    This article explores social class in English-language education in Oaxaca, Mexico. To this end, first, we discuss social class in Mexico as related to coloniality; second, for illustration, the paper presents the authors' own social-class analysis as language educators in Oaxaca; third, we discuss how social class impacts English education…

  9. 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…

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

    Directory of Open Access Journals (Sweden)

    Drew A. Linzer

    2011-08-01

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

  11. 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.

  12. 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.

  13. 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.

  14. 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

  15. 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…

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

    DEFF Research Database (Denmark)

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

    2016-01-01

    , 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...

  17. 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.

  18. Managerial performance and cost efficiency of Japanese local public hospitals: a latent class stochastic frontier model.

    Science.gov (United States)

    Besstremyannaya, Galina

    2011-09-01

    The paper explores the link between managerial performance and cost efficiency of 617 Japanese general local public hospitals in 1999-2007. Treating managerial performance as unobservable heterogeneity, the paper employs a panel data stochastic cost frontier model with latent classes. Financial parameters associated with better managerial performance are found to be positively significant in explaining the probability of belonging to the more efficient latent class. The analysis of latent class membership was consistent with the conjecture that unobservable technological heterogeneity reflected in the existence of the latent classes is related to managerial performance. The findings may support the cause for raising efficiency of Japanese local public hospitals by enhancing the quality of management. Copyright © 2011 John Wiley & Sons, Ltd.

  19. 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

  20. 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

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

    Science.gov (United States)

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

    2016-10-01

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

  2. Short-term memory development: differences in serial position curves between age groups and latent classes.

    Science.gov (United States)

    Koppenol-Gonzalez, Gabriela V; Bouwmeester, Samantha; Vermunt, Jeroen K

    2014-10-01

    In studies on the development of cognitive processes, children are often grouped based on their ages before analyzing the data. After the analysis, the differences between age groups are interpreted as developmental differences. We argue that this approach is problematic because the variance in cognitive performance within an age group is considered to be measurement error. However, if a part of this variance is systematic, it can provide very useful information about the cognitive processes used by some children of a certain age but not others. In the current study, we presented 210 children aged 5 to 12 years with serial order short-term memory tasks. First we analyze our data according to the approach using age groups, and then we apply latent class analysis to form latent classes of children based on their performance instead of their ages. We display the results of the age groups and the latent classes in terms of serial position curves, and we discuss the differences in results. Our findings show that there are considerable differences in performance between the age groups and the latent classes. We interpret our findings as indicating that the latent class analysis yielded a much more meaningful way of grouping children in terms of cognitive processes than the a priori grouping of children based on their ages. Copyright © 2014 Elsevier Inc. All rights reserved.

  3. 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…

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

    Science.gov (United States)

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

    2009-01-10

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

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

    Science.gov (United States)

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

    2017-08-25

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

  6. 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.

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

    Science.gov (United States)

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

    2004-02-01

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

  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. Micro-macro multilevel latent class models with multiple discrete individual-level variables

    NARCIS (Netherlands)

    Bennink, M.; Croon, M.A.; Kroon, B.; Vermunt, J.K.

    2016-01-01

    An existing micro-macro method for a single individual-level variable is extended to the multivariate situation by presenting two multilevel latent class models in which multiple discrete individual-level variables are used to explain a group-level outcome. As in the univariate case, the

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

    DEFF Research Database (Denmark)

    Kaplan, Sigal; Prato, Carlo Giacomo

    2013-01-01

    to prioritize safety issues and to devise efficient preventive measures. Method: The current study focused on cyclist–motorist crashes that occurred in Denmark during the period between 2007 and 2011. To uncover crash patterns, the current analysis applied latent class clustering, an unsupervised probabilistic...

  11. 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

  12. 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

  13. PR.Latent-class methods to evaluate diagnostics tests for echinococcus infections in dogs.

    NARCIS (Netherlands)

    Hartnack, S.; Budke, C.M.; Craig, P.S.; Jiamin, Q.; Boufana, B.; Campos Ponce, M.; Torgerson, P.R.

    2013-01-01

    Background: The diagnosis of canine echinococcosis can be a challenge in surveillance studies because there is no perfect gold standard that can be used routinely. However, unknown test specificities and sensitivities can be overcome using latent-class analysis with appropriate data. Methodology: We

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

    NARCIS (Netherlands)

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

    2017-01-01

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

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

    NARCIS (Netherlands)

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

    2017-01-01

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

  16. 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

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

    DEFF Research Database (Denmark)

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

    2017-01-01

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

  18. 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.…

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

    NARCIS (Netherlands)

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

    2014-01-01

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

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

    NARCIS (Netherlands)

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

    2017-01-01

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

  1. Evidence for Latent Classes of IQ in Young Children with Autism Spectrum Disorder

    Science.gov (United States)

    Munson, Jeffrey; Dawson, Geraldine; Sterling, Lindsey; Beauchaine, Theodore; Zhou, Andrew; Koehler, Elizabeth; Lord, Catherine; Rogers, Sally; Sigman, Marian; Estes, Annette; Abbott, Robert

    2008-01-01

    Autism is currently viewed as a spectrum condition that includes strikingly different severity levels; IQ is consistently described as one of the primary aspects of the heterogeneity in autism. To investigate the possibility of more than one distinct subtype of autism based on IQ, both latent class analysis and taxometrics methods were used to…

  2. 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

  3. 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

  4. 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.

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

    Science.gov (United States)

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

    2012-09-01

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

  6. 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.

  7. 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.

  8. Clustering of modifiable biobehavioral risk factors for chronic disease in US adults: a latent class analysis.

    Science.gov (United States)

    Leventhal, Adam M; Huh, Jimi; Dunton, Genevieve F

    2014-11-01

    Examining the co-occurrence patterns of modifiable biobehavioral risk factors for deadly chronic diseases (e.g. cancer, cardiovascular disease, diabetes) can elucidate the etiology of risk factors and guide disease-prevention programming. The aims of this study were to (1) identify latent classes based on the clustering of five key biobehavioral risk factors among US adults who reported at least one risk factor and (2) explore the demographic correlates of the identified latent classes. Participants were respondents of the National Epidemiologic Survey of Alcohol and Related Conditions (2004-2005) with at least one of the following disease risk factors in the past year (N = 22,789), which were also the latent class indicators: (1) alcohol abuse/dependence, (2) drug abuse/dependence, (3) nicotine dependence, (4) obesity, and (5) physical inactivity. Housing sample units were selected to match the US National Census in location and demographic characteristics, with young adults oversampled. Participants were administered surveys by trained interviewers. Five latent classes were yielded: 'obese, active non-substance abusers' (23%); 'nicotine-dependent, active, and non-obese' (19%); 'active, non-obese alcohol abusers' (6%); 'inactive, non-substance abusers' (50%); and 'active, polysubstance abusers' (3.7%). Four classes were characterized by a 100% likelihood of having one risk factor coupled with a low or moderate likelihood of having the other four risk factors. The five classes exhibited unique demographic profiles. Risk factors may cluster together in a non-monotonic fashion, with the majority of the at-risk population of US adults expected to have a high likelihood of endorsing only one of these five risk factors. © Royal Society for Public Health 2013.

  9. 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.

  10. 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.

  11. When do latent class models overstate accuracy for diagnostic and other classifiers in the absence of a gold standard?

    Science.gov (United States)

    Spencer, Bruce D

    2012-06-01

    Latent class models are increasingly used to assess the accuracy of medical diagnostic tests and other classifications when no gold standard is available and the true state is unknown. When the latent class is treated as the true class, the latent class models provide measures of components of accuracy including specificity and sensitivity and their complements, type I and type II error rates. The error rates according to the latent class model differ from the true error rates, however, and empirical comparisons with a gold standard suggest the true error rates often are larger. We investigate conditions under which the true type I and type II error rates are larger than those provided by the latent class models. Results from Uebersax (1988, Psychological Bulletin 104, 405-416) are extended to accommodate random effects and covariates affecting the responses. The results are important for interpreting the results of latent class analyses. An error decomposition is presented that incorporates an error component from invalidity of the latent class model. © 2011, The International Biometric Society.

  12. 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.

  13. 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.

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

    DEFF Research Database (Denmark)

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

    on individuals' environmental attitudes and values. Consumer involvement and environmental attitudes contribute significantly toward explaining sustainable choices, suggesting that greater consumer involvement may be targeted by policy makers and firms to more effectively nudge consumers toward green consumerism......To better understand motivations of consumers making choices among sustainability-labeled food products, this paper analyzes drivers of stated choices for a dietary staple labeled with carbon and water foodprints. Latent class modeling of survey responses reveals distinct consumer segments based...

  15. Evidence for Latent Classes of IQ In Young Children with Autism Spectrum Disorder

    OpenAIRE

    Munson, Jeffrey; Dawson, Geraldine; Sterling, Lindsey; Beauchaine, Theodore; Zhou, Andrew; Koehler, Elizabeth; Lord, Catherine; Rogers, Sally; Sigman, Marian; Estes, Annette; Abbott, Robert

    2008-01-01

    Autism is currently viewed as a spectrum condition including strikingly different severity levels. IQ is consistently described as one of the primary aspects of the heterogeneity in autism. To investigate the possibility of more than one distinct subtype of autism based on IQ, both latent class analysis and taxometric methods were used to classify Mullen IQ scores in a sample of children with autism spectrum disorder (N=456). Evidence for multiple IQ-based subgroups was found using both metho...

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

    OpenAIRE

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

    2017-01-01

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

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

    Science.gov (United States)

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

    2011-05-01

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

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

    Science.gov (United States)

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

    2006-10-01

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

  19. Latent Classes of Symptoms related to Clinically Depressed Mood in Adolescents.

    Science.gov (United States)

    Blom, Eva Henje; Forsman, Mats; Yang, Tony T; Serlachius, Eva; Larsson, Jan-Olov

    2014-01-01

    The diagnosis of major depressive disorder (MDD), according to the Diagnostic and Statistical Manual of Mental Disorders , is based only on adult symptomatology of depression and not adapted for age and gender. This may contribute to the low diagnostic specificity and validity of adolescent MDD. In this study, we investigated whether latent classes based on symptoms associated with depressed mood could be identified in a sample of adolescents seeking psychiatric care, regardless of traditionally defined diagnostic categories. Self-reports of the Strengths and Difficulties Questionnaire and the Development and Well-Being Assessment were collected consecutively from all new patients between the ages of 13 and 17 years at two psychiatric outpatient clinics in Stockholm, Sweden. Those who reported depressed mood at intake yielded a sample of 21 boys and 156 girls. Latent class analyses were performed for all screening items and for the depression-specific items of the Development and Well-Being Assessment. The symptoms that were reported in association with depressed mood differentiated the adolescents into two classes. One class had moderate emotional severity scores on the Strengths and Difficulties Questionnaire and mainly symptoms that were congruent with the Diagnostic and Statistical Manual of Mental Disorders criteria for MDD. The other class had higher emotional severity scores and similar symptoms to those reported in the first class. However, in addition, this group demonstrated more diverse symptomatology, including vegetative symptoms, suicidal ideation, anxiety, conduct problems, body dysmorphic symptoms, and deliberate vomiting. The classes predicted functional impairment in that the members of the second class showed more functional impairment. The relatively small sample size limited the generalizability of the results of this study, and the amount of items included in the analysis was restricted by the rules of latent class analysis. No conclusions

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

    Science.gov (United States)

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

    2005-12-01

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

  1. 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

  2. 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…

  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. Mixture Item Response Theory-MIMIC Model: Simultaneous Estimation of Differential Item Functioning for Manifest Groups and Latent Classes

    Science.gov (United States)

    Bilir, Mustafa Kuzey

    2009-01-01

    This study uses a new psychometric model (mixture item response theory-MIMIC model) that simultaneously estimates differential item functioning (DIF) across manifest groups and latent classes. Current DIF detection methods investigate DIF from only one side, either across manifest groups (e.g., gender, ethnicity, etc.), or across latent classes…

  5. Variation in Latent Classes of Adult Attention-Deficit Hyperactivity Disorder by Sex and Environmental Adversity.

    Science.gov (United States)

    Ebejer, Jane L; Medland, Sarah E; van der Werf, Julius; Lynskey, Michael; Martin, Nicholas G; Duffy, David L

    2016-11-01

    The findings of genetic, imaging and neuropsychological studies of attention-deficit hyperactivity disorder (ADHD) are mixed. To understand why this might be the case we use both dimensional and categorical symptom measurement to provide alternate and detailed perspectives of symptom expression. Interviewers collected ADHD, conduct problems (CP) and sociodemographic data from 3793 twins and their siblings aged 22 to 49 (M = 32.6). We estimate linear weighting of symptoms across ADHD and CP items. Latent class analyses and regression describe associations between measured variables, environmental risk factors and subsequent disadvantage. Additionally, the clinical relevance of each class was estimated. Five classes were found for women and men; few symptoms, hyperactive-impulsive, CP, inattentive, combined symptoms with CP. Women within the inattentive class reported more symptoms and reduced emotional health when compared to men and to women within other latent classes. Women and men with combined ADHD symptoms reported comorbid conduct problems but those with either inattention or hyperactivity-impulsivity only did not. The dual perspective of dimensional and categorical measurement of ADHD provides important detail about symptom variation across sex and with environmental covariates. © The Author(s) 2013.

  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. How do older adult drivers self-regulate? Characteristics of self-regulation classes defined by latent class analysis.

    Science.gov (United States)

    Bergen, Gwen; West, Bethany A; Luo, Feijun; Bird, Donna C; Freund, Katherine; Fortinsky, Richard H; Staplin, Loren

    2017-06-01

    Motor-vehicle crashes were the second leading cause of injury death for adults aged 65-84years in 2014. Some older drivers choose to self-regulate their driving to maintain mobility while reducing driving risk, yet the process remains poorly understood. Data from 729 older adults (aged ≥60years) who joined an older adult ride service program between April 1, 2010 and November 8, 2013 were analyzed to define and describe classes of driving self-regulation. Latent class analysis was employed to characterize older adult driving self-regulation classes using driving frequency and avoidance of seven driving situations. Logistic regression was used to explore associations between characteristics affecting mobility and self-regulation class. Three classes were identified (low, medium, and high self-regulation). High self-regulating participants reported the highest proportion of always avoiding seven risky driving situations and the lowest driving frequency followed by medium and low self-regulators. Those who were female, aged 80years or older, visually impaired, assistive device users, and those with special health needs were more likely to be high self-regulating compared with low self-regulating. Avoidance of certain driving situations and weekly driving frequency are valid indicators for describing driving self-regulation classes in older adults. Understanding the unique characteristics and mobility limitations of each class can guide optimal transportation strategies for older adults. Published by Elsevier Ltd.

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

    Science.gov (United States)

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

    2018-05-30

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

  9. STARD-BLCM: Standards for the Reporting of Diagnostic accuracy studies that use Bayesian Latent Class Models

    DEFF Research Database (Denmark)

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

    2017-01-01

    The Standards for the Reporting of Diagnostic Accuracy (STARD) statement, which was recently updated to the STARD2015 statement, was developed to encourage complete and transparent reporting of test accuracy studies. Although STARD principles apply broadly, the checklist is limited to studies......-BLCM (Standards for Reporting of Diagnostic accuracy studies that use Bayesian Latent Class Models), will facilitate improved quality of reporting on the design, conduct and results of diagnostic accuracy studies that use Bayesian latent class models....

  10. 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.

  11. 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.

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

    Science.gov (United States)

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

    2018-05-01

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

  13. 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

  14. 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.

  15. 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.

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

    Science.gov (United States)

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

    2011-01-01

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

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

    Science.gov (United States)

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

    2014-10-01

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

  18. Latent Classes of Polydrug Users as a Predictor of Crash Involvement and Alcohol Consumption.

    Science.gov (United States)

    Scherer, Michael; Romano, Eduardo; Voas, Robert; Taylor, Eileen

    2018-05-01

    Polydrug users have been shown to be at higher risk for alcohol consumption and crash involvement. However, research has shown that polydrug groups differ in some important ways. It is currently unknown how polydrug-using groups differ in terms of crash involvement and alcohol consumption. The current study used latent class analysis to examine subgroups of polydrug users (n = 384) among a sample of drivers in Virginia Beach, Virginia (N = 10,512). A series of logistic regression analyses were conducted to determine the relationship between polydrug use categories and crash involvement and alcohol consumption. Four distinct subclasses of users were identified among polydrug-using drivers: Class 1 is the "marijuana-amphetamines class" and accounts for 21.6% of polydrug users. Class 2 is the "benzo-antidepressant class" and accounts for 39.0% of polydrug users. Class 3 is the "opioid-benzo class" and accounts for 32.7% of polydrug users. Finally, Class 4 is the "marijuana-cocaine class" and accounts for 6.7% of the study sample. Drivers in the opioid-benzo class were significantly more likely than those in any other class as well as non-drug users and single-drug users to be involved in a crash and were more likely than those in most other conditions to consume alcohol. No significant difference was found between marijuana-amphetamine users or benzo-antidepressant users and non-drug users on crash risk. Some polydrug users are indeed at greater risk for crash involvement and alcohol consumption; however, not all polydrug users are significantly worse than single-drug users and/or non-drug users, and the practice of lumping polydrug users together when predicting crash risk runs the risk of inaccurately attributing crash involvement to certain drivers.

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

    Science.gov (United States)

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

    2016-07-28

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

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

    Science.gov (United States)

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

    2012-01-01

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

  2. What Do Test Scores Really Mean? A Latent Class Analysis of Danish Test Score Performance

    DEFF Research Database (Denmark)

    Munk, Martin D.; McIntosh, James

    2014-01-01

    Latent class Poisson count models are used to analyze a sample of Danish test score results from a cohort of individuals born in 1954-55, tested in 1968, and followed until 2011. The procedure takes account of unobservable effects as well as excessive zeros in the data. We show that the test scores...... of intelligence explain a significant proportion of the variation in test scores. This adds to the complexity of interpreting test scores and suggests that school culture and possible incentive problems make it more di¢ cult to understand what the tests measure....

  3. 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.

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

    Science.gov (United States)

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

    2016-05-24

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

  5. 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.

  6. Identification of a new class of small molecules that efficiently reactivate latent Epstein-Barr virus

    Science.gov (United States)

    Tikhmyanova, Nadezhda; Schultz, David C.; Lee, Theresa; Salvino, Joseph M.; Lieberman, Paul M.

    2014-01-01

    Epstein-Barr Virus (EBV) persists as a latent infection in many lymphoid and epithelial malignancies, including Burkitt's lymphomas, nasopharyngeal carcinomas, and gastric carcinomas. Current chemotherapeutic treatments of EBV-positive cancers include broad- spectrum cytotoxic drugs that ignore the EBV-positive status of tumors. An alternative strategy, referred to as oncolytic therapy, utilizes drugs that stimulate reactivation of latent EBV to enhance the selective killing of EBV positive tumors, especially in combination with existing inhibitors of herpesvirus lytic replication, like Ganciclovir (GCV). At present, no small molecule, including histone deacetylase (HDAC) inhibitors, have proven safe or effective in clinical trials for treatment of EBV positive cancers. Aiming to identify new chemical entities that induce EBV lytic cycle, we have developed a robust high throughput cell-based assay to screen 66,840 small molecule compounds. Five structurally related tetrahydrocarboline derivatives were identified, two of which had EC50 measurements in the range of 150-170 nM. We show that these compounds reactivate EBV lytic markers ZTA and EA-D in all EBV-positive cell lines we have tested independent of the type of latency. The compounds reactivate a higher percentage of latently infected cells than HDAC inhibitors or phorbol esters in many cell types. The most active compounds showed low toxicity to EBV-negative cells, but were highly effective at selective cell killing of EBV-positive cells when combined with GCV. We conclude that we have identified a class of small molecule compounds that are highly effective at reactivating latent EBV infection in a variety of cell types, and show promise for lytic therapy in combination with GCV. PMID:24028149

  7. 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

  8. Latent class analysis of accident risks in usage-based insurance: Evidence from Beijing.

    Science.gov (United States)

    Jin, Wen; Deng, Yinglu; Jiang, Hai; Xie, Qianyan; Shen, Wei; Han, Weijian

    2018-06-01

    Car insurance is quickly becoming a big data industry, with usage-based insurance (UBI) poised to potentially change the business of insurance. Telematics data, which are transmitted from wireless devices in car, are widely used in UBI to obtain individual-level travel and driving characteristics. While most existing studies have introduced telematics data into car insurance pricing, the telematics-related characteristics are directly obtained from the raw data. In this study, we propose to quantify drivers' familiarity with their driving routes and develop models to quantify drivers' accident risks using the telematics data. In addition, we build a latent class model to study the heterogeneity in travel and driving styles based on the telematics data, which has not been investigated in literature. Our main results include: (1) the improvement to the model fit is statistically significant by adding telematics-related characteristics; (2) drivers' familiarity with their driving trips is critical to identify high risk drivers, and the relationship between drivers' familiarity and accident risks is non-linear; (3) the drivers can be classified into two classes, where the first class is the low risk class with 0.54% of its drivers reporting accidents, and the second class is the high risk class with 20.66% of its drivers reporting accidents; and (4) for the low risk class, drivers with high probability of reporting accidents can be identified by travel-behavior-related characteristics, while for the high risk class, they can be identified by driving-behavior-related characteristics. The driver's familiarity will affect the probability of reporting accidents for both classes. Copyright © 2018 Elsevier Ltd. All rights reserved.

  9. 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

  10. A latent class distance association model for cross-classified data with a categorical response variable.

    Science.gov (United States)

    Vera, José Fernando; de Rooij, Mark; Heiser, Willem J

    2014-11-01

    In this paper we propose a latent class distance association model for clustering in the predictor space of large contingency tables with a categorical response variable. The rows of such a table are characterized as profiles of a set of explanatory variables, while the columns represent a single outcome variable. In many cases such tables are sparse, with many zero entries, which makes traditional models problematic. By clustering the row profiles into a few specific classes and representing these together with the categories of the response variable in a low-dimensional Euclidean space using a distance association model, a parsimonious prediction model can be obtained. A generalized EM algorithm is proposed to estimate the model parameters and the adjusted Bayesian information criterion statistic is employed to test the number of mixture components and the dimensionality of the representation. An empirical example highlighting the advantages of the new approach and comparing it with traditional approaches is presented. © 2014 The British Psychological Society.

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. Problems in detecting misfit of latent class models in diagnostic research without a gold standard were shown

    NARCIS (Netherlands)

    van Smeden, M.; Oberski, D.L.; Reitsma, J.B.; Vermunt, J.K.; Moons, K.G.M.; de Groot, J.A.H.

    2016-01-01

    Objectives The objective of this study was to evaluate the performance of goodness-of-fit testing to detect relevant violations of the assumptions underlying the criticized “standard” two-class latent class model. Often used to obtain sensitivity and specificity estimates for diagnostic tests in the

  16. A Latent Class Multidimensional Scaling Model for Two-Way One-Mode Continuous Rating Dissimilarity Data

    Science.gov (United States)

    Vera, J. Fernando; Macias, Rodrigo; Heiser, Willem J.

    2009-01-01

    In this paper, we propose a cluster-MDS model for two-way one-mode continuous rating dissimilarity data. The model aims at partitioning the objects into classes and simultaneously representing the cluster centers in a low-dimensional space. Under the normal distribution assumption, a latent class model is developed in terms of the set of…

  17. Latent Class Symptom Profiles of Selective Mutism: Identification and Linkage to Temperamental and Social Constructs.

    Science.gov (United States)

    Diliberto, Rachele; Kearney, Christopher A

    2017-11-21

    Selective mutism (SM) is a stable, debilitating psychiatric disorder in which a child fails to speak in most public situations. Considerable debate exists as to the typology of this population, with empirically-based studies pointing to possible dimensions of anxiety, oppositionality, and communication problems, among other aspects. Little work has juxtaposed identified symptom profiles with key temperamental and social constructs often implicated in SM. The present study examined a large, diverse, non-clinical, international sample of children aged 6-10 years with SM to empirically identify symptom profiles and to link these profiles to key aspects of temperament (i.e., emotionality, shyness, sociability, activity) and social functioning (i.e., social problems, social competence). Exploratory and confirmatory factor analysis revealed anxiety/distress, oppositionality, and inattention domains. In addition, latent class analysis revealed nuanced profiles labeled as (1) moderately anxious, oppositional, and inattentive, (2) highly anxious, and moderately oppositional and inattentive, and (3) mildly to moderately anxious, and mildly oppositional and inattentive. Class 2 was the most impaired group and was associated with greater emotionality, shyness, and social problems. Class 3 was the least impaired group and was associated with better sociability and social competence and activity. Class 1 was largely between the other classes, demonstrating less shyness and social problems than Class 2. The results help confirm previous findings of anxiety and oppositional profiles among children with SM but that nuanced classes may indicate subtle variations in impairment. The results have implications not only for subtyping this population but also for refining assessment and case conceptualization strategies and pursuing personalized and perhaps less lengthy treatment.

  18. 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

  19. 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

  20. 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.

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

    Science.gov (United States)

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

    2015-06-01

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

  2. 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."

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

    Science.gov (United States)

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

    2017-11-27

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

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

    Science.gov (United States)

    Lafortune, Louise; Béland, François; Bergman, Howard; Ankri, Joël

    2009-02-03

    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. 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. 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. 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 information for the planning of longitudinal studies of aging

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

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    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

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

    Science.gov (United States)

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

    2017-08-09

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

  7. Estimating Classification Errors Under Edit Restrictions in Composite Survey-Register Data Using Multiple Imputation Latent Class Modelling (MILC

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    Boeschoten Laura

    2017-12-01

    Full Text Available Both registers and surveys can contain classification errors. These errors can be estimated by making use of a composite data set. We propose a new method based on latent class modelling to estimate the number of classification errors across several sources while taking into account impossible combinations with scores on other variables. Furthermore, the latent class model, by multiply imputing a new variable, enhances the quality of statistics based on the composite data set. The performance of this method is investigated by a simulation study, which shows that whether or not the method can be applied depends on the entropy R2 of the latent class model and the type of analysis a researcher is planning to do. Finally, the method is applied to public data from Statistics Netherlands.

  8. Latent class joint model of ovarian function suppression and DFS for premenopausal breast cancer patients.

    Science.gov (United States)

    Zhang, Jenny J; Wang, Molin

    2010-09-30

    Breast cancer is the leading cancer in women of reproductive age; more than a quarter of women diagnosed with breast cancer in the US are premenopausal. A common adjuvant treatment for this patient population is chemotherapy, which has been shown to cause premature menopause and infertility with serious consequences to quality of life. Luteinizing-hormone-releasing hormone (LHRH) agonists, which induce temporary ovarian function suppression (OFS), has been shown to be a useful alternative to chemotherapy in the adjuvant setting for estrogen-receptor-positive breast cancer patients. LHRH agonists have the potential to preserve fertility after treatment, thus, reducing the negative effects on a patient's reproductive health. However, little is known about the association between a patient's underlying degree of OFS and disease-free survival (DFS) after receiving LHRH agonists. Specifically, we are interested in whether patients with lower underlying degrees of OFS (i.e. higher estrogen production) after taking LHRH agonists are at a higher risk for late breast cancer events. In this paper, we propose a latent class joint model (LCJM) to analyze a data set from International Breast Cancer Study Group (IBCSG) Trial VIII to investigate the association between OFS and DFS. Analysis of this data set is challenging due to the fact that the main outcome of interest, OFS, is unobservable and the available surrogates for this latent variable involve masked event and cured proportions. We employ a likelihood approach and the EM algorithm to obtain parameter estimates and present results from the IBCSG data analysis.

  9. 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

  10. Physicians' perception of demand-induced supply in the information age: a latent class model analysis.

    Science.gov (United States)

    Shih, Ya-Chen Tina; Tai-Seale, Ming

    2012-03-01

    This paper introduces a concept called 'demand-induced supply' that reflects the excess supply of services due to an increase in demand initiated by patients. We examine its association with the proportion of information-savvy patients in physicians' practice. Using data from a national representative physician survey, we apply latent class models to analyze this association. Our analyses categorize physicians into three 'types' according to the frequency with which they provided additional medical services at their patients' requests: frequent, occasional, and rare. The proportion of information-savvy patients is significantly and positively correlated with demand-induced supply for the frequent or occasional type, but not among physicians in the rare type. Efforts to contain healthcare costs through utilization control need to recognize the pattern of responses from physicians who treat an increasing number of information-savvy patients. Copyright © 2011 John Wiley & Sons, Ltd.

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

    Science.gov (United States)

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

    2016-01-01

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

  12. 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.

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

    Science.gov (United States)

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

    2016-08-12

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

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

    Science.gov (United States)

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

    2016-12-01

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

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

    Science.gov (United States)

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

    2011-01-01

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

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

    Science.gov (United States)

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

    2011-03-01

    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). 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. 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. 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.

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

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    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.

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

    Science.gov (United States)

    Hamza, Chloe A.; Willoughby, Teena

    2013-01-01

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

  19. 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.

  20. 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

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

    Science.gov (United States)

    Lawler, Margaret; Heary, Caroline; Nixon, Elizabeth

    2017-08-17

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

  2. High prevalence of latent tuberculosis infection among injection drug users in Tijuana, Mexico.

    Science.gov (United States)

    Garfein, R S; Lozada, R; Liu, L; Laniado-Laborin, R; Rodwell, T C; Deiss, R; Alvelais, J; Catanzaro, A; Chiles, P G; Strathdee, S A

    2009-05-01

    We studied prevalence and correlates of latent tuberculosis infection (LTBI) among injection drug users (IDUs) in Tijuana, Mexico, where tuberculosis (TB) is endemic. IDUs aged > or =18 years were recruited via respondent-driven sampling (RDS) and underwent standardized interviews, human immunodeficiency virus (HIV) antibody testing and LTBI screening using Quanti-FERON((R))-TB Gold In-Tube, a whole-blood interferon-gamma release assay (IGRA). LTBI prevalence was estimated and correlates were identified using RDS-weighted logistic regression. Of 1020 IDUs, 681 (67%) tested IGRA-positive and 44 (4%) tested HIV-positive. Mean age was 37 years, 88% were male and 98% were Mexican-born. IGRA positivity was associated with recruitment nearest the US border (aOR 1.64, 95%CI 1.09-2.48), increasing years of injection (aOR 1.20/5 years, 95%CI 1.07-1.34), and years lived in Tijuana (aOR 1.10/5 years, 95%CI 1.03-1.18). Speaking some English (aOR 0.38, 95%CI 0.25-0.57) and injecting most often at home in the past 6 months (aOR 0.68, 95%CI 0.45-0.99) were inversely associated with IGRA positivity. Increased LTBI prevalence among IDUs in Tijuana appears to be associated with greater drug involvement. Given the high risk for HIV infection among Tijuana's IDUs, interventions are urgently needed to prevent HIV infection and treat LTBI among IDUs before these epidemics collide.

  3. 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.

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

    Science.gov (United States)

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

    2015-09-01

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

  5. 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.

  6. 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.

  7. 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

  8. 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

  9. Interactions between lower urinary tract symptoms and cardiovascular risk factors determine distinct patterns of erectile dysfunction: a latent class analysis.

