Correlates of Amount Spent on Marijuana Buds During a Discrete Purchase at Medical Marijuana Dispensaries: Results from a Pilot Study

The importance of psychology for shaping legal cannabis regulation

Different patterns of cannabis use can be traced directly back to different interactions between 2 types of variables: pharmacological and environmental. As legal cannabis expands in the U.S. and around the world, state and national regulatory agencies are gaining control over these variables. Specifically, regulatory agencies are increasingly capable of altering (a) the pharmacological properties of cannabis products and (b) the way these products are distributed to the population. Consequently, cannabis regulatory agencies are in a unique position to use evidence from psychological science to alter cannabis consumption patterns in ways that mitigate potential harm to public health. However, most state-level legal cannabis regulatory systems in the U.S. are not yet evidence-based or public health-oriented. This applied review and commentary draws on evidence from the psychological science literature to help regulators better understand the types of behaviors they must address and guide empirically supported regulation of THC-laden cannabis, whether used putatively for medical or recreational reasons. This review is organized into 3 parts that correspond to the 3 primary agents within the cannabis regulation ecosystem: (a) the cannabis consumer, (b) the cannabis industry, and (c) the cannabis regulatory agency. Within this structure, the review addresses critical psychological variables that drive cannabis consumer and industry behaviors and discusses how regulatory agencies can use this information to protect public health. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Geolocation of Maryland Medical Marijuana Dispensaries by Community Income and Racial Characteristics: An Ecological Design

Background: Prior investigations have documented disparities in the supply side of Maryland's Medical Marijuana program. Initially a disproportionate share of licenses to cultivate and distribute medical marijuana were awarded to Non-Hispanic White owned businesses. The state has implemented measures to ameliorate the inequity by prioritizing license awards to qualified minority owned businesses. Objectives: The objective of this study is to examine the racial and income characteristics of communities where licensed dispensaries are located. We quantify the racial and income characteristics of communities where Maryland medical cannabis dispensaries are located and explore whether Maryland medical marijuana dispensaries disproportionately locate in high-income, majority-White zip codes. Method: Using data from the Maryland Medical Cannabis Commission and the American Communities Survey, we create geocodes for each of the operating dispensaries as of December 2019. We examine the distribution of medical cannabis dispensaries by zip code level household income and zip code level racial distribution. The data set encompasses 85 operating cannabis dispensaries in Maryland and 6.1 million Marylanders distributed across 468 zip codes in 2018-2019. Results: The analysis indicates that dispensaries are concentrated in zip codes whose residents are racially diverse, and with higher concentrations of retail establishments. Conclusion: Community level racial or income disparities in access to medical cannabis were not observed in Maryland. Access to medical cannabis, based on ability to pay out of pocket for the product, may be uneven.

Who's Buying What and How Much? Correlates of Purchase Behaviors From Medical Marijuana Dispensaries in Los Angeles, California

Venue-based distribution of marijuana has become the normative model in the United States to obtain marijuana. This study examines one-time purchase behaviors at medical marijuana dispensaries (MMDs) to identify potential venue- and individual-level targets for prevention. We used a two-stage, venue-based sampling approach to randomly select patrons exiting 16 MMDs in Los Angeles, California during the spring of 2013. Patrons (N = 595) reported their discrete purchase behaviors during their most recent visit to the sampled MMD. We used hierarchical linear modeling to examine the amount spent on marijuana products, regressed on characteristics of the sampled dispensaries and their patrons. We used hierarchical generalized linear modeling to examine the likelihood of purchasing specific types of marijuana products and total grams of loose-leaf buds purchased. Patrons spent US$41.73 on average, with a range of $0-$330. We observed significant variation in purchase behaviors across MMDs and associations between venues located within high median income census tracts and a higher total amount spent and lower odds of purchasing only loose-leaf buds. The networked distance between a patron's home and the sampled MMD was positively associated with the total amount spent and total quantity of buds purchased. We also found significant relationships between medical conditions reported for use in three models: total amount spent, purchase of pre-rolled joints, and total grams of buds purchased. Policy makers may want to explore regulating the availability of specialty items that may be attractive to naïve users, such as pre-rolled joints or edibles, or high-concentration products that may be sought out by regular, heavy users.

Characterization of mental health in cannabis dispensary users, using structured clinical interviews and standardized assessment instruments

BACKGROUND

Cannabis is commonly used for its medical properties. In particular, cannabis is purported to have beneficial effects on a wide range of neuropsychiatric conditions. Studies assessing mental health in cannabis dispensary users typically evaluate symptoms using self-report check lists, which provide limited information about symptom severity, and whether subjects meet criteria for a psychiatric diagnosis. There is, therefore, a need for studies which assess mental health in dispensary users with standardized and well validated scientific instruments, such as those used in clinical drug trials.

METHODS

One hundred medical cannabis users were recruited from a community dispensary. All subjects completed a structured clinical interview with the Mini-International Neuropsychiatric Interview (MINI). Subjects also completed the Perceived Stress Scale-10, PROMIS Fatigue Scale, PROMIS Sleep Disturbance Scale, Beck Depression Inventory, the Patient Health Questionnaire-15 and the Brief Pain Inventory. Details about cannabis use were also recorded.

