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Background: Valid, single-item cannabis screens for the frequency of past-year use (SIS-C) can identify patients at risk for cannabis use disorder (CUD); however, the prevalence of CUD for patients who report varying frequencies of use in the clinical setting remains unexplored., Objective: Compare clinical responses about the frequency of past-year cannabis use to typical use and CUD severity reported on a confidential survey., Participants: Among adult patients in an integrated health system who completed the SIS-C as part of routine care (3/28/2019-9/12/2019; n = 108,950), 5000 were selected for a confidential survey using stratified random sampling. Among 1688 respondents (34% response rate), 1589 who reported past-year cannabis use on the SIS-C were included., Main Measures: We compared patients with varying frequency of cannabis use on the SIS-C (< monthly, monthly, weekly, daily) to survey responses on the Composite International Diagnostic Interview Substance Abuse Module for CUD (any and moderate-severe CUD) and cannabis exposure measures (typical use per-week, per-day). Adjusted multinomial (categorical) and logistic regression (binary), weighted for population estimates, estimated the prevalence of outcomes across frequencies., Key Results: Patients were predominantly middle-aged (mean = 43.3 years [SD = 16.9]), male (51.8%), white (78.2%), non-Hispanic (94.0%), and commercially insured (68.9%). The prevalence of any and moderate-severe CUD increased with greater frequency of past-year cannabis use reported on the SIS-C (p-values < 0.001) and ranged from 12.7% (6.3-19.2%) and 0.9% (0.0-2.7%) for < monthly to 44.6% (41.4-47.7%) and 20.3% (17.8-22.9%) for daily use, respectively. Greater frequency of use on the SIS-C in the clinical setting corresponded with greater per-week and per-day use on the confidential survey., Conclusions: Among patients who reported past-year cannabis use as part of routine screening, the prevalence of CUD and other cannabis exposure measures increased with greater frequency of cannabis use, underscoring the utility of brief cannabis screens for identifying patients at risk for CUD., (© 2024. The Author(s), under exclusive licence to Society of General Internal Medicine.)

Importance: Alcohol withdrawal syndrome (AWS) is an important cause and complication of hospitalizations. Although common and preventable, the incidence of AWS during hospitalizations is poorly described., Objective: To evaluate the incidence and proportional incidence of hospitalizations involving AWS in an adult primary care population overall and across patient characteristics., Design, Setting, and Participants: This retrospective cohort study used electronic health records and insurance claims from Kaiser Permanente Washington (KPWA) between July 1, 2018, and June 30, 2022. The study included adults with 1 or more primary care visits during this period or the year prior, where primary care included annual standardized alcohol screening using the Alcohol Use Disorders Identification Test-Consumption (AUDIT-C)., Exposures: Age, sex, race, Hispanic ethnicity, AUDIT-C scores, and comorbid diagnoses., Main Outcome and Measures: Hospitalizations involving AWS were defined by diagnosis codes documented during hospitalizations (incidence numerator). Time enrolled in KPWA determined person-enrolled-years (incidence denominator). Proportional incidence was calculated as the incidence of hospitalizations involving AWS divided by the incidence of all-cause hospitalizations. Proportional incidence was also estimated for hospitalizations involving other common chronic conditions (chronic obstructive pulmonary disease, diabetes, heart failure, and hypertension), which were also defined using hospital diagnosis codes., Results: Among 544 825 adults engaged in primary care (mean [SD] age, 47.0 [17.9] years; 310 069 [56.9%] female; 3656 [0.7%] American Indian or Alaska Native, 55 206 [10.1%] Asian, 25 406 [4.7%] Black, 5204 [1.0%] Native Hawaiian or Other Pacific Islander, 365 780 [67.1%] White, 19 791 [3.6%] multiracial, 15 963 [2.9%] other races, and 53 819 [9.9%] unknown race; 33 987 [6.2%] Hispanic, 414 269 [76.0%] not Hispanic, and 96 569 [17.7%] unknown ethnicity), incidence of hospitalizations involving AWS was 169 (95% CI, 159-179) per 100 000 person-enrolled-years overall but as high as 15 347 (95% CI, 13 502-17 331) in patients with other alcohol-attributable diagnoses. The proportional incidence of hospitalizations involving AWS was 2.3% overall, with variation by age, sex, and AUDIT-C scores (eg, 9%-11% in male patients aged 30-49 years and 23%-44% in patients with high-risk AUDIT-C scores of 7-12 points). In most cases, among adults younger than 60 years, proportional incidence of hospitalizations involving AWS matched or surpassed that of other common chronic conditions (chronic obstructive pulmonary disease, diabetes, heart failure, and hypertension)., Conclusions and Relevance: In this cohort study of a large primary care population served by an integrated health system, AWS hospitalizations were common, especially in male patients, younger age groups, and individuals with high-risk alcohol use. During hospitalizations, the burden of AWS was similar to or exceeded complications of other chronic diseases that receive greater medical attention.

Objective: The Alcohol Addiction Research Domain Criteria (AARDoC) is an organizational framework for assessing heterogeneity in addictive disorders organized across the addiction cycle domains of incentive salience, negative emotionality, and executive functioning and may have benefits for precision medicine. Recent work found pretreatment self-report items mapped onto the addiction cycle domains and predicted 1- and 3-year alcohol use disorder treatment outcomes. Given the potential utility of the addiction cycle domains for predicting relevant treatment outcomes, this study sought to evaluate the longitudinal measurement invariance of the domains., Method: We conducted a secondary analysis of individuals with alcohol use disorder ( n = 1,383, 30.9% female, 76.8% non-Hispanic White, 11.2% Hispanic) who participated in the COMBINE study. Eleven items assessed at pre- and posttreatment were included in exploratory structural equation modeling (ESEM) and longitudinal invariance analyses., Results: The pre- and posttreatment ESEM models had factor loadings consistent with the three addiction cycle domains and fit the data well. The ESEM factor structure was invariant from pre- to posttreatment (representing configural invariance) and metric invariance (factor loadings) was largely supported, but analyses failed to support scalar invariance (item-level thresholds) of the addiction cycle domains., Conclusions: A three-factor structure representing addiction cycle domains can be modeled using brief self-report measures pre- and posttreatment. Individuals demonstrated a downward shift in the level of item endorsement, indicating improvement with treatment. Although this 11-item measure might be useful at baseline for informing treatment decisions, results indicate the need to exercise caution in comparing the addiction cycle domains pre- to posttreatment within persons. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Background: Primary care (PC) offers an opportunity to treat opioid use disorders (OUD). The Substance Use Symptom Checklist ("Checklist") can assess DSM-5 substance use disorder (SUD) symptoms in PC., Objective: To test the psychometric properties of the Checklist among PC patients with OUD or long-term opioid therapy (LTOT) in Kaiser Permanente Washington (KPWA)., Design: Observational study using item response theory (IRT) and differential item functioning (DIF) analyses of measurement consistency across age, sex, race and ethnicity, and receipt of treatment., Patients: Electronic health records (EHR) data were extracted for all adult PC patients visiting KPWA 3/1/15-8/30/2020 who had ≥ 1 Checklist documented and indication of either (a) clinically-recognized OUD (i.e., documented OUD diagnosis and/or OUD medication treatment) or (b) LTOT in the year prior to the checklist., Main Measure: The Checklist includes 11 items reflecting DSM-5 criteria for SUD. We described the prevalence of 2 SUD symptoms reported on the Checklist (consistent with mild-severe DSM-5 SUD). Analyses were conducted in the overall sample and in two subsamples (clinically-recognized OUD and LTOT only)., Key Results: Among 2007 eligible patients, 39.9% endorsed ≥ 2 SUD symptoms (74.3% in the clinically-recognized OUD subsample and 13.1% in LTOT subsample). IRT indicated that a unidimensional model for the 11 checklist items had excellent fit (comparative fit index = 0.998) with high item-level discrimination parameters for the overall sample and both subsamples. DIF across age, race and ethnicity, and treatment was observed for one item each, but had minimal impact on expected number of criteria (0-11) patients endorse., Conclusions: The Substance Use Symptom Checklist measured SUD symptoms consistent with DSM-5 conceptualization (scaled, unidimensional) in patients with clinically-recognized OUD and LTOT and had similar measurement properties across demographic subgroups. The Checklist may support symptom assessment in patients with OUD and diagnosis in patients with LTOT., (© 2024. The Author(s), under exclusive licence to Society of General Internal Medicine.)

Background: Diagnosis of alcohol use disorder (AUD) in primary care is critical for increasing access to alcohol treatment. However, AUD is underdiagnosed and may be inequitably diagnosed due to societal structures that determine access to resources (e.g., structural racism that limits opportunities for some groups and influences interpersonal interactions in and beyond health care). This study described patterns of provider-documented AUD in primary care across intersections of race, ethnicity, sex, and community-level socioeconomic status (SES)., Methods: This cross-sectional study used EHR data from a regional healthcare system with 35 primary care clinics that included adult patients who completed alcohol screenings between 3/1/2015 and 9/30/2020. The prevalence of provider-documented AUD in primary care based on International Classification of Diseases-9 (ICD-9) and ICD-10 diagnoses was compared across intersections of race, ethnicity, sex, and community-level SES., Results: Among 439,375 patients, 6.6% were Latine, 11.0% Asian, 5.4% Black, 1.3% Native Hawaiian/Pacific Islander (NH/PI), 1.5% American Indian/Alaska Native (AI/AN), and 74.2% White, and 58.3% women. The overall prevalence of provider-documented AUD was 1.0% and varied across intersecting identities. Among women, the prevalence was highest for AI/AN women with middle SES, 1.5% (95% CI 1.0-2.3), and lowest for Asian women with middle SES, 0.1% (95% CI 0.1-0.2). Among men, the prevalence was highest for AI/AN men with high and middle SES, 2.0% (95% CI 1.1-3.4) and 2.0% (95% CI 1.2-3.2), respectively, and lowest for Asian men with high SES, 0.5% (95% CI 0.3-0.7). Black and Latine patients tended to have a lower prevalence of AUD than White patients, across all intersections of sex and SES except for Black women with high SES. There were no consistent patterns of the prevalence of AUD diagnosis that emerged across SES., Conclusion: The prevalence of provider-documented AUD in primary care was highest in AI/AN men and women and lowest in Asian men and women. Findings of lower prevalence of provider-documented AUD in Black and Hispanic than White patients across most intersections of sex and SES differed from prior studies. Findings may suggest that differences in access to resources, which vary in effects across these identity characteristics and lived experiences, influence the diagnosis of AUD in clinical care., (© 2024. The Author(s).)