    Science.gov (United States)

    Barbosa, João A B A; Muracca, Eduardo; Nakano, Élcio; Assalin, Adriana R; Cordeiro, Paulo; Paranhos, Mario; Cury, José; Srougi, Miguel; Antunes, Alberto A

    2013-12-01

    An epidemiological association between lower urinary tract symptoms and erectile dysfunction is well established. However, interactions among multiple risk factors and the role of each in pathological mechanisms are not fully elucidated We enrolled 898 men undergoing prostate cancer screening for evaluation with the International Prostate Symptom Score (I-PSS) and simplified International Index of Erectile Function-5 (IIEF-5) questionnaires. Age, race, hypertension, diabetes, dyslipidemia, metabolic syndrome, cardiovascular disease, serum hormones and anthropometric parameters were also evaluated. Risk factors for erectile dysfunction were identified by logistic regression. The 333 men with at least mild to moderate erectile dysfunction (IIEF 16 or less) were included in a latent class model to identify relationships across erectile dysfunction risk factors. Age, hypertension, diabetes, lower urinary tract symptoms and cardiovascular event were independent predictors of erectile dysfunction (pclasses of patients with erectile dysfunction (R2 entropy=0.82). Latent class 1 had younger men at low cardiovascular risk and a moderate/high prevalence of lower urinary tract symptoms. Latent class 2 had the oldest patients at moderate cardiovascular risk with an increased prevalence of lower urinary tract symptoms. Latent class 3 had men of intermediate age with the highest prevalence of cardiovascular risk factors and lower urinary tract symptoms. Erectile dysfunction severity and lower urinary tract symptoms increased from latent class 1 to 3. Risk factor interactions determined different severities of lower urinary tract symptoms and erectile dysfunction. The effect of lower urinary tract symptoms and cardiovascular risk outweighed that of age. While in the youngest patients lower urinary tract symptoms acted as a single risk factor for erectile dysfunction, the contribution of vascular disease resulted in significantly more severe dysfunction. Applying a risk factor

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

    Science.gov (United States)

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

    2014-01-01

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

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

    Science.gov (United States)

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

    2014-01-01

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

  12. 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

  13. Estimating Classification Errors under Edit Restrictions in Composite Survey-Register Data Using Multiple Imputation Latent Class Modelling (MILC)

    NARCIS (Netherlands)

    Boeschoten, Laura; Oberski, Daniel; De Waal, Ton

    2017-01-01

    Both registers and surveys can contain classification errors. These errors can be estimated by making use of a composite data set. We propose a new method based on latent class modelling to estimate the number of classification errors across several sources while taking into account impossible

  14. 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

  15. 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

  16. 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%),…

  17. 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

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

    Science.gov (United States)

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

    2017-01-01

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

  19. 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…

  20. Combining choice experiments with psychometric scales to assess the social acceptability of wind energy projects: A latent class approach

    International Nuclear Information System (INIS)

    Strazzera, Elisabetta; Mura, Marina; Contu, Davide

    2012-01-01

    A choice experiment exercise is combined with psychometric scales in order: (1) to identify factors that explain support/opposition toward a wind energy development project; and (2) to assess (monetary) trade-offs between attributes of the project. A Latent Class estimator is fitted to the data, and different utility parameters are estimated, conditional on class allocation. It is found that the probability of class membership depends on specific psychometric variables. Visual impacts on valued sites are an important factor of opposition toward a project, and this effect is magnified when identity values are attached to the specific site, so much that no trade-off would be acceptable for a class of individuals characterized by strong place attachment. Conversely, other classes of individuals are willing to accept compensations, in form of private and/or public benefits. The distribution of benefits in the territory, and preservation of the option value related to the possible development of an archeological site, are important for a class of individuals concerned with the sustainability of the local economy. - Highlights: ► A Choice Experiment approach is used to assess acceptability of a wind farm project. ► Psychometric variables are used to model heterogeneity in a Latent Class model. ► No trade-off would be acceptable for a class of individuals. ► Another class of individuals is interested in private benefits. ► Other classes are interested in public benefits and sustainability of the development.

  1. Spurious Latent Class Problem in the Mixed Rasch Model: A Comparison of Three Maximum Likelihood Estimation Methods under Different Ability Distributions

    Science.gov (United States)

    Sen, Sedat

    2018-01-01

    Recent research has shown that over-extraction of latent classes can be observed in the Bayesian estimation of the mixed Rasch model when the distribution of ability is non-normal. This study examined the effect of non-normal ability distributions on the number of latent classes in the mixed Rasch model when estimated with maximum likelihood…

  2. A personalized BEST: characterization of latent clinical classes of nonischemic heart failure that predict outcomes and response to bucindolol.

    Directory of Open Access Journals (Sweden)

    David P Kao

    Full Text Available Heart failure patients with reduced ejection fraction (HFREF are heterogenous, and our ability to identify patients likely to respond to therapy is limited. We present a method of identifying disease subtypes using high-dimensional clinical phenotyping and latent class analysis that may be useful in personalizing prognosis and treatment in HFREF.A total of 1121 patients with nonischemic HFREF from the β-blocker Evaluation of Survival Trial were categorized according to 27 clinical features. Latent class analysis was used to generate two latent class models, LCM A and B, to identify HFREF subtypes. LCM A consisted of features associated with HF pathogenesis, whereas LCM B consisted of markers of HF progression and severity. The Seattle Heart Failure Model (SHFM Score was also calculated for all patients. Mortality, improvement in left ventricular ejection fraction (LVEF defined as an increase in LVEF ≥5% and a final LVEF of 35% after 12 months, and effect of bucindolol on both outcomes were compared across HFREF subtypes. Performance of models that included a combination of LCM subtypes and SHFM scores towards predicting mortality and LVEF response was estimated and subsequently validated using leave-one-out cross-validation and data from the Multicenter Oral Carvedilol Heart Failure Assessment Trial.A total of 6 subtypes were identified using LCM A and 5 subtypes using LCM B. Several subtypes resembled familiar clinical phenotypes. Prognosis, improvement in LVEF, and the effect of bucindolol treatment differed significantly between subtypes. Prediction improved with addition of both latent class models to SHFM for both 1-year mortality and LVEF response outcomes.The combination of high-dimensional phenotyping and latent class analysis identifies subtypes of HFREF with implications for prognosis and response to specific therapies that may provide insight into mechanisms of disease. These subtypes may facilitate development of personalized

  3. 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.

  4. 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

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

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    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

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

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

    2017-01-01

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

  7. 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.

  8. Latent class analysis of multimorbidity patterns and associated outcomes in Spanish older adults: a prospective cohort study.

    Science.gov (United States)

    Olaya, Beatriz; Moneta, Maria Victoria; Caballero, Francisco Félix; Tyrovolas, Stefanos; Bayes, Ivet; Ayuso-Mateos, José Luis; Haro, Josep Maria

    2017-08-18

    This study sought to identify multimorbidity patterns and determine the association between these latent classes with several outcomes, including health, functioning, disability, quality of life and use of services, at baseline and after 3 years of follow-up. We analyzed data from a representative Spanish cohort of 3541 non-institutionalized people aged 50 years old and over. Measures were taken at baseline and after 3 years of follow-up. Latent Class Analysis (LCA) was conducted using eleven common chronic conditions. Generalized linear models were conducted to determine the adjusted association of multimorbidity latent classes with several outcomes. 63.8% of participants were assigned to the "healthy" class, with minimum disease, 30% were classified under the "metabolic/stroke" class and 6% were assigned to the "cardiorespiratory/mental/arthritis" class. Significant cross-sectional associations were found between membership of both multimorbidity classes and poorer memory, quality of life, greater burden and more use of services. After 3 years of follow-up, the "metabolic/stroke" class was a significant predictor of lower levels of verbal fluency while the two multimorbidity classes predicted poor quality of life, problems in independent living, higher risk of hospitalization and greater use of health services. Common chronic conditions in older people cluster together in broad categories. These broad clusters are qualitatively distinct and are important predictors of several health and functioning outcomes. Future studies are needed to understand underlying mechanisms and common risk factors for patterns of multimorbidity and to propose more effective treatments.

  9. Investigating attribute non-attendance and its consequences in choice experiments with latent class models.

    Science.gov (United States)

    Lagarde, Mylene

    2013-05-01

    A growing literature, mainly from transport and environment economics, has started to explore whether respondents violate some of the axioms about individuals' preferences in Discrete Choice Experiments (DCEs) and use simple strategies to make their choices. One of these strategies, termed attribute non-attendance (ANA), consists in ignoring one or more attributes. Using data from a DCE administered to healthcare providers in Ghana to evaluate their potential resistance to changes in clinical guidelines, this study illustrates how latent class models can be used in a step-wise approach to account for all possible ANA strategies used by respondents and explore the consequences of such behaviours. Results show that less than 3% of respondents considered all attributes when choosing between the two hypothetical scenarios proposed, with a majority looking at only one or two attributes. Accounting for ANA strategies improved the goodness-of-fit of the model and affected the magnitude of some of the coefficient and willingness-to-pay estimates. However, there was no difference in the predicted probabilities of the model taking into account ANA and the standard approach. Although the latter result is reassuring about the ability of DCEs to produce unbiased policy guidance, it should be confirmed by other studies. Copyright © 2012 John Wiley & Sons, Ltd.

  10. 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.

  11. 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.

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

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    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.

  13. 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.

  14. 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.

  15. 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.

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

    Science.gov (United States)

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

    2016-03-01

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

  17. Evaluating photographic scales of facial pores and diagnostic agreement of tests using latent class models.

    Science.gov (United States)

    Ning, Yao; Qing, Zeng; Qing, Wang; Li, Li

    2017-02-01

    Ordinal severity scales illustrated by photographs have been widely developed to help dermatologists in evaluating skin problems or improvements. Numerous scales have been published, and none of them were used for assessing facial pores. A five-point photographic scale of facial pores was formulated, and photographs of pores on nasal ala from 128 female volunteers were acquired. Five dermatologists with similar experiences rated the 128 photographs independently using the reference photographs. Latent Class Models (LCM) were used to analyze the data. Firstly, we hypothesized that the conditional probabilities of the five dermatologists were identical to build the first LCM and without the restriction to formulate the second LCM. Conditional probability and posterior probability were also calculated. The five-point scales were ambiguous as the raters actually had difficulties in distinguishing between some adjacent categories. Adjacent categories were pooled for reanalyzing, and the model fitted well. The newly developed photographic scale of Chinese facial pores should be redefined to improve their quality and reproducibility in future studies. Standardized scales for the measurement of aging and response to cosmetic therapy were essential for assessing diagnostic experiment. The LCM can effectively deal with diagnostic test of agreement and reproducibility.

  18. 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.

  19. 1842676957299765Latent class cluster analysis to understand heterogeneity in prostate cancer treatment utilities

    Directory of Open Access Journals (Sweden)

    Meghani Salimah

    2009-01-01

    Full Text Available Abstract Background Men with prostate cancer are often challenged to choose between conservative management and a range of available treatment options each carrying varying risks and benefits. The trade-offs are between an improved life-expectancy with treatment accompanied by important risks such as urinary incontinence and erectile dysfunction. Previous studies of preference elicitation for prostate cancer treatment have found considerable heterogeneity in individuals' preferences for health states given similar treatments and clinical risks. Methods Using latent class mixture model (LCA, we first sought to understand if there are unique patterns of heterogeneity or subgroups of individuals based on their prostate cancer treatment utilities (calculated time trade-off utilities for various health states and if such unique subgroups exist, what demographic and urological variables may predict membership in these subgroups. Results The sample (N = 244 included men with prostate cancer (n = 188 and men at-risk for disease (n = 56. The sample was predominantly white (77%, with mean age of 60 years (SD ± 9.5. Most (85.9% were married or living with a significant other. Using LCA, a three class solution yielded the best model evidenced by the smallest Bayesian Information Criterion (BIC, substantial reduction in BIC from a 2-class solution, and Lo-Mendell-Rubin significance of < .001. The three identified clusters were named high-traders (n = 31, low-traders (n = 116, and no-traders (n = 97. High-traders were more likely to trade survival time associated with treatment to avoid potential risks of treatment. Low-traders were less likely to trade survival time and accepted risks of treatment. The no-traders were likely to make no trade-offs in any direction favouring the status quo. There was significant difference among the clusters in the importance of sexual activity (Pearson's χ2 = 16.55, P = 0.002; Goodman and Kruskal tau = 0.039, P < 0.001. In

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

    Science.gov (United States)

    Erickson, Darin J.; Laska, Melissa N.

    2015-01-01

    Background Food shopping is a complex behavior that consists of multiple dimensions. Little research has explored multiple dimensions of food shopping or examined how it relates to dietary intake. Objective To identify patterns (or ‘classes’) of food shopping across four domains (fresh food purchasing, “conscientious” food shopping, food shopping locations, and food/beverage purchasing on or near campus) and explore how these patterns relate to dietary intake among college students. Design A cross-sectional online survey was administered. Participants/setting Students attending a public 4-year university and a 2-year community college in the Twin Cities metropolitan area (n=1,201) participated in this study. Main outcome measures Fast food and soda consumption; meeting fruit and vegetable, fiber, added sugar, calcium, dairy, and fat recommendations. Statistical analyses Crude and adjusted latent class models and adjusted logistic regression models were fit. Results An eight-class solution was identified: “traditional shopper (14.9%),” “fresh food and supermarket shopper (14.1%),” “convenience shopper (18.8%),” “conscientious convenience shopper (13.8%),” “conscientious, fresh food, convenience shopper (11.8%),” “conscientious fresh food shopper (6.6%),” “conscientious non-shopper (10.2%)”, and “non-shopper (9.8%).” “Fresh food and supermarket shoppers” and “conscientious fresh food shopper” had better dietary intake (for fast food, calcium, dairy, and added sugar) while “convenience shoppers” and “conscientious convenience shoppers,” and “non-shoppers” had worse dietary intake (for soda, calcium, dairy, fiber, and fat) than “traditional shoppers.” Conclusions These findings highlight unique patterns in food shopping and associated dietary patterns that could inform tailoring of nutrition interventions for college students. Additional research is needed to understand modifiable contextual influences of

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

    Science.gov (United States)

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

    2014-01-01

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

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

    Directory of Open Access Journals (Sweden)

    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.

  3. 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.

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

    Science.gov (United States)

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

    2012-08-05

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

  5. 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.

  6. Acculturation and Self-Rated Mental Health Among Latino and Asian Immigrants in the United States: A Latent Class Analysis.

    Science.gov (United States)

    Bulut, Elif; Gayman, Matthew D

    2016-08-01

    This study assesses variations in acculturation experiences by identifying distinct acculturation classes, and investigates the role of these acculturation classes for self-rated mental health among Latino and Asian immigrants in the United States. Using 2002-2003 the National Latino and Asian American Study, Latent Class Analysis is used to capture variations in immigrant classes (recent arrivals, separated, bicultural and assimilated), and OLS regressions are used to assess the link between acculturation classes and self-rated mental health. For both Latinos and Asians, bicultural immigrants reported the best mental health, and separated immigrants and recent arrivals reported the worst mental health. The findings also reveal group differences in acculturation classes, whereby Latino immigrants were more likely to be in the separated class and recent arrivals class relative to Asian immigrants. While there was not a significant group difference in self-rated mental health at the bivariate level, controlling for acculturation classes revealed that Latinos report better self-rated mental health than Asians. Thus, Latino immigrants would actually have better self-rated mental health than their Asian counterparts if they were not more likely to be represented in less acculturated classes (separated class and recent arrivals) and/or as likely to be in the bicultural class as their Asian counterparts. Together the findings underscore the nuanced and complex nature of the acculturation process, highlighting the importance of race differences in this process, and demonstrate the role of acculturation classes for immigrant group differences in self-rated mental health.

  7. Friendship networks of inner-city adults: a latent class analysis and multi-level regression of supporter types and the association of supporter latent class membership with supporter and recipient drug use.

    Science.gov (United States)

    Bohnert, Amy S B; German, Danielle; Knowlton, Amy R; Latkin, Carl A

    2010-03-01

    Social support is a multi-dimensional construct that is important to drug use cessation. The present study identified types of supportive friends among the social network members in a community-based sample and examined the relationship of supporter-type classes with supporter, recipient, and supporter-recipient relationship characteristics. We hypothesized that the most supportive network members and their support recipients would be less likely to be current heroin/cocaine users. Participants (n=1453) were recruited from low-income neighborhoods with a high prevalence of drug use. Participants identified their friends via a network inventory, and all nominated friends were included in a latent class analysis and grouped based on their probability of providing seven types of support. These latent classes were included as the dependent variable in a multi-level regression of supporter drug use, recipient drug use, and other characteristics. The best-fitting latent class model identified five support patterns: friends who provided Little/No Support, Low/Moderate Support, High Support, Socialization Support, and Financial Support. In bivariate models, friends in the High, Low/Moderate, and Financial Support were less likely to use heroin or cocaine and had less conflict with and were more trusted by the support recipient than friends in the Low/No Support class. Individuals with supporters in those same support classes compared to the Low/No Support class were less likely to use heroin or cocaine, or to be homeless or female. Multivariable models suggested similar trends. Those with current heroin/cocaine use were less likely to provide or receive comprehensive support from friends. Published by Elsevier Ireland Ltd.

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

    Directory of Open Access Journals (Sweden)

    Manuela da Silva Solcà

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

  9. Perceived Treatment Need and Latent Transitions in Heroin and Methamphetamine Polydrug Use among People who Inject Drugs in Tijuana, Mexico.

    Science.gov (United States)

    Meacham, Meredith C; Roesch, Scott C; Strathdee, Steffanie A; Gaines, Tommi L

    2018-01-01

    People who inject drugs (PWID) in Tijuana, Mexico, use heroin and/or methamphetamine. While polydrug use is associated with HIV risk behavior, less is known about the stability of polydrug use patterns over time and how polydrug use is related to perceived treatment need. Within a cohort of PWID in Tijuana (N = 735) we sought to (1) characterize subgroups of polydrug and polyroute use from baseline to six months; (2) determine the probabilities of transitioning between subgroups; and (3) examine whether self-reported need for help for drug use modified these transition probabilities. Latent transition analysis (LTA) identified four latent statuses: heroin-only injection (38% at both baseline and follow-up); co-injection of heroin with methamphetamine (3% baseline, 15% follow-up); injection of heroin and methamphetamine (37% baseline, 32% follow-up); and polydrug and polyroute users who injected heroin and both smoked and injected methamphetamine (22% baseline, 14% follow-up). Heroin-only injectors had the highest probability of remaining in the same latent status at follow-up. The majority reported great or urgent need for treatment (51%) and these PWID had greater odds of transitioning to a higher-risk status at follow-up, emphasizing the need for evidence-based drug treatment options for PWID.

  10. Using the latent class approach to cluster firms in benchmarking: An application to the US electricity transmission industry

    Directory of Open Access Journals (Sweden)

    Manuel Llorca

    2014-03-01

    Full Text Available In this paper we advocate using the latent class model (LCM approach to control for technological differences in traditional efficiency analysis of regulated electricity networks. Our proposal relies on the fact that latent class models are designed to cluster firms by uncovering differences in technology parameters. Moreover, it can be viewed as a supervised method for clustering data that takes into account the same (production or cost relationship that is analysed later, often using nonparametric frontier techniques. The simulation exercises show that the proposed approach outperforms other sample selection procedures. The proposed methodology is illustrated with an application to a sample of US electricity transmission firms for the period 2001–2009.

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

    Science.gov (United States)

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

    2017-01-01

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

  12. Understanding today’s music acquisition mix: a latent class analysis of consumers’ combined use of music platforms

    OpenAIRE

    Weijters, Bert; Goedertier, Frank

    2016-01-01

    In response to diversifying music delivery modes, consumers increasingly combine various music platforms, both online and offline, legal and illegal, and free or paying. Based on survey data (N = 685), the current study segments consumers in terms of the combination of music delivery modes they use. We identify four latent classes based on their usage frequency of purchasing CDs, copying CDs, streaming music, streaming music videos, peer-to-peer file sharing, and purchased downloading. All-ro...

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

    OpenAIRE

    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 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 ...

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

    DEFF Research Database (Denmark)

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

    2008-01-01

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

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

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

    2015-01-01

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

  17. Serodiagnosis of tuberculosis in Asian elephants (Elephas maximus in Southern India: a latent class analysis.

    Directory of Open Access Journals (Sweden)

    Shalu Verma-Kumar

    Full Text Available BACKGROUND: Mycobacterium tuberculosis, a causative agent of chronic tuberculosis disease, is widespread among some animal species too. There is paucity of information on the distribution, prevalence and true disease status of tuberculosis in Asian elephants (Elephas maximus. The aim of this study was to estimate the sensitivity and specificity of serological tests to diagnose M. tuberculosis infection in captive elephants in southern India while simultaneously estimating sero-prevalence. METHODOLOGY/PRINCIPAL FINDINGS: Health assessment of 600 elephants was carried out and their sera screened with a commercially available rapid serum test. Trunk wash culture of select rapid serum test positive animals yielded no animal positive for M. tuberculosis isolation. Under Indian field conditions where the true disease status is unknown, we used a latent class model to estimate the diagnostic characteristics of an existing (rapid serum test and new (four in-house ELISA tests. One hundred and seventy nine sera were randomly selected for screening in the five tests. Diagnostic sensitivities of the four ELISAs were 91.3-97.6% (95% Credible Interval (CI: 74.8-99.9 and diagnostic specificity were 89.6-98.5% (95% CI: 79.4-99.9 based on the model we assumed. We estimate that 53.6% (95% CI: 44.6-62.8 of the samples tested were free from infection with M. tuberculosis and 15.9% (97.5% CI: 9.8 - to 24.0 tested positive on all five tests. CONCLUSIONS/SIGNIFICANCE: Our results provide evidence for high prevalence of asymptomatic M. tuberculosis infection in Asian elephants in a captive Indian setting. Further validation of these tests would be important in formulating area-specific effective surveillance and control measures.

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

    Science.gov (United States)

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

    2018-05-23

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

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

    Science.gov (United States)

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

    2018-01-01

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

  20. Sex-related and non-sex-related comorbidity subtypes of tic disorders: a latent class approach.

    Science.gov (United States)

    Rodgers, S; Müller, M; Kawohl, W; Knöpfli, D; Rössler, W; Castelao, E; Preisig, M; Ajdacic-Gross, V

    2014-05-01

    Recent evidence suggests that there may be more than one Gilles de la Tourette syndrome (GTS)/tic disorder phenotype. However, little is known about the common patterns of these GTS/tic disorder-related comorbidities. In addition, sex-specific phenomenological data of GTS/tic disorder-affected adults are rare. Therefore, this community-based study used latent class analyses (LCA) to investigate sex-related and non-sex-related subtypes of GTS/tic disorders and their most common comorbidities. The data were drawn from the PsyCoLaus study (n = 3691), a population-based survey conducted in Lausanne, Switzerland. LCA were performed on the data of 80 subjects manifesting motor/vocal tics during their childhood/adolescence. Comorbid attention-deficit hyperactivity disorder (ADHD), obsessive-compulsive disorder, depressive, phobia and panic symptoms/syndromes comprised the selected indicators. The resultant classes were characterized by psychosocial correlates. In LCA, four latent classes provided the best fit to the data. We identified two male-related classes. The first class exhibited both ADHD and depression. The second class comprised males with only depression. Class three was a female-related class depicting obsessive thoughts/compulsive acts, phobias and panic attacks. This class manifested high psychosocial impairment. Class four had a balanced sex proportion and comorbid symptoms/syndromes such as phobias and panic attacks. The complementary occurrence of comorbid obsessive thoughts/compulsive acts and ADHD impulsivity was remarkable. To the best of our knowledge, this is the first study applying LCA to community data of GTS symptoms/tic disorder-affected persons. Our findings support the utility of differentiating GTS/tic disorder subphenotypes on the basis of comorbid syndromes. © 2013 The Author(s) European Journal of Neurology © 2013 EFNS.

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

    Science.gov (United States)

    Kanayama, Mieko; Suzuki, Machiko; Yuma, Yoshikazu

    2016-01-01

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

  2. A comparison of latent class, K-means, and K-median methods for clustering dichotomous data.

    Science.gov (United States)

    Brusco, Michael J; Shireman, Emilie; Steinley, Douglas

    2017-09-01

    The problem of partitioning a collection of objects based on their measurements on a set of dichotomous variables is a well-established problem in psychological research, with applications including clinical diagnosis, educational testing, cognitive categorization, and choice analysis. Latent class analysis and K-means clustering are popular methods for partitioning objects based on dichotomous measures in the psychological literature. The K-median clustering method has recently been touted as a potentially useful tool for psychological data and might be preferable to its close neighbor, K-means, when the variable measures are dichotomous. We conducted simulation-based comparisons of the latent class, K-means, and K-median approaches for partitioning dichotomous data. Although all 3 methods proved capable of recovering cluster structure, K-median clustering yielded the best average performance, followed closely by latent class analysis. We also report results for the 3 methods within the context of an application to transitive reasoning data, in which it was found that the 3 approaches can exhibit profound differences when applied to real data. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

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

    Directory of Open Access Journals (Sweden)

    Haipeng Wang

    2017-09-01

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

  4. Risk-taking behaviors and subgrouping of suicide in Iran: A latent class analysis of national registries data.

    Science.gov (United States)

    Hajebi, Ahmad; Abbasi-Ghahramanloo, Abbas; Hashemian, Seyed Sepehr; Khatibi, Seyed Reza; Ghasemzade, Masomeh; Khodadost, Mahmoud

    2017-09-01

    Suicide is one the most important public health problem which is rapidly growing concerns. The aim of this study was to subgroup suicide using LCA method. This cross-sectional study was conducted in Iran based on 66990 records registered in Ministry of Health in 2014. A case report questionnaire in the form of software was used for case registries. Latent class analysis was used to achieve the research objectives. Four latent classes were identified; (a) Non-lethal attempters without a history of psychiatric disorders, (b) Non-lethal attempters with a history of psychiatric disorders, (c) Lethal attempters without a history of psychiatric disorders, (d) Lethal attempters with a history of psychiatric disorders. The probability of completed/an achieved suicide is high in lethal attempter classes. Being male increases the risk of inclusion in lethal attempters' classes (OR = 4.93). Also, being single (OR = 1.16), having an age lower than 25 years (OR = 1.14) and being a rural citizen (OR = 2.36) associate with lethal attempters classes. The males tend to use more violent methods and have more completed suicide. Majority of the individuals are non-lethal attempters who need to be addressed by implementing preventive interventions and mental support provision. Copyright © 2017. Published by Elsevier B.V.

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

    Science.gov (United States)

    Södergren, Marita; Wang, Wei Chun; Salmon, Jo; Ball, Kylie; Crawford, David; McNaughton, Sarah A

    2014-01-01

    The aim of this study was to identify subgroups of retirement age older adults with respect to their lifestyle patterns of eating, drinking, smoking, physical activity and TV viewing behaviors, and to examine the association between these patterns and socio-demographic covariates. The sample consisted of 3133 older adults aged 55-65 years from the Wellbeing, Eating and Exercise for a Long Life (WELL) study, 2010. This study used latent class analysis (stratified by sex), with a set of lifestyle indicators and including socio-demographic covariates. Statistical analyses were performed by generalized linear latent and mixed models in Stata. Two classes of lifestyle patterns were identified: Healthy (53% men and 72% women) and less healthy lifestyles. Physical activity, TV-viewing time, and fruit intake were good indicators distinguishing the "Healthier" class, whereas consumption of vegetables, alcohol (men) and fast food (women) could not clearly discriminate older adults in the two classes. Class membership was associated with education, body mass index, and self-rated health. This study contributes to the literature on lifestyle behaviors among older adults, and provides evidence that there are meaningful sex differences in lifestyle behaviors between subgroups of older adults. From a policy perspective, understanding indicators or "markers" of healthy and less healthy lifestyle patterns is important for identifying target groups for interventions. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  6. Microaggressions, Discrimination, and Phenotype among African Americans: A Latent Class Analysis of the Impact of Skin Tone and BMI.

    Science.gov (United States)

    Keith, Verna M; Nguyen, Ann W; Taylor, Robert Joseph; Mouzon, Dawne M; Chatters, Linda M

    2017-05-01

    Data from the 2001-2003National Survey of American Life are used to investigate the effects of phenotype on everyday experiences with discrimination among African Americans (N=3343). Latent class analysis is used to identify four classes of discriminatory treatment: 1) low levels of discrimination, 2) disrespect and condescension, 3) character-based discrimination, and 4) high levels of discrimination. We then employ latent class multinomial logistic regression to evaluate the association between skin tone and body weight and these four classes of discrimination. Designating the low level discrimination class as the reference group, findings revealed that respondents with darker skin were more likely to be classified into the disrespect/condescension and the high level microaggression types. BMI was unrelated to the discrimination type, although there was a significant interaction effect between gender and BMI. BMI was strongly and positively associated with membership in the disrespect and condescension type among men but not among women. These findings indicate that skin tone and body weight are two phenotypic characteristics that influence the type and frequency of discrimination experienced by African Americans.

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

    Directory of Open Access Journals (Sweden)

    Kobto G Koura

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

  8. Species, functional groups, and habitat preferences of birds in five agroforestry classes in Tabasco, Mexico

    NARCIS (Netherlands)

    Wal, van der J.C.; Peña-Álvarez, B.; Arriaga-Weiss, S.L.; Hernández-Daumás, S.

    2012-01-01

    We studied species, functional groups, and habitat preferences of birds in five classes of agroforestry systems: agroforests, animal agroforestry, linear agroforestry, sequential agroforestry, and crops under tree cover in Tabasco, Mexico. Sampling sites were >2 km from natural forest fragments.

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

    Science.gov (United States)

    Rinker, Dipali Venkataraman; Diamond, Pamela M; Walters, Scott T; Wyatt, Todd M; DeJong, William

    2016-09-01

    : First-year college students are at particular risk for experiencing negative alcohol-related consequences that may set the stage for experiencing such consequences in later life. Latent class analysis is a person-centered approach that, based on observable indicator variables, divides a population into mutually exclusive and exhaustive groups ('classes'). To date, no studies have examined the latent class structure of negative alcohol-related consequences experienced by first-year college students just before entering college. The aims of this study were to (a) identify classes of first-year college students based on the patterns of negative alcohol-related consequences they experienced just before entering college, and (b) determine whether specific covariates were associated with class membership. Incoming freshmen from 148 colleges and universities (N = 54,435) completed a baseline questionnaire as part of an alcohol education program they completed just prior to their first year of college. Participants answered questions regarding demographics and other personal characteristics, their alcohol use in the past 2 weeks, and the negative alcohol-related consequences they had experienced during that time. Four distinct classes of students emerged: (a) No Problems, (b) Academic Problems, (c) Injured Self and (d) Severe Problems. Average number of drinks per drinking day, total number of drinking days, age of drinking initiation, intention to join a fraternity or sorority and family history of alcohol problems were associated with membership in all of the problem classes relative to the No Problems class. These results can inform future campus-based prevention efforts. © The Author 2016. Medical Council on Alcohol and Oxford University Press. All rights reserved.

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

    Science.gov (United States)

    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; M age =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.

