A Multivariate Associative Finite Growth Mixture Modeling Approach Examining Adolescent Alcohol and Marijuana Use

Theoretical and empirical substance use development research suggests that adolescent populations are not homogenous and can often be separated into subpopulations characterized by qualitatively different patterns of substance use development. This paper demonstrates the application of a multivariate associative finite latent growth mixture modelling approach to examine heterogeneity in patterns of adolescent alcohol and marijuana use and the influence of age, gender, parent, and peer substance use. Substance use problem outcomes were also examined. Participants were male and female adolescents (N = 1,044) ranging in age from 11 to 17 years at the first assessment (Mean age = 14.47; SD = 1.95). Individuals were 45% female and 82% Caucasian. Using growth mixture methodology, a 7-class model captured distinct simultaneous alcohol and marijuana use patterns over a 3-year period. Findings highlight the importance of examining subgroups of adolescent substance use, rather than focusing only on single samples.