Abstract
Latent variable mixture modeling was used to identify subgroups of adolescents with distinct profiles of risk factors from individual, family, peer, and broader contextual domains. Data were drawn from the National Longitudinal Study of Adolescent Health. Four-class models provided the most theoretically meaningful solutions for both 7th (n = 907; 48% boys) and 11th (n = 1039; 51% boys) graders. The 4-class solution for 7th graders included low risk (LR; 66%), socioeconomic disadvantage (SD; 19%), peer high risk (PHR; 9%), and family high risk (FHR; 6%) groups. Similarly, the 4-class model for 11th graders included LR (32%), SD (43%), high risk (HR; 21%), and FHR (4%) groups. Subgroup membership predicted reported levels of depressive symptoms and conduct problems both concurrently and over time. Strengths and potential limitations of using latent variable mixture modeling to investigate risk profiles for adolescent psychopathology are discussed.
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