International Journal of Drug Policy

Objectives Outpatient buprenorphine-naltrexone (bup-nx) treatment reduces overdose risk, yet many patients still return to use or disengage from treatment. We sought to understand how patients and prescribers experience and manage relapse risk, monitoring, and treatment agency in routine bup-nx treatment to identify gaps in current practice. Methods We conducted a qualitative needs assessment using semi structured, critical incident interviews with patients receiving outpatient bup-nx and prescribers who manage bup-nx treatment. Interviews examined situations involving relapse risk and empowerment in treatment decisions. We structured data collection and analysis using the Theoretical Domains Framework and COM B model to characterize determinants. Transcripts were coded deductively and inductively until code level saturation was reached. Results Participants (9 patients, 8 prescribers) described nine treatment needs mapped to the Capability, Opportunity, and Motivation components of the COM B model. These themes highlighted how patient agency in bup-nx treatment was constrained by physiologic and emotional states, with withdrawal, craving, pain, and distress often overriding longer term goals. Relapse vulnerability was experienced as dynamic and intensifying between visits, while clinical detection remained anchored to visit bound assessments, urine drug testing, refill patterns, and crisis driven contact, creating blind spots. Structural friction (pharmacy rules, insurance disruptions, transportation and housing instability), stigma from family and recovery communities, and motivational processes tied to fluctuating readiness and trust in monitoring further shaped engagement, disclosure, and dosing decisions; the same monitoring tools could either support honest disclosure or provoke concealment when perceived as punitive. Conclusions Relapse risk and agency in bup-nx treatment are negotiated as dynamic processes within structurally constrained and trust sensitive systems. Addressing the identified capability, opportunity, and motivation gaps will require patient centered, trust preserving approaches to monitoring and shared decision making.

Aims: To assess whether recent declines in U.S. rolling 12-month-ending drug overdose death counts are projected to continue, compare the retrospective performance of short-term forecasting models, and estimate national and regional 12-month changes. Design: Comparative time-series forecasting study with a retrospective March 2025-February 2026 forecast evaluation and subsequent 12-month-ahead projections through February 2027. Setting: United States and four U.S. Census regions: Northeast, Midwest, South, and West. Cases: Aggregate drug overdose deaths reported in the National Center for Health Statistics Vital Statistics Rapid Release system (VSRR) and identified using ICD-10 underlying cause-of-death codes X40-X44, X60-X64, X85, and Y10-Y14. Measurements: The primary outcome was the monthly series of rolling 12-month-ending overdose deaths. Candidate models included ARIMA, generalized additive models, Prophet, and AICc-ranked n-sub-epidemic models. Models were calibrated using January 2020-February 2025 data and evaluated against March 2025-February 2026 observations using mean absolute error, mean squared error, empirical 95% prediction interval coverage, and weighted interval score (WIS). Individual models were ranked by retrospective WIS, and normalized inverse-WIS weights were used to construct ensembles from the top-ranked models. Final forecasts were generated for March 2026-February 2027 after recalibrating models using January 2020-February 2026 data. Results: Retrospective WIS performance differed geographically: GAM performed best nationally and in the Midwest and West, the leading n-sub-epidemic model in the Northeast, and ARIMA in the South. Median forecasts from all individual models and ensembles projected declines from February 2026 to February 2027 nationally and in each region, although prediction intervals varied substantially. Individual national median projections ranged from declines of 12.8% to 25.8%, while weighted-ensemble median projections indicated declines of 20.5% to 21.7%. Projected weighted-ensemble declines were larger in the Northeast (25.4%-30.0%) and Midwest (24.3%-26.3%) than in the South (16.6%-19.5%) and West (18.0%-21.8%). Summary: Ensemble forecasts of the reported provisional VSRR series were consistent with continued declines in rolling annual overdose death counts nationally and across U.S. Census regions. The projected magnitude of decline differed by region and model specification. Because the forecasts used provisional rolling 12-month-ending counts, they should be interpreted as surveillance projections rather than exact monthly mortality predictions.

In February 2021, Oregon became the first US state to decriminalize possession of small amounts of all commonly used illicit drugs (Measure 110); twenty-four days later, Washington's Supreme Court Blake ruling produced a weaker, shorter-lived decriminalization. Evaluations of these policy periods have focused on overdose deaths, with contested results; their association with the mental health of the general population is unknown. Using surveillance data on 6.3 million adult interviews (2011-2024) and synthetic control methods with permutation inference, we find frequent mental distress an estimated 2.15 percentage points higher in Oregon than in its synthetic counterfactual (largest positive gap among 45 jurisdictions; two-sided rank 2/45, p = 0.044, though not significant under the alternative fit-normalized statistic), with directionally consistent estimates in Washington and a joint test on the pair at p = 0.015. The increase concentrates in self-reported distress, among women and young adults, and is not mirrored in diagnoses, police-recorded partner violence or suicide.

