International Journal of Drug Policy

Background: Drug checking services (DCS) promote drug supply awareness among people who use drugs (PWUD) by detecting adulterants such as fentanyl and xylazine that are associated with overdose morbidity and mortality. However, there is limited research on DCS implementation in Latin America (LA). Methods: We conducted a survey of 38 DCS across LA (n=10) and the US (n=28) and compared program characteristics and barriers between these two regions. We also conducted a focus group discussion (FGD) with staff representing six organizations implementing DCS in LA. FGD themes were mapped to constructs quantitatively assessed in the survey. Results: Compared to US DCS, LA DCS more frequently reported funding gaps as a major implementation barrier (80% vs. 54%), law enforcement confiscating DCS supplies (38% vs. 11%), as well as offering supervised drug consumption (30% vs. 4%) and mental health/counseling (40% vs. 18%), but less frequently reported that DCS equipment was legal (44% vs. 75%). DCS on the Mexico-US border focused on people who inject drugs and offered syringe services, supervised consumption, and rapid sexually transmitted infection testing. DCS in central Mexico, Colombia, Peru, and Chile primarily provided DCS for the nightlife community (e.g., attendees of concerts/raves). Barriers to DCS implementation cited by FGD discussants included inadequate funding, DCS legal ambiguities, lack of government support, and cartel violence. Conclusion: DCS in LA would benefit from increased funding, government support, and a more permissive legal environment, thereby strengthening harm reduction efforts and improving safety for PWUD. Keywords: drug checking services; harm reduction; overdose; people who use drugs; Latin America; fentanyl; tusi

Background: Opioid-related mortality in Texas has escalated dramatically, increasingly driven by illicitly manufactured fentanyl. To address local surges in mortality, the Galveston County Health District deployed the Galveston County Opioid Defense Effort (GCODE) in July 2023, leveraging digitally integrated surveillance data from emergency medical services (EMS) and the Medical Examiner to provide targeted naloxone distribution in identified overdose hot spots. Methods: Using a segmented interrupted time series (ITS) design and Poisson regression with robust standard errors, we evaluated the population-level impact of GCODE on opioid-involved mortality through the end of 2025. Data were sourced from the Galveston Area Ambulance Authority (GAAA) and vital statistics (ICD-10 codes). We assessed mortality trajectory changes, the observed fatality ratio among EMS-detected opioid events (the Survival Gap), and demographic and geographic covariates. Results: The Poisson ITS model included 519 weekly observations (N = 14,827 tract-weeks across 101 census tracts). Pre-intervention, opioid mortality increased by 0.16% weekly (IRR = 1.0016; 95% CI: 1.000-1.003; p = 0.011). Following GCODE deployment, the mortality trajectory reversed to a sustained 0.55% weekly decrease (IRR = 0.9945; 95% CI: 0.990-0.999; p = 0.021). The observed fatality ratio among EMS-detected events declined from 7.59% (preintervention mean; SD = 0.111) to 1.71% (post-intervention; SD = 0.042; Chi^2 = 19.824; p = 0.0001). Opioid decedents were significantly younger than the general mortality population (OR = 0.945 per year of age; p < 0.001), and were descriptively more likely to lack documented race/ethnicity data (41.23% vs. 8.27% Unknown; p < 0.001), limiting equity analysis. Conclusions: The findings are consistent with GCODE having meaningfully reduced opioid mortality by substantially lowering event-level lethality. These results suggest that targeted, digitally coordinated harm reduction can decouple overdose incidence from fatal outcomes, with implications for harm reduction program design in structurally constrained environments.

Introduction. Current best practice is for primary care physicians (PCPs) to screen patients for problematic substance use at checkups. However, this practice is not routine, is done in an unstandardized manner, and contributes to the overburdening of PCPs. Screening practices also target current, potentially problematic use behaviors, thus limiting their capacity to help patients prevent problems before they start. Recent scientific advances in identifying people at high risk for substance use problems as a means of facilitating prevention efforts have not yet been integrated into medical practice. To address these issues, our research team developed a freestanding platform called the Comprehensive Addiction Risk Evaluation System (CARES). CARES provides personalized information about genetic and behavioral/environmental risk for substance use disorder (SUD) and connects individuals to resources based on their risk profile. The present study evaluated the potential for adoption and implementation of CARES within a health care system through qualitative interviews with key stakeholders. Methods. Semi-structured interviews were developed using the Consolidated Framework for Implementation Research (CFIR) and conducted with N=15 interviewees. Transcripts were analyzed using rapid qualitative analysis. Results. Key themes included perceived need for new SUD screening tools, current SUD screening procedures and their pros/cons, openness to new ideas and clinical tools, fit of CARES with organizational goals and priorities, considerations for use of CARES with adolescent populations, anticipated patient response to CARES, barriers to implementation and uptake of CARES, changes required for implementation, and possibility for medical record integration. Interviewees generally expressed need for new screening tools and openness to using new tools, but expressed concern that existing provider burden, lack of SUD knowledge, and discomfort/stigma could stymie efforts to implement CARES. Conclusions. There is a clear need for a low-burden, easy-to-use tool for substance use screening. CARES appears to be an acceptable and feasible approach to fill this gap. These findings will be used to inform pilot implementation of CARES in a clinical care setting.

