Drug and Alcohol Dependence

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.

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.

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.

Introduction: Clinical guidelines for managing opioid use disorder (OUD) recommend incremental dose titration for methadone and buprenorphine/naloxone to achieve a safe therapeutic maintenance dose. Dose titration recommendations are based on clinical experience, pharmacologic rationale, and expert consensus, with limited real-world evidence, especially in settings with widespread fentanyl use, where traditional titration schedules may be insufficient to address the higher opioid tolerance among people initiating treatment. This study aims to determine the comparative effectiveness of alternative titration schedules on completed induction and time to all-cause mortality. Methods and analysis: We will conduct a population-based retrospective cohort study using linked data from nine provincial health administrative databases. The study population will include adults ([≥]18 years) in British Columbia, Canada, who initiated methadone or buprenorphine/naloxone between 01/01/2010 and 30/06/2022. Primary outcomes are completed induction (defined as no dose increase for [≥]two weeks without any intervening decrease) and time to all-cause mortality, with overdose-related acute care visits or overdose-related death and treatment discontinuation as secondary outcomes. Using a target trial framework, this study will implement a clone-censor-weight approach to estimate the per-protocol effects of sustained titration schedules capturing adherence to and deviation from clinical guidelines. Sensitivity analyses will assess the robustness of findings through cohort and timeline restrictions as well as alternative exposure and outcome definitions. Discussion: This study will generate real-world evidence on the comparative effectiveness of alternative titration schedules of methadone and buprenorphine/naloxone on completed induction and all-cause mortality. The findings will support evidence-informed updates to OAT guidelines and clinical decision-making in British Columbia and other jurisdictions facing escalating opioid-related harms.

Repetitive Transcranial Magnetic Stimulation (rTMS) is a promising treatment for tobacco use disorder (TUD). Although at a group level, active stimulation outperforms sham, at an individual level, variability exists in clinical response. The behavioral and neurobiological factors that differentiate those who respond to rTMS from those who do not remain unclear. To explore individual factors that influence acute responses to rTMS, N = 60 human participants received one session of rTMS to the dorsolateral prefrontal cortex (DLPFC) and to a control region (visual cortex; V5) in a randomized order. They completed behavioral assessments and neuroimaging before and after rTMS sessions. Hypotheses involving behavioral and neuroimaging predictors of response were pre-registered prior to completion of data collection. rTMS to the DLPFC led to significant reductions in self-reported cigarette craving compared with rTMS to a control brain region (p = 0.0006) and participants were classified as n = 38 responders and n = 22 nonresponders. Responders used significantly more cigarettes per day (M = 11.441) compared to nonresponders (M = 7.952), reported higher levels of cigarette craving (d = 1.059), and more severe nicotine withdrawal (d = 0.803) prior to rTMS. Neuroimaging analyses based on preregistered hypotheses indicated that DLPFC-frontoparietal and insula whole-brain functional connectivity did not differ significantly between responders and nonresponders. However, exploratory analyses revealed that responders had reduced pre-rTMS functional connectivity between the insula and nucleus accumbens, precuneus, and occipital pole. These findings suggest that response to rTMS for TUD is associated with greater baseline cigarette consumption, craving, and withdrawal, in addition to distinct functional connectivity patterns related to salience, reward, and self-referential processes, providing candidate behavioral and neural markers for personalized rTMS interventions for TUD.

