PSUs exhibited greater temporo-occipital BOLD signals to wins than to losses, findings consistent with a recent meta-analysis reporting that 86% of addiction-related neuroimaging studies demonstrate significant visual cortex activity to drug cues . Although the RGT did not test drug-related responses, our results demonstrate an analogous relationship to general reward cues, suggesting that PSUs may allocate greater visual attention to risky rewards than to risky losses. Middle temporal lobe is involved in memory of reward-based information critical for future oriented decision making, suggesting that PSUs may be less able to consolidate information about outcomes differently . Together, PSUs are characterized by visual attention and memory activation during risky rewards but blunted responsivity to loss outcomes. Our third prediction was supported in that PSUs exhibited lower PFC, insula, and cingulate BOLD signals than DSUs during risky feedback. These findings align with a recent study conducted by our research group demonstrating that during a task evaluating how individuals learn to make decisions, PSUs exhibited lower insula and ACC activation across all available outcomes than DSUs . Such patterns are consistent with previous reports of PFC, insula, and ACC attenuations in chronic stimulant users that are linked with decreased ability to adapt behavior using prior experiences/ reduced inhibitory control, horticulture solutions interoceptive awareness, and conflict monitoring, respectively . Thus, young adults predisposed to SUD may have prior deficits in recruiting neural effort toward critical decision-making processes. Nonhypothesized group differences also emerged in thalamic, precuneus, and posterior cingulate regions that warrant discussion.
PSUs showed relatively greater precuneus and posterior cingulate BOLD signals when making risky decisions than when making safe decisions when compared with DSUs. Such differences are consistent with previous findings in SUD samples that heightened activation of these areas during exteroceptive awareness may underlie the maintenance and exacerbation of substance use . Greater thalamic response to risky reward versus loss feedback in PSUs is consistent with research demonstrating that thalamic BOLD signals are linked to relapse in cocaine-dependent individuals . Thalamus acts as a relay center for the brain by sending sensory information to insula for further interoceptive processing ; hypoactivation to loss may reflect differences in relay and integration of information during decision making. With respect to baseline characteristics, DSUs endorsed higher baseline levels of state depression than PSUs, which may have affected RGT performance given that individuals with depression tend to be risk averse . However, given that mean scores for DSUs are substantially below the Beck Depression Inventory threshold for clinical depression [in nonclinical populations, scores above 20 indicate depression ; it is unlikely that DSUs performed in a manner consistent with samples with depression].Across OSUs, lower frontal, temporal, parietal, insular, and thalamic BOLD signals during risky decisions compared with safe decisions predicted greater future marijuana use . These regions are considered important for executive functions such as inhibitory control, working memory, and attention as well as for being relay centers for integrating information critical for decision making . Therefore, blunted responses in these regions while making choices between risky and safe optionsdose–response effect may exist between brain activation and marijuana use, the relationship between brain activation and stimulant use may be better defined through a categorical perspective that includes accompanying clinical symptomology.
Although PSUs and DSUs used marijuana at significantly high rates , groups did not differ categorically in marijuana abuse/dependence frequency. In contrast, stimulant use in and of itself might not be related to brain differences unless it is accompanied by clinical problems, suggesting that a categorical perspective is a more useful way to conceptualize differences.This study has several unique strengths, including its longitudinal design, use of a model previously applied to chronic stimulant users, and assessment of substance use from both categorical and dimensional perspectives . However, this study is limited by our sample’s significant co-use of marijuana and the categorical criteria that prioritized differences as a function of SUD over marijuana use disorder given that PSUs and DSUs did not differ on baseline/interim marijuana use. In addition, although SUD has been associated with greater incidence of psychiatric illness , lack of clinical symptom measures collected at follow-up hinders our ability to determine whether mental health symptoms affected interim substance use. We are also limited by an inability to evaluate the RGT from a trialby-trial perspective to determine whether BOLD response patterns translate into future behavior or are affected by the preceding trial; due to the limited number of separate 40 and 80 trials, it would not be possible to obtain sufficient statistical power to conduct such an analysis.Studies report that depression is associated with substance use, which can worsen depression-related disability . These studies have found depression is associated with a two-fold increase in the rate of alcohol related problems and a six-fold increase in marijuana-related problems .
