Addiction

BackgroundPractical alcohol risk-reduction strategies are widely recommended in public-facing alcohol guidance, but randomized evidence from socially interactive drinking episodes remains limited. We conducted a pilot cluster randomized trial to evaluate the feasibility and preliminary effects of a package intervention comprising practical drinking-strategy information, participant self-selection of same-day strategies, and a brief commitment declaration in a social drinking laboratory. MethodsThis single-center, parallel-group pilot trial was conducted in Japan. Pre-existing social groups participated. One or two groups scheduled in the same session slot were combined into a time-slot allocation unit, which was randomized 1:1 either to the package intervention or to alcohol-related knowledge only. The primary outcome was total pure alcohol intake during the first 120 min. Session satisfaction on a Visual Analog Scale (VAS) was a prespecified secondary participant-experience outcome. ResultsOf 83 interested individuals, 63 were randomized and 59 participants in 17 social groups and 12 allocation units were included in the modified intention-to-treat analysis. The mean paired intervention-control difference for 120-min alcohol intake was-8.84 g (95% confidence interval [CI]-27.92 to 10.23; exact sign-flip p = 0.281). The corresponding exploratory 0-30 min difference was-4.90 g (95% CI-10.48 to 0.68; exact sign-flip p = 0.094). In a genotype-adjusted participant-level sensitivity analysis, the intervention coefficient for 120-min intake was-16.0 g (95% CI-30.9 to-1.1; p = 0.036). Session satisfaction was high in both arms with no clear between-arm difference. Next-day follow-up was 100%, and no adverse-event-related discontinuations occurred. ConclusionsThe intervention was feasible to deliver in a socially interactive drinking setting, and session satisfaction was high in both arms. Primary allocation-unit estimates favored lower alcohol intake but were imprecise. Larger trials are needed to estimate effects more precisely, while considering the potential influence of genotype imbalance on effect estimation in East Asian samples. Trial registrationUniversity Hospital Medical Information Network Clinical Trials Registry (UMIN-CTR) UMIN000060685. Registered 17 February 2026.

Objectives: Quantify hazardous alcohol consumption prevalence among individuals at risk of acquiring HIV infection and its association with high-risk sexual behaviors and incident HIV in 11 Eastern and Southern African countries. Design: Secondary analysis of 16 nationally-representative household surveys (2015-2023). Methods: The study included sexually active individuals aged [≥]15 years. Alcohol use patterns were classified using the AUDIT-C (non-drinkers/low-risk drinkers/hazardous non-binge drinkers/hazardous binge drinkers). Outcomes included high-risk sexual behaviors, recent HIV infection, and undiagnosed HIV infection. Survey-weighted alcohol use prevalence and logistic regression were estimated by gender, adjusting for sociodemographic covariates. Model outputs were used to estimate change in incident infections when removing excess risks associated with alcohol use patterns. Results: Analyses included 251,931 participants. Across countries, 5.8%-21.1% reported hazardous binge drinking, and 3.7%-15.7% reported hazardous non-binge drinking, with large gender differences. Sexual risk behaviors increased with drinking severity among men and women. Compared with non-drinkers, alcohol use was associated with higher odds of undiagnosed HIV infection; adjusted odds ratios ranged from 1.32 (1.16-1.50) for low-risk drinkers to 1.52 (1.34-1.72) for hazardous binge drinkers among men, and 1.28 (1.13-1.46) to 1.55 (1.31-1.82) among women. Simulated removal of alcohol-associated excess risk reduced undiagnosed HIV by 15.1% (10.9%-19.4%) among men and 5.8% (4.0%-7.9%) among women. Estimates for recent HIV infection followed a similar pattern but with larger uncertainty. Conclusions: Hazardous alcohol use was associated with sexual risk and HIV infection in Eastern and Southern Africa. Reaching individuals who use alcohol with effective HIV prevention may reduce HIV acquisition risk across the region.

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.

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.