Research designed to establish alcohol and other drug (AOD) mechanisms of behavioral change (MOBC) has centered on what variables mediate the relation between AOD treatment and outcomes. The purpose of this paper was to review this research evidence to identify empirically supported mediators of alcohol and other drug use and related outcomes and then to evaluate their potential as being AOD treatment MOBC. The first phase was a systematic review of reviews (2008-2023) to identify the variables with the strongest empirical support as mediators of AOD treatment effects. Eligible reviews focused on AOD treatment modalities, included empirically tested mediators, and targeted adult samples. The second phase was a systematic review of empirical studies (1990-2023) testing the hypothesis that variables identified in phase one were AOD treatment mediators/mechanisms and then evaluating each eligible stage two study according to the Kazdin and Nock (Journal of Child Psychology and Psychiatry, 44, 1116) criteria. Eligible articles included empirical studies with adult samples attending AOD treatment and empirically tested one of the three treatment mechanisms as a mediator of an AOD-related outcome. Databases were searched in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. This systematic review was not preregistered. The first review of 11 eligible review articles identified self-efficacy, social support, and craving as having the strongest empirical support. The second review captured 48 individual studies. An evaluation of each of these studies by the Kazdin and Nock criteria suggested that they likely are MOBC and therefore are ready for implementation. The implementation of self-efficacy, social support, and craving into clinical practice and training is warranted. Six directions for future research to solidify and generalize empirical support for the case that self-efficacy, social support, and craving are MOBC are presented, as are five implications for clinical practice and training., (© 2024 The Author(s). Alcohol, Clinical and Experimental Research published by Wiley Periodicals LLC on behalf of Research Society on Alcohol.)

Background: The National Institute on Alcohol Abuse and Alcoholism (NIAAA) recommends the paper-based or computerized Alcohol Symptom Checklist to assess alcohol use disorder (AUD) symptoms in routine care when patients report high-risk drinking. However, it is unknown whether Alcohol Symptom Checklist response characteristics differ when it is administered online (eg, remotely via an online electronic health record [EHR] patient portal before an appointment) versus in clinic (eg, on paper after appointment check-in)., Objective: This study evaluated the psychometric performance of the Alcohol Symptom Checklist when completed online versus in clinic during routine clinical care., Methods: This cross-sectional, psychometric study obtained EHR data from the Alcohol Symptom Checklist completed by adult patients from an integrated health system in Washington state. The sample included patients who had a primary care visit in 2021 at 1 of 32 primary care practices, were due for annual behavioral health screening, and reported high-risk drinking on the behavioral health screen (Alcohol Use Disorder Identification Test-Consumption score ≥7). After screening, patients with high-risk drinking were typically asked to complete the Alcohol Symptom Checklist-an 11-item questionnaire on which patients self-report whether they had experienced each of the 11 AUD criteria listed in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) over a past-year timeframe. Patients could complete the Alcohol Symptom Checklist online (eg, on a computer, smartphone, or tablet from any location) or in clinic (eg, on paper as part of the rooming process at clinical appointments). We examined sample and measurement characteristics and conducted differential item functioning analyses using item response theory to examine measurement consistency across these 2 assessment modalities., Results: Among 3243 patients meeting eligibility criteria for this secondary analysis (2313/3243, 71% male; 2271/3243, 70% White; and 2014/3243, 62% non-Hispanic), 1640 (51%) completed the Alcohol Symptom Checklist online while 1603 (49%) completed it in clinic. Approximately 46% (752/1640) and 48% (764/1603) reported ≥2 AUD criteria (the threshold for AUD diagnosis) online and in clinic (P=.37), respectively. A small degree of differential item functioning was observed for 4 of 11 items. This differential item functioning produced only minimal impact on total scores used clinically to assess AUD severity, affecting total criteria count by a maximum of 0.13 criteria (on a scale ranging from 0 to 11)., Conclusions: Completing the Alcohol Symptom Checklist online, typically prior to patient check-in, performed similarly to an in-clinic modality typically administered on paper by a medical assistant at the time of the appointment. Findings have implications for using online AUD symptom assessments to streamline workflows, reduce staff burden, reduce stigma, and potentially assess patients who do not receive in-person care. Whether modality of DSM-5 assessment of AUD differentially impacts treatment is unknown., (©Theresa E Matson, Amy K Lee, Malia Oliver, Katharine A Bradley, Kevin A Hallgren. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 22.07.2024.)

Objectives: This study aimed to evaluate the validity of World Health Organization (WHO) risk drinking level reductions as meaningful endpoints for clinical practice and research. This study examined whether such reductions were associated with a lower likelihood of a current alcohol use disorder (AUD) diagnosis and fewer AUD criteria., Methods: We conducted a secondary data analysis to address these objectives using data from a multisite randomized controlled trial of gabapentin enacarbil extended release in treating moderate to severe AUD among adults (N = 346). Participants received gabapentin enacarbil extended release or placebo for 6 months. The timeline follow-back was used to assess WHO risk drinking level reductions, and the Mini-International Neuropsychiatric Interview was used to assess Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) AUD diagnosis and criteria at baseline (past year) and end of treatment (past month)., Results: Most participants (80.1%) achieved at least a 1-level reduction in the WHO risk drinking levels from baseline to end of treatment, and nearly half of participants (49.8%) achieved at least a 2-level reduction. At least a 1-level reduction or at least a 2-level reduction in WHO risk drinking level predicted lower odds of an active AUD diagnosis (1-level: odds ratio, 0.74 [95% confidence interval (CI), 0.66-0.84]; 2-level: odds ratio, 0.71 [95% CI, 0.64-0.79]) and fewer AUD criteria (1-level: B , -1.66 [95% CI, -2.35 to -0.98]; 2-level: B , -1.76 [95% CI, -2.31 to -1.21]) at end of treatment., Conclusions: World Health Organization risk drinking level reductions correlate with Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) AUD diagnosis and criteria, providing further evidence for their use as endpoints in alcohol intervention trials, which has potential implications for broadening the base of AUD treatment., (Copyright © 2024 American Society of Addiction Medicine.)

Aims: Among individuals with alcohol use disorder (AUD), sleep disturbances are pervasive and contribute to the etiology and maintenance of AUD. However, despite increased attention toward the relationship between alcohol use and sleep, limited empirical research has systematically examined whether reductions in drinking during treatment for AUD are associated with improvements in sleep problems., Methods: We used data from a multisite, randomized, controlled trial that compared 6 months of treatment with gabapentin enacarbil extended-release with placebo for adults with moderate-to-severe AUD (N = 346). The Timeline Follow-back was used to assess WHO risk drinking level reductions and the Pittsburgh Sleep Quality Index was used to assess sleep quality over the prior month at baseline and the end of treatment., Results: Sleep problem scores in the active medication and placebo groups improved equally. Fewer sleep problems were noted among individuals who achieved at least a 1-level reduction (B = -0.99, 95% confidence interval (CI) [-1.77, -0.20], P = .014) or at least a 2-level reduction (B = -0.80, 95% CI [-1.47, -0.14], P = .018) in WHO risk drinking levels at the end of treatment. Reductions in drinking, with abstainers excluded from the analysis, also predicted fewer sleep problems at the end of treatment (1-level: B = -1.01, 95% CI [-1.83, -0.20], P = .015; 2-level: B = -0.90, 95% CI [-1.59, -0.22], P = .010)., Conclusions: Drinking reductions, including those short of abstinence, are associated with improvements in sleep problems during treatment for AUD. Additional assessment of the causal relationships between harm-reduction approaches to AUD and improvements in sleep is warranted., (© The Author(s) 2024. Medical Council on Alcohol and Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Introduction: Substance use disorders (SUDs) are underdiagnosed in healthcare settings. The Substance Use Symptom Checklist (SUSC) is a practical, patient-report questionnaire that has been used to assess SUD symptoms based on Diagnostic and Statistical Manual of Mental Disorders-5th edition (DSM-5) criteria. This study evaluates the test-retest reliability of SUSCs completed in primary and mental health care settings., Methods: We identified 1194 patients who completed two SUSCs 1-21 days apart as part of routine care after reporting daily cannabis use and/or any past-year other drug use on behavioral health screens. Test-retest reliability of SUSC scores was evaluated within the full sample, subsamples who completed both checklists in primary care (n=451) or mental health clinics (n=512) where SUSC implementation differed, and subgroups defined by sex, insurance status, age, and substance use reported on behavioral health screens., Results: In the full sample, test-retest reliability was high for indices reflecting the number of SUD symptoms endorsed (ICC=0.75, 95% CI:0.72-0.77) and DSM-5 SUD severity (kappa=0.72, 95% CI:0.69-0.75). These reliability estimates were higher in primary care (ICC=0.81, 95% CI:0.77-0.84; kappa=0.79, 95% CI:0.75-0.82, respectively) than in mental health clinics (ICC=0.74, 95% CI:0.70-0.78; kappa=0.73, 95% CI:0.68-0.77). Reliability differed by age and substance use reported on behavioral health screens, but not by sex or insurance status., Conclusions: The SUSC has good-to-excellent test-retest reliability when completed as part of routine primary or mental health care. Symptom checklists can reliably measure symptoms consistent with DSM-5 SUD criteria, which may aid SUD-related care in primary care and mental health settings., Competing Interests: Declaration of Competing Interest All authors declare no conflicts of interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Abstinence has historically been considered the preferred goal of alcohol use disorder (AUD) treatment. However, most individuals with AUD do not want to abstain and many are able to reduce their drinking successfully. Craving is often a target of pharmacological and behavioral interventions for AUD, and reductions in craving may signal recovery. Whether reductions in drinking during AUD treatment are associated with reductions in craving has not been well examined., Methods: We conducted secondary analyses of data from three AUD clinical trials (N's= 1327, 346, and 200). Drinking reductions from baseline to the end of treatment were measured as changes in World Health Organization (WHO) risk drinking levels; alcohol craving was measured using validated self-report measures. Regression analyses tested whether drinking reductions were associated with end-of-treatment craving reductions; moderation analyses tested whether associations between drinking reduction and end-of-treatment craving differed across AUD severity., Results: Reductions of at least 1 or at least 2 WHO risk drinking levels were associated with lower craving (all p's < 0.05). Results were substantively similar after removing abstainers at the end-of-treatment. Associations between drinking reductions and craving were generally not moderated by AUD severity., Conclusions: Individuals with WHO risk drinking level reductions reported significantly lower craving, as compared to those who did not achieve meaningful reductions in drinking. The results demonstrate the utility of WHO risk drinking levels as AUD clinical trial endpoints and provide evidence that drinking reductions mitigate craving., (© 2023 Research Society on Alcohol.)

