Given the importance of this issue for drug policy, research on the mechanisms through which medical marijuana laws promote the initiation of marijuana use by young adults should be prioritized. This study was subject to several limitations. We were unable to rule out the possibility that, over longer windows of time, state medical marijuana laws will exert impacts on marijuana consumption and initiation by younger people dwelling in these states. We tested models using variables representing the length of time that each state’s medical marijuana law had been in place but found no statistically significant effects. We also could not examine whether legalization of marijuana for medical purposes has different effects as compared with recreational legalization; the NSDUH data did not extend into the years after recreational policies were established. The NSDUH data collection takes place at various points through the calendar year, and the date of any given participant interview may or may not have matched up with enactment of new medical marijuana legislation in their state; however local variation in availability of marijuana would make even a stricter date-based classification subject to the same potential mismatch on the individual level. Under reporting of drug consumption and initiation is also likely because of social acceptability concerns and survey respondents’ fears of disclosure . The NSDUH used computer-assisted interviewing to increase the validity of self-reports consistently throughout the 10-year observation period. As young people’s views about marijuana grow more permissive over time , survey respondents could become more willing to report that they have tried marijuana thus introducing bias into this analysis. Our multivariate models controlled for time trends to address this problem. Finally, our analyses could not capture sub-state variation in the implementation of medical marijuana laws .Adolescence requires some risk-taking as independence from the family is taking form, but for some teens,rolling grow table risk taking may lead to unhealthy or unsafe decisions. Risky behaviors such as unprotected sex, reckless driving, and substance use are associated with lasting negative outcomes .
With regard to substance use, the annual Monitoring the Future study reported that marijuana is the most commonly used illicit drug in the United States, with 7% of 12th graders reporting daily use . Individuals who engage in regular substance use may have a higher propensity to take unsafe risks despite the possible negative consequences . Without testing adolescents prior to initiation of substance use, it is difficult to determine whether elevated levels of risk-taking predated substance use. However, risk-taking performances of adolescents with and without histories of regular marijuana use can help us to understand what leads some individuals to substance-related problems. The Balloon Analogue Risk Task offers a behavioral assessment of risk-taking. In adult samples, riskier BART performance has been associated with higher levels of alcohol use as well as substance use, gambling, unsafe sex, and stealing , and it has successfully differentiated MDMA 3,4-methylenedioxymethamphetamine; “ecstasy”) users from controls . Riskier BART performance was also associated with greater alcohol, cigarette, and poly drug use in a community sample of young adults . Among adolescents, riskier BART performance was related to greater self-reported substance use and safety risk behaviors . Adolescent patients with conduct disorder and co-morbid substance abuse/dependence have also shown greater risk-taking with the BART compared to healthy controls . Some studies have examined marijuana users specifically. For example, adolescent marijuana users demonstrated impulsive decision-making with the Information Sampling Test ; however, users had a median of less than 24 h of abstinence. Using the BART, Schuster et al. found that riskier BART performance was correlated with higher levels of risky sexual behavior among young adult marijuana users; however, participants may have used marijuana the day prior to testing and were not compared to non-users. Gonzalez et al. found no differences on the BART in a sample of young adult marijuana users versus non-using controls; however, Gonzales et al. allowed for recent marijuana use , with a median of three days since past use. Because previous studies of young marijuana users allowed for recent use, the effects of residual marijuana levels may have affected task performance. In the current study, we examined risk-taking via the BART in late adolescent marijuana users with at least two weeks of abstinence from marijuana, in comparison to non-using controls.
This approach considers how marijuana users function relative to their non-using peers and reduces possible residual effects from recent substance use. We hypothesized that participants reporting greater substance use would demonstrate riskier BART performance. Further, previous studies have not yet examined the relationship of risk-taking to executive functioning in adolescent marijuana users. Executive function is a complex collection of abilities primarily modulated by the prefrontal cortex. Several studies have found altered prefrontal cortex processing and executive dysfunction in marijuana users . Completing the BART has also been linked to increased prefrontal cortex activation in healthy controls , and a recent meta-analysis of neuroimaging studies suggested that individuals with substance use disorders may have altered risk processing compared to healthy controls, primarily in ventromedial prefrontal cortex, orbitofrontal cortex, striatum, and other areas involved in risk and decision-making . Given the involvement of the prefrontal cortex in both risk-taking and executive functioning, we examined whether elevated risk-taking, as measured by the BART, was associated with poorer executive functioning, as measured by traditional neuropsychological tests. We hypothesized that a riskier approach to the BART would be associated with poorer performance on executive function tests.Participants were part of a longitudinal study of marijuana’s effects on neurocognition during adolescence and young adulthood, with assessments at intake and at 18- and 36-month follow-ups . Adolescents were recruited from local high schools. Teens and their parents/guardians were screened for demographics, psychosocial functioning, and family history of Diagnostic and Statistical Manual for Mental Disorders, 4th Ed. , 2000) substance use and other Axis I disorders. Confidentiality was ensured within legal limits to encourage full disclosure. Prior to participation, written informed assent and consent were obtained in accordance with the University of California, San Diego Human Research Protections Program. At study intake, exclusionary criteria included history of psychiatric disorder other than substance use disorder, serious medical problem or head trauma, premature birth, prenatal drug or alcohol exposure, and substance use during monitored abstinence.
