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BACKGROUND: Understanding the course of anxiety and depressive symptoms in early opioid use disorder (OUD) treatment may inform efforts to promote positive early treatment response and reduce treatment attrition. METHODS: Persons in treatment for nonmedical opioid use were identified from 86 addiction treatment facilities. Growth mixture modeling was used to identify trajectories of anxiety and depression symptoms during the first month of treatment among individuals who screened positive for depression (N=3016) and/or anxiety (N=2779) at intake. RESULTS: A three-class solution best fit the data for anxiety symptoms and included the following trajectories: 1) persistent moderate-to-severe anxiety symptoms, 2) remitting severe anxiety symptoms, and 3) persistent minimal-to-mild anxiety symptoms. Similarly, a three-class solution best fit the data for depressive symptoms and included trajectories characterized by 1) persistent moderate-to-severe depressive symptoms, 2) persistent moderate depressive symptoms, and 3) mild/remitting depressive symptoms. Persistent moderate-to-severe anxiety and depressive symptoms were predicted by female gender and heavy past-month benzodiazepine co-use. LIMITATIONS: Fine grained-information about substance use was not collected. Results may not be generalizable to individuals receiving treatment outside of specialty addiction clinics. CONCLUSIONS: Analysis of anxiety and depression symptom trajectories in early treatment suggest that a subset of individuals entering treatment for opioid use experienced persistent and significant anxiety and depressive symptoms, whereas others experience a remission of symptoms. Interventions designed to target individuals at the greatest risk, such as women and individuals reporting opioid/benzodiazepine co-use, may help improve mental health symptoms in early OUD treatment.

Background and objectives Patients receiving opioid agonist therapies have high rates of psychiatric comorbidity. Some data suggest that comorbidity is associated with poorer treatment outcomes. The current study assessed predictors of multiple putative addictive behaviors among patients receiving opioid agonist therapies. Methods Adults (N = 176) recruited from an outpatient clinic providing opioid agonist therapy completed self-report measures of depression, anxiety, impulsivity, adverse childhood events, and the Recognizing Addictive Disorders (RAD) scale, which includes seven subscales assessing symptoms related to alcohol use, drug use, tobacco use, gambling, binge-eating, hypersexual behavior, and excessive video-gaming. Linear regression and hurdle models identified significant predictors of RAD subscales. Hurdle models included logistic regression estimation for the presence/absence of symptoms and negative binomial regression for estimation of the severity of symptoms. Results Most patients did not report significant symptoms beyond drug or tobacco use. However, 7% to 47% of participants reported some symptoms of other addictive behaviors (subscale score > 0). Higher impulsivity predicted the presence and/or increased severity of symptoms of drug use, gambling, binge-eating, and hypersexuality. Higher depression significantly predicted increased severity of drug use and binge-eating symptoms. Increased anxiety predicted lower severity of alcohol use and binge-eating and higher severity of smoking symptoms. Conclusion and scientific significance A broader range of potentially addictive symptoms may be present among patients engaged in treatment for opioid use disorder. Few studies have assessed symptoms of binge-eating, hypersexuality, and excessive video-gaming among patients receiving opioid agonist therapy. This study contributes to preliminary findings and highlights important future directions. (Am J Addict 2021;00:00-00).

Introduction: Driving after cannabis use is associated with a number of risks. Examination of driving after cannabis use among young adults is particularly important, as young adults have the highest rates of cannabis use and among the highest rates of traffic crashes. The current study examines rates and correlates of driving after cannabis use among young adults (aged 18–25) who reported past month cannabis use. Methods: Participants were from Michigan and recruited through paid Facebook and Instagram advertisements between February and March 2018 (n=461). Results: Nearly a third (31.9%) of the sample reported driving after cannabis use in the past month. Young adults who were employed (aOR=1.872, p=0.045), had medical cannabis cards (aOR=2.877, p

STUDY OBJECTIVES: Individuals with opioid use disorder (OUD) may experience worsening sleep quality over time, and a subset of individuals may have sleep disturbances that precede opioid use and do not resolve following abstinence. The purpose of the present study was to (1) collect retrospective reports of sleep across the lifespan and (2) identify characteristics associated with persistent sleep disturbance and changes in sleep quality in persons with OUD. METHODS: Adults with OUD (n = 154) completed a cross-sectional study assessing current and past sleep disturbance, opioid use history, and chronic pain. Repeated-measures analysis of variance was used to examine changes in retrospectively reported sleep quality, and whether changes varied by screening positive for insomnia and/or chronic pain. Multivariate linear regression analyses were used to identify additional correlates of persistent sleep disturbance. RESULTS: Participants reported that their sleep quality declined over their lifespan. Changes in reported sleep over time varied based on whether the individual screened positive for co-occurring insomnia and/or chronic pain. In regression analyses, female sex (β = 0.16, P = .042), a greater number of treatment episodes (β = 0.20, P = .024), and positive screens for chronic pain (β = 0.19, P = .018) and insomnia (β=0.22, P = .013) were associated with self-reported persistent sleep disturbance. Only a portion of participants who screened positive for sleep disorders had received a formal diagnosis. CONCLUSIONS: OUD treatment providers should routinely screen for co-occurring sleep disturbance and chronic pain. Interventions that treat co-occurring OUD, sleep disturbance, and chronic pain are needed. CITATION: Ellis JD, Mayo JL, Gamaldo CE, Finan PH, Huhn AS. Worsening sleep quality across the lifespan and persistent sleep disturbances in persons with opioid use disorder. J Clin Sleep Med. 2022;18(2):587–595.

