Suchergebnisse

We aimed to characterize developmental patterns of involvement in alcohol use, delinquency, and interpersonal aggression in a normative sample of adolescents by applying multitrajectory group‐based modeling. Using seven waves of data from a cohort sequential study spanning the 6th to 12th grades (n = 2,825; 50% girls), we identified four distinct trajectory groups: low risk (33%), declining peer aggressors (44%), peer and dating aggressors (13%), and multidomain high risk (10%). Across all comparisons, girls were more likely than boys to be members of the peer and dating aggressor group and less likely to be members of the multidomain high‐risk group. Moreover, individual (self‐control, negative emotionality), family (family violence, parental monitoring), and peer (substance use norms) distinguished class membership.

In the study of adolescent health, it is useful to derive indices of social dynamics from sociometric data, and to use these indices as predictors of health risk behaviors. In this manuscript, we introduce a flexible latent variable model as a novel way of obtaining estimates of social integration and social status from school‐based sociometric data. Such scores provide the flexibility of a regression‐based approach while accounting for measurement error in sociometric indicators. We demonstrate the utility of these factor scores in testing complex hypotheses through a combination of structural equation modeling and survival models, showing that deviance mediates the relationship between social status and smoking onset hazard at the transition to high school.

Introduction: Young adulthood is a critical time for the emergence of risk behaviors including smoking. Psychological health is associated with smoking, but studies rarely track both over time. We used longitudinal data to assess whether average patterns of psychological health influenced average patterns of smoking and whether short-term fluctuations in psychological health influenced fluctuations in smoking. Method: Young adults aged 18–30 from the Panel Study of Income Dynamics were followed from 2007 to 2013, and mean trajectories of smoking were modeled. Psychological health variables included ever having a mental health diagnosis and time-varying distress. Results: In regression models, individuals with poorer psychological health (higher distress or a diagnosis) were more likely to be smokers and to smoke greater number of cigarettes. The association of diagnosis with number of cigarettes smoked increased with age. Conclusions: Smoking-related interventions should target individuals with poorer psychological health, even if they have no formal mental health diagnosis.