Drug and alcohol dependence最新文献

{"title":"Predicting treatment-seeking status for alcohol use disorder using polygenic scores and machine learning in a deeply-phenotyped sample","authors":"Zeal Jinwala ,&nbsp;ReJoyce Green ,&nbsp;Yousef Khan ,&nbsp;Joel Gelernter ,&nbsp;Rachel L. Kember ,&nbsp;Emily E. Hartwell","doi":"10.1016/j.drugalcdep.2025.112797","DOIUrl":"10.1016/j.drugalcdep.2025.112797","url":null,"abstract":"<div><h3>Background</h3><div>Few individuals with alcohol use disorder (AUD) receive treatment. Previous studies have shown drinking behavior, psychological problems, and substance dependence to predict treatment seeking. However, to date, no studies have incorporated polygenic scores (PGS), a measure of genetic risk for AUD.</div></div><div><h3>Methods</h3><div>In a deeply-phenotyped sample, we identified 9103 individuals diagnosed with DSM-IV AUD and indicated treatment-seeking status. We implemented a random forest (RF) model to predict treatment-seeking based on 91 clinically relevant phenotypes. We calculated AUD PGS for those with genetic data (African ancestry [AFR] n = 3192, European ancestry [EUR] n = 3553) and generated RF models for each ancestry group, first without and then with PGS. Lastly, we developed models stratified by age (&lt; and ≥40 years old).</div></div><div><h3>Results</h3><div>66.6 % reported treatment seeking (M_age=40.0, 62.4 % male). Across models, top predictors included years of alcohol use and related psychological problems, psychiatric diagnoses, and heart disease. In the models without PGS, we found 77.6 % accuracy and 0.829 AUC for EUR and 75.1 % and 0.770 for AFR; the addition of PGS did not substantially change these metrics. PGS was the 9th most important predictor for EUR and 28th for AFR. In the age-stratified analysis, PGS ranked 8th for &lt; 40 and 34th for ≥ 40 in EUR ancestry, and it ranked 70th for &lt; 40 and 78th for ≥ 40 in the AFR sample.</div></div><div><h3>Conclusion</h3><div>Alcohol use, psychiatric issues, and comorbid medical disorders were predictors of treatment seeking. Incorporating PGS did not substantially alter performance, but was a more important predictor in younger individuals with AUD.</div></div>","PeriodicalId":11322,"journal":{"name":"Drug and alcohol dependence","volume":"274 ","pages":"Article 112797"},"PeriodicalIF":3.9,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144670674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Oral methadone versus sublingual buprenorphine for the treatment of acute opioid withdrawal: A triple-blind, double-dummy, randomized control trial","authors":"Anil Shekhawat ,&nbsp;Atul Ambekar ,&nbsp;Alok Agrawal ,&nbsp;Ravindra Venkat Rao ,&nbsp;Ashwani Kumar Mishra ,&nbsp;Arpit Parmar ,&nbsp;Tathagata Biswas","doi":"10.1016/j.drugalcdep.2025.112793","DOIUrl":"10.1016/j.drugalcdep.2025.112793","url":null,"abstract":"<div><h3>Background</h3><div>Opioid use disorder (OUD) is a global problem with treatment involving an initial assisted withdrawal followed by maintenance phase. Methadone and buprenorphine are most commonly used agents for acute opioid withdrawal management (AOWM), but their comparative effectiveness remains uncertain. This study was aimed at comparing the efficacy and safety of oral methadone and sublingual buprenorphine for AOWM in in-patient setting.</div></div><div><h3>Methods</h3><div>A randomized double-dummy clinical trial was conducted with 79 patients (ages 18–60) admitted with OUD a tertiary-care center, New Delhi, India over three years (2017–2019). Participants received either oral methadone (20<!--> <!-->mg/day; n = 40) or sublingual buprenorphine (3.6<!--> <!-->mg/day; n = 39) in a fixed schedule allowing gradual tapering from day 4–10. The primary outcome was treatment completion rate, with secondary outcomes including withdrawal severity (COWS, SOWS scores), opioid craving (VAS), additional medication use, and side effects. The study was conducted after approval from the Institutional Ethics Committee (IEC).