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Psychotic-like experiences (PLEs) are common throughout childhood, and the presence of these experiences is a significant risk factor for poor mental health later in development. Given the association of PLEs with a broad number of mental health diagnoses, these experiences serve as an important malleable target for early preventive interventions. However, little is known about these experiences across childhood. While these experiences may be common, longitudinal measurement in non-clinical settings is not. Therefore, in order to explore longitudinal trajectories of PLEs in childhood, we harmonized three school-based randomized control trials with longitudinal follow-up to identify heterogeneity in trajectories of these experiences. In an integrative data analysis (IDA) using growth mixture modeling, we identified three latent trajectory classes. One trajectory class was characterized by persistent PLEs, one was characterized by high initial probabilities but improving across the analytic period, and one was characterized by no reports of PLEs. Compared to the class without PLEs, those in the improving class were more likely to be male and have higher levels of aggressive and disruptive behavior at baseline. In addition to the substantive impact this work has on PLE research, we also discuss the methodological innovation as it relates to IDA. This IDA demonstrates the complexity of pooling data across multiple studies to estimate longitudinal mixture models.

The SAVA syndemic is frequently used to describe the co-occurrence of HIV, gender-based violence (GBV), and substance use. In this study we determine the extent to which the typologies of the SAVA syndemic can be described and utilized for intervention strategies among youth living in the slums of Kampala, Uganda. We analyzed the "Kampala Youth Survey 2014," a cross-sectional survey conducted in the spring of 2014, consisting of a convenience sample (N = 1134) of urban youth (12-18 years of age). Descriptive statistics were computed for hypothesized risk factors and demographic variables among the 8 typologies of GBV, HIV, and alcohol use. Multinomial logistic regression was conducted to determine statistically significant correlates with each typology. The overall prevalence of GBV was 31.7%, whereas the overall prevalence of alcohol use in the past 12 months was 31.2%. HIV-Positive youth comprised 10.5% of the total sample. Females comprised the majority of the typology with no SAVA components compared to males (55% vs. 45%, respectively), as well as the SAVA syndemic typology (GBV + HIV + ALC +) (58% vs. 42%, respectively). Engaging in commercial sex work (36%), witnessing parental abuse (61%), and depression/suicidality (81%) were all highly prevalent among youth in the SAVA syndemic typology (GBV, HIV, and alcohol use). Sex work and observing parental abuse were associated with the SAVA syndemic typology in the multivariable model. In our study, alcohol rarely coexisted without GBV among the typologies. Therefore, prevention efforts including structural interventions may be particularly warranted in vulnerable populations to address alcohol use, which may directly or indirectly impact GBV and HIV.

Using data from the Educational Longitudinal Study (2002), this study employed latent class analysis (LCA) to explore the relationship between students' engagement-related dispositions and their behavioral engagement in home, school, and community activities. The primary aim was to identify and describe the engagement characteristics of distinct subpopulations of students. Our higher-order LCA models yielded five subpopulation profiles of students' social-ecological engagement. In contrast to extant participation-identification models, these new profiles suggested that the relationship between students' behavioral engagement and their school-related identities and dispositions is nonlinear and nonhomogeneous. This major finding recommends comprehensive school-community improvement models as well as nuanced interventions that are tailor-made to fit the engagement needs and identity-related characteristics of each student subpopulation.

A multilevel-discrete time survival model may be appropriate for purely hierarchical data, but when data are non-purely hierarchical due to individual mobility across clusters, a cross-classified discrete time survival model may be necessary. The purpose of this research was to investigate the performance of a cross-classified discrete-time survival model and assess the impact of ignoring a cross-classified data structure on the model parameters of a conventional discrete-time survival model and a multilevel discrete-time survival model. A Monte Carlo simulation was used to examine the performance of three discrete-time survival models when individuals are mobile across clusters. Simulation factors included the value of the between-clusters variance, number of clusters, within-cluster sample size, Weibull scale parameter, and mobility rate. The results suggest that substantial relative parameter bias, unacceptable coverage of the 95% confidence intervals, and severely biased standard errors are possible for all model parameters when a discrete-time survival model is used that ignores the cross-classified data structure. The findings presented in this study are useful for methodologists and practitioners in educational research, public health, and other social sciences where discrete-time survival analysis is a common methodological technique for analyzing event-history data. [ABSTRACT FROM AUTHOR]