ABSTRACT Background and aims: Mental and behavioral disorders due to use of tobacco (MBDT) present a critical challenge to global health, yet modifiable lifestyle factors for reducing its risk remain poorly understood. Given that dietary fibre can affect mental health through gut-brain communication, we sought to explore how fibre intake relates to MBDT risks in smokers. Methods: We specifically evaluated the link between dietary fibre intake and MBDT within a smoking population. Utilizing the UK Biobank (UKB) database, we performed cross-sectional (N=19,943) and prospective cohort (N=19,885) evaluations applying logistic and Cox proportional hazards models, respectively. To determine potential causality, two-sample Mendelian randomization (MR) was applied, relying on GWAS summary data derived from the IEU Open GWAS Project and FinnGen repositories. Results: Cross-sectional findings indicated that individuals in the top quartile (Q4) of fibre intake exhibited decreased MBDT risks relative to the bottom quartile (Q1) (OR: 0.32, 95% CI: 0.13-0.79). Over a median observation time of 12.84 years, the prospective evaluation demonstrated a notable inverse correlation (Q4 HR: 0.46, 95% CI: 0.40-0.54). Non-linear modeling via restricted cubic splines uncovered an L-shaped dose-response curve. Furthermore, MR results confirmed a genetically predicted protective causality (IVW OR: 0.68, 95% CI: 0.49-0.95), which remained consistent across sensitivity validations. Conclusions: Among smokers, higher dietary fibre intake is robustly associated with a reduced risk of mental and behavioral disorders due to the use of tobacco, offering a modifiable dietary target for public health interventions.

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.

Substance use disorders run in families, yet the mechanisms underlying intergenerational transmission remain unclear. We investigated indirect genetic effects, pathways through which parental genotypes influence offspring phenotypes via the family environment, for alcohol use disorder (AUD), nicotine dependence (ND), and related quantitative outcomes, and aimed to identify family environmental factors through which such effects may operate. Using transmitted and non-transmitted polygenic scores (PGS) constructed for problematic alcohol use, tobacco use disorder, and general addiction liability, we analyzed 5972 European-ancestry adult offspring with at least one genotyped parent from the population-based Lifelines cohort (Netherlands). Offspring outcomes included lifetime DSM-5 AUD diagnosis, AUD symptom count, maximum drinks in 24 hours, Fagerstrom Test for Nicotine Dependence score, and cigarettes per day. AUD findings were meta-analyzed with data from the Brisbane Longitudinal Twin Study (N = 1368; Australia). We also examined parent-of-origin effects and mediation by parental substance use and socioeconomic status using structural equation modeling. Transmitted PGS robustly predicted all AUD and ND outcomes ({beta} = 0.07-0.16; OR = 1.20 for AUD diagnosis). Non-transmitted PGS, indexing indirect genetic effects, were negligible for all clinical syndrome outcomes. The only significant indirect genetic effect was on cigarettes per day ({beta} = 0.03, p = 0.01), mediated by parental smoking behavior but not socioeconomic status. These findings indicate that intergenerational transmission of risk for AUD and ND is driven primarily by direct genetic effects, with modest indirect genetic effects on smoking quantity. Larger samples and cross-trait analyses are needed to further elucidate these mechanisms.

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: 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.

Previous research links Adverse Childhood Experiences (ACEs) with problem gambling, but most studies rely on retrospective reporting and focus narrowly on maltreatment, overlooking adversities such as parental mental health issues. Using data on 3794 young adults in the Avon Longitudinal Study of Parents and Children, we examined longitudinal associations between 10 prospectively measured ACEs (individually and cumulatively), and moderate-risk/problem gambling (Problem Gambling Severity Index >=3) at ages 17, 20 and 24, adjusted for socioeconomic and other background factors. Population attributable fractions (PAFs) estimated proportions of cases potentially attributable to ACEs. Most ACEs were associated with higher odds of moderate-risk/problem gambling across ages (24/30 estimates) after adjustment, though effect sizes were generally small (median adjusted odds ratio [aOR] 1.31, interquartile range 1.24-1.59), and confidence intervals (CIs) wide. Sexual abuse showed the strongest association (aORs 2.4-4.2, CIs 0.5-10.5), while bullying and parental conviction were associated at ages 17 and 20 only, parental separation age 24 only. Evidence for a dose-response relationship was weak. PAFs suggested ACEs accounted for up to 12% of moderate-risk/problem gambling cases. These findings highlight potential impacts of ACEs on later gambling behaviour, but imprecise estimates suggest findings should be interpreted cautiously and strengthened through larger datasets and meta-analyses.