Drug overdose deaths in the United States reached record levels during the fentanyl era before recently declining. A plausible hypothesis is that a sudden drop in fentanyl purity beginning in 2023 caused the downturn in overdose mortality. We evaluated this hypothesis by replicating a published analysis with regional overdose data, using models that account for time trends and autocorrelation, and negative control indicators to test for spurious correlation. When fentanyl purity was rising, the national purity series did not track overdose increases in most regions and showed only a modest association in the West. When both purity and mortality later declined, the observed associations were also seen with unrelated macroeconomic indicators that shared the same time pattern. National fentanyl purity alone does not provide a sufficient explanation for recent overdose declines.

Objectives: To evaluate the effectiveness and cultural feasibility of family-supervised disulfiram as a first-line treatment for alcohol use disorder (AUD) in Sri Lanka, and to compare its clinical outcomes with standard therapy delivered at a tertiary psychiatric unit. Design: Single-blind Randomized Controlled Trial known as ETAT-RCT (Efficacy of Two Alcohol Treatments) was conducted under routine clinical setup with three parallel groups: family-supervised disulfiram, locally developed psychosocial intervention, and routine treatment. Allocation was independently concealed; assessors were blinded. Analyses followed an intention-to-treat approach using repeated-measures ANOVA (group x time). This paper reports the disulfiram (test) versus routine treatment (control) comparison; the psychosocial intervention will be reported separately. Setting: University Psychiatry Unit, National Hospital of Sri Lanka, Colombo (UPU, NHSLC). Participants: Patients aged [&ge;]14 years with AUD presenting to the unit were recruited consecutively without inducements. Planned allocation ratio was 1:1:1 with 31 participants per arm; key exclusions were lifetime psychotic disorder and current contraindication to disulfiram. Randomisation: Participants were randomised into each treatment arm using an independent concealed paper-based allocation system. Intervention: (1) family-supervised disulfiram, with psychoeducation/support only - DT arm, (2) a locally developed denormalization focused psychosocial programme - PT arm, and (3) standard therapy (motivational/cognitive/behavioural input; naltrexone permitted; no disulfiram/denormalisation) - ST arm. Outcome measures: Primary outcome was Alcohol Use Disorders Identification Test (AUDIT) score at 12 months. Key secondary outcomes were past 30 day alcohol use via Timeline Follow-Back (TLFB); alcohol biomarkers [ALT (alanine aminotransferase), {gamma}-GT (gamma-glutamyl transferase), MCV (mean corpuscular volume)]; locally developed measures of addiction-relevant cognitive, affective, behavioural factors [AARSU (Attitude Assessment Related to Substance Use), BARSU (Behaviour Assessment Related to Substance Use)]; and Quality of Life Enjoyment and Satisfaction Questionnaire Short Form (Q-LES-Q-SF). Outcomes were assessed at baseline, 6, and 12 months. Results: Participants in DT (n=33) and ST (n=38) were comparable at baseline. Both groups showed clinically and statistically significant improvement in AUDIT scores over 12 months (DT: F=39.90, p<0.001; ST: F=49.90, p<0.001), with no group x time interaction (F<0.001, p=0.98). Biomarkers and AARSU, and BARSU and Q-LES-Q-SF to a lesser degree, mirrored the AUDIT pattern. TLFB did not change significantly over time in either arm (p>0.05). In moderator analyses, improvement in AUDIT was not moderated by baseline motivation (F=0.20, p=0.89) but was moderated by baseline AUD severity (F=7.70, p=0.007). No serious adverse events were attributed to disulfiram. Adherence to supervised dosing was generally high during periods of supervision but intermittent overall. Conclusions: In this pilot RCT, family-supervised disulfiram achieved 12-month outcomes comparable to standard therapy in a tertiary Sri Lankan setting. Improvements were independent of baseline motivation and varied by baseline AUD severity. These findings may support family-supervised disulfiram as a culturally feasible first-line option in Sri Lanka; larger, adequately powered multicentre trials are warranted to confirm effectiveness and scalability. Trial registration: SLCTR/2014/021

Decarceration, the process of reducing incarceration rates, is increasingly viewed as a strategy to improve population health and reduce health inequities. Yet, evidence on its health effects remains limited and may depend on how decarceration occurs. We developed a national decarceration "atlas" to characterize the mechanisms and dynamics of decarceration across more than 2,800 U.S. counties between 1999-2019. Using longitudinal county-level jail and prison data, we identified four operational types of decarceration: reduced pretrial detention, reduced jail time, reduced prison admissions, and reduced prison time. Nearly two-thirds of counties, including most rural counties, experienced at least one decarceration type during the study period. Declines typically followed periods of recent growth and were relatively modest in magnitude, with median reductions of 19% to 38% ten years after onset. The frequency and timing of decarceration types varied by urbanicity, state, and region, with many counties experiencing multiple mechanisms concurrently. Validation against documented case studies of state and local decarceration demonstrated alignment with known legislative and de facto drivers, while revealing substantial sub-state heterogeneity. This atlas provides a scalable framework and hypothesis-generating resource to support comparative studies of decarceration's heterogeneous health effects.

