Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
Showing 56 appraisals
PloS one
Integrating smoking cessation into HIV care settings: A systematic review and meta-analysis of effectiveness and the evidence gap in cost-effectiveness.
The prevalence of smoking among people living with HIV (PLWH) is higher than in the general population, and PLWH who smoke are at increased risk of both smoking- and HIV-related comorbidities. As most PLWH reside in low- and middle-income countries (LMICs), there is a need for effective and cost-effective smoking cessation interventions in resource-constrained settings. We systematically reviewed and meta-analyzed the effectiveness of smoking cessation interventions for PLWH and looked for economic evaluations. Four databases (PubMed, Cochrane, Scopus, Web of Science) were searched up to March 23rd, 2026. Interventional and quasi-experimental studies evaluating smoking cessation interventions for PLWH were included. Risk of bias was assessed using Cochrane's risk-of-bias tool for randomized studies and the Effective Public Healthcare Panacea Project tool for non-randomized studies. Thirty-two articles met the inclusion criteria. Most evidence originated from high-income countries, with three randomized controlled trials conducted in LMICs (Kenya, South Africa and Vietnam). No economic evaluations were identified. Smoking cessation interventions varied in type, duration, intensity, and mode of delivery. Overall, studies had low to moderate risk of bias. GRADE assessments indicated moderate-certainty evidence that pharmacological interventions (RR 1.86, 95% CI 1.42-2.45) and tailored, intensive behavioral support (RR 1.34, 95% CI 1.05-1.71) increase smoking abstinence compared with standard care. This review indicates that pharmacological and tailored, intensive behavioral support interventions can support smoking cessation among PLWH, including emerging evidence from LMICs, but the absence of economic evaluations limits guidance for resource-constrained settings. Future research should prioritise implementation strategies and economic evaluations to support scalable integration into routine HIV care. (PROSPERO Registration no: CRD42022313630).
1 Aug 2026
Read appraisal →Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention
Natural language processing tool for extracting information about opioid overdoses in the USA from case narratives in the violent death reporting system.
BACKGROUND: Improving the infrastructure for drug overdose surveillance is critical for identifying new threats and responding to emerging trends. We aimed to develop a prototype tool using the principles of natural language processing that can extract information from the death records of drug overdose victims. METHODS: Data were obtained from the Violent Death Reporting System on drug overdose deaths. Narratives were manually labelled for 12 attributes of interest, totalling 82 labels about the circumstances of the overdose. Narratives were passed through the 'Excel Extractor' to identify and extract a target phrase and subsequently map the extracted phrase to predetermined code values. The output from the Excel Extractor was compared with manually labelled data to determine accuracy. Performance was compared against multiple machine learning models. RESULTS: The Excel Extractor performed well across the attributes of interest, achieving an F1 Score over 0.8 on nine of the 12 attributes. The Excel Extractor was the highest performing model on seven of the 12 attributes. The Excel Extractor achieved an F1 Score of 0.8 or higher on 46 of 82 (56%) of the labels, and a score of 0.9 or higher on nearly one-third (25 out of 82) of the labels. CONCLUSION: This work demonstrates it is feasible to develop a spreadsheet-formula-based natural language processing tool to accurately extract information about drug overdose deaths from narratives; for most attributes, a rule-based search performs well or better than deep learning. The Excel Extractor has the potential to streamline data abstraction for epidemiologists gathering data about drug overdose deaths.
21 July 2026
Read appraisal →Medicine
Effect of physical exercise on executive function in individuals with substance use disorder: A systematic review and meta-analysis
BACKGROUND: The increasing number of individuals with substance use disorder (SUD) has a serious impact on individuals, families, and society. As a complementary therapy, physical exercise has been used in the rehabilitation of individuals with SUD. This study systematically aimed to evaluate the effect of physical exercise interventions on enhancing executive function in individuals with SUD. METHODS: Electronic databases were searched, covering the period from their inception to December 26, 2024. The Cochrane Risk of Bias Assessment Tool was utilized to assess the methodological quality of the included literature. Data were extracted from study graphs using GetData Graph Digitizer 2.26, and Stata 17.0 was also employed to conduct analysis. Grading of recommendations assessment, development and evaluation pro was utilized to evaluate the quality of evidence of outcome indicators. RESULTS: Nine studies, encompassing 752 participants, were included in the analysis. Compared with the control group, physical exercise improved inhibition (Hedges's g = 0.47, 95% CI: 0.29 to 0.65, P < .001) and working memory (Hedges's g = 0.42, 95% CI: 0.16 to 0.69, P = .002), but did not significantly affect cognitive flexibility (Hedges's g = 0.51, 95% CI: -0.22 to 1.24, P = .170). Subgroup analysis revealed that physical exercise with single time of 46 to 60 minutes (Hedges's g = 0.39, 95% CI: 0.05 to 0.73, P = .024), 5 times per week (Hedges's g = 0.45, 95% CI: 0.07 to 0.83, P = .020), duration of 8 weeks (Hedges's g = 0.46, 95% CI: 0.14 to 0.77, P = .004) may improve working memory in individuals with SUD (these subgroup findings are exploratory and should be interpreted as hypothesis-generating). CONCLUSION: Evidence from this study suggests physical exercise may enhance inhibition and working memory in individuals with SUD. However, the improvement in cognitive flexibility requires further investigation in future studies.
19 July 2026
Read appraisal →Journal of behavioral addictions
Efficacy of a mobile-based approach-avoidance task training (PROTECTapp) for problematic usage of the internet in young adults: A randomized controlled trial
BACKGROUND AND AIMS: Problematic usage of the internet (PUI) has been linked to impaired mental health and academic functioning in young adults. This randomized controlled trial evaluated the efficacy of a 3-week mobile-based approach-avoidance task (AAT) training (PROTECTapp) for reducing PUI in university students. METHODS: Ninety-two participants (Mage = 22.00 years, 69.6% women) with elevated levels of PUI were randomized to the PROTECTapp intervention (n = 45) or a waitlist control group (n = 47). Primary outcomes were PUI severity and internet-related craving. Secondary outcomes included motivation to change, psychopathological symptoms and academic functioning. Participants were assessed at baseline and postintervention; the intervention group completed additional 3- and 12-week follow-ups. RESULTS: Intention-to-treat analyses indicated greater reductions in PUI following the PROTECTapp intervention compared to the waitlist (p = .003; d = -0.80, 95% CI [-1.23, -0.38]). No significant effects emerged for craving or broader psychological outcomes (ps > .05), though favorable effects were observed on motivation to change (ambivalence: p = .020; d = -0.24, 95% CI [-0.65, 0.17]; taking steps: p = .002; d = 0.45 [0.04, 0.87]). Satisfaction with the intervention was moderate (M = 18.32 of 32), and participants completed on average 35.52 training sessions. Adverse events were reported infrequent (7.1%). DISCUSSION AND CONCLUSIONS: PROTECTapp is a promising mobile-based intervention to reduce PUI and enhance motivation to change in young adults. Its brevity, scalability, and safety profile highlight its potential as a low-threshold preventive or adjunctive intervention for young individuals at-risk.
18 July 2026
Read appraisal →Journal of behavioral addictions
Problematic internet use and borderline personality features: A systematic review informed by the alternative model of personality disorders.
BACKGROUND AND AIMS: Associations between problematic internet use (PIU) and borderline personality disorder (BPD) have been reported, but the literature is highly heterogeneous, with some studies assessing overall BPD severity and others examining individual traits (e.g., emotional lability, impulsivity, dissociation). This review synthesizes these approaches using the Alternative Model of Personality Disorders (AMPD), examining how BPD-relevant pathological personality traits (Criterion B) and impairments in self and interpersonal functioning (Criterion A) relate to PIU. METHODS: Following PRISMA 2020 guidelines, we searched PsycINFO, Web of Science, PubMed, Embase, and Scopus for studies examining associations between PIU (e.g., general use, social media, gaming, smartphone use) and personality traits or functioning in adults. Study quality was assessed using the NIH Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. RESULTS: Thirty studies (N = 21,358) met inclusion criteria. Emotional lability and impulsivity showed the most consistent associations with PIU across outcome types. Few studies examined impairments in personality functioning, but available evidence suggests that identity disturbance may predict PIU over time and that interpersonal dysfunction is associated with greater use of online environments for reassurance and emotion regulation. Associations involving dissociation and detachment were relatively weak and less consistent. DISCUSSION AND CONCLUSIONS: Studies varied widely in design, measures, and theoretical approach, limiting direct comparison across studies. Despite this heterogeneity, findings indicate that emotional lability, impulsivity, and identity disturbance appear to represent transdiagnostic vulnerabilities that increase risk for PIU and shape patterns of online engagement.
18 July 2026
Read appraisal →JMIR infodemiology
Self-Reported Tianeptine Experiences on Reddit: Natural Language Processing-Assisted Qualitative Study
This study, using natural language processing and manual thematic analysis of Reddit posts, revealed a rapid rise in discussions about tianeptine, with posts frequently reporting dependence, withdrawal, and coingestion with other unregulated substances, highlighting tianeptine as an emerging public health concern.
