Conversely, other studies have found that individuals with comorbid opioid and psychiatric disorders have equivalent or better treatment outcomes, such as improved negative urine drug assays, longer treatment engagement, and better medication adherence . These conflicting findings indicate treatment outcomes may be different by type of psychiatric condition and influenced by the duration of observation, which underscores the need for additional evidence on the impact of psychiatric comorbidities on treatment outcomes among patients with OUD. We aimed to address this gap in knowledge by examining a longitudinal cohort study of patients with OUD to assess different types of psychiatric disorders in relation to treatment experiences. We conducted a secondary analysis of data provided by the Starting Treatment with Agonist Replacement Therapies study , which was conducted at nine federally licensed opioid treatment program sites with 1269 participants randomized to buprenorphine or methadone from 2006 to 2009 . All participants were tapered off their assigned study medications by 32 weeks post-randomization. Any OUD pharmacotherapy received during the follow-up interval was arranged by the participants themselves independent of the study and could change over time. Analyses also included data from a follow-up study of all randomized participants conducted from 2011 to 2016, nearly 2–8 years after randomization, performing three assessments 1 year apart . After participants provided written informed consent, face-to-face interviews and urine samples were collected at the first follow-ups at each site . The second and third follow-ups were conducted by research staff via phone interviews. Participants were compensated for each visit according to local site policies for study testing and assessments .

The parent study and the follow-up study were funded by the National Institute on Drug Abuse Clinical Trials Network . The studies were approved by the Institutional Review Boards at each site, the State of California, and UCLA. A federal Certificate of Confidentiality was also obtained to protect participants’ information further. At the outset of the follow-up study, two sites were dropped,seedling grow rack accounting for 189 participants due to small sample sizes and difficulties with conducting follow-ups. Hence, 1080 study participants were ultimately targeted for the three follow-up visits. At the first follow-up interview , conducted August 2011–April 2014, 965 participants were located, and 797 were interviewed . At the second follow-up interview , conducted August 2012-June 2016, 723 participants from the group who completed Visit 1 were administered the Mini-International Neuropsychiatric Interview ; of these, 597 were again interviewed , from December 2013–June 2016, as the final followup interview . We omitted patients with eating disorders and psychotic disorders for the present paper, yielding a final analysis sample of 593 participants who completed all assessments. The mean length of the follow-up period among 593 participants was 6.5 years . The study flowchart provides additional details . The MINI was used at Visit 2 to assess psychiatric disorders according to DSM-IV criteria. The MINI includes modules on current diagnosis of different types of psychiatric disorders. We used indicators of current diagnoses to construct four mutually exclusive groups: 1) bipolar disorder , 2) major depressive disorder , 3) anxiety disorders , and 4) no mental disorder . Some participants had several mental health conditions . Thus, drawing on prior research , we used the following hierarchy to categorize participants into one group based on diagnostic severity. First, those with any current BPD diagnosis were assigned to the BPD group, regardless of other non-SUD mental health diagnoses and the presence of psychotic features. The MDD and AXD groups were then similarly constructed. The remaining participants did not have any current non-SUD mental disorders and therefore were categorized to the NMD group. It is important to note that post-traumatic stress disorder was included as an anxiety disorder in this study, consistent with DSM-IV classification, given that the data collection was initiated before the publication of the DSM-5, at which time PTSD was recategorized.

Chi-square test for categorical variables and ANOVA for continuous variables were used to compare group differences in baseline characteristics, treatment engagement measured from Visit 2 to Visit 3, substance use, ASI composite scores, BSI scale scores, and SF-36 physical and mental component summary scores at Visit 3. Also, pairwise comparisons were conducted using the Bonferroni correction for categorical variables and the Tukey-Kramer method for continuous variables. Except for pairwise comparisons, all other two-tailed tests with a p-value less than 0.05 were considered statistically significant. All data analyses were performed in SAS version 9.4 . Table 4 presents the group differences in addiction severity , physical and psychiatric symptoms , and quality of life at Visit 3. Compared to the NMD group, each of the three psychiatric disorder groups had greater problem severity in 6 of 7 domains , worse symptoms in all 10 measures of physical and psychiatric health, and poorer quality of life. Among three groups with mental disorders, participants with BPD had the worst physical and psychiatric symptoms. In the sensitivity analysis, adding the excluded 2 participants with eating disorders and 2 with psychotic disorders in the AXD group as a new group did not change the results . Attrition analysis revealed no statistically significant differences in the demographics of those interviewed and not interviewed except for gender . This study aimed to characterize psychiatric disorders and their association with long-term treatment outcomes among individuals initially treated with methadone or buprenorphine for OUD in the START study. In our follow-up study, we found that the participants without mental disorders had the lowest proportion of females, injection drug use, and history of psychiatric disorders at baseline. During follow-up visits, those with MDD had a higher proportion of follow-up months with OUD pharmacotherapy than those without mental disorders. At the end of the follow-up, participants with BPD had significantly more days of using heroin and all opioids in the past 30 days. Furthermore, those with comorbid psychiatric disorders showed more severe substance-related conditions, psychosocial functioning, and psychiatric symptoms at the end of follow-up. It has been well-established by previous studies that women are more likely than men to be diagnosed with a mental health condition . We also found that the prevalence of injection drug use at baseline was higher among patients with OUD and comorbid psychiatric disorders. Other studies have reported that psychiatric and substance abuse comorbidity is highly prevalent among people who inject drugs .