Long-acting injectable (LAI) formulations of pre-exposure prophylaxis (PrEP) and medications for opioid use disorder (MOUD) offer promising new approaches for addressing the intersecting challenges of HIV and opioid use disorder (OUD) in carceral settings. However, successful implementation requires understanding the perspectives of key carceral and community stakeholders. This qualitative study involved 17 semi-structured stakeholder interviews including correctional staff (medical and administrative) and community healthcare providers. Participants were recruited from jails in Washington, DC and surrounding Maryland counties. Interviews were coded using a mixed inductive and deductive methodology, and data were analyzed to identify key themes. Four overarching themes relevant to implementation emerged: (1) The presence of resource barriers, including jail staffing shortages and financial constraints; (2) Challenges administering medications including stigma, medical mistrust, and limited patient knowledge of medications; (3) challenging and restrictive carceral infrastructure; and (4) the importance of care continuity during carceral-to-community transition. Stakeholders emphasized that while LAI PrEP and MOUD could provide critical support to justice-involved individuals, systemic barriers challenged successful implementation and delivery in jail and during community re-entry. Our findings underscore the need for targeted interventions to address the resource, medication, and infrastructure challenges identified. Ensuring sustainable funding, providing staff training and education, improving patient education, addressing stigma, and strengthening community linkages are essential for the successful implementation of LAI PrEP and MOUD in carceral settings. These insights can inform future policies and practices aimed at improving health outcomes for justice-involved populations.

Introduction: Risk of recurrent opioid use during buprenorphine-naloxone (bup-nx) treatment is dynamic and remains elevated after initiation, with vulnerability shaped in part by treatment intensity and gaps between visits, yet routine outpatient care relies on episodic encounters and retrospective data. This mismatch can delay recognition of emerging instability and limit timely treatment adjustments. This paper reports the development and specification of an intervention strategy to address this mismatch. Methods: We used a structured, multi-phase design process to specify and configure a measurement-based care (MBC) strategy for bup-nx treatment (Bup-MBC) in outpatient addiction clinics through three phases: (1) a systematic review of patient-reported outcome measures (PROMs) for substance use treatment; (2) a qualitative needs assessment using the Theoretical Domains Framework and COM-B (Capability, Opportunity, Motivation-Behavior) model to identify gaps in risk monitoring, agency, and trust; and (3) iterative co-design with multidisciplinary clinicians to refine workflow fit and trust-preserving use of data. Patients informed item and feedback content during the needs assessment but did not participate in the co-design cycles. Results: Bup-MBC integrates (1) brief between-visit PROMs (e.g., withdrawal, craving, adherence); (2) immediate non-punitive patient feedback; (3) clinician-facing summaries and non-directive prompts in the electronic health record (EHR); and (4) an opt-in between-visit outreach pathway with predefined safety triggers, all configured within existing EHR and patient portal infrastructure. It targets patient and clinician capability to recognize changes in risk, opportunity for action through structured monitoring and visit preparation, and trust and agency through non-punitive communication, without adding substantial burden. The full measure set, severity bands, and question-to-action map are provided as supplementary material. Key trade-offs included prioritizing single-item measures for feasibility, balancing opt-in outreach with safety overrides, and assuming routine clinician use of summaries. Conclusion: This development study specifies an EHR-integrated MBC strategy for outpatient bup-nx treatment. As single-center design work with co-design limited to clinicians and delivery contingent on portal or text-message access, its outputs are hypotheses about mechanism and fit rather than demonstrated effects. Feasibility studies are needed to evaluate uptake, acceptability, workflow fit, and effects on treatment.