8 July 2026
Read appraisal →The Journal of international medical research
Examining the state of telehealth for mental health and substance use care after the coronavirus disease 2019 pandemic: An integrative review.
ObjectiveThe objective of this integrative review was to synthesize literature and provide implications for clinical practice on telehealth use among patients with serious mental illness and substance use disorders following the coronavirus disease 2019 pandemic.MethodsAn integrative review guided by Socio-Technical Systems Theory was applied. The PubMed, Cumulative Index to Nursing and Allied Health Literature, PsycINFO, Medline, Academic Search Complete, and Gale Health and Wellness databases were searched for publications from 1 January 2019 to 1 December 2024. Articles selected according to the established inclusion and exclusion criteria were evaluated using a rapid critical appraisal checklist developed by Fineout-Overholt and Melnyk.ResultsAmong the 172 articles reviewed, 16 peer-reviewed and 2 government publications were included. Four themes were identified: (a) treatment adherence; (b) satisfaction reported by patients and providers; (c) telehealth policy developments; and (d) access to services. Telehealth supported continuity of care, improved satisfaction, and improved access. Technological and financial barriers restricted equitable access. Policy changes enabled broader adoption; however, regulatory approaches varied across jurisdictions.ConclusionTelehealth remains an integral method for delivering mental health and substance use care following the coronavirus disease 2019 pandemic. Greater focus is needed on long-term effectiveness and limitations of telehealth.
3 July 2026
Read appraisal →Current opinion in psychiatry
Opportunities and risks of large language models in digital interventions for substance use disorders
PURPOSE OF REVIEW: Large language models (LLMs) are increasingly integrated into digital mental health tools, yet their role in substance use disorder (SUD) interventions remains poorly understood. This review synthesizes emerging evidence on the opportunities and risks of applying LLMs across the digital SUD care continuum. RECENT FINDINGS: Studies report promising applications in early detection, personalized support, continuous monitoring, and relapse prevention. LLMs demonstrate capacity to extract substance-use signals from natural language, generate supportive and motivational responses, and interpret narrative data for patient-reported outcomes. However, risks are substantial. LLMs can produce inaccurate or hallucinated content, may reinforce stigma or demographic bias, and can generate misleading or potentially unsafe advice. Privacy concerns are amplified in SUD contexts, where sensitive data are often managed outside regulated healthcare systems. Existing regulatory frameworks such as the EU AI Act or U.S. device regulations, do not yet provide clear governance for anonymous, AI-supported SUD interventions. SUMMARY: LLMs have potential to expand scalable, low-threshold support for SUDs, but their safe deployment requires validation, bias mitigation, transparent data governance, and robust human oversight. Evidence remains preliminary, and clinical integration should proceed cautiously.
2 July 2026
Read appraisal →PloS one
Long-term effects following prenatal cocaine exposure: A systematic review.
Cocaine use represents a global public-health concern, and children's exposure to this substance is receiving growing attention. Despite the importance of this phenomenon, efforts to isolate cocaine-specific long-term effects are affected by the limited availability of human cohorts followed into adulthood and by the influence of environmental factors and co-exposures. Addressing ongoing debates in the literature, this systematic review synthesizes human evidence on long-term outcomes following prenatal cocaine exposure (PCE), from infancy to early adulthood. A comprehensive search of PubMed and Scopus from inception to August 2025 identified 26 eligible studies. Results suggest that across maturational stages, PCE is consistently associated with early developmental effects (including smaller head circumference and motor delays), deficits in visuospatial, language and executive functions, focal neuroimaging alterations (white-matter microstructure and task-related functional recruitment), growth deficits, and elevated externalizing behaviours. However, evidence is characterised by heterogeneity in exposure assessment, frequent prenatal polysubstance exposure, socioeconomic confounding, caregiving instability and small neuroimaging samples. Overall, this review suggests that PCE is linked to a broad spectrum of detrimental effects and that some biological vulnerabilities associated with PCE may persist. Nonetheless, supportive postnatal environments may mitigate developmental disadvantages and promote better trajectories for affected children. These findings underscore the need for integrated public-health and clinical strategies that combine prevention of prenatal substance use with family-focused postnatal supports.
28 June 2026
Read appraisal →Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco
Efficacy of Yoga in Tobacco Cessation: A Systematic Review and Meta-Analysis
INTRODUCTION: Tobacco consumption is a global epidemic with a high relapse rate. A complementary method like yoga, recognized for addressing psychological and behavioral aspects of addiction, was evaluated in this systematic review and metaanlaysis. METHODS: The objective was to comprehensively summarize the current evidence and evaluate the efficacy of yoga in tobacco cessation. This review was registered with PROSPERO (CRD42025643806). A systematic search across four databases identified randomized controlled trials (RCTs) in English up to September 2024. Eligible studies included adults (≥18 years) using any form of tobacco excluding vaping, randomized to yoga as monotherapy or adjunct therapy. The primary outcome was 7-day point prevalence abstinence (7PPA), while the secondary outcomes included quality of life, depression, anxiety, and mood states. Two reviewers independently extracted data and assessed quality using the Cochrane Risk of Bias (RoB2) tool. A meta-analysis was conducted for outcomes assessed in at least two studies. RESULTS: Seven RCTs were included, with five suitable for meta-analysis. The pooled odds ratio for 7PPA at the end of treatment was 1.50 (95% confidence interval = 0.60 to 3.73), suggesting a positive but inconsistent effect. Considerable heterogeneity was observed (I2 = 65%, p = .07; τ2 = 0.7127), indicating substantial variability across studies. Heterogeneity (I2 = 65%) markedly reduced to 16% when high-risk trials were excluded in sensitivity analysis. Studies reported improvements in depression, anxiety, and quality of life. CONCLUSION: This review consolidates the best available evidence on the effects of yoga interventions for tobacco cessation, showcasing the promising potential of yoga in smoking cessation. IMPLICATIONS: Active yoga styles like hatha, vinyasa, and Iyengar improved 7PPA by reducing stress and depression, while pranayama reduced cravings and negative affect. Future research should explore yoga-based cessation programs in diverse settings, especially low- and middle-income countries, to address unique challenges. Standardizing methodologies across populations will enable a more comprehensive evaluation of yoga's role in tobacco cessation and its potential to enhance global public health outcomes.
25 June 2026
Read appraisal →Cancer
Alcohol consumers' receptivity to artificial intelligence-generated alcohol-cancer risk messages: An experimental study.
BACKGROUND: Alcohol is a group 1 carcinogen linked to seven cancers, yet awareness of this risk remains low in the United State. Identifying effective alcohol-cancer communication strategies is a public health priority. The objective of this study was to test the effects of message specificity (general vs. cancer-specific) and visual intensity (text-only, neutral pictorial, graphic pictorial) on message receptivity (attention, emotional reactions) and precursors of behavior (harm perception; intentions to reduce, limit, or stop drinking) among moderate and heavy alcohol consumers. METHODS: Eight evidence-based text messages were created across two topics: general and cancer-specific harm. Artificial intelligence was used to generate pictorial versions at two intensities: neutral (symbolic, no visible disease) and graphic (explicit health consequences). In a 2025 online within-subject/between-subject crossover experiment, 639 US adult consumers (aged 21 years and older; 49.3% female) each viewed two randomly selected messages (one general, one cancer-specific) presented in three formats (text-only, neutral, and graphic; for six total formats), with counterbalanced order. Linear mixed-effects models were used to estimate differences by intensity, specificity, and drinking levels, reporting regression coefficients (β, 95% confidence intervals). RESULTS: Cancer-specific messages produced greater attention, emotional reactions, and intentions to reduce drinking than general messages (β = 0.10-0.19; p < .05). Graphic pictorials outperformed neutral images on emotional and behavioral outcomes (β = 0.19-0.22; p < .05). Moderate consumers showed stronger perceived harm and message responsiveness than heavy consumers (β = 0.29-0.77; p < .05). CONCLUSIONS: Artificial intelligence-generated alcohol-cancer messages are feasible and effective in strengthening precursors to behavior change. Cancer-specific content and higher visual intensity enhance impact, particularly among moderate consumers, highlighting the importance of tailoring alcohol-cancer communication strategies to different audience characteristics. Many people in the United States are unaware that drinking alcohol increases the risk of several cancers. This study tested different ways of communicating the alcohol–cancer link, including text‐only messages, messages with artificial intelligence–generated images (neutral or graphic), and general versus cancer‐specific content; in addition, the authors examined whether responses differed between moderate drinkers and heavy drinkers. The authors observed that messages with images were more effective than those with text alone, especially when the images clearly showed health harm. Messages that named specific cancers (such as breast or colon cancer) were also more effective than general statements about cancer; however, heavy drinkers, who face the highest cancer risk, were less responsive overall. The findings suggest that effective alcohol–cancer communication should carefully consider what the message says, how it is presented, and who the audience is. Nonstigmatizing, harm‐reduction messages that encourage small, realistic changes and are delivered in supportive settings, such as conversations with health care providers, may work better for heavy drinkers. The study also highlights the promise of artificial intelligence as a tool for developing and tailoring health messages. Future research should explore how different messages influence behavior over time.
