Effect sizes are presented as partial eta-squared , and interpretations of statistical significance were made if p<0.05. We used Pearson correlations to examine associations between risk-taking, demographic, and neuropsychological variables. As an exploratory analysis, we performed hierarchical multiple regressions to examine whether BART performance predicted past 18-month substance use, as described below. Distributions of substance use variables were examined and appropriately log10 transformed to meet the assumptions of parametric analysis.This study examined risk taking via the BART in late adolescents with or without a history of marijuana use. As hypothesized, participants reporting greater substance use evidenced riskier BART performance. Specifically, marijuana users with at least two weeks of abstinence from marijuana, other drugs, or alcohol binge popped more balloons than non-using controls throughout the task, especially in the first 20 balloons. Although speculative, it appears that the marijuana users started the task with a higher level of risk taking. After receiving feedback about their performance , they attempted to modify their approach to avoid popping balloons. The controls may have taken a similar approach, as illustrated in Figure 1; however, the marijuana users remained slightly more “risky” in their approach throughout the test. Notably, the groups did not significantly differ in average adjusted pumps, which is the most commonly used variable for this task. Importantly, Pleskac et al. have suggested that the average adjusted pumps score may be biased and an underestimate of risky responses because it excludes the trials in which the balloon popped, as explained further below. For this reason, the number of popped balloons may be a more sensitive measure of risk-taking. Importantly, the groups were matched on self-reported levels of depressive, anxiety,plant growing stand and internalizing symptoms; marijuana users scored higher on externalizing behavior, as expected.
BART performance was not associated with these self-reported mood and personality characteristics or demographic variables including age. This suggests that group differences in risk taking may be due to marijuana or other substance use, rather than other personal characteristics. Previous studies have found mixed results. Consistent with the current study, some found that alcohol and other substance use was related to riskier BART performance ; however, others did not find group differences between non-using controls and at-risk/ addicted individuals or recently abstinent marijuana users using the BART average adjusted pumps variable . Further, BART performance did not relate to cannabis use disorder symptoms in Gonzalez et al., 2012. Our study is consistent with Meda et al. and Gonzalez et al. with regard to finding no group difference on average adjusted pumps; however, the previous studies did not examine group differences in the number of popped balloons. We also found that having a riskier BART performance significantly predicted a higher number of other drug use episodes in the past 18 months, above and beyond the effects of age. The equation using popped balloons to predict past 18-month marijuana use was also significant, but higher age was a stronger predictor than popped balloons. Having a riskier BART performance did not predict recent alcohol use. In other words, it appears that BART performance was associated with other drug use but not alcohol or marijuana use when also considering age. However, that result did not remain significant when controls were removed from the analysis. The BART may therefore have had relatively low sensitivity for measuring additional risk among regular marijuana users in this sample. Future studies could explore whether BART performance is a useful predictor of additional risk above and beyond alcohol and marijuana use. In addition to elevated BART risk-taking, abstinent marijuana users performed worse than controls on one aspect of executive functioning measured, consistent with previous studies reporting deficient executive skills or abnormal brain activation among marijuana users in this and other samples .
Specifically, marijuana users exhibited poorer visuomotor set-shifting relative to nonusing controls. This suggests that young, abstinent marijuana users may have a mild weakness in cognitive flexibility in the context of changing task demands. Nevertheless, it is not clear if the average group difference on this task is clinically meaningful, and marijuana users did not differ from controls on other aspects of executive skills including working memory, verbal fluency, and planning. Although not correlated with putative measures of executive function, riskier BART performance was associated with faster psychomotor sequencing speed. It is possible that a faster rate of responding may produce more popped balloons, or as speculation, risky behavior without adequate forethought may result in losses. This may concur with Solowij et al. who reported that marijuana using adolescents demonstrated “reflection impulsivity,” having faster response times even when uncertain and making more errors. Vigil-Colet also found that BART performance was most strongly related to “functional impulsivity,” a style in which decisions are made quickly and impulsively under certain beneficial circumstances. On the other hand, Meda et al. used principal components analysis to show that risk-taking may be distinct from other measures of the multidimensional construct of impulsivity . Therefore the relationship between a faster processing speed, impulsivity, and risk-taking is not entirely clear and warrants additional study. Overall, the BART appears to measure distinct aspects of risk-taking that have been associated with real-world behavior , suggesting it is a useful tool for assessing risk-taking in adolescents and young adults. Since the BART was not correlated with established tests of executive functioning, this suggests that it is measuring a behavior distinct from executive function, or at least distinct from the present tests of executive functions. Given the constellation of elevated risk-taking and inferior executive functioning, marijuana using teens may be at greater risk than non-users for antisocial and safety risk behaviors, thus increasing the possibility of negative personal, social, legal, or occupational consequences .