This study investigates body image concerns and disordered weight- and shape-related behaviors across adolescence and young adulthood in males and how patterns vary by sexual orientation. Participants were 5,388 males from the U.S. national Growing Up Today Study. In 2001, 2003, and 2005 (spanning ages 15-20 years), participants reported sexual orientation, past-year desire for toned/defined muscles and concerns with weight and shape, and past-year binge eating, restrictive dieting, purging (vomiting or laxative use), and use of products to increase muscularity (e.g., creatine, steroids). Latent class analyses identified 2 patterns at ages 15-16 years and 3 patterns at 17-18 and 19-20 years: healthy (all ages; low body image concerns and weight- and shape-related behaviors; 54-74% of observations), muscle-concerned (ages 17-18 and 19-20; relatively high muscularity concern and product use; 18-21% of observations), and lean-concerned (all ages; relatively high weight and shape concern, dieting, and binge eating; 19-28% of observations). Latent transition analyses revealed that sexual minority males (i.e., mostly heterosexual, gay, and bisexual) were more likely than completely heterosexual males to be lean-concerned at ages 17-18 and 19-20 years and to transition to the lean-concerned class from the healthy class. There were no sexual orientation differences in odds of being muscle-concerned. Both heterosexual and sexual minority males are at risk for presenting body image concerns and weight- and shape-related behaviors that may have deleterious health consequences. Results suggest the need for screening for concerns and behaviors related to leanness and muscularity in early adolescence among all males, regardless of sexual orientation.

Background: We used a latent class analysis (LCA) to characterize coping styles of urban youth and examined if coping styles moderated the association between experiencing discrimination and bullying and depressive symptoms. Methods: The data come from the 2006 Boston Youth Survey, where students were asked to select 2 behaviors they do most often when they are upset, from a list of 15 options. A total of 927 (75%) students contributed to the LCA analytic sample (44% non-Hispanic Blacks, 29% Hispanics, and 58% girls). Relative and absolute fit indices determined the number of classes. An interaction term between types of discrimination and bullying experienced and coping style tested for moderation. Results: The LCA revealed that a 3-class solution had the best fit (Lo-Mendell-Rubin likelihood ratio test, 4-class vs 3-class, p-value 0.12). The largest coping style class was characterized by high endorsement of distractive coping strategies (59%), the second class was characterized by using supportive coping strategies (27%), and the third class was characterized by using avoidance coping strategies (12%). We found a significant interaction between discrimination and coping style for depressive symptoms. Conclusions: The relationship between experiencing discrimination and depression varied based on coping style and the type of discrimination and bullying experienced.

Although studies have established associations between parenting characteristics and adolescent suicidality, the strength of the evidence for these links remains unclear, largely because of methodological limitations, including lack of accounting for possible child effects on parenting. This study addresses these issues by using autoregressive cross-lag models with data on 802 adolescents and their parents across 5 years. Observed parenting behaviors predicted change in adolescent suicidal problems across 1-year intervals even after controlling for adolescents' effects on parenting. Nurturant-involved parenting continued to demonstrate salutary effects after controlling for adolescent and parent internalizing psychopathology: over time, observed nurturant-involved parenting reduced the likelihood of adolescent suicidal problems. This study increases the empirical support implicating parenting behaviors in the developmental course of adolescent suicidality. (Contains 2 figures and 1 table.)

The focus of this study was to prospectively investigate the effect of aggressive behavior and of classroom behavioral context, as measured in the fall of 1st grade, on the timing of 1st school removal across Grades 1-7 in a sample of predominately urban minority youths from Baltimore, Maryland. Using a multilevel discrete-time survival framework, we found that demographic characteristics of the students as well as early individual- and classroom-level of aggression contribute to the onset of school removal. Although early individual aggression was positively associated with the risk of school removal, initially higher levels of classroom aggression corresponded to lower risk of school removal. (Contains 1 footnote, 2 tables, and 6 figures.)

Although suicide ideation, plans, and attempts increase during adolescence, it remains unclear whether boys' and girls' risk for these outcomes peaks at different ages. We used longitudinal categorical data ("never," "once," "2+ times") from the Family Transitions Project (N = 1,248 rural European Americans, ages 11-19) to investigate whether yearly prevalence rates of adolescent suicidal episodes follow different patterns by sex. Multiple-group growth models revealed that peak levels of past-year ideation and plans occurred during mid adolescence for girls, but slowly increased through late adolescence for boys. We found that prevalence patterns for attempts were very similar for boys and girls, with both increasing through mid adolescence and then declining, although girls' risk declined slightly more rapidly. This information may help alert gatekeepers to developmental periods during which boys and girls are particularly vulnerable to suicide-related experiences, and also may help inform the timing of preventive efforts.