15 June 2026
Read appraisal →Journal of epidemiology and community health
Role of socioeconomic status in modifying the relationship between alcohol use and injury events: evidence from the UK Biobank
BACKGROUND: Alcohol consumption is a well-established risk factor for injuries, yet the role of socioeconomic status (SES) in modifying this relationship remains underexplored. This study examines how SES influences the association between alcohol use and injury events, including both fatal and non-fatal injuries as well as the risk of repeated injuries requiring hospitalisation. METHODS: Using data from the UK Biobank, we applied Cox proportional hazards models to assess whether SES modifies the relationship between different dimensions of alcohol use, average level and heavy episodic drinking (HED), and injury events. For injuries requiring hospitalisation, we fitted negative binomial regression models to estimate incidence rate ratios (IRRs) for the total number of unique injury admissions per individual. RESULTS: Among 482 078 participants, 48 045 injuries were recorded during follow-up. A statistically significant interaction was observed between alcohol use and low education, with individuals in lower education groups showing elevated injury risk compared with the high education group, particularly among those consuming 20-40 g/day with HED (HR: 1.17, 95% CI 1.06 to 1.28) and those consuming over 40 g/day (HR: 1.13, 95% CI 1.04 to 1.23). For non-fatal injuries, similar statistically significant interactions were found (IRR 1.17, 95% CI 1.06 to 1.28; and 1.18, 95% CI 1.08 to 1.29, respectively). CONCLUSION: Our findings highlight that individuals with lower SES face higher risks of alcohol-related injuries. Future research should investigate specific mechanisms underlying these disparities to inform more targeted policies. Population-based pricing policies could be combined with community-based programmes and tailored health messaging to address SES-related vulnerabilities.
13 June 2026
Read appraisal →The Journal of clinical psychiatry
Placebo Effects in Alcohol, Cocaine, and Methamphetamine Use Disorder: A Systematic Review and Meta-Analysis
Objective: The placebo effect is established in psychiatry, yet its role in substance use disorders (SUDs) treatment remains unclear. The aim of this study was to evaluate changes in craving scores in placebo groups in randomized controlled trials (RCTs) across different SUDs in adults. Data sources: Eight different databases (PubMed, Embase, Web of Science, Cochrane Library, Emcare, MEDLINE, PsycINFO, and Academic Search) were systematically searched up to October 28, 2024, by 2 independent researchers. Study selection: Placebo-controlled, double-blind RCTs assessing craving in patients with SUDs were included based on predefined eligibility criteria, published in English, Dutch, Spanish, or German language. Search terms were a combination and synonyms of "craving," "addiction," and "placebo." From a total of 1945 unique records identified, 9 articles met our eligibility criteria. Data extraction: Data on demographic characteristics, study design, and outcome results were extracted. Standardized mean differences (SMDs) with 95% confidence intervals (CIs) were calculated for pre-post craving scores within each placebo group; a positive difference point towards improvement in the postplacebo period. Results: A total of n=495 placebo-treated participants were included from nine RCTs in three different SUDs (n=300 in alcohol, n=88 in cocaine, and n=107 in methamphetamine use disorder). Craving scores significantly decreased over time (meaning symptom improvement) in the placebo treatment group in alcohol use disorder (5 studies, SMD=0.93 [95% CI=0.33 to 1.54]) but did not reach statistical significance in cocaine use disorder (2 studies, SMD=0.61 [95% CI=-1.41 to 2.62]) or in (meth)amphetamine use disorder (2 studies, SMD=0.44 [95% CI=-3.43 to 4.32]). Conclusions: Placebo treatment led to reductions in craving scores across all three SUDs, although statistical significance was achieved only in alcohol use disorder. Given the low number of studies for cocaine and (meth)amphetamine use disorder, these estimates were captured with much uncertainty. These findings may inform the design of future RCTs and support the development of more individualized treatment approaches in clinical settings.
13 June 2026
Read appraisal →JMIR research protocols
Implementation of Mobile-Based Programs for Alcohol Cessation in the Treatment of Alcohol-associated Liver Disease: Protocol for a Type 1 Hybrid Implementation-Effectiveness Trial
BACKGROUND: The rising burden of alcohol-associated liver disease (ALD) calls for effective interventions. Alcohol cessation remains the only intervention known to reduce long-term ALD morbidity and mortality. Integrating treatment for alcohol use disorder with medical and hepatology care shows significant promise. OBJECTIVE: This study aims to conduct a randomized, controlled, type 1 hybrid implementation-effectiveness trial in patients with ALD to evaluate an evidence-based smartphone app for alcohol use disorder (Connections). The primary aim is to (1) compare the effectiveness of the Connections app plus usual care to the effectiveness of usual care alone on days of alcohol abstinence for patients with ALD and (2) assess the implementation of the Connections app in the ALD population using a multilevel model of system change to determine facilitators and barriers to the successful adoption of the app at the patient, provider, and clinic levels. METHODS: Study procedures were approved by the Institutional Review Board on March 13, 2024. Patients are recruited from General Hepatology and Multidisciplinary Clinics in Wisconsin and Michigan. Participants are randomized to an intervention (Connections + treatment as usual) or no intervention (treatment as usual). During the 6-month enrollment period, participants complete monthly e-surveys measuring alcohol consumption and quarterly e-surveys measuring patient health indicators and behaviors. Patients earn up to US $240 for participation. RESULTS: This study was funded in September 2023. Recruitment began in June 2024 and is ongoing. As of February 26, 2026, 144 participants have been enrolled in the study. Of these, 65 (45.1%) have completed all the study activities. We aim to recruit 298 participants through 2027, with analysis and results publication estimated in 2028. CONCLUSIONS: Implementation insights highlight the importance of flexibility and strong provider relationships. Challenges include reliance on technology, which limits access for patients with low digital literacy, and the risk of loss to follow-up. This trial is the first fully powered implementation-effectiveness study of a mobile health app for alcohol cessation in ALD, testing a new care model that integrates multidisciplinary expertise. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/94231.
1 June 2026
Read appraisal →JMIR mHealth and uHealth
Effects, Acceptability, and Use of a Dynamically Tailored Mobile What Do You Drink Intervention to Reduce Excessive Drinking Among Adolescents and Young Adults in the Netherlands: Randomized Controlled Trial
BACKGROUND: Excessive alcohol consumption among adolescents and young adults is a serious health problem. Dynamically tailored interventions could reduce their excessive drinking. We therefore developed "What Do You Drink" (WDYD), a 17-week dynamically tailored mHealth (mobile health) intervention providing personalized support on alcohol consumption. OBJECTIVE: We aim to evaluate the effectiveness, acceptability, and use of WDYD in reducing alcohol consumption of adolescents and young adults at risk. METHODS: We conducted a 2-arm, parallel-group randomized controlled trial using ecological momentary assessments. Recruitment was via an educational alcohol program, an online lifestyle monitor, social media advertisements, or news items on websites. Participants downloaded the standalone WDYD app, and when having given active informed consent, were randomized to the intervention or control group. Participants in the intervention group received dynamically tailored feedback sessions on alcohol consumption (wk 0-5, 7, 9, 13, and 17) and goal-monitoring reminders. Both groups completed an online baseline survey, 2 follow-up surveys (wk 9 and 33), and various ecological momentary assessments (7 daily assessments during wk 1, 7, 13, 19, 25, 31, and 33). Participants provided consent before randomization, in which they were informed that 2 study groups existed. After randomization, no disclosure of group assignment was provided, although participants could potentially infer it from receiving tailored sessions vs no tailored sessions. Primary outcomes were excessive drinking, binge drinking, and weekly alcohol consumption. Secondary outcomes were intrinsic motivation, self-confidence, and mood. Acceptability of WDYD was measured by survey questions; use was tracked via app data logs. RESULTS: Analyses were based on data from 1767 participants; 720 in the intervention group and 1047 participants in the control group. Almost half of them were female (2276/4795, 47.5%), and most (3471/4595, 72.4%) participants were aged 18-24 (median 19.40, IQR 2.92) years. The dropout rate was high, up to 96% (4603/4795) in the final 33rd week. No significant effect of WDYD was found on primary outcomes and mood, except for week 1 (excessive drinking: standardized β=-0.35, SE 0.15; 95% CI -0.64 to -0.05; binge drinking: standardized β=-0.36, SE 0.16; 95% CI -0.68 to -0.04; mood: standardized β=0.20, SE 0.06, 95% CI 0.08 to 0.32). Both groups reduced their alcohol consumption. Significant positive effects were found for intrinsic motivation and self-confidence up to 25 weeks (wk 25: standardized β=0.54, SE 0.24; 95% CI 0.06 to 1.02 for motivation; standardized β=0.72, SE 0.26; 95% CI 0.22 to 1.23 for self-confidence). Participants evaluated WDYD as acceptable and usable. CONCLUSIONS: WDYD did not significantly reduce excessive drinking compared to control, but improved motivation and self-confidence. High dropout rates highlight challenges in sustaining engagement in long-term mHealth interventions. Future research should explore strategies to enhance retention and optimize dynamic tailoring.