Background: Firearms are frequently transferred through inheritance and other non-purchase pathways, leaving many individuals in possession of unwanted guns and limited options for safe disposal. This study examined the characteristics and motivations of individuals relinquishing firearms at community gun buyback and destruction events in Michigan to inform understanding of firearm divestment and disposal pathways. Methods: We conducted an explanatory sequential mixed-methods study of six faith-based gun buyback and destruction events held in southeastern Michigan between June and October 2024. Quantitative surveys (n = 109) captured participant demographics and firearm characteristics. Follow-up qualitative interviews (n = 7) explored participants' experiences and motivations using inductive-deductive thematic analysis. Results: Across six events, 151 individuals relinquished 318 firearms, most of which were handguns. Nearly one-third of participants disposed of firearms on behalf of others, and two-thirds of personally owned guns had been obtained through non-purchase transfers, most commonly inheritance. Participants frequently expressed anxiety about storing unwanted firearms and relief after safe disposal. The most common motivations were concern about misuse (59%) and fear of theft (54%). Interviews identified five intersecting themes: inheritance and unwanted firearms, safety and family protection, evolving views on ownership, barriers to legal disposal, and emotional relief and closure after relinquishment. Conclusions: Many individuals become firearm owners through inheritance or other non-purchase transfers rather than intentional acquisition. Their experiences reveal that unwanted firearms can generate sustained unease and moral responsibility, motivating voluntary divestment when safe, non-punitive options are available. Results: Across six events, 151 individuals relinquished 318 firearms, most of which were handguns. Nearly one-third of participants disposed of firearms on behalf of others, and two-thirds of personally owned guns had been obtained through non-purchase transfers, most commonly inheritance. Participants frequently expressed anxiety about storing unwanted firearms and relief after safe disposal. The most common motivations were concern about misuse (59%) and fear of theft (54%). Interviews identified five intersecting themes: inheritance and unwanted firearms, safety and family protection, evolving views on ownership, barriers to legal disposal, and emotional relief and closure after relinquishment. Conclusions: Many individuals become firearm owners through inheritance or other non-purchase transfers rather than intentional acquisition. Their experiences reveal that unwanted firearms can generate sustained unease and moral responsibility, motivating voluntary divestment when safe, non-punitive options are available.

Introduction. Empirical evidence linking specific national structural policies to the provision of key HIV services in low- and middle-income settings remains scarce. This study addresses the research gap by quantifying the within-country relationships between six national structural policy indicators and the presence of the HIV prevention service component targeted at sex workers in Southeast Asia. Methods. We constructed a balanced panel dataset covering eight Southeast Asian countries from 2018 to 2025 from the UNAIDS Global AIDS Monitoring (GAM) framework. We used Fixed-Effects (FE) and Random-Effects (RE) models to analyse the relationships, with the FE model selected as the more statistically appropriate estimator. We enhanced robustness by using clustered standard errors and one-period lagged explanatory variables. Results. The primary finding from the FE model indicated a statistically significant and positive contemporaneous association between the existence of legal or administrative barriers to social protection (barriers_spi,t) and the presence of HIV prevention services for sex workers ({beta} = 0.8531; p < 0.001). However, the robustness check revealed a statistically significant negative association between the two when using the lagged barrier variable (barriers_spi,t-1), suggesting a decline in HIV prevention service availability over time ({beta} = -0.3540; p < 0.05). We did not find any other policy variable's coefficient to be statistically significant in the FE models. Conclusions. While the immediate recognition (contemporaneous effect) of structural barriers to access social protection may occur alongside prioritised HIV prevention service provision, the sustained presence of these impediments acts as a long-term constraint that undermines the effectiveness and sustainability of targeted HIV programmes. National HIV programmes must urgently prioritise the removal of structural barriers to ensure long-term service stability for key populations.

