Purpose of Review-The purpose of this review is to provide an overview of the existing literature on the relationship between the co-use of cannabis and alcohol including (1) epidemiology, comorbidity, and associated consequences of cannabis and alcohol use disorders; (2) preclinical and clinical laboratory studies examining behavioral pharmacology of cannabis and alcohol co-use; and (3) clinical outcomes related to co-use. Recent Findings-Findings from the literature reviewed suggest that the co-use of alcohol and cannabis is associated with additive performance impairment effects, higher and more frequent consumption levels, increased social and behavioral consequences such as driving while impaired, and greater likelihood of the experiencing comorbid substance use and mental health disorders. Furthermore, co-use may be associated with worse clinical outcomes, yet there are few studies examining the development and evaluation of interventions on reducing the co-use of cannabis and alcohol. Summary-There is a need for more rigorous and longitudinal research studies on the co-use of cannabis and alcohol to glean a more complete understanding of the relationship between the two substances. Findings can be used to develop and refine intervention strategies to successfully reduce cannabis and alcohol co-use.

Background A valid measure of the relative economic value of marijuana is needed to characterize individual variation in the drug’s reinforcing value and inform evolving national marijuana policy. Relative drug value (demand) can be measured via purchase tasks, and demand for alcohol and cigarettes has been associated with craving, dependence, and treatment response. This study examined marijuana demand with a marijuana purchase task (MPT). Methods The 22-item self-report MPT was administered to 99 frequent marijuana users (37.4% female, 71.5% marijuana use days, 15.2% cannabis dependent). Results Pearson correlations indicated a negative relationship between intensity (free consumption) and age of initiation of regular use (r=−0.34, p<0.001), and positive associations with use days (r=0.26, p<0.05) and subjective craving (r=0.43, p<0.001). Omax (maximum expenditure) was positively associated with use days (r=0.29, p<0.01) and subjective craving (r=0.27, p<0.01). Income was not associated with demand. An exponential demand model provided an excellent fit to the data across users (R2=0.99). Group comparisons based on presence or absence of DSM-IV cannabis dependence symptoms revealed that users with any dependence symptoms showed significantly higher intensity of demand and more inelastic demand, reflecting greater insensitivity to price increases. Conclusions These results provide support for construct validity of the MPT, indicating its sensitivity to marijuana demand as a function of increasing cost, and its ability to differentiate between users with and without dependence symptoms. The MPT may denote abuse liability and is a valuable addition to the behavioral economic literature. Potential applications to marijuana pricing and tax policy are discussed.

Background Distinct behavioral economic domains, including high perceived drug value (demand) and delay discounting (DD), have been implicated in the initiation of drug use and the progression to dependence. However, it is unclear whether frequent marijuana users conform to a “reinforcer pathology” addiction model wherein marijuana demand and DD jointly increase risk for problematic marijuana use and cannabis dependence (CD). Methods Participants (n=88, 34% female, 14% cannabis dependent) completed a marijuana purchase task at baseline. A delay discounting task was completed following placebo marijuana cigarette (0% THC) administration during a separate experimental session. Results Marijuana demand and DD were quantified using area under the curve (AUC). In multiple regression models, demand uniquely predicted frequency of marijuana use while DD did not. In contrast, DD uniquely predicted CD symptom count while demand did not. There were no significant interactions between demand and DD in either model. Conclusions These findings suggest that frequent marijuana users exhibit key constituents of the reinforcer pathology model: high marijuana demand and steep discounting of delayed rewards. However, demand and DD appear to be independent rather than synergistic risk factors for elevated marijuana use and risk for progression to CD. Findings also provide support for using AUC as a singular marijuana demand metric, particularly when also examining other behavioral economic constructs that apply similar statistical approaches, such as DD, to support analytic methodological convergence.