Marijuana Use among Adolescents and Emerging Adults in the Midst of Policy Change: Introduction to the Special Issue

Recreational cannabis legislation and binge drinking in U.S. adolescents and adults

BACKGROUND

Recreational cannabis laws (RCLs) may have spillover effects on binge drinking. Our aims were to investigate binge drinking time trends and the association between RCLs and changes in binge drinking in the United States (U.S.).

METHODS

We used restricted National Survey on Drug Use and Health data (2008-2019). We examined trends in the prevalence of past-month binge drinking by age groups (12-20, 21-30, 31-40, 41-50, 51+). Then, we compared model-based prevalences of past-month binge drinking before and after RCL by age group, using multi-level logistic regression with state random intercepts, an RCL by age group interaction term, and controlling for state alcohol policies.

RESULTS

Binge drinking declined overall from 2008 to 2019 among people aged 12-20 (17.54% to 11.08%), and those aged 21-30 (43.66% to 40.22%). However, binge drinking increased among people aged 31+ (ages 31-40: 28.11% to 33.34%, ages 41-50: 25.48% to 28.32%, ages 51+: 13.28% to 16.75%). When investigating model-based prevalences after versus before RCL, binge drinking decreased among people aged 12-20 (prevalence difference=-4.8%; adjusted odds ratio (aOR)=0.77, [95% confidence interval (CI) 0.70-0.85]), and increased among participants aged 31-40 (+1.7%; 1.09[1.01-1.26]), 41-50 (+2.5; 1.15[1.05-1.26]) and 51+ (+1.8%; 1.17[1.06-1.30]). No RCL-related changes were noted in respondents ages 21-30.

CONCLUSIONS

Implementation of RCLs was associated with increased past-month binge drinking in adults aged 31+ and decreased past-month binge drinking in those aged < 21. As the cannabis legislative landscape continues to change in the U.S., efforts to minimize harms related to binge drinking are critical.

Substance-Specific Risk Factors for Cannabis and Alcohol Use Among Young Adults Following Implementation of Nonmedical Cannabis Legalization

Laws regarding cannabis are rapidly changing in the USA as more states legalize nonmedical cannabis for adults aged 21 and older. Previous research has examined whether legalization has led to an increase in cannabis use as well as the use of other substances. The current study examined changes in cannabis- and alcohol-specific risk factors following legalization of nonmedical cannabis. We used 6 years of annual cross-sectional data (2014-2019) from 12,951 young adults age 18 to 25 who resided in Washington state. Risk factors examined include perceiving that use was common among same-age peers, believing use was acceptable, having easy access, and low perceived physical and psychological harm from use. Logistic regression models estimated annual rate of increase in these risk factors. All cannabis-specific risk factors increased among those aged 21+ (range of ORs for annual rate of change: 1.07-1.31) while significant increase in cannabis-related risk factors among those under age 21 was limited to perceptions of cannabis use being common (medical use: OR=1.08, 95% CI: 1.03, 1.12; nonmedical use: OR=1.13, 95% CI: 1.08, 1.18) and low perceived physical harm of occasional use (OR=1.08, 95% CI: 1.03, 1.13). Although descriptive norms for past-year use of alcohol among those aged 21+ increased (OR = 1.09, 95% CI: 1.02, 1.17), other risk factors for alcohol did not change significantly or, in the case of low perceived physical and psychological harm, decreased among both those under age 21 and those aged 21+ (range of ORs = 0.90-0.94). Given these findings show an increase in cannabis-specific risk factors since legalization was implemented, particularly among those young adults aged 21+, preventive interventions correcting risk misperceptions and related risk factors among young adults aged 21+ may prove efficacious in reducing use and resultant negative consequences.