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

    Science.gov (United States)

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

    2017-01-01

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

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

    Science.gov (United States)

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

    2017-05-24

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

  13. A Latent Class Analysis of Weight-Related Health Behaviors among 2-and 4-Year College Students and Associated Risk of Obesity

    Science.gov (United States)

    Mathur, Charu; Stigler, Melissa; Lust, Katherine; Laska, Melissa

    2014-01-01

    Little is known about the complex patterning of weight-related health behaviors in 2-and 4-year college students. The objective of this study was to identify and describe unique classes of weight-related health behaviors among college students. Latent class analysis was used to identify homogenous, mutually exclusive classes of nine health…

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

    Science.gov (United States)

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

    2018-03-01

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

  15. Outcomes of empirical eating disorder phenotypes in a clinical female sample: results from a latent class analysis.

    Science.gov (United States)

    Dechartres, Agnes; Huas, Caroline; Godart, Nathalie; Pousset, Maud; Pham, Alexandra; Divac, Snezana M; Rouillon, Frederic; Falissard, Bruno

    2011-01-01

    To empirically classify phenotypes of eating disorders (ED) using latent class analysis (LCA), and to validate this classification based on clinical outcomes. LCA was applied to 968 inpatients. The resultant classes were validated by clinical outcomes including mortality. A 5-class solution showed the best fit. The symptoms of latent class 1 (LC1; 26% of the sample) resembled anorexia nervosa (AN), bingeing-purging (AN-B/P) subtype; those of LC2 (23%) resembled bulimia nervosa; those of LC3 (11%) were close to AN-B/P without weight and body concerns; those of LC4 resembled restrictive anorexia nervosa (RAN) without weight and body concerns, and those of LC5 RAN. A history of hospitalization for ED was significantly more frequent for LC3 and LC4. The lowest BMI at admission were presented in LC4. LC1 showed the highest level of psychological disturbances and LC4 the lowest. LC3 and LC4 differed from LC1 and LC5 by higher percentages of treatment dropout (64.9 vs. 57.2 and 55.7 vs. 47.5%, respectively; overall p = 0.001). Survival rates tended to be different between the LC (p = 0.09). Subgroups of AN patients with low weight and body concerns seem more severe at hospitalization and more difficult to manage, with a higher rate of treatment dropout than the 'typical' AN patients. Copyright © 2010 S. Karger AG, Basel.

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

    Science.gov (United States)

    Valente, Juliana Y; Cogo-Moreira, Hugo; Sanchez, Zila M

    2017-11-01

    To identify different patterns of drug use in adolescence and determine if these are associated with parenting styles and other sociodemographic factors. A latent class analysis was conducted using baseline data collected in a sample (n=6381) from a randomized controlled trial conducted to evaluate the effectiveness of the #Tamojunto drug-use prevention program, carried out with 7th- and 8th-grade public school students in six Brazilian cities. Three latent classes were identified among the students: 1) abstainers/low users (81.54%), 2) alcohol users/binge drinkers (16.65%), and 3) polydrug users (1.80%). A gradient of inverse association was found between parenting styles (authoritative, authoritarian, and indulgent, with the neglectful style as a reference point) and the classes "alcohol users/binge drinkers" (aOR=0.36, 95%CI=0.27-0.47; aOR=0.56, 95%CI=0.43-0.72; and aOR=0.64, 95%CI=0.51-0.80, respectively) and "polydrug users" (aOR=0.09, 95%CI=0.03-0.24; aOR=0.23, 95%CI=0.11-0.52; and aOR=0.24, 95%CI=0.08-0.74, respectively). Associations were also revealed between the latent classes and the adolescent's age and socioeconomic status. The results suggest that activities to develop parenting skills should be included in school programs aimed at the prevention of drug use among adolescents in order to reduce neglectful practices and thereby possibly reduce drug use among the children. Copyright © 2017. Published by Elsevier B.V.

  17. Interferon Gamma-Based Detection of Latent Tuberculosis Infection in the Border States of Nuevo Leon and Tamaulipas, Mexico.

    Science.gov (United States)

    Oren, Eyal; Alatorre-Izaguirre, Gabriela; Vargas-Villarreal, Javier; Moreno-Treviño, Maria Guadalupe; Garcialuna-Martinez, Javier; Gonzalez-Salazar, Francisco

    2015-01-01

    Nearly one-third of the world's population is infected with latent tuberculosis (LTBI). Tuberculosis (TB) rates in the border states are higher than national rates in both the US and Mexico, with the border accounting for 30% of total registered TB cases in both countries. However, LTBI rates in the general population in Mexican border states are unknown. In this region, LTBI is diagnosed using the tuberculin skin test (TST). New methods of detection more specific than TST have been developed, although there is currently no gold standard for LTBI detection. Our objective is to demonstrate utility of the Quantiferon TB gold In-Tube (QFT-GIT) test compared with the TST to detect LTBI among border populations. This is an observational, cross-sectional study carried out in border areas of the states of Nuevo Leon and Tamaulipas, Mexico. Participants (n = 210) provided a TST and blood sample for the QFT-GIT. Kappa coefficients assessed the agreement between TST and QFT-GIT. Participant characteristics were compared using Fisher exact tests. Thirty-eight percent of participants were diagnosed with LTBI by QFT-GIT. The proportion of LTBI detected using QFT-GIT was almost double [38% (79/210)] that found by TST [19% (39/210)] (P < 0.001). Concordance between TST and QFT-GIT was low (kappa = 0.37). We recommend further studies utilizing the QFT-GIT test to detect LTBI among border populations.

  18. 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.

  19. 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.

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

    Science.gov (United States)

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

    2016-01-01

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

  1. 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.

  2. Latent Class Analysis of Polysubstance Use, Sexual Risk Behaviors, and Infectious Disease Among South African Drug Users

    Science.gov (United States)

    Trenz, Rebecca C.; Scherer, Michael; Duncan, Alexandra; Harrell, Paul; Moleko, Anne Gloria; Latimer, William

    2013-01-01

    Background HIV transmission risk among non-injection drug users is high due to the co-occurrence of drug use and sexual risk behaviors. The purpose of the current study was to identify patterns of drug use among polysubstance users within a high HIV prevalence population. Methods The study sample included 409 substance users from the Pretoria region of South Africa. Substances used by 20% or more the sample included: cigarettes, alcohol, marijuana and heroin in combination, marijuana and cigarettes in combination, and crack cocaine. Latent class analysis was used to identify patterns of polysubstance use based on types of drugs used. Multivariate logistic regression analyses compared classes on demographics, sexual risk behavior, and disease status. Results Four classes of substance use were found: MJ+Cig (40.8%), MJ+Her (30.8%), Crack (24.7%), and Low Use (3.7%). The MJ+Cig class was 6.7 times more likely to use alcohol and 3 times more likely to use drugs before/during sex with steady partners than the Crack class. The MJ+Cig class was16 times more likely to use alcohol before/during sex with steady partners than the MJ+Her class. The Crack class was 6.1 times more likely to engage in transactional sex and less likely to use drugs before/during steady sex than the MJ+Her class. Conclusions Findings illustrate patterns of drug use among a polysubstance using population that differ in sexual risk behavior. Intervention strategies should address substance use, particularly smoking as a route of administration (ROA), and sexual risk behaviors that best fit this high-risk population. PMID:23562370

  3. 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.

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

    Science.gov (United States)

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

    2017-12-13

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

  5. A framework for estimating causal effects in latent class analysis: is there a causal link between early sex and subsequent profiles of delinquency?

    Science.gov (United States)

    Butera, Nicole M; Lanza, Stephanie T; Coffman, Donna L

    2014-06-01

    Prevention scientists use latent class analysis (LCA) with increasing frequency to characterize complex behavior patterns and profiles of risk. Often, the most important research questions in these studies involve establishing characteristics that predict membership in the latent classes, thus describing the composition of the subgroups and suggesting possible points of intervention. More recently, prevention scientists have begun to adopt modern methods for drawing causal inference from observational data because of the bias that can be introduced by confounders. This same issue of confounding exists in any analysis of observational data, including prediction of latent class membership. This study demonstrates a straightforward approach to causal inference in LCA that builds on propensity score methods. We demonstrate this approach by examining the causal effect of early sex on subsequent delinquency latent classes using data from 1,890 adolescents in 11th and 12th grade from wave I of the National Longitudinal Study of Adolescent Health. Prior to the statistical adjustment for potential confounders, early sex was significantly associated with delinquency latent class membership for both genders (p = 0.02). However, the propensity score adjusted analysis indicated no evidence for a causal effect of early sex on delinquency class membership (p = 0.76) for either gender. Sample R and SAS code is included in an Appendix in the ESM so that prevention scientists may adopt this approach to causal inference in LCA in their own work.

  6. 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

  7. Measuring energy efficiency under heterogeneous technologies using a latent class stochastic frontier approach: An application to Chinese energy economy

    International Nuclear Information System (INIS)

    Lin, Boqiang; Du, Kerui

    2014-01-01

    The importance of technology heterogeneity in estimating economy-wide energy efficiency has been emphasized by recent literature. Some studies use the metafrontier analysis approach to estimate energy efficiency. However, for such studies, some reliable priori information is needed to divide the sample observations properly, which causes a difficulty in unbiased estimation of energy efficiency. Moreover, separately estimating group-specific frontiers might lose some common information across different groups. In order to overcome these weaknesses, this paper introduces a latent class stochastic frontier approach to measure energy efficiency under heterogeneous technologies. An application of the proposed model to Chinese energy economy is presented. Results show that the overall energy efficiency of China's provinces is not high, with an average score of 0.632 during the period from 1997 to 2010. - Highlights: • We introduce a latent class stochastic frontier approach to measure energy efficiency. • Ignoring technological heterogeneity would cause biased estimates of energy efficiency. • An application of the proposed model to Chinese energy economy is presented. • There is still a long way for China to develop an energy efficient regime

  8. 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.

  9. 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

  10. Eight-Year Latent Class Trajectories of Academic and Social Functioning in Children with Attention-Deficit/Hyperactivity Disorder.

    Science.gov (United States)

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

    2017-09-15

    We examined trajectories of academic and social functioning in children with attention-deficit/hyperactivity disorder (ADHD) to identify those who might be at risk for especially severe levels of academic and social impairment over time. We estimated a series of growth mixture models using data from two subsamples of children participating in the NIMH Collaborative Multisite Multimodal Treatment Study of Children with ADHD (MTA) including those with at least baseline and 96-month data for reading and mathematics achievement (n = 392; 77.3% male; M age = 7.7; SD = 0.8) or social skills ratings from teachers (n = 259; 74.9% male; M age = 7.6; SD = 0.8). We compared latent trajectories for children with ADHD to mean observed trajectories obtained from a local normative (i.e., non-ADHD) comparison group (n = 289; 80.6% male; M age = 9.9; SD = 1.1). Results indicated six latent trajectory classes for reading and mathematics and four classes for teacher social skills ratings. There was not only a relationship between trajectories of inattention symptoms and academic impairment, but also a similarly strong association between trajectory classes of hyperactive-impulsive symptoms and achievement. Trajectory class membership correlated with socio-demographic and diagnostic characteristics, inattention and hyperactive-impulsive symptom trajectories, externalizing behavior in school, and treatment receipt and dosage. Although children with ADHD display substantial heterogeneity in their reading, math, and social skills growth trajectories, those with behavioral and socio-demographic disadvantages are especially likely to display severe levels of academic and social impairment over time. Evidence-based early screening and intervention that directly address academic and social impairments in elementary school-aged children with ADHD are warranted. The ClinicalTrials.gov identifier is NCT00000388.

  11. A Latent Class Analysis of Early Adolescent Peer and Dating Violence: Associations With Symptoms of Depression and Anxiety.

    Science.gov (United States)

    Garthe, Rachel C; Sullivan, Terri N; Behrhorst, Kathryn L

    2018-02-01

    Violence within peer and dating contexts is prevalent among early adolescents. Youth may be victims and/or aggressors and be involved in violence across multiple contexts, resulting in negative outcomes. This study identified patterns of perpetration and victimization for peer and dating violence, using a latent class analysis (LCA), and examined how different patterns of engaging in or experiencing violence among early adolescents were associated with symptoms of depression and anxiety. Participants included a sample of 508 racially and ethnically diverse youth (51% male) who had dated in the past 3 months. Youth were in the seventh grade within 37 schools and were primarily from economically disadvantaged communities across four sites in the United States. LCA identified three classes: (a) a low involvement in violence class, (b) a peer aggression and peer victimization class, and (c) a peer and dating violence class. Youth involved with multiple forms of violence displayed significantly higher levels of depressive and anxious symptoms than those with low involvement in violence. Study findings revealed the importance of understanding how peer and dating violence co-occur, and how different patterns of aggression and victimization were related to internalizing symptoms. Prevention efforts should address the intersection of victimization and perpetration in peer and dating contexts in potentially reducing internalizing symptoms among early adolescents.

  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

    of disease status (i.e., disease status is a latent variable). Statistical methods were introduced in this context by Hui and Walter and have been succesfully applied since then, with the majority of the work being carried out in a Bayesian framework. While STARD provides useful reporting guidelines...... 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...

  13. 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.

  14. 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.

  15. Pathological and non-pathological variants of restrictive eating behaviors in middle childhood: A latent class analysis.

    Science.gov (United States)

    Schmidt, Ricarda; Vogel, Mandy; Hiemisch, Andreas; Kiess, Wieland; Hilbert, Anja

    2018-08-01

    Although restrictive eating behaviors are very common during early childhood, their precise nature and clinical correlates remain unclear. Especially, there is little evidence on restrictive eating behaviors in older children and their associations with children's shape concern. The present population-based study sought to delineate subgroups of restrictive eating patterns in N = 799 7-14 year old children. Using Latent Class Analysis, children were classified based on six restrictive eating behaviors (for example, picky eating, food neophobia, and eating-related anxiety) and shape concern, separately in three age groups. For cluster validation, sociodemographic and objective anthropometric data, parental feeding practices, and general and eating disorder psychopathology were used. The results showed a 3-cluster solution across all age groups: an asymptomatic class (Cluster 1), a class with restrictive eating behaviors without shape concern (Cluster 2), and a class showing restrictive eating behaviors with prominent shape concern (Cluster 3). The clusters differed in all variables used for validation. Particularly, the proportion of children with symptoms of avoidant/restrictive food intake disorder was greater in Cluster 2 than Clusters 1 and 3. The study underlined the importance of considering shape concern to distinguish between different phenotypes of children's restrictive eating patterns. Longitudinal data are needed to evaluate the clusters' predictive effects on children's growth and development of clinical eating disorders. Copyright © 2018 Elsevier Ltd. All rights reserved.

  16. 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.

  17. A latent class analysis of substance use and culture among gay, bisexual and other men who have sex with men.

    Science.gov (United States)

    Card, Kiffer G; Armstrong, Heather L; Carter, Allison; Cui, Zishan; Wang, Lu; Zhu, Julia; Lachowsky, Nathan J; Moore, David M; Hogg, Robert S; Roth, Eric A

    2018-03-28

    Assessments of gay and bisexual men's substance use often obscures salient sociocultural and identity-related experiences related to how they use drugs. Latent class analysis was used to examine how patterns of substance use represent the social, economic and identity-related experiences of this population. Participants were sexually active gay and bisexual men (including other men who have sex with men), aged ≥ 16 years, living in Metro Vancouver (n = 774). LCA indicators included all substances used in the past six months self-reported by more than 30 men. Model selection was made with consideration to model parsimony, interpretability and optimisation of statistical criteria. Multinomial regression identified factors associated with class membership. A six-class solution was identified representing: 'assorted drug use' (4.5%); 'club drug use' (9.5%); 'street drug use' (12.1%); 'sex drug use' (11.4%); 'conventional drug use' (i.e. tobacco, alcohol, marijuana; 25.9%); and 'limited drug use' (36.7%). Factors associated with class membership included age, sexual orientation, annual income, occupation, income from drug sales, housing stability, group sex event participation, gay bars/clubs attendance, sensation seeking and escape motivation. These results highlight the need for programmes and policies that seek to lessen social disparities and account for social distinctions among this population.

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

    DEFF Research Database (Denmark)

    Nielsen, Anne Mølgaard

    questionnaire and the clinicians’ findings on a standardised examination of the low back. By using pattern recognition, subgroups of patients were identified within which their responses and scores are similar, and therefore the patients are more alike within the subgroups than across the subgroups. Latent......, the optimal application of the LCA method in this context is unknown and therefore, two methodological considerations were addressed during the process. Firstly, when using existing questionnaire data, whether using each single item or the summary scores would provide better subgroup information. Secondly...... the questionnaires was preferred, due to the more nuanced description available within the resulting subgroups. Therefore, the single‐item strategy was used in the subsequent single‐stage and two‐stage LCA, which identified seven and nine patient subgroups, respectively, with similar face validity and adequate...

  19. Co-development of Problem Gambling and Depression Symptoms in Emerging Adults: A Parallel-Process Latent Class Growth Model.

    Science.gov (United States)

    Edgerton, Jason D; Keough, Matthew T; Roberts, Lance W

    2018-02-21

    This study examines whether there are multiple joint trajectories of depression and problem gambling co-development in a sample of emerging adults. Data were from the Manitoba Longitudinal Study of Young Adults (n = 679), which was collected in 4 waves across 5 years (age 18-20 at baseline). Parallel process latent class growth modeling was used to identified 5 joint trajectory classes: low decreasing gambling, low increasing depression (81%); low stable gambling, moderate decreasing depression (9%); low stable gambling, high decreasing depression (5%); low stable gambling, moderate stable depression (3%); moderate stable problem gambling, no depression (2%). There was no evidence of reciprocal growth in problem gambling and depression in any of the joint classes. Multinomial logistic regression analyses of baseline risk and protective factors found that only neuroticism, escape-avoidance coping, and perceived level of family social support were significant predictors of joint trajectory class membership. Consistent with the pathways model framework, we observed that individuals in the problem gambling only class were more likely using gambling as a stable way to cope with negative emotions. Similarly, high levels of neuroticism and low levels of family support were associated with increased odds of being in a class with moderate to high levels of depressive symptoms (but low gambling problems). The results suggest that interventions for problem gambling and/or depression need to focus on promoting more adaptive coping skills among more "at-risk" young adults, and such interventions should be tailored in relation to specific subtypes of comorbid mental illness.

  20. 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.

  1. 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.

  2. 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...

  3. How does consumer knowledge affect environmentally sustainable choices? Evidence from a cross-country latent class analysis of food labels.

    Science.gov (United States)

    Peschel, Anne O; Grebitus, Carola; Steiner, Bodo; Veeman, Michele

    2016-11-01

    This paper examines consumers' knowledge and lifestyle profiles and preferences regarding two environmentally labeled food staples, potatoes and ground beef. Data from online choice experiments conducted in Canada and Germany are analyzed through latent class choice modeling to identify the influence of consumer knowledge (subjective and objective knowledge as well as usage experience) on environmentally sustainable choices. We find that irrespective of product or country under investigation, high subjective and objective knowledge levels drive environmentally sustainable food choices. Subjective knowledge was found to be more important in this context. Usage experience had relatively little impact on environmentally sustainable choices. Our results suggest that about 20% of consumers in both countries are ready to adopt footprint labels in their food choices. Another 10-20% could be targeted by enhancing subjective knowledge, for example through targeted marketing campaigns. Copyright © 2016 Elsevier Ltd. All rights reserved.

  4. A latent class analysis of social activities and health among community-dwelling older adults in Korea.

    Science.gov (United States)

    Park, Mi Jin; Park, Nan Sook; Chiriboga, David A

    2018-05-01

    This study presents an empirical typology of social activity and its association with the depressive symptoms and self-rated health of community-dwelling older adults (n = 464) in South Korea. Latent class analysis (LCA) was used to classify the types of social activities. Data analyses were conducted using Mplus 7.2 program for LCA and SPSS 22.0 for multiple regression analyses. LCA identified people who fell into one of the four activity groups: Diverse, Community Center/Disengaged, Religion Plus, and Friendship/Leisure. Membership in these four groups predicted differences in depressive symptoms and self-rated health. Results indicate that typologies of social activity could enhance practitioners' understanding of activity patterns and their associations with health and well-being.

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. Identification and Prediction of Latent Classes of Hikers Based on Specialization and Place Attachment

    Directory of Open Access Journals (Sweden)

    Hwasung Song

    2018-04-01

    Full Text Available The purpose of this study is to extend previous research by combining the specialization and place attachment concepts. Applying a latent profile analysis (LPA to data from hikers on the Olle Trail of Jeju Island in South Korea (N = 428, we classified hikers who share similar profiles based on multiple dimensions of specialization and place attachment, and examined correlates of the derived typologies for drawing managerial implications. We also explored associations between these typologies and outcome variables of hikers. LPA identified three subgroups: “novice” (38%, “affection-driven” (40%, and “expert” (22%. The findings indicated that these groups differed in their past experience and socio-demographic characteristics, such that the “affection-driven” and “expert” groups have more experience in the setting than the “novice” group. These typologies also showed significant associations with hikers’ satisfaction and revisit intention; thus, “novice” hikers tended to be less satisfied with their hiking and the setting. Furthermore, the “novice” group reported lower intention to revisit the setting. Our findings reveal that LPA can be a useful tool for identifying subgroups of individuals who have engaged in particular sets of strategies by incorporating multiple activity-place dimensions.

  10. Latent class analysis of need descriptors within an Irish youth mental health early intervention program toward a typology of need.

    Science.gov (United States)

    Peiper, Nicholas; Illback, Robert J; O'Reilly, Aileen; Clayton, Richard

    2017-02-01

    Significant overlap and comorbidity has been demonstrated among young people with mental health problems. This paper examined demographic characteristics, heterogeneity of need descriptors and services provided among young people (12-25 years) engaging in brief interventions at Jigsaw in the Republic of Ireland. Between 1 January 2013 and 31 December 2013, a total of 2571 young people sought help from 1 of 10 Jigsaw sites. Of these, 1247 engaged in goal-focused brief interventions, typically consisting of one to six face-to-face sessions. Descriptive statistics were used to summarize social and demographic factors. Latent class analysis was used to cluster young people into relevant typologies of presenting issues. Multinomial logistic regression was then performed to determine significant predictors of class membership. The most common age of young people was 16. More women (59.6%) than men engaged in brief interventions, 56% attended school, 74% lived with their family of origin or with one parent, and 54.2% came from families where parents were married. Using established fit criteria, four relevant typologies emerged: Developmental (26.8%), Comorbid (15.8%), Anxious (42.7%) and Externalising (14.6%). Predictors varied by class membership, but general family problems and lack of adult support emerged as the strongest predictors for all classes. This study demonstrated that the mental health needs of young people in Ireland are significant and diverse. Because Jigsaw favours a more descriptive approach to problem identification, the four typologies suggest a need to determine program capacity in engaging youth with heterogeneous presenting issues and to tailor brief interventions to each group's clinical profiles. © 2015 Wiley Publishing Asia Pty Ltd.

  11. Four Distinct Health Profiles in Older Patients With Cancer: Latent Class Analysis of the Prospective ELCAPA Cohort.

    Science.gov (United States)

    Ferrat, Emilie; Audureau, Etienne; Paillaud, Elena; Liuu, Evelyne; Tournigand, Christophe; Lagrange, Jean-Leon; Canoui-Poitrine, Florence; Caillet, Philippe; Bastuji-Garin, Sylvie

    2016-12-01

    Several studies have evaluated the independent prognostic value of impairments in single geriatric-assessment (GA) components in elderly cancer patients. None identified homogeneous subgroups. Our aims were to identify such subgroups based on combinations of GA components and to assess their associations with treatment decisions, admission, and death. We prospectively included 1,021 patients aged ≥70 years who had solid or hematologic malignancies and who underwent a GA in one of two French teaching hospitals. Two geriatricians independently selected candidate GA parameters for latent class analysis, which was then performed on the 821 cases without missing data. Age, gender, tumor site, metastatic status, and inpatient versus outpatient status were used as active covariates and predictors of class membership. Outcomes were cancer treatment decisions, overall 1-year mortality, and 6-month unscheduled admissions. Sensitivity analyses were performed on the overall population of 1,021 patients and on 375 newly enrolled patients. We identified four classes: relatively healthy (LC1, 28%), malnourished (LC2, 36%), cognitive and mood impaired (LC3, 15%), and globally impaired (LC4, 21%). Tumor site, metastatic status, age, and in/outpatient status independently predicted class membership (p LC4 was associated with 1-year mortality and palliative treatment compared to LC2 and LC3 (p ≤ .05). We identified four health profiles that may help physicians select cancer treatments and geriatric interventions. Researchers may find these profiles useful for stratifying patients in clinical trials. © The Author 2016. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  12. Using hybrid latent class model for city-HUBs´users behaviour analysis

    OpenAIRE

    Di Ciommo, Floridea; Monzón de Cáceres, Andrés; Oña, Rocío de; Oña López, Juan de; Hernández del Olmo, Sara

    2014-01-01

    Data from an attitudinal survey and stated preference ranking experiment conducted in two urban European interchanges (i.e. City-HUBs) in Madrid (Spain) and Thessaloniki (Greece) show that the importance that City-HUBs users attach to the intermodal infrastructure varies strongly as a function of their perceptions of time spent in the interchange (i.e.intermodal transfer and waiting time). A principal components analysis allocates respondents (i.e. city-HUB users) to two classes with substant...

  13. Courses of helping alliance in the treatment of people with severe mental illness in Europe: a latent class analytic approach.

    Science.gov (United States)

    Loos, Sabine; Arnold, Katrin; Slade, Mike; Jordan, Harriet; Del Vecchio, Valeria; Sampogna, Gaia; Süveges, Ágnes; Nagy, Marietta; Krogsgaard Bording, Malene; Østermark Sørensen, Helle; Rössler, Wulf; Kawohl, Wolfram; Puschner, Bernd

    2015-03-01

    The helping alliance (HA) between patient and therapist has been studied in detail in psychotherapy research, but less is known about the HA in long-term community mental health care. The aim of this study was to identify typical courses of the HA and their predictors in a sample of people with severe mental illness across Europe over a measurement period of one year. Self-ratings of the HA by 588 people with severe mental illness who participated in a multicentre European study (CEDAR; ISRCTN75841675) were examined using latent class analysis. Four main patterns of alliance were identified: (1) high and stable (HS, 45.6 %), (2) high and increasing (HI, 36.9 %), (3) high and decreasing (HD, 11.3 %) and (4) low and increasing (LI, 6.1 %). Predictors of class membership were duration of illness, ethnicity, and education, receipt of state benefits, recovery, and quality of life. Results support findings from psychotherapy research about a predominantly stable course of the helping alliance in patients with severe mental illness over time. Implications for research and practice indicate to turn the attention to subgroups with noticeable courses.

  14. Identification of subgroups of inflammatory and degenerative MRI findings in the spine and sacroiliac joints: a latent class analysis of 1037 patients with persistent low back pain

    DEFF Research Database (Denmark)

    Arnbak, Bodil; Jensen, Rikke Krüger; Manniche, Claus

    2016-01-01

    BACKGROUND: The aim of this study was to investigate subgroups of magnetic resonance imaging (MRI) findings for the spine and sacroiliac joints (SIJs) using latent class analysis (LCA), and to investigate whether these subgroups differ in their demographic and clinical characteristics. METHODS...

  15. Multilevel Latent Class Analysis for Large-Scale Educational Assessment Data: Exploring the Relation between the Curriculum and Students' Mathematical Strategies

    Science.gov (United States)

    Fagginger Auer, Marije F.; Hickendorff, Marian; Van Putten, Cornelis M.; Béguin, Anton A.; Heiser, Willem J.

    2016-01-01

    A first application of multilevel latent class analysis (MLCA) to educational large-scale assessment data is demonstrated. This statistical technique addresses several of the challenges that assessment data offers. Importantly, MLCA allows modeling of the often ignored teacher effects and of the joint influence of teacher and student variables.…

  16. Latent Class Analysis of HIV Risk Behaviors Among Russian Women at Risk for Alcohol-Exposed Pregnancies.

    Science.gov (United States)

    Bohora, Som; Chaffin, Mark; Shaboltas, Alla; Bonner, Barbara; Isurina, Galina; Batluk, Julia; Bard, David; Tsvetkova, Larissa; Skitnevskaya, Larissa; Volkova, Elena; Balachova, Tatiana

    2017-11-01

    The number of HIV cases attributed to heterosexual contact and the proportion of women among HIV positive individuals has increased worldwide. Russia is a country with the highest rates of newly diagnosed HIV infections in the region, and the infection spreads beyond traditional risk groups. While young women are affected disproportionately, knowledge of HIV risk behaviors in women in the general population remains limited. The objectives of this study were to identify patterns of behaviors that place women of childbearing age at high risk for HIV transmission and determine whether socio-demographic characteristics and alcohol use are predictive of the risk pattern. A total of 708 non-pregnant women, aged between 18 and 44 years, who were at risk for an alcohol-exposed pregnancy were enrolled in two regions in Russia. Participants completed a structured interview focused on HIV risk behaviors, including risky sexual behavior and alcohol and drug use. Latent class analysis was utilized to examine associations between HIV risk and other demographic and alcohol use characteristics and to identify patterns of risk among women. Three classes were identified. 34.93% of participants were at high risk, combining their risk behaviors, e.g., having multiple sexual partners, with high partner's risk associated with partner's drug use (class I). Despite reporting self-perceived risk for HIV/STI, this class of participants was unlikely to utilize adequate protection (i.e., condom use). The second high risk class included 13.19% of participants who combined their risky sexual behaviors, i.e., multiple sexual partners and having STDs, with partner's risk that included partner's imprisonment and partner's sex with other women (class II). Participants in this class were likely to utilize protection/condoms. Finally, 51.88% of participants were at lower risk, which was associated primarily with their partners' risk, and these participants utilized protection (class III). The odds

  17. Evidence of the dissociative PTSD subtype: A systematic literature review of latent class and profile analytic studies of PTSD.

    Science.gov (United States)

    Hansen, Maj; Ross, Jana; Armour, Cherie

    2017-04-15

    The dissociative PTSD (D-PTSD) subtype was first introduced into the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) in 2013. Prior to this, studies using latent profile analysis (LPA) or latent class analysis (LCA), began to provide support for the D-PTSD construct and associated risk factors. This research is important, because dissociative symptoms in the context of PTSD may potentially interfere with treatment course or outcome. The aims of the present study were twofold: to systematically review the LCA and LPA studies investigating support for the D-PTSD construct; and to review the associated research on the risk factors or covariates of D-PTSD in the identified studies. Six databases (PubMed, Web of Science, Scopus, PILOTS, PsychInfo, and Embase) were systematically searched for relevant papers. Eleven studies were included in the present review. The majority of the studies were supportive of the D-PTSD subtype; primarily characterized by depersonalization and derealization. Several covariates of the D-PTSD subtype have been investigated with mixed results. Many limitations relate to the state of the current literature, including a small number of studies, the use of self-report measurements of PTSD, and heterogeneity across the samples in investigated covariates. The results were overall supportive of the D-PTSD construct. Future research on D-PTSD and associated risk factors is needed to shed light on the possibilities of facilitating preventive actions, screening, and implications on treatment effects. Copyright © 2017 Elsevier B.V. All rights reserved.