</div></div><div><h3>Results</h3><div>Both groups were comparable in terms of sociodemographic and baseline clinical parameters. Both groups had similar treatment completion rates (buprenorphine: 82 %, methadone: 82.5 %; <em>p</em> = 0.95). While both medications significantly reduced withdrawal symptoms and cravings over time, methadone showed greater reductions in withdrawal severity (COWS, SOWS scores; <em>p</em> = 0.01). Side effects were comparable between groups.</div></div><div><h3>Conclusion</h3><div>Methadone and buprenorphine demonstrated similar efficacy in treatment completion rates for acute opioid withdrawal. These findings suggest that methadone, alongside buprenorphine, can be an effective and safe option for acute opioid withdrawal management in inpatient settings.</div></div><div><h3>Trial Registration</h3><div>CTRI/2017/03/0079977</div></div>","PeriodicalId":11322,"journal":{"name":"Drug and alcohol dependence","volume":"274 ","pages":"Article 112793"},"PeriodicalIF":3.9,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144653709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prevalence of congenital heart defects among children with and without diagnosed fetal alcohol spectrum disorders, 2016–2022","authors":"Amanda N. Dorsey ,&nbsp;Karrie F. Downing ,&nbsp;Nicholas P. Deputy ,&nbsp;Mary Kate Weber ,&nbsp;Penelope P. Howards","doi":"10.1016/j.drugalcdep.2025.112790","DOIUrl":"10.1016/j.drugalcdep.2025.112790","url":null,"abstract":"<div><h3>Background</h3><div>Alcohol use during pregnancy might be a risk factor for some congenital heart defects (CHDs), but CHD prevalence among children with fetal alcohol spectrum disorders (FASDs) is not well understood. We used two administrative databases to explore CHD prevalence among U.S. children with and without FASDs.</div></div><div><h3>Methods</h3><div>We limited 2016–2022 Merative™ MarketScan® Multi-State Medicaid and Commercial data to children ≤ 17 years old with ≥ 1 year of continuous enrollment with complete data on mental health and substance use services. CHD prevalence was calculated by FASD status, overall and by age group, using log-binomial prevalence ratios (PRs) and 95 % confidence intervals (CIs). Analyses were repeated after matching on enrollment length, and age and year at the start of enrollment. In the Medicaid sample, we also stratified by demographic characteristics and analyzed severe and non-severe CHD diagnoses separately. Multidimensional bias analysis considered the influence of unmeasured prenatal tobacco exposure.</div></div><div><h3>Results</h3><div>Among 8732,345 children in the Medicaid sample, 5.2 % with FASDs and 1.0 % without FASDs had CHDs (matched cohort PR = 3.4 [CI: 2.8, 4.1]). PRs were similar when stratified by sex and race and ethnicity, and when looking at exclusively severe or non-severe CHDs. Among 10,567,765 children in the commercial claims sample, 3.0 % with FASDs and 0.6 % without FASDs had CHDs (matched cohort PR= 4.6 [CI: 3.3, 6.4]).</div></div><div><h3>Conclusion</h3><div>CHDs were more common among children with FASDs compared to those without FASDs in two administrative database samples. Increased provider awareness about CHDs as a potential FASD comorbidity may improve timely CHD care.</div></div>","PeriodicalId":11322,"journal":{"name":"Drug and alcohol dependence","volume":"274 ","pages":"Article 112790"},"PeriodicalIF":3.9,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144670675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exposure to cannabis marketing in the United States and differences by cannabis laws: Findings from the International Cannabis Policy Study","authors":"Lauren Winfield-Ward ,&nbsp;Elle Wadsworth ,&nbsp;Pete Driezen ,&nbsp;Vicki L. Rynard ,&nbsp;David Hammond","doi":"10.1016/j.drugalcdep.2025.112787","DOIUrl":"10.1016/j.drugalcdep.2025.112787","url":null,"abstract":"<div><h3>Background</h3><div>A growing number of US states have legalized adult “recreational” cannabis; however, there is little evidence on the impact of cannabis policies on cannabis marketing exposure to date. The current study examined marketing exposure in the US, including differences between states where cannabis is illegal (‘illegal’ states), legal for medical use (‘medical’), and legal for recreational use (‘recreational’).