Journal: JAMA Network Open, 2026, doi:10.1001/jamanetworkopen.2025.52136
Authors: Sarah S. Kawasaki, Jane M. Liebschutz, Cristina Murray-Krezan, Galen E. Switzer, Samantha Nash, Kwonho Jeong, & Erin L. Winstanley
Abstract:
Importance: Anecdotal accounts suggest an increase in problems initiating buprenorphine (BUP) treatment among individuals using illicitly manufactured fentanyl. Limited empirical data illuminate these challenges.
Objective: To determine the prevalence of clinician-reported problems initiating BUP treatment among patients using fentanyl and describe clinical strategies used to overcome engagement challenges.
Design, Setting, and Participants: For this survey study, an online survey was pilot tested and refined with a convenience sample of physicians. The final survey included 96 items and took less than 15 minutes to complete. The survey queried patients’ use of fentanyl, BUP induction problems (precipitated or prolonged withdrawal), strategies to overcome induction problems, clinician characteristics, and practice characteristics. Eligible clinicians initiated BUP for at least 10 patients with opioid use disorder in the past year and at least 1 patient in the past 90 days. The survey was live from June 2, 2023, to March 18, 2024.
Main Outcome and Measures: The main outcome of interest was precipitated and/or prolonged opioid withdrawal. Descriptive statistics are reported, and logistic regression was used to identify factors associated with BUP initiation problems.
Results: A random sample of physicians and advanced practice clinicians in the US Drug Enforcement Administration (DEA) registrant dataset from October 2022 (n = 3141) were invited to participate; of 2485 eligible for inclusion, 649 (26.1%) completed the prescreen survey. Of 421 (64.9%) eligible to complete the survey, the final sample included 396 (94.1%) clinicians who completed at least 50% of the survey items. Of 390 participants, 284 (72.8%) reported problems when initiating BUP in patients using fentanyl, with 242 of 394 (61.4%) reporting patients’ experiencing precipitated withdrawal. A total of 264 or 392 participants (67.3%) reported modifying their standard induction procedures, changing how they counsel patients, or changing both medication and counseling protocols. In multivariable modeling, clinicians were more likely to report problems initiating BUP in patients if they had a DEA waiver to treat more than 100 patients (OR, 1.92; 95% CI, 1.08-3.40), vs those waivered to treat fewer patients; if they reported at least 75% of their patients using fentanyl (OR, 6.31; 95% CI, 2.59-15.35), vs no patients; or if they inducted patients in noninpatient settings (OR, 2.79; 95% CI, 1.39-5.61), vs inpatient settings.
Conclusions and Relevance: In this survey study of clinician-reported problems initiating BUP treatment, clinicians working in high-volume noninpatient settings reported more problems initiating BUP in patients using fentanyl, and many reported changing their clinical practices in response to these problems. Further research is warranted to match alternate BUP induction strategies by clinical settings.
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Journal: eClinicalMedicine, 2026, doi: 10.1016/j.eclinm.2025.103723
Authors: Henrique Nunes Pereira Oliva, Tiago Paiva Prudente, Alisson M. Paredes Naveda, Renato Sobral Monteiro-Junior, Marc N. Potenza, Peter T. Morgan, & Gustavo A. Angarita
Abstract:
Background: Sleep disturbances are common in individuals with substance use disorders (SUDs), often persisting beyond initial abstinence and hindering recovery. However, the underlying sleep abnormalities warrant further investigation, particularly given mixed findings regarding specific substances.
Methods: This systematic review and meta-analysis aimed to identify sleep-related abnormalities associated with alcohol (AUD), benzodiazepine (BUD), cannabis (CaUD), cocaine (CoUD), methamphetamine (MUD), nicotine (NUD), and opioid (OUD) use disorders. We systematically searched Embase, PsycINFO, PubMed, Scopus, and Web of Science until November 2025, following a pre-registered protocol (PROSPERO: CRD42024531160).
Findings: We conducted a systematic review of 43 eligible publications involving approximately 7500 participants, using both objective (eg, polysomnography) and subjective (eg, Pittsburg Sleep Quality Index [PSQI]) measures. Results showed that total sleep time (TST) was reduced in AUD (−14.32, 95% CI = −16.69 to −11.96; I2 = 0%), NUD (−0.33, 95% CI = −0.59 to −0.06; I2 = 37%), and OUD (−38.16, 95% CI = −63.04 to −13.28; I2 = 0%). Slow-wave sleep (SWS) was reduced in AUD (−3.68, 95% CI −4.99 to 2.38; I2 = 73%) and CoUD (−30.69, 95% CI = −47.27 to −14.10; I2 = 90%). Sleep quality, measured by the PSQI, was poorer in AUD (4.89, 95% CI = 3.01 to 6.77; I2 = 98%), CoUD (0.98, 95% CI = 0.04–1.93; I2 = 0%) and NUD (2.64, 95% CI = 0.41–4.88; I2 = 96%). Results for CaUD could not be meta-analyzed due to scarcity of data. No study met criteria to be included for BUD or MUD.
Interpretation: These findings suggest specific relationships between specific addictive substances and sleep, highlight areas of convergence in these relationships, and indicate instances in which the same drug is related with both objective and subjective alterations. Further research is needed to explore further, at a meta-analytical level, relationships between sleep and specific substances.