  18. 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

  19. A personality-based latent class typology of outpatients with major depressive disorder: association with symptomatology, prescription pattern and social function.

    Science.gov (United States)

    Hori, Hiroaki; Teraishi, Toshiya; Nagashima, Anna; Koga, Norie; Ota, Miho; Hattori, Kotaro; Kim, Yoshiharu; Higuchi, Teruhiko; Kunugi, Hiroshi

    2017-08-01

    While major depressive disorder (MDD) is considered to be a heterogeneous disorder, the nature of the heterogeneity remains unclear. Studies have attempted to classify patients with MDD using latent variable techniques, yet the empirical approaches to symptom-based subtyping of MDD have not provided conclusive evidence. Here we aimed to identify homogeneous classes of MDD based on personality traits, using a latent profile analysis. We studied 238 outpatients with DSM-IV MDD recruited from our specialized depression outpatient clinic and assessed their dimensional personality traits with the Temperament and Character Inventory. Latent profile analysis was conducted with 7 dimensions of the Temperament and Character Inventory as indicators. Relationships of the identified classes with symptomatology, prescription pattern, and social function were then examined. The latent profile analysis indicated that a 3-class solution best fit the data. Of the sample, 46.2% was classified into a "neurotic" group characterized by high harm avoidance and low self-directedness; 30.3% into an "adaptive" group characterized by high self-directedness and cooperativeness; and 23.5% into a "socially-detached" group characterized by low reward dependence and cooperativeness and high self-transcendence. The 2 maladaptive groups, namely neurotic and socially-detached groups, demonstrated unique patterns of symptom expression, different classes of psychotropic medication use, and lower social functioning. Generalizability of the findings was limited since our patients were recruited from the specialized depression outpatient clinic. Our personality-based latent profile analysis identified clinically meaningful 3 MDD groups that were markedly different in their personality profiles associated with distinct symptomatology and functioning. Copyright © 2017 Elsevier B.V. All rights reserved.

  20. Maternal eating disorder and infant diet. A latent class analysis based on the Norwegian Mother and Child Cohort Study (MoBa).

    Science.gov (United States)

    Torgersen, Leila; Ystrom, Eivind; Siega-Riz, Anna Maria; Berg, Cecilie Knoph; Zerwas, Stephanie C; Reichborn-Kjennerud, Ted; Bulik, Cynthia M

    2015-01-01

    Knowledge of infant diet and feeding practices among children of mothers with eating disorders is essential to promote healthy eating in these children. This study compared the dietary patterns of 6-month-old children of mothers with anorexia nervosa, bulimia nervosa, binge eating disorder, and eating disorder not otherwise specified-purging subtype, to the diet of children of mothers with no eating disorders (reference group). The study was based on 53,879 mothers in the Norwegian Mother and Child Cohort Study (MoBa). Latent class analysis (LCA) was used to identify discrete latent classes of infant diet based on the mothers' responses to questions about 16 food items. LCA identified five classes, characterized by primarily homemade vegetarian food (4% of infants), homemade traditional food (8%), commercial cereals (35%), commercial jarred baby food (39%), and a mix of all food groups (11%). The association between latent dietary classes and maternal eating disorders were estimated by multinomial logistic regression. Infants of mothers with bulimia nervosa had a lower probability of being in the homemade traditional food class compared to the commercial jarred baby food class, than the referent (O.R. 0.59; 95% CI 0.36-0.99). Infants of mothers with binge eating disorder had a lower probability of being in the homemade vegetarian class compared to the commercial jarred baby food class (O.R. 0.77; 95% CI 0.60-0.99), but only before adjusting for relevant confounders. Anorexia nervosa and eating disorder not otherwise specified-purging subtype were not statistically significantly associated with any of the dietary classes. These results suggest that maternal eating disorders may to some extent influence the child's diet at 6 months; however, the extent to which these differences influence child health and development remains an area for further inquiry. Copyright © 2014 Elsevier Ltd. All rights reserved.

  1. 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.

  2. 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.

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

    DEFF Research Database (Denmark)

    Wibaek, Rasmus; Kæstel, Pernille; Girma, Tsinuel

    to identify infants with distinct fat mass (FM) and fat-free mass (FFM) trajectories from 0-6 months of age and examined associations with BP at 4 years of age. Material and methods: Air displacement plethysmography was used to measure body composition monthly from birth to 6 months of age in 364 Ethiopian...... 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....... Results: We identified four distinct FM and two distinct FFM growth trajectories (figure 1). Overall mean (SD) systolic BP (SBP) was 87.4 (6.8) mmHg and diastolic BP (DBP) was 52.9 (8.3) mmHg at 4 years of age. Compared to the "High intermediate FM" reference group, infants in the "Accelerated FM" group...

  4. A latent class analysis of friendship network types and their predictors in the second half of life.

    Science.gov (United States)

    Miche, Martina; Huxhold, Oliver; Stevens, Nan L

    2013-07-01

    Friendships contribute uniquely to well-being in (late) adulthood. However, studies on friendship often ignore interindividual differences in friendship patterns. The aim of this study was to investigate such differences including their predictors. The study builds on Matthews's qualitative model of friendship styles. Matthews distinguished 3 approaches to friendship differing by number of friends, duration of friendships, and emotional closeness. We used latent class analysis to identify friendship network types in a sample of middle-aged and older adults aged 40-85 years (N = 1,876). Data came from the German Aging Survey (DEAS). Our analysis revealed 4 distinct friendship network types that were in high congruence with Matthews's typology. We identified these as a discerning style, which focuses on few close relationships, an independent style, which refrains from close engagements, and 2 acquisitive styles that both acquire new friends across their whole life course but differ regarding the emotional closeness of their friendships. Socioeconomic status, gender, health, and network-disturbing and network-sustaining variables predicted affiliations with network types. We argue that future studies should consider a holistic view of friendships in order to better understand the association between friendships and well-being in the second half of life.

  5. Two-year trajectory of fall risk in people with Parkinson’s disease: a latent class analysis

    Science.gov (United States)

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

    2015-01-01

    Objective To examine fall risk trajectories occurring naturally in a sample of individuals with early to middle stage Parkinson’s disease (PD). Design Latent class analysis, specifically growth mixture modeling (GMM) of longitudinal fall risk trajectories. Setting Not applicable. Participants 230 community-dwelling PD participants of a longitudinal cohort study who attended at least two of five assessments over a two year period. Interventions Not applicable. Main Outcome Measures Fall risk trajectory (low, medium or high risk) and stability of fall risk trajectory (stable or fluctuating). Fall risk was determined at 6-monthly intervals using a simple clinical tool based on fall history, freezing of gait, and gait speed. Results The GMM optimally grouped participants into three fall risk trajectories that closely mirrored baseline fall risk status (p=.001). The high fall risk trajectory was most common (42.6%) and included participants with longer and more severe disease and with higher postural instability and gait disability (PIGD) scores than the low and medium risk trajectories (pfall risk (posterior probability fall risk trajectories over two years. Further investigation is required to determine whether interventions to improve gait and balance may improve fall risk trajectories in people with PD. PMID:26606871

  6. 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.

  7. A latent class growth analysis of school bullying and its social context: the self-determination theory perspective.

    Science.gov (United States)

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

    2015-03-01

    The contribution of social context to school bullying was examined from the self-determination theory perspective in this longitudinal study of 536 adolescents from 3 secondary schools in Hong Kong. Latent class growth analysis of the student-reported data at 5 time points from grade 7 to grade 9 identified 4 groups of students: bullies (9.8%), victims (3.0%), bully-victims (9.4%), and typical students (77.8%). There was a significant association between academic tracking and group membership. Students from the school with the lowest academic performance had a greater chance of being victims and bully-victims. Longitudinal data showed that all 4 groups tended to report less victimization over the years. The victims and the typical students also had a tendency to report less bullying over the years, but this tendency was reversed for bullies and bully-victims. Perceived support from teachers for relatedness significantly predicted membership of the groups of bullies and victims. Students with higher perceived support for relatedness from their teachers had a significantly lower likelihood of being bullies or victims. The findings have implications for the theory and practice of preventive interventions in school bullying.

  8. Differential factors associated with challenge-proven food allergy phenotypes in a population cohort of infants: a latent class analysis.

    Science.gov (United States)

    Peters, R L; Allen, K J; Dharmage, S C; Lodge, C J; Koplin, J J; Ponsonby, A-L; Wake, M; Lowe, A J; Tang, M L K; Matheson, M C; Gurrin, L C

    2015-05-01

    Food allergy, eczema and wheeze are early manifestations of allergic disease and commonly co-occur in infancy although their interrelationship is not well understood. Data from population studies are essential to determine whether there are differential drivers of multi-allergy phenotypes. We aimed to define phenotypes and risk factors of allergic disease using latent class analysis (LCA). The HealthNuts study is a prospective, population-based cohort of 5276 12-month-old infants in Melbourne, Australia. LCA was performed using the following baseline data collected at age 12 months: food sensitization (skin prick test ≥ 2 mm) and allergy (oral food challenge) to egg, peanut and sesame; early (food-sensitized eczema (16%), single egg allergy (9%), multiple food allergies (predominantly peanut) (3%) and multiple food allergies (predominantly egg) (2%). Compared to the baseline group of no allergic disease, shared risk factors for all allergic phenotypes were parents born overseas (particularly Asia), delayed introduction of egg, male gender (except for single egg allergy) and family history of allergic disease, whilst exposure to pet dogs was protective for all phenotypes. Other factors including filaggrin mutations, vitamin D and the presence of older siblings differed by phenotype. Multiple outcomes in infancy can be used to determine five distinct allergy phenotypes at the population level, which have both shared and separate risk factors suggesting differential mechanisms of disease. © 2014 John Wiley & Sons Ltd.

  9. An Estimation of a Nonlinear Dynamic Process Using Latent Class Extended Mixed Models: Affect Profiles After Terrorist Attacks.

    Science.gov (United States)

    Burro, Roberto; Raccanello, Daniela; Pasini, Margherita; Brondino, Margherita

    2018-01-01

    Conceptualizing affect as a complex nonlinear dynamic process, we used latent class extended mixed models (LCMM) to understand whether there were unobserved groupings in a dataset including longitudinal measures. Our aim was to identify affect profiles over time in people vicariously exposed to terrorism, studying their relations with personality traits. The participants were 193 university students who completed online measures of affect during the seven days following two terrorist attacks (Paris, November 13, 2015; Brussels, March 22, 2016); Big Five personality traits; and antecedents of affect. After selecting students whose negative affect was influenced by the two attacks (33%), we analysed the data with the LCMM package of R. We identified two affect profiles, characterized by different trends over time: The first profile comprised students with lower positive affect and higher negative affect compared to the second profile. Concerning personality traits, conscientious-ness was lower for the first profile compared to the second profile, and vice versa for neuroticism. Findings are discussed for both their theoretical and applied relevance.

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

    Science.gov (United States)

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

    2018-01-01

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

  11. 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

  12. Vulnerability Factors in the Middle Class: Evidence for Argentina and Mexico after the Crisis of the 1990s

    OpenAIRE

    Galassi, Gabriela Liliana; González, Leandro Mariano

    2012-01-01

    This paper explores the profile of the Argentinean and Mexican middle classes during the most recent crisis in both countries. It combines the perspectives of social vulnerability and class analysis theoretically underlying a "matrix of vulnerability and social classes." The analysis used household surveys in Argentina for 1998 and 2003 and those in Mexico for 1994 and 1996. The results show that whereas the Mexican middle class was primarily affected during the "Tequila crisis" through its p...

  13. Qualitative and quantitative aspects of information processing in first psychosis: latent class analyses in patients, at-risk subjects, and controls.

    Science.gov (United States)

    van Tricht, Mirjam J; Bour, Lo J; Koelman, Johannes H T M; Derks, Eske M; Braff, David L; de Wilde, Odette M; Boerée, Thijs; Linszen, Don H; de Haan, Lieuwe; Nieman, Dorien H

    2015-04-01

    We aimed to determine profiles of information processing deficits in the pathway to first psychosis. Sixty-one subjects at ultrahigh risk (UHR) for psychosis were assessed, of whom 18 converted to a first episode of psychosis (FEP) within the follow-up period. Additionally, 47 FEP and 30 control subjects were included. Using 10 neurophysiological parameters associated with information processing, latent class analyses yielded three classes at baseline. Class membership was related to group status. Within the UHR sample, two classes were found. Transition to psychosis was nominally associated with class membership. Neurophysiological profiles were unstable over time, but associations between specific neurophysiological components at baseline and follow-up were found. We conclude that certain constellations of neurophysiological variables aid in the differentiation between controls and patients in the prodrome and after first psychosis. Copyright © 2014 Society for Psychophysiological Research.

  14. How does consumer knowledge affect environmentally sustainable choices?:Evidence from a cross-country latent class analysis of food labels

    OpenAIRE

    Peschel, Anne O; Grebitus, Carola; Steiner, Bodo; Veeman, Michele

    2016-01-01

    This paper examines consumers' knowledge and lifestyle profiles and preferences regarding two environmentally labelled food staples, potatoes and ground beef. Data from online choice experiments conducted in Canada and Germany are analyzed through latent class choice modelling to identify the influence of consumer knowledge (subjective and objective knowledge as well as usage experience) on environmentally sustainable choices. We find that irrespective of product or country under investigatio...

  15. 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.

  16. 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.

  17. Identifying and predicting subgroups of information needs among cancer patients: an initial study using latent class analysis.

    Science.gov (United States)

    Neumann, Melanie; Wirtz, Markus; Ernstmann, Nicole; Ommen, Oliver; Längler, Alfred; Edelhäuser, Friedrich; Scheffer, Christian; Tauschel, Diethard; Pfaff, Holger

    2011-08-01

    Understanding how the information needs of cancer patients (CaPts) vary is important because met information needs affect health outcomes and CaPts' satisfaction. The goals of the study were to identify subgroups of CaPts based on self-reported cancer- and treatment-related information needs and to determine whether subgroups could be predicted on the basis of selected sociodemographic, clinical and clinician-patient relationship variables. Three hundred twenty-three CaPts participated in a survey using the "Cancer Patients Information Needs" scale, which is a new tool for measuring cancer-related information needs. The number of information need subgroups and need profiles within each subgroup was identified using latent class analysis (LCA). Multinomial logistic regression was applied to predict class membership. LCA identified a model of five subgroups exhibiting differences in type and extent of CaPts' unmet information needs: a subgroup with "no unmet needs" (31.4% of the sample), two subgroups with "high level of psychosocial unmet information needs" (27.0% and 12.0%), a subgroup with "high level of purely medical unmet information needs" (16.0%) and a subgroup with "high level of medical and psychosocial unmet information needs" (13.6%). An assessment of sociodemographic and clinical characteristics revealed that younger CaPts and CaPts' requiring psychological support seem to belong to subgroups with a higher level of unmet information needs. However, the most significant predictor for the subgroups with unmet information needs is a good clinician-patient relationship, i.e. subjective perception of high level of trust in and caring attention from nurses together with high degree of physician empathy seems to be predictive for inclusion in the subgroup with no unmet information needs. The results of our study can be used by oncology nurses and physicians to increase their awareness of the complexity and heterogeneity of information needs among CaPts and of

  18. 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

  19. Mexico.

    Science.gov (United States)

    Semaan, Leslie

    The text explores Mexico's history, geography, art, religion, and lifestyles in the context of its complex economy. The text focuses on Mexico's economy and reasons for its current situation. Part I of this teaching unit includes: Teacher Overview, Why Study Mexico, Mexico Fact Sheet, Map of Mexico, the Land and Climate, History, Government,…

  20. 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, C; Stigler, M; Lust, K; Laska, M

    2016-01-01

    Little is known about the complex patterning of weight-related health behaviors in 2- and 4-year college students. The objective of this study was to identify and describe unique classes of weight-related health behaviors among college youth. Latent class analysis was used to identify homogenous, mutually exclusive classes of nine health behaviors which 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 5 and 4 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. PMID:24990599

  1. 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

  2. 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

  3. A Three-Step Latent Class Analysis to Identify How Different Patterns of Teen Dating Violence and Psychosocial Factors Influence Mental Health.

    Science.gov (United States)

    Choi, Hye Jeong; Weston, Rebecca; Temple, Jeff R

    2017-04-01

    Although multiple forms (i.e., physical, threatening, psychological, sexual, and relational abuse) and patterns (i.e., perpetration and victimization) of violence can co-occur, most existing research examines these experiences individually. Thus, the purpose of this study is to investigate: (1) homogenous subgroups based on victimization and perpetration of multiple forms of teen dating violence; (2) predictors of membership in these subgroups; and (3) mental health consequences associated with membership in each subgroup. Nine hundred eighteen adolescents in the 9 th or 10 th grade at seven public high schools in 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.

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

    Directory of Open Access Journals (Sweden)

    Dimitrios Stamovlasis

    2018-04-01

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

  5. 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.

  6. 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.

  7. 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. Utilizing a sample of 12- to 14-year-old adolescents (N = 4,743) from the 1997 National Longitudinal Survey of Youth (NLSY97), results identified a four-class model of maternal responsiveness and autonomy-granting: low responsiveness/high autonomy-granting, moderate responsiveness/moderate autonomy-granting, high responsiveness/low autonomy-granting, high responsiveness/moderate autonomy-granting. Membership in the low responsiveness/high autonomy-granting class predicted greater sexual risk-taking in mid- and late-adolescence compared to all other classes, and membership in the high responsiveness/ moderate autonomy-granting class predicted lower sexual risk-taking. Gender and ethnic differences in responsiveness and autonomy-granting class membership were also found, potentially informing gender and ethnic disparities of adolescent sexual risk-taking. PMID:23828712

  8. On the Estimation of Disease Prevalence by Latent Class Models for Screening Studies Using Two Screening Tests with Categorical Disease Status Verified in Test Positives Only

    Science.gov (United States)

    Chu, Haitao; Zhou, Yijie; Cole, Stephen R.; Ibrahim, Joseph G.

    2010-01-01

    Summary To evaluate the probabilities of a disease state, ideally all subjects in a study should be diagnosed by a definitive diagnostic or gold standard test. However, since definitive diagnostic tests are often invasive and expensive, it is generally unethical to apply them to subjects whose screening tests are negative. In this article, we consider latent class models for screening studies with two imperfect binary diagnostic tests and a definitive categorical disease status measured only for those with at least one positive screening test. Specifically, we discuss a conditional independent and three homogeneous conditional dependent latent class models and assess the impact of misspecification of the dependence structure on the estimation of disease category probabilities using frequentist and Bayesian approaches. Interestingly, the three homogeneous dependent models can provide identical goodness-of-fit but substantively different estimates for a given study. However, the parametric form of the assumed dependence structure itself is not “testable” from the data, and thus the dependence structure modeling considered here can only be viewed as a sensitivity analysis concerning a more complicated non-identifiable model potentially involving heterogeneous dependence structure. Furthermore, we discuss Bayesian model averaging together with its limitations as an alternative way to partially address this particularly challenging problem. The methods are applied to two cancer screening studies, and simulations are conducted to evaluate the performance of these methods. In summary, further research is needed to reduce the impact of model misspecification on the estimation of disease prevalence in such settings. PMID:20191614

  9. 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

  10. 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.

  11. When addiction symptoms and life problems diverge: a latent class analysis of problematic gaming in a representative multinational sample of European adolescents.

    Science.gov (United States)

    Colder Carras, Michelle; Kardefelt-Winther, Daniel

    2018-04-01

    The proposed diagnosis of Internet gaming disorder (IGD) in DSM-5 has been criticized for "borrowing" criteria related to substance addiction, as this might result in misclassifying highly involved gamers as having a disorder. In this paper, we took a person-centered statistical approach to group adolescent gamers by levels of addiction-related symptoms and gaming-related problems, compared these groups to traditional scale scores for IGD, and checked how groups were related to psychosocial well-being using a preregistered analysis plan. We performed latent class analysis and regression with items from IGD and psychosocial well-being scales in a representative sample of 7865 adolescent European gamers. Symptoms and problems matched in only two groups: an IGD class (2.2%) having a high level of symptoms and problems and a Normative class (63.5%) having low levels of symptoms and problems. We also identified two classes comprising 30.9% of our sample that would be misclassified based on their report of gaming-related problems: an Engaged class (7.3%) that seemed to correspond to the engaged gamers described in previous literature, and a Concerned class (23.6%) reporting few symptoms but moderate to high levels of problems. Our findings suggest that a reformulation of IGD is needed. Treating Engaged gamers as having IGD when their poor well-being might not be gaming related may delay appropriate treatment, while Concerned gamers may need help to reduce gaming but would not be identified as such. Additional work to describe the phenomenology of these two groups would help refine diagnosis, prevention and treatment for IGD.

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

    Science.gov (United States)

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

    2015-09-25

    This study is one part of a five-year tobacco-control project in China, which aimed to gain insight into the smoking behavior, knowledge, and attitudes among medical teachers in China. In May 2010, a cross-sectional survey was conducted among medical teachers of Xiangya Medical School, Central South University, China. A total number of 682 medical teachers completed the surveys. Latent class analysis indicated the sample of smoking patterns was best represented by three latent subgroups of smoking consumption severity levels. Most respondents were informed of smoking related knowledge, but lack of knowledge on smoking cessation. Most of them held a supportive attitude towards their responsibilities among tobacco control, as well as the social significance of smoking. However, both smoking related knowledge and attitude were not correlated with severity of smoking consumption among medical teachers. The smoking prevalence among medical teachers in China remains high. Programs on smoking cessation training are required. Future study should also develop targeted interventions for subgroups of smokers based on smoking consumption. Persistent and effective anti-tobacco efforts are needed to achieve the goals of creating smoke-free campuses and hospitals.

  13. 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.

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

    DEFF Research Database (Denmark)

    Matt, Monika; Nordentoft, Steen; Ian, Kopacka

    2016-01-01

    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....... 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 [0.85-0.98]). In our study, PCR detection on boot sock samples is more sensitive than conventional culture. In view...

  15. Latent class analysis of real time qPCR and bacteriological culturing for the diagnosis of Streptococcus agalactiae in cow composite milk samples

    DEFF Research Database (Denmark)

    Holmøy, Ingrid H.; Toft, Nils; Jørgensen, Hannah J.

    2018-01-01

    Streptococcus agalactiae (S. agalactiae) has re-emerged as a mastitis pathogen among Norwegian dairy cows. The Norwegian cattle health services recommend that infected herds implement measures to eradicate S. agalactiae, this includes a screening of milk samples from all lactating cows....... The performance of the qPCR-test currently in use for this purpose has not been evaluated under field conditions. The objective of this study was to estimate the sensitivity and specificity of the real-time qPCR assay in use in Norway (Mastitis 4 qPCR, DNA Diagnostics A/S, Risskov, Denmark) and compare...... it to conventional bacteriological culturing for detection of S. agalactiae in milk samples. Because none of these tests are considered a perfect reference test, the evaluation was performed using latent class models in a Bayesian analysis. Aseptically collected cow-composite milk samples from 578 cows belonging...

  16. The association between subgroups of MRI findings identified with latent class analysis and low back pain in 40-year-old Danes

    DEFF Research Database (Denmark)

    Jensen, Rikke K; Kent, Peter; Jensen, Tue S

    2018-01-01

    for identifying latent classes (subgroups) of MRI findings within multivariable datasets. The purpose of this study was to investigate the association between subgroups of MRI findings and the presence of LBP in people from the general population. METHODS: To identify subgroups of lumbar MRI findings...... regression. RESULTS: Six subgroups were identified in the clinical dataset and the data from the general population cohort fitted the subgroups well, with a median posterior probability of 93%-100%. These six subgroups described two pathways of increasing degeneration on upper (L1-L3) and lower (L4-L5......) lumbar levels. An association with LBP was found for the subgroups describing severe and multiple degenerative MRI findings at the lower lumbar levels but none of the other subgroups were associated with LBP. CONCLUSION: Although MRI findings are common in asymptomatic people and the association between...

  17. 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

    Considerable effort has been devoted to improving the existing diagnostic tests for bovine tuberculosis (single intradermal comparative tuberculin test [SICTT] and ¿-interferon assay [¿-IFN]) and to develop new tests. Previously, the diagnostic characteristics (sensitivity, specificity) have been...... 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...... immunoassay [Enferplex-TB]) diagnostic tests under Irish field conditions where true disease status was unknown. The study population consisted of herds recruited in areas with no known TB problems (2197 animals) and herds experiencing a confirmed TB breakdown (2740 animals). A Bayesian model was developed...

  18. Novel approach to characterising individuals with low back-related leg pain: cluster identification with latent class analysis and 12-month follow-up.

    Science.gov (United States)

    Stynes, Siobhán; Konstantinou, Kika; Ogollah, Reuben; Hay, Elaine M; Dunn, Kate M

    2018-04-01

    Traditionally, low back-related leg pain (LBLP) is diagnosed clinically as referred leg pain or sciatica (nerve root involvement). However, within the spectrum of LBLP, we hypothesised that there may be other unrecognised patient subgroups. This study aimed to identify clusters of patients with LBLP using latent class analysis and describe their clinical course. The study population was 609 LBLP primary care consulters. Variables from clinical assessment were included in the latent class analysis. Characteristics of the statistically identified clusters were compared, and their clinical course over 1 year was described. A 5 cluster solution was optimal. Cluster 1 (n = 104) had mild leg pain severity and was considered to represent a referred leg pain group with no clinical signs, suggesting nerve root involvement (sciatica). Cluster 2 (n = 122), cluster 3 (n = 188), and cluster 4 (n = 69) had mild, moderate, and severe pain and disability, respectively, and response to clinical assessment items suggested categories of mild, moderate, and severe sciatica. Cluster 5 (n = 126) had high pain and disability, longer pain duration, and more comorbidities and was difficult to map to a clinical diagnosis. Most improvement for pain and disability was seen in the first 4 months for all clusters. At 12 months, the proportion of patients reporting recovery ranged from 27% for cluster 5 to 45% for cluster 2 (mild sciatica). This is the first study that empirically shows the variability in profile and clinical course of patients with LBLP including sciatica. More homogenous groups were identified, which could be considered in future clinical and research settings.

  19. A Latent Class Analysis of Gambling Activity Patterns in a Canadian University Sample of Emerging Adults: Socio-demographic, Motivational, and Mental Health Correlates.

    Science.gov (United States)

    Sanscartier, Matthew D; Edgerton, Jason D; Roberts, Lance W

    2017-12-02

    This analysis of gambling habits of Canadian university students (ages 18-25) dovetails two recent developments in the field of gambling studies. First, the popularity of latent class analysis to identify heterogeneous classes of gambling patterns in different populations; second, the validation of the Gambling Motives Questionnaire (with financial motives) among university students-specifically to understand both how and why emerging adults gamble. Our results support a four-class model of gambling activity patterns, consisting of female-preponderant casual and chance-based gambling groups, and male-preponderant skill-based and extensive gambling groups. Each class shows a specific combination of motives, underscoring the necessity for nuanced responses to problem gambling among emerging adults. More specifically, gambling for the skill-based group appears primarily to be a source of thrill and a way to cope; for the chance-based group, gambling appears but one symptom of a set of wider issues involving depression, anxiety, substance use, and low self-esteem; while extensive gamblers seem to seek excitement, sociality, and coping, in that order. Only the chance-based group was significantly more likely than casual gamblers to be motivated by financial reasons. Situating our analysis in the literature, we suggest that interventions for the predominantly male subtypes should address gambling directly (e.g. re-focusing excitement seeking into other activities, instilling more productive coping mechanisms) while interventions for predominantly female subtypes should address low self-esteem in conjunction with depression, substance abuse, and problematic levels of gambling. We conclude future research should focus on links between self-esteem, depression, substance abuse, and financial motives for gambling among female emerging adults.

  20. 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.

  1. 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®.

  2. Latent class analysis of real time qPCR and bacteriological culturing for the diagnosis of Streptococcus agalactiae in cow composite milk samples.

    Science.gov (United States)

    Holmøy, Ingrid H; Toft, Nils; Jørgensen, Hannah J; Mørk, Tormod; Sølverød, Liv; Nødtvedt, Ane

    2018-06-01

    Streptococcus agalactiae (S. agalactiae) has re-emerged as a mastitis pathogen among Norwegian dairy cows. The Norwegian cattle health services recommend that infected herds implement measures to eradicate S. agalactiae, this includes a screening of milk samples from all lactating cows. The performance of the qPCR-test currently in use for this purpose has not been evaluated under field conditions. The objective of this study was to estimate the sensitivity and specificity of the real-time qPCR assay in use in Norway (Mastitis 4 qPCR, DNA Diagnostics A/S, Risskov, Denmark) and compare it to conventional bacteriological culturing for detection of S. agalactiae in milk samples. Because none of these tests are considered a perfect reference test, the evaluation was performed using latent class models in a Bayesian analysis. Aseptically collected cow-composite milk samples from 578 cows belonging to 6 herds were cultured and tested by qPCR. While 37 (6.4%) samples were positive for S. agalactiae by bacteriological culture, 66 (11.4%) samples were positive by qPCR. The within-herd prevalence in the six herds, as estimated by the latent class models ranged from 7.7 to 50.8%. At the recommended cut-off (cycle threshold 37), the sensitivity of the qPCR was significantly higher at 95.3 (95% posterior probability interval [PPI] [84.2; 99.6]) than that of bacteriological culture at 58.2 (95% PPI [43.8; 74.4]). However, bacterial culture had a higher specificity of 99.7 (95% PPI [98.5; 100.0]) compared to the qPCR at 98.5 (95% PPI [94.6; 99.9]). The median estimated negative predictive values of qPCR was consistently higher than those of the BC at all estimated prevalences, and the superiority of the qPCR increased with increasing within-herd prevalence. The median positive predictive values of BC was in general higher than the estimates for the qPCR, however, at the highest prevalence the predictive ability of both tests were similar. Copyright © 2018 Elsevier B.V. All

  3. Multimorbidity and survival for patients with acute myocardial infarction in England and Wales: Latent class analysis of a nationwide population-based cohort.