Importance: Understanding patterns of substance use and environmental exposures to tobacco, cannabis, and electronic nicotine delivery systems (ENDS) among youth is critical for developing targeted prevention strategies, particularly as co-use of tobacco, ENDS, and cannabis becomes more prevalent. Objective: To identify latent classes of tobacco, ENDS, and cannabis use, and environmental exposures to these products among adolescents and emerging adults. Design, Setting, and Participants: Data from the Environmental influences on Child Health Outcomes (ECHO) consortium (3rd data release, 2018 to 2022) were analyzed from March 2025 to January 2026. The sample (N=2,786) included early adolescents (ages 11 to 13; n=226, 7.9%), middle adolescents (ages 14 to 17; n=1,248, 43.4%), and late adolescents/emerging adults (ages 18 to 24; n=1,402, 48.7%) from 19 ECHO cohorts. Main Outcomes and Measures: The Youth Risk Behavior Survey, Substance Use module measured experimental and current use of cannabis, ENDS, and tobacco products, as well as daily environmental exposure to tobacco smoke, nicotine aerosols, and cannabis smoke within home and social contexts. A multiple group latent class analysis was used to identify distinct latent classes of substance use and environmental exposure to tobacco smoke, nicotine aerosols, and cannabis smoke and compared class prevalences across early, middle, and late adolescence. Results: Four latent classes were identified, including: No Use/No Exposure (53%), No Use, Polyexposure (10%), Experimental Use/Low Exposure (22%), and Polysubstance Use/High Polyexposure (14%). Cannabis was the most used substance (34% experimental or current use) and the most common source of environmental exposure (20%), followed by ENDS use (26% experimental or current use; 19% environmental exposure) and combustible tobacco (15% use; 19% environmental exposure). The No Use/No Exposure and No Use/Polyexposure classes were primarily made up of early and middle-aged adolescents, whereas the Experimental Use/Low Exposure and Polysubstance Use/High Polyexposure classes primarily consisted of late adolescents and emerging adults. Conclusions: Our study revealed distinct, developmentally patterned groupings of substance use and environmental exposure among US adolescents and emerging adults, highlighting the need for developmentally tailored interventions, messaging, and policies that address both active use and environmental exposure across adolescence.

Objectives: Non-suicidal self-injury (NSSI) and self-harming sexual behaviours share functional and behavioural overlaps. However, the relationship between NSSI and problematic sexual behaviour (PSB) remains underexplored. This study aimed to investigate the association between NSSI and PSB in two cohorts - a non-clinical university cohort and a clinical PSB patient cohort. Methods: Data were collected from 2,189 university participants and 477 clinical PSB patients. NSSI was assessed via self-report, and PSB was measured with the Sexual Addiction Screening Test-Revised (SAST-R) Core. The four core addictive dimensions of PSB: relationship disturbance, loss of control, preoccupation, and affect disturbance, were also evaluated. Logistic regression analyses were conducted to examine the association between PSB (presence/absence and severity) and NSSI, looking at effects of gender and contributions of addictive dimensions of PSB. Results: Rates of NSSI were similar in the university (7.1%) and patient (5.7%) cohorts; stratified by gender, a higher proportion of women PSB patients had NSSI compared to in the university cohort (29.3% vs 9.3%). In the university group, who had milder PSB than patients, PSB was associated with NSSI (OR=2.11, p<0.001); a significant gender by PSB interaction was found showing that women with PSB were over four times more likely to have NSSI than men without PSB (OR=4.44, p=0.037). In contrast, PSB severity was not associated with NSSI in PSB patients (OR=1.10, p=0.25). Associations of the addictive dimensions of PSB with NSSI were observed only in the subgroup of university women, in the 'preoccupation' dimension (p<0.001). Conclusions: Our findings highlight gender-specific patterns in the association between PSB and NSSI, suggesting the need for further research and possibly targeted prevention and intervention strategies in women.

Background: The Adolescent Brain Cognitive Development (ABCD) Study provides rich longitudinal data on environmental, genetic, and behavioral factors related to substance use initiation. Classical marginal structural models (MSMs) require selecting covariates for propensity models, which is challenging when there are many correlated predictors. Methods: We analyzed longitudinal panel data from 11,868 ABCD participants with repeated observations over time. Interval-level binary outcomes were defined for initiation of alcohol, nicotine, cannabis, and any substance, including only participants at risk before initiation. All predictors were constructed as lagged variables to preserve temporal ordering. We used a two-stage machine learning-based causal framework. First, we performed graph discovery using a Granger-inspired lagged predictive modeling approach with elastic-net logistic regression to identify relationships between past predictors and future outcomes. Stable candidate edges were selected using subject-level bootstrap stability selection. Second, we estimated adjusted effects for stable predictors using double machine learning (DML) with partialling-out and cross-fitting. For each predictor, the lagged variable was treated as the exposure and adjusted for high-dimensional lagged covariates. Cross-fitting with group-based splitting accounted for within-subject dependence. Nuisance functions were estimated using random forests, and cluster-robust standard errors were used for inference. Results: We identified stable predictors across multiple domains, including sleep patterns, family environment, peer relationships, behavioral traits, and genetic risk. Many predictors were shared across substance outcomes, while some were outcome-specific. Effect sizes were modest, typically ranging from -0.01 to 0.02 per standard deviation increase in the predictor. Both risk-increasing and protective associations were observed. Risk factors included sleep disturbance and behavioral risk indicators, while protective factors included parental monitoring and structured environments. Conclusions: This study presents a practical framework for analyzing high-dimensional longitudinal data and identifying time-varying predictors of substance use initiation. The approach combines machine learning for variable selection with causal inference for effect estimation. The results highlight both shared and outcome-specific risk factors and identify modifiable targets, such as family environment and sleep, that may inform prevention strategies.