28 May 2026
Read appraisal →European journal of psychotraumatology
Biological and neurocognitive correlates of comorbid post-traumatic stress disorder and alcohol use disorder: a systematic review
Background: Post-traumatic stress disorder (PTSD) and alcohol use disorder (AUD) frequently co-occur, leading to greater clinical burden than either disorder alone. Despite this, little is known about the biological pathways linking these two disorders.Objective: We conducted a systematic review to synthesize evidence on molecular, genetic, neural, and cognitive mechanisms contributing to comorbid PTSD & AUD.Method: Following PRISMA guidelines, we performed a comprehensive search of five databases using PTSD-related, AUD-related, biological, and neurocognitive terms. Participants had to meet diagnostic criteria for both PTSD and AUD, and studies were required to have a comparator including controls, PTSD only, or AUD only. A critical appraisal was completed for all studies.Results: From 3904 identified papers, 14 met the inclusion criteria. Four studies examined the same molecular marker, with three papers derived from the same cohort, investigating baseline and stress-induced cortisol and adrenocorticotropic hormone, and found no differences unique to PTSD & AUD. One study linked low brain-derived neurotrophic factor and hazardous drinking to PTSD onset over 2 years following hospital admission. Genetic studies showed considerable overlap (72%) between PTSD and AUD in female twins, whereby the DRD2 A1 allele and the absence of the APOE ϵ2 allele were strongly associated with PTSD and drinking. Studies also reported lower neurometabolites, white matter integrity, and hippocampal volume in PTSD & AUD. Critical appraisal of these studies highlighted prominent selection bias (predominantly male and veterans) and limited justification of sample size.Conclusions: These findings suggest that PTSD & AUD may be characterized by distinct neurobiological alterations and genetic vulnerabilities relative to comparator groups. However, as there are currently insufficient data to support or refute these findings, this highlights the need for further research. PTSD and AUD frequently co-occur, leading to greater clinical burden than either disorder alone. Despite this, little is known about the biological pathways linking these two disorders.The current study aimed to review the existing molecular, genetic, neural, and cognitive evidence, and suggests similar impacted stress regulation across PTSD-only, AUD-only, and PTSD & AUD, yet distinct neural and genetic substrates among individuals with PTSD & AUD.Future research should include more female participants and a broader range of trauma types (currently dominated by veteran samples), and use large-scale neuroimaging and genetic datasets to help to identify mechanisms underpinning PTSD & AUD.
27 May 2026
Read appraisal →Journal of medical systems
A Standardized Framework for Evaluating State Opioid Surveillance Dashboards: A Health Informatics Assessment
BACKGROUND: State public health agencies across the U.S. depend on opioid surveillance dashboards to monitor overdose trends and guide interventions. Despite their central role in decision-making, no standardized framework exists to evaluate how well these dashboards actually function. OBJECTIVE: We developed a health informatics framework to systematically assess state opioid surveillance dashboards and applied it across all 50 U.S. states. METHODS: Our framework evaluates dashboards across nine domains (including temporal analysis, geographic granularity, data disaggregation, visualization features, narrative support, simplification techniques, and interactive functionality) using 28 specific sub-variables. Sub-variables were selected based on public health informatics literature on effective dashboard design, including features identified in COVID-19 dashboard evaluations and usability frameworks. We scored each feature as either present or absent, creating composite scores with a theoretical maximum of 28 points. All 50 U.S. state-level dashboards were reviewed twice by the study team, with an external consistency check on a subset of 10 dashboards. We calculated the correlation coefficient between dashboard scores and state population estimates. RESULTS: Dashboard scores varied widely, ranging from 12 to 22 points (mean:19.18, standard deviation:2.20). Three states (Delaware, Indiana, and New York) achieved the highest score of 22 by offering comprehensive geographic detail, extensive data breakdowns, and full interactive capabilities. Interactive filtering was present in 92% of dashboards, but only 80% enabled switching between visualization modes. While nearly all dashboards showed time trends, only 6% provided zip code-level detail, and over a third lacked race and ethnicity data. Single external reviewer demonstrated strong correlation (r = 0.84, p = 0.002). Dashboard scores were not correlated with state population size (r = 0.187, p = 0.193). CONCLUSIONS: State opioid surveillance dashboards varied substantially in observable capabilities. This framework provides a standardized method to compare dashboard features and identify gaps that may inform future refinement.
25 May 2026
Read appraisal →Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco
Training a Smoking Status Probabilistic Model Using Cotinine Levels in a Large Claims Database
INTRODUCTION: Smoking status is an important confounder for many epidemiologic studies, yet it is not well documented in common sources of real-world data, including administrative claims. Probabilistic models can be used to create a proxy for smoking status, yet most published models have been trained using self-reported data. The objective of this study was to train a smoking status probabilistic model using cotinine values available in a large claims database. METHODS: Beneficiaries were included if they had at least one cotinine measurement and were categorized as a "current smoker" if their serum or plasma cotinine value was ≥5 ng/mL or urine cotinine value was ≥30 ng/mL. Predictors were collected across one year prior to the cotinine assessment date. The model was fit using logistic regression with stepwise forward selection. Model performance was assessed using discrimination and calibration. RESULTS: The final model yielded an area under the receiver operating characteristic curve of 0.77 (95%CI:0.75-0.78) and was well calibrated across most prediction deciles. The strongest predictors included diagnosis codes for smoking and drug abuse, and number of medications. The model was found to be highly specific, yet not sensitive at probability cutoffs ≥0.2. CONCLUSIONS: A smoking status model was developed and internally validated for application in claims data, using available cotinine values to define smoking status and found to have acceptable discrimination and calibration. The model is based on 26 predictors, fewer than other similar published smoking status models. External validation of the model should be a next step toward utilizing the model for epidemiological research. IMPLICATIONS: This study tests the utility of cotinine values to validate a smoking status probabilistic model, which has not been done in the literature to date. The results were robust to various cotinine levels used to define smoking status, per current guidance. The final model uses only 26 factors to predict smoking status, simplifying the application of the model in other claims databases.
25 May 2026
Read appraisal →Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco
Patterns of e-Cigarette Use and Smoking Cessation Outcomes: Secondary Analysis of a Large Randomised Controlled Trial to Inform Clinical Advice
INTRODUCTION: Limited data exist on how to use e-cigarettes (EC) to optimize smoking cessation. METHODS: We examined associations between patterns of EC use and outcomes at 1 year in a large trial (N = 886) comparing nicotine replacement therapy (NRT) and EC. RESULTS: Use of tobacco flavor was limited and associated with a lower smoking cessation rate compared to other flavors (relative risk; RR = 0.56, 95% CI = 0.35 to 0.89). EC users reduced nicotine strength over time. Abstainers using EC reported lower urges to smoke than abstainers using NRT at both weeks 1 (b = -0.25, 95% CI = -0.45 to -0.04) and 4 (b = -0.37, 95% CI = -0.58 to -0.16). Participants using both cigarettes and EC (dual users) at week 1 were more likely to stop smoking at week 4 than exclusive smokers (RR = 4.45, 95% CI = 1.96 to 10.10). Dual users at 4 weeks and 6 months were also more likely to achieve validated 50% reduction in smoke intake at 1 year (RR = 2.37, 95% CI = 1.36 to 4.11 and RR = 4.56, 95% CI = 2.71 to 7.66, respectively). CONCLUSIONS: Non-tobacco flavors were preferred and may be also more effective. Urges to smoke were lower in EC users than in users of NRT. Dual use was associated with a reduction in smoking and quitting smoking later on. IMPLICATIONS: Clinicians advising smokers wanting to use EC as a quitting aid can consider recommending non-tobacco flavors; explaining that EC reduce urges to smoke more than combination NRT; and reassuring those worried about dual use that such use is associated with reduced smoking and a higher chance of stopping smoking altogether later on.
25 May 2026
Read appraisal →Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco
Mediators of the Effect of Opt-In Versus Opt-Out Treatment on Smoking Cessation in a Randomized Clinical Trial
INTRODUCTION: Smoking cessation interventions are effective. Most smokers do not receive them, in part because smokers are required to "opt-in". Changing the default (CTD) randomized clinical trial, conducted at a large academic medical center, demonstrated that CTD to providing treatment unless refused (opt-out) improved quit rates. The objective of this study was to evaluate if treatment participation and default-theory based variables explained the effect of opt-out on cessation. METHODS: We conducted a secondary analysis of CTD data (N = 739). Descriptive statistics and correlations of the baseline variables were provided. Structural equation models were employed to investigate whether the treatment assignment was causally mediated by a priori proposed mediators including perceived endorsement, counseling participation, and medication utilization. RESULTS: The mean age of the participants was 51.39 (SD = 14.71) years, among whom 349 (47.23%) were females, and the majority was White (428, 57.92%). The indirect effects from the opt-out treatment arm to counseling participation to smoking cessation (b = 0.201, 95% CI = 0.105 to 0.303), and from opt-out to perceived endorsement to counseling participation to smoking cessation (b = 0.010, 95% CI = 0.002 to 0.022) were significant. The indirect effect from opt-out to perceived endorsement to counseling participation to medication utilization to smoking cessation was marginally significant (b = .001, 95% CI = 0.000 to 0.003). CONCLUSIONS: The opt-out approach enhanced patients' sense that their counselor endorsed and/or recommended treatment, as well as counseling participation. The results partially support our hypothesis that the advantage of Opt-out care would increase treatment participation and would do so by psychological variables thought to underpin the efficacy of defaults. IMPLICATIONS: Our results strengthen evidence for the value of delivering smoking cessation as a default (opt-out rather than opt-in) by illuminating likely mechanisms of action. These include increasing participation in counseling and two default-based theoretical mechanisms, perceived endorsement and implied endorsement.