Background: The Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) is a three-item screening measure of unhealthy alcohol use that is widely used in healthcare settings. Evidence shows high test-retest reliability of the AUDIT-C in research samples, but most studies had limited external validity and used small samples that could not be used to evaluate reliability across demographic subgroups and/or screening modalities. This study evaluates the test-retest reliability of the AUDIT-C completed in routine care in a large primary care sample, including across demographic subgroups defined by age, sex, race, ethnicity, and screening modality (i.e., completed in-clinic or online)., Methods: We used electronic health record (EHR) data from Kaiser Permanente Washington. The sample included 18,491 adult primary care patients who completed two AUDIT-C screens 1-21 days apart as part of routine care in 2021. Test-retest reliability was evaluated for AUDIT-C total scores (0-12) and for a binary measure indicating unhealthy alcohol use (scores ≥3 women, ≥4 men). Using previously established cutoffs, we interpreted reliability coefficients >0.75 as indicating "excellent" reliability., Results: AUDIT-C screens completed in routine care and documented in EHRs had excellent test-retest reliability for total scores (ICC = 0.87, 95% CI: 0.87-0.87) and the binary indicator of unhealthy alcohol use (κ = 0.79, 95% CI: 0.78-0.80). Reliability coefficients were good to excellent across all demographic groups and for in-clinic and online modalities. Higher reliability was seen when both screens were completed through online patient portals (ICC = 0.93, 95% CI: 0.93-0.93) versus in-clinic (ICC = 0.81, 95% CI: 0.79-0.82) or when one screen was completed using each modality (ICC = 0.83, 95% CI: 0.82-0.83). Lower reliability was seen in American Indian/Alaska Native (ICC = 0.82, 95% CI: 0.75-0.87) and multiracial individuals (ICC = 0.82, 95% 0.80-0.84)., Conclusions: In real-world routine care conditions, AUDIT-C screens have excellent test-retest reliability across demographic subgroups and modalities (online and in-clinic). Future research should examine why reliability varies slightly across modalities and demographic subgroups., (© 2023 Research Society on Alcohol.)

Introduction: Co-occurring substance use disorders (SUDs) are common among people with opioid use disorder (OUD) and known to hinder receipt of medications for OUD (MOUD). It is important to understand how MOUD care implemented outside of SUD specialty settings impacts access for patients with co-occurring SUDs. The Veterans Health Administration's (VA) Stepped Care for Opioid Use Disorder Train the Trainer (SCOUTT) initiative was implemented in primary care, mental health, and pain clinics in 18 VA facilities, and was found to increase MOUD receipt. This study assessed the SCOUTT initiative's impact among patients with and without co-occurring SUDs., Methods: This study used a controlled interrupted time series design. We extracted electronic health record data for patients with OUD with visits in SCOUTT intervention or matched comparison clinics during the post-implementation year (9/1/2018-8/31/2019). We examined the monthly proportion of patients who received MOUD in SCOUTT intervention or comparison clinics (primary care, mental health, and pain clinics), or in a VA SUD specialty clinic (where patients may have been referred), during the pre- and post-implementation years. Segmented logistic regression models estimated pre-post changes in outcomes (immediate level change from the final month of the pre-implementation period to the first month of the post-implementation period, change in trend/slope) in intervention vs. comparison facilities, adjusting for patient characteristics and pre-implementation trends. We stratified analyses by the presence of co-occurring SUDs., Results: Among patients without co-occurring SUDs, the pre-post trend/slope change in MOUD received in SCOUTT intervention or comparison clinics was greater in intervention vs. comparison facilities (adjusted odds ratio [aOR]: 1.06, 95% confidence interval [CI]: 1.02-1.10), and the immediate increase in MOUD received in SUD clinics was greater in intervention vs. comparison facilities (aOR: 1.12, 95% CI: 1.02-1.22). These changes did not significantly differ in intervention vs. comparison facilities among patients with co-occurring SUDs., Conclusions: The SCOUTT initiative may have increased MOUD receipt primarily among patients without co-occurring SUDs. Focusing on increasing MOUD receipt for patients with co-occurring SUDs may improve the overall effectiveness of MOUD implementation efforts., Competing Interests: Declaration of competing interest None., (Published by Elsevier Inc.)

Background: Brief cannabis screening followed by standardized assessment of symptoms may support diagnosis and treatment of cannabis use disorder (CUD). This study tested whether the probability of a medical provider diagnosing and treating CUD increased with the number of substance use disorder (SUD) symptoms documented in patients' EHRs., Methods: This observational study used EHR and claims data from an integrated healthcare system. Adult patients were included who reported daily cannabis use and completed the Substance Use Symptom Checklist, a scaled measure of DSM-5 SUD symptoms (0-11), during routine care 3/1/2015-3/1/2021. Logistic regression estimated associations between SUD symptom counts and: 1) CUD diagnosis; 2) CUD treatment initiation; and 3) CUD treatment engagement, defined based on Healthcare Effectiveness Data and Information Set (HEDIS) ICD-codes and timelines. We tested moderation across age, gender, race, and ethnicity., Results: Patients (N=13,947) were predominantly middle-age, male, White, and non-Hispanic. Among patients reporting daily cannabis use without other drug use (N=12,568), the probability of CUD diagnosis, treatment initiation, and engagement increased with each 1-unit increase in Symptom Checklist score (p's<0.001). However, probabilities of diagnosis, treatment, and engagement were low, even among those reporting ≥2 symptoms consistent with SUD: 14.0% diagnosed (95% CI: 11.7-21.6), 16.6% initiated treatment among diagnosed (11.7-21.6), and 24.3% engaged in treatment among initiated (15.8-32.7). Only gender moderated associations between Symptom Checklist and diagnosis (p=0.047) and treatment initiation (p=0.012). Findings were similar for patients reporting daily cannabis use with other drug use (N=1379)., Conclusion: Despite documented symptoms, CUD was underdiagnosed and undertreated in medical settings., Competing Interests: Declaration of Competing Interest Matson reports support from Veteran Affairs Puget Sound Health Services Research & Development outside the submitted work. Remaining authors have no affiliation with or financial involvement in any organization or entity with a direct financial interest in the subject matter or materials discussed in the manuscript., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Background and Aims: The Opioid Use Disorder (OUD) Cascade of Care is a public health model that has been used to measure population-level OUD risk, treatment engagement, retention, service and outcome indicators. However, no studies have examined its relevance for American Indian and Alaska Native (AI/AN) communities. Thus, we aimed to understand (1) the utility of existing stages and (2) the relative 'fit' of the OUD Cascade of Care from a tribal perspective., Design, Setting, Participants and Measurements: Qualitative analysis of in-depth interviews with 20 individuals who were knowledgeable regarding the treatment of OUD in an Anishinaabe tribal setting in Minnesota, USA. Community member roles included clinicians, peer support specialists and cultural practitioners, among others. Thematic analysis was used to analyze the data., Findings: Participants identified the key transition points of prevention, assessment, inpatient/outpatient pathways and recovery as relevant to their community. They re-imagined an Aanji'bide (Changing our Paths) model of opioid recovery and change that was non-linear; included developmental stage and individual pathways; and demonstrated resilience through connection to culture/spirituality, community and others., Conclusions: Community members living/working in a rural tribal nation in Minnesota, USA identified non-linearity and cultural connection as key elements to include in an Anishinaabe-centered model of opioid recovery and change., (© 2023 The Authors. Addiction published by John Wiley & Sons Ltd on behalf of Society for the Study of Addiction.)

Background: Methadone, a cornerstone of opioid use disorder treatments for many decades, is an essential tool for combatting the opioid epidemic. However, requirements for observing methadone dosing in person through direct observed therapy (DOT) impose significant barriers for many patients. Digital technology can facilitate remote DOT, which could reduce barriers to methadone treatment. Currently, there are limited data on the usability of such technology among patients and counselors in methadone treatment settings., Objective: The primary objective of this study was to assess the workload, usability, and engagement of a video-based DOT mobile app for patients with opioid use disorder receiving methadone treatment. The secondary objective was to assess the workload, usability, and engagement of the provider-facing app portal used by counselors., Methods: Patients (n=12) and counselors (n=3) who previously tried video DOT for methadone through a smartphone app in an opioid treatment program participated in usability testing sessions. Participants completed essential tasks for video DOT, then provided ratings of workload (NASA Task Load Index), usability (modified System Usability Scale), and engagement (modified Engagement Scale) with the core features of the video DOT program., Results: Patients and counselors reported low mental, physical, and temporal demands, successful performance, low effort, and low frustration associated with activities. Patients reported high usability (mean 85, SD 9.5) and engagement (mean 3.8, SD 1.1); counselors reported moderate usability (mean 43.3, SD 17.7) and engagement (mean 2.81, SD 0.63)., Conclusions: A mobile health app that facilitates video-based DOT for methadone required a low workload for patients and counselors and was highly usable for patients in an opioid treatment program; however, there are opportunities to improve usability and engagement for the counselor-facing portal., (©Bulat Idrisov, Kevin A Hallgren, Alyssa Michaels, Sean Soth, James Darnton, Paul Grekin, Steve Woolworth, Andrew J Saxon, Judith I Tsui. Originally published in JMIR Human Factors (https://humanfactors.jmir.org), 13.07.2023.)

Background: In the United States, methamphetamine-related overdoses have tripled from 2015 to 2020 and continue to rise. However, efficacious treatments such as contingency management (CM) are often unavailable in health systems., Objective: We conducted a single-arm pilot study to evaluate the feasibility, engagement, and usability of a fully remotely delivered mobile health CM program offered to adult outpatients who used methamphetamine and were receiving health care within a large university health system., Methods: Participants were referred by primary care or behavioral health clinicians between September 2021 and July 2022. Eligibility criteria screening was conducted by telephone and included self-reported methamphetamine use on ≥5 out of the past 30 days and a goal of reducing or abstaining from methamphetamine use. Eligible participants who agreed to take part then completed an initial welcome phase that included 2 videoconference calls to register for and learn about the CM program and 2 "practice" saliva-based substance tests prompted by a smartphone app. Participants who completed these welcome phase activities could then receive the remotely delivered CM intervention for 12 consecutive weeks. The intervention included approximately 24 randomly scheduled smartphone alerts requesting a video recording of themselves taking a saliva-based substance test to verify recent methamphetamine abstinence, 12 weekly calls with a CM guide, 35 self-paced cognitive behavioral therapy modules, and multiple surveys. Financial incentives were disbursed via reloadable debit cards. An intervention usability questionnaire was completed at the midpoint., Results: Overall, 37 patients completed telephone screenings, with 28 (76%) meeting the eligibility criteria and consenting to participate. Most participants who completed a baseline questionnaire (21/24, 88%) self-reported symptoms consistent with severe methamphetamine use disorder, and most had other co-occurring non-methamphetamine substance use disorders (22/28, 79%) and co-occurring mental health disorders (25/28, 89%) according to existing electronic health records. Overall, 54% (15/28) of participants successfully completed the welcome phase and were able to receive the CM intervention. Among these participants, engagement with substance testing, calls with CM guides, and cognitive behavioral therapy modules varied. Rates of verified methamphetamine abstinence in substance testing were generally low but varied considerably across participants. Participants reported positive opinions about the intervention's ease of use and satisfaction with the intervention., Conclusions: Fully remote CM can be feasibly delivered within health care settings lacking existing CM programs. Although remote delivery may help reduce barriers to treatment access, many patients who use methamphetamine may struggle to engage with initial onboarding. High rates of co-occurring psychiatric conditions in the patient population may also contribute to uptake and engagement challenges. Future efforts could leverage greater human-to-human connection, more streamlined onboarding procedures, larger incentives, longer durations, and the incentivization of non-abstinence-based recovery goals to increase uptake and engagement with fully remote mobile health-based CM., (©Kevin A Hallgren, Mark H Duncan, Matthew D Iles-Shih, Eliza B Cohn, Connor J McCabe, Yanni M Chang, Andrew J Saxon. Originally published in JMIR Formative Research (https://formative.jmir.org), 06.07.2023.)