College students mandated to substance use courses: Age-of-onset as a predictor of contemporary polysubstance use

Objective: College campuses report alcohol and other drug policy violations as the most frequent reason students receive disciplinary referrals and, thus, are mandated to programming. This study sought to determine predictors of mandated students' alcohol use frequency, and the likelihood of early-onset alcohol using college students enrolled in mandated programming engaging in current polysubstance use. Methods and participants: Employing a purposive sampling method, n = 822 participants were recruited from a pool of students who violated their university's alcohol policy between October 2019 and July 2021. Results: Data analysis revealed early-onset alcohol use (p < .001), gender ID (p < .01), Greek Affiliation (p < .001), ethnicity (p < .05), and perceived norms (p < .001) significantly predicted alcohol frequency. Analysis also revealed engaging in early-onset alcohol use significantly predicted current participation in polysubstance use (p < 0.01), outside of controls. Conclusions: University programs should consider exploring polysubstance use targeted interventions to mitigate these harmful behaviors and associated negative consequences.

Substance-Specific Risk Factors among Young Adults: Potential Prevention Targets across Cannabis-Permissive Environments

PURPOSE

This study examined levels of substance-specific risk factors such as perception of harm from substance use among young adults in a range of cannabis-permissive environments. The main objective was to inform future preventive interventions aimed at reducing cannabis use in the context of increasingly permissive environments.

METHODS

Data came from the Community Youth Development Study (CYDS) collected in 2016 when participants were about 23 years old (n = 1,722 participants residing in 46 U.S. states). Young adults self-reported their perceptions about the harms related to cannabis, alcohol, and cigarette use; attitudes about and ease of access to cannabis and other substances; and perceived wrongfulness and social acceptability of cannabis, alcohol, and cigarette use and of selling of cannabis and other illegal drugs.

RESULTS

Young adults in more permissive cannabis contexts reported higher levels of all cannabis-specific risk factors (e.g., greater access to and more favorable attitudes about cannabis use), except for perception of harm from regular cannabis use. However, permissiveness of the cannabis environment was not associated with heightened levels of risk factors for other substance use (such as alcohol, cigarettes, and opioids).

CONCLUSIONS

Future preventive interventions for young adults living in more permissive cannabis contexts may need to focus on cannabis-specific risk factors in particular and go beyond considerations of harm from regular use. Future studies should replicate these findings with other samples.

Simultaneous use of marijuana and alcohol: Potential prevention targets among young adults who use alcohol

Simultaneous alcohol and marijuana use (SAM) such that their effects overlap has emerged as a behavior that is riskier than using either substance separately. It has been associated with high-risk binge drinking and driving while intoxicated during young adulthood, and it has been demonstrated to cause greater physical and mental impairment than use of alcohol or marijuana separately. To identify intervention and prevention targets specific to SAM, we examined the relationships between alcohol- and marijuana-specific beliefs and attitudes (risk factors) and self-reported SAM compared to non-simultaneous co-use (CAM) and alcohol use only in the past 30 days in a sample of young adults (n = 1,023, mean age = 23.17; SD = 0.43). Of those who reported drinking alcohol in the past 30 days, 20.7% reported SAM, 12.6% reported CAM, and 66.6% reported using only alcohol. Results from multinomial logistic regression analyses indicated that some marijuana-specific risk factors (e.g., belief that it is not at all wrong for someone their age to use marijuana) differentiated SAM or CAM from alcohol use only, but alcohol-specific risk factors generally did not. However, the perceptions that parents approved of their using marijuana or frequently drinking heavily were associated with a greater likelihood of SAM compared to CAM (OR ranged from 2.25 to 3.53). Findings point to the salience of individuals' attitudes and beliefs around marijuana use and their perception of parental approval of heavy drinking and marijuana use as potential targets for prevention programs targeting risk reduction among young adults.

Trends in youth cannabis use across cannabis legalization: Data from the COMPASS prospective cohort study

Canada legalized recreational cannabis use for adults on October 17, 2018 with decision-makers emphasising the need to reduce cannabis use among youth. We sought to characterise trends of youth cannabis use before and after cannabis legalization by relying on a quasi-experimental design evaluating cannabis use among high school students in Alberta, British Columbia, Ontario, and Québec who participated in the COMPASS prospective cohort study. Overall trends in use were examined using a large repeat cross-sectional sample (n = 102,685) at two time points before legalization (16/17 and 17/18 school years) and one after (18/19 school year). Further differential changes in use among students affected by legalization were examined using three sequential four-year longitudinal cohorts (n = 5,400) of students as they progressed through high school. Youth cannabis use remains common with ever-use increasing from 30.5% in 2016/17 to 32.4% in 2018/19. In the repeat cross-sectional sample, the odds of ever use in the year following legalization were 1.05 times those of the preceding year (p = 0.0090). In the longitudinal sample, no significant differences in trends of cannabis use over time were found between cohorts for any of the three use frequency metrics. Therefore, it appears that cannabis legalization has not yet been followed by pronounced changes on youth cannabis use. High prevalence of youth cannabis use in this sample remains a concern. These data suggest that the Cannabis Act has not yet led to the reduction in youth cannabis use envisioned in its public health approach.