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. 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.

BackgroundSustained retention in care supports continuous access to antiretroviral therapy, routine clinical monitoring, and long-term viral suppression. ObjectiveTo compare the effectiveness of interventions for improving retention in care among people living with HIV (PLHIV). DesignSystematic review and network meta-analysis Data sourcesPubMed, Embase, CINAHL, PsycINFO, Web of Science, and the Cochrane Library from 1995 to December 2024. Eligibility criteriaRandomised controlled trials (RCTs) evaluating interventions to improve retention in care, viral load suppression, or quality of life (QoL) among PLHIV, compared with standard of care (SoC) or other interventions. Data extraction and synthesisPairs of reviewers independently screened studies, extracted data, and assessed risk of bias using ROBUST-RCT. We conducted a fixed-effect frequentist network meta-analysis and rated interventions categories relative to SoC based on effect estimates effects and the certainty of evidence.. Dichotomous outcomes were summarized as odds ratios (ORs) with 95% confidence intervals (CIs), and continuous outcomes as mean differences (MDs) with 95% CI. ResultsEighty-four trials enrolling 107 137 PLHIV evaluated 13 intervention categories. For retention in care, five interventions supported by moderate or high certainty evidence proved superior to SoC: multi-month dispensing (OR 2.02, 95% CI 1.32 to 3.09), task shifting (OR 1.94, 95% CI 1.42 to 2.66), differentiated service delivery (OR 1.47, 95% CI 1.22 to 1.76), behavioural counselling (OR 1.36, 95% CI 1.21 to 1.54), and supportive interventions (OR 1.31, 95% CI 1.11 to 1.55). For viral load suppression, two interventions supported by moderate or high certainty evidence proved superior to SoC: task shifting (OR 2.07, 95% CI 1.25 to 3.43) and behavioural counselling (OR 1.34, 95% CI 1.11 to 1.67). Across outcomes, no intervention demonstrated convincing superiority over other active interventions. ConclusionsAmong 13 intervention categories, only a subset provided moderate or high-certainty evidence of superiority to the standard of care, and no superiority to other interventions. Persistent evidence gaps for key populations, diverse settings, and long-term outcomes support the need for context-sensitive and patient-centred interventions. RegistrationPROSPERO CRD42024589177 Strengths and limitations of this study[tpltrtarr] This systematic review followed Cochrane methods and was reported in accordance with PRISMA-NMA guidelines. [tpltrtarr]The network meta-analysis integrated direct and indirect evidence to compare multiple intervention categories within a single framework. [tpltrtarr]Risk of bias and certainty of evidence were assessed using ROBUST-RCT and the GRADE approach for network meta-analysis, respectively. [tpltrtarr]Some networks were sparse, and limited representation of key populations and long-term follow-up constrained the strength and generalisability of inferences.

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

BackgroundSubstance use initiation in adolescence is influenced by both genetic and environmental factors; however, large-scale genetic studies often treat initiation as a binary outcome and underuse longitudinal timing information. MethodsWe conducted time-to-event (survival) genome-wide association analyses (GWAS) of initiation for four outcomes--alcohol, nicotine, cannabis, and any substance use--using longitudinal follow-up data from the Adolescent Brain Cognitive Development (ABCD) Study. We performed ancestry-stratified GWAS within European (EUR), African (AFR), and Hispanic (HISP) groups, applying consistent quality control and covariate adjustment. Summary statistics were harmonized across ancestries and meta-analyzed using inverse-variance weighted fixed-effects and DerSimonian-Laird random-effects models. We evaluated genomic inflation and heterogeneity (Cochrans Q and I2), identified independent lead variants at genome-wide and suggestive significance thresholds, and assessed cross-trait overlap of associated loci. ResultsIn the multi-ancestry meta-analysis, we observed suggestive association signals across traits (minimum p-values: alcohol [~] 1 x 10-7, any [~] 1 x 10-7, cannabis [~] 5 x 10-8, nicotine [~] 1 x 10-8). Nicotine initiation showed one genome-wide significant variant in both fixed- and random-effects meta-analyses (p < 5 x 10-8). Across traits, suggestive loci demonstrated limited overlap, with the strongest concordance between alcohol and any substance use, consistent with shared liability. Heterogeneity statistics indicated that some loci exhibited cross-ancestry variation in effect estimates. ConclusionsSurvival GWAS leveraging initiation timing can identify genetic signals that may be missed by binary designs and enables principled multi-ancestry synthesis. Our results highlight both shared and trait-specific genetic contributions to early substance initiation and provide a foundation for downstream functional annotation and integrative modeling with environmental risk factors. These findings demonstrate the value of incorporating developmental timing into genetic discovery and provide a framework for integrating longitudinal risk modeling with genomic analyses.