Background: The Alcohol Use Disorders Identification Test-Consumption version (AUDIT-C) has been robustly validated as a point-in-time screen for unhealthy alcohol use, but less is known about the significance of changes in AUDIT-C scores from routine screenings over time. Unhealthy alcohol use and depression commonly co-occur, and changes in drinking often co-occur with changes in depression symptoms. We assess the associations between changes in AUDIT-C scores and changes in depression symptoms reported on brief screens completed in routine care., Methods: The study sample included 198,335 primary care patients who completed two AUDIT-C screens 11 to 24 months apart and the Patient Health Questionnaire-2 (PHQ-2) depression screen on the same day as each AUDIT-C. Both screening measures were completed as part of routine care within a large health system in Washington state. AUDIT-C scores were categorized to reflect five drinking levels at both time points, resulting in 25 subgroups with different change patterns. For each of the 25 subgroups, within-group changes in the prevalence of positive PHQ-2 depression screens were characterized using risk ratios (RRs) and McNemar's tests., Results: Patient subgroups with increases in AUDIT-C risk categories generally experienced increases in the prevalence of positive depression screens (RRs ranging from 0.95 to 2.00). Patient subgroups with decreases in AUDIT-C risk categories generally experienced decreases in the prevalence of positive depression screens (RRs ranging from 0.52 to 1.01). Patient subgroups that did not have changes in AUDIT-C risk categories experienced little or no change in the prevalence of positive depression screens (RRs ranging from 0.98 to 1.15)., Conclusions: As hypothesized, changes in alcohol consumption reported on AUDIT-C screens completed in routine care were associated with changes in depression screening results. Results support the validity and clinical utility of monitoring changes in AUDIT-C scores over time as a meaningful measure of changes in drinking., (© 2023 Research Society on Alcohol.)

Background: Most people with opioid use disorder (OUD) have co-occurring substance use, which is associated with lower receipt of OUD medications (MOUD). Expanding MOUD provision and care linkage outside of substance use disorder (SUD) specialty settings is a key strategy to increase access. Therefore, it is important to understand how MOUD providers in these settings approach care for patients with co-occurring substance use. This qualitative study of Veterans Health Administration (VA) clinicians providing buprenorphine care in primary care, mental health, and pain settings aimed to understand (1) their approach to addressing OUD in patients with co-occurring substance use, (2) perspectives on barriers/facilitators to MOUD receipt for this population, and (3) support needed to increase MOUD receipt for this population., Methods: We interviewed a purposive sample of 27 clinicians (12 primary care, 7 mental health, 4 pain, 4 pharmacists) in the VA northwest network. The interview guide assessed domains of the Tailored Implementation for Chronic Diseases Checklist. Interviews were transcribed and qualitatively analyzed using inductive content analysis., Results: Participants reported varied approaches to identifying co-occurring substance use and addressing OUD in this patient population. Although they reported that this topic was not clearly addressed in clinical guidelines or training, participants generally felt that patients with co-occurring substance use should receive MOUD. Some viewed their primary role as providing this care, others as facilitating linkage to OUD care in SUD specialty settings. Participants reported multiple barriers and facilitators to providing buprenorphine care to patients with co-occurring substance use and linking them to SUD specialty care, including provider, patient, organizational, and external factors., Conclusions: Efforts are needed to support clinicians outside of SUD specialty settings in providing buprenorphine care to patients with co-occurring substance use. These could include clearer guidelines and policies, more specific training, and increased care integration or cross-disciplinary collaboration. Simultaneously, efforts are needed to improve linkage to specialty SUD care for patients who would benefit from and are willing to receive this care, which could include increased service availability and improved referral/hand-off processes. These efforts may increase MOUD receipt and improve OUD care quality for patients with co-occurring substance use., (© 2023. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Objective: The addiction cycle has been proposed as a framework for understanding the progression of alcohol use disorder (AUD) in terms of psychological and biological domains, including reward drinking/incentive salience, relief drinking/negative emotionality, and loss of control/executive functioning impairment. To have utility in clinical practice, self-report measures of these domains that are applicable across sociodemographic groups and associated with clinical outcomes are needed. This study sought to validate domains from self-report measures and to test whether domains are measurement invariant across sociodemographic groups and associated with treatment outcomes., Method: Secondary analysis of individuals with AUD ( n = 3,092) who participated in two alcohol clinical trials, Project Matching Alcohol Treatment to Client Heterogeneity (MATCH) and COMBINE. Factor analytic methods were used to derive addiction cycle domains at baseline. These domains were then examined as predictors of outcomes., Results: Fifteen self-report items were used as indicators of the addiction cycle domains, with sociodemographic differences in measurement by sex, age, race, education, and AUD symptoms. Relief/negative emotionality and reward/incentive salience were significantly associated with outcomes at 1 and 3 years following treatment, and executive functioning also predicted nonabstinent recovery at 3 years., Conclusions: The results support the utility of domains relevant to the addiction cycle in predicting AUD treatment outcomes and recovery among individuals who sought treatment for AUD. The addiction cycle domains were more strongly associated with outcomes than other measures clinicians might use to predict outcomes (e.g., AUD symptoms). Future research should continue to develop and refine the items and test whether the addiction cycle domains can inform treatment planning. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Objectives: Among people with opioid use disorder (OUD), having a co-occurring substance use disorder (SUD) is associated with lower likelihood of receiving OUD treatment medications (MOUD). However, it is unclear how distinct co-occurring SUDs are associated with MOUD receipt. This study examined associations of distinct co-occurring SUDs with initiation and continuation of MOUD among patients with OUD in the national Veterans Health Administration (VA)., Methods: Electronic health record data were extracted for outpatients with OUD who received care August 1, 2016, to July 31, 2017. Analyses were conducted separately among patients without and with prior-year MOUD receipt to examine initiation and continuation, respectively. SUDs were measured using diagnostic codes; MOUD receipt was measured using prescription fills/clinic visits. Adjusted regression models estimated likelihood of following-year MOUD receipt for patients with each co-occurring SUD relative to those without., Results: Among 23,990 patients without prior-year MOUD receipt, 12% initiated in the following year. Alcohol use disorder (adjusted incidence rate ratio [aIRR], 0.80; 95% confidence interval [CI], 0.72-0.90) and cannabis use disorder (aIRR, 0.78; 95% CI, 0.70-0.87) were negatively associated with initiation. Among 11,854 patients with prior-year MOUD receipt, 83% continued in the following year. Alcohol use disorder (aIRR, 0.94; 95% CI, 0.91-0.97), amphetamine/other stimulant use disorder (aIRR, 0.94; 95% CI, 0.90-0.99), and cannabis use disorder (aIRR, 0.95; 95% CI, 0.93-0.98) were negatively associated with continuation., Conclusions: In this study of national VA outpatients with OUD, those with certain co-occurring SUDs were less likely to initiate or continue MOUD. Further research is needed to identify barriers related to specific co-occurring SUDs., Competing Interests: The authors report no conflicts of interest., (Copyright © 2022 American Society of Addiction Medicine.)

Importance: Substance use disorders (SUDs) are underrecognized in primary care, where structured clinical interviews are often infeasible. A brief, standardized substance use symptom checklist could help clinicians assess SUD., Objective: To evaluate the psychometric properties of the Substance Use Symptom Checklist (hereafter symptom checklist) used in primary care among patients reporting daily cannabis use and/or other drug use as part of population-based screening and assessment., Design, Setting, and Participants: This cross-sectional study was conducted among adult primary care patients who completed the symptom checklist during routine care between March 1, 2015, and March 1, 2020, at an integrated health care system. Data analysis was conducted from June 1, 2021, to May 1, 2022., Main Outcomes and Measures: The symptom checklist included 11 items corresponding to SUD criteria in the Diagnostic and Statistical Manual for Mental Disorders (Fifth Edition) (DSM-5). Item response theory (IRT) analyses tested whether the symptom checklist was unidimensional and reflected a continuum of SUD severity and evaluated item characteristics (discrimination and severity). Differential item functioning analyses examined whether the symptom checklist performed similarly across age, sex, race, and ethnicity. Analyses were stratified by cannabis and/or other drug use., Results: A total of 23 304 screens were included (mean [SD] age, 38.2 [5.6] years; 12 554 [53.9%] male patients; 17 439 [78.8%] White patients; 20 393 [87.5%] non-Hispanic patients). Overall, 16 140 patients reported daily cannabis use only, 4791 patients reported other drug use only, and 2373 patients reported both daily cannabis and other drug use. Among patients with daily cannabis use only, other drug use only, or both daily cannabis and other drug use, 4242 (26.3%), 1446 (30.2%), and 1229 (51.8%), respectively, endorsed 2 or more items on the symptom checklist, consistent with DSM-5 SUD. For all cannabis and drug subsamples, IRT models supported the unidimensionality of the symptom checklist, and all items discriminated between higher and lower levels of SUD severity. Differential item functioning was observed for some items across sociodemographic subgroups but did not result in meaningful change (<1 point difference) in the overall score (0-11)., Conclusions and Relevance: In this cross-sectional study, a symptom checklist, administered to primary care patients who reported daily cannabis and/or other drug use during routine screening, discriminated SUD severity as expected and performed well across subgroups. Findings support the clinical utility of the symptom checklist for standardized and more complete SUD symptom assessment to help clinicians make diagnostic and treatment decisions in primary care.