    Science.gov (United States)

    Hall, Marlous; Dondo, Tatendashe B; Yan, Andrew T; Mamas, Mamas A; Timmis, Adam D; Deanfield, John E; Jernberg, Tomas; Hemingway, Harry; Fox, Keith A A; Gale, Chris P

    2018-03-01

    There is limited knowledge of the scale and impact of multimorbidity for patients who have had an acute myocardial infarction (AMI). Therefore, this study aimed to determine the extent to which multimorbidity is associated with long-term survival following AMI. This national observational study included 693,388 patients (median age 70.7 years, 452,896 [65.5%] male) from the Myocardial Ischaemia National Audit Project (England and Wales) who were admitted with AMI between 1 January 2003 and 30 June 2013. There were 412,809 (59.5%) patients with multimorbidity at the time of admission with AMI, i.e., having at least 1 of the following long-term health conditions: diabetes, chronic obstructive pulmonary disease or asthma, heart failure, renal failure, cerebrovascular disease, peripheral vascular disease, or hypertension. Those with heart failure, renal failure, or cerebrovascular disease had the worst outcomes (39.5 [95% CI 39.0-40.0], 38.2 [27.7-26.8], and 26.6 [25.2-26.4] deaths per 100 person-years, respectively). Latent class analysis revealed 3 multimorbidity phenotype clusters: (1) a high multimorbidity class, with concomitant heart failure, peripheral vascular disease, and hypertension, (2) a medium multimorbidity class, with peripheral vascular disease and hypertension, and (3) a low multimorbidity class. Patients in class 1 were less likely to receive pharmacological therapies compared with class 2 and 3 patients (including aspirin, 83.8% versus 87.3% and 87.2%, respectively; β-blockers, 74.0% versus 80.9% and 81.4%; and statins, 80.6% versus 85.9% and 85.2%). Flexible parametric survival modelling indicated that patients in class 1 and class 2 had a 2.4-fold (95% CI 2.3-2.5) and 1.5-fold (95% CI 1.4-1.5) increased risk of death and a loss in life expectancy of 2.89 and 1.52 years, respectively, compared with those in class 3 over the 8.4-year follow-up period. The study was limited to all-cause mortality due to the lack of available cause-specific mortality

  4. Multimorbidity and survival for patients with acute myocardial infarction in England and Wales: Latent class analysis of a nationwide population-based cohort.

    Directory of Open Access Journals (Sweden)

    Marlous Hall

    2018-03-01

    Full Text Available There is limited knowledge of the scale and impact of multimorbidity for patients who have had an acute myocardial infarction (AMI. Therefore, this study aimed to determine the extent to which multimorbidity is associated with long-term survival following AMI.This national observational study included 693,388 patients (median age 70.7 years, 452,896 [65.5%] male from the Myocardial Ischaemia National Audit Project (England and Wales who were admitted with AMI between 1 January 2003 and 30 June 2013. There were 412,809 (59.5% patients with multimorbidity at the time of admission with AMI, i.e., having at least 1 of the following long-term health conditions: diabetes, chronic obstructive pulmonary disease or asthma, heart failure, renal failure, cerebrovascular disease, peripheral vascular disease, or hypertension. Those with heart failure, renal failure, or cerebrovascular disease had the worst outcomes (39.5 [95% CI 39.0-40.0], 38.2 [27.7-26.8], and 26.6 [25.2-26.4] deaths per 100 person-years, respectively. Latent class analysis revealed 3 multimorbidity phenotype clusters: (1 a high multimorbidity class, with concomitant heart failure, peripheral vascular disease, and hypertension, (2 a medium multimorbidity class, with peripheral vascular disease and hypertension, and (3 a low multimorbidity class. Patients in class 1 were less likely to receive pharmacological therapies compared with class 2 and 3 patients (including aspirin, 83.8% versus 87.3% and 87.2%, respectively; β-blockers, 74.0% versus 80.9% and 81.4%; and statins, 80.6% versus 85.9% and 85.2%. Flexible parametric survival modelling indicated that patients in class 1 and class 2 had a 2.4-fold (95% CI 2.3-2.5 and 1.5-fold (95% CI 1.4-1.5 increased risk of death and a loss in life expectancy of 2.89 and 1.52 years, respectively, compared with those in class 3 over the 8.4-year follow-up period. The study was limited to all-cause mortality due to the lack of available cause

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

    Directory of Open Access Journals (Sweden)

    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.

  6. 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

    2018-04-01

    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.

  7. 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.

  8. 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.

  9. 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.

  10. Using a bayesian latent class model to evaluate the utility of investigating persons with negative polymerase chain reaction results for pertussis.

    Science.gov (United States)

    Tarr, Gillian A M; Eickhoff, Jens C; Koepke, Ruth; Hopfensperger, Daniel J; Davis, Jeffrey P; Conway, James H

    2013-07-15

    Pertussis remains difficult to control. Imperfect sensitivity of diagnostic tests and lack of specific guidance regarding interpretation of negative test results among patients with compatible symptoms may contribute to its spread. In this study, we examined whether additional pertussis cases could be identified if persons with negative pertussis test results were routinely investigated. We conducted interviews among 250 subjects aged ≤18 years with pertussis polymerase chain reaction (PCR) results reported from 2 reference laboratories in Wisconsin during July-September 2010 to determine whether their illnesses met the Centers for Disease Control and Prevention's clinical case definition (CCD) for pertussis. PCR validity measures were calculated using the CCD as the standard for pertussis disease. Two Bayesian latent class models were used to adjust the validity measures for pertussis detectable by 1) culture alone and 2) culture and/or more sensitive measures such as serology. Among 190 PCR-negative subjects, 54 (28%) had illnesses meeting the CCD. In adjusted analyses, PCR sensitivity and the negative predictive value were 1) 94% and 99% and 2) 43% and 87% in the 2 types of models, respectively. The models suggested that public health follow-up of reported pertussis patients with PCR-negative results leads to the detection of more true pertussis cases than follow-up of PCR-positive persons alone. The results also suggest a need for a more specific pertussis CCD.

  11. 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.

  12. 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.

    2016-01-01

    Abstract Introduction: 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 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. PMID:27556920

  13. 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.

  14. Mexico.

    Science.gov (United States)

    1993-01-01

    The background notes on Mexico provide text and recent statistical information on the geography, population, government, economy, and foreign relations, specifically the North American Free Trade Agreement with US. The 1992 population is estimated at 89 million of which 60% are mestizo (Indian-Spanish), 30% are American Indian, 9% are Caucasian, and 1% are other. 90% are Roman Catholic. There are 8 years of compulsory education. Infant mortality is 30/1000 live births. Life expectancy for males is 68 years and 76 years for females. The labor force is comprised of 30% in services, 24% in agriculture and fishing, 19% in manufacturing, 13% in commerce, 7% in construction, 4% in transportation and communication, and .4% in mining. There are 31 states and a federal district. Gross domestic product (GDP) per capita was $3200 in 1991. Military expenditures were .5% of GDP in 1991. The average inflation rate is 19%. Mexico City with 20 million is the largest urban center in the world. In recent years, the economy has been restructured with market oriented reforms; the result has been a growth of GDP of 3.6% in 1991 from 2% in 1987. Dependence on oil exports has decreased. There has been privatization and deregulation of state-owned companies. Subsidies to inefficient companies have been stopped. Tariff rates were reduced. The financial debt has been reduced and turned into a surplus of .8% in 1992. Mexico's foreign debt has been reduced from its high in 1987 of $107 billion. Agricultural reforms have been ongoing for 50 years. Land was redistributed, but standards of living and productivity have improved only slightly. Rural land tenure regulations have been changed, and other economic reforms are expected. Mexico engages in ad hoc international groups and is selective about membership in international organizations.

  15. 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.

  16. Evaluation of performance of bacterial culture of feces and serum ELISA across stages of Johne's disease in cattle using a Bayesian latent class model.

    Science.gov (United States)

    Espejo, L A; Zagmutt, F J; Groenendaal, H; Muñoz-Zanzi, C; Wells, S J

    2015-11-01

    The objective of this study was to evaluate the performance of bacterial culture of feces and serum ELISA to correctly identify cows with Mycobacterium avium ssp. paratuberculosis (MAP) at heavy, light, and non-fecal-shedding levels. A total of 29,785 parallel test results from bacterial culture of feces and serum ELISA were collected from 17 dairy herds in Minnesota, Pennsylvania, and Colorado. Samples were obtained from adult cows from dairy herds enrolled for up to 10 yr in the National Johne's Disease Demonstration Herd Project. A Bayesian latent class model was fitted to estimate the probabilities that bacterial culture of feces (using 72-h sedimentation or 30-min centrifugation methods) and serum ELISA results correctly identified cows as high positive, low positive, or negative given that cows were heavy, light, and non-shedders, respectively. The model assumed that no gold standard test was available and conditional independency existed between diagnostic tests. The estimated conditional probabilities that bacterial culture of feces correctly identified heavy shedders, light shedders, and non-shedders were 70.9, 32.0, and 98.5%, respectively. The same values for the serum ELISA were 60.6, 18.7, and 99.5%, respectively. Differences in diagnostic test performance were observed among states. These results improve the interpretation of results from bacterial culture of feces and serum ELISA for detection of MAP and MAP antibody (respectively), which can support on-farm infection control decisions and can be used to evaluate disease-testing strategies, taking into account the accuracy of these tests. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  17. 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.

  18. Mexico

    International Nuclear Information System (INIS)

    2003-06-01

    This document summarizes the key energy data for Mexico: 1 - energy organizations and policy: Ministry of energy (SENER), Comision Reguladora de Energia (CRE), Ministry of Finances, Ministry of trade and industrial development (SECOFI), national commission for energy savings (CONAE); 2 - companies: federal commission of electricity (CFE), Minera Carbonifera Rio Escondido (MICARE - coal), Pemex (petroleum); 3 - energy production: resources, electric power, petroleum, natural gas; 4 - energy consumption; 5 - stakes and perspectives. Some economic and energy indicators are summarized in a series of tables: general indicators, supply indicators (reserves, refining and electric capacity, energy production, foreign trade), demand indicators (consumption trends, end use, energy independence, energy efficiency, CO 2 emissions), energy status per year and per energy source. (J.S.)

  19. 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

    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...... cut-offs, indicating under estimation of S. agalactiae IMI in the examined dairy cows. In conclusion, Se of PCR is always higher than Se of BC at all tested cut-offs. The lower cut-off, the more comparable becomes Se of PCR and Se of BC. The changes in Se in both PCR and BC at different Ct-value cut...... 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...

  20. 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.

  1. 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

  2. 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

  3. Patterns of Gender-Based Violence and Associations with Mental Health and HIV Risk Behavior Among Female Sex Workers in Mombasa, Kenya: A Latent Class Analysis.

    Science.gov (United States)

    Roberts, Sarah T; Flaherty, Brian P; Deya, Ruth; Masese, Linnet; Ngina, Jacqueline; McClelland, R Scott; Simoni, Jane; Graham, Susan M

    2018-03-30

    Gender-based violence (GBV) is common among female sex workers (FSWs) and is associated with multiple HIV risk factors, including poor mental health, high-risk sexual behavior, and sexually transmitted infections (STIs). Prior studies have focused on GBV of one type (e.g. physical or sexual) or from one kind of perpetrator (e.g., clients or regular partners), but many FSWs experience overlapping types of violence from multiple perpetrators, with varying frequency and severity. We examined the association between lifetime patterns of GBV and HIV risk factors in 283 FSWs in Mombasa, Kenya. Patterns of GBV were identified with latent class analysis based on physical, sexual, or emotional violence from multiple perpetrators. Cross-sectional outcomes included depressive symptoms, post-traumatic stress disorder (PTSD) symptoms, disordered alcohol and other drug use, number of sex partners, self-reported unprotected sex, prostate-specific antigen (PSA) in vaginal secretions, and a combined unprotected sex indicator based on self-report or PSA detection. We also measured HIV/STI incidence over 12 months following GBV assessment. Associations between GBV patterns and each outcome were modeled separately using linear regression for mental health outcomes and Poisson regression for sexual risk outcomes. Lifetime prevalence of GBV was 87%. We identified 4 GBV patterns, labeled Low (21% prevalence), Sexual (23%), Physical/Moderate Emotional (18%), and Severe (39%). Compared to women with Low GBV, those with Severe GBV had higher scores for depressive symptoms, PTSD symptoms, and disordered alcohol use, and had more sex partners. Women with Sexual GBV had higher scores for disordered alcohol use than women with Low GBV, but similar sexual risk behavior. Women with Physical/Moderate Emotional GBV had more sex partners and a higher prevalence of unprotected sex than women with Low GBV, but no differences in mental health. HIV/STI incidence did not differ significantly by GBV

  4. 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…

  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. 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

    DEFF Research Database (Denmark)

    Cederlöf, Sara Ellinor; Toft, Nils; Aalbæk, Bent

    2012-01-01

    characteristics of PathoProof TM 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 TM Mastitis PCR Assay. Latent class analysis was used to estimate test properties for PCR and BC in the absence...

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

    CERN Document Server

    Skrondal, Anders; Rabe-Hesketh, Sophia

    2004-01-01

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

  9. 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.

    Science.gov (United States)

    Mahmmod, Yasser S; Toft, Nils; Katholm, Jørgen; Grønbæk, Carsten; Klaas, Ilka C

    2013-05-01

    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 recording, 2456 quarter milk samples were taken aseptically for BC and the routinely taken cow level milk samples were analyzed by PCR. Results showed that 53 cows (8.6%) were positive for S. agalactiae IMI by BC. Sensitivity of PCR at cut-offs; ≤ 39, ≤ 37, ≤ 34, and ≤ 32, was 96.2%, 91.9%, 87.2% and 73.9%, while Se of BC was 25.7%, 29.9%, 59.9% and 72.1%. Specificity of PCR at cut-offs; ≤ 39, ≤ 37, ≤ 34, and ≤ 32, was 96.8%, 96.9%, 96.7%, and 97.22%, while Sp of BC was 99.7%, 99.5%, 99.2%, and 98.9%. The estimated prevalence of S. agalactiae IMI by PCR was higher than the apparent prevalence at the tested cut-offs, indicating under estimation of S. agalactiae IMI in the examined dairy cows. In conclusion, Se of PCR is always higher than Se of BC at all tested cut-offs. The lower cut-off, the more comparable becomes Se of PCR and Se of BC. The changes in Se in both PCR and BC at different Ct-value cut-offs may indicate a change in the definition of the latent infection. The similar Se of both tests at cut-off ≤ 32 may indicate high concentrations of S. agalactiae viable cells, representing a cow truly/heavily infected with S. agalactiae and thus easier to detect with BC. At cut-off ≤ 39 the latent 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

  10. Evaluation by latent class analysis of a magnetic capture based DNA extraction followed by real-time qPCR as a new diagnostic method for detection of Echinococcus multilocularis in definitive hosts.

    Science.gov (United States)

    Maas, Miriam; van Roon, Annika; Dam-Deisz, Cecile; Opsteegh, Marieke; Massolo, Alessandro; Deksne, Gunita; Teunis, Peter; van der Giessen, Joke

    2016-10-30

    A new method, based on a magnetic capture based DNA extraction followed by qPCR, was developed for the detection of the zoonotic parasite Echinococcus multilocularis in definitive hosts. Latent class analysis was used to compare this new method with the currently used phenol-chloroform DNA extraction followed by single tube nested PCR. In total, 60 red foxes and coyotes from three different locations were tested with both molecular methods and the sedimentation and counting technique (SCT) or intestinal scraping technique (IST). Though based on a limited number of samples, it could be established that the magnetic capture based DNA extraction followed by qPCR showed similar sensitivity and specificity as the currently used phenol-chloroform DNA extraction followed by single tube nested PCR. All methods have a high specificity as shown by Bayesian latent class analysis. Both molecular assays have higher sensitivities than the combined SCT and IST, though the uncertainties in sensitivity estimates were wide for all assays tested. The magnetic capture based DNA extraction followed by qPCR has the advantage of not requiring hazardous chemicals like the phenol-chloroform DNA extraction followed by single tube nested PCR. This supports the replacement of the phenol-chloroform DNA extraction followed by single tube nested PCR by the magnetic capture based DNA extraction followed by qPCR for molecular detection of E. multilocularis in definitive hosts. Copyright © 2016 Elsevier B.V. All rights reserved.

  11. 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.

  12. 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.

  13. Latent lifestyle preferences and household location decisions

    Science.gov (United States)

    Walker, Joan L.; Li, Jieping

    2007-04-01

    Lifestyle, indicating preferences towards a particular way of living, is a key driver of the decision of where to live. We employ latent class choice models to represent this behavior, where the latent classes are the lifestyles and the choice model is the choice of residential location. Thus, we simultaneously estimate lifestyle groups and how lifestyle impacts location decisions. Empirical results indicate three latent lifestyle segments: suburban dwellers, urban dwellers, and transit-riders. The suggested lifestyle segments have intriguing policy implications. Lifecycle characteristics are used to predict lifestyle preferences, although there remain significant aspects that cannot be explained by observable variables.

  14. Determining non-cigarette tobacco, alcohol, and substance use typologies across menthol and non-menthol smokers using latent class analysis

    Directory of Open Access Journals (Sweden)

    Amy M. Cohn

    2017-01-01

    LCA allowed for the identification of distinct classes of smokers based on factors related to poor cessation outcomes, including menthol use, that have not previously been examined in combination. Interventions should target specific groups of smokers, rather than take a “one size fits all” approach.

  15. How “Gendered” Are Gendered Pathways into Prison?: a Latent Class Analysis of the Life Experiences of Male and Female Prisoners in The Netherlands

    NARCIS (Netherlands)

    Joosen, Katharina J.; Palmen, Hanneke; Kruttschnitt, Candace; Bijleveld, Catrien; Dirkzwager, Anja; Nieuwbeerta, Paul

    2016-01-01

    Purpose Studies of pathways to offending have mainly focused on identifying either gendered trajectories in criminal careers, gendered risk factors for offending, or gendered pathways. Less common is research that explores to what extent classes or types of pathways to offending are actually

  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. Evaluation of the Diagnostic Accuracy of a Typhoid IgM Flow Assay for the Diagnosis of Typhoid Fever in Cambodian Children Using a Bayesian Latent Class Model Assuming an Imperfect Gold Standard

    Science.gov (United States)

    Moore, Catrin E.; Pan-Ngum, Wirichada; Wijedoru, Lalith P. M.; Sona, Soeng; Nga, Tran Vu Thieu; Duy, Pham Thanh; Vinh, Phat Voong; Chheng, Kheng; Kumar, Varun; Emary, Kate; Carter, Michael; White, Lisa; Baker, Stephen; Day, Nicholas P. J.; Parry, Christopher M.

    2014-01-01

    Rapid diagnostic tests are needed for typhoid fever (TF) diagnosis in febrile children in endemic areas. Five hundred children admitted to the hospital in Cambodia between 2009 and 2010 with documented fever (≥ 38°C) were investigated using blood cultures (BCs), Salmonella Typhi/Paratyphi A real-time polymerase chain reactions (PCRs), and a Typhoid immunoglobulin M flow assay (IgMFA). Test performance was determined by conventional methods and Bayesian latent class modeling. There were 32 cases of TF (10 BC- and PCR-positive cases, 14 BC-positive and PCR-negative cases, and 8 BC-negative and PCR-positive cases). IgMFA sensitivity was 59.4% (95% confidence interval = 41–76), and specificity was 97.8% (95% confidence interval = 96–99). The model estimate sensitivity for BC was 81.0% (95% credible interval = 54–99). The model estimate sensitivity for PCR was 37.8% (95% credible interval = 26–55), with a specificity of 98.2% (95% credible interval = 97–99). The model estimate sensitivity for IgMFA (≥ 2+) was 77.9% (95% credible interval = 58–90), with a specificity of 97.5% (95% credible interval = 95–100). The model estimates of IgMFA sensitivity and specificity were comparable with BCs and better than estimates using conventional analysis. PMID:24218407

  18. Comparison of the Performance of the TPTest, Tubex, Typhidot and Widal Immunodiagnostic Assays and Blood Cultures in Detecting Patients with Typhoid Fever in Bangladesh, Including Using a Bayesian Latent Class Modeling Approach.

    Science.gov (United States)

    Islam, Kamrul; Sayeed, Md Abu; Hossen, Emran; Khanam, Farhana; Charles, Richelle C; Andrews, Jason; Ryan, Edward T; Qadri, Firdausi

    2016-04-01

    There is an urgent need for an improved diagnostic assay for typhoid fever. In this current study, we compared the recently developed TPTest (Typhoid and Paratyphoid Test) with the Widal test, blood culture, and two commonly used commercially available kits, Tubex and Typhidot. For analysis, we categorized 92 Bangladeshi patients with suspected enteric fever into four groups: S. Typhi bacteremic patients (n = 28); patients with a fourfold change in Widal test from day 0 to convalescent period (n = 7); patients with Widal titer ≥1:320 (n = 13) at either acute or convalescent stage of disease; and patients suspected with enteric fever, but with a negative blood culture and Widal titer (n = 44). We also tested healthy endemic zone controls (n = 20) and Bangladeshi patients with other febrile illnesses (n = 15). Sample size was based on convenience to facilitate preliminary analysis. Of 28 S. Typhi bacteremic patients, 28 (100%), 21 (75%) and 18 (64%) patients were positive by TPTest, Tubex and Typhidot, respectively. In healthy endemic zone controls, the TPTest method was negative in all, whereas Tubex and Typhidot were positive in 3 (15%) and 5 (25%), respectively. We then estimated sensitivity and specificity of all diagnostic tests using Bayesian latent class modeling. The sensitivity of TPTest, Tubex and Typhidot were estimated at 96.0% (95% CI: 87.1%-99.8%), 60.2% (95% CI: 49.3%-71.2%), and 59.6% (95% CI: 50.1%-69.3%), respectively. Specificity was estimated at 96.6% (90.7%-99.2%) for TPTest, 89.9% (79.6%-96.8%) for Tubex, and 80.0% (67.7%-89.7%) for Typhidot. These results suggest that the TPTest is highly sensitive and specific in diagnosing individuals with typhoid fever in a typhoid endemic setting, outperforming currently available and commonly used alternatives.

  19. CLASSIFICATION OF IRANIAN NURSES ACCORDING TO THEIR MENTAL HEALTH OUTCOMES USING GHQ-12 QUESTIONNAIRE: A COMPARISON BETWEEN LATENT CLASS ANALYSIS AND K-MEANS CLUSTERING WITH TRADITIONAL SCORING METHOD.

    Science.gov (United States)

    Jamali, Jamshid; Ayatollahi, Seyyed Mohammad Taghi

    2015-10-01

    Nurses constitute the most providers of health care systems. Their mental health can affect the quality of services and patients' satisfaction. General Health Questionnaire (GHQ-12) is a general screening tool used to detect mental disorders. Scoring method and determining thresholds for this questionnaire are debatable and the cut-off points can vary from sample to sample. This study was conducted to estimate the prevalence of mental disorders among Iranian nurses using GHQ-12 and also compare Latent Class Analysis (LCA) and K-means clustering with traditional scoring method. A cross-sectional study was carried out in Fars and Bushehr provinces of southern Iran in 2014. Participants were 771 Iranian nurses, who filled out the GHQ-12 questionnaire. Traditional scoring method, LCA and K-means were used to estimate the prevalence of mental disorder among Iranian nurses. Cohen's kappa statistic was applied to assess the agreement between the LCA and K-means with traditional scoring method of GHQ-12. The nurses with mental disorder by scoring method, LCA and K-mean were 36.3% (n=280), 32.2% (n=248), and 26.5% (n=204), respectively. LCA and logistic regression revealed that the prevalence of mental disorder in females was significantly higher than males. Mental disorder in nurses was in a medium level compared to other people living in Iran. There was a little difference between prevalence of mental disorder estimated by scoring method, K-means and LCA. According to the advantages of LCA than K-means and different results in scoring method, we suggest LCA for classification of Iranian nurses according to their mental health outcomes using GHQ-12 questionnaire.

  20. 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. Denver School .... and greater access to services and media exposure) ..... other factors (e.g. urbanity) as the influencer.

  1. Latent palmprint matching.

    Science.gov (United States)

    Jain, Anil K; Feng, Jianjiang

    2009-06-01

    The evidential value of palmprints in forensic applications is clear as about 30 percent of the latents recovered from crime scenes are from palms. While biometric systems for palmprint-based personal authentication in access control type of applications have been developed, they mostly deal with low-resolution (about 100 ppi) palmprints and only perform full-to-full palmprint matching. We propose a latent-to-full palmprint matching system that is needed in forensic applications. Our system deals with palmprints captured at 500 ppi (the current standard in forensic applications) or higher resolution and uses minutiae as features to be compatible with the methodology used by latent experts. Latent palmprint matching is a challenging problem because latent prints lifted at crime scenes are of poor image quality, cover only a small area of the palm, and have a complex background. Other difficulties include a large number of minutiae in full prints (about 10 times as many as fingerprints), and the presence of many creases in latents and full prints. A robust algorithm to reliably estimate the local ridge direction and frequency in palmprints is developed. This facilitates the extraction of ridge and minutiae features even in poor quality palmprints. A fixed-length minutia descriptor, MinutiaCode, is utilized to capture distinctive information around each minutia and an alignment-based minutiae matching algorithm is used to match two palmprints. Two sets of partial palmprints (150 live-scan partial palmprints and 100 latent palmprints) are matched to a background database of 10,200 full palmprints to test the proposed system. Despite the inherent difficulty of latent-to-full palmprint matching, rank-1 recognition rates of 78.7 and 69 percent, respectively, were achieved in searching live-scan partial palmprints and latent palmprints against the background database.

  2. The Integration of Continuous and Discrete Latent Variable Models: Potential Problems and Promising Opportunities

    Science.gov (United States)

    Bauer, Daniel J.; Curran, Patrick J.

    2004-01-01

    Structural equation mixture modeling (SEMM) integrates continuous and discrete latent variable models. Drawing on prior research on the relationships between continuous and discrete latent variable models, the authors identify 3 conditions that may lead to the estimation of spurious latent classes in SEMM: misspecification of the structural model,…

  3. 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

  4. On the explaining-away phenomenon in multivariate latent variable models.

    Science.gov (United States)

    van Rijn, Peter; Rijmen, Frank

    2015-02-01

    Many probabilistic models for psychological and educational measurements contain latent variables. Well-known examples are factor analysis, item response theory, and latent class model families. We discuss what is referred to as the 'explaining-away' phenomenon in the context of such latent variable models. This phenomenon can occur when multiple latent variables are related to the same observed variable, and can elicit seemingly counterintuitive conditional dependencies between latent variables given observed variables. We illustrate the implications of explaining away for a number of well-known latent variable models by using both theoretical and real data examples. © 2014 The British Psychological Society.

  5. 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....

  6. Latent Growth and Dynamic Structural Equation Models.

    Science.gov (United States)

    Grimm, Kevin J; Ram, Nilam

    2018-05-07

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

  7. Classification criteria of syndromes by latent variable models

    DEFF Research Database (Denmark)

    Petersen, Janne

    2010-01-01

    patient's characteristics. These methods may erroneously reduce multiplicity either by combining markers of different phenotypes or by mixing HALS with other processes such as aging. Latent class models identify homogenous groups of patients based on sets of variables, for example symptoms. As no gold......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...... 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...

  8. 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...

  9. Suicide behavior and associated psychosocial factors among adolescents in Campeche, Mexico.

    Science.gov (United States)

    González-Forteza, Catalina; Juárez-López, Carlos E; Jiménez, Alberto; Montejo-León, Liliana; Rodríguez-Santisbón, Ulises R; Wagner, Fernando A

    2017-12-01

    Suicide is an important public health problem that requires a preventive approach. The present study aimed at assessing suicidal behaviors and their relations with other psychosocial factors in Campeche, Mexico, in order to inform the design of potential preventive interventions. A multistage probability sample of 2386 students representative of all middle schools of the state of Campeche, Mexico, took a standardized, paper-and-pencil survey covering selected psychosocial constructs including suicide behavior, depression, drug use, familial relationships, locus of control, impulsivity, and self-esteem, among others. Latent classes were identified and multinomial logistic regression was used to analyze associations between class membership and psychosocial covariates. An estimated 8% of the middle school population in Campeche had three or more psychosocial problems in the past month including drug use, major depression episode symptoms, as well as suicidal problems like attempts and self-inflicted injuries. Four latent classes were identified, one with lowest risk and three with varying characteristics in terms of binge alcohol and other drug use, depression, and suicide behaviors. Associations between psychosocial covariates and latent class were observed, as predicted based on a multi-dimensional theoretical framework. Heterogeneity across "High-Risk" groups and their potential determinants highlight the need for differentiated, specialized efforts ranging from universal to indicated interventions. Given the high level of risk factors in this population, universal preventive interventions should aim at building resiliency among youth by helping them develop an array of coping resources, as well as by creating a more nurturing psychosocial environment. Copyright © 2017 Elsevier Inc. All rights reserved.

  10. 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

    Respiratory Disorders" (2%). Female gender was associated with an increased likelihood of belonging to any of the six multimorbidity classes except for class 2 (Hypertension). Low educational attainment predicted membership of all of the multimorbidity classes except for class 5 (Asthma-Allergy). Marked...... had nearly identical profiles in relation to health-related quality of life. CONCLUSION: The results clearly support that diseases tend to compound and interact, which suggests that a differentiated public health and treatment approach towards multimorbidity is needed.......% of the population) labeled "1) Relatively Healthy" and six classes with a very high prevalence of multimorbidity labeled; "2) Hypertension" (14%); "3) Musculoskeletal Disorders" (10%); "4) Headache-Mental Disorders" (7%); "5) Asthma-Allergy" (6%); "6) Complex Cardiometabolic Disorders" (3%); and "7) Complex...

  11. Mental toughness latent profiles in endurance athletes.

    Science.gov (United States)

    Zeiger, Joanna S; Zeiger, Robert S

    2018-01-01

    Mental toughness in endurance athletes, while an important factor for success, has been scarcely studied. An online survey was used to examine eight mental toughness factors in endurance athletes. The study aim was to determine mental toughness profiles via latent profile analysis in endurance athletes and whether associations exist between the latent profiles and demographics and sports characteristics. Endurance athletes >18 years of age were recruited via social media outlets (n = 1245, 53% female). Mental toughness was measured using the Sports Mental Toughness Questionnaire (SMTQ), Psychological Performance Inventory-Alternative (PPI-A), and self-esteem was measured using the Rosenberg Self-Esteem Scale (RSE). A three-class solution emerged, designated as high mental toughness (High MT), moderate mental toughness (Moderate MT) and low mental toughness (Low MT). ANOVA tests showed significant differences between all three classes on all 8 factors derived from the SMTQ, PPI-A and the RSE. There was an increased odds of being in the High MT class compared to the Low MT class for males (OR = 1.99; 95% CI, 1.39, 2.83; Pathletes who were over 55 compared to those who were 18-34 (OR = 2.52; 95% CI, 1.37, 4.62; Pathletes. High MT is associated with demographics and sports characteristics. Mental toughness screening in athletes may help direct practitioners with mental skills training.

  12. Mental toughness latent profiles in endurance athletes.

    Directory of Open Access Journals (Sweden)

    Joanna S Zeiger

    Full Text Available Mental toughness in endurance athletes, while an important factor for success, has been scarcely studied. An online survey was used to examine eight mental toughness factors in endurance athletes. The study aim was to determine mental toughness profiles via latent profile analysis in endurance athletes and whether associations exist between the latent profiles and demographics and sports characteristics. Endurance athletes >18 years of age were recruited via social media outlets (n = 1245, 53% female. Mental toughness was measured using the Sports Mental Toughness Questionnaire (SMTQ, Psychological Performance Inventory-Alternative (PPI-A, and self-esteem was measured using the Rosenberg Self-Esteem Scale (RSE. A three-class solution emerged, designated as high mental toughness (High MT, moderate mental toughness (Moderate MT and low mental toughness (Low MT. ANOVA tests showed significant differences between all three classes on all 8 factors derived from the SMTQ, PPI-A and the RSE. There was an increased odds of being in the High MT class compared to the Low MT class for males (OR = 1.99; 95% CI, 1.39, 2.83; P<0.001, athletes who were over 55 compared to those who were 18-34 (OR = 2.52; 95% CI, 1.37, 4.62; P<0.01, high sports satisfaction (OR = 8.17; 95% CI, 5.63, 11.87; P<0.001, and high division placement (OR = 2.18; 95% CI, 1.46,3.26; P<0.001. The data showed that mental toughness latent profiles exist in endurance athletes. High MT is associated with demographics and sports characteristics. Mental toughness screening in athletes may help direct practitioners with mental skills training.