Introduction: Monitoring trends in transitions in the use of electronic nicotine delivery systems (ENDS) and cigarettes among youth is important for understanding the potential public health impacts of these products. Methods: Using a weighted Markov multistate transition model accounting for complex survey design, we estimated transition rates and one-year transition probabilities between never, non-current, ENDS-only, and cigarette use (with or without dual use of ENDS) among 26,744 youth aged 12-17 years who participated in at least two consecutive waves from Waves 2-7.5 (approximately 2015-2023) of the nationally representative Population Assessment of Tobacco and Health (PATH) Study. We also estimated transitions stratified by ages 12-14 and 15-17 years. Results. The one-year probability of ENDS-only initiation from never use among youth peaked in 2017-19 (Waves 4-5) at 4.0% (95%CI: 3.6-4.3%) and was higher for 15-17-year-olds at 5.8% (95%CI: 5.2-6.4%) than 12-14-year-olds at 2.2% (95%CI: 1.8-2.6%). In the following years, ENDS-only initiation rates declined and plateaued, with 2.6% (95%CI: 2.3-3.0%) initiation in 2022-23. Cigarette initiation from never use decreased over 2015-23 from 0.8% (95%CI: 0.6-1.0%) in 2015-16 to 0.1% (95%CI: 0.0-0.2%) in 2022-23. There was an increase in the fraction of youth who transitioned from non-current product use to ENDS-only use from 13.7% (95%CI: 7.5-20.0%) in 2015-16 to 35.1% (95%CI: 25.4-44.8%) in 2022-23, paired with a decrease in non-current use to cigarette use from 20.9% (95%CI: 11.8-30.0%) to 6.3% (95%CI: 1.7-10.8%). Transitions from ENDS-only or cigarette use to non-current use remained relatively constant over time at around 25% and 15% per year, respectively. Conclusion. ENDS-only use initiation has changed over time, peaking around 2019 and subsequently decreasing and plateauing, but cessation rates for both ENDS and cigarettes have remained relatively stable. Thus, interruption of tobacco product initiation may be the most effective approach to reducing tobacco product use among youth.

Background: Early initiation of substance use is linked to later adverse outcomes, and risk factors come from multiple domains and are shared across substances. In our previous work, traditional time-to-event Cox models identified individual risk factors, but these models are not designed to jointly model multiple outcomes or capture complex non-linear relationships. Multi-task learning (MTL) can leverage shared structure across related outcomes to improve prediction and distinguish common versus substance-specific predictors. However, most MTL studies rely on baseline features and focus on single outcomes, which limits their ability to capture shared risk and temporal changes. Substance use initiation is a time-dependent process that unfolds during development and reflects changing exposures over time. Baseline-only models cannot capture these changes or represent risk dynamics. Discrete-time modeling provides a practical approach by estimating interval-level initiation risk and combining it into cumulative risk at the subject level. By integrating multi-task learning with dynamic modeling, it is possible to share information across outcomes while capturing how risk evolves over time, which may improve prediction performance. Methods: Using the Adolescent Brain Cognitive Development (ABCD) Study (release 5.1), we developed two complementary multi-task learning (MTL) frameworks to predict initiation of alcohol, nicotine, cannabis, and any substance use. A baseline MTL model predicted fixed- horizon (48-month) initiation using one record per participant, while a dynamic discrete-time MTL model incorporated longitudinal interval data to model time-varying risk. Both models used multi-domain environmental exposures, core covariates, and polygenic risk scores (PRS). Performance was evaluated on a held-out test set using AUROC, PR-AUC, and calibration metrics, and compared with single-task logistic regression (LR). Feature importance was assessed using permutation importance and compared with Cox proportional hazards models. Results: MTL showed comparable or improved performance relative to LR, with larger gains for low-prevalence outcomes (cannabis and nicotine). Incorporating longitudinal information led to consistent improvements across all outcomes. Dynamic models increased AUROC by +0.044 to +0.062 for MTL and +0.050 to +0.084 for LR, indicating that temporal information was the primary driver of performance gains. Feature importance analyses showed modest overlap across methods, with higher agreement between dynamic MTL and Cox models than static MTL. A small set of features, including externalizing behavior, parental monitoring, and developmental factors, were consistently identified across all approaches. Conclusions: Dynamic multi-task learning improves the prediction of substance use initiation by leveraging longitudinal structure and shared information across outcomes. While MTL provides additional gains, incorporating time-varying information is the dominant factor for improving performance. Combining baseline and dynamic frameworks offers a comprehensive strategy for identifying robust risk factors and modeling adolescent substance use initiation.