Background: Screening for unhealthy alcohol use in primary care may help identify patients at risk for negative health outcomes., Aims: This study examined the associations between 1) screening with the AUDIT-C (alcohol consumption) and 2) an Alcohol Symptom Checklist (symptoms of alcohol use disorder) and subsequent-year hospitalizations., Methods: This retrospective cohort study was conducted in 29 primary care clinics in Washington State. Patients were screened in routine care (10/1/2016-2/1/2019) with the AUDIT-C (0-12) and administered the Alcohol Symptom Checklist (0-11) if they had AUDIT-C score ≥ 7. All-cause hospitalizations were measured within 1 year of the AUDIT-C and Alcohol Symptom Checklist. AUDIT-C and Alcohol Symptom Checklist scores were categorized based on previously used cut-points., Findings: Of 305,376 patients with AUDIT-Cs, 5.3% of patients were hospitalized in the following year. AUDIT-C scores had a J-shaped relationship with hospitalizations, with risk for all-cause hospitalizations higher for patients with the AUDIT-C scores 9-12 (12.1%; 95% CI: 10.6-13.7%, relative to a comparison group of those with AUDIT-C scores 1-2 (female)/1-3 (male) (3.7%; 95% CI: 3.6-3.8%), adjusted for socio-demographics. Patients with AUDIT-C ≥ 7 and Alcohol Symptom Checklist scores reflecting severe AUD were at increased risk of hospitalization (14.6%, 95% CI: 11.9-17.9%) relative to those with lower scores., Conclusions: Higher AUDIT-C scores were associated with higher incidence of hospitalizations except among people with low-level drinking. Among patients with AUDIT-C ≥ 7, the Alcohol Symptom Checklist identified patients at increased risk of hospitalization. This study helps demonstrate the potential clinical utility of the AUDIT-C and Alcohol Symptom Checklist., Competing Interests: Conflict of interest Nothing declared., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Background: Opioid use disorder (OUD) contributes to rising morbidity and mortality. Life-saving OUD treatments can be provided in primary care but most patients with OUD don't receive treatment. Comorbid depression and other conditions complicate OUD management, especially in primary care. The MI-CARE trial is a pragmatic randomized encouragement (Zelen) trial testing whether offering collaborative care (CC) to patients with OUD and clinically-significant depressive symptoms increases OUD medication treatment with buprenorphine and improves depression outcomes compared to usual care., Methods: Adult primary care patients with OUD and depressive symptoms (n ≥ 800) from two statewide health systems: Kaiser Permanente Washington and Indiana University Health are identified with computer algorithms from electronic Health record (EHR) data and automatically enrolled. A random sub-sample (50%) of eligible patients is offered the MI-CARE intervention: a 12-month nurse-driven CC intervention that includes motivational interviewing and behavioral activation. The remaining 50% of the study cohort comprise the usual care comparison group and is never contacted. The primary outcome is days of buprenorphine treatment provided during the intervention period. The powered secondary outcome is change in Patient Health Questionnaire (PHQ)-9 depression scores. Both outcomes are obtained from secondary electronic healthcare sources and compared in "intent-to-treat" analyses., Conclusion: MI-CARE addresses the need for rigorous encouragement trials to evaluate benefits of offering CC to generalizable samples of patients with OUD and mental health conditions identified from EHRs, as they would be in practice, and comparing outcomes to usual primary care. We describe the design and implementation of the trial, currently underway., Trial Registration: ClinicalTrials.gov Identifier: NCT05122676. Clinical trial registration date: November 17, 2021., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Background: Federal and state regulations require frequent direct observation of methadone ingestion at an Opioid Treatment Program (OTP)-a requirement that creates barriers to patient access. Video observed therapy (VOT) may help to address public health and safety concerns of providing take-home medications while simultaneously reducing barriers to treatment access and long-term retention. Evaluating user experiences with VOT is important for understanding the acceptability of this strategy., Methods: We conducted a qualitative evaluation of a clinical pilot program of VOT via smartphone that was rapidly implemented between April and August 2020 during the COVID-19 pandemic within three opioid treatment programs. In the program, selected patients submitted video recordings of themselves ingesting methadone take-home doses, which were asynchronously reviewed by their counselor. We recruited participating patients and counselors for semi-structured, individual interviews to explore their VOT experiences after program completion. Interviews were audio recorded and transcribed. Transcripts were analyzed using thematic analysis to identify key factors influencing acceptability and the effect of VOT on the treatment experience., Results: We interviewed 12 of the 60 patients who participated in the clinical pilot and 3 of the 5 counselors. Overall, patients were enthusiastic about VOT, noting multiple benefits over traditional treatment experiences, including avoiding frequent travel to the clinic. Some noted how this allowed them to better meet recovery goals by avoiding a potentially triggering environment. Most appreciated having increased time to devote to other life priorities, including maintaining consistent employment. Participants described how VOT increased their autonomy, allowed them to keep treatment private, and normalized treatment to align with other medications that do not require in-person dosing. Participants did not describe major usability issues or privacy concerns with submitting videos. Some participants reported feeling disconnected from counselors while others felt more connected. Counselors felt some discomfort in their new role confirming medication ingestion but saw VOT as a useful tool for select patients., Conclusions: VOT may be an acceptable tool to achieve equipoise between lowering barriers to treatment with methadone and protecting the health and safety of patients and their communities., (© 2023. The Author(s).)

Background: Alcohol use disorder (AUD) treatments, including medications, are increasingly offered via telehealth. Objective: This study characterizes 90-day treatment retention and changes in objectively measured blood alcohol concentration (BAC) in a large cohort receiving AUD telehealth. Methods: Patients received AUD treatment through Ria, a virtual (telehealth) program offering AUD treatment that is tailored to patient goals (e.g. abstinence or controlled drinking). Patients were encouraged to complete breathalyzer readings twice daily for measurement-based care. We characterized rates of 90-day treatment retention (i.e. completing a BAC reading or medical/coaching encounter on the 90 th day or later) and used growth curve analyses to model changes in daily estimated peak BAC over 90 days. Results: Of 4121 patients (51.5% women), 50.1% had 90-day treatment retention ( n = 2066, 52.2% women). Most patients received prescriptions for AUD medications (84.6%) and completed encounters with medical providers (86.7%) and coaches (86.1%). Patients with 90-day retention provided 184,817 BAC readings in the first 90 days. Growth curve analyses revealed significant reductions in daily estimated peak BAC ( p < .001) from a mean of 0.092 (day 1) to 0.038 (day 90). Similar magnitudes of BAC reduction were observed for men and women and for patients with abstinence and controlled drinking goals. Conclusion: Telehealth appears to be a viable approach to delivering AUD treatments in a manner that promotes drinking reductions. Telehealth approaches can yield reductions in objectively measured BAC, including for some patient subgroups that have historically faced greater stigma in AUD treatment settings, such as women and people with non-abstinence drinking goals.

Background : People with opioid use disorder (OUD) are increasingly started on buprenorphine in the hospital, yet many patients do not attend outpatient buprenorphine care after discharge. Peer providers, people in recovery themselves, are a growing part of addiction care. We examine whether patients who received a low-intensity, peer-delivered intervention during hospitalization had a greater rate of linking with outpatient buprenorphine care relative to those not seen by a peer. Methods : This was a retrospective cohort study of adults with OUD who were started on buprenorphine during hospitalization. The primary outcome was receipt of a buprenorphine prescription within 30 days of discharge. Secondary outcomes included attendance at a follow-up visit with a buprenorphine provider within 30 days and hospital readmission within 90 days. Modified Poisson regression analyses tested for differences in the rate ratios (RR) of each binary outcome for patients who were versus were not seen by a peer provider. Peer notes in the electronic health record were reviewed to characterize peer activities. Results : 111 patients met the study inclusion criteria, 31.5% of whom saw a peer provider. 55.0% received a buprenorphine prescription within 30 days of hospital discharge. Patients with versus without peer provider encounters did not significantly differ in the rates of receiving a buprenorphine prescription (RR = 1.06, 95% CI: 0.74-1.51), hospital readmission (RR = 1.45, 95% CI: 0.80-2.64), or attendance at a buprenorphine follow-up visit (RR = 1.03, 95% CI: 0.68-1.57). Peers most often listened to or shared experiences with patients (68.6% of encounters) and helped facilitate medical care (60.0% of encounters). Conclusions : There were no differences in multiple measures of buprenorphine follow-up between patients who received this low-intensity peer intervention and those who did not. There is need to investigate what elements of peer provider programs contribute to patient outcomes and what outcomes should be assessed when evaluating peer programs.

Background: Methadone is one of the most utilized treatments for opioid use disorder. However, requirements for observing methadone dosing can impose barriers to patients and increase risk for respiratory illness transmission (e.g., COVID-19). Video observation of methadone dosing at home could allow opioid treatment programs (OTPs) to offer more take-home doses while ensuring patient safety through remote observation of ingestion., Methods: Between April and August 2020, a clinical pilot program of video observation of methadone take-home dosing via smartphone was conducted within a multisite OTP agency. Participating patients completed a COVID-19 symptom screener and submitted video recordings of themselves ingesting all methadone take-home doses. Patients who followed these procedures for a two-week trial period could continue participating in the full pilot program and potentially receive more take-home doses. This retrospective observational study characterizes patient engagement and compares clinical outcomes with matched controls., Results: Of 44 patients who initiated the two-week trial, 33 (75 %) were successful and continued participating in the full pilot program. Twenty full pilot participants (61 %) received increased take-home doses. Full pilot participants had more days with observed dosing over a 60-day period than matched controls (mean = 53.2 vs. 16.6 days, respectively). Clinical outcomes were similar between pilot participants and matched controls., Conclusions: Video observation of methadone take-home dosing implemented during the COVID-19 pandemic was feasible. This model has the potential to enhance safety by increasing rates of observed methadone dosing and reducing infection risks and barriers associated with relying solely on face-to-face observation of methadone dosing., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Background: Research shows that improvements in coping strategies, abstinence self-efficacy, craving, and depression are potential mechanisms of behavioral change (MOBC) in treatments for substance use disorders (SUDs). However, little is known about how these insights regarding MOBC can be applied to SUD treatment settings. One way to facilitate MOBC-informed care in frontline settings could be to measure and monitor changes in MOBC throughout treatment using brief, frequent questionnaires that patients complete by using mobile technologies (eg, smartphones). The results derived from these questionnaires could potentially be used for clinical monitoring (ie, measurement-based care) to better understand whether individual patients are experiencing treatment-related improvements on key clinical targets., Objective: This study evaluated whether brief, weekly MOBC questionnaires completed by patients remotely can potentially provide clinically meaningful information about changes in MOBC in the context of real-world, community-based SUD treatment., Methods: A total of 30 patients (14/30, 47% female; 13/30, 43% racial or ethnic minority) in a community SUD treatment clinic participated in a pilot study where they were invited to complete brief, weekly questionnaires that assessed various MOBC, including coping strategies, abstinence self-efficacy, craving, depression, and therapeutic alliance. Questionnaires were typically completed remotely via smartphone for up to 6 months; 618 questionnaires were completed in total. Participants also completed longer, psychometrically validated measures of the same MOBC at baseline and 6-month research appointments. Statistical analyses tested whether brief, weekly, remotely completed MOBC questionnaires exhibited characteristics that would be desirable for real-world longitudinal clinical monitoring, including a tendency to detect within-person changes in MOBC over time; cross-sectional and longitudinal associations with longer, psychometrically validated measures completed at research appointments; and similar patterns of associations with 6-month percentage of days abstinent as longer, psychometrically validated MOBC measures completed at research appointments., Results: The results of this study indicated that the brief, weekly, remotely completed MOBC measures exhibited characteristics that are desirable for clinical monitoring, including a tendency to vary longitudinally (within patients over time) more often than measures of alcohol and drug consumption, generally having medium to large cross-sectional and longitudinal correlations with longer psychometrically validated measures of MOBC completed at research appointments, and generally having similar patterns of association with 6-month percentage of days abstinent from alcohol and drugs as longer psychometrically validated MOBC measures completed at research appointments., Conclusions: The results of this pilot study provide initial evidence that incorporating brief, weekly, and remotely completed MOBC questionnaires into community SUD treatment may be a viable approach for facilitating MOBC-informed care. Such questionnaires can potentially support measurement-based care by providing meaningful information about within-patient changes in clinical domains that are often directly targeted in SUD treatments and predict long-term substance use outcomes., (©Kevin A Hallgren. Originally published in JMIR Formative Research (https://formative.jmir.org), 07.11.2022.)