RESULTS

Lifetime prevalence of mental illness in this cohort was high, and a large proportion of subjects endorsed psychological symptoms. The proportion of subjects who met criteria for classification of a current psychiatric disorder was low for mood disorders, but high for anxiety disorders and substance abuse/dependence. Cannabis use differed between the main psychiatric conditions.

CONCLUSIONS

The present results indicate that rates of mental illness may be high in medical cannabis dispensary users. Use of structured clinical assessments combined with standardized symptom severity questionnaires provide a feasible way to provide a more rigorous and detailed evaluation of conditions and symptoms in this population.

Cannabis use disorder and male sex predict medical cannabis card status in a sample of high risk adolescents

OBJECTIVE

To examine if a substance use disorder (SUD), especially cannabis use disorder in adolescence, predicts future medical cannabis card status among high-risk youth.

METHODS

Data collection occurred in Denver and San Diego. We recruited adolescents, with or at high risk for SUD and conduct problems (hereafter probands) and their siblings (n=654). Baseline (Wave 1) assessments took place between 1999 and 2008, and follow-up (Wave 2) took place between 2010 and 2013. In initial bivariate analyses, we examined whether baseline DSM-IV cannabis abuse/dependence (along with other potential predictors) was associated with possessing a medical cannabis card in young adulthood (Wave 2). Significant predictors were then included in a multiple binomial regression. Self-reported general physical health was also evaluated at both time points. Finally, within Wave 2, we tested whether card status was associated with concurrent substance dependence.

RESULTS

About 16% of the sample self-reported having a medical cannabis card at follow-up. Though bivariate analyses demonstrated that multiple predictors were significantly associated with Wave 2 card status, in our multiple binomial regression only cannabis abuse/dependence and male sex remained significant. At Wave 2, those with a medical cannabis card were significantly more likely to endorse criteria for concurrent cannabis dependence. There was no significant difference in self-reported general physical health.

CONCLUSIONS

Cannabis abuse/dependence and male sex positively predicted future medical cannabis card holder status among a sample of high risk adolescents. Physicians conducting evaluations for medical cannabis cards should carefully evaluate and consider past and concurrent cannabis addiction.

Medical Decision-Making Processes and Online Behaviors Among Cannabis Dispensary Staff

Background:

Most cannabis patients engage with dispensary staff, like budtenders, for medical advice on cannabis. Yet, little is known about these interactions and how the characteristics of budtenders affect these interactions. This study investigated demographics, workplace characteristics, medical decision-making, and online behaviors among a sample of budtenders.

Methods:

Between June and September 2016, a cross-sectional Internet survey was administered to budtenders in the San Francisco Bay Area and Greater Los Angeles. A total of 158 budtenders fully responded to the survey. A series of comparisons were conducted to determine differences between trained and untrained budtenders.

Results:

Among the 158 budtenders, 56% had received formal training to become a budtender. Several demographic differences were found between trained and untrained budtenders. For workplace characteristics, trained budtenders were more likely to report budtender as their primary job (74% vs 53%), practice more than 5 years (34% vs 11%), and receive sales commission (57% vs 16%). Trained budtenders were significantly less likely to perceive medical decision-making as very important (47% vs 68%) and have a patient-centered philosophy (77% vs 89%). Although trained budtenders had significantly lower Internet usage, they were significantly more likely to exchange information with patients through e-mail (58% vs 39%), text message (46% vs 30%), mobile app (33% vs 11%), video call (26% vs 3%), and social media (51% vs 23%).

Conclusions:

Budtenders who are formally trained exhibit significantly different patterns of interaction with medical cannabis patients. Future studies will use multivariate methods to better determine which factors independently influence interactions and how budtenders operate after the introduction of regulations under the newly passed Proposition 64 that permits recreational cannabis use in California.

Patterns of Twitter Behavior Among Networks of Cannabis Dispensaries in California

Background

Twitter represents a social media platform through which medical cannabis dispensaries can rapidly promote and advertise a multitude of retail products. Yet, to date, no studies have systematically evaluated Twitter behavior among dispensaries and how these behaviors influence the formation of social networks.

Objectives

This study sought to characterize common cyberbehaviors and shared follower networks among dispensaries operating in two large cannabis markets in California.

Methods

From a targeted sample of 119 dispensaries in the San Francisco Bay Area and Greater Los Angeles, we collected metadata from the dispensary accounts using the Twitter API. For each city, we characterized the network structure of dispensaries based upon shared followers, then empirically derived communities with the Louvain modularity algorithm. Principal components factor analysis was employed to reduce 12 Twitter measures into a more parsimonious set of cyberbehavioral dimensions. Finally, quadratic discriminant analysis was implemented to verify the ability of the extracted dimensions to classify dispensaries into their derived communities.

Results

The modularity algorithm yielded three communities in each city with distinct network structures. The principal components factor analysis reduced the 12 cyberbehaviors into five dimensions that encompassed account age, posting frequency, referencing, hyperlinks, and user engagement among the dispensary accounts. In the quadratic discriminant analysis, the dimensions correctly classified 75% (46/61) of the communities in the San Francisco Bay Area and 71% (41/58) in Greater Los Angeles.

Conclusions

The most centralized and strongly connected dispensaries in both cities had newer accounts, higher daily activity, more frequent user engagement, and increased usage of embedded media, keywords, and hyperlinks. Measures derived from both network structure and cyberbehavioral dimensions can serve as key contextual indicators for the online surveillance of cannabis dispensaries and consumer markets over time.