Background: Khat (Catha edulis) is a widely consumed natural amphetamine-analog used across East Africa and the Arabian Peninsula. Accurate field-feasible measurement of recent khat use is a prerequisite for large-scale epidemiological research; yet no validated alternatives to laboratory reference methods have been identified in the scientific literature. This nested validation study evaluated the diagnostic accuracy of two point-of-care measures, a commercial amphetamine immunoassay and a Timeline Followback (TLFB) Assisted Self-Report (ASR), against high-performance liquid chromatography (HPLC) quantification of urinary norephedrine (NE), while additionally assessing agreement between the two field measures. Methods: A prospective, random sub-sample of 119 male participants aged 18-40 years from the Gilgel Gibe Field Research Center (GGFRC) longitudinal cohort, Ethiopia (validation timepoint T2, 2015), was used. Three index-reference comparisons were conducted: (1) amphetamine immunoassay (nal von minden, Drug-Screen AMP test, 300 ng/mL cutoff) vs. HPLC; (2) binary ASR (past-week use) vs. HPLC; and (3) binary ASR vs. immunoassay. Sensitivity (positive percent agreement, PPA), specificity (negative percent agreement, NPA), positive predictive value (PPV), negative predictive value (NPV), overall accuracy (overall percent agreement, OPA), and Cohen's kappa were calculated with 95% confidence intervals. Pre-specified secondary analyses applied three pharmacokinetically-informed recall windows (0-2, 3-5, and 6-7 days prior to interview) to ASR. Results: Against HPLC (77 positive, 42 negative), the immunoassay showed perfect specificity (1.0 [0.916-1.0]) and PPV (1.0 [0.91-1.0]) but low sensitivity (0.52 [0.40-0.64]), NPV (0.53 [0.42-0.65]), overall accuracy (0.69 [0.60-0.77]), and weak kappa (0.43 [0.34-0.52]). Binary ASR showed high sensitivity (0.96 [0.89-0.99]), specificity of 0.60 [0.433-0.74], PPV (0.81 [0.72-0.89]), NPV (0.89 [0.72-0.98]), with overall accuracy 0.83 [0.75-0.89] and moderate kappa (0.60 [0.51,0.69]). Restricting ASR to use within 0-2 days improved specificity to 0.69 [0.52-0.84], PPV to 0.86 [0.77-0.93], overall accuracy to 0.87 [0.79-0.93], and kappa to 0.69 [0.61-0.78] (moderate), while sensitivity (0.96 [0.89-0.99]) and NPV (0.89 [0.72-0.98]) remained stable. Against the immunoassay, ASR achieved high PPA of (1.0 [0.91-1.0]), NPA of 0.35 [0.25-0.47], OPA of 0.57 [0.48-0.66], and minimal kappa (0.27 [0.19-0.35]). Conclusions: Time-stratified ASR (0-2 days) is a valid, scalable alternative to biological testing for recent khat use in resource-limited settings. The immunoassay's 300 ng/mL cutoff functions as a marker of heavy or recent high-dose khat use rather than any-use detection. Its perfect specificity and PPV make it valuable as a confirmatory test for substantial exposure, while its lower sensitivity reflects calibration to amphetamine rather than to khat-derived cathinone metabolite. Keywords: khat; Catha edulis; diagnostic accuracy; STARD; self-report; immunoassay; HPLC; Ethiopia; substance use measurement

Importance: Cannabis use remains prevalent in youth despite concerns regarding its potential impact on cognitive function. Unraveling whether the association between cannabis use and cognition is partially due to preexisting differences or primarily related to use is vital to understanding underlying mechanisms. Objective: To estimate the longitudinal association between cannabis initiation and cognitive trajectories, indexed by task performance and P3 event-related potential (ERP), and to estimate whether baseline cognition is associated with cannabis initiation. Design: Data were analyzed from the ongoing longitudinal Collaborative Study on the Genetics of Alcoholism (COGA) cohort, which was followed up approximately every 2-5 years from 2004 to 2025. Setting: 6 sites across the United States. Participants: Adolescent and young adult offspring of past COGA participants and control families who reported on their cannabis use and who had Visual Oddball (VOP) performance and P3 ERP data (N=4814; 52.4% female, 68.4% white) were grouped based on the timing of cognitive data collection relative to cannabis initiation into Pre-onset (n=2,449; [&ge;]1 assessment) and Post-onset (n=998; [&ge;]3 assessments) subsamples. Main Outcomes and Measures: VOP measures include performance accuracy (%), reaction times (ms), and P3 amplitude (V) and latency (ms) during target trials. Cannabis measures included lifetime use of cannabis (i.e., ever used) and age at first use. Results: High P3 amplitude, and prolonged P3 latency and reaction time were associated with a reduced hazard of cannabis initiation (All Hazards Ratio, [H.R.s]< 0.91, p's<.008). Following initiation, cannabis use was associated with steeper declines in P3 amplitude (b=-0.29, p=0.02) and stabilized reaction time (b=0.35; p=0.005). Steeper decline in P3 amplitude (i.e., slope) was associated with greater cannabis progression (e.g., Cannabis Use Disorder, Odds Ratio, [O.R.]=2.34, p<.001), whereas steeper decline in reaction time was associated with reduced progression (O.R.=.79, p=.002). Conclusion: Baseline P3 indices and reaction time were associated with cannabis initiation, while cannabis use was associated with subsequent changes in P3 amplitude and reaction time trajectories. These findings indicate that accelerated neurodevelopment may modify the likelihood of cannabis initiation which, in turn, may further contribute to neurocognitive changes that deepen cannabis involvement.