Objective To measure the accuracy of clinical coding, clinician review, and a locally deployed large language model (LLM) in identifying alcohol, drug, and self-harm involvement in emergency department (ED) attendances, and quantify prevalence. Design Two-phase diagnostic accuracy study. In a validation week, the identification strategies were assessed against a conflict-adjudicated reference standard (n=2,256); the LLM was then applied to n=105,096 annual attendances at the same site. Setting UK Type 1 Emergency Department treating patients [&ge;]16yrs. Main outcome measures Prevalence quantification compared with the reference standard; sensitivity, specificity, and balanced accuracy of each strategy; monthly identification rates and adjusted annual prevalence. Results The reference standard identified 12.1% of attendances as involving alcohol, drugs, or self-harm (coding 6.0%; clinician 10.0%, LLM 15.6%). LLM balanced accuracy matched or outperformed clinician review in all three domains (alcohol 0.942 v 0.930, p=0.635; drug 0.959 v 0.791, p<0.001; self-harm 0.982 v 0.908, p=0.004). Coding recorded 1.07 domains per identified patient against 1.32 in the reference standard. Adjusted annual prevalence corresponded to 12,890 domain involvements per year not identifiable in coded data. Subdomain classification found at least 81.6% of self-harm attendances required medical assessment for injury or overdose before psychiatric review. Conclusions Clinical coding identified fewer than half of presentations involving alcohol, drugs, and self-harm and rarely captured co-occurring domains; under-recording was present across a full year. A locally deployed LLM generated more complete structured data from existing clinical text within NHS infrastructure, at a scale which is not feasible for manual review.

Polysubstance use is rising and linked to heightened overdose rates and increased treatment challenges, further exacerbated by increasing detection of adulterants (e.g., xylazine) in the street drug supply. Harm reduction groups provide sterile syringes in exchange for used ones, creating a unique opportunity to characterize prevalent polysubstance combinations and inform translational and preclinical research We analyzed residues from used syringes (N=3,168) obtained from several harm reduction organizations in Jefferson County, KY (Jan-Dec 2025) for the presence of substances using gas chromatography mass spectrometry (GC-MS). We classified compounds as adulterants (e.g., diphenhydramine [DPH]/Benadryl), byproducts/precursors of synthesis (e.g., 4-ANPP), and recreational drugs (e.g., meth). We excluded byproducts/precursors and determined the most frequent substance and pairs/trios containing one or more recreational substance. Results. Of 3,168 syringes, 2,522 (79.61%) tested positive for substances. Out of those positive, the top recreational substances were meth (n=1,387; 54.99%), fentanyl (n=1,220; 48.37%), and heroin (n=653; 25.89%). Top adulterants were DPH (n=1021; 40.48%), dimethyl sulfone (n=749; 29.69%), and lidocaine (n=736; 29.18%). The most common pairs were DPH+fentanyl (n=670; 26.57%), lidocaine+fentanyl (n=659; 26.13%), dimethyl sulfone+meth (n=621; 24.62%), and fentanyl+heroin (n=484; 19.19%). The most common trios were DPH+lidocaine+fentanyl (n=369; 14.63%), DPH+fentanyl+heroin (n=327; 12.97%), lidocaine+fentanyl+heroin (n=297; 11.77%), diphenhydramine+xylazine+fentanyl (n=273; 10.82%), and meth+lidocaine+fentanyl (n=262; 10.39%). Our findings highlight evolving patterns of multiple-opioid and opioid-stimulant polysubstance use, generating insights that can be rapidly applied to strengthen clinical, preclinical, and translational polysubstance research. These insights allow for investigations into biobehavioral mechanisms and consequences of emerging use patterns, accelerating development of novel therapeutics.

Quantifying decision-making in experimental settings that mimic real-world conditions may provide insights into mechanisms underlying addiction. This study developed a computational model of opioid-seeking behavior. Out-of-treatment persons who regularly used heroin were stabilized on buprenorphine 8mg/day to minimize opioid withdrawal. Across programmatically-linked studies, three experimental conditions presented differing money vs. opioid unit amounts that could be earned per trial ($2 vs. 1-mg hydromorphone, n=23; $2 vs. 2-mg hydromorphone, n=36; $4 vs. 2-mg hydromorphone, n=24), controlling other factors. Progressive ratio schedules on each choice option required increasing effort across trials to earn the same amount. Trial-level outcomes were decision latency and choice on each option, and session-level outcomes were drug-money latency and breakpoint difference scores. A Markov computational model was used to predict the probability of choosing the same option as the previous trial (vs. switching). Model inputs included effort discrepancy (between earning the same vs. other commodity on next choice) and logarithm of the ratio of decisional speed (current vs. previous choice). Participants who more rapidly chose hydromorphone vs. money made more consecutive drug choices and expended greater effort earning hydromorphone. First-trial hydromorphone choice predicted continued effortful opioid-seeking. Participants repeated choices on 80% of trials; the model accurately predicted stick vs. switch behavior on 93% of trials. Participants typically repeated choices when faced with lower effort discrepancies and higher hydromorphone dose (2-mg vs. 1-mg). In conclusion, a Markov computational model accurately predicted effortful behavior in a choice paradigm that mimics real-world decisions between opioid and nondrug reinforcers.

