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Background Depression is currently the second largest contributor to non-fatal disease burden globally. For that reason, economic evaluations are increasingly being conducted using data from depression prevalence estimates to analyze return on investments for services that target mental health. Psychiatric epidemiology studies have reported large cross-national differences in the prevalence of depression. These differences may impact the cost-effectiveness assessments of mental health interventions, thereby affecting decisions regarding government and multi-lateral investment in mental health services. Some portion of the differences in prevalence estimates across countries may be due to true discrepancies in depression prevalence, resulting from differential levels of risk in environmental and demographic factors. However, some portion of those differences may reflect non-invariance in the way standard tools measure depression across countries. This paper attempts to discern the extent to which measurement differences are responsible for reported differences in the prevalence of depression across countries. Methods and findings This analysis uses data from the World Mental Health Surveys, a coordinated series of psychiatric epidemiology studies in 27 countries using multistage household probability samples to assess prevalence and correlates of mental disorders. Data in the current study include responses to the depression module of the World Mental Health Composite International Diagnostic Interview (CIDI) in four countries: Two high-income, western countries—the United States (n = 20, 015) and New Zealand (n = 12,992)—an upper-middle income sub-Saharan African country, South Africa (n = 4,351), and a lower-middle income sub-Saharan African country, Nigeria (n = 6,752). Latent class analysis, a type of finite mixture modeling, was used to categorize respondents into underlying categories based on the variation in their responses to questions in each of three sequential parts of the CIDI depression module: 1) The initial screening items, 2) Additional duration and severity exclusion criteria, and 3) The core symptom questions. After each of these parts, exclusion criteria expel respondents from the remainder of the diagnostic interview, rendering a diagnosis of "not depressed". Latent class models were fit to each of the three parts in each of the four countries, and model fit was assessed using overall chi-square values and Pearson standardized residuals. Latent transition analysis was then applied in order to model participants' progression through the CIDI depression module. Proportion of individuals falling into each latent class and probabilities of transitioning into subsequent classes were used to estimate the percentage in each country that ultimately fell into the more symptomatic class, i.e. classified as "depressed". This latent variable design allows for a non-zero probability that individuals were incorrectly excluded from or retained in the diagnostic interview at any of the three exclusion points and therefore incorrectly diagnosed. Prevalence estimates based on the latent transition model reversed the order of depression prevalence across countries. Based on the latent transition model in this analysis, Nigeria has the highest prevalence (21.6%), followed by New Zealand (17.4%), then South Africa (15.0%), and finally the US (12.5%). That is compared to the estimates in the World Mental Health Surveys that do not allow for measurement differences, in which Nigeria had by far the lowest prevalence (3.1%), followed by South Africa (9.8%), then the United States (13.5%) and finally New Zealand (17.8%). Individuals endorsing the screening questions in Nigeria and South Africa were more likely to endorse more severe depression symptomology later in the module (i.e. they had higher transition probabilities), suggesting that individuals in the two Western countries may be more likely to endorse screening questions even when they don't have as severe symptoms. These differences narrow the range of depression prevalence between countries 14 percentage points in the original estimates to 6 percentage points in the estimate taking account of measurement differences. Conclusions These data suggest fewer differences in cross-national prevalence of depression than previous estimates. Given that prevalence data are used to support key decisions regarding resource-allocation for mental health services, more critical attention should be paid to differences in the functioning of measurement across contexts and the impact these differences have on prevalence estimates. Future research should include qualitative methods as well as external measures of disease severity, such as impairment, to assess how the latent classes predict these external variables, to better understand the way that standard tools estimate depression prevalence across contexts. Adjustments could then be made to prevalence estimates used in cost-effectiveness analyses.

Most applications of person-centered methodologies have relied on data-driven approaches to class enumeration. As person-centered analyses grow in popularity within organizational research, confirmatory approaches may be sought to provide more stringent theoretical tests and to formalize replication efforts. Confirmatory latent class analysis (LCA) is achieved through placement of modeling constraints, yet there is variation in the types of potential constraints and a lack of standardization in evaluating model fit in published work. This article provides a comprehensive framework for operationalizing model constraints and demonstrates confirmatory LCA via two illustrations: (a) a dual sample approach ( n = 1,366 and n = 1,367 in exploratory and validation samples, respectively) and (b) confirmatory testing of a hypothesized latent class structure ( n = 1,483). We depict operationalization of threshold boundary and/or equality constraints under both illustrations to generate a confirmatory latent class structure, and explain methods of model evaluation and comparison to alternative models. The confirmatory model was well supported under the dual sample approach, and partially supported under the hypothesis-driven approach. We discuss decision making at various points of model estimation and end with future methodological developments.

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.

AbstractThis 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.

Parental physical illness has been associated with a variety of negative child outcomes but the mechanisms explaining this relationship are not fully understood. Additionally, few studies have explored what role, if any, marital status may play in this relationship. This study used prospective longitudinal survey data from 382 two-parent and 182 single-parent families in the Iowa Youth and Families and Single Parents Project to explore the relationship between maternal illness and parenting with depressed affect as a potential mediator. Multiple group structural equation modeling was used to investigate whether the relationships between these indicators were the same for single and married mothers. Analyses revealed associations between mothers' illness and parenting for both single and married mothers, but mothers' depressed affect played a meditational role for single mothers, which was not evident with married mothers. Both the empirical and clinical implications of these findings are discussed.

BACKGROUND: Youth living in the slums of Kampala face many adversities, such as dire environmental conditions, poverty, and lack of government infrastructure. OBJECTIVE: The purpose of this study is to examine the interplay of alcohol use and child maltreatment on suicidal ideation among youth living in the slums of Kampala, Uganda. PARTICIPANTS AND SETTING: The study sample includes service-seeking youth who were attending Uganda Youth Development Link (UYDEL) drop-in centers in spring 2014 (n=1,134). METHODS: Indicators of child maltreatment included parental physical abuse, parental neglect, and sexual abuse. Problematic alcohol use was specified using a hybrid structural equation mixture model that distinguished current drinking status with the frequency and intensity of use among current drinkers. This novel approach is more flexible than restricting our analysis to only drinkers or analyzing only current drinking status. The primary outcome of interest was suicidal ideation. All associations controlled for gender and age, and all associations were estimated simultaneously. All analyses were conducted in SAS 9.4 and Mplus 7.4. RESULTS: The overall prevalence of suicidal ideation was 23.5% (n=266). Overall, current drinking status (OR: 1.80; 95% CI: 1.31, 2.46), the child maltreatment sum score (OR: 1.88; 95% CI: 1.48, 2.39), and sexual abuse (OR: 2.88; 95% CI: 1.52, 5.47) were statistically significantly associated with reporting suicidal ideation. CONCLUSIONS: This study highlights a population that would potentially benefit from prevention efforts not only aimed at suicide prevention but also harm reduction in terms of alcohol use and experiences of child maltreatment.

Scant research exists on the development of mostly heterosexual identity, the largest sexual orientation minority subgroup. We used longitudinal latent class analysis to characterize the patterns of identification with lesbian, gay, bisexual (LGB), or mostly heterosexual identities from ages 12 to 23 in 13,859 youth (57% female) in a U.S. national cohort. Three classes emerged: completely heterosexual (88.2%), mostly heterosexual (9.5%), and LGB (2.4%). LGB class youth generally identified with sexual minority identities by ages 12–17. In contrast, mostly heterosexual class youth identified with sexual minority identities gradually, with steady increases in endorsement starting at the age of 14. Developmental implications of these differential patterns are discussed.