Affect and craving are dynamic processes that are clinically relevant in opioid use disorder (OUD) treatment, and can be quantified in terms of intra-individual variability and stability. The purpose of the present analysis was to explore associations between opioid use and variability and stability of affect and craving among individuals receiving medication treatment for OUD (MOUD). Adults (N = 224) with OUD in outpatient methadone or buprenorphine treatment completed ecological momentary assessment (EMA) prompts assessing positive affect, negative affect, opioid craving, and opioid use. Dynamic structural equation modeling (DSEM) was used to quantify person-level indices of magnitude and stability of change. Beta regression was used to examine associations between intra-individual variability and stability and proportion of opioid-use days, when controlling for overall intensity of affect and craving. Results suggested that greater magnitude of craving variability was associated with opioid use on a greater proportion of days, particularly among individuals with lower average craving. Low average positive affect was also associated with higher proportion of days of use. Individuals who experience substantial craving variability in the context of lower average craving may be particularly vulnerable to opioid use during treatment. Ongoing assessment of craving may be useful in identifying treatment needs. Examining correlates of intra-individual variability and stability in MOUD treatment remains a relevant direction for future work.

OBJECTIVE: Substance use disorders and behavioral addictions commonly co-occur. However, few available self-report measures reliably and validly assess the full range of addictive conditions. The development and initial validation of a new measure—Recognizing Addictive Disorders scale (RAD) addresses a significant gap in the literature. METHOD: After items were generated and evaluated in Study 1, Study 2 (N = 300), applied exploratory factor analysis to the item pool using an online-based community sample. In Study 3 (N = 427), the factor structure was validated using an independent online-based community sample and confirmatory factor analysis. RESULTS: The scale demonstrated good internal consistency (a = .91) and construct validity, including replication of the factor structure (χ(2) (553) = 760.83, p < .001, CFI = .997, TLI = .997, RMSEA = .030) and correlation with a related transdiagnostic measure of addiction (r = .72). DISCUSSION: Overall, results support preliminary validity of a brief transdiagnostic measure of addiction that considers a diverse range of behaviors. For patients presenting to substance abuse treatment, this tool may be useful in identifying the frequency of other types of non- substance problems, which could ultimately aid in treatment planning.

Background and objectives Regular cannabis users experience cannabis-related consequences across many domains of functioning. The present study examined demographic, cannabis use, and depressive correlates of cannabis consequences. We hypothesized that (1) earlier onset of use would predict greater psychological and functional consequences; and (2) women would endorse more psychological and withdrawal consequences. Methods Data were collected from an urban sample of 184 adults who reported regular cannabis use. Seventeen items from a cannabis consequence checklist were grouped into three domains: Psychological Consequences, Cannabis Withdrawal, and Functional Consequences. Three multiple regressions were performed to explore demographic and cannabis use correlates of each domain. Correlations between domains and depressive symptoms were assessed using Pearson's r. Results Greater endorsement on the Psychological Consequence subgroup was predicted by female sex, lower educational attainment, and treatment-seeking history for cannabis abuse/dependence. Individuals with greater number of quit attempts or treatment-seeking history endorsed more items in the Cannabis Withdrawal domain. Although the model failed to reach significance for Functional Consequences, age at onset of regular and daily cannabis use were negatively associated with this domain. Correlational analyses demonstrated higher Beck Depression Inventory-Second Edition scores were related to greater endorsement of Psychological Consequence and Cannabis Withdrawal items. Discussion and conclusions Regular cannabis users report consequences of use, which can be grouped into content-specific subgroups. Individual characteristics are differentially associated with these subgroups. Scientific significance Understanding which individual characteristics are related to cannabis use sequelae could help identify those at risk for greater consequences, thus leading to improved assessment and treatment interventions. (Am J Addict 2019;28:295-302).