Importance: Cannabis use is prevalent and increasing, and frequent use intensifies the risk of cannabis use disorder (CUD). CUD is underrecognized in medical settings, but a validated single-item cannabis screen could increase recognition., Objective: To evaluate the Single-Item Screen-Cannabis (SIS-C), administered and documented in routine primary care, compared with a confidential reference standard measure of CUD., Design, Setting, and Participants: This diagnostic study included a sample of adult patients who completed routine cannabis screening between January 28 and September 12, 2019, and were randomly selected for a confidential survey about cannabis use. Random sampling was stratified by frequency of past-year use and race and ethnicity. The study was conducted at an integrated health system in Washington state, where adult cannabis use is legal. Data were analyzed from May 2021 to March 2022., Exposures: The SIS-C asks about frequency of past-year cannabis use with responses (none, less than monthly, monthly, weekly, daily or almost daily) documented in patients' medical records., Main Outcomes and Measures: The Diagnostic and Statistical Manual, Fifth Edition (DSM-5) Composite International Diagnostic Interview-Substance Abuse Module (CIDI-SAM) for past-year CUD was completed on a confidential survey and considered the reference standard. The SIS-C was compared with 2 or more criteria on the CIDI-SAM, consistent with CUD. All analyses were weighted, accounting for survey design and nonresponse, to obtain estimates representative of the health system primary care population., Results: Of 5000 sampled adult patients, 1688 responded to the cannabis survey (34% response rate). Patients were predominantly middle-aged (weighted mean [SD] age, 50.7 [18.1]), female or women (weighted proportion [SE], 55.9% [4.1]), non-Hispanic (weighted proportion [SE], 96.7% [1.0]), and White (weighted proportion [SE], 74.2% [3.7]). Approximately 6.6% of patients met criteria for past-year CUD. The SIS-C had an area under receiver operating characteristic curve of 0.89 (95% CI, 0.78-0.96) for identifying CUD. A threshold of less than monthly cannabis use balanced sensitivity (0.88) and specificity (0.83) for detecting CUD. In populations with a 6% prevalence of CUD, predictive values of a positive screen ranged from 17% to 34%, while predictive values of a negative screen ranged from 97% to 100%., Conclusions and Relevance: In this diagnostic study, the SIS-C had excellent performance characteristics in routine care as a screen for CUD. While high negative predictive values suggest that the SIS-C accurately identifies patients without CUD, low positive predictive values indicate a need for further diagnostic assessment following positive results when screening for CUD in primary care.

Background: Although alcohol use disorder can complicate depression management, there is no standard process for assessing AUD symptoms (i.e., AUD diagnostic criteria) in primary care for patients who screen positive for depression. This study characterizes the association between depressive symptoms and high-risk drinking reported by primary care patients on screening measures in routine care. Then, using data from a novel clinical program, this study characterizes the association between depressive symptoms and AUD symptoms reported by primary care patients with high-risk drinking via an Alcohol Symptom Checklist., Methods: In this cross-sectional study, electronic health record data were obtained from patients who visited 33 Kaiser Permanente Washington primary care clinics between 03/2018 and 02/2020 and completed depression (PHQ-2) and alcohol consumption (AUDIT-C) screening measures as part of routine care (N = 369,943). Patients who reported high-risk drinking (AUDIT-C scores 7-12) also completed an Alcohol Symptom Checklist where they reported the presence or absence of 11 AUD criteria as defined by the DSM-5 (N = 8,184). Generalized linear models estimated and compared the prevalence of high-risk drinking (AUDIT-C scores 7-12) and probable AUD (2-11 AUD symptoms on Alcohol Symptom Checklists) for patients with and without positive depression screens., Results: Patients who screened positive for depression had a 131% higher prevalence of high-risk drinking than those who screened negative (5.2% vs. 2.2%; p < 0.001). Among patients with high-risk drinking, positive depression screens were associated with a significantly higher prevalence of probable AUD (69.8% vs. 48.0%; p < 0.001), with large differences in the prevalence of probable AUD observed with increasing PHQ-2 scores (e.g., probable AUD prevalence of 37.6%, 55.3% and 65.2%, for PHQ-2 scores of 0, 1, and 2, respectively). Although the overall prevalence of high-risk drinking was higher for male patients, similar patterns of association between depression screens, high-risk drinking, and AUD symptoms were observed for male and female patients., Conclusions: Patients with positive depression screens are more likely to have high-risk drinking. Large percentages of patients with positive depression screens and high-risk drinking report symptoms consistent with AUD to healthcare providers when given the opportunity to do so using an Alcohol Symptom Checklist., (© 2022. The Author(s).)

Objective: People living with severe mental illness are at increased risk of medical comorbidity as well as poverty, food insecurity, and inadequate social support in managing their mental and physical health conditions. Lack of access to sufficient food negatively affects a person's ability to manage health conditions, in particular diabetes, which is twice as common among people with severe mental illness as the general population. This study aimed to explore associations among food insecurity, social support, and psychiatric symptoms among adults with severe mental illness and diabetes., Method: A cross-sectional survey was conducted between January and May 2021 among adults ( N = 156) with severe mental illness and type 2 diabetes who received primary care through a large academic health-care system (26% response rate). Valid and reliable questionnaires were implemented to measure food insecurity, social support, and mental health. Regression analysis was applied to examine the associations between food security status, social support, and mental health., Results: Food insecurity and social support are both correlated with psychiatric symptom severity. Specifically, support from family members has the largest protective role against food insecurity., Conclusions and Implications for Practice: This study found food insecurity is likely a critical issue to address whenever it is present in adults with severe mental illness (SMI) and type 2 diabetes. The presence of family support mitigates the need for addressing food insecurity. Practices and policies aimed at both addressing health inequities such as food insecurity and strengthening family support among people living with SMI and comorbid medical conditions are important adjuncts to self-management interventions. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Objective: Practitioner attitudes regarding the nature of psychosis and prospects of recovery are important targets in supervision and training of practitioners who work therapeutically with this population. The 19-item Psychosis Attitudes Scale (PAS) was developed as a way to monitor changes in psychosis-related attitudes among practitioners being trained in an Evidence Based Treatment (EBT) for psychosis. This study reports the development and underlying factor structure of the PAS., Method: Three hundred twenty-five community mental health clinicians completed the PAS following a Cognitive Behavioral Therapy for psychosis (CBTp) multiday workshop training. We conducted an exploratory factor analysis to investigate the underlying structure of the initial set of items., Results: Our analyses suggest that the PAS taps into four attitude groupings, which can be conceptualized as perceived confidence in working with individuals with psychosis (Factor 1), a recovery orientation (Factor 2), expectations of fulfillment (Factor 3), and a stress-vulnerability orientation (Factor 4)., Conclusions and Implications for Practice: Factors 1 and 3 appear to tap into general themes relevant to training practitioners in an evidence-based psychotherapeutic intervention for psychosis. Factors 2 and 4 are consistent with guiding principles of high-fidelity CBTp. At the individual level, practitioner attitudes have implications for training retention and treatment delivery. At the organizational level, the collective attitudes of staff in a given setting may serve as an indicator of readiness for EBT for psychosis implementation. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Background: Alcohol use disorder (AUD) is highly prevalent but underrecognized and undertreated in primary care settings. Alcohol Symptom Checklists can engage patients and providers in discussions of AUD-related care. However, the performance of Alcohol Symptom Checklists when they are used in routine care and documented in electronic health records (EHRs) remains unevaluated., Objective: To evaluate the psychometric performance of an Alcohol Symptom Checklist in routine primary care., Design: Cross-sectional study using item response theory (IRT) and differential item functioning analyses of measurement consistency across age, sex, race, and ethnicity., Patients: Patients seen in primary care in the Kaiser Permanente Washington Healthcare System who reported high-risk drinking on the Alcohol Use Disorder Identification Test Consumption screening measure (AUDIT-C ≥ 7) and subsequently completed an Alcohol Symptom Checklist between October 2015 and February 2020., Main Measure: Alcohol Symptom Checklists with 11 items assessing AUD criteria defined in the Diagnostic and Statistical Manual for Mental Disorders, 5th edition (DSM-5), completed by patients during routine medical care and documented in EHRs., Key Results: Among 11,464 patients who screened positive for high-risk drinking and completed an Alcohol Symptom Checklist (mean age 43.6 years, 30.5% female), 54.1% reported ≥ 2 DSM-5 AUD criteria (threshold for AUD diagnosis). IRT analyses demonstrated that checklist items measured a unidimensional continuum of AUD severity. Differential item functioning was observed for some demographic subgroups but had minimal impact on accurate measurement of AUD severity, with differences between demographic subgroups attributable to differential item functioning never exceeding 0.42 points of the total symptom count (of a possible range of 0-11)., Conclusions: Alcohol Symptom Checklists used in routine care discriminated AUD severity consistently with current definitions of AUD and performed equitably across age, sex, race, and ethnicity. Integrating symptom checklists into routine care may help inform clinical decision-making around diagnosing and managing AUD., (© 2021. Society of General Internal Medicine.)

