Psychosocial predictors of substance use in adolescents and young adults: Longitudinal risk and protective factors.

Published on May 16, 2021in Addictive Behaviors3.645
· DOI :10.1016/J.ADDBEH.2021.106985
Ty Brumback15
Estimated H-index: 15
,
Wesley K. Thompson68
Estimated H-index: 68
+ 2 AuthorsSusan F. Tapert88
Estimated H-index: 88
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Abstract
Many psychosocial factors have been implicated in the onset and escalation of substance use in adolescence and young adulthood. Typically, each factor explains a small amount of the variance in substance use outcomes, and effects are typically applied across a broad range of ages or computed from cross-sectional data. The current study evaluated the association of factors including social influence (e.g., peer substance use), cognitive features (e.g., alcohol expectancies), and personality and emotional characteristics (e.g., impulsivity and typical responses to stress) in substance use throughout adolescence and emerging adulthood (ages 13-25; N = 798). Mixed-effects models tailored for the accelerated longitudinal design employed in this study were constructed with psychosocial and developmental factors predicting alcohol and cannabis use. As most participants in the sample exhibited little or no substance use at baseline by design, we excluded baseline assessments and examined data from follow-up years 1, 2, 3, and 4. Interactions between age cohort, change in age, and psychosocial predictors of substance use revealed differing associations over the developmental window for alcohol and cannabis use. For example, positive alcohol expectancies and sensation seeking were most strongly associated with greater drinking after age 18, whereas sensation seeking was associated with increased cannabis use as early as age 15. Higher emotion regulation skills led to less cannabis use in younger ages (i.e., shallower slopes below age 17), but this protective effect diminished after age 17. Results highlight developmentally important factors that differentially contribute to substance use in adolescence and young adulthood. We also demonstrate the importance of developmentally sensitive analyses that maximize the value of data from accelerated longitudinal designs.
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