23 May 2026
Read appraisal →JMIR human factors
Emotion-Adaptive Large Language Model-Driven Clinical Decision Support: User Evaluation of the Empathic Clinical Decision Support System Framework for Trust and Explainability
BACKGROUND: The increasing prevalence of cannabis use has motivated researchers to develop computational behavioral models that predict usage patterns and related health impacts in naturalistic environments. However, the opaque nature of many artificial intelligence (AI) systems limits users' ability to interpret outputs and undermines trust. Existing explainable artificial intelligence techniques often remain overly technical and do not account for the confusion or frustration clinicians may experience when interpreting complex model explanations. OBJECTIVE: We propose and evaluate an empathic clinical decision support system (empathic-CDSS) that integrates large language models (LLMs) with real-time emotion recognition and explainability modules. The goal is to provide transparent, adaptive, and emotionally attuned explanations that enhance interpretability, user confidence, and trust in AI-assisted clinical decision-making. METHODS: Our empathic-CDSS integrates explainable artificial intelligence, causal inference, and affective computing within an interactive LLM-driven framework. Users' affective states were inferred using the circumplex model of affect, which characterizes emotions along 2 dimensions: valence (the degree of pleasure or displeasure) and arousal (the level of physiological activation or energy). Based on the captured emotional signals, the system dynamically adjusts the tone, structure, style, and complexity of its explanations generated by a fine-tuned LLM, enabling personalized and plain-language explanations. A total of 33 participants with diverse medical and technical backgrounds engaged with the system through guided evaluation tasks and postsession assessments to evaluate 6 dimensions of user-centered questions: usability, personalization and relevance of insights, clarity and comprehensibility, system benefits, satisfaction, and trust and reliability. RESULTS: Our empathic-CDSS effectively generated personalized and transparent explanations that revealed the causal reasoning behind model predictions while enhancing users' emotional engagement and trust in the system's decision logic. Continuous, affect-based feedback enabled the system to dynamically adapt explanation delivery to individual user needs. Participants reported significantly improved usability, clarity, satisfaction, and trust compared with a baseline clinical decision support system without emotion adaptation. Improvements were also observed across additional evaluation dimensions, including personalization and perceived system benefits, supporting the feasibility and added value of integrating empathy-aware communication into AI-driven clinical decision support. CONCLUSIONS: This study introduces a transparent, trustworthy, and emotionally adaptive framework for AI-assisted prediction and clinical decision support. By uniting causal reasoning, affective sensing, and LLM-based natural-language explanations, the empathic-CDSS offers a novel direction for developing emotionally intelligent and user-centered AI systems, with potential applications in behavioral monitoring and personalized interventions, including cannabis use and related health domains.
23 May 2026
Read appraisal →Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco
Identifying Key Predictors of Smoking Cessation Success: Text-Based Feature Selection Using a Large Language Model
INTRODUCTION: The most effective way to reduce mortality and morbidity among current smokers is to quit smoking. Although about half of smokers attempted to quit, only one-tenth succeeded in 2022. Understanding key predictors of smoking cessation success would inform smoking cessation interventions and increase quitting rates. METHODS: We analyzed data from waves 5 and 6 of the Population Assessment of Tobacco and Health (PATH) study (December 2018 to November 2021). Using OpenAI's GPT-4.1, we identified the top 45 variables from wave 5 that are highly predictive of 12-month smoking abstinence in wave 6, based on descriptions of survey variables. We then validated the predictive power of the GPT-4.1-selected variables by comparing the performance of eXtreme Gradient Boosting (XGBoost) trained on different sets of variables. Finally, we derived insights into the top 10 variables, ranked according to their SHapley Additive exPlanations values. RESULTS: The performance of XGBoost trained with all possible wave 5 variables and the 45 selected variables was almost identical (AUC:0.749 vs AUC:0.752). The top 10 variables included past 30-day smoking frequency, minutes from waking up to smoking first cigarette, important people's views on tobacco use, prevalence of tobacco use among close associates, daily electronic nicotine product use, emotional dependence, and health harm concerns. CONCLUSIONS: The high predictive performance of XGBoost, when trained on the selected variables, underscores the efficiency and efficacy of GPT-4.1-based feature selection. The top 10 variables include various risk factors that have been previously reported in the literature for their influence on smoking behavior. IMPLICATIONS: Our findings do not establish causal relationships between the selected predictors and 12-month smoking abstinence. However, identifying these key predictors provides valuable insights into the factors highly associated with smoking cessation success. This study demonstrates the ability of OpenAI's GPT-4.1 to perform feature selection using only the textual descriptions of variables. The efficient and successful application of GPT-4.1 for variable selection highlights the potential of integrating artificial intelligence tools into tobacco research to guide resource-efficient and targeted intervention strategies.
23 May 2026
Read appraisal →Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco
Acceptability of Using Large Language Models to Support Smoking Cessation Attempts: a Qualitative Study Among African Americans Who Smoke
INTRODUCTION: African Americans face significant disparities in tobacco-related diseases and access to smoking cessation resources. Digital health interventions using large language models (LLMs) show promise in increasing engagement and successful quit attempts. However, impressions regarding acceptability of LLM-based interventions among African Americans are unknown and evidence suggests such interventions require tailoring for underserved communities. Our goal was to evaluate perceptions of LLM-based interventions among African Americans to inform development of an LLM-based chatbot to support quit attempts. METHODS: We conducted remote focus groups with adult African Americans residing in Minnesota who smoke cigarettes to determine acceptability of LLM-based health interventions and inform the functionality of an LLM-based chatbot supporting quit attempts. Discussions followed a structured guide and were recorded to facilitate analysis. Transcripts were coded independently by two analysts with a shared codebook. RESULTS: 21 adults participated in focus group discussions. 57.1% of participants were female and the mean age was 45.6 (SD, 10.5). Three themes united participants' feedback: (1) participants limited familiarity with LLM and related AI technology, (2) willingness to use an LLM-based app to support quit attempts, and (3) perceptions of features that impact the acceptability of an LLM-based chatbot to support quit attempts. CONCLUSION: African Americans have complex perceptions and expectations regarding the use of LLMs to deliver health interventions. While many recognize the potential benefits, significant concerns and knowledge gaps remain. To build trust and acceptability, intervention developers should prioritize community engagement and ethical guidelines to ensure that LLM-driven solutions are inclusive and effective for multiple communities. IMPLICATIONS: Large language models and related AI technologies have shown promise for improving access and engagement when deployed through digital health interventions. Focus groups with African Americans who smoke combustible cigarettes revealed factors impacting the acceptability in using LLM-based interventions to support quit attempts. Efforts to build digital health interventions should prioritize community engagement to reduce apprehensions and improve alignment with community needs and values.
23 May 2026
Read appraisal →Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco
The Public Health Impacts of Flavored Cigar Bans: A Systematic Review and Meta-Analysis
INTRODUCTION: This review summarizes research on the public health impacts of flavored cigar bans, which are policies that restrict the sale of cigars containing characterizing flavors. METHODS: A systematic literature search was conducted using PubMed, Scopus, PsycINFO, Cumulative Index to Nursing and Allied Health Literature, and Applied Social Sciences Index and Abstracts. Studies were included if they evaluated the impact of a real-world or hypothesized flavored cigar ban. The primary outcome was tobacco use behavior. Secondary outcomes included retailer compliance, sales, and the tobacco industry response to flavored cigar bans. Two reviewers independently screened articles for inclusion, extracted data, and assessed study quality. We also conducted a meta-analysis using random effects models to pool estimates on tobacco use behavior after a flavored cigar ban. This review was registered with PROSPERO (CRD42023481603). RESULTS: Of 2,399 articles identified in the preliminary search, 55 were included in the review. Many real-world studies found declines in cigar use post-ban, specifically among youth. However, other studies found no significant changes in cigar use. Among studies examining sales, there were declines in flavored cigar sales but increases in sales of non-flavored cigars and other tobacco products. Among studies assessing hypothesized tobacco use behavior, pooled results indicate that 8% (95% CI: 2%, 27%) of flavored cigar users intend to quit tobacco altogether, 45% (95% CI: 39%, 50%) would switch to non-flavored cigars or cigarettes, and 41% (95% CI: 32%, 51%) would switch to other tobacco products. CONCLUSIONS: Flavored cigar bans may reduce cigar use and improve public health when policies are comprehensive and well-enforced. IMPLICATIONS: Overall, findings from this review suggest that flavored cigar bans may reduce tobacco use and have the potential to improve public health, but not all research is consistent. Several studies examining the impacts of flavored cigar bans on tobacco use found a decrease in cigar use among youth, but some found that there was no significant change in cigar use. Research on policy impacts among adults is limited. To maximize intended policy impact, monitoring of retailer compliance and the tobacco industry's response to flavored cigar bans is needed.