</div></div><div><h3>Methods</h3><div>Data are from the US component of the International Cannabis Policy Study: national repeat cross-sectional data from surveys conducted with 187,573 respondents aged 16–65 over 6 annual survey waves (2018–2023). Adjusted mixed effects logistic regression (GLIMMIX) models examined differences in self-reported exposure to cannabis marketing (‘noticing’) by state-level cannabis laws.</div></div><div><h3>Results</h3><div>Self-reported exposure to cannabis marketing differed across policy changes. Noticing cannabis marketing was lowest in illegal states and increased in the first 12-months following medical legalization (35.4 % vs. 39.2 %: AOR=1.16; 95 % CI=1.01–1.33; p = 0.034). Noticing marketing was highest in ‘recreational’ states, with increases in the first 12-months following legalization (50.0 % vs. 41.1 %: AOR=1.41; 95 % CI=1.34–1.48; p &lt; .001), and additional increases 1–3 years (56.2 %: AOR=1.20; 95 % CI=1.14–1.25; p &lt; .001) and 4 or more years following legalization (63.9 %: AOR=1.21; 95 % CI=1.16–1.27; p &lt; .001). Noticing was highest among people who consume cannabis and younger ages.</div></div><div><h3>Conclusions</h3><div>Self-reported exposure to cannabis marketing increases following medical and recreational legalization and is disproportionately noticed by underaged people. Cannabis regulations in ‘legal’ markets should account for marketing, which has been shown to promote cannabis use.</div></div>","PeriodicalId":11322,"journal":{"name":"Drug and alcohol dependence","volume":"274 ","pages":"Article 112787"},"PeriodicalIF":3.9,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144653711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Acceptability and perceived feasibility of restroom motion sensors for overdose detection and response in public bathrooms: A cross-sectional study of businesses and community organizations","authors":"Joseph G. Rosen ,&nbsp;Ryan Koch ,&nbsp;Rehan Aslam ,&nbsp;Gabrielle Riendeau ,&nbsp;Maxwell S. Krieger ,&nbsp;Michelle McKenzie ,&nbsp;Susan E. Ramsey ,&nbsp;Traci C. Green ,&nbsp;Josiah D. Rich ,&nbsp;Ju Nyeong Park","doi":"10.1016/j.drugalcdep.2025.112788","DOIUrl":"10.1016/j.drugalcdep.2025.112788","url":null,"abstract":"<div><h3>Purpose</h3><div>Solitary drug use amplifies fatal overdose risk for people who use drugs. Restroom motion sensors (RMS) are emerging technologies to enhance detection and facilitate rapid response to overdoses in high-traffic public restrooms (where unmonitored drug use is likely to occur), but there has been limited study of employee and staff perspectives on the perceived value and appropriateness of RMS for their workplaces.</div></div><div><h3>Methods</h3><div>From November 2022 to April 2024, we identified business, health, and community organizations in opioid overdose hotspots across eight townships in Rhode Island (United States of America), surveying managers and shift supervisors about the acceptability and perceived feasibility of RMS. We analyzed data descriptively, identifying bivariate correlates of RMS acceptability and feasibility, respectively, using Fisher’s exact tests of association.</div></div><div><h3>Results</h3><div>Participants (median age: 35 years, 53 % cisgender women) across 100 workplaces exhibited low awareness (4 %) but high comfort with RMS being installed (73 %) and confidence (66 %) in implementing RMS in their workplaces in the future. Organizations without staff adequately trained in overdose response were more likely than organizations with trained staff (81 % vs. 64 %, <em>p</em> = 0.055) to endorse confidence in RMS implementation.</div></div><div><h3>Conclusions</h3><div>Management and shift supervisors in heterogenous occupational contexts endorsed RMS’ compatibility and utility in their workplaces, despite low prior awareness of the technology. Efforts to bolster staff competencies in overdose response and equipping workplaces with the necessary tools (i.e., onsite naloxone) to respond appropriately to onsite overdoses will be imperative to successful implementation of RMS in businesses and community organizations.