Background: The nicotine analog 6-methyl nicotine (6-MN) has appeared in commercial e-cigarette liquids, and other products, spurring interest in determining the extent to which it conveys similar effects to those of nicotine. Objective: To determine if 6-MN acts like nicotine to decrease body temperature, decrease nociception, suppress wheel activity and reinforce operant behavior when delivered by vapor inhalation using an Electronic Nicotine Delivery System (ENDS; "e-cigarette") approach in a rat model. Methods: Male and female (N=8 per sex) young adult Sprague-Dawley rats were evaluated for rectal temperature and nociceptive responses (warm water tail-withdrawal) to the inhalation of vapor from (-)-6-MN or (-)-nicotine in concentrations ranging from 5-30 mg/mL in the propylene glycol vehicle. Rats were then assessed for the reinforcing effects of nicotine and 6-MN using a vapor self-administration procedure and the rate suppressing effects of nicotine and 6-MN on wheel activity following injection. Results: Inhalation of nicotine or 6-MN for 30 minutes decreased the rectal temperature and increased tail-withdrawal latency of female and male rats in a concentration-dependent manner. The magnitude of the effects of 6-MN and nicotine were similar at similar vapor concentrations. Operant responding for 6-MN vapor was increased by pre-treatment with the antagonist mecamylamine. 6-MN was more potent than nicotine at suppressing wheel activity after injection. Conclusions: 6-MN induces effects very similar to those of nicotine, at a similar potency when inhaled and at a slightly increased potency when injected.

Background: Individuals with attention-deficit hyperactivity disorder (ADHD) are at increased risk for cannabis misuse, with increasing prevalence among young adults. Existing evidence suggests that cannabis can have therapeutic effects on ADHD symptoms, and continued use may be partly driven by perceived improvements in symptom-related deficits. To investigate the neural evidence for these associations, we integrated functional neuroimaging and Allen Human Brain Atlas transcriptomic data to assess neural correlates of ADHD in regions targeted by cannabinoids as predictors of cannabis use. We hypothesized that greater ADHD symptoms would lead to higher cannabis use frequency through associations of ADHD symptoms with functional deficits in cannabinoid receptor type 1 (CB1R; encoded by the CNR1 gene) expressing brain regions. Methods: We tested 466 college students (ages 18-19) with varying ADHD symptom severity and cannabis use, self-reported at baseline and three yearly-follow up questionnaires. ADHD-related neural deficits were tested in a subset of 144 participants using an fMRI stop-signal task at baseline. Growth mixture modelling categorized participants with similar cannabis use into three latent classes. The covariance between the CNR1 gene expression map and differences in stop-signal task activation were tested as a mediator linking ADHD symptoms and cannabis use. Results: Greater ADHD symptoms significantly predicted reduced activation within CNR1-expressing regions, which predicted higher-use cannabis class membership. Conclusions: Our results add support for the self-medication hypothesis for higher rates of cannabis use among individuals with greater ADHD symptoms, which may be mechanistically linked through CB1R-enriched attention and inhibitory networks, highlighting neural targets for prevention and treatment.