This paper provides an introduction to a recently developed conceptual framework--the dimensional-categorical spectrum--for utilizing general factor mixture models to explore the latent structures of psychological constructs. This framework offers advantages over traditional latent variable models that usually employ either continuous latent factors or categorical latent class variables to characterize the latent structure and require an a priori assumption about the underlying nature of the construct as either purely dimension or purely categorical. The modeling process is discussed in detail and then illustrated with data on the delinquency items of Achenbach's child behavior checklist from a sample of children in the National Adolescent and Child Treatment Study.

The gateway drug model is a popular conceptualization of a progression most substance users are hypothesized to follow as they try different legal and illegal drugs. Most forms of the gateway hypothesis are that "softer" drugs lead to "harder," illicit drugs. However, the gateway hypothesis has been notably difficult to directly test--that is, to test as competing hypotheses in a single model that licit drug use might lead to illicit drug use "or" the reverse. This article presents a novel statistical technique, dual-process discrete-time survival analysis, which enables this comparison. This method uses mixture-modeling software to estimate 2 concurrent time-to-event processes and their effects on each other. Using this method, support for the gateway hypothesis in the National Longitudinal Survey of Youth, 1997, was weak. However, this article was not designed as a strong test of causal direction but more as a technical demonstration and suffered from certain technological limitations. Both these limitations and future directions are discussed. (Contains 1 footnote, 3 tables, and 1 figure.)

Analyzing problem-behavior trajectories can be difficult. The data are generally categorical and often quite skewed, violating distributional assumptions of standard normal-theory statistical models. In this article, the authors present several currently available modeling options, all of which make appropriate distributional assumptions for the observed categorical data. Three are based on the generalized linear model: a hierarchical generalized linear model, a growth mixture model, and a latent class growth analysis. They also describe a longitudinal latent class analysis, which requires fewer assumptions than the first 3. Finally, they illustrate all of the models using actual longitudinal adolescent alcohol-use data. They guide the reader through the model-selection process, comparing the results in terms of convergence properties, fit and residuals, parsimony, and interpretability. Advances in computing and statistical software have made the tools for these types of analyses readily accessible to most researchers. Using appropriate models for categorical data will lead to more accurate and reliable results, and their application in real data settings could contribute to substantive advancements in the field of development and the science of prevention. (Contains 11 figures, 6 tables, and 14 footnotes.)

A sense of mastery is an important component of psychological health and wellbeing across the life-span; however, relatively little is known about the development of mastery during childhood and adolescence. Utilizing prospective, longitudinal data from 444 adolescent sibling pairs and their parents, our conceptual model proposes that family socioeconomic status (SES) in the form of parental education promotes effective family problem-solving, which, in turn, fosters adolescent mastery. Results show: (1) a significant increase in mastery for younger and older siblings, (2) parental education promoted effective problem-solving between parents and adolescents and between siblings but not between the parents themselves, and (3) all forms of effective family problem-solving predicted greater adolescent mastery. Parental education had a direct effect on adolescent mastery as well as the hypothesized indirect effect through problem-solving effectiveness, suggesting both a social structural and social process influence on the development of mastery during adolescence. (Contains 2 figures, 2 tables and 1 note.)

Presented are the results of a study using latent profile analysis to describe the self-reported practices of 138 evaluators. Four classes emerged and were labeled (a) indistinct pattern of practice, (b) method-focused, (c) user-focused, and (d) robust pattern of practice. Evaluators in the "indistinct pattern of practice" class had mean item responses closest to zero relative to the other three classes, suggesting relatively weak associations with the practices described by the study instrument. The "method-focused" class had strong and distinct preferences for using particular methods. The "user-focused" class placed high importance on the role of the evaluator as facilitator, and was concerned with attaining a high level of stakeholder/participant involvement. The "robust pattern of practice" class evaluators showed a high degree of rigor in their reported patterns of practice, specifically as they are prescribed by evaluation theorists. The four profiles were distinguished by years of evaluation experience, degree attainment, and internal/external evaluator status. (Contains 4 tables and 3 notes.)