23 May 2026
Read appraisal →Journal of medical Internet research
Toward Participatory Precision Health With Co-Designed Recommendations: Systematic Review of Just-in-Time Adaptive Interventions in Adolescents and Young Adults
BACKGROUND: The transition from adolescence to young adulthood (age 10-25 years) constitutes a sensitive developmental period marked by rapid biological, psychological, and social change, during which preventive health interventions can shape long-term outcomes. Mobile health tools offer accessible opportunities for tailored support for this population, but often adapt poorly to dynamic contexts, resulting in inconsistent engagement and effects. Just-in-time adaptive interventions (JITAIs), which tailor support in real time using ongoing data, are increasingly explored as precision health strategies. However, how these mechanisms are designed, implemented, and evaluated for adolescents and young adults (AYAs) has not been systematically reviewed. OBJECTIVE: This review aimed to synthesize the evidence on JITAIs developed for AYAs, examine how their adaptive mechanisms have been designed to support specific health goals and changing AYA contexts, and assess methodological reporting quality to inform future precision health intervention development. METHODS: We conducted a systematic review in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and SWiM (Synthesis Without Meta-Analysis) reporting guidelines. Twelve databases were searched for peer-reviewed studies published from 2013 to 2025. Eligible studies focused on participants aged 10 to 25 years and reported real-time adaptive mobile health interventions consistent with JITAI design principles. Two reviewers independently conducted screening, data extraction, and methodological quality appraisal using the Joanna Briggs Institute checklists. AYA coauthors contributed to all phases. Due to substantial heterogeneity in study populations, intervention content, adaptive mechanisms, comparators, and outcome measurements, findings were synthesized narratively, and no meta-analysis was conducted. RESULTS: A total of 61 unique interventions were included. JITAIs for AYAs addressed substance use (n=24, 39.3%), mental health (n=23, 37.7%), and physical health or chronic conditions (n=14, 23%). JITAI tailoring mechanisms relied predominantly on self-reported behavioral data. Decision rules were typically symptom threshold-based, and decision points were commonly daily or event-triggered. Methodological concerns with reporting on intervention administration, participant selection, and outcome measurement reliability were pervasive across all studies, limiting the interpretability of observed effects and cross-study comparisons. Ethical considerations, including researcher positioning and reflexivity, alongside the depth of reporting around participatory AYA engagement in design and implementation, were also inconsistent. CONCLUSIONS: This review contributes a novel perspective to AYA digital health by moving beyond intervention outcomes to examine how core adaptive mechanisms are operationalized for AYAs across multiple health domains, while also integrating AYA perspectives into the interpretation of findings and recommendations. Unlike prior reviews focused primarily on adults or specific conditions, it identifies broader contextual, methodological, and ethical considerations relevant to AYA precision health. These findings highlight the need for more transparent, contextually responsive, and youth-centered adaptive interventions, alongside more rigorous designs for evaluating adaptive intervention components in daily life contexts.
23 May 2026
Read appraisal →BMJ open
Impact of COVID-19-related data drift on machine-learning prognostic models predicting 30-day opioid-related emergency department visits, hospitalisation or mortality: a population-level administrative data study in Alberta, Canada
OBJECTIVE: To develop machine-learning (ML) models during the COVID-19 pandemic and adjacent time periods to evaluate the impact of data drift on model performance. DESIGN: This prognostic study used population-level administrative health data to develop ML prediction models. SETTING: Alberta, Canada during 2019-2023. PARTICIPANTS: All patients over 18 who received at least one opioid dispensation from a community pharmacy within the province of Alberta between 2019-2023. EXPOSURE: Each opioid dispensation served as the unit-of-analysis. MAIN OUTCOMES/MEASURES: Opioid-related outcomes were identified from linked health administrative datasets. Light Gradient Boosting-machine models were developed on pre-pandemic, pandemic and endemic data and temporally validated on 2023 data (pre-pandemic model was also validated on 2020-2021 data) to predict the risk of emergency department visit, hospitalisation or mortality within 30-days of an opioid dispensation. We described key feature distributions across the study time period and changes in model prediction performance on the validation sets using relevant metrics. RESULTS: Among 1.2 million study participants representing over 13 million opioid dispensations, there were 59 809 (2.1%), 134 402 (2.4%) and 62 143 (2.3%) events reported in the pre-pandemic (2019), pandemic (2020 and 2021) and endemic (2022) time periods, respectively (estimated 2023 validation set pre-test probability of 2.8%). Notable differences in key features were observed in the 2020-2021 model relative to other years. In the 2023 validation set, discrimination performance was highest for the pre-pandemic and endemic models compared with the pandemic model (0.81, 0.83, 0.74, respectively). A similar trend regarding changes from pre-test to post-test probabilities in higher categories of predicted risk (23%, 40%, 16%) was observed. 2020-2021 had the lowest discrimination performance (0.71) and uninformative post-test probabilities (<10%). CONCLUSION: COVID-19 pandemic health data contributed to significant ML drift. Although ML approaches allow for quick re-training to mitigate drift, health regulators should approach ML prediction with caution when using pandemic-times data.
23 May 2026
Read appraisal →Journal of medical Internet research
Effect of Integrated Internet-Based Acceptance and Commitment Therapy and Behavioral Activation Among Ethnic Minority Young Adults With Alcohol Use Disorder in Hong Kong: Pilot Randomized Controlled Trial
BACKGROUND: Alcohol use disorder (AUD) profoundly affected ethnic minority young adults due to unique stressors, such as acculturation challenges and discrimination. Our prior studies found that experiential avoidance behavior and discrimination significantly contributed to AUD. These findings warranted third-wave interventions, such as acceptance and commitment therapy (ACT). Nonetheless, barriers to engagement with value-based activities may affect ACT efficacy. Behavioral activation (BA) may be an alternative for this shortcoming. Integrating these interventions has shown promise. However, no studies evaluated its effectiveness in this group. Therefore, evaluating the preliminary effectiveness and feasibility of this intervention was needed. OBJECTIVE: This study aimed to evaluate the feasibility measures. The secondary objective aimed to examine its effectiveness on cumulative abstinence duration, drinking days, drinks per drinking day, heavy drinking days, alcohol abstinence self-efficacy, readiness to change, psychological flexibility (Acceptance and Action Questionnaire-version II), and everyday discrimination score. METHODS: A pilot parallel randomized controlled trial was conducted. Forty young ethnic minorities who can speak English and have AUD based on DSM-5 (Diagnostic and Statistical Manual of Mental Disorders [Fifth Edition]) criteria were recruited and randomly assigned to either Acceptance and Commitment Therapy with Behavioral Activation (ACT-BA; n=20) or Treatment-as-Usual (TAU; n=20) using a computer-generated random number; assessors were blinded to group assignment. Outcomes were collected at baseline (T0) and postintervention (T1). The analysis included descriptive statistics, independent samples t test, chi-square test, and generalized estimating equations with multiple imputations. To further supplement findings, a qualitative interview was conducted. RESULTS: A total of 148 ethnic minority young adults were screened, with an eligibility rate of 38.5% (57/148). Of these, 85.9% (49/57) consented, and among them, 81.6% (40/49) were randomized to either the ACT-BA or TAU. The retention rate was 82.5% (33/40), of which 75% (30/40) completed the postintervention assessment (ACT-BA: 16/20, 80%; TAU: 14/20, 70%). The adherence rate was 81.7% (4.9/6 sessions), and participants reported no adverse effects. Finally, 40 participants (20 for each group) were analyzed. The intervention group showed a promising improvement in drinking days (B=-4.12, 95% CI -8.10 to -0.13; P=.04, d=-0.57), drinks per drinking day (B=-1.56, 95% CI -3.06 to -0.07; P=.04, d=-1.89), alcohol abstinence self-efficacy (B=11.95, 95% CI 0.10-23.81; P=.048, d=0.81), and Acceptance and Action Questionnaire-version II (B=-6.41, 95% CI -12.77 to -0.06; P=.04, d=-0.65). CONCLUSIONS: This study, unlike existing evidence, presents an innovative integration of ACT and BA delivered via an internet-based self-help format. The findings contribute to the field by providing preliminary evidence that this integrated intervention is feasible and promising for AUD. The main implication in the real world is to conduct a fully powered randomized controlled trial to further examine its effectiveness with longer follow-up to serve as a stand-alone treatment option for ethnic minorities.