Medical marijuana laws (MMLs) and dispensary provisions not associated with higher odds of adolescent marijuana or heavy marijuana use: A 46 State Analysis, 1991-2015

Background: States are rapidly moving to reverse marijuana prohibition, most frequently through legalization of medical marijuana laws (MMLs), and there is concern that marijuana legalization may affect adolescent marijuana use. Methods: This natural-experimental study used state Youth Risk Behavior Survey (YRBS) data collected from participants in grades 9-12 from 1991 to 2015 in 46 states (N = 1,091,723). Taking advantage of heterogeneity across states in MML status and MML dispensary design, difference-in-difference estimates compared states with enacted MMLs/dispensaries to non-MML/dispensaries states. Multivariable logistic regression modeling was used to adjust for state and year effects, and student demographics. The main outcome assessed was past 30-day adolescent marijuana use ["any" and "heavy" (≥20)]. Results: In the overall sample, the adjusted odds of adolescents reporting any past 30-day marijuana use was lower in states that enacted MMLs at any time during the study period (OR 0.94, 95% CI 0.89 to 0.99; p < .05), and in states with operational dispensaries in 2015 (OR 0.93, 95% CI 0.88 to 0.99; p < .05). Among grade cohorts, only 9th graders showed a significant effect, with lower odds of use with MML enactment. We found no effects on heavy marijuana use. Conclusions: This study found no evidence between 1991 and 2015 of increases in adolescents reporting past 30-day marijuana use or heavy marijuana use associated with state MML enactment or operational MML dispensaries. In a constantly evolving marijuana policy landscape, continued monitoring of adolescent marijuana use is important for assessing policy effects.

Do the Transmissible Liability Index (TLI) and Adolescent Cannabis Use Predict Paranoid and Schizotypal Symptoms at Young Adulthood?

Background: Adolescent cannabis use is an established risk factor for the development of psychosis, but the premorbid vulnerability factors and specificity versus generality of the psychotic symptom domains affected in cannabis-psychosis relationships remain incompletely understood. To improve our understanding of these relationships, we used longitudinal data to examine the individual and interactive effects of preadolescent transmissible liability to substance use disorders (SUD), measured via the transmissible liability index (TLI), and adolescent cannabis use on the development of two distinct psychotic symptom domains, paranoid and schizotypal personality traits in young adulthood. Methods: We performed secondary analysis of data from the Center for Education and Drug Abuse (CEDAR) study, which longitudinally assessed offspring of men with (N = 211) and without (N = 237) lifetime history of SUD at ages 10-12, and across adolescence as they transitioned to young adulthood. TLI scores were calculated at age 10-12, self-reported cannabis use was assessed at age 16, and paranoid and schizotypal symptoms were assessed at age 19. Results: Cannabis use at age 16 and family history of SUD were significantly associated with paranoid and schizotypal symptoms at age 19, but TLI scores were not. The interactive effect of TLI x cannabis use was also not significant. Paranoid and schizotypal symptoms showed different dose-dependent sensitivities to cannabis exposure at age 16. Conclusions: These findings indicate that adolescent cannabis use and family history of SUD differentially contribute to the development of paranoid and schizotypal personality traits through mechanisms that do not include behavioral disinhibition.