BackgroundDespite their potential to serve as a reduced-harm alternative to combustible tobacco, e-cigarette take-up remains low among older (45+) adult smokers, especially in the U.S. While social media is a known driver of vaping attitudes and behaviors in younger populations, its influence on older smokers is poorly understood. This paper provides the first focused analysis of e-cigarette-related social media exposure in this population, documenting its prevalence, characteristics, and attitudinal correlates. MethodsData come from an opt-in survey of U.S. adults (N = 974) recruited via Prolific, comprising three groups: (i) non-vaping smokers aged 45+ (N = 484), (ii) former-smoking vapers aged 45+ (N = 149), and (iii) any-vaping-status smokers aged 18-35 (N = 341). Descriptive statistics, weighted to U.S. population benchmarks, characterize self-reported exposure to e-cigarette-related content on social media. Logistic regressions estimate associations between exposure and intentions for future e-cigarette use, e-cigarette harm perceptions, and related attitudes. ResultsOlder smokers (35.3%) reported exposure to e-cigarette-related content on social media less frequently than both older vapers (44.0%) and younger smokers (72.0%). For older smokers, e-cigarette health risks were the most frequently reported topic of content viewed, followed by youth vaping and e-cigarette addiction. Among this group, exposure was positively associated with stated intentions for future e-cigarette use. Exposure was not significantly associated with perceived e-cigarette harms for any group. ConclusionsFindings provide suggestive evidence that social media exposure may promote e-cigarette adoption among older smokers. However, the cross-sectional design limits causal inference, and the observed associations may reflect selection bias or reverse causality. If a causal relationship exists, the patterns observed suggest that exposure influences e-cigarette adoption through mechanisms other than updating beliefs about e-cigarette risks. While these results tentatively support the potential of social media as a channel for older-smoker harm reduction, any policy applications must carefully weigh privacy concerns and risks to youth. Rigorous experimental studies are needed to confirm these findings and clarify how social media might be leveraged to improve public health outcomes among older smokers.

Background. Young sexual and gender minorities of color face compound health risks shaped by interlocking systems of racism, cisgenderism, and class inequality. Spatial health research documents that place shapes health, but existing methods cannot specify the mechanisms through which spatial configurations produce different health outcomes for differently positioned people. This gap prevents targeted intervention. ObjectiveTo develop and pilot test the Spatial Intersectionality Health Framework (SIHF), which specifies three mechanisms through which space produces intersectional health inequities: Layered (multiple oppressive systems activating simultaneously), Positional (the same space producing different health pathways by intersectional position), and Conditional (nominally protective spaces carrying hidden costs for specific positions). We also introduce and validate Intersectional Geographically-Explicit Ecological Momentary Assessment (IGEMA) as the methodology operationalizing SIHF across three data levels. MethodsThe GeoSense study enrolled 32 young sexual and gender minorities of color (ages 18-29) in New York City. IGEMA was implemented across three integrated levels: (1) GPS mobility tracking via participants personal smartphones, linked to census tract structural exposure indices across n=19 participants; (2) ecological momentary assessment of intersectional discrimination with multilevel modeling of mood, stress, and sleep outcomes; and (3) map-guided qualitative interviews with SIHF mechanism coding and intercoder reliability assessment across 92 coded records from 18 participants. This study was conducted as the pilot for NIH R01HL169503. ResultsAll three SIHF mechanisms were empirically detectable. A compound structural gendered racism index outperformed every single-axis alternative in predicting daily mood (b=-0.048, p=.001) and stress (b=0.121, p<.001). The Positional mechanism accounted for 71% of coded harm experiences. Intercoder reliability for mechanism assignment reached kappa=0.824 at Stage 2 reconciliation. Daily intersectional discrimination predicted greater sleep disturbance (b=1.308, p=.004). ConclusionsSIHF and IGEMA together provide an empirically testable framework for specifying how space produces intersectional health inequities. Mechanism specification, not spatial location alone, is the condition for designing research and intervention that reaches the source of harm for multiply marginalized populations.