22 May 2026
Read appraisal →JMIR research protocols
Mobile Health Technology for Personalized Tobacco Cessation Support in Laos (Project Support Laos): Protocol for a Randomized Controlled Trial
BACKGROUND: Tobacco use remains the leading cause of preventable morbidity and mortality in Lao People's Democratic Republic (Lao PDR). Despite the prevalence of cigarette smoking in Lao PDR (51% in men and 7% in women), no national tobacco treatment programs are available. Therefore, the development and evaluation of sustainable tobacco cessation interventions suitable for widespread adoption in Lao PDR are pressing public health needs. OBJECTIVE: This project aims to adapt our theoretically and empirically based mobile health (mHealth) technology to help people quit smoking cigarettes in Lao PDR. METHODS: Our mHealth approach includes a fully automated, interactive, personalized, smartphone-delivered intervention for behavioral treatment. This project includes 2 main phases. In the first phase, we use formative research methods to adapt our intervention content to the sociocultural context, language, and communication styles of Laotians. In the second phase, we conduct a randomized controlled trial to evaluate the efficacy of our mHealth intervention. In the trial, adult smokers are recruited through 2 national hospitals: Setthathirath Hospital in Vientiane and Champasak Hospital in Champasak Province. Participants (n=500) are randomized to either the standard care (SC; n=250) or automated treatment (AT; n=250) group. SC consists of brief advice to quit smoking delivered by research staff, self-help written materials, and a 2-week supply of nicotine replacement therapy (transdermal patches). AT consists of all SC components plus a fully automated smartphone-based treatment program that involves interactive and personalized proactive messages, images, or videos. The primary health outcome of the trial is biochemically confirmed self-reported 7-day point prevalence abstinence 12 months post study enrollment. Secondary outcomes include abstinence at 3 and 6 months post enrollment. RESULTS: This study was approved by the ethical review boards of the respective domestic and international institutions. Data collection for the formative phase occurred from January 2022 to May 2023, and data analyses are ongoing. Data collection for the trial phase is ongoing and is expected to be completed by the end of 2026. CONCLUSIONS: If the proposed project is successful, it has the potential to transform health care services for tobacco treatment throughout Lao PDR and, ultimately, to significantly reduce tobacco-induced morbidity and mortality in the country. The AT's potential for widespread adoption and sustainability is enhanced by the direct involvement of Lao governmental stakeholders at multiple national institutes. Furthermore, the US-Lao collaborative work and capacity-building activities in this project will contribute to creating a knowledge base for mHealth research applications and advancing mHealth research capacity in Lao PDR.
22 May 2026
Read appraisal →JMIR formative research
Development, Feasibility, Acceptability, and Usability of an Artificial Intelligence-Powered Chatbot (Suzy) to Support Patients in Substance Use Disorder Recovery: Multiphase Study
BACKGROUND: Substance use disorder (SUD) remains a major public health crisis in the United States, with significant challenges in treatment access, retention, and workforce capacity. SUD care teams, including addiction medicine physicians and peer recovery coaches (PRCs), support patients receiving SUD treatment but face heavy workloads and burnout. Artificial intelligence (AI) innovations, particularly large language model (LLM)-based chatbots, may extend PRC support and provide patients with on-demand recovery support between clinic visits and PRC contacts. However, evidence on their development, feasibility, acceptability, and usability in addiction services remains limited. OBJECTIVE: This study describes the development, feasibility, acceptability, and usability of an AI-powered health coaching chatbot (Suzy) designed to support patients in SUD recovery. METHODS: A total of 2 clinicians, 5 researchers, and 2 technology developers led a small, multiphase pilot study. In the formative phase, they conducted focus groups and qualitative in-depth interviews with 12 health care professionals and 8 patients with substance use histories to specify chatbot functions and develop a rule-based chatbot. In phase 2, they conducted usability testing of the rule-based chatbot with 8 patients who reported substance use and completed standardized tasks, surveys, and qualitative interviews. Measures included the System Usability Scale (SUS), Net Promoter Score (NPS), and Single Ease of Use Question (SEQ). In phase 3, they developed an LLM-based chatbot co-designed and fine-tuned with PRCs and other SUD experts. RESULTS: Rule-based chatbot functions included craving management, appointment reminders, resource referrals, care team contacts, and goal setting. Usability task testing supported feasibility. In this small pilot sample, quantitative and qualitative feedback indicated acceptability and usability, with an average SUS score of 93 (benchmark 68), an NPS of 63 (benchmark 35), and a mean SEQ score of 6.5/7. Patients valued Suzy's approachable, nonjudgmental language and features that promoted accountability, self-monitoring, and 24/7 availability, while emphasizing that chatbots should supplement but not replace human support. The LLM-based chatbot development emphasized information accuracy, safety escalation protocols to mitigate risks of inappropriate chatbot responses, human-in-the-loop features, and expanded conversational flexibility and personal tailoring. CONCLUSIONS: In this pilot study, a rule-based chatbot designed to support SUD care demonstrated feasibility, usability, and acceptability. LLM-based chatbot development required more robust safety and emergency reporting features, while offering more patient-responsive conversational functions. By providing on-demand coaching, referrals, and reminders, Suzy may extend the reach of care teams, alleviate provider burden, and enhance patient engagement. Additional work is needed to understand how to best integrate Suzy into patients' recovery journeys to ensure human support remains accessible and prioritized. LLM evaluation was based on expert testing and safety review. Clinical effectiveness, including the impact on substance use, was not evaluated. Next steps include evaluating the LLM chatbot in real-world settings with larger samples and assessing its efficacy in reducing substance use.
21 May 2026
Read appraisal →Psychological medicine
Effectiveness of a one-year smoking cessation intervention for people with severe mental illness: results of the KISMET cluster-randomized controlled trial
BACKGROUND: This study evaluated the effectiveness of a one-year smoking cessation intervention for people with severe mental illness compared with treatment as usual (TAU) in outpatient mental healthcare. METHODS: The KISMET study is a pragmatic cluster-randomized controlled trial conducted in 21 outpatient mental healthcare teams in the Netherlands. Eleven teams delivered the KISMET intervention comprising cognitive-behavioral and peer support, combined with optional pharmacological reatment. Ten teams participated in the TAU condition. We collected data between October 2022 and July 2024. The primary outcome was self-reported smoking cessation at 12 months, verified through exhaled carbon monoxide levels below 10 parts per million. Secondary outcomes included depression and anxiety (HADS), severity of psychotic symptoms (PANSS-6), quality of life (SF-12), disease self-management (PAM-13), lipid profile, blood pressure, body mass index, glucose level, and physical fitness. Crude and adjusted linear and multivariable logistic regression and mixed model analyses were performed. RESULTS: Eighty-nine participants were included in the KISMET intervention and 44 in TAU. Smoking cessation rates were significantly higher in the KISMET group at 3 months (OR 12.1, 95% CI 1.4 to 103.7) and at 12 months (OR 4.2, 95% CI 1.0 to 17.2) but not at 6 months (OR 1.9, 95% CI 0.5 to 6.9). No significant differences between groups were found for secondary outcomes. Dropout rates were 58% in the intervention and 32% in the TAU group. CONCLUSIONS: The KISMET intervention shows potential without signs of physical or psychopathological complications. However, results must be interpreted with the high dropout rates in mind.
17 May 2026
Read appraisal →JMIR mHealth and uHealth
Smartphone Apps for Cannabis Cessation: Quality Assessment and Content Analysis
BACKGROUND: Over the past 2 decades, global rates of cannabis use have risen significantly, especially among young adults. This has corresponded to an increase in cannabis-related problems and hospitalizations. Thus, there has been significant interest in developing new interventions that can help facilitate cannabis cessation and reduce hospitalization rates. Specifically, mobile apps have emerged as scalable and accessible stand-alone or adjunct interventions that can help individuals with cannabis use disorders. OBJECTIVE: This study aimed to evaluate the quality of free cannabis cessation apps available on both the Apple App Store and Google Play Store, focusing on the analysis of their features, content, and adherence to evidence-based practices. METHODS: A systematic search was conducted in April 2023 using a variety of keywords. The apps were deemed eligible if they were free, available in English, accessible on both the Apple App Store and the Google Play Store, and related to cannabis cessation. Eligible apps were used for at least 1 month and were rated on the Mobile App Rating Scale by 2 reviewers. Interrater reliability was excellent, with a weighted Cohen κ of 0.893 (95% CI 0.835-0.943). RESULTS: Four apps were included in the analysis, namely, "Grounded-Quit Weed," "Quit Weed," "Marijuana Addiction Calendar," and "Marijuana Anonymous." The mean overall quality score of the apps was 3.4 out of 5, indicating poor to acceptable quality. The apps scored the highest on the "functionality" section and the lowest on the "information" section. Of the 4 apps, 3 focused on tracking cannabis use and duration of abstinence, whereas 1 focused on peer support. A limited number of cannabis cessation apps were identified, and those that were available were of low quality due to a lack of evidence-based information. CONCLUSIONS: This study is the first to evaluate the current availability and quality of mobile apps designed for cannabis cessation. Unlike previous research that broadly assessed cannabis-related mobile apps, this study focuses on the limited number of free cannabis cessation tools, reflecting what is most available to the general population. The findings highlight a significant gap between the growing demand for virtual cessation tools and the quality of existing options. With the rising global prevalence of cannabis use disorders, there is an increasing need for robust, accessible, and evidence-based therapeutic options. While mobile health apps may be a viable option to support cannabis cessation, the current landscape is limited by poor quality apps and a lack of evidence-based information. From a real-world perspective, this study highlights the need for users to exercise caution when relying on current cannabis cessation apps and underscores the urgent need for the development and evaluation of new evidence-based digital interventions.
