Impacts of Marijuana Commercialization on Adolescents' Marijuana Beliefs, Use, and Co-use With Other Substances

Legalization and retail availability of recreational marijuana and adolescent use in schools

Legalization of use and retail sales of recreational marijuana in U.S. states and the associated potential increase in access to marijuana and normalization of its use by adults could lead to increased use by adolescents. Studies have found that states with legal recreational marijuana have higher rates of adolescent use and frequency of use compared to states without legal use. We examined changes in student office discipline referrals (ODRs) for substance use offenses in Oregon middle and high schools before and after the legalization of recreational marijuana relative to comparison schools in other states. We found that rates of substance use related ODRs in middle schools increased by 0.14 per 100 students (30% of the mean) with legalization relative to comparison schools. This increase was moderated by the presence of a marijuana outlet within one mile of the school. We found no statistically discernible changes in high school ODRs. Marijuana use in adolescence has been linked to negative health and social consequences, including academic problems, mental health issues, and impaired driving. Potential adverse impact on adolescents and investments in school-based prevention programs could be important considerations for policymakers and public health officials when evaluating marijuana legalization.

Health, safety, and socioeconomic impacts of cannabis liberalization laws: An evidence and gap map

Background

Globally, cannabis laws and regulations are rapidly changing. Countries are increasingly permitting access to cannabis under various decriminalization, medicalization, and legalization laws. With strong economic, public health, and social justice incentives driving these domestic cannabis policy reforms, liberalization trends are bound to continue. However, despite a large and growing body of interdisciplinary research addressing the policy-relevant health, safety, and socioeconomic consequences of cannabis liberalization, there is a lack of robust primary and systematic research that comprehensively investigates the consequences of these reforms.

Objectives

This evidence and gap map (EGM) summarizes the empirical evidence on cannabis liberalization policies. Primary objectives were to develop a conceptual framework linking cannabis liberalization policies to relevant outcomes, descriptively summarize the empirical evidence, and identify areas of evidence concentration and gaps.

Search Methods

We comprehensively searched for eligible English-language empirical studies published across 23 academic databases and 11 gray literature sources through August 2020. Additions to the pool of potentially eligible studies from supplemental sources were made through November 2020.

Selection Criteria

The conceptual framework for this EGM draws upon a legal epidemiological perspective highlighting the causal effects of law and policy on population-level outcomes. Eligible interventions include policies that create or expand access to a legal or decriminalized supply of cannabis: comprehensive medical cannabis laws (MCLs), limited medical cannabidiol laws (CBDLs), recreational cannabis laws (RCLs), industrial hemp laws (IHLs), and decriminalization of cultivations laws (DCLs). Eligible outcomes include intermediate responses (i.e., attitudes/behaviors and markets/environments) and longer-term consequences (health, safety, and socioeconomic outcomes) of these laws.

Data Collection and Analysis

Both dual screening and dual data extraction were performed with third person deconfliction. Primary studies were appraised using the Maryland Scientific Methods Scale and systematic reviews were assessed using AMSTAR 2.

Main Results

The EGM includes 447 studies, comprising 438 primary studies and nine systematic reviews. Most research derives from the United States, with little research from other countries. By far, most cannabis liberalization research focuses on the effects of MCLs and RCLs. Studies targeting other laws-including CBDLs, IHLs, and DCLs-are relatively rare. Of the 113 distinct outcomes we documented, cannabis use was the single most frequently investigated. More than half these outcomes were addressed by three or fewer studies, highlighting substantial evidence gaps in the literature. The systematic evidence base is relatively small, comprising just seven completed reviews on cannabis use (3), opioid-related harms (3), and alcohol-related outcomes (1). Moreover, we have limited confidence in the reviews, as five were appraised as minimal quality and two as low quality.

Authors’ Conclusions

More primary and systematic research is needed to better understand the effects of cannabis liberalization laws on longer-term-and arguably more salient-health, safety, and socioeconomic outcomes. Since most research concerns MCLs and RCLs, there is a critical need for research on the societal impacts of industrial hemp production, medical CBD products, and decriminalized cannabis cultivation. Future research should also prioritize understanding the heterogeneous effects of these laws given differences in specific provisions and implementation across jurisdictions.