</div></div>","PeriodicalId":11322,"journal":{"name":"Drug and alcohol dependence","volume":"274 ","pages":"Article 112788"},"PeriodicalIF":3.9,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144605889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of the Communities That HEAL intervention on initiation, retention, and linkage to medications for opioid use disorder (MOUD): A cluster randomized wait-list controlled trial","authors":"Jennifer L. Brown ,&nbsp;Marc R. Larochelle ,&nbsp;Laura C. Fanucchi ,&nbsp;Deirdre C. Calvert ,&nbsp;Aimee N.C. Campbell ,&nbsp;Redonna K. Chandler ,&nbsp;Daniel J. Feaster ,&nbsp;LaShawn M. Glasgow ,&nbsp;Erin B. Gibson ,&nbsp;JaNae Holloway ,&nbsp;Michelle R. Lofwall ,&nbsp;Aimee Mack ,&nbsp;Nicole Mack ,&nbsp;Edward V. Nunes ,&nbsp;Jeffery C. Talbert ,&nbsp;Sylvia Tan ,&nbsp;Nathan Vandergrift ,&nbsp;Jennifer Villani ,&nbsp;Kat Asman ,&nbsp;Hermik Babakhanlou-Chase ,&nbsp;Sharon L. Walsh","doi":"10.1016/j.drugalcdep.2025.112785","DOIUrl":"10.1016/j.drugalcdep.2025.112785","url":null,"abstract":"<div><div>Medications for opioid use disorder (MOUD) can reduce opioid use and overdose deaths. This study examined whether the Communities That HEAL (CTH) intervention increased MOUD initiation, retention, and linkage. The HEALing Communities Study was a multi-site, 2-arm, parallel, community-level, cluster-randomized, unblinded, wait-list controlled trial conducted in 67 communities (n = 34 intervention, n = 33 control). Using Prescription Drug Monitoring Programs and Medicaid claims data, we compared mean community-level rates of MOUD outcomes during the 1-year comparison period (July 2021-June 2022) for: (a) MOUD receipt at least once; (b) continuous MOUD receipt for 180 days; and (c) MOUD linkage within 31 days following an opioid-related emergency department or hospital encounter. For intervention and control communities, adjusted rates of receiving MOUD at least once were 578 (95 % CI: 562, 594) and 596 (95 % CI: 572, 621) per 1000 Medicaid enrollees, respectively [adjusted Relative Rate (aRR)= 0.97 (95 % CI: 0.93, 1.01)]. Adjusted rates of receiving MOUD for 180 consecutive days (retention) were 614 (95 % CI: 595, 634) and 620 (95 % CI: 603, 638) per 1000 Medicaid enrollees receiving MOUD at least once for intervention and control communities, respectively [aRR= 0.99 (95 % CI: 0.95, 1.04)]. The adjusted rate of linkage was 280 (95 % CI: 254, 310) and 252 (95 % CI: 226, 281) per 1000 encounters for intervention and control communities, respectively [aRR= 1.11 (95 % CI: 0.96, 1.28). Compared to control communities, communities that received the CTH intervention did not demonstrate higher rates of MOUD use, retention, or linkage. Additional efforts are needed to improve uptake and sustained use of MOUD.</div></div><div><h3>Trial registration</h3><div>ClinicalTrials.gov Identifier: NCT04111939</div></div>","PeriodicalId":11322,"journal":{"name":"Drug and alcohol dependence","volume":"274 ","pages":"Article 112785"},"PeriodicalIF":3.9,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144662951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Associations between local cigarette and e-cigarette prices and smoke-free legislation with prenatal smoking and birth outcomes","authors":"Summer Sherburne Hawkins ,&nbsp;Christopher F. Baum","doi":"10.1016/j.drugalcdep.2025.112777","DOIUrl":"10.1016/j.drugalcdep.2025.112777","url":null,"abstract":"<div><h3>Background</h3><div>While state cigarette taxes have been shown to reduce disparities in prenatal smoking and birth outcomes, less is known about the effects of local tobacco control policies. We examined the associations between county-level cigarette and e-cigarette prices and smoke-free legislation with racial/ethnic and educational disparities in prenatal smoking and birth outcomes.</div></div><div><h3>Methods</h3><div>Using 2013–2018 county-level natality data on 18,663,683 singletons linked to cigarette and e-cigarette price data and smoke-free legislation, we conducted conditional mixed-process models to examine the associations between tobacco control policies and prenatal smoking, then on the associated changes in birth outcomes. We included interactions between race/ethnicity, education, and prices.