This study aims to explore the extent to which risk factors grounded in general strain theory consistently influence adolescent substance use across varying situational contexts.
Drawing on self-reported data from the 2022 Minnesota Student Survey (MSS; n = 123,583), this study employs conjunctive analysis of case configurations to explore profiles of adolescents at risk of substance use through the lens of general strain theory.
The results of this study indicated that some strains experienced by adolescents contribute to an increased risk of substance use and that these outcomes are highly context dependent.
While the outcomes of this study generally align with prior research demonstrating a link between adolescents’ experiences of certain strains and substance use, the results regarding the dominant profiles and the main effects of likelihood on substance use were not necessarily consistently stable across these profiles.
Schools offering adolescent substance use programs should consider the significant strains youth face and incorporate these factors into effective, evidence-based interventions tailored to those most at risk, using generated risk profiles informed by a Conjunctive Analysis of Case Configurations (CACC) approach. This targeted strategy is likely more effective than generalized programs aimed at the broader student population.
By acknowledging limited resources and funding many schools face, such an approach ensures that support reaches those who need it most and avoids blanket strategies that have demonstrated ineffective results.
While few studies have attempted to explain why adolescents engage in substance use through the lens of General Strain Theory (GST), consistent support for the core propositions of GST is lacking. One potential explanation for this inconsistency lies in the reliance on variable-oriented methods in prior research. These inquiries have not systematically examined the contextual profiles of adolescents and the likelihood of substance use defined by these multidimensional profiles. In response, data from the 2022 MSS were analyzed using CACC.
