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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.

Introduction: Blunt and hemp wraps, as a means of consuming cannabis, have emerged into the retail space where the prevalence has been increasing since 2017. There is limited epidemiological research on the prevalence of use of these products across the U.S. particularly among young adults who are at greater risk of tobacco and cannabis use. Methods: This study draws from a U.S. national representative sample of young adults (n = 1178) captured in May 2022. Respondents participated in an online survey about their use of blunt and hemp wraps. Multinomial regression was used to examine differences in sociodemographic characteristics (gender, race/ethnicity, sexual orientation, educational attainment, and region) in relation to use of each wrap type. Results: One quarter (22.7%) of young adults reported ever having used a blunt wrap, 3.2% in the past 30-days. One in seven (14.3%) had ever used a hemp wrap, 2.3% in the past 30-days. Non-Hispanic Black young adults were 1.55 and 2.91 times as likely to have ever used blunt or hemp wraps, respectively, compared to non-Hispanic Whites. Similarly, participants who identified as gay or lesbian or bisexual similarly had greater odds of having ever used blunt or hemp wraps. Hispanic young adults were 2.49 times as likely to have used hempwraps compared to non-Hispanic Whites. Conclusion: Blunt and hemp wrap use is prevalent among young adults, particularly among minoritized populations. Continued research and surveillance of use of these products is needed to fully evaluate the impact their use may have on the broader population. [ABSTRACT FROM AUTHOR]

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.

Individuals with autism demonstrate atypical and variable responses to social and emotional stimuli, perhaps reflecting heterogeneity of the disorder. The goal of this study was to determine whether unique profiles of psychophysiological responses to such stimuli could be identified in individuals diagnosed with autism spectrum disorder (ASD), with fragile X syndrome (FXS), and with comorbid autism and fragile X syndrome (ASD + FXS), and in typically developing (TYP) individuals. This study included 52 boys (ages 10-17): idiopathic ASD (n = 12), FXS (n = 12), comorbid ASD + FXS (n = 17), and TYP (n = 11). Physiological responses, including potentiated startle, electrodermal response, heart rate variability, and vagal tone, were collected concurrently while participants viewed emotionally evocative pictures of human faces or nonsocial images. Although some of these measures have been utilized separately for investigations on these diagnostic groups, they have not been considered together. Results using Kruskal-Wallis one-way analysis of variance by ranks indicate statistically significant differences in distributions of autonomic regulation responses between groups. The most notable differences were between the ASD group and both the FXS groups on measures of sympathetic activity, with FXS groups evincing increased activity. Also, both the ASD and ASD + FXS groups showed significantly decreased parasympathetic activity compared with FXS and TYP groups. In addition, the ASD + FXS group demonstrated a unique distribution of startle potentiation and arousal modulation. This study provides evidence that autonomic arousal and regulation profiles could be useful for distinguishing subgroups of autism and shed light on the variability underlying emotional responsivity.

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.

Research increasingly emphasizes understanding differential effects. This article focuses on understanding regression mixture models, which are relatively new statistical methods for assessing differential effects by comparing results to using an interactive term in linear regression. The research questions which each model answers, their formulation, and their assumptions are compared using Monte Carlo simulations and real data analysis. The capabilities of regression mixture models are described and specific issues to be addressed when conducting regression mixtures are proposed. The article aims to clarify the role that regression mixtures can take in the estimation of differential effects and increase awareness of the benefits and potential pitfalls of this approach. Regression mixture models are shown to be a potentially effective exploratory method for finding differential effects when these effects can be defined by a small number of classes of respondents who share a typical relationship between a predictor and an outcome. It is also shown that the comparison between regression mixture models and interactions becomes substantially more complex as the number of classes increases. It is argued that regression interactions are well suited for direct tests of specific hypotheses about differential effects and regression mixtures provide a useful approach for exploring effect heterogeneity given adequate samples and study design.

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.

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]

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]

Peer victimization is common and linked to maladjustment. Prior research has typically identified four peer victimization subgroups: aggressors, victims, aggressive‐victims, and uninvolved. However, findings related to sex and racial‐ethnic differences in subgroup membership have been mixed. Using data collected in September of 2002 and 2003, this study conducted confirmatory latent class analysis of a racially‐ethnically diverse sample of 5415 sixth graders (49% boys; 50.6% Black; 20.9% Hispanic) representing two cohorts from 37 schools in four U.S. communities to replicate the four subgroups and evaluate measurement invariance of latent class indicators across cohort, sex, race‐ethnicity, and study site. Results replicated the four‐class solution and illustrated that sociodemographic differences in subgroup membership were less evident after accounting for differential item functioning. [ABSTRACT FROM AUTHOR]