Background: Opioid use disorder (OUD) is associated with a wide range of cognitive, affective, and motivational impairments, suggesting a disruption of large-scale brain systems that support diverse domains of functioning. Resting-state brain network segregation quantifies the degree of functional specialization within brain networks, is age-related, has been linked to brain glucose metabolism, and has been shown to be reduced in substance use disorders. We examined brain network segregation in individuals with OUD and non-OUD controls and tested associations with the duration of opioid use. Methods: Resting-state functional MRI data were collected from 149 individuals with OUD and 126 non-OUD controls. Functional connectivity was computed between brain regions assigned to functionally specialized networks supporting higher-order "association" or "sensorimotor" processes. For each network, segregation was quantified as the extent to which within-network connectivity exceeded between-network connectivity. Results: Individuals with OUD demonstrated lower segregation of the association and sensorimotor networks than non-OUD controls. Within the OUD group, more years of opioid use was associated with lower segregation of the association network, but not the sensorimotor network. Conclusions: OUD is characterized by overall lower resting-state brain network segregation. More years of opioid exposure was associated with lower association-network segregation, consistent with there being cumulative effects of chronic opioid use on large-scale brain organization, though causation could not be examined in this cross-sectional dataset. These findings identify altered network segregation as a potential neurobiological marker of OUD and suggest that restoration of brain network specialization is a measurable target of OUD treatment and potentially recovery.

Aims: To evaluate whether Cue-Induced Retrieval and Reconsolidation with Episodic Future Thinking (CIREF), which combines personalized drug-cue retrieval with structured future-oriented processing, produces greater changes in craving and delay discounting than a recent-past episodic active control in individuals with opioid use disorder receiving methadone maintenance treatment. Design: Multicentre, two-arm, parallel-group randomized controlled pilot trial with per-protocol analyses. Setting: Two outpatient addiction treatment and rehabilitation centres in Tehran, Iran. Participants: Thirty participants with opioid use disorder receiving methadone maintenance treatment were randomized to CIREF or Episodic Recent Thinking (ERT; n = 15 per group). Twenty-eight completed the intervention and were included in the analyses (n = 14 per group). Intervention and comparator: Participants completed one screening, baseline, and personalized cue-development session followed by three 75-minute intervention sessions. CIREF combined personalized drug-cue retrieval with future-oriented simulation, prediction, intention, and planning. ERT was structurally matched but anchored episodic processing to the recent past. Measurements: Primary craving outcomes comprised the three Desire for Drug Questionnaire (DDQ) subscales assessing session-level phasic/current craving immediately before and after each intervention session and the four Obsessive-Compulsive Drug Use Scale (OCDUS) subscales assessing tonic craving before and after the intervention period. The secondary outcome was Monetary Choice Questionnaire (MCQ) log(k), with more negative values indicating less steep delay discounting. Findings: After Holm correction across the three DDQ subscales, Group x Occasion interactions indicated greater reductions with CIREF for Desire and Intention to Drug Use, FGG(1.23, 32.09) = 24.37, pHolm < .001, partial eta-squared = .484, and Negative Reinforcement, FGG(1.35, 35.23) = 17.67, pHolm < .001, partial eta-squared = .405, but not Drug Abuse Control (pHolm = .172). After Holm correction across the four OCDUS subscales, only Desire and Mental Preoccupation with Drugs showed a significant Group x Time interaction, F(1, 26) = 12.35, pHolm = .007, partial eta-squared = .322; the remaining subscales were not significant (adjusted ps >= .177). MCQ log(k) showed a Group x Time interaction, F(1, 26) = 7.18, p = .013, partial eta-squared = .217; mean log(k) changed from -1.22 (0.36) to -1.80 (0.55) in CIREF and from -1.39 (0.32) to -1.44 (0.44) in ERT. Conclusions: In this small pilot sample, the future-oriented retrieval-based intervention produced greater changes than the recent-past active control in two dimensions of session-level phasic craving, one dimension of tonic craving, and monetary delay discounting. The results are preliminary and do not establish memory reconsolidation or effects on relapse or longer-term clinical outcomes.