Intake classification criteria for the marijuana-user group included >60 lifetime marijuana experiences; past month marijuana use; <100 lifetime uses of drugs other than marijuana, alcohol, or nicotine; and not meeting Cahalan criteria for heavy drinking status . To produce an adequate sample size, controls were included if they had <5 lifetime experiences with marijuana , no previous use of any other drug except nicotine or alcohol, and did not meet criteria for heavy drinking status. The current data were collected at the 18-month follow-up, when participants were aged 17–20 years. A total of 48 marijuana users and 52 controls completed the BART task at the 18-month follow-up; however, 24 marijuana users and 18 controls were excluded from analyses based on the following abstinence requirements: at least two weeks since last use of marijuana, other drugs, or alcohol binge ; and at least three days since last use of any alcohol or psychiatric medications . Beyond the abstinence requirements, follow-up controls were further excluded for meeting abuse or dependence criteria for alcohol or any other substance . One participant in the baseline marijuana group had no marijuana uses in the previous 18 months and was also excluded, and one additional control was excluded due to meeting DSM-IV criteria for current post-traumatic stress disorder. Following these exclusions, the resulting sample of 58 demographically matched adolescents and young adults included 24 marijuana users and 34 non-using controls. At the 18-month follow-up, marijuana users were about seven months older , and as expected, reported higher levels of marijuana, alcohol,indoor plant table and other drug use than controls. marijuana users had 200+ lifetime marijuana use episodes and <130 lifetime experiences with other drugs. In addition, 10 marijuana users met DSM-IV criteria for marijuana abuse and seven for marijuana dependence , 10 met criteria for alcohol abuse, and two met criteria for other drug abuse. At the 18-month follow-up, the 34 controls had ≤15 lifetime experiences with marijuana, minimal to no previous other drug use except nicotine or alcohol .A structured clinical interview measured psychosocial functioning, health history, and family history of psychiatric and substance use disorders . Probable DSM-IV Axis I disorders were determined by the computerized Diagnostic Interview Schedule for Children Predictive Scales . Adult participants living independently completed corresponding modules of the computerized Diagnostic Interview Schedule .Parent interview. A parent/guardian was interviewed on child development and behavior, and youth/family medical and psychiatric history . Parents/guardians corroborated youth diagnostic reports with the parent version of the Diagnostic Interview Schedule for Children Predictive Scales. If participant self-report and parent collateral data were discrepant, additional information was reviewed from the file, and data were coded to reflect the presence of the symptom, to reduce participant and researcher bias. Substance use. Participants were administered the Customary Drinking and Drug Use Record to evaluate their lifetime, past three-month, and past 18-month use of nicotine, alcohol, marijuana, stimulants , hallucinogens, inhalants, opiates , dissociatives , sedatives , and abuse of over-the-counter or prescription medications.
Teens were also assessed for alcohol and drug withdrawal symptoms, related life problems, and DSM-IV abuse and dependence criteria . The Timeline Follow back facilitated recall of substance use over the past 28 days through a calendar layout. BART. The BART is a computer-based risk-taking assessment . Participants used the space bar to pump 30 simulated balloons one at a time to achieve the highest possible score. Balloons pop at an unpredictable rate , and a noise follows each response . The points earned for a balloon are lost if it pops, but temporary points can be saved by choosing “Save Points.” Participants weigh the increasing risk of popping each balloon against the potential gain of continuing to pump the balloon . The primary outcome measures were the mean number of pumps for balloons that did not pop and the total number of popped balloons during the session. High values on either variable suggest greater risk taking. The number of points earned on any balloon and the total points saved are not revealed to the participant – only whether they had earned a small, medium, big, or bonus prize depending on the amount of points saved. They were shown the possible candy rewards prior to starting the task and received the reward immediately upon completion of the task. Participants had no practice trials to assess risk, and each participant completed the same task . This measure has good test-retest reliability . Mood and personality. Mood and personality were measured to help characterize the sample and examine whether elevations in depressive, anxiety, or internalizing/externalizing symptoms were related to BART performance. Mood and anxiety were assessed using the Beck Depression Inventory and the Spielberger State-Trait Anxiety Inventory . We used the Child Behavior Checklist Youth Self-Report and Adult Self-Report to measure internalizing and externalizing behaviors. Neuropsychological testing. General intellectual ability was assessed by the Vocabulary and Block Design subtests of the Wechsler Abbreviated Scale of Intelligence . Measures of executive function included the Digit Span task from the Wechsler Adult Intelligence Scale-Third Edition ; and the Trail Making, Towers, and Verbal Fluency tests from the DelisKaplan Executive Functioning System .Participants were abstinent from marijuana, other drugs, and alcohol binge for at least two weeks prior to the assessment, verified with biweekly breathalyzer tests and urine screens including at the neuropsychological testing session. The urine screen tested for major substances including amphetamines, barbiturates, benzodiazepines, cocaine metabolites, marijuana metabolites, and opiates.All participants completed questionnaires and the neuropsychological battery. Teens and their parents/guardians received monetary compensation upon study completion.We used Fisher’s Exact Tests to compare categorical variables between groups and analysis of variance to examine group differences on continuous variables. Some alcohol and drug use variables did not meet requirements for parametric analysis; therefore we used the Mann-Whitney procedure to compare these characteristics between groups. Because marijuana users were slightly older than controls, age was controlled in analyses of test performance using univariate analysis of covariance .