Cannabis use among adolescents and emerging adults who use e-cigarettes: Findings from an online, national U.S. Sample

Concurrent use of e-cigarettes and cannabis among adolescents and emerging adults is a growing public health concern. More research is needed describing cannabis use among adolescents and emerging adults who vape. The objective of this study was to characterize cannabis use among adolescents and emerging adults (age 14-20) who reported e-cigarette ever-use, particularly their use of blunts and liquid cannabis vape (LCV) products. Using cross-sectional data from a national online survey, we describe their patterns of cannabis use, detail their use of flavored cannabis and tobacco products, and estimate associations of demographic factors and other current substance use behaviors with levels of blunt and LCV use. Of the 2253 respondents in the sample, 1379 (61 %) reported some form of cannabis use in the past 30 days, among whom 80 % used flavored cannabis (including edibles). Significant associations with current cannabis use were observed on several demographic measures, with current cannabis blunt use more frequent among participants not in school, non-Hispanic Blacks, multiracial respondents, and those whose incomes do not meet their expenses. Other than income, demographic characteristics were generally not associated with LCV use frequency. Use of other substances was associated with more frequent use of both blunts and LCV in the past 30 days, and enrollment in college or the military seems somewhat protective for emerging adults. These findings suggest a need for tailored prevention efforts among high-risk adolescents and emerging adults, potential regulation of added flavors in commercialized cannabis products, and stronger enforcement of retail restrictions for individuals under age 21 more broadly.

Do We Have Structure, Process and Outcomes to Support Cannabis as Supportive Therapy in Cancer?

Cannabis is becoming more popular and more available in the United States. It has been approved for use by multiple states for various conditions and several states now allow recreational cannabis. We explore the structure of cannabis distribution, the process of acquisition, outcomes, and the safety of cannabis in the United States.

Early and Late Adolescent Factors that Predict Co-use of Cannabis with Alcohol and Tobacco in Young Adulthood

The changing legal landscape of cannabis in the USA has coincided with changes in how cannabis is used, including its co-use with other substances. This study analyzed 10 years of data from a diverse cohort of youth (N = 2429; 54% Hispanic, 16% Asian, 16% white, 3% black, 10% multiracial) to examine predictors in early and late adolescence of co-use of alcohol with cannabis (AC) and tobacco with cannabis (TC) at age 21. Two forms of co-use were examined: concurrent (use of both substances in past month) and sequential (use of one substance right after the other). Analyses focused on four predictor domains: individual (e.g., resistance self-efficacy), peer (e.g., time spent around peers who use), family (e.g., sibling use), and neighborhood (i.e., perceived alcohol and drug problems in neighborhood). For each co-use combination (AC or TC), we estimated parallel process piecewise latent growth models in a structural equation modeling framework using Mplus v8. The final AC and TC co-use models included all predictor variables from the four domains. Increases in positive expectancies and time spent around peers who use AC, as well as steeper decreases in resistance self-efficacy, were all related to a greater likelihood of AC co-use in young adulthood. Increases in sibling TC use and time spent around peers who use TC, as well as steeper decreases in resistance self-efficacy, were all related to a greater likelihood of TC co-use in young adulthood. Overall, findings highlight the importance of addressing peer influence in prevention programming during both early and late adolescence.

Validation of secondary data sources for enumerating marijuana dispensaries in a state commercializing marijuana

OBJECTIVES

To assess 1) the validity of online crowdsourcing platforms in enumerating licensed brick-and-mortar marijuana dispensaries and 2) the validity of state licensing directory and online crowdsourcing platforms in enumerating active brick-and-mortar marijuana dispensaries in California.

METHODS

We obtained business lists from California Bureau of Cannabis Control (BCC) licensing directory and three online crowdsourcing platforms (Weedmaps, Leafly, and Yelp) in May 2019. Calls were made to verify street address, operation status, dispensary category (recreational-only, medical-only, recreational & medical), and presence of storefronts in May-July 2019. Validity measures, including sensitivity, specificity, positive predictive value, and negative predictive value, were calculated when applicable.

RESULTS

In identifying licensed dispensaries in BCC, Leafly had the highest sensitivity (.66) and Yelp had the highest specificity (.87). The dispensary category posted on online crowdsourcing platforms in over 25 % licensed dispensaries and the dispensary category claimed in call verification in over 10 % licensed dispensaries disagreed with the approved category in BCC. There were 2121 businesses combined from BCC and online crowdsourcing platforms, among which 826 were verified to be active brick-and-mortar dispensaries. Weedmaps had the highest sensitivity (.80) and Yelp had the highest negative predictive value (.74) in identifying verified dispensaries. Weedmaps overall had the highest sensitivity in all three dispensary categories. Weedmaps had the highest sensitivity in more populated counties whereas BCC had the highest sensitivity in less populated counties.