Objectives: Tobacco and cannabis co-use is common, and reductions in one substance may theoretically lead to compensatory increases in the other. This secondary analysis examined whether cannabis cue-induced dorsolateral prefrontal cortex repetitive transcranial magnetic stimulation (DLPFC-rTMS) affects tobacco consumption among tobacco-using individuals with cannabis use disorder (CUD). Methods: Data were analyzed from a randomized, sham-controlled trial of DLPFC-rTMS for CUD. Participants were treatment-seeking adults with moderate or severe CUD who reported baseline tobacco use. Active or sham 10-Hz DLPFC-rTMS was delivered during cannabis cue exposure over 10 treatment visits. Linear mixed-effects models examined group differences in weekly percentage change from baseline in tobacco consumption over treatment and follow-up, adjusting for baseline tobacco consumption. Additional models examined whether changes in cannabis use were associated with changes in tobacco use. Results: Twenty participants were included, with 10 assigned to active rTMS and 10 to sham. Active rTMS was associated with a greater reduction in tobacco consumption than sham at 1-week post-treatment (t = -2.49, p = 0.015). Changes in cannabis use were not significantly associated with group differences in tobacco reduction. Estimated group differences did not indicate compensatory increases in tobacco use among participants with larger reductions in cannabis use. Conclusions: Cannabis cue-induced DLPFC-rTMS was associated with a short-term reduction in tobacco consumption relative to sham among tobacco-using individuals with CUD. These preliminary findings suggest possible cross-substance effects of DLPFC-rTMS and did not indicate compensatory tobacco increases. Larger trials specifically designed for cannabis-tobacco co-use are warranted.

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.

Background: Observational studies frequently report a J- or U- shaped association between alcohol use and anxiety and depression, with moderate drinkers appearing to have lower risk than abstainers. However, this pattern may be driven in part by confounding due to health-related selection into abstinence or low-risk drinking (sick-quitter bias), whereby individuals reduce or stop drinking in response to declining health that is independently associated with worse mental health outcomes. We aimed to evaluate whether this association reflects a causal effect or residual confounding driven by sick-quitter bias. Methods: We analyzed data from 4,673 participants in the CHASING COVID Cohort, a U.S. longitudinal study with repeated measures from September 2021 through December 2023. Alcohol use was assessed at five timepoints using the AUDIT-C and categorized as abstinent, low-risk, moderate-risk, or high/severe-risk. Using a target trial emulation framework, we estimated the effects of sustained alcohol use strategies on anxiety and depression symptom severity (GAD-7 and PHQ-8) at follow-up. Artificial censoring and stabilized inverse probability weighting were applied to account for time-varying confounding and loss to follow-up. To assess the role of sick-quitter bias, we compared the abstinent versus moderate-risk contrast across strata of health status at time zero. Results: In the full sample, a J-shaped pattern was observed, with moderate-risk drinkers having the lowest predicted symptom scores. The abstinent versus moderate-risk symptom score contrast was 1.38 for depression (PHQ-8: 95% CI: 0.65, 2.14), and 0.95 for anxiety (GAD-7: 95% CI 0.24, 1.65). Among participants without underlying conditions or poor self-rated health, this pattern attenuated, with contrasts near zero for both outcomes. In contrast, the J-shaped pattern was amplified among participants with poorer baseline health, with abstinent versus moderate-risk contrasts of 3.31 for depression (95% CI: 2.14, 4.32) and 2.83 for anxiety (95% CI: 1.61, 3.86). High-risk drinking was consistently associated with higher symptom scores across all analyses. Conclusions: The J-shaped pattern between alcohol use and anxiety and depression symptoms observed in the full cohort was attenuated among participants without poorer baseline health, consistent with sick-quitter bias. Findings underscore the importance of addressing confounding due to declining health in observational alcohol research and caution against interpreting moderate drinking as beneficial for symptoms of anxiety and depression.

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.

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.