  13. Latent semantic analysis.

    Science.gov (United States)

    Evangelopoulos, Nicholas E

    2013-11-01

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

  14. Latent heat coldness storage; Stockage du froid par chaleur latente

    Energy Technology Data Exchange (ETDEWEB)

    Dumas, J.P. [Pau Univ., Lab. de Thermodynamique et Energetique, LTE, 64 (France)

    2002-07-01

    This article presents the advantages of latent heat storage systems which use the solid-liquid phase transformation of a pure substance or of a solution. The three main methods of latent heat storage of coldness are presented: ice boxes, encapsulated nodules, and ice flows: 1 - definition of the thermal energy storage (sensible heat, latent heat, thermochemical storage); 2 - advantages and drawbacks of latent heat storage; 3 - choice criteria for a phase-change material; 4 - phenomenological aspect of liquid-solid transformations (phase equilibrium, crystallisation and surfusion); 5 - different latent heat storage processes (ice boxes, encapsulated nodules, two-phase refrigerating fluids); 6 - ice boxes (internal and external melting, loop, air injection, measurement of ice thickness); 7 - encapsulated nodules (nodules, tank, drainage, advantage and drawbacks, charge and discharge); 8 - two-phase refrigerating fluids (composition, ice fabrication, flow circulation, flow storage, exchangers). (J.S.)

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

    Science.gov (United States)

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

    2003-01-01

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

  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. Bayesian latent feature modeling for modeling bipartite networks with overlapping groups

    DEFF Research Database (Denmark)

    Jørgensen, Philip H.; Mørup, Morten; Schmidt, Mikkel Nørgaard

    2016-01-01

    Bi-partite networks are commonly modelled using latent class or latent feature models. Whereas the existing latent class models admit marginalization of parameters specifying the strength of interaction between groups, existing latent feature models do not admit analytical marginalization...... by the notion of community structure such that the edge density within groups is higher than between groups. Our model further assumes that entities can have different propensities of generating links in one of the modes. The proposed framework is contrasted on both synthetic and real bi-partite networks...... feature representations in bipartite networks provides a new framework for accounting for structure in bi-partite networks using binary latent feature representations providing interpretable representations that well characterize structure as quantified by link prediction....

  18. Longitudinal Research with Latent Variables

    CERN Document Server

    van Montfort, Kees; Satorra, Albert

    2010-01-01

    This book combines longitudinal research and latent variable research, i.e. it explains how longitudinal studies with objectives formulated in terms of latent variables should be carried out, with an emphasis on detailing how the methods are applied. Because longitudinal research with latent variables currently utilizes different approaches with different histories, different types of research questions, and different computer programs to perform the analysis, the book is divided into nine chapters. Starting from some background information about the specific approach, short history and the ma

  19. 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.

  20. World Class Teachers.

    Science.gov (United States)

    Mitchell, Rosalita

    1998-01-01

    School communities are challenged to find ways to identify good teachers and give other teachers a chance to learn from them. The New Mexico World Class Teacher Project is encouraging teachers to pursue certification by the National Board for Professional Teaching Standards. This process sharpens teachers' student assessment skills and encourages…

  1. Powering Mexico

    International Nuclear Information System (INIS)

    Anon.

    1992-01-01

    This article examines Mexico's demand for electricity and the market for independent power generation. The topics discussed in the article include the outlook for the 1990s for growth in Mexico's economy and energy demand, renewable energy, energy conservation, small-scale, off-grid renewable energy systems, and estimates of Mexico's market for electric power generating equipment

  2. Mexico Geoid Heights (MEXICO97)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This 2' geoid height grid for Mexico, and North-Central America, is the MEXICO97 geoid model. The computation used about one million terrestrial and marine gravity...

  3. Latent geometry of bipartite networks

    Science.gov (United States)

    Kitsak, Maksim; Papadopoulos, Fragkiskos; Krioukov, Dmitri

    2017-03-01

    Despite the abundance of bipartite networked systems, their organizing principles are less studied compared to unipartite networks. Bipartite networks are often analyzed after projecting them onto one of the two sets of nodes. As a result of the projection, nodes of the same set are linked together if they have at least one neighbor in common in the bipartite network. Even though these projections allow one to study bipartite networks using tools developed for unipartite networks, one-mode projections lead to significant loss of information and artificial inflation of the projected network with fully connected subgraphs. Here we pursue a different approach for analyzing bipartite systems that is based on the observation that such systems have a latent metric structure: network nodes are points in a latent metric space, while connections are more likely to form between nodes separated by shorter distances. This approach has been developed for unipartite networks, and relatively little is known about its applicability to bipartite systems. Here, we fully analyze a simple latent-geometric model of bipartite networks and show that this model explains the peculiar structural properties of many real bipartite systems, including the distributions of common neighbors and bipartite clustering. We also analyze the geometric information loss in one-mode projections in this model and propose an efficient method to infer the latent pairwise distances between nodes. Uncovering the latent geometry underlying real bipartite networks can find applications in diverse domains, ranging from constructing efficient recommender systems to understanding cell metabolism.

  4. Biomarkers of latent TB infection

    DEFF Research Database (Denmark)

    Ruhwald, Morten; Ravn, Pernille

    2009-01-01

    For the last 100 years, the tuberculin skin test (TST) has been the only diagnostic tool available for latent TB infection (LTBI) and no biomarker per se is available to diagnose the presence of LTBI. With the introduction of M. tuberculosis-specific IFN-gamma release assays (IGRAs), a new area...... of in vitro immunodiagnostic tests for LTBI based on biomarker readout has become a reality. In this review, we discuss existing evidence on the clinical usefulness of IGRAs and the indefinite number of potential new biomarkers that can be used to improve diagnosis of latent TB infection. We also present...... early data suggesting that the monocyte-derived chemokine inducible protein-10 may be useful as a novel biomarker for the immunodiagnosis of latent TB infection....

  5. What is Urban? A study of census and satellite-derived urban classes in the United States (1990-2010) with comparisons to India and Mexico

    Science.gov (United States)

    Balk, D.; Leyk, S.; Jones, B.; Clark, A.; Montgomery, M.

    2017-12-01

    Geographers and demographers have contributed much to understanding urban population and urban place. Yet, we nevertheless remain ill-prepared to fully understand past urban processes and our urban future, and importantly, connect that knowledge to pressing concerns such as climate and environmental change. This is largely due to well-known data limitations and inherent inconsistencies in the urban definition across countries and over time and spatial scales, and because urban models and definitions arise out of disciplinary silos. This paper provides a new framework for urban inquiry in that it combines urban definitions used by the U.S. Census Bureau from 1990-2010 with newly available satellite-based (mostly Landsat) data on built-up area from the Global Human Settlement Layer (GHSL). We identify areas of agreement and disagreement, as well as the population distribution underlying various GHSL derived built-up land thresholds. Our analysis allows for a systematic means of discerning peri-urban areas from other types of urban development, as well as examines differences in these patterns at the national and Metropolitan Statistical Area (MSA)-level. While we find overwhelming areas of agreement - about 70% of the census-designated urban population can be characterized as living on land that is at least 50% built-up - we also learn much of the significant heterogeneity in levels and patterns of growth between different MSAs. We further compare the US results with those for India and Mexico. This research unlocks the potential of such alternative measures for creating globally and temporally consistent proxies of urban land and may guide further research on consistent modeling of spatial demographic urban change, highly urgent for future work to distinguish between fine-scale levels of urban development and to forecast urban expansion.

  6. Depressive symptoms among adolescents and older adults in Mexico City.

    Science.gov (United States)

    Sánchez-García, Sergio; García-Peña, Carmen; González-Forteza, Catalina; Jiménez-Tapia, Alberto; Gallo, Joseph J; Wagner, Fernando A

    2014-06-01

    Determine the structure of depressive symptoms among adolescents and older adults through the person-centered approach of latent class analysis (LCA). The study is based on data from two independent samples collected in Mexico City (2,444 adolescents and 2,223 older adults) which included the revised version of the CES-D. The presence or absence of depressed mood (dysphoria), diminished pleasure (anhedonia), drastic change in weight, sleep problems, thinking and concentration difficulties, excessive or inappropriate guilt, fatigue, psychomotor agitation/retardation, and suicide ideation were used in LCA to determine the structure of depressive symptoms for adolescents and older adults. Adolescents reported higher excessive or inappropriate guilt compared to older adults, while older adults had higher proportions of anhedonia, sleep problems, fatigue, and psychomotor agitation/retardation. Similar proportions were found in other symptoms. The LCA analysis showed the best fit with four latent classes (LC): LC 1, "symptoms suggestive of major depressive episode (MDE)" with prevalence of 5.9 % (n = 144) and 10.3 % (n = 230) among adolescents and older adults, respectively; LC 2, "probable MDE symptoms" 18.2 % (n = 446) and 23.0 % (n = 512); LC 3, "possible MDE" 27.7 % (n = 676) and 21.8 % (n = 485); LC 4, "without significant depressive symptoms" 48.2 % (n = 1,178) and 44.8 % (n = 996). The differences in item thresholds between the two groups (adolescents vs. older adults) were statistically significant (Wald test = 255.684, df = 1, p depressive symptoms between adolescents and older adults that merit acknowledgment, further study, and consideration of their potential clinical and public health implications.

  7. Differences in Students' School Motivation: A Latent Class Modelling Approach

    Science.gov (United States)

    Korpershoek, Hanke; Kuyper, Hans; van der Werf, Greetje

    2015-01-01

    In this study, we investigated the school motivation of 7,257 9th grade students in 80 secondary schools across the Netherlands. Using a multiple goal perspective, four motivation dimensions were included: performance, mastery, extrinsic, and social motivation. Our first aim was to identify distinct motivation profiles within our sample, using the…

  8. A Latent Class Approach to Examining Forms of Peer Victimization

    Science.gov (United States)

    Bradshaw, Catherine P.; Waasdorp, Tracy E.; O'Brennan, Lindsey M.

    2013-01-01

    There is growing interest in gender differences in the experience of various forms of peer victimization; however, much of the work to date has used traditional variable-centered approaches by focusing on scales or individual forms of victimization in isolation. The current study explored whether there were discrete groups of adolescents who…

  9. Differences in students' school motivation : A latent class modelling approach

    NARCIS (Netherlands)

    Korpershoek, Hanke; Kuyper, Hans; van der Werf, Greetje

    In this study, we investigated the school motivation of 7,257 9th grade students in 80 secondary schools across the Netherlands. Using a multiple goal perspective, four motivation dimensions were included: performance, mastery, extrinsic, and social motivation. Our first aim was to identify distinct

  10. Latent class analysis of indicators of intolerance of uncertainty

    NARCIS (Netherlands)

    Boelen, P.A.|info:eu-repo/dai/nl/174011954; Lenferink, L.I.M.|info:eu-repo/dai/nl/411295896

    Intolerance of Uncertainty (IU) is a transdiagnostic vulnerability factor involved in depression and anxiety symptoms and disorders. IU encompasses Prospective IU (“Unforeseen events upset me greatly”) and Inhibitory IU (“The smallest doubt can stop me from acting”). Research has yet to explore

  11. Heterogeneity of postpartum depression: a latent class analysis

    NARCIS (Netherlands)

    Putnam, K.; Robertson-Blackmore, E.; Sharkey, K.; Payne, J.; Bergink, V.; Munk-Olsen, T.; Deligiannidis, K.; Altemus, M.; Newport, J.; Apter, G.; Devouche, E.; Vikorin, A.; Magnusson, P.; Lichtenstein, P.; Penninx, B.W.J.H.; Buist, A.; Bilszta, J.; O'Hara, M.; Stuart, S.; Brock, R.; Roza, S.; Tiemeier, H.; Guille, C.; Epperson, C.N.; Kim, D.; Schmidt, P.; Martinez, P.; Wisner, K.L.; Stowe, Z.; Jones, I.; Rubinow, D.; Sullivan, P.; Meltzer-Brody, S.

    2015-01-01

    Background: Maternal depression in the postpartum period confers substantial morbidity and mortality, but the definition of postpartum depression remains controversial. We investigated the heterogeneity of symptoms with the aim of identifying clinical subtypes of postpartum depression. Methods: Data

  12. Anomalously High Recruitment of the 2010 Gulf Menhaden (Brevoortia patronus) Year Class: Evidence of Indirect Effects from the Deepwater Horizon Blowout in the Gulf of Mexico.

    Science.gov (United States)

    Short, Jeffrey W; Geiger, Harold J; Haney, J Christopher; Voss, Christine M; Vozzo, Maria L; Guillory, Vincent; Peterson, Charles H

    2017-07-01

    Gulf menhaden (Brevoortia patronus) exhibited unprecedented juvenile recruitment in 2010 during the year of the Deepwater Horizon well blowout, exceeding the prior 39-year mean by more than four standard deviations near the Mississippi River. Abundance of that cohort remained exceptionally high for two subsequent years as recruits moved into older age classes. Such changes in this dominant forage fish population can be most parsimoniously explained as consequences of release from predation. Contact with crude oil induced high mortality of piscivorous seabirds, bottlenose dolphin (Tursiops truncatus), waders, and other fish-eating marsh birds, all of which are substantial consumers of Gulf menhaden. Diversions of fresh water from the Mississippi River to protect coastal marshes from oiling depressed salinities, impairing access to juvenile Gulf menhaden by aquatic predators that avoid low-salinity estuarine waters. These releases from predation led to an increase of Gulf menhaden biomass in 2011 to 2.4 million t, or more than twice the average biomass of 1.1 million t for the decade prior to 2010. Biomass increases of this magnitude in a major forage fish species suggest additional trophically linked effects at the population-, trophic-level and ecosystem scales, reflecting an heretofore little appreciated indirect effect that may be associated with major oil spills in highly productive marine waters.

  13. Parametric embedding for class visualization.

    Science.gov (United States)

    Iwata, Tomoharu; Saito, Kazumi; Ueda, Naonori; Stromsten, Sean; Griffiths, Thomas L; Tenenbaum, Joshua B

    2007-09-01

    We propose a new method, parametric embedding (PE), that embeds objects with the class structure into a low-dimensional visualization space. PE takes as input a set of class conditional probabilities for given data points and tries to preserve the structure in an embedding space by minimizing a sum of Kullback-Leibler divergences, under the assumption that samples are generated by a gaussian mixture with equal covariances in the embedding space. PE has many potential uses depending on the source of the input data, providing insight into the classifier's behavior in supervised, semisupervised, and unsupervised settings. The PE algorithm has a computational advantage over conventional embedding methods based on pairwise object relations since its complexity scales with the product of the number of objects and the number of classes. We demonstrate PE by visualizing supervised categorization of Web pages, semisupervised categorization of digits, and the relations of words and latent topics found by an unsupervised algorithm, latent Dirichlet allocation.

  14. Treatment of Latent Tuberculosis Infection

    OpenAIRE

    Tang, Patrick; Johnston, James

    2017-01-01

    Opinion statement The treatment of latent tuberculosis infection (LTBI) is an essential component of tuberculosis (TB) elimination in regions that have a low incidence of TB. However, the decision to treat individuals with LTBI must consider the limitations of current diagnostic tests for LTBI, the risk of developing active TB disease, the potential adverse effects from chemoprophylactic therapy, and the importance of treatment adherence. When an individual has been diagnosed with LTBI and ac...

  15. New approaches for examining associations with latent categorical variables: applications to substance abuse and aggression.

    Science.gov (United States)

    Feingold, Alan; Tiberio, Stacey S; Capaldi, Deborah M

    2014-03-01

    Assessments of substance use behaviors often include categorical variables that are frequently related to other measures using logistic regression or chi-square analysis. When the categorical variable is latent (e.g., extracted from a latent class analysis [LCA]), classification of observations is often used to create an observed nominal variable from the latent one for use in a subsequent analysis. However, recent simulation studies have found that this classical 3-step analysis championed by the pioneers of LCA produces underestimates of the associations of latent classes with other variables. Two preferable but underused alternatives for examining such linkages-each of which is most appropriate under certain conditions-are (a) 3-step analysis, which corrects the underestimation bias of the classical approach, and (b) 1-step analysis. The purpose of this article is to dissuade researchers from conducting classical 3-step analysis and to promote the use of the 2 newer approaches that are described and compared. In addition, the applications of these newer models-for use when the independent, the dependent, or both categorical variables are latent-are illustrated through substantive analyses relating classes of substance abusers to classes of intimate partner aggressors.

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

    Science.gov (United States)

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

    2018-05-14

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

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

    Directory of Open Access Journals (Sweden)

    Yiqin Pan

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

  18. Resveratrol Reactivates Latent HIV through Increasing Histone Acetylation and Activating Heat Shock Factor 1.

    Science.gov (United States)

    Zeng, Xiaoyun; Pan, Xiaoyan; Xu, Xinfeng; Lin, Jian; Que, Fuchang; Tian, Yuanxin; Li, Lin; Liu, Shuwen

    2017-06-07

    The persistence of latent HIV reservoirs presents a significant challenge to viral eradication. Effective latency reversing agents (LRAs) based on "shock and kill" strategy are urgently needed. The natural phytoalexin resveratrol has been demonstrated to enhance HIV gene expression, although its mechanism remains unclear. In this study, we demonstrated that resveratrol was able to reactivate latent HIV without global T cell activation in vitro. Mode of action studies showed resveratrol-mediated reactivation from latency did not involve the activation of silent mating type information regulation 2 homologue 1 (SIRT1), which belonged to class-3 histone deacetylase (HDAC). However, latent HIV was reactivated by resveratrol mediated through increasing histone acetylation and activation of heat shock factor 1 (HSF1). Additionally, synergistic activation of the latent HIV reservoirs was observed under cotreatment with resveratrol and conventional LRAs. Collectively, this research reveals that resveratrol is a natural LRA and shows promise for HIV therapy.

  19. Latent semantics as cognitive components

    DEFF Research Database (Denmark)

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

    2010-01-01

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

  20. Large-scale weakly supervised object localization via latent category learning.

    Science.gov (United States)

    Chong Wang; Kaiqi Huang; Weiqiang Ren; Junge Zhang; Maybank, Steve

    2015-04-01

    Localizing objects in cluttered backgrounds is challenging under large-scale weakly supervised conditions. Due to the cluttered image condition, objects usually have large ambiguity with backgrounds. Besides, there is also a lack of effective algorithm for large-scale weakly supervised localization in cluttered backgrounds. However, backgrounds contain useful latent information, e.g., the sky in the aeroplane class. If this latent information can be learned, object-background ambiguity can be largely reduced and background can be suppressed effectively. In this paper, we propose the latent category learning (LCL) in large-scale cluttered conditions. LCL is an unsupervised learning method which requires only image-level class labels. First, we use the latent semantic analysis with semantic object representation to learn the latent categories, which represent objects, object parts or backgrounds. Second, to determine which category contains the target object, we propose a category selection strategy by evaluating each category's discrimination. Finally, we propose the online LCL for use in large-scale conditions. Evaluation on the challenging PASCAL Visual Object Class (VOC) 2007 and the large-scale imagenet large-scale visual recognition challenge 2013 detection data sets shows that the method can improve the annotation precision by 10% over previous methods. More importantly, we achieve the detection precision which outperforms previous results by a large margin and can be competitive to the supervised deformable part model 5.0 baseline on both data sets.

  1. Latent variable models are network models.

    Science.gov (United States)

    Molenaar, Peter C M

    2010-06-01

    Cramer et al. present an original and interesting network perspective on comorbidity and contrast this perspective with a more traditional interpretation of comorbidity in terms of latent variable theory. My commentary focuses on the relationship between the two perspectives; that is, it aims to qualify the presumed contrast between interpretations in terms of networks and latent variables.

  2. Learning Latent Vector Spaces for Product Search

    NARCIS (Netherlands)

    Van Gysel, C.; de Rijke, M.; Kanoulas, E.

    2016-01-01

    We introduce a novel latent vector space model that jointly learns the latent representations of words, e-commerce products and a mapping between the two without the need for explicit annotations. The power of the model lies in its ability to directly model the discriminative relation between

  3. Plutonium and latent nuclear proliferation

    International Nuclear Information System (INIS)

    Quester, G.H.

    1992-01-01

    A country producing nuclear electric power acquires an ability to produce atomic bombs quite easily and without taking many steps beyond that which would be perfectly normal for civilian purposes. The role of plutonium in the three fold list of the gains that must be sought in arms control formulated by Schelling and Halpevin are discussed. On the first, that we should seek to reduce the likelihood of war, it can be argued that plutonium reduces the likelihood in some cases. The second, that we should seek to reduce the destruction in war, is made worse by plutonium. On the third criterion, that we should seek to reduce the burdens in peacetime of everyone's being prepared for war, the situation is confusing and depends on the prospects for nuclear electrical power. It is concluded that latent capability to produce nuclear weapons may be sufficient without the need for actual detonations and deployment of bombs. (UK)

  4. Paternal Work Stress and Latent Profiles of Father-Infant Parenting Quality

    Science.gov (United States)

    Goodman, W. Benjamin; Crouter, Ann C.; Lanza, Stephanie T.; Cox, Martha J.; Vernon-Feagans, Lynne

    2011-01-01

    The current study used latent profile analysis (LPA) to examine the implications of fathers' experiences of work stress for paternal behaviors with infants across multiple dimensions of parenting in a sample of fathers living in nonmetropolitan communities (N = 492). LPA revealed five classes of fathers based on levels of social-affective…

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

    Science.gov (United States)

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

    2008-01-01

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

  6. Latent Culture as a Force for Change and the Change Process in Operation.

    Science.gov (United States)

    Banfield, Beryle

    The purpose of this study was to apply a theory of latent culture to describe the role of middle class black parents and students in effecting change in an elite educational organization and to use Schein's conceptual model of the Kurk Lewin paradigm of the change process (Unfreezing--Changing--Refreezing) to analyze this process over a three year…

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

    Science.gov (United States)

    Johnson, Ursula Y.; Hull, Darrell M.

    2014-01-01

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

  8. Dependent Classes

    DEFF Research Database (Denmark)

    Gasiunas, Vaidas; Mezini, Mira; Ostermann, Klaus

    2007-01-01

    of dependent classes and a machine-checked type soundness proof in Isabelle/HOL [29], the first of this kind for a language with virtual classes and path-dependent types. [29] T.Nipkow, L.C. Poulson, and M. Wenzel. Isabelle/HOL -- A Proof Assistant for Higher-Order Logic, volume 2283 of LNCS, Springer, 2002......Virtual classes allow nested classes to be refined in subclasses. In this way nested classes can be seen as dependent abstractions of the objects of the enclosing classes. Expressing dependency via nesting, however, has two limitations: Abstractions that depend on more than one object cannot...... be modeled and a class must know all classes that depend on its objects. This paper presents dependent classes, a generalization of virtual classes that expresses similar semantics by parameterization rather than by nesting. This increases expressivity of class variations as well as the flexibility...

  9. Latent class analysis suggests four distinct classes of complementary medicine users among women with breast cancer

    OpenAIRE

    Strizich, Garrett; Gammon, Marilie D.; Jacobson, Judith S.; Wall, Melanie; Abrahamson, Page; Bradshaw, Patrick T.; Terry, Mary Beth; Teitelbaum, Susan; Neugut, Alfred I.; Greenlee, Heather

    2015-01-01

    Background Breast cancer patients commonly report using >1 form of complementary and alternative medicine (CAM). However, few studies have attempted to analyze predictors and outcomes of multiple CAM modalities. We sought to group breast cancer patients by clusters of type and intensity of complementary and alternative medicine (CAM) use following diagnosis. Methods Detailed CAM use following breast cancer diagnosis was assessed in 2002?2003 among 764 female residents of Long Island, New York...

  10. Extraction of latent images from printed media

    Science.gov (United States)

    Sergeyev, Vladislav; Fedoseev, Victor

    2015-12-01

    In this paper we propose an automatic technology for extraction of latent images from printed media such as documents, banknotes, financial securities, etc. This technology includes image processing by adaptively constructed Gabor filter bank for obtaining feature images, as well as subsequent stages of feature selection, grouping and multicomponent segmentation. The main advantage of the proposed technique is versatility: it allows to extract latent images made by different texture variations. Experimental results showing performance of the method over another known system for latent image extraction are given.

  11. Glaucoma Medication Preferences among Glaucoma Specialists in Mexico

    OpenAIRE

    Lazcano-Gomez, Gabriel; Alvarez-Ascencio, Daniela; Haro-Zuno, Cindy; Turati-Acosta, Mauricio; Garcia-Huerta, Magdalena; Jimenez-Arroyo, Jesus; Castañeda-Diez, Rafael; Castillejos-Chevez, Armando; Gonzalez-Salinas, Roberto; Dominguez-Dueñas, Francisca; Jimenez-Roman, Jesus

    2017-01-01

    Aim To determine the glaucoma specialists’ preferences for the different brands of topical glaucoma medications available in Mexico. Materials and methods A web-based survey was sent to 150 board-certified glaucoma specialists in Mexico, with 14 questions related to brand preferences for all glaucoma medications available in Mexico. Participants were asked to select each glaucoma medication class by brand and to state the factors leading to their choice. Results Data from 111 (74%) glaucoma s...

  12. Heteroscedastic Latent Trait Models for Dichotomous Data.

    Science.gov (United States)

    Molenaar, Dylan

    2015-09-01

    Effort has been devoted to account for heteroscedasticity with respect to observed or latent moderator variables in item or test scores. For instance, in the multi-group generalized linear latent trait model, it could be tested whether the observed (polychoric) covariance matrix differs across the levels of an observed moderator variable. In the case that heteroscedasticity arises across the latent trait itself, existing models commonly distinguish between heteroscedastic residuals and a skewed trait distribution. These models have valuable applications in intelligence, personality and psychopathology research. However, existing approaches are only limited to continuous and polytomous data, while dichotomous data are common in intelligence and psychopathology research. Therefore, in present paper, a heteroscedastic latent trait model is presented for dichotomous data. The model is studied in a simulation study, and applied to data pertaining alcohol use and cognitive ability.

  13. Latent Heat Storage Through Phase Change Materials

    Indian Academy of Sciences (India)

    IAS Admin

    reducing storage volume for different materials. The examples are numerous: ... Latent heat is an attractive way to store solar heat as it provides high energy storage density, .... Maintenance of the PCM treated fabric is easy. The melted PCM.

  14. New Treatment Regimen for Latent Tuberculosis Infection

    Centers for Disease Control (CDC) Podcasts

    In this podcast, Dr. Kenneth Castro, Director of the Division of Tuberculosis Elimination, discusses the December 9, 2011 CDC guidelines for the use of a new regimen for the treatment of persons with latent tuberculosis infection.

  15. Latent variables and route choice behavior

    DEFF Research Database (Denmark)

    Prato, Carlo Giacomo; Bekhor, Shlomo; Pronello, Cristina

    2012-01-01

    In the last decade, a broad array of disciplines has shown a general interest in enhancing discrete choice models by considering the incorporation of psychological factors affecting decision making. This paper provides insight into the comprehension of the determinants of route choice behavior...... and bound algorithm. A hybrid model consists of measurement equations, which relate latent variables to measurement indicators and utilities to choice indicators, and structural equations, which link travelers’ observable characteristics to latent variables and explanatory variables to utilities. Estimation...

  16. UNSOLVED AND LATENT CRIME: DIFFERENCES AND SIMILARITIES

    Directory of Open Access Journals (Sweden)

    Mikhail Kleymenov

    2017-01-01

    Full Text Available УДК 343Purpose of the article is to study the specific legal and informational nature of the unsolved crime in comparison with the phenomenon of delinquency, special study and analysis to improve the efficiency of law enforcement.Methods of research are abstract-logical, systematic, statistical, study of documents. The main results of research. Unsolved crime has specific legal, statistical and informational na-ture as the crime phenomenon, which is expressed in cumulative statistical population of unsolved crimes. An array of unsolved crimes is the sum of the number of acts, things of which is suspended and not terminated. The fault of the perpetrator in these cases is not proven, they are not considered by the court, it is not a conviction. Unsolved crime must be registered. Latent crime has a different informational nature. The main symptom of latent crimes is the uncertainty for the subjects of law enforcement, which delegated functions of identification, registration and accounting. Latent crime is not recorded. At the same time, there is a "border" area between the latent and unsolved crimes, which includes covered from the account of the crime. In modern Russia the majority of crimes covered from accounting by passing the decision about refusal in excitation of criminal case. Unsolved crime on their criminogenic consequences represents a significant danger to the public is higher compared to latent crime.It is conducted in the article a special analysis of the differences and similarities in the unsolved latent crime for the first time in criminological literature.The analysis proves the need for radical changes in the current Russian assessment of the state of crime and law enforcement to solve crimes. The article argues that an unsolved crime is a separate and, in contrast to latent crime, poorly understood phenomenon. However unsolved latent crime and have common features and areas of interaction.

  17. Exposing Latent Information in Folksonomies for Reasoning

    Science.gov (United States)

    2010-01-14

    1.73 $.") http://www.w3.org/2006/07/SWD/ SKOS /reference/20081001/ Spiteri, L.F. (2007) "The structure and form of folksonomy tags: The road to the...Exposing Latent Information in Folksonomies for Reasoning January 14, 2010 Sponsored by Defense Advanced Research Projects Agency (DOD...DATES COVERED (From - To! 4/14/2009-12/23/2009 4. TITLE AND SUBTITLE Exposing Latent Information in Folksonomies for Reasoning Sa. CONTRACT

  18. Do recognizable lifetime eating disorder phenotypes naturally occur in a culturally asian population? A combined latent profile and taxometric approach.

    Science.gov (United States)

    Thomas, Jennifer J; Eddy, Kamryn T; Ruscio, John; Ng, King Lam; Casale, Kristen E; Becker, Anne E; Lee, Sing

    2015-05-01

    We examined whether empirically derived eating disorder (ED) categories in Hong Kong Chinese patients (N = 454) would be consistent with recognizable lifetime ED phenotypes derived from latent structure models of European and American samples. We performed latent profile analysis (LPA) using indicator variables from data collected during routine assessment, and then applied taxometric analysis to determine whether latent classes were qualitatively versus quantitatively distinct. Latent profile analysis identified four classes: (i) binge/purge (47%); (ii) non-fat-phobic low-weight (34%); (iii) fat-phobic low-weight (12%); and (iv) overweight disordered eating (6%). Taxometric analysis identified qualitative (categorical) distinctions between the binge/purge and non-fat-phobic low-weight classes, and also between the fat-phobic and non-fat-phobic low-weight classes. Distinctions between the fat-phobic low-weight and binge/purge classes were indeterminate. Empirically derived categories in Hong Kong showed recognizable correspondence with recognizable lifetime ED phenotypes. Although taxometric findings support two distinct classes of low weight EDs, LPA findings also support heterogeneity among non-fat-phobic individuals. Copyright © 2015 John Wiley & Sons, Ltd and Eating Disorders Association.