Taken together, these findings replicate prior evidence and highlight the need to design treatments and other interventions that are sensitive to gender and infectious disease risk behaviors. We also found that over 5 or more years of observation, patients with co-occurring opioid and major depressive disorders engaged with OUD pharmacotherapy for more months during follow-up than those without mental disorders. The continued high utilization of pharmacotherapy among patients with OUD and comorbid psychiatric disorders compared to those without mental disorders is notable and may have several explanations. Findings from the literature on the association between psychiatric comorbidity and treatment engagement have been inconsistent . Possible reasons for inconsistent results include different outcome variables, multiple types of medication used, and different diagnostic criteria for psychiatric disorders. However, MDD diagnosis has been associated with improved opioid treatment outcomes in prior research, possibly related to greater engagement in treatment , and that depression symptoms are associated with higher motivation to change opioid use . In the current study, we found higher utilization of methadone than buprenorphine by participants,greenhouse growing racks which may be explained by methadone clinic procedures. Patients receiving methadone were required to attend a clinic daily to obtain medication following regulations regarding methadone dispensing and thus were more regularly in contact with the clinic personnel, which likely enhanced treatment engagement. Conversely, buprenorphine patients were not required to attend the clinic daily, given the nature of buprenorphine self administration without supervision. Another explanation is that methadone treatment was more accessible to this group of individuals who were largely impoverished. At the end of the follow-up, more than 5 years after baseline, participants with BPD had significantly more heroin and other opioid use in the past 30-days. This finding further supports the claim that some patients with OUD and comorbid psychiatric disorders may have higher rates of opioid use due to their greater psychiatric symptom severity . Consistent with previous studies , patients with OUD and comorbid psychiatric disorders reported poor functioning across multiple domains. Numerous significant group differences in components of ASI composite scores, BSI scale scores, SF-36 physical and mental component summary scores indicated higher problem severity across multiple problem areas in patients with OUD and different comorbid psychiatric disorders. Based on severity, participants with BPD had the poorest functional outcomes.

Since the 1970s and 80 s, a number of studies demonstrated that psychotherapy can be used effectively with individuals with SUDs . To reduce healthcare costs, however, support was reduced for these psychiatrically focused treatments. These findings point to an unmet need for medication and psychosocial therapies for patients with OUD and psychiatric comorbidity. This study has several limitations. First, we assessed the type of psychiatric disorders at follow-up Visit 2. Although the question about the history of psychiatric disorders was included at treatment entry , the pre-existing diagnosis patterns according to objective measures and the temporal relationship between OUD and psychiatric disorders are unknown. Second, attrition analysis showed that female participants had a higher follow-up rate, which might be over represented in this study, but the rates of treatment engagement in the present study were similar to an 11-year follow-up of the Australian Treatment Outcome Study . Third, results are based on a sample of individuals treated for OUD in community-based, federally regulated OTP clinics, and thus findings may have limited applicability to patients treated in primary care clinics or other settings. Fourth, we did not include sedative use , which is common in individuals with OUD and did not collect information about participants’ treatment for mental health disorders, both of which could have impacted treatment outcomes. Finally, substance use and treatment participation were self-reported and may be subject to recall bias. As for study strengths, this secondary analysis was conducted with a relatively large sample derived from a multi-site clinical trial and a follow-up prospective longitudinal study with a long duration to assess associations between OUD pharmacotherapy treatment outcomes and co-occurring psychiatric conditions. Our study sample has a similar rate of psychiatric disorders as has been reported in nationally representative data . Electronic -cigarettes are drug delivery devices primarily used for the inhalation of nicotine and marijuana, in the form of tetracannabinoids . The modern e-cigarette was invented in 2003, entered the global market in 2007, and has rapidly become popular across the world. There are many types of e-cigarettes, from cig-a-likes to vape pens and box Mods to pod-devices, but they all involve heating and aerosolization of e-liquids . The base ingredients of e-liquids, nicotine, propylene glycol and glycerin, have an unappealing flavor on their own such that chemical flavorants are added to >99% of e-liquids to increase the appeal to users. Use patterns of electronic -cigarettes and vaping devices differ greatly across age groups. Adults most commonly pick up vaping in the setting of conventional cigarette smoking, either adding it into their smoking practice or switching to e-cigarettes as a means to stop smoking. While 3.2% of all adults use ecigarettes, the rates are much higher in young adults 18-24 years-old, of whom 7.6% vape, and higher still in high school students, of whom 27.5% have used a vaping device within the past month. Sadly, middle school students as young as age 11 also have high rates of e-cigarettes use. While adult e-cigarette users are most often active smokers or ex-smokers, 44.3% of adolescents and young adults were never smokers prior to e-cigarette use. Of concern, it has been shown that e-cigarette use in never smokers leads to higher initiation of cigarette smoking, up to four-fold. A great deal of research to date has been focused on comparing e-cigarette use to cigarette smoking to assess the potential benefit of switching from smoking to vaping as a form of harm reduction, while less focus has been on the health effects of vaping in non-smokers, for whom the rates of vaping continue to rise, particularly in the youth.