BackgroundSex differences in psychostimulant-related behaviors are often attributed to biological sex; however, individual variability may also strongly influence behavioral outcomes. The new MISSING (Mapping Intrinsic Sex Similarities as an Integral quality of Normalized Groups) model identifies mixed-sex behavioral groups in which differences are driven primarily by individual variability rather than sex. The goal of this study was to validate the MISSING model for psychostimulant/sucrose self-administration. MethodsLong Evans rats self-administered methamphetamine (METH, male n = 25, female n = 32, 0.1 mg/kg/infusion, FR1, 6h per day for 20 days), sucrose (male n = 20, female n = 22, one-20 mg pellet/delivery, all other conditions being equal) and saline (male n = 3, female n = 10, other things being equal). We developed a new Quantitative Structure of Curve Analytical (QSCAn) model (using exponential-plateau and linear fit) for the assessment of individual drug self-administration time curve profiles irrespective of biological sex. We analyzed our data using regression analysis and ANOVA. ResultsQSCAn identified three distinct self-administration profiles (consisting of both sexes), which we named exponential-plateau negative (EP-), exponential-plateau positive (EP+), and undefined (EP0). There were no differences in self-administration profiles when we compared males and females within the same group. Differences between sexes (when observed) were due to mismatched comparisons (males from one group versus females from a different group). ConclusionsOur study reinforces the MISSING model for psychostimulant and sucrose self-administration by indicating that differences between males and females (when observed) may not necessarily be driven by biological sex. Significance StatementCurrent approaches often interpret variability in psychostimulant self-administration between males and females primarily through the lens of biological sex. However, this framework may overlook meaningful behavioral phenotypes shared across sexes. The present quantitative model suggests that individual patterns of behavior may better account for variability than sex alone, particularly in behaviors not strongly driven by sex-hormone-dependent mechanisms such as drug self-administration. By classifying animals according to behavioral profiles rather than biological sex, this approach may foster the identification of clinically and biologically relevant phenotypes underlying psychostimulant reinforcement.

Background Alcohol-associated injury is a leading cause of emergency department (ED) utilization in the United States and a clinically important driver of preventable morbidity across the adult lifespan. Prior surveillance research has characterized how the rate and severity of alcohol-associated injury vary by patient age, but whether the seasonal timing of injury risk is equally predictable across age groups (a question directly relevant to the timing of clinical screening intensification and public health intervention) has not been formally tested. Methods We conducted a retrospective surveillance analysis of 45,876 alcohol-associated ED visits among adults aged 18 years and older, identified from the National Electronic Injury Surveillance System (NEISS), 2019-2025 (weighted national estimate: 2,092,319 visits), using the structured Alcohol_Involved indicator introduced into NEISS case abstraction in 2019. Patients were stratified by sex and five age groups (18-24, 25-34, 35-49, 50-64, and [&ge;]65 years). Single-harmonic cosinor (Poisson) regression was used to estimate the seasonal peak day of injury risk (acrophase) for each stratum. To assess reliability, we performed leave-one-year-out jackknife resampling (seven iterations per group), case-resampling bootstrap confidence intervals (1,000 iterations), and likelihood-ratio tests of seasonal-phase interactions. Results Peak injury timing differed significantly across age groups (X^2 [8] = 2356.2, p < .0001). Adults aged 25-64 years showed a highly reproducible early-to-mid-July peak, with jackknife estimates shifting [&le;]14 days when any single study year was excluded. Adults aged [&ge;]65 years showed significant seasonal variation annually (all p < .0001, amplitude comparable to younger groups) but a pooled peak estimate that shifted by up to 100 days across jackknife iterations. Sex-stratified analyses revealed that this instability was driven entirely by females aged [&ge;]65 years (jackknife range: 332 days, peak consistently in late October through early January) rather than males aged [&ge;]65 (jackknife range: 31 days, peak consistently in early August). Hospital admission rates increased monotonically with age from 9.0% (18-24 years) to 31.8% ([&ge;]65 years). Conclusions Alcohol-associated injury follows a reproducible, calendar-stable summer seasonal pattern in adults aged 25-64 years. Among adults [&ge;]65 years, the previously reported temporal instability is concentrated in the female subgroup, whose seasonal injury risk does not converge on a fixed calendar window. These findings suggest that fixed-calendar prevention and screening strategies are well suited to working-age adults and older men, but older women may require a year-round, individually tailored approach. Keywords: Alcohol-related injury; Emergency department; Seasonality; Age factors; Sex differences; Injury surveillance; Cosinor analysis; Older adults

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.