  19. Cutting Classes

    Science.gov (United States)

    Hacker, Andrew

    1976-01-01

    Provides critical reviews of three books, "The Political Economy of Social Class", "Ethnicity: Theory and Experience," and "Ethnicity in the United States," focusing on the political economy of social class and ethnicity. (Author/AM)

  20. Latent Cognitive Phenotypes in De Novo Parkinson's Disease: A Person-Centered Approach.

    Science.gov (United States)

    LaBelle, Denise R; Walsh, Ryan R; Banks, Sarah J

    2017-08-01

    Cognitive impairment is an important aspect of Parkinson's disease (PD), but there is considerable heterogeneity in its presentation. This investigation aims to identify and characterize latent cognitive phenotypes in early PD. Latent class analysis, a data-driven, person-centered, cluster analysis was performed on cognitive data from the Parkinson's Progressive Markers Initiative baseline visit. This analytic method facilitates identification of naturally occurring endophenotypes. Resulting classes were compared across biomarker, symptom, and demographic data. Six cognitive phenotypes were identified. Three demonstrated consistent performance across indicators, representing poor ("Weak-Overall"), average ("Typical-Overall"), and strong ("Strong-Overall") cognition. The remaining classes demonstrated unique patterns of cognition, characterized by "Strong-Memory," "Weak-Visuospatial," and "Amnestic" profiles. The Amnestic class evidenced greater tremor severity and anosmia, but was unassociated with biomarkers linked with Alzheimer's disease. The Weak-Overall class was older and reported more non-motor features associated with cognitive decline, including anxiety, depression, autonomic dysfunction, anosmia, and REM sleep behaviors. The Strong-Overall class was younger, more female, and reported less dysautonomia and anosmia. Classes were unrelated to disease duration, functional independence, or available biomarkers. Latent cognitive phenotypes with focal patterns of impairment were observed in recently diagnosed individuals with PD. Cognitive profiles were found to be independent of traditional biomarkers and motoric indices of disease progression. Only globally impaired class was associated with previously reported indicators of cognitive decline, suggesting this group may drive the effects reported in studies using variable-based analysis. Longitudinal and neuroanatomical characterization of classes will yield further insight into the evolution of cognitive

  1. Heterogeneity in patterns of DSM-5 posttraumatic stress disorder and depression symptoms: Latent profile analyses.

    Science.gov (United States)

    Contractor, Ateka A; Roley-Roberts, Michelle E; Lagdon, Susan; Armour, Cherie

    2017-04-01

    Posttraumatic stress disorder (PTSD) and depression co-occur frequently following the experience of potentially traumatizing events (PTE; Morina et al., 2013). A person-centered approach to discern heterogeneous patterns of such co-occurring symptoms is recommended (Galatzer-Levy and Bryant, 2013). We assessed heterogeneity in PTSD and depression symptomatology; and subsequently assessed relations between class membership with psychopathology constructs (alcohol use, distress tolerance, dissociative experiences). The sample consisted of 268 university students who had experienced a PTE and susequently endorsed clinical levels of PTSD or depression severity. Latent profile analyses (LPA) was used to identify the best-fitting class solution accouring to recommended fit indices (Nylund et al., 2007a); and the effects of covariates was analyzed using a 3-step approach (Vermunt, 2010). Results of the LPA indicated an optimal 3-class solutions: high severity (Class 2), lower PTSD-higher depression (Class 1), and higher PTSD-lower depression (Class 3). Covariates of distress tolerance, and different kinds of dissociative experiences differentiated the latent classes. Use of self-report measure could lead to response biases; and the specific nature of the sample limits generalizability of results. We found evidence for a depressive subtype of PTSD differentiated from other classes in terms of lower distress tolerance and greater dissociative experiences. Thus, transdiagnostic treatment protocols may be most beneficial for these latent class members. Further, the distinctiveness of PTSD and depression at comparatively lower levels of PTSD severity was supported (mainly in terms of distress tolerance abilities); hence supporting the current classification system placement of these disorders. Copyright © 2017 Elsevier B.V. All rights reserved.

  2. The Latent Structure of Dictionaries.

    Science.gov (United States)

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

    2016-07-01

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

  3. September 1985 Mexico City, Mexico Images

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The magnitude 8.1 earthquake occurred off the Pacific coast of Mexico. The damage was concentrated in a 25 square km area of Mexico City, 350 km from the epicenter....

  4. Reliability measures in item response theory: manifest versus latent correlation functions.

    Science.gov (United States)

    Milanzi, Elasma; Molenberghs, Geert; Alonso, Ariel; Verbeke, Geert; De Boeck, Paul

    2015-02-01

    For item response theory (IRT) models, which belong to the class of generalized linear or non-linear mixed models, reliability at the scale of observed scores (i.e., manifest correlation) is more difficult to calculate than latent correlation based reliability, but usually of greater scientific interest. This is not least because it cannot be calculated explicitly when the logit link is used in conjunction with normal random effects. As such, approximations such as Fisher's information coefficient, Cronbach's α, or the latent correlation are calculated, allegedly because it is easy to do so. Cronbach's α has well-known and serious drawbacks, Fisher's information is not meaningful under certain circumstances, and there is an important but often overlooked difference between latent and manifest correlations. Here, manifest correlation refers to correlation between observed scores, while latent correlation refers to correlation between scores at the latent (e.g., logit or probit) scale. Thus, using one in place of the other can lead to erroneous conclusions. Taylor series based reliability measures, which are based on manifest correlation functions, are derived and a careful comparison of reliability measures based on latent correlations, Fisher's information, and exact reliability is carried out. The latent correlations are virtually always considerably higher than their manifest counterparts, Fisher's information measure shows no coherent behaviour (it is even negative in some cases), while the newly introduced Taylor series based approximations reflect the exact reliability very closely. Comparisons among the various types of correlations, for various IRT models, are made using algebraic expressions, Monte Carlo simulations, and data analysis. Given the light computational burden and the performance of Taylor series based reliability measures, their use is recommended. © 2014 The British Psychological Society.

  5. Forensic Discrimination of Latent Fingerprints Using Laser-Induced Breakdown Spectroscopy (LIBS) and Chemometric Approaches.

    Science.gov (United States)

    Yang, Jun-Ho; Yoh, Jack J

    2018-01-01

    A novel technique is reported for separating overlapping latent fingerprints using chemometric approaches that combine laser-induced breakdown spectroscopy (LIBS) and multivariate analysis. The LIBS technique provides the capability of real time analysis and high frequency scanning as well as the data regarding the chemical composition of overlapping latent fingerprints. These spectra offer valuable information for the classification and reconstruction of overlapping latent fingerprints by implementing appropriate statistical multivariate analysis. The current study employs principal component analysis and partial least square methods for the classification of latent fingerprints from the LIBS spectra. This technique was successfully demonstrated through a classification study of four distinct latent fingerprints using classification methods such as soft independent modeling of class analogy (SIMCA) and partial least squares discriminant analysis (PLS-DA). The novel method yielded an accuracy of more than 85% and was proven to be sufficiently robust. Furthermore, through laser scanning analysis at a spatial interval of 125 µm, the overlapping fingerprints were reconstructed as separate two-dimensional forms.

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

    Science.gov (United States)

    BOYSAN, Murat

    2014-01-01

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

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

    Science.gov (United States)

    Ward, Elizabeth Kennedy

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

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

    Science.gov (United States)

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

    2016-09-01

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

  9. Learning Latent Structure in Complex Networks

    DEFF Research Database (Denmark)

    Mørup, Morten; Hansen, Lars Kai

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

  10. A Multinomial Probit Model with Latent Factors

    DEFF Research Database (Denmark)

    Piatek, Rémi; Gensowski, Miriam

    2017-01-01

    be meaningfully linked to an economic model. We provide sufficient conditions that make this structure identified and interpretable. For inference, we design a Markov chain Monte Carlo sampler based on marginal data augmentation. A simulation exercise shows the good numerical performance of our sampler......We develop a parametrization of the multinomial probit model that yields greater insight into the underlying decision-making process, by decomposing the error terms of the utilities into latent factors and noise. The latent factors are identified without a measurement system, and they can...

  11. Mexico; Mexique

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2003-06-01

    This document summarizes the key energy data for Mexico: 1 - energy organizations and policy: Ministry of energy (SENER), Comision Reguladora de Energia (CRE), Ministry of Finances, Ministry of trade and industrial development (SECOFI), national commission for energy savings (CONAE); 2 - companies: federal commission of electricity (CFE), Minera Carbonifera Rio Escondido (MICARE - coal), Pemex (petroleum); 3 - energy production: resources, electric power, petroleum, natural gas; 4 - energy consumption; 5 - stakes and perspectives. Some economic and energy indicators are summarized in a series of tables: general indicators, supply indicators (reserves, refining and electric capacity, energy production, foreign trade), demand indicators (consumption trends, end use, energy independence, energy efficiency, CO{sub 2} emissions), energy status per year and per energy source. (J.S.)

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

    OpenAIRE

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

    2009-01-01

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

  13. Anxiety sensitivity class membership moderates the effects of pre-quit reduction in anxiety sensitivity on quit-day tobacco craving

    NARCIS (Netherlands)

    Bakhshaie, J.; Zvolensky, M.J.; Langdon, K.J.; Leventhal, A.M.; Smits, J.A.J.; Allan, N.; Schmidt, N.B.

    2016-01-01

    Background: Although anxiety sensitivity has been primarily conceptualized as a dimensional latent construct, empirical evidence suggests that it also maintains a latent class structure, reflecting low-, moderate-, and high-risk underlying classes. The present study sought to explore whether these

  14. A Discrete Latent State Approach to Diagnostic Testing. Final Report on Contract Number N00014-81-K-0564.

    Science.gov (United States)

    Paulson, James A.

    This paper reports on a project which has developed the general latent class model as a framework for representation of item responses. This framework can be used to represent data in applications such as mastery tests and other kinds of achievement tests, where there is reason to believe that current foundations are deficient. Methods of…

  15. Variable importance in latent variable regression models

    NARCIS (Netherlands)

    Kvalheim, O.M.; Arneberg, R.; Bleie, O.; Rajalahti, T.; Smilde, A.K.; Westerhuis, J.A.

    2014-01-01

    The quality and practical usefulness of a regression model are a function of both interpretability and prediction performance. This work presents some new graphical tools for improved interpretation of latent variable regression models that can also assist in improved algorithms for variable

  16. Detection of latent prints by Raman imaging

    Science.gov (United States)

    Lewis, Linda Anne [Andersonville, TN; Connatser, Raynella Magdalene [Knoxville, TN; Lewis, Sr., Samuel Arthur

    2011-01-11

    The present invention relates to a method for detecting a print on a surface, the method comprising: (a) contacting the print with a Raman surface-enhancing agent to produce a Raman-enhanced print; and (b) detecting the Raman-enhanced print using a Raman spectroscopic method. The invention is particularly directed to the imaging of latent fingerprints.

  17. Statistical inference based on latent ability estimates

    NARCIS (Netherlands)

    Hoijtink, H.J.A.; Boomsma, A.

    The quality of approximations to first and second order moments (e.g., statistics like means, variances, regression coefficients) based on latent ability estimates is being discussed. The ability estimates are obtained using either the Rasch, oi the two-parameter logistic model. Straightforward use

  18. Residual Structures in Latent Growth Curve Modeling

    Science.gov (United States)

    Grimm, Kevin J.; Widaman, Keith F.

    2010-01-01

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

  19. Forensic Chemistry: The Revelation of Latent Fingerprints

    Science.gov (United States)

    Friesen, J. Brent

    2015-01-01

    The visualization of latent fingerprints often involves the use of a chemical substance that creates a contrast between the fingerprint residues and the surface on which the print was deposited. The chemical-aided visualization techniques can be divided into two main categories: those that chemically react with the fingerprint residue and those…

  20. Endogenous Opioid-Masked Latent Pain Sensitization

    DEFF Research Database (Denmark)

    Pereira, Manuel P; Donahue, Renee R; Dahl, Jørgen B

    2015-01-01

    UNLABELLED: Following the resolution of a severe inflammatory injury in rodents, administration of mu-opioid receptor inverse agonists leads to reinstatement of pain hypersensitivity. The mechanisms underlying this form of latent pain sensitization (LS) likely contribute to the development of chr...

  1. Prediction of incidence and stability of alcohol use disorders by latent internalizing psychopathology risk profiles in adolescence and young adulthood.

    Science.gov (United States)

    Behrendt, Silke; Bühringer, Gerhard; Höfler, Michael; Lieb, Roselind; Beesdo-Baum, Katja

    2017-10-01

    Comorbid internalizing mental disorders in alcohol use disorders (AUD) can be understood as putative independent risk factors for AUD or as expressions of underlying shared psychopathology vulnerabilities. However, it remains unclear whether: 1) specific latent internalizing psychopathology risk-profiles predict AUD-incidence and 2) specific latent internalizing comorbidity-profiles in AUD predict AUD-stability. To investigate baseline latent internalizing psychopathology risk profiles as predictors of subsequent AUD-incidence and -stability in adolescents and young adults. Data from the prospective-longitudinal EDSP study (baseline age 14-24 years) were used. The study-design included up to three follow-up assessments in up to ten years. DSM-IV mental disorders were assessed with the DIA-X/M-CIDI. To investigate risk-profiles and their associations with AUD-outcomes, latent class analysis with auxiliary outcome variables was applied. AUD-incidence: a 4-class model (N=1683) was identified (classes: normative-male [45.9%], normative-female [44.2%], internalizing [5.3%], nicotine dependence [4.5%]). Compared to the normative-female class, all other classes were associated with a higher risk of subsequent incident alcohol dependence (p<0.05). AUD-stability: a 3-class model (N=1940) was identified with only one class (11.6%) with high probabilities for baseline AUD. This class was further characterized by elevated substance use disorder (SUD) probabilities and predicted any subsequent AUD (OR 8.5, 95% CI 5.4-13.3). An internalizing vulnerability may constitute a pathway to AUD incidence in adolescence and young adulthood. In contrast, no indication for a role of internalizing comorbidity profiles in AUD-stability was found, which may indicate a limited importance of such profiles - in contrast to SUD-related profiles - in AUD stability. Copyright © 2017 Elsevier B.V. All rights reserved.

  2. Incorporating direct marketing activity into latent attrition models

    NARCIS (Netherlands)

    Schweidel, David A.; Knox, George

    2013-01-01

    When defection is unobserved, latent attrition models provide useful insights about customer behavior and accurate forecasts of customer value. Yet extant models ignore direct marketing efforts. Response models incorporate the effects of direct marketing, but because they ignore latent attrition,

  3. Word classes

    DEFF Research Database (Denmark)

    Rijkhoff, Jan

    2007-01-01

    in grammatical descriptions of some 50 languages, which together constitute a representative sample of the world’s languages (Hengeveld et al. 2004: 529). It appears that there are both quantitative and qualitative differences between word class systems of individual languages. Whereas some languages employ...... a parts-of-speech system that includes the categories Verb, Noun, Adjective and Adverb, other languages may use only a subset of these four lexical categories. Furthermore, quite a few languages have a major word class whose members cannot be classified in terms of the categories Verb – Noun – Adjective...... – Adverb, because they have properties that are strongly associated with at least two of these four traditional word classes (e.g. Adjective and Adverb). Finally, this article discusses some of the ways in which word class distinctions interact with other grammatical domains, such as syntax and morphology....

  4. Class size versus class composition

    DEFF Research Database (Denmark)

    Jones, Sam

    Raising schooling quality in low-income countries is a pressing challenge. Substantial research has considered the impact of cutting class sizes on skills acquisition. Considerably less attention has been given to the extent to which peer effects, which refer to class composition, also may affect...... bias from omitted variables, the preferred IV results indicate considerable negative effects due to larger class sizes and larger numbers of overage-for-grade peers. The latter, driven by the highly prevalent practices of grade repetition and academic redshirting, should be considered an important...

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

    Science.gov (United States)

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

    2015-12-01

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

  6. New Mexico Parks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This dataset provides an initial version of the locations of parks in New Mexico, in point form, with limited attributes, compiled using available data from a...

  7. New Mexico State Parks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This dataset provides an initial version of the generalized physical boundaries of New Mexico State Parks, in polygonal form with limited attributes, compiled using...

  8. New Mexico Ghost Towns

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This data provides locations and non-spatial attributes of many ghost towns in the State of New Mexico, compiled from various sources. Locations provided with...

  9. SANDIA MOUNTAIN WILDERNESS, NEW MEXICO.

    Science.gov (United States)

    Hedlund, D.C.; Kness, R.F.

    1984-01-01

    Geologic and mineral-resource investigations in the Sandia Mountains in New Mexico indicate that a small part of the area has a probable mineral-resource potential. Most of the mineral occurrences are small barite-fluorite veins that occur along faults on the eastern slope of the range. The barite veins in the Landsend area and in the Tunnel Spring area are classed as having a probable mineral-resource potential. Fluorite veins which occur at the La Luz mine contain silver-bearing galeana and the area near this mine is regarded as having a probable resource potential for silver. No energy resources were identified in this study.

  10. English Teaching in Mexico.

    Science.gov (United States)

    Salazar, Denise

    2002-01-01

    Discusses teaching English in Mexico, a country with important social, cultural, and economic ties to the United States. Looks at the various English teaching situations as well as teacher education for teachers in Mexico. Concludes that the English teaching situation in Mexico reflects great diversity and growth, and that the knowledge of English…

  11. Psychology in Mexico

    Science.gov (United States)

    Ruiz, Eleonora Rubio

    2011-01-01

    The first formal psychology course taught in Mexico was in 1896 at Mexico's National University; today, National Autonomous University of Mexico (UNAM in Spanish). The modern psychology from Europe and the US in the late 19th century were the primary influences of Mexican psychology, as well as psychoanalysis and both clinical and experimental…

  12. Modeling Nonlinear Change via Latent Change and Latent Acceleration Frameworks: Examining Velocity and Acceleration of Growth Trajectories

    Science.gov (United States)

    Grimm, Kevin; Zhang, Zhiyong; Hamagami, Fumiaki; Mazzocco, Michele

    2013-01-01

    We propose the use of the latent change and latent acceleration frameworks for modeling nonlinear growth in structural equation models. Moving to these frameworks allows for the direct identification of "rates of change" and "acceleration" in latent growth curves--information available indirectly through traditional growth…

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

    Science.gov (United States)

    Johnson, Ursula Yvette

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

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

    Science.gov (United States)

    Terhune, Devin Blair

    2015-05-01

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

  15. Latent factors and route choice behaviour

    DEFF Research Database (Denmark)

    Prato, Carlo Giacomo

    . A reliable dataset was prepared through measures of internal consistency and sampling adequacy, and data were analyzed with a proper application of factor analysis to the route choice context. For the dataset obtained from the survey, six latent constructs affecting driver behaviour were extracted and scores...... on each factor for each survey participant were calculated. Path generation algorithms were examined with respect to observed behaviour, through a measure of reproduction with deterministic techniques of the routes indicated in the answers to the survey. Results presented evidence that the majority...... and Link Nested Logit. Estimates were produced from model specifications that considered level-of-service, label and facility dummy variables. Moreover, a modelling framework was designed to represent drivers’ choices as affected by the latent constructs extracted with factor analysis. Previous experience...

  16. Social Classes

    DEFF Research Database (Denmark)

    Aktor, Mikael

    2018-01-01

    . Although this social structure was ideal in nature and not equally confirmed in other genres of ancient and medieval literature, it has nevertheless had an immense impact on Indian society. The chapter presents an overview of the system with its three privileged classes, the Brahmins, the Kṣatriyas......The notions of class (varṇa) and caste (jāti) run through the dharmaśāstra literature (i.e. Hindu Law Books) on all levels. They regulate marriage, economic transactions, work, punishment, penance, entitlement to rituals, identity markers like the sacred thread, and social interaction in general...

  17. Exploring galaxy evolution with latent space walks

    Science.gov (United States)

    Schawinski, Kevin; Turp, Dennis; Zhang, Ce

    2018-01-01

    We present a new approach using artificial intelligence to perform data-driven forward models of astrophysical phenomena. We describe how a variational autoencoder can be used to encode galaxies to latent space, independently manipulate properties such as the specific star formation rate, and return it to real space. Such transformations can be used for forward modeling phenomena using data as the only constraints. We demonstrate the utility of this approach using the question of the quenching of star formation in galaxies.

  18. New Treatment Regimen for Latent Tuberculosis Infection

    Centers for Disease Control (CDC) Podcasts

    2012-03-15

    In this podcast, Dr. Kenneth Castro, Director of the Division of Tuberculosis Elimination, discusses the December 9, 2011 CDC guidelines for the use of a new regimen for the treatment of persons with latent tuberculosis infection.  Created: 3/15/2012 by National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention (NCHHSTP).   Date Released: 3/15/2012.

  19. Barcelona - Talent Latent 09 / Ahto Sooaru

    Index Scriptorium Estoniae

    Sooaru, Ahto

    2010-01-01

    Fotonäitusest "Talent Latent 09" Barcelonas Arts Santa Monica kunstikeskuses. Loetletud näitusel eksponeeritud fotode autorid. Pikemalt Rafael Milach'i (sünd. 1978), Lucia Ganieva, Javier Marquerie Thomas'i (sünd. 1986), Amaury da Cunha (sünd. 1976) töödest. Lühidalt ka teistest näitustest Arts Santa Monica kunstikeskuses

  20. Farmer preference for improved corn seeds in Chiapas, Mexico: A choice experiment approach

    International Nuclear Information System (INIS)

    Sánchez-Toledano, Blanca I.; Kallas, Zein; Gil-Roig, José M.

    2017-01-01

    Appropriate technologies must be developed for adoption of improved seeds based on the farmers’ preferences and needs. Our research identified the farmers’ willingness to pay (WTP) as a key determinant for selecting the improved varieties of maize seeds and landraces in Chiapas, Mexico. This work also analyzed the farmers’ observed heterogeneity on the basis of their socio-economic characteristics. Data were collected using a semi-structured questionnaire from 200 farmers. A proportional choice experiment approach was applied using a proportional choice variable, where farmers were asked to state the percentage of preference for different alternative varieties in a choice set. The generalized multinomial logit model in WTP-space approach was used. The results suggest that the improved seed varieties are preferred over the Creole alternatives, thereby ensuring higher yields, resistance to diseases, and larger ear size. For the preference heterogeneity analyses, a latent class model was applied. Three types of farmers were identified: innovators (60.5%), transition farmers (29.4%), and conservative farmers (10%). An understanding of farmers’ preferences is useful in designing agricultural policies and creati

  1. Farmer preference for improved corn seeds in Chiapas, Mexico: A choice experiment approach

    Directory of Open Access Journals (Sweden)

    Blanca I. Sánchez-Toledano

    2017-12-01

    Full Text Available Appropriate technologies must be developed for adoption of improved seeds based on the farmers’ preferences and needs. Our research identified the farmers’ willingness to pay (WTP as a key determinant for selecting the improved varieties of maize seeds and landraces in Chiapas, Mexico. This work also analyzed the farmers’ observed heterogeneity on the basis of their socio-economic characteristics. Data were collected using a semi-structured questionnaire from 200 farmers. A proportional choice experiment approach was applied using a proportional choice variable, where farmers were asked to state the percentage of preference for different alternative varieties in a choice set. The generalized multinomial logit model in WTP-space approach was used. The results suggest that the improved seed varieties are preferred over the Creole alternatives, thereby ensuring higher yields, resistance to diseases, and larger ear size. For the preference heterogeneity analyses, a latent class model was applied. Three types of farmers were identified: innovators (60.5%, transition farmers (29.4%, and conservative farmers (10%. An understanding of farmers’ preferences is useful in designing agricultural policies and creating pricing and marketing strategies for the dissemination of quality seeds.

  2. Farmer preference for improved corn seeds in Chiapas, Mexico: A choice experiment approach

    Energy Technology Data Exchange (ETDEWEB)

    Sánchez-Toledano, Blanca I.; Kallas, Zein; Gil-Roig, José M.

    2017-07-01

    Appropriate technologies must be developed for adoption of improved seeds based on the farmers’ preferences and needs. Our research identified the farmers’ willingness to pay (WTP) as a key determinant for selecting the improved varieties of maize seeds and landraces in Chiapas, Mexico. This work also analyzed the farmers’ observed heterogeneity on the basis of their socio-economic characteristics. Data were collected using a semi-structured questionnaire from 200 farmers. A proportional choice experiment approach was applied using a proportional choice variable, where farmers were asked to state the percentage of preference for different alternative varieties in a choice set. The generalized multinomial logit model in WTP-space approach was used. The results suggest that the improved seed varieties are preferred over the Creole alternatives, thereby ensuring higher yields, resistance to diseases, and larger ear size. For the preference heterogeneity analyses, a latent class model was applied. Three types of farmers were identified: innovators (60.5%), transition farmers (29.4%), and conservative farmers (10%). An understanding of farmers’ preferences is useful in designing agricultural policies and creati.

  3. Birthing Classes

    Science.gov (United States)

    ... management options. Breastfeeding basics. Caring for baby at home. Birthing classes are not just for new parents, though. ... midwife. Postpartum care. Caring for your baby at home, including baby first aid. Lamaze One of the most popular birthing techniques in the U.S., Lamaze has been around ...

  4. Incorporating Latent Variables into Discrete Choice Models - A Simultaneous Estimation Approach Using SEM Software

    Directory of Open Access Journals (Sweden)

    Dirk Temme

    2008-12-01

    Full Text Available Integrated choice and latent variable (ICLV models represent a promising new class of models which merge classic choice models with the structural equation approach (SEM for latent variables. Despite their conceptual appeal, applications of ICLV models in marketing remain rare. We extend previous ICLV applications by first estimating a multinomial choice model and, second, by estimating hierarchical relations between latent variables. An empirical study on travel mode choice clearly demonstrates the value of ICLV models to enhance the understanding of choice processes. In addition to the usually studied directly observable variables such as travel time, we show how abstract motivations such as power and hedonism as well as attitudes such as a desire for flexibility impact on travel mode choice. Furthermore, we show that it is possible to estimate such a complex ICLV model with the widely available structural equation modeling package Mplus. This finding is likely to encourage more widespread application of this appealing model class in the marketing field.

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

    Science.gov (United States)

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

    2010-10-01

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

  6. Martin Parr in Mexico: Does Photographic Style Translate?

    Directory of Open Access Journals (Sweden)

    Timothy R. Gleason

    2011-11-01

    Full Text Available This study analyzes Martin Parr’s 2006 photobook, Mexico. Parr is a British documentary photographer best known for a direct photographic style that reflects upon “Englishness.”Mexico is his attempt to understand this foreign country via his camera. Mexico, as a research subject, is not a problem to solve but an opportunity to understand a photographer’s work. Parr’s Mexico photography (technique, photographic content, and interest in globalization, economics, and culture is compared to his previous work to explain how Parr uses fashion and icons to represent a culture or class. This article argues Parr’s primary subjects, heads/hats, food, and Christs, are photographed without excessive aesthetic pretensions so that the thrust of Parr’s message about globalization can be more evident:Mexico maintains many of its traditions and icons while adopting American brands.

  7. Bayesian modeling of ChIP-chip data using latent variables.

    KAUST Repository

    Wu, Mingqi

    2009-10-26

    BACKGROUND: The ChIP-chip technology has been used in a wide range of biomedical studies, such as identification of human transcription factor binding sites, investigation of DNA methylation, and investigation of histone modifications in animals and plants. Various methods have been proposed in the literature for analyzing the ChIP-chip data, such as the sliding window methods, the hidden Markov model-based methods, and Bayesian methods. Although, due to the integrated consideration of uncertainty of the models and model parameters, Bayesian methods can potentially work better than the other two classes of methods, the existing Bayesian methods do not perform satisfactorily. They usually require multiple replicates or some extra experimental information to parametrize the model, and long CPU time due to involving of MCMC simulations. RESULTS: In this paper, we propose a Bayesian latent model for the ChIP-chip data. The new model mainly differs from the existing Bayesian models, such as the joint deconvolution model, the hierarchical gamma mixture model, and the Bayesian hierarchical model, in two respects. Firstly, it works on the difference between the averaged treatment and control samples. This enables the use of a simple model for the data, which avoids the probe-specific effect and the sample (control/treatment) effect. As a consequence, this enables an efficient MCMC simulation of the posterior distribution of the model, and also makes the model more robust to the outliers. Secondly, it models the neighboring dependence of probes by introducing a latent indicator vector. A truncated Poisson prior distribution is assumed for the latent indicator variable, with the rationale being justified at length. CONCLUSION: The Bayesian latent method is successfully applied to real and ten simulated datasets, with comparisons with some of the existing Bayesian methods, hidden Markov model methods, and sliding window methods. The numerical results indicate that the

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

    Science.gov (United States)

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

    2013-06-01

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

  9. Coding Class

    DEFF Research Database (Denmark)

    Ejsing-Duun, Stine; Hansbøl, Mikala

    Denne rapport rummer evaluering og dokumentation af Coding Class projektet1. Coding Class projektet blev igangsat i skoleåret 2016/2017 af IT-Branchen i samarbejde med en række medlemsvirksomheder, Københavns kommune, Vejle Kommune, Styrelsen for IT- og Læring (STIL) og den frivillige forening...... Coding Pirates2. Rapporten er forfattet af Docent i digitale læringsressourcer og forskningskoordinator for forsknings- og udviklingsmiljøet Digitalisering i Skolen (DiS), Mikala Hansbøl, fra Institut for Skole og Læring ved Professionshøjskolen Metropol; og Lektor i læringsteknologi, interaktionsdesign......, design tænkning og design-pædagogik, Stine Ejsing-Duun fra Forskningslab: It og Læringsdesign (ILD-LAB) ved Institut for kommunikation og psykologi, Aalborg Universitet i København. Vi har fulgt og gennemført evaluering og dokumentation af Coding Class projektet i perioden november 2016 til maj 2017...

  10. 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.

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

    Science.gov (United States)

    Armour, Cherie; Elklit, Ask; Shevlin, Mark

    2011-01-01

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

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

    Science.gov (United States)

    Armour, Cherie; Elklit, Ask; Shevlin, Mark

    2011-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Cherie Armour

    2011-12-01

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

  14. Aspects of physicochemical methods for the detection of latent fingerprints

    International Nuclear Information System (INIS)

    Knowles, A.M.