Has Cannabis Use Among Youth Increased After Changes in Its Legal Status? A Commentary on Use of Monitoring the Future for Analyses of Changes in State Cannabis Laws

As US states move toward various forms of adult access to cannabis, there has been a great interest in measuring the impact of such changes on adolescent cannabis use. Two recent prominent analyses have used Monitoring the Future (MTF), a nationally representative survey of students, to examine the effects. We compared MTF data for California and for Washington State with other survey data on use by adolescents in those states. In both studies, findings based on MTF were different from those using other larger, state-representative surveys. The discrepancy reflects the high within-state variation in prevalence rates and the small number of schools in MTF state samples. Using the Washington Health Youth Survey, we estimate that after recreational cannabis legalization past 30-day cannabis use prevalence in grade 8 decreased by 22.0%, in grade 10 prevalence decreased by 12.7%, and no effect in grade 12. These trends are consistent with those in states without recreational cannabis laws, suggesting that legalization did not impact adolescent use prevalence. Long-term trends in MTF are consistent with other data, but year-to-year volatility in state-level series undermines the survey's suitability for evaluation of state cannabis policy changes. Survey-based analyses at the state level need to be cross-validated with findings from other data sources. When findings are disparate and methodological rigor is equivalent, analyses of data sources specifically designed to describe state-level phenomena are more credible.

Recruiting and Retaining Youth and Young Adults in the Policy and Communication Evaluation (PACE) Vermont Study: Randomized Controlled Trial of Participant Compensation

BACKGROUND

The standard approach for evaluating the effects of population-level substance use prevention efforts on youth and young adult perceptions and behaviors has been to compare outcomes across states using national surveillance data. Novel surveillance methods that follow individuals over shorter time intervals and capture awareness of substance use prevention policy and communication efforts may provide a stronger basis for their evaluation than annual cross-sectional studies.

OBJECTIVE

This study aimed to identify a combination of strategies to recruit a sample of youth and young adults sufficiently representative of the Vermont population and determine how best to retain a web-based panel of youth and young adults over a 6-month period.

METHODS

Eligible participants were Vermont residents aged 12 to 25 years who were willing to complete three 10 to 15-minute web-based surveys over a 6-month period. Recruitment was conducted via the following three main mechanisms: (1) web-based recruitment (paid and unpaid), (2) community-based recruitment through partners, and (3) participant referrals via a personalized link. Upon completion of the baseline survey, participants were randomly assigned to one of the following three retention incentive conditions: (1) guaranteed incentive (US $10), (2) lottery incentive (US $50 weekly lottery drawing), and (3) preferred method (guaranteed or lottery). Analyses examined cost per survey start by recruitment source, distribution of demographic characteristics across incentive conditions, and retention by study condition at 3-month and 6-month follow-ups.

RESULTS

Over a 10-week period in 2019, we recruited 480 eligible youth (aged 12-17 years) and 1037 eligible young adults (aged 18-25 years) to the Policy and Communication Evaluation (PACE) Vermont Study. Facebook and Instagram advertising produced the greatest number of survey starts (n=2013), followed by posts to a state-wide web-based neighborhood forum (n=822) and Google advertisements (n=749). Retention was 78.11% (1185/1517) at 3 months and 72.18% (1095/1517) at 6 months. Retention was equivalent across all incentive study conditions at both waves, despite a strong stated preference among study participants for the guaranteed payment at baseline. Youth had greater retention than young adults at both waves (wave 2: 395/480, 82.3% vs 790/1037, 76.18%; wave 3: 366/480, 76.3% vs 729/1037, 70.30%). Substance use prevalence in this cohort was similar to national and state-level surveillance estimates for young adults, but was lower than state-level surveillance estimates for youth. Most participants retained at wave 3 provided positive qualitative feedback on their experience.

CONCLUSIONS

Our study supports the feasibility of recruiting a web-based cohort of youth and young adults with representation across an entire state to evaluate substance use prevention efforts. Findings suggest that a guaranteed payment immediately upon survey completion coupled with a bonus for completing all survey waves and weekly survey reminders may facilitate retention in a cohort of youth and young adults.

Trends in college students' alcohol, nicotine, prescription opioid and other drug use after recreational marijuana legalization: 2008-2018

BACKGROUND

Young adult college students may be particularly sensitive to recreational marijuana legalization (RML). Although evidence indicates the prevalence of marijuana use among college students increased after states instituted RML, there have been few national studies investigating changes in college students' other substance use post-RML.

