Cannabis Use Disorder Uniquely Predicts Educational Impairment in College Students Over and Above other Mental Health Disorders
Authors: Blessing Alexis , Russell Patricia , Hale Willie , Morissette Sandra 
Published: September 2022

Background: Approximately 40% of college students report using cannabis in the past year (Scholenberg et al., 2020) and nearly 1 in 10 (9.4%) first-year college students meet criteria for a cannabis use disorder (CUD; Caldiera et al., 2008). The prevalence CUD is concerning as it is linked to greater number of skipped classes and failure to graduate from college (Arria et al., 2015; Hunt et al., 2010). In addition, CUD is often co-morbid with other substance use and mental health symptoms that impact educational outcomes, including post-traumatic stress disorder (PTSD; Morissette et al., 2020), major depressive disorder (De Roma et al., 2009), and alcohol use disorder (AUD; Meda et al., 2017), yet the impact of CUD has not been examined within the larger context of these mental health problems. The aim of the current study was to examine the impact of CUD on education functioning and GPA within the context of co-occurring PTSD, MDD, and AUD. It was predicted that CUD, measured both continuously (CUD symptom severity) and dichotomously (presence/absence), would predict greater educational impairment and lower current overall GPA, even after taking into account age, gender, and presence of probable PTSD, MDD, and AUD. Method: College students (N = 210) who reported using cannabis within the past six months completed self-report questionnaires assessing trauma exposure (LEC-5), educational impairment (IPF-ES), CUD (CUDIT-R), PTSD (PCL-5), depression (PHQ-9), and AUD (AUDIT-R). Overall GPA was retrieved from college transcripts. Results: A series of hierarchical multiple regression analyses were conducted in SPSS version 25. In the continuous model, younger age (β = -.13, p < .05), presence of probable PTSD (β = .26, p < .01), and CUD symptom severity (β = .20, p < .01) significantly predicted educational impairment, with CUD symptom severity significantly improving model fit (R2 =.20; F(1, 203) = 10.13, p <.01). In the dichotomous model, younger age (β = -.13, p < .05), male gender (β = -.16, p < .05), presence of probable MDD (β = .17, p < .05), probable PTSD (β = .26, p < .01), significantly predicted educational impairment, however probable CUD did not ((β = .01, p = .151). Similar models for GPA indicated CUD symptom severity was the only significant predictor of low GPA (β = -.15, p < .01), yet presence of probable CUD was not significant (β = -.09, p = .183). Model fit was poor for both measurement types (Continuous Model: R2 =.01; F(1, 203) = 4.09, p <.05; Dichotomous Model: R2 = .00, F(1, 203) = 1.78, p = .183). Conclusion: CUD symptom severity negatively predicted both educational impairment and GPA, whereas probable CUD did not predict either outcome. Importantly, CUD symptom severity predicted over and above other common mental health conditions among college students. In the context of rapid legalization of cannabis, these data suggest that university counseling centers may need to incorporate CUD into treatment planning, particularly when students are experiencing educational challenges.