Objective: Measurement-based care (MBC) is an evidence-based practice in which patients routinely complete standardized measures throughout treatment to help monitor clinical progress and inform clinical decision-making. Despite its potential benefits, MBC is rarely used in community-based substance use disorder (SUD) treatment. In this pilot study, we evaluated the feasibility of incorporating a digital and remotely delivered MBC system into SUD treatment within a community setting by characterizing patients' and clinicians' engagement with and usability ratings toward the MBC system that was piloted., Methods: A pilot study was conducted with 30 patients receiving SUD treatment and eight clinicians providing SUD treatment in a large, publicly funded addiction and mental health treatment clinic. Services as usual within the clinic included individual psychotherapy, case management, group therapy, peer support, and medication management for mental health and SUD, including buprenorphine. Patients who enrolled in the pilot continued to receive services as usual and were automatically sent links to complete a 22-item questionnaire, called the weekly check-in , via text message or email weekly for 24 weeks. Results of the weekly check-in were summarized on a clinician-facing web-based dashboard. Engagement was characterized by calculating the mean number of weekly check-ins completed by patients and the mean number times clinicians logged into the MBC system. Ratings of the MBC system's usability and clinical utility were provided by patients and clinicians., Results: Patient participants (53.3% male, 56.7% white, 90% Medicaid enrolled) completed a mean of 20.60 weekly check-ins (i.e., 85.8% of the 24 expected per patient). All but one participating clinician with a patient enrolled in the study logged into the clinician-facing dashboard at least once, with an average of 12.20 logins per clinician. Patient and clinician ratings of usability and clinical utility were favorable: most patients agreed with statements that the weekly check-in was easy to navigate and aided self-reflection. All clinicians who completed usability questionnaires agreed with statements indicating that the dashboard was easy to navigate and that it provided meaningful information for SUD treatment., Conclusions: A digital and remotely delivered MBC system can yield high rates of patient and clinician engagement and high ratings of usability and clinical utility when added into SUD treatment as usual. The success of this clinical pilot may be attributable, in part, to the user-centered design processes that were used to develop and refine the MBC system that was piloted. Future efforts may focus on strategies to test whether MBC can be sustainably implemented and offers clinical benefits to patients in community SUD treatment settings., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Hallgren, Cohn, Ries and Atkins.)

Background: Alcohol use disorder (AUD) is underdiagnosed and undertreated in medical settings, in part due to a lack of AUD assessment instruments that are reliable and practical for use in routine care. This study evaluates the test-retest reliability of a patient-report Alcohol Symptom Checklist questionnaire when it is used in routine care, including primary care and mental health specialty settings., Methods: We performed a pragmatic test-retest reliability study using electronic health record (EHR) data from Kaiser Permanente Washington, an integrated health system in Washington state. The sample included 454 patients who reported high-risk drinking on a behavioral health screen and completed two Alcohol Symptom Checklists 1 to 21 days apart. Subgroups of these patients who completed both checklists in primary care (n = 271) or mental health settings (n = 79) were also examined. The primary measure was an Alcohol Symptom Checklist on which patients self-reported whether they experienced each of the 11 AUD criteria within the past year, as defined by the Diagnostic and Statistical Manual of Mental Disorders-5 th edition (DSM-5)., Results: Alcohol Symptom Checklists completed in routine care and documented in EHRs had excellent test-retest reliability for measuring AUD criterion counts (ICC = 0.79, 95% CI: 0.76 to 0.82). Test-retest reliability estimates were also high and not significantly different for the subsamples of patients who completed both checklists in primary care (ICC = 0.82, 95% CI: 0.77 to 0.85) or mental health settings (ICC = 0.74, 95% CI: 0.62 to 0.83). Test-retest reliability was not moderated by having a past two-year AUD diagnosis, nor by the age or sex of the patient completing it., Conclusions: Alcohol Symptom Checklists can reliably and pragmatically assess AUD criteria in routine care among patients who screen positive for high-risk drinking. The Alcohol Symptom Checklist may be a valuable tool in supporting AUD-related care and monitoring AUD criteria longitudinally in routine primary care and mental health settings., (© 2022 by the Research Society on Alcoholism.)

Background: Self-report measures of alcohol problems are commonly included in studies evaluating treatment and recovery from alcohol use disorder (AUD), but no prior study has examined the replicability of the measurement of alcohol problems across studies with various measures and diverse samples. Further, it is unclear which items may be better indicators of alcohol problems for patient subgroups. In the present study, we integrated data from four large alcohol treatment studies to develop a commensurate measure of alcohol problems using moderated nonlinear factor analysis (MNLFA)., Methods: Data were from the COMBINE study, Project MATCH, the Relapse Replication and Extension Project (RREP), and the United Kingdom Alcohol Treatment Trial (UKATT), yielding a total sample size of 4414. MNLFA was carried out on the Drinker Inventory of Consequences (COMBINE, MATCH, RREP) and Alcohol Problems Questionnaire (UKATT)., Results: We successfully created a 78-item commensurate measure of alcohol problems and examined differential item functioning (DIF) by study membership, time, and socio-demographic characteristics. Sixty-two items demonstrated intercept DIF, suggesting differences in rates of item endorsement for clients with the same underlying levels of alcohol problems across patient subgroups. Six items demonstrated loading DIF, suggesting differences in the extent to which the items were indicative of alcohol problems across patient subgroups., Conclusions: The self-reported measurement of alcohol problems replicates across measures and diverse samples. Items with DIF have clinical implications for the treatment of AUD. Finally, MNLFA scores can be used to test substantive research questions across these studies., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Objectives: The purpose of this study was to examine associations between psychotherapy session attendance, alcohol treatment outcomes, and Alcoholics Anonymous (AA) attendance., Method: Using data from Project MATCH, repeated measures latent class analyses of psychotherapy session attendance were conducted among participants in the outpatient arm who were randomly assigned to complete 12-session cognitive-behavioral therapy (CBT; n = 301), 12-session twelve-step facilitation (TSF; n = 335), or 4-session motivational enhancement therapy (MET; n = 316). Associations between psychotherapy attendance classes, heavy drinking, alcohol-related consequences, psychosocial functioning, and AA attendance were examined at posttreatment (97% retention), 1-year posttreatment (92% retention), and 3-years posttreatment (85% retention)., Results: In general, participants who attended all 12 CBT/TSF sessions had significantly fewer heavy drinking days and alcohol-related consequences at all posttreatment time points than participants who attended 0-2 CBT/TSF sessions. Participants who attended all four MET sessions generally had significantly fewer heavy drinking days and alcohol-related consequences at posttreatment and 1-year posttreatment than participants who attended 0-1 MET sessions. Participants who attended more TSF and MET sessions generally attended more AA meetings, and participants who attended less CBT sessions generally attended fewer AA meetings., Conclusions: With some exceptions, attending all sessions in CBT, TSF, and MET was related to the most favorable heavy drinking and alcohol-related consequences outcomes. Alcoholics' Anonymous and other mutual help groups may be attended differently based on the form and dose of psychotherapy (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Objectives: The purpose of this study was to examine whether changes in heavy drinking occurring within alcohol treatment predict long-term functioning., Method: Latent profile analyses were conducted using data from Project MATCH and COMBINE. Observed changes in heavy and nonheavy drinking within consecutive 2-week periods over the respective treatment durations were characterized for each participant and were used to identify latent profiles., Results: Both data sets revealed 6 profiles: (1) continuous "remission" (nonheavy drinking); (2) transition from heavy drinking ("relapse") to remission; (3) mostly remission, limited relapse; (4) numerous short transitions between relapse and remission; (5) transition to relapse; and (6) continuous relapse. Profiles 1 and 2 had the best long-term outcomes, Profiles 5 and 6 had the worst, and Profiles 3 and 4 fell between these groups. Within-treatment patterns of heavy drinking and nonheavy drinking were also associated with post-treatment patterns of relapse and remission., Conclusions: Patterns of transition between episodes that respectively include heavy and nonheavy drinking predict long-term alcohol use and psychosocial outcomes and seem essential for clinicians to discuss with their patients. Relapses during outpatient treatment do not necessarily indicate treatment failure, provided they are relatively brief and/or infrequent. In addition, some individuals can and do change from transition patterns of heavy drinking within treatment that are predictive of poorer long-term functioning to transition patterns that predict better functioning within the first year post-treatment., (Copyright © 2021. Published by Elsevier B.V.)

Objective: Four decades ago, the "controlled drinking" controversy roiled the alcohol field. Data have subsequently accumulated indicating that nonabstinent alcohol use disorder (AUD) recovery is achievable, but questions remain whether it is sustainable long-term. This study examined whether nonabstinent recovery at 3 years after AUD treatment is associated with better functioning at 10 years after treatment., Methods: Data were from the 10-year follow-up of Project MATCH (New Mexico site only, n  = 146; 30.1% female, 58.6% non-White). Recovery was defined by latent profile analyses based on psychosocial functioning and alcohol consumption 3 years after treatment. Drinking practices and consequences, depression, purpose in life, and anger were assessed 10 years after treatment. Distal outcome analyses examined differences in drinking and functional outcomes at 10 years as a function of the 3-year latent profiles. Analyses were preregistered at https://osf.io/3hbxr., Results: Four latent profiles identified at 3 years after treatment (ie, low functioning frequent heavy drinkers, low functioning infrequent heavy drinkers, high functioning heavy drinkers, and high functioning infrequent nonheavy drinkers) were significantly associated with outcomes 10 years after treatment. The 2 high functioning profiles at 3 years had the highest level of psychological functioning at 10 years posttreatment, regardless of alcohol consumption level. Abstinence at 3 years did not predict better psychological functioning at 10 years., Conclusions: Nonabstinent AUD recovery is possible and is sustainable for up to 10 years after treatment. The current findings align with recent proposals to move beyond relying on alcohol consumption as a central defining feature of AUD recovery., Competing Interests: The authors have no conflicts of interests to disclose., (Copyright © 2020 American Society of Addiction Medicine.)

Background: Measurement-based care (MBC) is the practice of routinely administering standardized measures to support clinical decision-making and monitor treatment progress. Despite evidence of its effectiveness, MBC is rarely adopted in routine substance use disorder (SUD) treatment settings and little is known about the factors that may improve its adoptability in these settings. The current study gathered qualitative data from SUD treatment clinicians about their perceptions of MBC, the clinical outcomes they would most like to monitor in MBC, and suggestions for the design and implementation of MBC systems in their settings., Methods: Fifteen clinicians from one publicly-funded and two privately-funded outpatient SUD treatment clinics participated in one-on-one research interviews. Interviews focused on clinicians' perceived benefits, drawbacks, and ideas related to implementing MBC technology into their clinical workflows. Interviews were audio recorded, transcribed, and coded to allow for thematic analysis using a mixed deductive and inductive approach. Clinicians also completed a card sorting task to rate the perceived helpfulness of routinely measuring and monitoring different treatment outcomes., Results: Clinicians reported several potential benefits of MBC, including improved patient-provider communication, client empowerment, and improved communication between clinicians. Clinicians also expressed potential drawbacks, including concerns about subjectivity in patient self-reports, limits to personalization, increased time burdens, and needing to learn to use new technologies. Clinicians generated several ideas and preferences aimed at minimizing burden of MBC, illustrating clinical changes over time, improving ease of use, and improving personalization. Numerous patient outcomes were identified as "very helpful" to track, including coping skills, social support, and motivation for change., Conclusions: MBC may be a beneficial tool for improving clinical care in SUD treatment settings. MBC tools may be particularly adoptable if they are compatible with existing workflows, help illustrate gradual and nonlinear progress in SUD treatment, measure outcomes perceived as clinically useful, accommodate multiple use cases and stakeholder groups, and are framed as an additional source of information meant to augment, rather than replace, existing practices and information sources.

