Individual Differences in Substance Use Motives, Trauma, and Stress Among College-Based Polysubstance Users

Abstract

Background: Co-use of alcohol and other drugs within a certain time frame (i.e., polysubstance use) has become increasingly prevalent, particularly among college-aged individuals, but understanding motives for co-use remains limited. Polysubstance use has been associated with a higher likelihood of negative health consequences as compared to single substance use. Objectives: The current study examined associations between motivations for using alcohol, tobacco, and cannabis among college students who use multiple substances versus students using only one substance or no substances. Additionally, we examined the effect of trauma and daily stress on polysubstance use in self-report data from individuals (N=134) participating in the MAPme Study. Results: First, the observed prevalence of polysubstance use was greater than expected by chance, with most individuals co-using alcohol and cannabis. "Alcohol and Other Drug Users" were more frequently motivated to drink for social (β=0.27, CI=[0.07, 0.44]), enhancement (β=0.26, CI=[0.01, 0.42]) and coping (β=0.21, CI=[0.06, 0.47]) reasons compared to individuals who consumed alcohol alone. Conclusions: Individual differences in motivations for use were partly explained by frequency of alcohol use and alcohol problem severity, but not by history of trauma or stress. Finally, while patterns of correlations among motivations for use across substances suggested a general tendency to be motivated to use substances for similar reasons, this was not supported by confirmatory factor models. Overall, shared motives may inform potential behavioral patterns for co-use of substances during college and might advise future treatment efforts.

Keywords: Polysubstance use; stress; substance co-use; substance use motives; trauma.

Figure 1a:

General Factor Model i. A Priori General Factor Model

Figure 1b:

Correlated Factor Model ii. A Priori Correlated Factors Model

Figure 1c:

Bifactor Model iii. A Priori Bifactor Model

Figure 1d:

Correlated Motives Factor Model iv. A Priori Correlated Factor Model

Figure 2:

Grneral Factor Model iv. General Factor Model with Factor Loadings and 95% CI

Figure 3:

Correlated Factor Model v. Correlated Factor Model with Factor Loadings and 95% CI

Figure 4:

Bifactor Model vi. Bifactor model with Factor Loadings and 95% CI