METHOD

The cross-sectional National College Health Assessment-II survey was administered twice yearly from 2008 to 2018 at four-year colleges and universities. Participants were 18-26 year old undergraduates attending college in states that did (n = 243,160) or did not (n = 624,342) implement RML by 2018. Outcome variables were self-reported nicotine use, binge drinking, illicit drug use, and misuse of prescription stimulants, sedatives, and opioids. Other variables included individual and contextual covariates, and institution-reported institutional and community covariates. Publicly available information was used to code state RML status at each survey administration.

RESULTS

Accounting for state differences and time trends, RML was associated with decreased binge drinking prevalence among college students age 21 and older [OR (95% CI) = 0.91 (0.87 - 0.95), p < .0001] and increased sedative misuse among minors [OR (95% CI) = 1.20 (1.09 - 1.32), p = .0003]. RML did not disrupt secular trends in other substance use.

CONCLUSIONS

In the context of related research showing national increases in college students' marijuana use prevalence and relative increases following state RML, we observed decreases in binge drinking and increases in sedative use that both depended on age. Findings support some specificity in RML-related changes in substance use trends and the importance of individual factors.

Intergenerational congruence in adolescent onset of alcohol, tobacco, and marijuana use

We examined alcohol, tobacco, and marijuana (ATM) use onset across early to late adolescence in a sample of fathers and their offspring. We tested a theory of developmental congruence in polysubstance use, or the extent to which fathers' ATM use onset in early adolescence increased risk for earlier ATM onset by their offspring. Average rates of adolescent ATM use onset were also compared across generations, which may reflect intergenerational discontinuity and secular trends. Children (n = 223, 44% boys) and their fathers (n = 113; originally recruited as boys at neighborhood risk for delinquency) contributed repeated prospective self-reports of their ATM use across adolescence (as late as age 18 years). Mothers' ATM use (retrospective) through age 18 years was available for 205 children. Data were analyzed using discrete-time survival mixture analysis. Compared with their fathers, boys and girls showed later onset for tobacco use, and girls showed later onset alcohol use. Developmental congruence was partially supported: Children showed earlier ATM use onset if their fathers were assigned to the early adolescent polysubstance use onset class, compared to the late-adolescent predominantly alcohol and tobacco onset class; mothers' ATM use in adolescence attenuated this effect. Consistent with national secular trends, rates of adolescent onset tobacco and alcohol use declined across generations, whereas marijuana use onset did not. However, there was intergenerational transmission of risk for early polysubstance use onset. Prevention that delays early substance use may have early life span effects as well as transgenerational implications. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Identifying adolescent protective factors that disrupt the intergenerational transmission of cannabis use and disorder

Adolescent cannabis use is common, has been associated with several deleterious outcomes, and is often associated with previous parent cannabis use. Therefore, identifying protective factors that prevent this intergenerational transmission of cannabis use is increasingly important given shifting contemporary policies around cannabis use. The present study examines 3 protective factors in adolescence (active coping, positive activity involvement, and school grades) that may disrupt patterns of intergenerational cannabis use. The present study uses data from a high-risk longitudinal sample followed for over 30 years that includes Generation 1 (G1) parents (54.19% with lifetime alcohol use disorder, 8.15% with lifetime cannabis use disorder), their Generation 2 (G2) children, and their Generation 3 (G3) grandchildren and therefore provides the opportunity to replicate effects across 2 intergenerational cohorts (a G1-G2 cohort and a G2-G3 cohort). Results from ordered logistic regression models reveal that in both intergenerational cohorts, greater midadolescent active coping, higher positive activity involvement, and higher grades prospectively predict lower late adolescent cannabis use at significant (p < .05) or marginal (p < .10) levels, even after powerful control variables, such as parent cannabis use and alcohol use, as well as previous early adolescent cannabis use, are accounted for. Additionally, in both intergenerational cohorts, midadolescent high levels of active coping disrupt intergenerational transmission of cannabis use. Results indicate replication in the intergenerational transmission of cannabis use and in the protective effects of coping, grades, and, to a lesser extent, positive activity involvement across generational cohorts. Implications for prevention programming are discussed. (PsycInfo Database Record (c) 2020 APA, all rights reserved).