One limitation of the present study was that, given the inter correlations between various substances of abuse, it was not possible to determine whether elevated risk-taking is a direct consequence of marijuana or any other substance use. Further, elevated risk taking may predate substance use. However, one might speculate that substance use exacerbates a premorbid tendency toward risk taking, placing the user at greater risk for harmful consequences . Because we studied a community sample of marijuana users , the differences between the non-using controls and marijuana users may be attenuated relative to clinical samples of marijuana users. We also acknowledge that, given the number of comparisons made, the risk of type-I error is increased. Given the sample size, we were not able to examine the presence of gender differences,plant grow table and this is an area for future research. In addition, we used a food reward because the participants started the study when they were less than 18 years old, and we had to adjust reimbursement for study participation to protect this initially underage sample from possible coercion. Although Gonzalez et al. , as well as the originators of the BART task used monetary rewards for BART performance , the current sample had a higher average number of pumps , suggesting that a food reward was a sufficient motivator in this sample. This study used a version of the BART that required manual pumps for each balloon and did not provide feedback after each trial . According to Pleskac et al., this manual BART may be biased due to psychomotor demands . They further explained that the average adjusted pumps score is biased because it excludes responses that ended in an explosion ; therefore, it is an underestimate of the number of pumps the participant would have completed if the balloon had not popped. Given that we are examining the risky behavior that would lead to increased pumps and popped balloons, the average adjusted pumps may not be the optimal estimate of risky behavior. This may partially explain why marijuana users and nonusing controls did not differ on this score. A newer automatic BART avoids biases by informing participants of the optimal number of pumps , allowing them to numerically input pumps , rather than tapping the spacebar 85 times, and providing trial-by-trial feedback . Future studies should consider the automated BART to maximize behavioral variability. Additionally, we excluded recent users to reduce residual effects of substance use; however, it is possible that cannabis users who did not complete the abstinence protocol may have produced a different pattern of results. Thus, risk-taking behavior may be examined over the first few weeks of abstinence to determine how behavior changes when substance use is stopped. We were not able to examine the precise role of various substances on BART performance; therefore, the role of alcohol and other drug use in risk-taking should be further explored. Future studies may also examine physiological measures of marijuana levels prior to and throughout the abstinence period.
Given that self-reported externalizing behavior was not correlated with BART performance, we did not pursue this variable further; however, future studies may consider the role of externalizing behavior on risk-taking and BART performance.Marijuana and other substance use during adolescence and young adulthood is concerning because this is a critical time of continuing brain development .A review by Gowin et al. suggests that individuals with substance use disorders show alterations in the prefrontal cortex and in adjacent areas involved in executive functions and risk/reward processing , and these alterations have been associated with greater risk-taking on behavioral measures and elevated levels of substance use. Our finding of elevated risk-taking among marijuana users is in agreement with their hypothesis that substance users have impaired risk processing that may result from under activation of areas responsible for evaluating risks and/or an over activation of reward processing centers . Marijuana users’ poorer executive function , while not correlated with the current measure of risk-taking, may reflect a weakness in flexibility of thinking that could also lead to deficiencies in effectively integrating and organizing information. In their review of prefrontal cortex function and addiction, George and Koob described the prefrontal cortex as highly modulated with a variety of subsystems, and a dysfunction of any of these subsystems could explain the individual differences in self-regulation and vulnerabilities to substance use and/or addiction. Consistent with Romer et al. , our findings also suggest that risk-taking is not always associated with executive dysfunction, and that there may not always be a linear relationship between the various executive cognitive functions and more emotionally driven risk or reward processing. In light of the current and previous findings, clinicians should consider that dysfunction within one or more prefrontal executive subsystems may be responsible for behavior leading to or resulting from problematic substance use, and that risk-taking may not necessarily imply deficient executive functioning. While some risk-taking in adolescence is important as youth evolve into independent adults, continued research on the neurobehavioral mechanisms for maladaptive risk-taking can help us to understand why some youth progress to regular substance use or develop substance use disorders.As more states legalize the sale and consumption of marijuana, the number of Americans using it continues to rise . This increase in the use of marijuana highlights the need for a better understanding of its risks and benefits. One area of importance is its effect on cardiovascular disease, the number one cause of morbidity and mortality worldwide . Marijuana may affect cardiovascular health in several ways. Like other psychoactive drugs, it may have hemodynamic effects that can precipitate events . The active ingredient in marijuana is Δ9-tetrahydrocannabinol , which is responsible for the psychoactive effects of marijuana through its interaction with cannabinoid receptors. These receptors are ubiquitous in the brain and its vasculature and present throughout the body, including the myocardium, coronary endothelium, and smooth muscle cells . In vitro and animal studies have reported that THC can modulate cannabinoid receptors on human cardiomyocytes and vascular smooth muscles, resulting in ischemia . In vitro studies also have demonstrated that THC influences the regulation of glucose and lipid metabolism, suggesting a possible effect on vascular risk factors . At the cellular level, THC may cause inflammatory cytokine release, alteration in lipid metabolism , and reactive oxygen species formation . These effects may potentiate the progression of vascular disease.