Examining Approval and Social Norms as Proximal Predictors of the Impulsivity-Cannabis Use Relation

Authors

  • Angela K. Stevens Texas Tech University, Lubbock, TX
  • Brittany E. Blanchard Texas Tech University, Lubbock, TX
  • Andrew K. Littlefield Texas Tech University, Lubbock, TX

Abstract

Cannabis is a commonly used substance among college students and is associated with a host of negative consequences. Psychosocial variables (e.g., social norms, attitudes, and impulsivity) may explain individual differences regarding the increased cannabis use in recent years. Attitudes, social norms, and broadband impulsivity have demonstrated consistent, independent relations with increased cannabis use; however, relations among approval and social norms, narrowband impulsivity, and cannabis use remain elusive. The current study (N = 718) examined approval (i.e., approval of peer cannabis use) and social norms as proximal predictors of impulsivity-cannabis use relations among college students across models of varying multivariate complexity. Results from simpler multivariate models indicated that indirect effects of impulsivity-like facets, as assessed by the UPPS-P Impulsive Behavior Scale, were statistically significant for all models via approval, descriptive norms, and injunctive norms. In general, individuals higher in impulsivity-like facets reported more positive attitudes or more perceived use or approval by friends, which, in turn, was associated with more cannabis use. Differential relations emerged for the complex multivariate mediation model, such that approval exhibited the most consistent unique mediation effect. Multi-group analyses by gender revealed an indirect effect of sensation seeking via descriptive norms stronger for males than females. Consistent with the alcohol literature, this research highlights the importance of examining approval and social norms as proximal predictors of cannabis use, particularly as it is relevant for developing efficacious clinical interventions to reduce cannabis use by employing personalized normative feedback.

DOI: 10.26828/cannabis.2018.01.005

Additional Files

Published

2018-01-30

Issue

Section

Original Report