Background: Racial discrimination, including microaggressions, contributes to health inequities, yet research on discrimination and microaggressions has focused on single measures without adequate psychometric evaluation. To address this gap, we examined the psychometric performance of three discrimination/microaggression measures among American Indian and Alaska Native (AI/AN) college students in a large Southwestern city., Methods: Students (N = 347; 65% female; ages 18-65) completed the revised-Everyday Discrimination Scale, Microaggressions Distress Scale, and Experiences of Discrimination measure. The psychometric performance of these measures was evaluated using item response theory and confirmatory factor analyses. Associations of these measures with age, gender, household income, substance use, and self-rated physical health were examined., Results: Discrimination and microaggression items varied from infrequently to almost universally endorsed and each measure was unidimensional and moderately correlated with the other two measures. Most items contributed information about the overall severity of discrimination and collectively provided information across a continuum from everyday microaggressions to physical assault. Greater exposure to discrimination on each measure had small but significant associations with more substance use, lower income, and poorer self-rated physical health. The Experiences of Discrimination measure included more severe forms of discrimination, while the revised-Everyday Discrimination Scale and the Microaggressions Distress Scale represented a wider range of severity., Conclusions: In clinical practice, these measures can index varying levels of discrimination for AI/ANs, particularly for those in higher educational settings. This study also informs the measurement of racial discrimination and microaggressions more broadly.

Theoretical views and a growing body of empirical evidence suggest that psychiatric relapses in schizophrenia-spectrum disorders (SSDs) have measurable warning signs. However, because they are time- and resource-intensive, existing assessment approaches are not well-suited to detect these warning signs in a timely, scalable fashion. Mobile technologies deploying frequent measurements-i.e., ecological momentary assessment-could be leveraged to detect increases in symptoms that may precede relapses. The present study examined EMA measurements with growth curve models in the 100 days preceding and following 27 relapses (among n = 20 individuals with SSDs) to identify (1) what symptoms changed in the periods gradually preceding, following, and right as relapses occur, (2) how large were these changes, and (3) on what time scale did they occur. Results demonstrated that, on average, participants reported elevations in negative mood ( d = 0.34), anxiety ( d =0.49), persecutory ideation ( d =0.35), and hallucinations ( d =0.34) on relapse days relative to their average during the study. These increases emerged gradually on average from significant and steady increases ( d = 0.05 per week) in persecutory ideation and hallucinations over the 100-day period preceding relapse. This suggests that brief (i.e., 1-2 item) assessments of psychotic symptoms may detect meaningful signals that precede psychiatric relapses long before they occur. These assessments could increase opportunities for relapse prevention as remote measurement-based care management platforms develop., Competing Interests: DB-Z has an intervention content licensing agreement with Pear Therapeutics and has financial interest in FOCUS technology. He has consulted for Trusst Health Inc., eQuility, and Otsuka Pharmaceuticals Ltd. TC is a co- founder and holds equity stake at HealthRhythms Inc. JK has been a consultant for or received honoraria from Alkermes, Allergan, Dainippon Sumitomo, H. Lundbeck. Intracellular Therapies, Janssen Pharmaceutica, Johnson and Johnson, LB Pharmaceuticals, Merck, Minerva, Neurocrine, Otsuka, Reviva, Roche, Saladex, Sunovion, Takeda and Teva. He has received grant support from Otsuka, Lundbeck, and Janssen. JK is also a shareholder in Vanguard Research Group, LB Pharmaceuticals, Inc. and North Shore Therapuetics. KH has been a consultant for Pear Therapeutics. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Buck, Hallgren, Campbell, Choudhury, Kane and Ben-Zeev.)

Objective: Adolescents' drinking is influenced by their friends' drinking. However, it is unclear whether individually-targeted alcohol interventions reduce drinking in the friends of individuals who receive the intervention. This study used simulations of drinking in simulated longitudinal social networks to test whether individually-targeted alcohol interventions may be expected to spread to non-targeted individuals., Method: Stochastic actor-based models simulated longitudinal social networks where changes in drinking and friendships were modeled using parameters from a meta-analysis of high school 10th grade social networks. Social influence (i.e., how much one's friends' drinking affects their own drinking) and social selection (i.e., how much one's drinking affects who they select as friends) were manipulated at several levels. At the midpoint of each simulation, a randomly-selected heavy-drinking individual was experimentally assigned to an intervention (changing their drinking status to non-drinking) or a control condition (no change in drinking status) and the drinking statuses of that individual's friends were recorded at the end of the simulation., Results: Friends of individuals who received the intervention significantly reduced their drinking, with higher reductions occurring in networks with greater social influence. However, all effect sizes were small (e.g., average per-friend reduction of .07 on a 5-point drinking scale)., Conclusions: Individually-targeted alcohol interventions may have small effects on reducing the drinking of non-targeted adolescents, with social influence being a mechanism that drives such effects. Due to small effect sizes, many adolescents may need to receive alcohol interventions to produce measurable effects on drinking outcomes for non-targeted individuals. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

American Indian communities in Minnesota have been disproportionately impacted by the opioid use disorder (OUD) epidemic, which tribal communities have taken numerous steps to address. The Cascade of Care is a public health framework for measuring population-level OUD risk, treatment engagement, treatment retention, and recovery outcomes, which can help communities monitor the impact of responses to the OUD epidemic and identify where treatment- and recovery-related barriers and facilitators may exist. However, no studies have quantified the Cascade of Care stages within tribal communities and the extent to which these stages can be quantified using existing data sources is unknown. We utilized data from the Minnesota Drug and Alcohol Abuse Normative Evaluation System (DAANES) to quantify OUD Cascade of Care stages for an American Indian tribal nation in Minnesota and for the entire state. DAANES data indicated 269 individuals in the tribal community received treatment for opioid-related problems in 2018. Among them, an estimated 65-99 % initiated medications for OUD and an estimated 13-41 % were retained in treatment for at least 180 days. Existing state-level data can provide information about Cascade of Care stages for American Indian communities, particularly with regard to treatment admission, initiation of medications for OUD, and treatment retention. Additional data sources are needed to measure population-level OUD risk, recovery, and cultural and contextual factors that may impact treatment and recovery., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Objective: Clients who receive alcohol use disorder (AUD) treatment experience variable outcomes. Measuring clinical progress during treatment using standardized measures (i.e., measurement-based care) can help indicate whether clinical improvements are occurring. Measures of mechanisms of behavioral change (MOBCs) may be particularly well-suited for measurement-based care; however, measuring MOBCs would be more feasible and informative if measures were briefer and if their ability to detect reliable change with individual clients was better articulated., Method: Three abbreviated measures of hypothesized MOBCs (abstinence self-efficacy, coping strategies, anxiety) and a fourth full-length measure (depression) were administered weekly during a 12-week randomized trial of cognitive-behavioral therapy (CBT) for women with AUD. Psychometric analyses estimated how reliably each measure distinguished within-person change from between-person differences and measurement error. Reliability coefficients were estimated for simulated briefer versions of each instrument (i.e., instruments with fewer items than the already-abbreviated instruments) and rates of reliable improvement and reliable worsening were estimated for each measure., Results: All four measures had good reliability (.86-.90) for detecting within-person change. Many participants (41.4%-62.5%) reliably improved on MOBCs from first to last treatment session. Reliable improvement on MOBCs was associated with reductions in percentage of drinking days (PDD) at 3, 9, and 15-month follow-ups. Simulated briefer versions of each instrument retained good reliability for detecting change with only 3 (self-efficacy), 11 (coping strategies), 5 (anxiety), or 10 items (depression)., Conclusions: Brief MOBC measures can detect reliable change for individuals in AUD treatment. Routinely measuring MOBCs may help with monitoring clinical progress. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Young adult frequent cannabis use has increased in prevalence and some frequent users have problems reducing their use. A strong link between momentary craving and subsequent use behaviors among individuals with problematic cannabis use has been reported in the literature, including young adults. In treatment contexts, interventions based on associative learning and reinforcement aim to reduce the prevalence of problematic substance use by altering the association between craving and use by increasing craving management skills such as mindfulness and reducing unhelpful responding such as avoidance or suppression. However, this model has not been tested among young adult cannabis users. The current study examined the influence of trait and state craving management strategies (mindfulness, coping style, experiential avoidance, and craving beliefs) on the link between momentary craving and use, using ecological momentary assessment in a sample of young adults with problematic use interested in reducing their use. Results demonstrated that two craving management constructs were associated with use: non-reactivity (p = 0.02) and non-judgment (p < 0.01). Interactions with momentary craving were observed for two constructs: non-judgmentalness (p = 0.02) and craving beliefs (p < 0.01). Findings suggest that treatments that increase non-reactivity and non-judgmentalness may reduce the occurrence of cannabis use for young adults contemplating reduction during an important period of biopsychosocial development by mitigating the impact of craving or directly reducing use. Additionally, negative beliefs about craving may serve a protective function during acute periods of elevation in momentary craving, an unexpected finding deserving further investigation., (Published by Elsevier Ltd.)

Background: The World Health Organization (WHO) categorizes alcohol consumption according to grams consumed into low-, medium-, high-, and very-high-risk drinking levels (RDLs). Although abstinence has been considered the ideal outcome of alcohol treatment, reductions in WHO RDLs have been proposed as primary outcomes for alcohol use disorder (AUD) trials., Objective: The current study examines the stability of WHO RDL reductions and the association between RDL reductions and long-term functioning for up to 3 years following treatment., Design and Participants: Secondary data analysis of patients with AUD enrolled in the COMBINE Study and Project MATCH, two multi-site, randomized AUD clinical trials, who were followed for up to 3 years post-treatment (COMBINE: n = 694; MATCH: n = 806)., Measures: Alcohol use was measured via calendar-based methods. We estimated all models in the total sample and among participants who did not achieve abstinence during treatment., Key Results: One-level RDL reductions were achieved by 84% of patients at the end of treatment, with 84.9% of those individuals maintaining that reduction at a 3-year follow-up. Two-level RDL reductions were achieved by 68% of patients at the end of treatment, with 77.7% of those individuals maintaining that reduction at a 3-year follow-up. One- and two-level RDL reductions at the end of treatment were associated with significantly better mental health, quality of life (including physical quality of life), and fewer drinking consequences 3 years after treatment (p < 0.05), as compared to no change or increased drinking., Conclusion: AUD patients can maintain WHO RDL reductions for up to 3 years after treatment. Patients who had WHO RDL reductions functioned significantly better than those who did not reduce their drinking. These findings are consistent with prior reports suggesting that drinking reductions, short of abstinence, yield meaningful improvements in patient health, well-being, and functioning.