Yet clinical outcomes of depression patients who use marijuana are understudied in contrast to alcohol, perhaps due to the larger public health burden associated with depression and alcohol use . However, there is also considerable potential for marijuana to impede the recovery of vulnerable subgroups, including clinical populations. Clinical studies report that marijuana use among depression patients can lead to worse symptoms, more depressive episodes, and impede treatment . These findings suggest that marijuana may be a critical issue for further understanding recovery outcomes in adults with depression. Differences in demographic, clinical, and marijuana use characteristics are important considerations for the treatment and recovery of persons with depression. Depressed persons who use drugs, including marijuana are often younger, male, divorced or never married and not of Hispanic origin . Marijuana and other drug use among depressed persons can lead to worse anxiety, drug use relapse post-treatment, and poor functioning . Whether such findings are present and persist over time in a clinical sample of depressed patients is largely unknown. This study addresses this important question by examining 6-month patterns of marijuana use and its impact on symptom and functional recovery outcomes for 307 depressed outpatients using and not using marijuana and participating in an alcohol/illicit-drug use intervention. We identified: longitudinal patterns of marijuana use; demographic and clinical predictors of marijuana use; associations between marijuana use, depression and anxiety symptoms, and functioning over the 6-month follow-up. Data were collected for a randomized controlled trial of motivational interviewing in alcohol/drug use treatment for depressed patients,grow shelving for which the results have been reported . A total of 307 patients were recruited from Kaiser Permanente Southern Alameda Center Department of Psychiatry in Union City and Fremont, CA. Inclusion criteria were: aged 18 or older; Patient Health Questionnaire score ≥ 5 ; met drug use or hazardous drinking criteria within the past 30-days. A Hazardous drinking standard more conservative than that recommended for the general population was used . Patients with mania or psychosis were excluded. The present study makes use of secondary data from the previously described trial of MI in alcohol/drug use for depressed patients. In this secondary analysis, we focused on examining the 6-month patterns and predictors of marijuana use and its association with recovery for those using and not using marijuana . Eligibility of the 307 participants was determined by baseline alcohol/drug use measures and PHQ-9 depression. Patient information was collected at baseline and then participants were randomized . Patients were offered $50 gift cards for completing the interviews . Of the 307 participants, 296 completed the 3-month telephone follow-up, 302 completed 6-month follow-up. Substance use, and participant’s symptoms and functioning were collected at baseline, 3-, and 6-months. The University of California, San Francisco Committee on Human Subjects and the Kaiser Permanente Institutional Review Board approved the procedures. Patients were provided with written informed consent prior to participation.
Analyses began by examining baseline differences between patients using and not using marijuana by using χ2 and independent sample t tests. Longitudinal analyses proceeded using a series of mixed-effects growth models, a form a hierarchical linear modeling for repeated measures data, where multiple measurement occasions are nested within individuals . Patterns of patients using marijuana were tested using generalized mixed-effects growth models employing penalized-quasi likelihood estimation for computing parameter estimates of binary outcomes. Analyses began with unconditional growth models predicting marijuana use from time to examine overall trajectories of marijuana use. Conditional growth models were computed to examine characteristics that may predict increased use of marijuana. Age, sex, marital status, race/ethnicity, MI, non-marijuana substance use, time-varying psychiatry visits, and time-varying depression were included in conditional models with marijuana use. Predictors were chosen because prior research signaled the variable as related to marijuana use and depression or the variable was significant in prior analyses. GAD-7 anxiety was not included as a predictor with marijuana use outcomes, owing to its high its correlation with PHQ-9 depression. Finally, associations between marijuana use and recovery outcomes were examined. These analyses were conducted with mixed-effects growth models using restricted maximum likelihood estimation for continuous outcomes, predicting symptom and functioning outcomes from time and time-varying marijuana. Rather than discard partial completers , the expectation maximization approach was used to handle missing data at analysis. Analyses were carried out in R version 2.14.2 . Statistical significance was defined at p < .05. After finding few baseline differences between the marijuana using and non-marijuana using groups, the patterns and predictors of marijuana use over 6-months were investigated. As reported in Table 2, the unconditional growth model results showed that the number of patients using marijuana significantly declined over time. Depression symptoms were associated with significantly increased rates of marijuana over 6-months. Marijuana use significantly increased for those aged 50+ over 6-months compared to the youngest age group, although patients aged 50+ were less likely to use marijuana at baseline . With respect to the 6-month recovery trajectories, findings revealed that patients using marijuana demonstrated significantly less improvement with regards to their depression and anxiety symptomatology, as well as mental health functioning than those not using marijuana. No evidence of a significant difference was found between those using and not using marijuana and physical health functioning . Post-hoc analyses using mixed-effect growth models were employed in the marijuana use sub-sample to investigate whether recovery outcome differences existed between those who used the drug recreationally or medicinally. No significant differences were found between those who reported recreational or medicinal use on the symptom or mental health functioning outcomes , indicating comparable impairment in these domains. However, compared to those reporting recreational marijuana use , those reporting medicinal use of the drug had significantly poorer physical health functioning. This study examined 307 depression outpatients using and not using marijuana on their recovery and marijuana outcomes over 6 months. Baseline findings revealed those who used marijuana were younger and less likely to be married. Reported rates of marijuana use were the highest within 30 days of baseline and then declined overall; however, patterns varied by patient characteristics. Higher depressive symptoms placed patients at risk for continued marijuana use, and patients aged 50+ were at high risk for increased marijuana use. Ongoing marijuana use led to poorer symptom and mental health functioning; medical marijuana was associated with poorer physical health functioning. Results suggest marijuana use is common and associated with poor recovery among psychiatry outpatients with depression.This work provides further support that marijuana use can be clinically problematic for psychiatry patients and suggests that on-going efforts to improve education around the adverse health effects of marijuana use are important . For example, if depression patients were more aware that ongoing symptom distress is linked to marijuana use, they might be more likely to consider treatment options to cut back. Many adults with depression try to stop using marijuana suggesting these patients may be more willing to try interventions with demonstrated efficacy such as MI . Marijuana prevention and treatment strategies also should target younger age groups, since use is high and associated with adverse consequences in adolescents and young adults . We found marijuana users were largely comprised of younger adults, but additionally that those age 50+ increased their use over time, suggesting the potential for adverse consequences among older adults and treatment needs for them.