Introduction: The Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) is a widely utilized screening tool in large-scale electronic health record (EHR) biobanks. However, its categorical, range-based survey responses present a significant challenge for epidemiological research, especially where continuous quantitative variables may be preferred. Standard workarounds, such as assigning categorical midpoints or utilizing aggregate ordinal scores for regression mapping often introduce false mathematical precision or obscure critical behavioral nuances between drinking frequency and quantity. This report presents a novel framework for presenting and bounding categorical alcohol survey data. Materials and Methods: I developed two complementary descriptive techniques: (1) a two-dimensional cross-tabulation matrix that preserves the interaction between drinking frequency and typical quantity, and (2) a systematic bounding algorithm that applies time-interval correction factors to calculate strict lower and upper estimates of average daily alcohol consumption. To demonstrate the real-world utility of this framework, I applied these methods to three analytical descriptive scenarios within a European ancestry (EUR) cohort of the All of Us Research Program: Generalized Anxiety Disorder (GAD) prevalence (n=104,893), minor allele frequency (MAF) for the rs1229984 genetic variant (n=104,890), and self-reported active duty military service history (n=104,893). Results: Application of the cross-tabulation matrix revealed patterns across all three descriptive scenarios. For example, participants reporting the highest frequency ("4 or more times a week") combined with the highest quantity ("10 or More" drinks) demonstrated a GAD prevalence of 13.5%, compared to 5.8% among those reporting the same frequency but a low quantity ("1 or 2" drinks). A general trend of increased anxiety in higher quantity drinkers contrasts with a general trend of decreased anxiety in higher frequency drinkers. Bounding estimates for average daily consumption ranged from 0.299 to 0.730 drinks for individuals with GAD, and 0.303 to 0.787 for those without. Those who reported having been active duty in the US Armed Forces demonstrated a general trend toward more frequent drinking and higher average daily consumption estimates (0.339 to 0.875) than those who had not (0.297 to 0.770). The minor allele of the genetic variant rs1229984 exhibited a clear effect reducing both frequency and quantity, resulting in lower average daily consumption estimates. Conclusions: This bounding and mapping framework provides researchers with an additional method to traditional midpoint and aggregate scoring methods. By explicitly defining the uncertainty inherent in categorical survey instruments and visualizing cohort distributions across intersecting behavioral axes, this methodology improves the resolution, reproducibility, and interpretability of lifestyle exposure data.

Synthetic cathinones, colloquially called bath salts or flakka, are a group of psychoactive substances used recreationally, including mephedrone and eutylone. Studies examining the prevalence of bath salt use among select samples in the United States have found that approximately 1% of nightclub attendees in New York, high school seniors, and college students have used them. The purpose of this study was to examine the national prevalence of lifetime and past-12-month use of bath salts among a nationally representative sample of persons in the United States from 2021 to 2023. This study also examined nationwide poison center data to identify the number of poisonings from 2021 to 2023 in which bath salt use was intentional and not necessarily an adulterant in another illicitly obtained recreational substance. This study identified the prevalence of lifetime bath salt use among a nationally representative sample of persons 12 years and older in the U.S. to be 0.2% (n = 670,611) in 2021, 0.3% (n = 838,941) in 2022, and 0.3% (n = 836,128) in 2023. The national prevalence of past-12-month bath salt use was 0.0% (n = 111,039) in 2021, 0.1% (n = 167,815) in 2022, and 0.1% (n = 152,276) in 2023. From 2021 to 2023, there were 148 cases in which bath salt use was intentional and involved in a reported poisoning to one of the 55 poison centers in the U.S. Future studies are needed to examine risk factors associated with bath salt-related poisonings.

Abstract Importance Stigma and discrimination against transgender and gender-diverse people are prevalent across many settings and may contribute to substantial health disparities. Objective To synthesize global evidence on the prevalence of stigma, discrimination, and resilience among transgender (trans) and gender-diverse adults. Data Sources A systematic search was conducted in PubMed, Embase, CINAHL, Cochrane Central, LILACS, and PsycInfo for articles published between January 1, 2010 and January 2, 2023. This database search was supplemented by grey literature and secondary reference searches. Article Selection Studies were eligible if they presented primary quantitative data on prevalence of stigma, discrimination, and/or resilience among trans and gender-diverse adults (aged 18 and over), with no restrictions on study design, language, or geographic region. Data Extraction and Synthesis Two independent reviewers extracted data using standardized forms, with discrepancies resolved by consensus. The JBI Critical Appraisal Checklist for Prevalence Articles was used to assess risk of bias. Random effects meta-analysis was conducted for dichotomous prevalence measures using inverse variance weighting and logit transformation; non-dichotomous prevalence data were summarized descriptively. Main Outcomes and Measures Outcomes included prevalence estimates for various forms of stigma (anticipated, perceived, internalized, and experienced), discrimination in legal/institutional settings (housing, healthcare, employment, police/prison), and resilience. Results A total of 97 articles, with data from 72,158 unique trans and gender-diverse participants across 26 countries, met inclusion criteria. Studies showed moderate levels of anticipated stigma, perceived stigma, and internalized stigma. Meta-analyses of 36 studies provided pooled estimates of discrimination prevalence across multiple domains: 21.4% in housing (e.g., eviction, rental denial), 24.6% in healthcare (e.g., denial of care, mistreatment), 32.8% in employment (e.g., hiring bias, workplace harassment), and 39.1% in police/prison settings (e.g., profiling, mistreatment). High heterogeneity was observed across studies, reflecting regional and methodological differences. Resilience scores ranged from moderate to high, indicating variation within trans and gender-diverse communities. Conclusions and Relevance This systematic review and meta-analysis found that stigma and discrimination against trans and gender-diverse adults are pervasive globally. Variation in stigma and discrimination across settings and regions underscores the need for targeted interventions and policy reforms. Funding World Health Organization through a grant from the Elton John AIDS Foundation and the Bill and Melinda Gates Foundation.

