A behavioral economic approach to assessing demand for marijuana.

Abstract

In the U.S., marijuana is the most commonly used illicit drug. Its prevalence is growing, particularly among young adults. Behavioral economic indices of the relative reinforcing efficacy (RRE) of substances have been used to examine the appeal of licit (e.g., alcohol) and illicit (e.g., heroin) drugs. The present study is the first to use an experimental, simulated purchasing task to examine the RRE of marijuana. Young-adult (M age = 21.64 years) recreational marijuana users (N = 59) completed a computerized marijuana purchasing task designed to generate demand curves and the related RRE indices (e.g., intensity of demand - purchases at lowest price; Omax - max. spent on marijuana; Pmax - price at which marijuana expenditure is max). Participants “purchased” high-grade marijuana across 16 escalating prices that ranged from $0/free to $160/joint. They also provided 2-weeks of real-time, ecological momentary assessment reports on their marijuana use. The purchasing task generated multiple RRE indices. Consistent with research on other substances, the demand for marijuana was inelastic at lower prices but became elastic at higher prices, suggesting that increases in the price of marijuana could lessen its use. In regression analyses, the intensity of demand, Omax and Pmax, and elasticity each accounted for significant variance in real-time marijuana use. These results provide support for the validity of a simulated marijuana purchasing task to examine its reinforcing efficacy. This study highlights the value of applying a behavioral economic framework to young-adult marijuana use and has implications for prevention, treatment, and policies to regulate marijuana use.

Further validation of a marijuana purchase task

“…MPT data were consistent with previous research employing purchase tasks to assess drug demand (e.g., Collins et al, 2014; MacKillop et al, 2008; Murphy and MacKillop, 2006), as estimated consumption of marijuana hits decreased as price per hit increased. Moreover, the MPT demonstrated robust convergent validity, as demand metrics (i.e., intensity, O max , and elasticity) were significantly associated with marijuana use variables (i.e., subjective marijuana craving, age at initiation of regular marijuana use, marijuana dependence symptoms, and percent of marijuana use days).…”

“…The first study examining the behavioral economics of marijuana utilized a novel marijuana purchase task (MPT) to investigate simulated demand for marijuana (Collins et al, 2014). Collins and colleagues (2014) administered a MPT to 59 recreational marijuana users, asking them to estimate the number of marijuana joints they would purchase at increasing prices. The study employed ecological momentary assessment to collect real-time marijuana use data and subsequently investigated the associations between marijuana use and MPT demand indices.…”

Change in delay discounting and substance reward value following a brief alcohol and drug use intervention

“…Further, although our results suggesting that alcohol demand is relevant to marijuana use outcomes is interesting, future research should include a measure of marijuana demand (Collins, Vincent, Yu, Liu, & Epstein, 2014). Finally, although research has shown that college student self-report measures of substance use are generally accurate (Hagman, Clifford, Noel, Davis, & Cramond, 2007), a biological measure of alcohol or marijuana use may have been helpful in confirming these results.…”

Further evidence of close correspondence for alcohol demand decision making for hypothetical and incentivized rewards

“…Future studies should extend these findings to other addictive commodities, such as comparing preferences for hypothetical and actual cigarettes (Jacobs and Bickel 1999; MacKillop et al 2008) or illicit drugs (Collins et al 2014). More broadly, this study offers additional support for utilizing purchase tasks as efficient and valid assessments of behavioral economic demand.…”

“…Demand can be readily assessed via self-report purchase tasks that ask individuals how much of an addictive commodity (e.g., alcohol, tobacco, illicit drugs) they would consume at escalating prices (Collins et al 2014; Jacobs and Bickel 1999; MacKillop et al 2008; Murphy and MacKillop 2006). Studies using alcohol purchase tasks (APTs), for instance, have found that alcohol demand is associated with quantity/frequency of alcohol consumption, alcohol use disorder severity, and treatment outcomes (e.g., Murphy and MacKillop 2006; MacKillop, Miranda, et al 2010; MacKillop and Murphy 2007).…”