Background: Alcohol-involved drinking episodes vary in whether they involve hazardous alcohol consumption alone, near-miss sexual risk, or sexual risk behavior, but the within-event mechanisms underlying this variability remain unclear. Methods: Guided by syndemic theory, we conducted a qualitative event-level analysis using modified grounded theory among adults in the San Francisco Bay Area who reported hazardous alcohol consumption, defined as an Alcohol Use Disorder Identification Test score [&ge;]16. In-depth interviews elicited narratives of recent heavy drinking episodes and yielded 64 discrete drinking events across 22 participants. We focused on 35 events with evidence of within-event interaction between biopsychosocial and contextual factors. Using constant comparison, we identified escalation pathways, characterized interruption, and examined how events diverge into three outcomes: hazardous alcohol consumption only, hazardous alcohol consumption with near-miss sexual risk (when risk was plausible but not enacted), and hazardous alcohol consumption with sexual risk behavior. Results: Two primary escalation pathways emerged. Dose-driven escalation involved cumulative alcohol or substance exposure that progressively impaired awareness and self-regulation. Meaning-driven escalation involved prioritizing connection, intimacy, or belonging despite awareness of risk. Time-driven continuation extended exposure across contexts and amplified both pathways. Hazardous alcohol consumption-only events more often followed dose-driven pathways, whereas events involving sexual risk behavior more often followed meaning-driven pathways. Near-miss events occurred across both pathways and illustrated how interruption before the escalation constraint point, when the capacity to modify behavior became reduced, could redirect escalation before sexual risk behavior occurred. Across events with similar levels of intoxication narratives, outcomes diverged according to when the interruption occurred and whether it altered escalation. Conclusion: Hazardous drinking episodes diverge into different outcomes based on escalation pathways and the timing and effectiveness of interruption. Early and effective interruption before the escalation constraint point may represent a key target for harm-reduction strategies to prevent progression to sexual risk behavior.

Background: Adolescent substance-use rehabilitation is a care-continuum problem spanning detection, engagement, active treatment, relapse prevention, aftercare, family support, and equity-oriented implementation. Existing reviews are often modality-specific and do not show how evidence aligns with substances, populations, outcomes, stages of care, or policy needs. Objectives: To map and synthesise the 2015-2025 adolescent and transitional-age youth SUD rehabilitation literature across intervention domains, stages, substances, outcomes, equity/disadvantage, geography, and economics, and to perform meta-analysis only where pooling was clinically defensible. Methods: PubMed, Scopus, and Web of Science records were harmonised to 2015-2025 and deduplicated. Two reviewer roles applied a predefined charting codebook for substance focus, technique family, rehabilitation stage, equity/disadvantage flags, outcome family, and study-design signal. Evidence was synthesised across AI/digital, psychiatric/psychotherapeutic, pharmacological, family/social, behavioural, residential/continuing-care, school/community, harm-reduction, and policy domains. Random-effects meta-analysis was restricted to comparative youth OUD medication-supported trials with extractable binary outcomes. Results: The search identified 1,676 records; 554 duplicates were removed, leaving 1,122 unique records. Metadata screening retained 579 records for evidence-map charting: 112 high-confidence records and 467 conservative metadata-supported records requiring full-text verification before final selective-journal submission. The charted evidence was concentrated in active treatment (n=433) and relapse prevention (n=114); aftercare/follow-up was weak (n=8). Intervention-family signals were led by pharmacological/MOUD (n=72), psychotherapy/psychiatric care (n=65), school/community/brief interventions (n=46), residential/continuing care (n=41), family/social therapy (n=30), AI/digital/telehealth (n=25), harm-reduction/policy (n=24), and CM (n=22). The primary youth OUD retention/completion meta-analysis favoured medication-supported treatment (OR 7.67, 95% CI 3.98-14.78; I^2=0%; k=2; n=188). An exploratory favourable-outcome analysis produced a similar estimate (OR 7.94, 95% CI 4.24-14.89; I^2=0%; k=3; n=229). Conclusions: The strongest pooled quantitative claim supports medication-supported treatment for youth OUD. For non-opioid substances, digital care, family therapy, CM, residential care, aftercare, and equity-oriented implementation, the literature is clinically important but not yet consistently synthesis-ready. Future trials should evaluate complete care pathways, adopt core outcomes, report age-banded and equity subgroup effects, and include economic and implementation endpoints.

