A two-factor structure for cannabis use disorder identification test and its associations with demographic factors and cannabis use motives.

Abstract

Introduction: Cannabis use is linked to the risk of developing a Cannabis Use Disorder (CUD), which can often be chronic. Early identification of problematic cannabis use is crucial to lower the risk of CUD and associated adverse effects. However, the factor structure of the widely used Cannabis Use Disorder Identification Test (CUDIT) remains ambiguous. Furthermore, the impact of age and gender on CUD assessed with CUDIT is unknown. Exploring cannabis use motives has been proposed to better understand susceptibility to CUD. This study aims to clarify the CUDIT's factor structure, its links to cannabis use motives, and the influence of age and gender on CUD.

Materials and methods: We analyzed data from 3454 people who use cannabis (20.5% women; mean age = 30.31 years), collected from a Swiss online survey. Participants were categorized into four groups: younger men, younger women, older men, older women. Principal Component Analysis and Confirmatory Factor Analysis tested the factor structure of the revised CUDIT version (CUDIT-R). Structural Equation Modeling explored whether the influence of use motives on the CUDIT-R factors differs between demographic groups.

Results: The results suggest that the CUDIT-R scale is best represented by two factors: Use Intensity (Cronbach's $\alpha$ = 0.71) and Awareness of Problematic Use (Cronbach's $\alpha$ = 0.72). Use Intensity was lowest for younger women, and younger participants were more aware of negative effects. Gender, age, and use motives uniquely relate with both CUDIT-R factors, highlighting the CUDIT-R's potential to guide early identification and treatment of individuals at risk for CUD.