</div></div><div><h3>Results</h3><div>Cigarette price increases were associated with larger declines in prenatal smoking than e-cigarette prices, with effect sizes decreasing across the educational gradient. Among women with 0–11 years of education, a 10 % increase in cigarette prices was associated with a decrease in smoking by 8.61 percentage points for White women and 2.92 percentage points for Black women and subsequently an increase in their infants’ birth weights by 8.01 and 2.72 g, respectively. Increases in cigarette and e-cigarette smoke-free legislation coverage were associated with small declines in prenatal smoking, but no subsequent changes in birth outcomes.</div></div><div><h3>Conclusions</h3><div>Local cigarette price increases contribute to the flattening of educational gradients in prenatal smoking and birth outcomes, particularly among White and Black women. Local cigarette prices may be more indicative of how fiscal policies influence smoking behavior than state cigarette taxes, particularly for low-educated pregnant women who are more likely to be price sensitive.</div></div>","PeriodicalId":11322,"journal":{"name":"Drug and alcohol dependence","volume":"274 ","pages":"Article 112777"},"PeriodicalIF":3.9,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144611788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Parenting through the eyes of mothers with substance use disorder: Implications for treatment and related services","authors":"Brittany T. Smith ,&nbsp;Danielle D. Davidov ,&nbsp;Meghan Gannon ,&nbsp;Caroline P. Groth ,&nbsp;Alfgeir L. Kristjansson","doi":"10.1016/j.drugalcdep.2025.112782","DOIUrl":"10.1016/j.drugalcdep.2025.112782","url":null,"abstract":"<div><h3>Background</h3><div>Maternal substance use can negatively impact parenting. However, most research on this topic come from epidemiological studies. Thus, the purpose of this study is to qualitatively explore how mothers receiving substance misuse treatment feel their substance use disorder (SUD) has influenced their experiences of motherhood and parenting while also exploring their perception of how their children may have been impacted by their SUD</div></div><div><h3>Methods</h3><div>35 one-on-one semi-structured interviews with mothers receiving substance use treatment were conducted and analyzed using thematic analysis.</div></div><div><h3>Results</h3><div>Four themes emerged from the analysis: 1) Battle between recovery and motherhood, 2) Challenges being fully present as a parent, 3) Parenting within government and legal systems, and 4) Impacts on children. Mothers mostly reported that their SUD did negatively impact their children in numerous ways. However, their SUD was also reported to be a barrier to parenting that brought unique challenges.</div></div><div><h3>Conclusion</h3><div>Parenting and SUD are interrelated and can influence one another. To best serve mothers with SUD and their children this interconnectedness must be considered.</div></div>","PeriodicalId":11322,"journal":{"name":"Drug and alcohol dependence","volume":"274 ","pages":"Article 112782"},"PeriodicalIF":3.9,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144653707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Opioid misuse detection from cognitive and physiological data with temporal fusion deep learning","authors":"Bhanu Gullapalli ,&nbsp;Yunfei Luo ,&nbsp;Tauhidur Rahman ,&nbsp;Eric L. Garland","doi":"10.1016/j.drugalcdep.2025.112774","DOIUrl":"10.1016/j.drugalcdep.2025.112774","url":null,"abstract":"<div><h3>Introduction</h3><div>Machine learning may enable detection of opioid misuse to prevent opioid-related risks including overdose and opioid use disorder.