Adolescent use of alcohol, nicotine, and marijuana remains a major public health concern in the United States. Early identification of youth at elevated risk is critical for prevention before use begins or escalates. We developed and evaluated a longitudinal machine learning framework to predict alcohol, nicotine, and marijuana use at the next observed assessment wave. Data came from the Adolescent Brain Cognitive Development (ABCD) Study Release 6.0. The models incorporated predictors from multiple domains, including demographics, friends, family and community context, mental health, physical health, and prior substance-related behaviors. To reduce information leakage across individuals, we implemented a leakage-aware stacked ensemble. This ensemble combined diverse base learners through out-of-fold predictions and an elastic-net meta-learner. Across all three substances, the lagged stacked ensemble outperformed the cross-sectional stack and all single base learners. Adolescents identified as highest risk showed substantially higher observed rates of substance use than would be expected under random screening. Feature-importance analyses showed that the full longitudinal models were strongly influenced by developmental timing and prior-use history. Analyses restricted to current-wave features revealed distinct substance-specific risk patterns beyond prior-use history and developmental timing. Bootstrap stability analyses identified top-ranked features showing consistent positive predictive relevance across resampled adolescents. These findings suggest that longitudinal, leakage-aware machine learning can generate substance-specific risk estimates to support targeted prevention and screening in adolescent populations.

Objective: To examine changes in vaping and smoking trends following the announcement and implementation of the disposable vape ban in Great Britain. Design: Interrupted time-series analysis of representative monthly cross-sectional data from the Smoking Toolkit Study. Setting: Great Britain. Participants: 118,946 adults ([&ge;]16y), including 12,042 young adults (16-24y), surveyed between Jan-2022 and Feb-2026. Main outcome measures: Changes in trends in disposable vape use among vapers, and current vaping and smoking prevalence, using seasonally-adjusted generalised additive models with comparisons against a no-ban counterfactual in which pre-announcement trends continued unchanged. Results: The proportion of vapers mainly using disposable devices began to decline following the announcement of the ban in Jan-2024, with the fall accelerating after implementation in June-2025. By Feb-2026, 5.6% (95%CI 4.6-6.9) of adult vapers and 7.1% (5.1-10.1) of young adult vapers mainly used disposables, compared with 62.0% (53.6-71.8) and 63.6% (52.7-76.7), respectively, under a no-ban counterfactual. Increases in vaping prevalence slowed post-announcement and plateaued post-implementation; by Feb-2026, prevalence was lower than the no-ban counterfactual in adults (13.6% v 18.8%; difference -5.2 percentage points, 95%CI -7.1 to -3.3) and young adults (27.8% v 39.1%; -11.3, -18.6 to -4.1). Declines in smoking prevalence stalled among adults and reversed among young adults post-announcement, before shifting downward again post-implementation; by Feb-2026, smoking prevalence was similar to the no-ban counterfactual in adults (difference +0.9 percentage points, -0.5 to +2.2) but possibly higher in young adults (+3.3, -0.5 to +7.1). Conclusions: The disposable vape ban in Great Britain was associated with substantial changes after both announcement and implementation, including a marked reduction in disposable vape use and a slowing then plateauing of growth in overall vaping prevalence. However, declines in smoking also temporarily slowed--and among young adults, reversed--after the announcement, before downward trends resumed after implementation.