Background and objectives Drug-related dreams are commonly reported by individuals in treatment for substance use disorders, which may be distressing. Existing evidence suggests that dream recollection may be influenced by clinically relevant phenomena, such as opioid use and withdrawal, general sleep disturbance, affective symptoms, and chronic pain. However, very few studies have explored drug-related dreams among individuals who screened positive for opioid use disorder (OUD). Methods Adults recruited from Amazon Mechanical Turk (MTurk) who screened positive for OUD (N = 154) completed a questionnaire about drug-related dreams, as well as measures assessing sleep, opioid use history, stress, anxiety, and chronic pain. χ2 analyses, one-way analysis of variance, and bivariate correlations, correcting for the false discovery rate, were used as appropriate to explore correlates of (1) recollecting a drug-related dream, and (2) experiencing post-dream craving and distress. Results Individuals who recollected a past-week drug-related dream were more likely to report other recent sleep disturbances, including poorer sleep quality, greater insomnia symptoms, and a higher risk for sleep apnea. Post-dream craving and distress were both associated with greater insomnia symptoms, poor sleep hygiene behaviors, and greater anxiety symptoms. Individuals who had ever experienced a drug-related dream (recently, or in their lifetime) were more likely to report a history of severe withdrawal, overdose, and intravenous opioid use. Conclusion and scientific significance Drug-related dreams were common among individuals in the present sample and were related to other clinically relevant phenomena. Interventions that treat co-occurring OUD, pain, sleep symptoms, and affective symptoms may improve overall well-being in this population.

Non-medical use of both opioids and sedatives increases risk of overdose or accident. The purpose of the present study was to describe rates of co-use, to examine baseline characteristics and psychiatric conditions potentially associated with meeting criteria for co-occurring opioid use disorder and sedative use disorder, and to examine whether these relationships varied by gender. Participants were 330 individuals from the NESARC-III who met criteria for current opioid use disorder. Gender-stratified logistic regression analyses, accounting for the survey design, were used to identify psychiatric conditions associated with meeting criteria for co-occurring sedative use disorder. Results indicated that 16.4% of the sample also met criteria for sedative use disorder. Notably, 55.6% of the sample attained opioids through their own prescription. Of those with co-occurring sedative use disorder, 47.2% attained sedatives through their own prescription. Posttraumatic stress disorder (OR = 3.02, 95% CI = 1.40–6.51) and antisocial personality disorder (OR = 2.72, 95% CI = 1.37–5.41) were associated with co-occurring sedative use disorder among both men and women with opioid use disorder. Depressive disorders (OR = 2.12, 95% CI = 1.01–4.42) and schizotypal personality disorder (OR = 5.78, 95% CI = 2.48–13.49) were associated with co-occurring sedative use disorder in women only. Results of the present study highlight the importance of prescription monitoring, further research into gender-informed treatments, and implementation of treatments for substance use and co-occurring symptoms.

Contingency management (CM) is an effective intervention for reducing use of licit and illicit substances in a variety of populations. Pregnant women are a vulnerable population with much to gain from effective interventions for substance use disorders, and for whom CM interventions may be especially well-suited. We reviewed the literature on CM interventions among pregnant women with tobacco and other substance use disorders with 3 aims: (a) describe the effectiveness of CM for reducing use of tobacco and other substances during pregnancy, (b) describe the effects of CM interventions on infant outcomes, and (c) identify needs for future research on CM in pregnancy. Our search strategy revealed 27 primary studies of CM in pregnancy. CM was effective in the majority of studies targeting nicotine abstinence, and results were mixed in studies targeting illicit substances. A variety of methodologies were used within the relatively small number of studies making it difficult to identify underlying mechanisms. Also, very few studies reported maternal and infant outcomes, and significant effects of CM were only apparent when secondary analyses pooled data from multiple studies. Furthermore, there is extremely limited data on the cost effectiveness of CM interventions in pregnancy. Future research should address these 3 areas to better determine the ultimate value of CM as an efficacious treatment for pregnant women with substance use disorders. (PsycINFO Database Record

Opioid-related deaths have risen dramatically in rural communities. Prior studies highlight few medication treatment providers for opioid use disorder in rural communities, though literature has yet to examine rural-specific treatment barriers.We conducted a systematic review to highlight the state of knowledge around rural medication treatment for opioid use disorder, identify consumer- and provider-focused treatment barriers, and discuss rural-specific implications.We systematically reviewed the literature using PsycINFO, Web of Science, and PubMed databases (January 2018). Articles meeting inclusion criteria involved rural samples or urban/rural comparisons targeting outpatient medication treatment for opioid use disorder, and were conducted in the U.S. to minimize healthcare differences. Our analysis categorized consumer- and/or provider-focused barriers, and coded barriers as related to treatment availability, accessibility, and/or acceptability.Eighteen articles met inclusion, 15 which addressed consumer-focused barriers, while seven articles reported provider-focused barriers. Availability barriers were most commonly reported across consumer (n = 10) and provider (n = 5) studies, and included the lack of clinics/providers, backup, and resources. Acceptability barriers, described in three consumer and five provider studies, identified negative provider attitudes about addiction treatment, and providers' perceptions of treatment as unsatisfactory for rural patients. Finally, accessibility barriers related to travel and cost were detailed in four consumer-focused studies whereas two provider-focused studies identified time constraints.Our findings consistently identified a lack of medication providers and rural-specific implementation challenges. This review highlights a lack of rural-focused studies involving consumer participants, treatment outcomes, or barriers impacting underserved populations. There is a need for innovative treatment delivery for opioid use disorder in rural communities and interventions targeting provider attitudes.