Integrative data analysis (IDA) is an analytic tool that allows researchers to combine raw data across multiple, independent studies, providing an improved measurement of latent constructs as compared to single study analysis or meta-analyses. This is often achieved through the implementation of moderated non-linear factor analysis (MNLFA), an advanced modeling approach that allows for covariate moderation of item and factor parameters. The current paper provides an overview of this modeling technique, highlighting distinct advantages most apt for IDA. We further illustrate the complex model building process involved in MNLFA by providing a tutorial using empirical data from five separate prevention trials. The code and data used for analyses are also provided. [ABSTRACT FROM AUTHOR]

Although suicide ideation, plans, and attempts increase during adolescence, it remains unclear whether boys' and girls' risk for these outcomes peaks at different ages. We used longitudinal categorical data (never, once, 2+ times) from the Family Transitions Project (N = 1,248 rural European Americans, ages 11-19) to investigate whether yearly prevalence rates of adolescent suicidal episodes follow different patterns by sex. Multiple-group growth models revealed that peak levels of past-year ideation and plans occurred during mid adolescence for girls, but slowly increased through late adolescence for boys. We found that prevalence patterns for attempts were very similar for boys and girls, with both increasing through mid adolescence and then declining, although girls' risk declined slightly more rapidly. This information may help alert gatekeepers to developmental periods during which boys and girls are particularly vulnerable to suicide-related experiences, and also may help inform the timing of preventive efforts.

Analyzing problem-behavior trajectories can be difficult. The data are generally categorical and often quite skewed, violating distributional assumptions of standard normal-theory statistical models. In this article, the authors present several currently available modeling options, all of which make appropriate distributional assumptions for the observed categorical data. Three are based on the generalized linear model: a hierarchical generalized linear model, a growth mixture model, and a latent class growth analysis. They also describe a longitudinal latent class analysis, which requires fewer assumptions than the first 3. Finally, they illustrate all of the models using actual longitudinal adolescent alcohol-use data. They guide the reader through the model-selection process, comparing the results in terms of convergence properties, fit and residuals, parsimony, and interpretability. Advances in computing and statistical software have made the tools for these types of analyses readily accessible to most researchers. Using appropriate models for categorical data will lead to more accurate and reliable results, and their application in real data settings could contribute to substantive advancements in the field of development and the science of prevention. Keywords: longitudinal analysis, generalized linear models, mixture models, drinking trajectories, adolescent alcohol use

To purchase or authenticate to the full-text of this article, please visit this link: http://dx.doi.org/10.1111/j.1467-8624.2007.01001.x Byline: Shannon J. Dogan (1), Rand D. Conger (1), Kee Jeong Kim (2), Katherine E. Masyn (1) Abstract: This study examined the role of adolescent perceptions of parental behavior and disrupted parenting in the continuity of antisocial behavior across generations. Participants included 430 adolescents and their biological parents assessed during the period from the 9th to 12th grades (9th grade age in years: M=15.09, SD=0.43). Structural equation modeling provided support for the mediating role of adolescent perceptions and disrupted parenting in the familial transmission of antisocial behavior. Furthermore, the results were consistent across parent and adolescent gender. The findings extend previous research by suggesting a significant role for adolescent perceptions of parents' activities in the development and growth of antisocial behavior. Results also support significant stability in antisocial tendencies over the course of adolescence. Author Affiliation: (1)University of California at Davis (2)Virginia Polytechnic Institute and State University Article note: Correspondence concerning this article should be addressed to Shannon J. Dogan, Department of Human & Community Development, University of California at Davis, Family Research Group, 202 Cousteau Place, Suite 100, Davis, CA 95616. Electronic mail may be sent to sjdogan@ucdavis.edu.

Multiple group analysis and general growth mixture modeling was used to determine whether aggressive-disruptive behavior trajectories during elementary school, and their association with young adulthood antisocial outcomes, vary by gender. Participants were assessed longitudinally beginning at age 6 as part of an evaluation of 2 school-based preventive programs. Two analogous trajectories were found for girls and boys: chronic high aggression-disruption (CHAD) and stable low aggressiondisruption (LAD). A 3rd class of low moderate aggression-disruption (LMAD) for girls and increasing aggression-disruption (lAD) for boys also was found. Girls and boys in analogous CHAD classes did not differ in trajectory level and course, but girls in the CHAD and LAD classes had lower rates of antisocial outcomes than boys. Girls with the LMAD trajectory differed from boys with the IAD trajectory. Keywords: aggression, trajectories, growth mixture modeling, multiple group comparison, gender differences