Background: Generative artificial intelligence (GenAI) tools, including large language model (LLM)-based platforms such as ChatGPT, Google Gemini, and Microsoft Copilot, are being adopted across healthcare settings with increasing speed. Despite the increasing popularity of GenAI, empirical data on the extent and nature of adoption by mental health clinicians in routine psychotherapy practice globally remain scarce. Objective: This study aimed to characterize current use patterns of GenAI tools among a global sample of practicing mental health professionals, including prevalence of use, specific tools employed, clinical and administrative purposes served, perceived effect on workload, and the institutional context shaping adoption (e.g., encouragement, prohibition, and training). Methods: We administered a cross-sectional online survey to a global convenience sample of licensed mental health professionals who provide psychotherapy as part of the scope of their practice (i.e., psychotherapists, psychologists, counsellors, nurses, and psychiatrists). Participants were recruited via professional networks, purposely avoiding the use of social media platforms. Within the survey, we captured GenAI use behaviors in psychotherapy contexts, and demographic and professional background data. Descriptive statistics were analyzed for all variables. Multivariate logistic regression was used to examine demographic and professional predictors of GenAI use. Results: A total of 766 mental health professionals who provide psychotherapy from 30 countries completed the survey. Of these, 54.6% (n=418) reported having purposely used at least one GenAI tool in psychotherapy clinical practice. ChatGPT was the most frequently used tool (354/418, 84.7%). The most commonly reported clinical purpose was assisting with treatment planning (175/418, 41.9%), followed by managing administrative tasks (173/418, 41.4%) and generating psychoeducational materials for clients (166/418, 39.7%). 82.8% of AI users reported that these tools reduced their overall work burden. Only 18.1% (139/766) of respondents reported institutional encouragement to use AI tools, while 81.1% (621/766) reported not having received any professional training on AI use. Predictors of AI adoption included younger age and rural practice setting. Conclusions: In this global convenience sample survey, GenAI use among mental health professionals in psychotherapy settings is widespread, concentrated in a wide variety of clinical and administrative tasks. Formal training and institutional guidance substantially lag behind current adoption patterns. These findings highlight an urgent need for evidence-based competency frameworks, regulatory clarity, and professional education to support safe and ethically informed integration of AI into clinical mental health practice.

Background: People with disabilities (PWD) represent over one-quarter of the US population and disproportionately experience chronic pain, yet limited research explores disparities they face in opioid use disorder (OUD) treatment. Objective: To examine disparities across disability status regarding opioid use disorder (OUD)-related outcomes and understand how chronic pain interacts with these associations. Methods: We completed a cross-sectional, secondary analysis of data from the All of Us Research Program, including 370,722 adults with electronic health record data available between January 2021-September 2023. We identified prevalence of disability, chronic pain, OUD, receipt of medications for OUD (MOUD), and OUD remission using diagnostic codes. We performed interaction analyses between chronic pain, disability subtype, and MOUD receipt in affecting OUD outcomes. Results: OUD was more common among individuals with physical (aOR: 2.74, 95% CI: 2.54-2.95), cognitive (2.19, 1.94-2.45), and multiple disabilities (2.43, 2.19-2.68), compared to those without disabilities. Among patients with OUD, those with physical disabilities were less likely to receive MOUD (0.81, 0.69-0.94). Compared to those without disabilities, chronic pain was associated with higher probabilities of OUD diagnosis and lower probabilities of MOUD and OUD remission across all subjects. These relationships were stronger for OUD diagnosis in cognitive disabilities, MOUD in multiple disabilities, and OUD remission in physical disabilities. Conclusions: Disability and chronic pain jointly shape disparities in OUD treatment and underscore the urgent need for care models that integrate OUD treatment with pain management and address the unique access challenges faced by people with disabilities.

Background: Loneliness and social isolation may contribute to tobacco and nicotine use, but existing studies have been inconsistent. This systematic review and meta-analysis examined these associations among adults amid the evolving nicotine product landscape. Methods: A systematic search of PubMed, MEDLINE, PsycINFO, and CINAHL identified peer-reviewed quantitative studies published between 2014 and 2025 searched in February-April 2026. Eligible studies included adults aged [&ge;]18 years examining loneliness and/or social isolation in relation to smoking or nicotine use. Two reviewers independently screened studies, extracted data, and assessed risk of bias (using the National Heart, Lung, and Blood Institute risk of bias tool). Random effects meta-analyses were conducted to estimate pooled odds ratio (OR) with 95% confidence intervals (CIs). Results: 22 studies involving 273,954 participants met inclusion criteria, and 14 studies were included in the meta-analysis. A majority of the studies had low risk of bias. Meta-analysis findings showed that social isolation or loneliness was associated with significantly higher odds of nicotine product use (OR 1.84, 95% CI 1.48-2.29). Although no statistically significant association of nicotine product use and social isolation or loneliness (OR 1.35, 95% CI 0.72-2.53), some studies suggested bidirectional relationships, with smoking contributing to reduced social support and greater isolation over time. Sensitivity analysis showed the robustness of the meta-analysis findings. Subgroup analysis found no statistically significant differences were seen between subgroups defined by type of nicotine product, age groups, social isolation vs loneliness, measures of nicotine use behaviours and pre- vs post- COVID-19 pandemic period in the meta-regression. Limitations of included studies and analysis are discussed. Conclusions: Loneliness and social isolation are significant psychosocial correlates of nicotine product use. Cessation interventions may benefit from integrating social support and mental health strategies alongside traditional nicotine dependence treatment.