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Authors: Edwin S. Won, Caitlin N. Dorsey, Tara C. Beatty, Jennifer F. Bobb, Kelsey Stefanik-Guizlo, Dustin L. Key, … Joseph E. Glass
Journal: PLOS digital health, 2026, doi: 10.1371/journal.pdig.0001145
Abstract:
Evidence-based digital therapeutics are a promising approach for the scale-up of substance use disorder (SUD) treatments. Despite demonstrated efficacy, utilization of digital therapeutics is low. Strategic implementation approaches have potential for increasing digital therapeutic use. Applicability to health systems depends, in part, on the economic costs. The objective of this study was to describe implementation and intervention costs of implementation strategies to increase uptake of an evidence-based digital treatment for SUD. We conducted an economic evaluation alongside a hybrid type III cluster-randomized trial within a large integrated health system. All clinics implemented a standard implementation (SI) strategy, and clinics were assigned using 2×2 factorial randomization to additionally receive practice facilitation (PF) and/or health coaching (HC). Implementation costs included the cost of time devoted to implementation activities and direct operating costs. Time devoted to implementation activities was ascertained through structured meeting logs and time use surveys. Operating costs were captured using project budget reports. Intervention costs included expenses for prescriptions and healthcare encounters related to the digital therapeutic, measured using electronic health record data. Univariate statistics were calculated for cost estimates with comparisons presented by trial arm, implementation activity, staff role and study month. Analyses were conducted from a health system perspective. Twenty-one primary care sites participated in the trial. Over the 50-month study period, the total cost of all implementation activities was $748,088. Implementation costs per clinic were highest in the SI + PF + HC arm ($48,029), followed by SI + HC ($36,544), SI + PF ($30,665) and SI alone ($24,774). Intervention costs were highest in the SI + PF + HC arm ($18,051), followed by SI + PF ($11,492), SI + HC ($967) and SI alone ($1,879). Findings from this study can guide health systems by informing the economic investment required to employ implementation strategies demonstrated to increase uptake of evidence-based practices for behavioral health conditions.
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Journal: Substance Abuse Treatment, Prevention, and Policy, 2026, doi: 10.1186/ s13011-025-00694-2
Authors: Jennifer Whittaker, Katherine Kellom, Anyun Chatterjee, Rebecka Rosenquist, Douglas Strane, & Meredith Matone
Abstract:
Background: Opioid use in pregnancy and the postpartum period in the United States has continued to rise. There are significant barriers to accessing evidence-based treatment and appropriate wrap-around services for pregnant and postpartum individuals and their families. These challenges sit at the intersection of multiple incongruent and fragmented systems, including criminal justice, child welfare, childcare, health insurance, and physical and behavioral health treatment. To support and improve outcomes for this population, with their unique medical and social complexities, we seek to understand how individuals access Medication for Opioid Use (MOUD), barriers to MOUD treatment, and how the policy environment supports or hinders care delivery and recovery.
Methods: To understand this, we use in-depth interviews with interest-holders from across a mid-Atlantic state with a county-administered system, including prenatal care providers, county-level administrators, treatment programs, and pregnant and parenting people. From these interviews, we develop composite narratives that merge and share findings through the lens of four separate perspectives: an obstetrician, a director of a treatment organization, a local government official, and a parenting person who experiences opioid use disorder. We map these narratives onto the World Health Organization’s Commission on Social Determinants of Health to illustrate the mechanisms for achieving positive health outcomes and demonstrate opportunities for policy engagement.
Results: The narratives highlight the social and structural determinants of health and illustrate the policy barriers that prevent pregnant and postpartum people with opioid use disorder from accessing care. We highlight policies that govern criminal justice and substance control, child welfare, and childcare systems, as well as policies related to health insurance and treatment center operations.
Conclusions: This paper articulates how substance use care for pregnant and postpartum people and their families is distinctly different from substance use disorder care for other populations. Efforts to improve outcomes for this population must consider the policy environment, stigma, and the structural determinants of health.
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Journal: Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 2026, doi: 10.1016/j.bpsc.2025.12.014
Authors: Sophia H. Blyth, Lauren D. Hill, Anna Huang, Neil D. Woodward, Baxter P. Rogers, Simon Vandekar, & Heather Burrell Ward
Abstract:
Background: Adolescent substance use is associated with increased risk of suicide, overdose, and executive dysfunction. Alcohol and marijuana are the two most used substances among young people. Substance use is associated with dysfunctional resting-state network connectivity between the default mode network (DMN), executive control network (ECN), and salience network (SN), and executive dysfunction. There is limited research on triple-network connectivity (DMN, ECN, SN) in adolescents who use substances.
Methods: In typically developing youth from the Philadelphia Neurodevelopmental Cohort, regression models were used to examine relationships between alcohol and marijuana use and triple-network connectivity (n=520), adjusting for age, sex, maternal education, and head motion. In individuals with neurocognitive and substance use data (n=4197), regression models were used to examine relationships with executive control.
Results: Alcohol use was not associated with any connectivity measures after FDR correction. Higher marijuana use was associated with higher DMN–ECN connectivity (F(2,507) = 5.08, p = 0.0066, q = 0.039). Higher alcohol use was associated with better working memory (p = 0.020), mental flexibility (p<.0001), attention (p = 0.019), and executive efficiency (p = 0.0015) and accuracy (p = 0.00044), which may have been due to other socioeconomic factors. Marijuana use was not associated with neurocognitive performance.
Conclusions: In typically developing youth, marijuana use was associated with DMN-ECN connectivity, while alcohol use was associated with neurocognitive performance. Future research should use interventions targeting the DMN, ECN, and SN to interrogate relationships between connectivity, cognitive performance, and substance use.
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