Introduction Social media is a central part of young people's lives, yet research on its mental health effects remains mixed. We posit that these inconsistencies stem in part from treating youth as a homogeneous group, obscuring distinct behavioral patterns associated with divergent mental health and wellbeing trajectories. Objectives This study aimed to: (1) explore heterogeneity in social media engagement styles among U.S. youth aged 15-24; and (2) examine how these engagement styles are embedded within a broader system of mental health, wellbeing, emotional regulation, belonging, family and neighborhood context, and stress and adversity. Methods Data were drawn from a 2024 nationally representative cross-sectional survey of 2,563 U.S. youth, conducted as part of the Youth Mental Health Tracker initiative. We employed unsupervised clustering to identify five distinct social media engagement profiles. Subsequently, we used Bayesian network-based causal discovery to examine (a) upstream factors that emerge as drivers of engagement styles and (b) downstream outcomes influenced by profile membership in the learned system. Results Five profiles were identified: the Perpetually Plugged-In (31.3%), characterized by near-constant multifaceted social media use, for both positive and negative purposes across multiple domains of life; the Burned-Out Browsers (21.9%), with high exposure to negative and comparison-based content with frequent attempts to disengage; the Practical Navigators (20.7%) who engage in structured, goal-oriented use focused on learning, hobbies, and maintaining connections; the Positive Engagers (13.6%) with high social and identity-driven engagement; and the Light Touch Users (12.5%) who have low overall engagement and limited reliance on social media for connection, identity, or support. Causal analyses revealed that the Perpetually Plugged-In and Burned-Out Browsers had the worst mental health and wellbeing, with their engagement driven by different reasons. While both engagement profiles were influenced by similar psychosocial risk factors, they were distinguished by their dominant drivers: contemporaneous social stressors (bullying, discrimination, and emotional dysregulation) for Perpetually Plugged-In youth, versus adverse childhood experiences for Burned-Out Browsers. In contrast, Positive Engagers reported high social media engagement alongside the highest levels of social wellbeing, using social media for identity exploration and social support within a context of low cumulative stress and adversity. Conclusions Findings suggest that youth social media risk is not driven by intensity of use alone, but by the interaction between engagement style and offline emotional and social conditions. Policies focused solely on restricting access risk overlooking these differences and may inadvertently sever important sources of connection for many youth. Strategies should identify experiential risk signals while strengthening supportive contexts that enable healthier engagement. Overall, youth social media use is best understood as part of a broader psychosocial system, and recognizing this heterogeneity is essential for designing more targeted, equitable, and evidence-based interventions.

Previous studies have linked opioid use to altered metabolic profiles, but findings have been inconsistent and mechanisms remain unclear. One potential mechanism involves increased adiposity, leading to chronic low-grade inflammation that elevates metabolic risk. Here, we examined metabolic profiles in individuals with opioid use disorder (OUD) and matched non-OUD controls, focusing on the sequential mediating roles of BMI and inflammation. Data from individuals with OUD (n=281) and non-OUD (n=246) were drawn from a natural history screening protocol from the National Institute on Alcohol Abuse and Alcoholism intramural program. Groups were matched on age, sex, race, ethnicity, socioeconomic status, and education via propensity score matching. Metabolic measures included BMI, blood glucose, hemoglobin A1c (HbA1c), and lipid profiles, with lipid imbalance indexed by the atherogenic index of plasma (AIP). Inflammatory markers included C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR). Individuals with OUD had significantly higher BMI (F1,481=12.9, p<0.001), HbA1c (F1,481=10.5, p=0.001), lower high-density lipoprotein cholesterol (HDL-C; F1,481= 46.2, p< 0.001), higher low-density lipoprotein cholesterol (LDL-C; F1, 481=11.9, p< 0.001), and higher AIP (F1,481=20.7, p< 0.001) compared to non-OUD. Inflammatory markers were also elevated in individuals with OUD, including CRP (F1,481=9.4, p=0.002) and ESR (F1,481=7.4, p= 0.007), and statistically mediated group differences in AIP and HbA1c, respectively. Our results are consistent with prior evidence of metabolic dysfunctions in individuals with OUD and suggest inflammation as a contributing mechanism. Targeting metabolic health and inflammation may offer new avenues for improving long-term health outcomes in OUD.