Background: Alcohol affordability is a determinant of consumption and alcohol-related harm. In many low- and middle-income countries (LMICs), informal production, variable alcohol strength, and non-standard packaging complicate conventional affordability measures, limiting evidence on the economic accessibility of alcohol and the cost of intoxication. Objective: To assess the affordability of intoxication in Uganda by estimating the cost of obtaining ethanol to reach intoxication across alcohol products, packaging types, and retail contexts. Methods: Data were collected on 824 alcoholic beverages from urban, rural, and urban-slum retail markets. Ethanol-standardized pricing (price per gram of alcohol) was calculated, and the cost of consuming 60 g of ethanol was estimated. Multivariate regression identified determinants of ethanol affordability. Results: Affordability varied by product type and packaging. Opaque beers and illicit spirits provided the cheapest pathways to intoxication, with median costs of UGX 1,200-1,500 per 60 g of ethanol. Plastic packaging was associated with lower ethanol costs than glass packaging. Ethanol prices differed across formal and informal markets (p < 0.01), while rural areas and urban informal settlements had 20-25% lower costs than urban areas. Regulatory status alone did not predict affordability. Conclusions: In Ugandas diverse alcohol market, affordability is driven by access to ethanol rather than beverage price alone. Low-cost, high-strength alcohol sold through informal channels enables intoxication at minimal expense, among disadvantaged populations. Implications: Alcohol policies should target ethanol content through minimum unit pricing, alcohol-content-based taxation, and regulation of informal markets and packaging practices to reduce harmful consumption and inequities.

Objectives To compare hospital claims and costs for major tobacco associated diseases with ICD 10 F17 tobacco dependence coding in Indonesian national health insurance claims and to assess whether the insurer records tobacco addiction or mainly pays for its complications. Design Retrospective claims based observational study using routinely collected administrative claims reported according to STROBE and the RECORD extension. Setting Indonesian national health insurance scheme Jaminan Kesehatan Nasional including referral hospital and primary care claims from 2015 to 2023. Participants A national mental health claims sample of 54820 members with at least one ICD 10 mental or behavioral F code diagnosis weighted to 1032022 members and 2074277 referral hospital visits. Primary and secondary outcome measures The primary outcome was verified claim costs in USD for hospital visits with a primary diagnosis of chronic obstructive pulmonary disease J44 or tracheal bronchial or lung cancer C33 to C34 or ischemic heart disease I20 to I25 or stroke I60 to I69. Secondary outcomes were counts of ICD 10 F17 tobacco dependence coding and the disease to F17 coding ratio. Results The four tobacco associated disease groups accounted for 13946 visits among 5223 patients and USD 4.20 million in verified costs representing 6.0 percent of hospital spending in the sample. Weighted costs were USD 74.7 million of which cardiovascular and cerebrovascular disease accounted for 95 percent. F17 appeared in only 51 referral hospital encounters and 26 primary care encounters. Only 2 of 5223 patients with these tobacco associated diseases or 0.04 percent were ever coded with F17. Conclusions The Indonesian national insurer paid substantially for tobacco associated morbidity while tobacco dependence was almost never coded. Smoking related diseases were reimbursed but tobacco dependence treatment was not captured as a financed care target. Embedding brief cessation care reimbursable pharmacotherapy and routine F17 coding into primary care could help shift tobacco related expenditure from downstream complications toward addiction care. Keywords tobacco dependence smoking cessation F17 coding health expenditure administrative claims Indonesia

