Reconsidering cannabis dependence
BACKGROUND: While the association between cannabis use and dependence is often characterised as being a dose-response type relationship, the available evidence does not support this consistently. As such, this study investigated associations between cannabis use factors and dependence with the aim of determining which factors explain variance in cannabis dependence scores of current cannabis users. A range of psychosocial and demographic factors were also investigated.
METHOD: The study sample consisted of 172 participants (60% female) who had used cannabis at least once in the past three months. Participants ranged in age from 18 to 71 years (M = 30.9; SD = 10.6) and had been using cannabis for 14 years on average (SD = 11.0; range: < 1 year to 46 year). They were recruited through social media and online forums to complete an anonymous online questionnaire. The questionnaire included detailed questioning regarding patterns of cannabis use as well as the Marijuana Motives Measure, the Severity of Dependence Scale. A range of psychosocial measures and demographic factors were also included.
RESULTS: Initially, subsets of variables that were expected to explain variance in SDS scores were examined through separate regression analyses. These were completed on the following five subsets of variables: demographics, history of use, frequency of use, cannabis consumption factors, and motives for use. Demographic factors (age, sex, education) and history of use (age at initiation, duration of use) factors were not found to explain a significant amount of variance in SDS scores, Frequency of use within the past 12 months and recent use accounted for 19% of variance in SDS scores. Cannabis consumption factors, including usual strength and quantity of cannabis consumed in a session and usual intoxication level, explained14% of variance in SDS scores. Interestingly, the motives for use explained a higher proportion of variance in SDS scores than the aforementioned patterns of cannabis use and consumption factors, accounting for 28% of the variance. In the final combined model, 44% of variance in SDS scores was explained by variables, with Coping motives accounting for the largest unique proportion of variance (11%), followed by usual intoxication level (6%). The role of psychosocial factors in explaining cannabis dependence will also be discussed.
CONCLUSIONS: To better understand why some cannabis users become dependent while others do not, we need to move beyond the rather simplistic dose-response explanation of cannabis dependence. While it is evident that cannabis can be an addictive substance, those who become dependent are not necessarily those who are heavier users of it. Rather, a range of other factors, including motives for using, play an important role. Further investigation of the complexity of factors contributing to cannabis dependence will enable a deeper and more nuanced understanding of what it means to be dependent on, or addicted to, cannabis. This will, thus, enhance our ability to prevent those at increased risk from becoming dependent and to treat those who are already affected.