CONCLUSIONS

Each secondary data source has strengths and limitations. The findings inform surveillance and research regarding how to best strategize data use when resources are limited.

The association between recreational cannabis commercialization and cannabis exposures reported to the US National Poison Data System

BACKGROUND AND AIMS

Recreational cannabis has been legalized in 11 states and District of Columbia (DC) in the United States. Among these, 10 states further permitted retail sale to provide a legal supply to adults. This study examined the associations of cannabis exposures with recreational cannabis legalization and commercialization.

DESIGN

Secondary data analysis of state-quarter level cannabis exposures during 2010-17 in the United States. Linear regressions with a difference-in-differences design were used to compare pre- and post-legalization trends in states that legalized recreational cannabis to contemporaneous trends in states that did not legalize recreational cannabis.

SETTING

United States, including all 50 states and DC.

CASES

Cannabis exposures reported to the US National Poison Data System.

MEASUREMENTS

The primary outcome was state age-adjusted cannabis exposures reported to the US National Poison Data System per 1 000 000 population per quarter. The two policy variables of interest included (1) the enactment of recreational cannabis legalization (i.e. removing penalties for adults' possession of cannabis in a small amount for recreational use) and (2) the initiation of recreational cannabis commercialization (i.e. providing a legal supply of cannabis to adults through licensed dispensaries).

FINDINGS

The association between a state's enactment of recreational cannabis legalization and its changes in cannabis exposures was statistically non-significant overall. After controlling for recreational cannabis legalization, however, the initiation of recreational cannabis commercialization was associated with 5.06-5.80 more exposures per 1 000 000 population per quarter (67-77% increase relative to the pre-legalization average), depending on the composition of comparison states. The increase associated with commercialization was higher among minors than adults (7.97-9.53 versus 3.83-4.21 more exposures), higher among males than females (6.16-7.56 versus 3.76-3.91 more exposures) and higher among exposures with medical consequences than those without medical consequences (4.09-4.79 versus 0.97-1.01 more exposures).

CONCLUSION

An increase in cannabis exposures reported to the US National Poison Data System was observed following recreational cannabis commercialization in the United States.

Adolescent treatment admissions for marijuana following recreational legalization in Colorado and Washington

INTRODUCTION

There is concern that recreational marijuana legalization (RML) may lead to increased cannabis use disorder (CUD) among youth due to increased marijuana use. This study investigates whether adolescent substance use disorder treatment admissions for marijuana use increased in Colorado and Washington following RML.

METHODS

Annual data on 2008-2017 treatment admissions for marijuana use from the SAMHSA TEDS-A dataset for adolescents age 12-17 were used to model state treatment admissions trends. Difference-in-differences models were used to investigate whether treatment admissions increased following RML in Colorado/Washington compared to non-RML states, after adjusting for socioeconomic characteristics and treatment availability.

RESULTS

Over all states in the analysis, the rate of adolescent treatment admissions for marijuana use declined significantly over the study period (β=-3.375, 95 % CI=-4.842, -1.907), with the mean rate falling nearly in half. The decline in admissions rate was greater in Colorado and Washington compared to non-RML states following RML, though this difference was not significant (β=-7.671, 95 % CI=-38.798, 23.456).

CONCLUSION

Adolescent treatment admissions for marijuana use did not increase in Colorado and Washington following RML. This may be because youth marijuana use did not increase, CUD did not increase (even if use did increase), or treatment seeking behaviors changed due to shifts in attitudes and perceptions of risk towards marijuana use.

Adolescent Substance Use Disorder Treatment: an Update on Evidence-Based Strategies

PURPOSE OF REVIEW

To examine the most recent published evidence (2016-2019) regarding the treatment of adolescent substance use disorders and to provide an update on evidence-based strategies, adjunctive interventions, and methods to improve currently established treatment approaches.

RECENT FINDINGS

Recent evidence suggests that psychosocial treatments such as family-based therapy, cognitive behavioral therapy, and multicomponent approaches remain the most effective methods of treatment; however, innovative ways of improving these treatment strategies may include digital and culturally based interventions. New advances in adjunctive treatments such as pharmacotherapy, exercise, mindfulness, and recovery-oriented educational centers may have some clinical utility. Well-established psychosocial interventions remain the primary modality of treatment. Promising new adjunctive treatments and improvements in our currently established treatments may yield significant improvements.