Background: For US young adults aged 18-25 in the 2018-2024 period, fentanyl was involved in 78.2% of the 44,020 unintentional or undetermined-intent overdose deaths, most often co-involving stimulants and other non-opioid substances. While fatal overdose rates in this age group have fallen to their lowest recorded level, emergency medical services-attended non-fatal overdose events have reached record highs, shifting the decisive variable toward bystander recognition and response. College students report near-universal alcohol education but minimal education on the substances actually driving overdose mortality. Methods: We conducted a single-group pre-post evaluation of the DopaGE Portal, a gamified, mastery-based digital platform covering cocaine, MDMA, benzodiazepines, and opioid overdose response, deployed at a public university (UNL) and a multi-campus volunteer network (TACO). Paired pre/post surveys (N=42) measured self-efficacy (7 items; primary), behavioral intentions, risk perception, and knowledge/attitudes on 5-point scales, plus four factual knowledge questions. Paired t-tests, exact McNemar tests, and Benjamini-Hochberg correction across eight primary tests were applied. Institutional naloxone distribution at UNL was tracked as an ecological behavioral outcome. A mandated high-school cohort (N=94) provided supplementary acceptability data. Results: Self-efficacy increased from 2.82 to 4.46 (d=2.00, 95% CI 1.46-2.55; adjusted p<.001), and behavioral intentions from 4.24 to 4.81 (d=1.43; adjusted p<.001), with effects statistically indistinguishable across sites. Three of four knowledge items improved significantly (+31 to +41 percentage points). Risk perception was at ceiling at baseline (4.38/5) and did not change. In the two months following deployment, 38 naloxone kits were distributed on campus (limited to one per person from the campus pharmacy and health center) versus 14 in the preceding two years combined; the campus health center had distributed zero kits in 2025 despite stocked availability. Evaluation ratings were uniformly positive across voluntary and mandated cohorts, with zero negative ratings. Conclusions: A digital-only, gamified intervention produced large gains in overdose-response self-efficacy and substance-specific knowledge, with concurrent campus-level naloxone acquisition consistent with behavioral translation. These findings are preliminary -- single-group, modest N, ecological behavioral outcome -- and motivate a future randomized controlled trial.

Documenting and measuring mortality in correctional facilities is essential for understanding the health consequences of incarceration, identifying preventable deaths, and informing policy interventions. We undertook a compilation of publicly available mortality records in state-operated correctional facilities, encompassing data gathered from administrative, nonprofit, and public records. The Harmonized Carceral Mortality Database (HCMD) standardizes decedent characteristics, facility identifiers, locations, dates of death, and causes of death to enable epidemiological analyses of mortality in U.S. prisons, outside of federal reporting. At the time of writing, the HCMD includes 49,682 deaths from at least 1,089 prisons in 50 states, spanning 1996-2024, with regular updates annually. The HCMD supports carceral health research across a range of disciplines from environmental health to sociology to criminology and supports use beyond the scientific community, including journalists, lawyers, and community-based organizers.

Background and Aims: Anxiety remains prevalent among adolescents while tobacco and nicotine product use, especially the recent increases of novel product use such as e-cigarettes and nicotine pouches, raises further public health concerns. The associations between novel tobacco and nicotine product use and anxiety remains understudied. This study aims to determine whether tobacco and nicotine product use is associated with generalised anxiety and whether this association differs by used product. Design: Cross-sectional survey, School Health Promotion study in 2025. Setting: A school-based nationwide survey conducted in all Finnish lower and upper secondary schools. Participants: Students aged 13-20 years in three school levels: 8.-9. grade students in lower secondary schools (N= 94 743, 73% of the students), 1st and 2nd-year students in general upper secondary schools (n=47 248, 70% of the students) and of vocational institutions (n=24 998, 38% of the students). Measurements: Exclusive (single product) and non-exclusive ([&ge;]1 products) daily or weekly use of tobacco and nicotine products, including nicotine pouches, e-cigarettes, cigarettes, and smokeless tobacco (snus). Generalised anxiety was measured using the Generalised Anxiety Disorder Scale (GAD-7). The cut-off of >10 points indicated participants with moderate to severe self-reported generalised anxiety symptoms. Background variables included sociodemographic variables and heavy drinking. Results: Of the 166,989 participants 51.4% were females, mean age was 15.7 (SD 1.27), 21.2% reported generalised anxiety. Prevalence of generalised anxiety increased gradient-wise in accordance with both non-exclusive and exclusive use frequency of different tobacco and nicotine products, as well as with number of products used. Daily use of nicotine pouches was associated with higher odds of anxiety compared with never use (boys: adjusted odds ratios (aOR) 1.19, 95% CI, 1.05 to 1.34; girls: aOR 1.74, 95% CI, 1.58 to 1.91), yet the association between daily e-cigarette use seemed to be stronger (boys aOR 1.96, 95% CI, 1.54 to 2.49; girls: aOR 2.29, 95% CI, 2.09 to 2.51). Summary: Any use of tobacco and nicotine products, including new products, is associated with generalised anxiety among adolescents, with some differences between products. Measures to prevent the initiation of tobacco and nicotine product use and to promote mental health among adolescents should be enacted.