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 intercorrelations 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, 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 non-using controls did not differ on this score. A newer automatic BART avoids biases by informing participants of the optimal number of pumps ,indoor garden table allowing them to numerically input pumps , rather than tapping the space bar 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 . The primary structure involved in executive functions and impulse control is one of the last cortical structures to mature . 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.

Tobacco dependence is prevalent among individuals in Medication Assisted Treatment for opioid use disorder. Methadone maintenance patients have been the most extensively studied, and between 84% and 94% of them report they are current smokers.One group reported a 90% current smoking rate in a sample that included patients receiving methadone or buprenorphine MAT for opioid use disorder.Two groups compared the smoking status of patients with opioid use disorder receiving either methadone or buprenorphine; both found similar rates in both groups, with over 90% of the patients reporting current smoking.Most patients in treatment for opioid use disorder have lower educational and socioeconomic status than the general population, and higher smoking rates are associated with lower status.Opioid administration may make smoking cessation difficult, as increases in both methadone dose and buprenorphine dose are related to increased smoking.Stress is related to cigarette smoking,and individuals with opioid use disorders often lead stressful lives.Nevertheless, 44–80% of methadone maintenance clients report wanting to quit smoking cigarettes.Randomized controlled trials of treatment for cigarette smoking in patients receiving MAT for opioid use disorder have been reported. The earliest study compared cognitive–behavioral therapy alone to CBT plus a 20% methadone dose increase .Post treatment cigarette abstinence rates were 0 in the dose increase plus CBT condition and 18% in the CBT alone condition. At follow-up, one participant in the control condition was abstinent from cigarettes and none in the experimental condition. In a second study,participants received 12 weeks of nicotine replacement therapy and were assigned to one of four conditions: NRT-only, relapse prevention + NRT, contingency management + NRT, or relapse prevention + contingency management + NRT. During treatment, contingency management participants showed higher abstinence rates than those who did not receive contingency management. At 6- and 12-month follow-up visits, there were no differences between conditions. Sigmon et al. found that extending contingent reinforcement for abstinence increased extended abstinence rate over non-contingent reinforcement.Stein et al. randomized 383 patients to either advice only or an experimental condition.Abstinence rates did not differ between conditions at either 3 months or 6 months . A fourth study recruited 225 cigarette smokers from methadone maintenance and other drug and alcohol treatment clinics.Participants were randomly assigned to 12 weeks of CBT+NRT or to treatment as usual. Smoking abstinence rates were 10–11% during the five-week treatment period in the CBT+NRT condition, and “negligible” in the control condition. At 13- and 26-week follow-up, differences between the two conditions were non-significant and ranged from a low of 0 in the control condition at week 13 to a high of 5.7% in the experimental condition at week 26.

Effects of nonnicotinic pharmacotherapy on cigarette abstinence in patients receiving MAT for opioid use disorder have been studied. Efficacy of 6 months of varenicline treatment compared to placebo and to combined NRT did not indicate significant differences, with low rates in all conditions . Nahvi et al. found differences favoring varenicline over placebo at 12 weeks in methadone maintenance clients, although rates were low and differences were not maintained after drug treatment ended.In the combined data from two studies, Sigmon et al. found no effect for bupropion treatment.In summary, cigarette smoking rates in patients receiving MAT for opioid use disorder are high, although these patients report a desire to quit smoking. Interventions generally considered effective in other populations have not been successful in effecting long-term abstinence in patients receiving MAT for opioid use disorder, and abstinence rates are low. In the current study, we compared an extended innovative system intervention with a standard treatment control to increase cigarette smoking abstinence in buprenorphine treatment patients. The E-ISI had two components modeled after a similar intervention used successfully in a study of smokers in treatment for depression.It included the Expert System intervention, a motivational tool that is designed to intervene with individuals who may not be willing to make the commitment to quit smoking cigarettes.In the current study, we offered an extended, intensive treatment that provided extended NRT,grow rack as well as the opportunity to receive varenicline, and an extended cognitive behavioral intervention . The E-CBT has produced high and stable long-term abstinence rates in three treatment studies in the general population.The study was conducted in the Integrated Buprenorphine Intervention Service operated under the San Francisco Department of Public Health . All IBIS patients received their maintenance drug through a single central pharmacy. The study was approved by the University of California San Francisco Institutional Review Board and written informed consent obtained after verification of study eligibility. Clinic data indicated that 83% of the IBIS patients smoked cigarettes. To be eligible for services through IBIS, patients must have been 18 years of age or older, have had a diagnosis of opioid use disorder, resided in San Francisco City or County, and be eligible for treatment through the SFDPH system of health care. Patients dependent on benzodiazepines or alcohol, who had an uncontrolled medical or psychiatric condition, who had a pain syndrome requiring opioid analgesics, or who were pregnant or planning to become pregnant were treated elsewhere in the SFDPH system. Potential participants needed to have smoked ≥5 CPD for the last week, and, in order to insure a degree of stability, to have been in IBIS for at least 3 months. They did not need to want to quit smoking. Patients with contraindications for NRT were excluded. Patients with a history of Schizophrenia or Bipolar Disorder in their medical record, or diagnosed with these disorders on the Mini International Neuropsychiatric Inventory,were not eligible. Potential participants with current major depressive disorder, or who reported a suicide attempt within the last year, were not eligible to receive varenicline but were eligible for NRT and E-CBT. Participants were recruited via flyers at the clinic or were approached by the research staff to solicit participation. Research staff routinely reviewed medical records of patients who had been in treatment at IBIS for at least 3 months,and approached those patients. All participants had clearance from IBIS staff to participate.At each assessment, participants reported CPD and were queried about other smoking treatments used, if any. An expired-air carbon monoxide sample was obtained and a urine sample for anatabine/anabasine assays.At the follow-up assessments, participants were coded as abstinent if they reported not smoking within the past 7 days, had expired CO levels <5,and anatabine/anabasine levels <2.The primary outcome variables were 7-day self-reported cigarette abstinence biochemically verified by CO and anatabine and anabasine assays at months 12 and 18. A questionnaire with demographic, smoking history, and smoking behavior questions was also administered at baseline. At all assessments, we also administered the Profile of Mood States,the Fagerström Test for Cigarette Dependence ,the Medical Outcomes Scale, Short-Form ,the Drug and Alcohol severity and Psychiatric severity scales of the Addiction Severity Index,the Thoughts About Abstinence Questionnaire,the Minnesota Nicotine Withdrawal Scale,a questionnaire that assessed Stages of Change,and questions about life-time and 30-day cannabis use that are part of the Addiction Severity Index .