</div></div><div><h3>Methods</h3><div>Here, we collected 9238 datapoints from on-body sensors and cognitive tasks in a sample of 169 patients who were prescribed opioid analgesics to manage chronic pain. We categorized patients into one of two groups using the Current Opioid Misuse Measure (COMM): those showing signs of opioid misuse (MISUSE+, n = 116) and those without signs of opioid misuse (MISUSE-, n = 53). Heart rate variability and respiration rate were assessed while participants completed a Dot Probe task involving shifting attention towards and away from opioid-related and emotional cues, and a Go/No-Go task involving inhibition of automatic responses. Cross-sectional data (e.g., physiological responses, task reaction times, task accuracy) were analyzed with a temporal fusion transformer machine learning (ML) model to predict COMM opioid misuse status. We employed Leave-One-Group-Out (LOGO) cross-validation with the participants divided into 10 groups. Each cycle, one group was held out for testing, ensuring robust, unbiased model validation across different subsets of participants.</div></div><div><h3>Results</h3><div>The ML model showed good predictive performance for identifying opioid misuse (AUC, 0.81; specificity, 0.78; sensitivity, 0.78). Behavioral responses were stronger predictors of misuse status than physiological signals.</div></div><div><h3>Conclusions</h3><div>ML models using data from cognitive tasks and on-body sensors detected opioid misuse with an accuracy comparable to gold-standard self-reported opioid misuse assessments. Wearable sensors may provide only incremental predictive power over behavioral responses. Our ML model should be benchmarked against objective measures of opioid misuse.</div></div>","PeriodicalId":11322,"journal":{"name":"Drug and alcohol dependence","volume":"274 ","pages":"Article 112774"},"PeriodicalIF":3.9,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144662950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Another carfentanil fatal outbreak in Florida?","authors":"Chris Delcher ,&nbsp;Eugene Shin ,&nbsp;Arjun Iyer ,&nbsp;Trokon K. Johnson ,&nbsp;Agnes D. Winokur ,&nbsp;Bruce A. Goldberger","doi":"10.1016/j.drugalcdep.2025.112784","DOIUrl":"10.1016/j.drugalcdep.2025.112784","url":null,"abstract":"<div><h3>Background</h3><div>In 2016 and 2017, carfentanil was implicated in the deadliest fatal outbreak involving a fentanyl analog in the United States with 1190 deaths in Florida alone. Recent surveillance signals suggest that Florida is experiencing a resurgence in carfentanil-involved deaths. The purpose of this paper is to examine carfentanil-involved overdoses using up-to-date medical examiners reports triangulated with carfentanil-related indicators at multiple levels.</div></div><div><h3>Methods</h3><div>Florida’s medical examiner data were analyzed in three periods (2016, 2017, 2018–2023) to examine changes in decedent demographic, geographic, and toxicologic characteristics. We triangulated six additional state and national data sources which included completed death certificates, the National Forensic Laboratory Information System, Reddit mentions, and clinical urine drug tests positive for carfentanil.</div></div><div><h3>Results</h3><div>There were 24 carfentanil-involved deaths in a 2-month period (Dec/Nov 2023). Compared to 2017, recent decedents were significantly older (42.9 years old <em>vs.</em> 37.1 years old, <em>p &lt; 0.0001</em>) with increased exposure to fentanyl (23.4–68.8 %, <em>p &lt; .0001</em>) and methamphetamine (8.5–20.4 %, <em>p = 0.0003</em>). The state’s prior three-county epicenter showed limited involvement (6.5 % vs. 18.9 % total carfentanil deaths) when compared to the prior outbreak. All triangulated national data sources showed strong retrospective concordance. More timely death certificate data suggests that monthly carfentanil deaths were more frequent (<em>mean</em>=4 deaths/mo.) in 2024.</div></div><div><h3>Conclusions</h3><div>The state may have averted a fatal outbreak as of December 2024, but carfentanil deaths have reached new monthly levels with increasingly active signals in other systems. These systems should be monitored regularly to decrease lag time in fatal overdose surveillance for a faster public health response.</div></div>","PeriodicalId":11322,"journal":{"name":"Drug and alcohol dependence","volume":"274 ","pages":"Article 112784"},"PeriodicalIF":3.9,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144633116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}