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.

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.

Background Hospital admissions for mental health (MH) and stress related presentations (SRP; symptoms without a clear medical cause which may be psychosomatic in nature) among children and young people (CYP) have risen over time. Rehospitalisation contributes to service costs, may indicate gaps in community based care, and can also disrupt education and social development. Methods This retrospective cohort study used NHS Hospital Episode Statistics to identify all CYP aged 10 to 25 with >1 MH/SRP related hospital admissions in England between 1 April 2014 and 31 March 2018, with follow up until 31 March 2019. Admissions were classified from ICD10 codes into internalising, externalising, personality, and eating disorders, psychosis, self-harm, substance use, postpartum, or potentially psychosomatic diagnostic groups. Outcomes included 30 day all cause readmission, 1 year all cause readmission, and 1 year MH/SRP-specific rehospitalisation. Time to rehospitalisation, and number of MH/SRP readmissions were also evaluated. Clinical and sociodemographic characteristics associated with rehospitalisation were assessed using regression models, time to rehospitalisation using Kaplan Meier analyses, and diagnostic transitions were visualised using Sankey diagrams. Results Of 492,061 CYP with hospital admission for MH/SRP, approximately one third were rehospitalised within one year. Females, older CYP and those from more deprived areas had higher odds of all cause readmission. The odds of MH/SRP rehospitalisation were highest among those aged 14 to 15 years. Co occurring chronic physical health conditions, personality and eating disorders were associated with higher odds, and shorter time, to readmission. Conclusions Rehospitalisation following MH/SRP admissions is common and socioeconomically patterned among CYP. Targeted discharge planning and continuity of care interventions are needed, particularly for high risk CYP admitted with eating and personality disorders.

Regular cannabis use has been associated with alterations in reward-related neural processes, yet findings remain inconsistent and the relationship between neural activity and behavioural performance is not fully understood. The present study aimed to characterise neural and behavioural correlates of reward processing in regular cannabis users (CU) compared with matched non-users (NU) using the Monetary Incentive Delay Task (MIDT). Firstly, we assessed behavioural performance through reaction times, accuracy and monetary earnings to determine whether potential neural alterations were reflected in task performance. Secondly, focusing on reward-related brain regions, we examined group differences in BOLD functional MRI activity during anticipation and outcome phases separately for monetary win and loss conditions. Finally, we explored the association between behavioural performance and neural activation. Our findings indicate that regular cannabis use is associated with altered engagement of key nodes within the mesocorticolimbic circuit during both anticipatory and outcome phases of reward processing, accompanied by impaired behavioural performance. Particularly, compared with NU, CU showed (I) lower striatal activity during anticipation of monetary win and higher ventral striatum and frontal pole activity during anticipation of monetary loss; (II) greater VTA activation during outcome of successful monetary win and loss avoidance and lower frontal pole activity during outcome of unsuccessful loss avoidance; (III) impaired behavioural performance, reflected in lower monetary rewards and a trend towards slower reaction times and reduced accuracy; (IV) disrupted brain-behaviour coupling. Results from this study may help inform future research on the neurobiological mechanisms underlying changes in reward function and the resultant behavioural consequences of cannabis use.