    1978-01-01

    This paper reviews physicochemical methods of detecting latent finger-prints on a wide range of materials commonly found at the scene of a crime, with particular emphasis placed on the newer autoradiographic techniques. This is set against a description of studies on the fundamental nature of the latent fingerprint and its host substrate, with a brief review of the history of reagents used in latent fingerprint examination. (author)

  15. Governability in Contemporary Mexico

    Directory of Open Access Journals (Sweden)

    Leonardo Curzio Gutiérrez

    1998-04-01

    Full Text Available Given the difficulties to establish a concept of governability and the frequent ideological usage of the term, it is much more operative to turn to the principle of governability, in the broad sense, which supports itself on five pillars: the political legitimacy of the government, the governmental efficiency to attend to the demands of society, the existence of shared social project, the agreement with the principle special interest groups, and international viability. The analysis of the structure and relevance of these five points during the long period of political transition that Mexico underwent between 1988 and 1997 shows how it was possible for this country to play off certain factors against each other in order to secure governability and safeguard against the consequences of any resultant imbalances. Between 1998-1993, the government of Salinas de Gotari based itself on the viability of a neoliberal project within an international context, and on this projectís attention to domestic demands as well as on the governmentís pact with elites. Institutional integration and legitimacy made up, then, for a process of discreet liberalization and the lack of democratic electoral commitment, which culminated in the PRI’s 1994 elections victory.The assassination of Colosia, though, and the appearance of the EZLN and the subsequent crisis surrounding the peso’s devaluation that accompanied Ernesto Zedilloís rise to power soon led to the collapse of those pillars of support. Crowning the process of the silenttransition were the elections of 1997, which makes it possible to say that in Mexico today there are now smooth elections, but that reform of the State is still unresolved —a subject that includes the reduction of the president’s competence. Seen in the short term, the most direct threats to Mexico’s governability will come as a result of the lack of attention to those demands of society’s underprivileged and the ill

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

    Directory of Open Access Journals (Sweden)

    Andrew Denovan

    2018-01-01

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

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

    Science.gov (United States)

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

    2018-01-01

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

  18. A Framework for Reproducible Latent Fingerprint Enhancements.

    Science.gov (United States)

    Carasso, Alfred S

    2014-01-01

    Photoshop processing of latent fingerprints is the preferred methodology among law enforcement forensic experts, but that appproach is not fully reproducible and may lead to questionable enhancements. Alternative, independent, fully reproducible enhancements, using IDL Histogram Equalization and IDL Adaptive Histogram Equalization, can produce better-defined ridge structures, along with considerable background information. Applying a systematic slow motion smoothing procedure to such IDL enhancements, based on the rapid FFT solution of a Lévy stable fractional diffusion equation, can attenuate background detail while preserving ridge information. The resulting smoothed latent print enhancements are comparable to, but distinct from, forensic Photoshop images suitable for input into automated fingerprint identification systems, (AFIS). In addition, this progressive smoothing procedure can be reexamined by displaying the suite of progressively smoother IDL images. That suite can be stored, providing an audit trail that allows monitoring for possible loss of useful information, in transit to the user-selected optimal image. Such independent and fully reproducible enhancements provide a valuable frame of reference that may be helpful in informing, complementing, and possibly validating the forensic Photoshop methodology.

  19. Latent heat of traffic moving from rest

    Science.gov (United States)

    Farzad Ahmadi, S.; Berrier, Austin S.; Doty, William M.; Greer, Pat G.; Habibi, Mohammad; Morgan, Hunter A.; Waterman, Josam H. C.; Abaid, Nicole; Boreyko, Jonathan B.

    2017-11-01

    Contrary to traditional thinking and driver intuition, here we show that there is no benefit to ground vehicles increasing their packing density at stoppages. By systematically controlling the packing density of vehicles queued at a traffic light on a Smart Road, drone footage revealed that the benefit of an initial increase in displacement for close-packed vehicles is completely offset by the lag time inherent to changing back into a ‘liquid phase’ when flow resumes. This lag is analogous to the thermodynamic concept of the latent heat of fusion, as the ‘temperature’ (kinetic energy) of the vehicles cannot increase until the traffic ‘melts’ into the liquid phase. These findings suggest that in situations where gridlock is not an issue, drivers should not decrease their spacing during stoppages in order to lessen the likelihood of collisions with no loss in flow efficiency. In contrast, motion capture experiments of a line of people walking from rest showed higher flow efficiency with increased packing densities, indicating that the importance of latent heat becomes trivial for slower moving systems.

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

    Science.gov (United States)

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

    2008-11-01

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

  1. Semi-Markov models control of restorable systems with latent failures

    CERN Document Server

    Obzherin, Yuriy E

    2015-01-01

    Featuring previously unpublished results, Semi-Markov Models: Control of Restorable Systems with Latent Failures describes valuable methodology which can be used by readers to build mathematical models of a wide class of systems for various applications. In particular, this information can be applied to build models of reliability, queuing systems, and technical control. Beginning with a brief introduction to the area, the book covers semi-Markov models for different control strategies in one-component systems, defining their stationary characteristics of reliability and efficiency, and uti

  2. [Aging in Mexico].

    Science.gov (United States)

    Contreras de Lehr, E

    1986-01-01

    Demographic social and economic aspects of the situation of the elderly in Mexico are described with special emphasis upon education programmes and types of care in nursing homes. Considering the future trends of an increase in Mexico's elderly population, the author calls for more efforts in research and training in the field of gerontology. First results in this area are reported.

  3. Intercept Centering and Time Coding in Latent Difference Score Models

    Science.gov (United States)

    Grimm, Kevin J.

    2012-01-01

    Latent difference score (LDS) models combine benefits derived from autoregressive and latent growth curve models allowing for time-dependent influences and systematic change. The specification and descriptions of LDS models include an initial level of ability or trait plus an accumulation of changes. A limitation of this specification is that the…

  4. A Review of the Latent and Manifest Benefits (LAMB) Scale

    Science.gov (United States)

    Muller, Juanita; Waters, Lea

    2012-01-01

    The latent and manifest benefits (LAMB) scale (Muller, Creed, Waters & Machin, 2005) was designed to measure the latent and manifest benefits of employment and provide a single scale to test Jahoda's (1981) and Fryer's (1986) theories of unemployment. Since its publication in 2005 there have been 13 studies that have used the scale with 5692…

  5. Prevalence and risk factors of latent Tuberculosis among ...

    African Journals Online (AJOL)

    Background: Latent Tuberculosis treatment is a key tuberculosis control intervention. Adolescents are a high risk group that is not routinely treated in low income countries. Knowledge of latent Tuberculosis (TB) burden among adolescents may influence policy. Objectives: We determined the prevalence and risk factors of ...

  6. Gene Variants Associated with Antisocial Behaviour: A Latent Variable Approach

    Science.gov (United States)

    Bentley, Mary Jane; Lin, Haiqun; Fernandez, Thomas V.; Lee, Maria; Yrigollen, Carolyn M.; Pakstis, Andrew J.; Katsovich, Liliya; Olds, David L.; Grigorenko, Elena L.; Leckman, James F.

    2013-01-01

    Objective: The aim of this study was to determine if a latent variable approach might be useful in identifying shared variance across genetic risk alleles that is associated with antisocial behaviour at age 15 years. Methods: Using a conventional latent variable approach, we derived an antisocial phenotype in 328 adolescents utilizing data from a…

  7. Tweets clustering using latent semantic analysis

    Science.gov (United States)

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

    2017-04-01

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

  8. Iron appetite and latent learning in rats.

    Science.gov (United States)

    Woods, S C; Vasselli, J R; Milam, K M

    1977-11-01

    Two experiments are reported which show that rats are capable of forming an association between the presence of iron in a solution when it is not specifically needed and a subsequent state of iron deficiency. Specifically, rats were trained to lever press for water while thirsty. One group received ferrous ions in addition to the water. When these rats were subsequently rendered iron deficient, they lever pressed more under extinction conditions as a graded function of lower hemoglobin levels. Controls that either did not receive ferrous ions during training or received solutions other than ferrous solutions during training did not respond this way under extinction conditions. This is therefore a type of latent learning previously demonstrated only for sodium appetite.

  9. What Matters for Excellence in PhD Programs? Latent Constructs of Doctoral Program Quality Used by Early Career Social Scientists

    Science.gov (United States)

    Morrison, Emory; Rudd, Elizabeth; Zumeta, William; Nerad, Maresi

    2011-01-01

    This paper unpacks how social science doctorate-holders come to evaluate overall excellence in their PhD training programs based on their domain-specific assessments of aspects of their programs. Latent class analysis reveals that social scientists 6-10 years beyond their PhD evaluate the quality of their doctoral program with one of two…

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

    Science.gov (United States)

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

    2013-12-01

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

  11. Personality and trajectories of posttraumatic psychopathology: A latent change modelling approach.

    Science.gov (United States)

    Fletcher, Susan; O'Donnell, Meaghan; Forbes, David

    2016-08-01

    Survivors of traumatic events may develop a range of psychopathology, across the internalizing and externalizing dimensions of disorder and associated personality traits. However, research into personality-based internalizing and externalizing trauma responses has been limited to cross-sectional investigations of PTSD comorbidity. Personality typologies may present an opportunity to identify and selectively intervene with survivors at risk of posttraumatic disorder. Therefore this study examined whether personality prospectively influences the trajectory of disorder in a broader trauma-exposed sample. During hospitalization for a physical injury, 323 Australian adults completed the Multidimensional Personality Questionnaire-Brief Form and Structured Clinical Interview for DSM-IV, with the latter readministered 3 and 12 months later. Latent profile analysis conducted on baseline personality scores identified subgroups of participants, while latent change modelling examined differences in disorder trajectories. Three classes (internalizing, externalizing, and normal personality) were identified. The internalizing class showed a high risk of developing all disorders. Unexpectedly, however, the normal personality class was not always at lowest risk of disorder. Rather, the externalizing class, while more likely than the normal personality class to develop substance use disorders, were less likely to develop PTSD and depression. Results suggest that personality is an important mechanism in influencing the development and form of psychopathology after trauma, with internalizing and externalizing subtypes identifiable in the early aftermath of injury. These findings suggest that early intervention using a personality-based transdiagnostic approach may be an effective method of predicting and ultimately preventing much of the burden of posttraumatic disorder. Copyright © 2016 Elsevier Ltd. All rights reserved.

  12. Latent Virus Reactivation in Space Shuttle Astronauts

    Science.gov (United States)

    Mehta, S. K.; Crucian, B. E.; Stowe, R. P.; Sams, C.; Castro, V. A.; Pierson, D. L.

    2011-01-01

    Latent virus reactivation was measured in 17 astronauts (16 male and 1 female) before, during, and after short-duration Space Shuttle missions. Blood, urine, and saliva samples were collected 2-4 months before launch, 10 days before launch (L-10), 2-3 hours after landing (R+0), 3 days after landing (R+14), and 120 days after landing (R+120). Epstein-Barr virus (EBV) DNA was measured in these samples by quantitative polymerase chain reaction. Varicella-zoster virus (VZV) DNA was measured in the 381 saliva samples and cytomegalovirus (CMV) DNA in the 66 urine samples collected from these subjects. Fourteen astronauts shed EBV DNA in 21% of their saliva samples before, during, and after flight, and 7 astronauts shed VZV in 7.4% of their samples during and after flight. It was interesting that shedding of both EBV and VZV increased during the flight phase relative to before or after flight. In the case of CMV, 32% of urine samples from 8 subjects contained DNA of this virus. In normal healthy control subjects, EBV shedding was found in 3% and VZV and CMV were found in less than 1% of the samples. The circadian rhythm of salivary cortisol measured before, during, and after space flight did not show any significant difference between flight phases. These data show that increased reactivation of latent herpes viruses may be associated with decreased immune system function, which has been reported in earlier studies as well as in these same subjects (data not reported here).

  13. ENDOGENOUS ANALGESIA, DEPENDENCE, AND LATENT PAIN SENSITIZATION

    Science.gov (United States)

    Taylor, Bradley K; Corder, Gregory

    2015-01-01

    Endogenous activation of μ-opioid receptors (MORs) provides relief from acute pain. Recent studies have established that tissue inflammation produces latent pain sensitization (LS) that is masked by spinal MOR signaling for months, even after complete recovery from injury and re-establishment of normal pain thresholds. Disruption with MOR inverse agonists reinstates pain and precipitates cellular, somatic and aversive signs of physical withdrawal; this phenomenon requires N-methyl-D-aspartate receptor-mediated activation of calcium-sensitive adenylyl cyclase type 1 (AC1). In this review, we present a new conceptual model of the transition from acute to chronic pain, based on the delicate balance between LS and endogenous analgesia that develops after painful tissue injury. First, injury activates pain pathways. Second, the spinal cord establishes MOR constitutive activity (MORCA) as it attempts to control pain. Third, over time, the body becomes dependent on MORCA, which paradoxically sensitizes pain pathways. Stress or injury escalates opposing inhibitory and excitatory influences on nociceptive processing as a pathological consequence of increased endogenous opioid tone. Pain begets MORCA begets pain vulnerability in a vicious cycle. The final result is a silent insidious state characterized by the escalation of two opposing excitatory and inhibitory influences on pain transmission: LS mediated by AC1 (which maintains accelerator), and pain inhibition mediated by MORCA (which maintains the brake). This raises the prospect that opposing homeostatic interactions between MORCA analgesia and latent NMDAR–AC1-mediated pain sensitization create a lasting vulnerability to develop chronic pain. Thus, chronic pain syndromes may result from a failure in constitutive signaling of spinal MORs and a loss of endogenous analgesic control. An overarching long-term therapeutic goal of future research is to alleviate chronic pain by either: a) facilitating endogenous opioid

  14. Laser interrogation of latent vehicle registration number

    Energy Technology Data Exchange (ETDEWEB)

    Russo, R.E. [Lawrence Berkeley Lab., CA (United States). Energy and Environment Div.]|[Lawrence Livermore National Lab., CA (United States). Forensic Science Center; Pelkey, G.E. [City of Livermore Police Dept., CA (United States); Grant, P.; Whipple, R.E.; Andresen, B.D. [Lawrence Livermore National Lab., CA (United States). Forensic Science Center

    1994-09-01

    A recent investigation involved automobile registration numbers as important evidentiary specimens. In California, as in most states, small, thin metallic decals are issued to owners of vehicles each year as the registration is renewed. The decals are applied directly to the license plate of the vehicle and typically on top of the previous year`s expired decal. To afford some degree of security, the individual registration decals have been designed to tear easily; they cannot be separated from each other, but can be carefully removed intact from the metal license plate by using a razor blade. In September 1993, the City of Livermore Police Department obtained a blue 1993 California decal that had been placed over an orange 1992 decal. The two decals were being investigated as possible evidence in a case involving vehicle registration fraud. To confirm the suspicion and implicate a suspect, the department needed to known the registration number on the bottom (completely covered) 1992 decal. The authors attempted to use intense and directed light to interrogate the colored stickers. Optical illumination using a filtered white-light source partially identified the latent number. However, the most successful technique used a tunable dye laser pumped by a pulsed Nd:YAG laser. By selectively tuning the wavelength and intensity of the dye laser, backlit illumination of the decals permitted visualization of the underlying registration number through the surface of the top sticker. With optimally-tuned wavelength and intensity, 100% accuracy was obtained in identifying the sequence of latent characters. The advantage of optical techniques is their completely nondestructive nature, thus preserving the evidence for further interrogation or courtroom presentation.

  15. A Probability Distribution over Latent Causes, in the Orbitofrontal Cortex.

    Science.gov (United States)

    Chan, Stephanie C Y; Niv, Yael; Norman, Kenneth A

    2016-07-27

    The orbitofrontal cortex (OFC) has been implicated in both the representation of "state," in studies of reinforcement learning and decision making, and also in the representation of "schemas," in studies of episodic memory. Both of these cognitive constructs require a similar inference about the underlying situation or "latent cause" that generates our observations at any given time. The statistically optimal solution to this inference problem is to use Bayes' rule to compute a posterior probability distribution over latent causes. To test whether such a posterior probability distribution is represented in the OFC, we tasked human participants with inferring a probability distribution over four possible latent causes, based on their observations. Using fMRI pattern similarity analyses, we found that BOLD activity in the OFC is best explained as representing the (log-transformed) posterior distribution over latent causes. Furthermore, this pattern explained OFC activity better than other task-relevant alternatives, such as the most probable latent cause, the most recent observation, or the uncertainty over latent causes. Our world is governed by hidden (latent) causes that we cannot observe, but which generate the observations we see. A range of high-level cognitive processes require inference of a probability distribution (or "belief distribution") over the possible latent causes that might be generating our current observations. This is true for reinforcement learning and decision making (where the latent cause comprises the true "state" of the task), and for episodic memory (where memories are believed to be organized by the inferred situation or "schema"). Using fMRI, we show that this belief distribution over latent causes is encoded in patterns of brain activity in the orbitofrontal cortex, an area that has been separately implicated in the representations of both states and schemas. Copyright © 2016 the authors 0270-6474/16/367817-12$15.00/0.

  16. Assessing Trust and Effectiveness in Virtual Teams: Latent Growth Curve and Latent Change Score Models

    Directory of Open Access Journals (Sweden)

    Michael D. Coovert

    2017-08-01

    Full Text Available Trust plays a central role in the effectiveness of work groups and teams. This is the case for both face-to-face and virtual teams. Yet little is known about the development of trust in virtual teams. We examined cognitive and affective trust and their relationship to team effectiveness as reflected through satisfaction with one’s team and task performance. Latent growth curve analysis reveals both trust types start at a significant level with individual differences in that initial level. Cognitive trust follows a linear growth pattern while affective trust is overall non-linear, but becomes linear once established. Latent change score models are utilized to examine change in trust and also its relationship with satisfaction with the team and team performance. In examining only change in trust and its relationship to satisfaction there appears to be a straightforward influence of trust on satisfaction and satisfaction on trust. However, when incorporated into a bivariate coupling latent change model the dynamics of the relationship are revealed. A similar pattern holds for trust and task performance; however, in the bivariate coupling change model a more parsimonious representation is preferred.

  17. Pain patterns during adolescence can be grouped into four pain classes with distinct profiles

    DEFF Research Database (Denmark)

    Holden, Sinead; Rathleff, Michael Skovdal; Roos, E. M.

    2018-01-01

    L (assessed by Euro-QoL 5D-3L). Latent class analysis was used to classify spatial pain patterns, based on the pain sites. The analysis included 2953 adolescents. RESULTS: Four classes were identified as follows: (1) little or no pain (63% of adolescents), (2) majority lower extremity pain (10%), (3) multi......-site bodily pain (22%) and (4) head and stomach pain (3%). The lower extremity multi-site pain group reported highest weekly sports participation (p ....001). Males were more likely to belong to the little or no pain class, whereas females were more likely to belong to the multi-site bodily pain class. CONCLUSIONS: Latent class analysis identified distinct classes of pain patterns in adolescents, characterized by sex, differences in HRQoL and sports...

  18. Mexico and Central America.

    Science.gov (United States)

    Bronfman, M

    1998-01-01

    This article reviews the literature on migration and HIV/AIDS in Mexico and Central America, including Belize, Costa Rica, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, and Panama. Most migrants travel to the US through Mexico. US-Mexico trade agreements created opportunities for increased risk of HIV transmission. The research literature focuses on Mexico. Most countries, with the exception of Belize and Costa Rica, are sending countries. Human rights of migrants are violated in transit and at destination. Migration policies determine migration processes. The Mexican-born population in the US is about 3% of US population and 8% of Mexico's population. About 22% arrived during 1992-97, and about 500,000 are naturalized US citizens. An additional 11 million have a Mexican ethnic background. Mexican migrants are usually economically active men who had jobs before leaving and were urban people who settled in California, Texas, Illinois, and Arizona. Most Mexican migrants enter illegally. Many return to Mexico. The main paths of HIV transmission are homosexual, heterosexual, and IV-drug-injecting persons. Latino migrants frequently use prostitutes, adopt new sexual practices including anal penetration among men, greater diversity of sexual partners, and use of injectable drugs.

  19. Latent profile analyses of posttraumatic stress disorder, depression and generalized anxiety disorder symptoms in trauma-exposed soldiers.

    Science.gov (United States)

    Contractor, Ateka A; Elhai, Jon D; Fine, Thomas H; Tamburrino, Marijo B; Cohen, Gregory; Shirley, Edwin; Chan, Philip K; Liberzon, Israel; Galea, Sandro; Calabrese, Joseph R

    2015-09-01

    Posttraumatic stress disorder (PTSD) is comorbid with major depressive disorder (MDD; Kessler et al., 1995) and generalized anxiety disorder (GAD; Brown et al., 2001). We aimed to (1) assess discrete patterns of post-trauma PTSD-depression-GAD symptoms using latent profile analyses (LPAs), and (2) assess covariates (gender, income, education, age) in defining the best fitting class solution. The PTSD Checklist (assessing PTSD symptoms), GAD-7 scale (assessing GAD symptoms), and Patient Health Questionnaire-9 (assessing depression) were administered to 1266 trauma-exposed Ohio National Guard soldiers. Results indicated three discrete subgroups based on symptom patterns with mild (class 1), moderate (class 2) and severe (class 3) levels of symptomatology. Classes differed in symptom severity rather than symptom type. Income and education significantly predicted class 1 versus class 3 membership, and class 2 versus class 3. In conclusion, there is heterogeneity regarding severity of PTSD-depression-GAD symptomatology among trauma-exposed soldiers, with income and education predictive of class membership. Copyright © 2015 Elsevier Ltd. All rights reserved.

  20. Data on the interexaminer variation of minutia markup on latent fingerprints.

    Science.gov (United States)

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

    2016-09-01

    The data in this article supports the research paper entitled "Interexaminer variation of minutia markup on latent fingerprints" [1]. The data in this article describes the variability in minutia markup during both analysis of the latents and comparison between latents and exemplars. The data was collected in the "White Box Latent Print Examiner Study," in which each of 170 volunteer latent print examiners provided detailed markup documenting their examinations of latent-exemplar pairs of prints randomly assigned from a pool of 320 pairs. Each examiner examined 22 latent-exemplar pairs; an average of 12 examiners marked each latent.

  1. Mexico's nuclear paradox

    International Nuclear Information System (INIS)

    Redclift, M.

    1989-01-01

    Opposition to Mexico's nuclear reactors at Laguna Verde has grown during the last two years. The nuclear programme is blamed for being expensive and wasteful, and the decision to rely on the USA contradicts Mexico's espoused policy of greater independence from the USA. The way in which petroleum revenues were used to precipitate the nuclear option is compared with the lack of urgency given to renewable energy and greater energy efficiency. From a social and environmental perspective, as well as an economic one, Mexico's nuclear programme is judged expensive and irrelevant. (author)

  2. How 'core' are motor timing difficulties in ADHD? A latent class comparison of pure and comorbid ADHD classes

    NARCIS (Netherlands)

    van der Meer, Jolanda M. J.; Hartman, Catharina A.; Thissen, Andrieke J. A. M.; Oerlemans, Anoek M.; Luman, Marjolein; Buitelaar, Jan K.; Rommelse, Nanda N. J.

    Children with attention-deficit/hyperactivity disorder (ADHD) have motor timing difficulties. This study examined whether affected motor timing accuracy and variability are specific for ADHD, or that comorbidity with autism spectrum disorders (ASD) contributes to these motor timing difficulties. An

  3. Reading Ability Development from Kindergarten to Junior Secondary: Latent Transition Analyses with Growth Mixture Modeling

    Directory of Open Access Journals (Sweden)

    Yuan Liu

    2016-10-01

    Full Text Available The present study examined the reading ability development of children in the large scale Early Childhood Longitudinal Study (Kindergarten Class of 1998-99 data; Tourangeau, Nord, Lê, Pollack, & Atkins-Burnett, 2006 under the dynamic systems. To depict children's growth pattern, we extended the measurement part of latent transition analysis to the growth mixture model and found that the new model fitted the data well. Results also revealed that most of the children stayed in the same ability group with few cross-level changes in their classes. After adding the environmental factors as predictors, analyses showed that children receiving higher teachers' ratings, with higher socioeconomic status, and of above average poverty status, would have higher probability to transit into the higher ability group.

  4. Morphometry of latent palmprints as a function of time.

    Science.gov (United States)

    Barros, Rodrigo M; Faria, Bruna E F; Kuckelhaus, Selma A S

    2013-12-01

    In many crimes, the elapsed time between production and collecting fingermark traces is crucial. and a method able to detect the aging of latent prints would represent an improvement in forensic procedures. Considering that as the latent print gets older, substantial changes in the relative proportion of individual components secreted by skin glands could affect the morphology of ridges, morphometry could be a potential tool to assess the aging of latent fingermarks. Then, considering the very limited research in the field, the present work aims to evaluate the morphometry of latent palmprint ridges, as a function of time, in order to identify an aging pattern. The latent marks were deposited by 20 donors on glass microscope slides considering pressure and contact angle, and then were maintained under controlled environmental conditions. The morphometric study was conducted on marks developed with magnetic powder in 7 different time intervals after deposition (0, 5, 10, 15, 20, 25 or 30 days); 60 ridges were evaluated for each developed mark. The results showed that: 1) the method for the replacement and mixing of skin secretions on the palm was appropriate to ensure reproducibility of latent prints, and 2) considering the studied group, there was a time-dependent reduction in the width of ridges and on the percentage of visible ridges over 30 days. Results suggest the possibility of using the morphometric method to determine an aging profile of latent palmprints on glass surface, aiming for forensic purposes. © 2013.

  5. Tropical Gravity Wave Momentum Fluxes and Latent Heating Distributions

    Science.gov (United States)

    Geller, Marvin A.; Zhou, Tiehan; Love, Peter T.

    2015-01-01

    Recent satellite determinations of global distributions of absolute gravity wave (GW) momentum fluxes in the lower stratosphere show maxima over the summer subtropical continents and little evidence of GW momentum fluxes associated with the intertropical convergence zone (ITCZ). This seems to be at odds with parameterizations forGWmomentum fluxes, where the source is a function of latent heating rates, which are largest in the region of the ITCZ in terms of monthly averages. The authors have examined global distributions of atmospheric latent heating, cloud-top-pressure altitudes, and lower-stratosphere absolute GW momentum fluxes and have found that monthly averages of the lower-stratosphere GW momentum fluxes more closely resemble the monthly mean cloud-top altitudes rather than the monthly mean rates of latent heating. These regions of highest cloud-top altitudes occur when rates of latent heating are largest on the time scale of cloud growth. This, plus previously published studies, suggests that convective sources for stratospheric GW momentum fluxes, being a function of the rate of latent heating, will require either a climate model to correctly model this rate of latent heating or some ad hoc adjustments to account for shortcomings in a climate model's land-sea differences in convective latent heating.

  6. The latent rationality of risky decisions

    Energy Technology Data Exchange (ETDEWEB)

    Japp, K.P. [Bielefeld Univ. (Germany). Faculty for Sociology

    1999-12-01

    . So rationality will stay latent as the operation of re-entry. It may become manifest as legitimating of something else, for instance as rational choice. In everyday life re-entries emerge as compromise. But compromises conceal the relevant difference. In scientific life re-entries emerge as mixed scanning. But mixed scanning displays a mix, not a difference. And it is always a difference which makes a difference. This remains latent.

  7. The latent rationality of risky decisions

    International Nuclear Information System (INIS)

    Japp, K.P.

    1999-01-01

    The general question of rationality has changed from the old-fashioned difference of means and ends to the modern difference of system and environment. Organizations as social systems producing and reproducing decisions translate this difference into the difference of stability and variety. The question then is: In which way can the difference between stability and variety express rationality? - In the temporal dimension of risk-taking, re-entries may be expressed as 'present futures' or 'future presences'. These expressions indicate both: The irresolvable uncertainty of any risk-taking, indicated by open futures, and its boundedness by self-application of distinctions, e.g. projected futures from the background of a known past. - In the material dimension of risk-taking, re-entries may be expressed as 'stable flexibility' or 'flexible stability'. Again, these expressions indicate both: The irresolvable uncertainty of any risk-taking, indicted by open flexibilities, and its boundedness by self-application of distinctions, e.g. flexibility and stability after learning the respective costs of the single options. In the social dimension of risk-taking, re-entries may be expressed as 'pragmatic dissent' or 'controversial pragmatism'. Again, these expressions indicate both: The irresolvable uncertainty of any risk-taking, indicated by open dissent or controversies, and its boundedness by self-application of distinctions, e.g. pragmatic agreements and irresolvable dissent. Again, all three asymmetries represent re-entries. The built-in preferences simply do not work without the subtleties of re-entries, at least when these processes are described by sociologically informed observers. Who else should know that he or she is operating on the basis of something called re-entries? In everyday life communication, no one sees a thing like that since every observation has an in-built bias for one side of a distinction. So rationality will stay latent as the operation of re

  8. Latent effectiveness of desiccant wheel: A silica gels- water system

    International Nuclear Information System (INIS)

    Rabah, A. A.; Mohamed, S. A.

    2009-01-01

    A latent heat effectiveness model in term of dimensionless groups? =f (NTU, m * ,Crm * ) for energy wheel has been analytically derived. The energy wheel is divided into humidification and dehumidification sections. For each section macroscopic mass differential equations for gas and the matrix were applied. In this process local latent effectiveness (? c ,? h ) for the humidification and dehumidification section of the wheel were obtained. The Latent effectiveness of the wheel is then derived form local effectiveness [? =f (? c ,? h)]. The model is compared with the existing experimental investigation and manufacturer data for energy wheel. More than 90% of the experimental data within a confidence limit of 95%. (Author)

  9. Towards an HIV-1 cure: measuring the latent reservoir

    Science.gov (United States)

    Bruner, Katherine M.; Hosmane, Nina N.; Siliciano, Robert F.

    2015-01-01

    The latent reservoir of HIV-1 in resting memory CD4+ T cells serves as a major barrier to curing HIV-1 infection. While many PCR- and culture-based assays have been used to measure the size of the latent reservoir, correlation between results of different assays is poor and recent studies indicate that no available assay provides an accurate measurement of reservoir size. The discrepancies between assays are a hurdle to clinical trials that aim to measure the efficacy of HIV-1 eradication strategies. Here we describe the advantages and disadvantages of various approaches to measure the latent reservoir. PMID:25747663

  10. Silencing criticism in Mexico

    Directory of Open Access Journals (Sweden)

    Ximena Suárez

    2017-10-01

    Full Text Available Journalists and human rights defenders in Mexico are being attacked in an attempt to silence their criticism. Many are forced to flee or risk being assassinated. The consequences are both personal and of wider social significance.

  11. New Mexico State Boundary

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Shapefiles are an extract of selected geographic and cartographic information from the Census MAF/TIGER database. The Census MAF/TIGER database...

  12. New Mexico Federal Lands

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This map layer consists of federally owned or administered lands of the United States, Puerto Rico, and the U.S. Virgin Islands. Only areas of 640 acres or more are...

  13. New Mexico Mountain Ranges

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The Geographic Names Information System (GNIS) actively seeks data from and partnerships with Government agencies at all levels and other interested organizations....

  14. Mexico - Surface Weather Observations

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Mexican Surface Daily Observations taken at 94 observatories located throughout Mexico, beginning in 1872 and going up through 1981. The data resided on paper...

  15. Doing Business in Mexico

    OpenAIRE

    Zimmermann, Thomas A.

    2002-01-01

    On 1 July 2001, a far-reaching free trade agreement between the EFTA States and Mexico entered into force. ”Doing Business in Mexico” provides targeted assistance to Swiss Small and Medium-Sized Enterprises (SME) that wish to tap the potential of Mexico as both an export destination and investment location. This comprehensive guide contains information and advice on market research, market entry, and investment in this fascinating country. Part I introduces the reader to this fascinating ...