17 May 2026
Read appraisal →PloS one
Optimising supervised machine learning algorithms predicting cigarette cravings and lapses for a smoking cessation just-in-time adaptive intervention (JITAI).
This study aimed to optimise the balance between participant burden and algorithm performance for predicting high-risk moments in a smoking cessation just-in-time adaptive intervention (JITAI) by systematically varying ecological momentary assessment (EMA) prompt frequency, predictor count, and training data source. Thirty-seven participants completed 16 EMAs per day for the first 10 days of their smoking cessation attempt, reporting mood, context, behaviour, cravings, and smoking lapses. Random forest algorithms predicting lapses and cravings were evaluated in terms of F1-score and ROC-AUC via mixed effects models accounting for clustering within individuals. Performance across out-of-sample individuals ranged from excellent to poor but was, on average, modest. Lapse prediction outperformed craving prediction, particularly for ROC-AUC (Median F1-score: Lapses 0.436 [IQR 0.180-0.625], Cravings 0.400 [IQR 0.048-0.649]; Median ROC-AUC: Lapses 0.659 [IQR 0.514-0.809], Cravings 0.628 [IQR: 0.510-0.729]). A substantial proportion of configurations fell below commonly used minimum performance thresholds, particularly for F1-score. Reducing EMA frequency had outcome- and metric-dependent effects. Lapse F1-scores improved with fewer prompts (16 EMAs: 0.254 [IQR 0.081-0.500], 3 EMAs: 0.588 [IQR 0.353-0.667]), while ROC-AUC showed a slight, inconsistent decline (16 EMAs: 0.661 [IQR 0.520-876], 4 EMAs: 0.613 [IQR 0.494-0.786], 3 EMAs: 0.704 [IQR 0.567-0.809]). For cravings, both metrics declined with fewer prompts (F1-score: 16 EMAs: 0.470 [IQR 0.141-0.745]; 3 EMAs: 0.333 [IQR 0.000-0.600]; ROC-AUC: 16 EMAs 0.700 [IQR 0.582-0.811], 3 EMAs 0.544 [IQR 0.421-0.676]). Feature reduction had negligible impact on lapse prediction (F1-score: all features 0.435, selected features 0.441; ROC-AUC: all 0.660, selected 0.657), but slightly reduced craving performance (F1-score: all 0.410 [IQR 0.117-0.646], selected 0.400 [IQR 0.000-0.650]; ROC-AUC: all 0.632, selected 0.622). Including participant-specific data improved lapse F1-scores (None 0.286 [IQR 0.000-0.571], 30 pc 0.542 [IQR: 0.329-0.667]), but not ROC-AUC (None 0.655 [IQR: 0.512-0.786], 30 pc 0.694 [IQR 0.513-0.852]); and impaired craving ROC-AUC (None 0.650 [IQR: 0.544-0.734], 30 pc 0.614 [IQR 0.493-0.730]; F1-score: None 0.424 [IQR 0.143-0.649], 30 pc 0.400 [IQR 0.000-0.703]). Overall, EMA-based machine learning detected lapse risk but showed modest overall performance and substantial inter-individual variability. Algorithms using higher EMA density, larger predictor sets, and participant-specific training data did not consistently outperform over more parsimonious approaches. However, machine learning prediction alone is unlikely to be sufficient for real-world JITAI implementation and may be best combined with complementary rules-based approaches.
16 May 2026
Read appraisal →European journal of psychotraumatology
Attenuating trauma- and cocaine-related intrusions by blocking memory reconsolidation with minocycline: protocol for a transdiagnostic randomized controlled trial
Background: Post-traumatic stress disorder (PTSD) and substance use disorders frequently co-occur, with their comorbidity linked to poorer treatment outcomes. Beyond this epidemiological overlap, PTSD and, in particular, cocaine use disorder (CUD) have also been conceptually linked, as maladaptive memory processes are thought to play a central role in both of their etiopathogeneses. PTSD and CUD are each characterized by intrusive memories - either trauma or cocaine related - that sustain distress and craving, respectively. These parallels have motivated transdiagnostic mechanistic research targeting memory reconsolidation. Matrix metalloproteinase-9 (MMP-9) is critically involved in synaptic plasticity and memory updating, and has been suggested as a pharmacological entry point for modulating reconsolidation-related processes.Objective: This study examines whether pharmacological interference with reconsolidation via MMP-9 inhibition by minocycline modulates trauma- and cocaine-related intrusive memories and their neurobiological correlates in PTSD and CUD.Method: In this monocentric, randomized, double-blind, placebo-controlled trial (NCT05902819), individuals with PTSD (n = 60) or CUD (n = 60) receive a single dose of minocycline - a tetracycline inhibiting MMP-9 - or placebo prior to an individualized, imagery-based reactivation of their most salient intrusive memory. Intrusive memories in day-to-day life are assessed using event-based ecological momentary assessment and pre-post intrusion questionnaires. Neurobiological correlates of maladaptive memory processing are indexed through functional magnetic resonance imaging and magnetic resonance spectroscopy, and peripheral biomarkers are obtained from blood, urine, and hair samples. Diagnostic status and comorbid symptoms are characterized using clinical interviews and standardized self-report measures.Conclusions: This trial adopts a mechanistic framework to investigate whether minocycline-augmented memory reactivation modulates intrusions and associated neurobiological markers in PTSD and CUD. By directly targeting candidate memory mechanisms shared by both disorders, it evaluates a transdiagnostic reconsolidation-based approach and is expected to inform models of intrusive memory persistence and updating. The findings may guide future development of memory-focused interventions in trauma- and addiction-related disorders. This randomized controlled trial evaluates a transdiagnostic, mechanism-focused intervention targeting maladaptive memory processes in PTSD and cocaine use disorder.Minocycline is used as an MMP-9 inhibitor to modulate intrusive trauma- and cocaine-related memories following brief imagery-based memory reactivation.The study integrates multimodal neurobiological assessments (fMRI, MRS, peripheral biomarkers) with ecological momentary intrusion measures to characterize changes in memory-related mechanisms.
14 May 2026
Read appraisal →JMIR mental health
Therapeutic Interventions Targeted at Problematic Use of Digital Technology: Systematic Review and Meta-Analysis of Evidence
BACKGROUND: Problematic use of digital technology has increased across the world. Despite growing research, evidence on treatment effectiveness across digital behaviors remains fragmented. OBJECTIVE: This study aimed to systematically evaluate and compare the effectiveness of therapeutic interventions targeted at problematic use of digital technology across various behavioral domains. METHODS: A systematic review and meta-analysis was conducted in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines (PROSPERO: CRD420251052442). Electronic searches of PubMed, Scopus, and Embase (up to April 2025) were conducted. It identified 125 eligible studies, including 73 randomized controlled trials (RCTs), 32 non-RCTs, 14 pre-post studies, and 6 pilot studies. The interventions that were assessed in these studies included psychological therapies, digital or web-based programs, exercise-based interventions, pharmacological treatments, neuromodulation, parent-focused programs, virtual reality-based interventions, educational programs, and multicomponent approaches. Random-effects meta-analyses using standardized mean differences (SMDs) were performed. RESULTS: For problematic internet use, psychological treatments showed a strong effect (effect size=-2.68; P<.001). Digital interventions also showed significant benefit (effect size=-1.16; P<.001). For smartphone addiction, psychological treatments (effect size=-1.49; P<.001) and exercise-based programs (effect size=-3.07; P=.001) showed significant improvement. For gaming disorder, psychological treatments showed improvement (effect size=-1.01; P=.02), but results were mixed. There were limited studies to calculate pooled results for social media addiction, pornography use, gambling, screen time, and over-the-top content watching. No treatment studies were found for problematic over-the-top content watching. High heterogeneity and evidence of small-study effects were observed in several studies. CONCLUSIONS: Overall, structured psychological therapies showed the most consistent benefit. These findings support structured interventions that aim for control of use and reduce cues linked to high use. Evidence remains limited for several emerging digital behaviors. More high-quality studies are needed in clinical settings and for less-studied forms of digital addiction.
14 May 2026
Read appraisal →BMC psychiatry
N-acetylcysteine for patients with alcohol use disorder, post-traumatic stress disorder, and their co-occurrence: a systematic review of placebo-controlled randomized trials
INTRODUCTION: Alcohol use disorder (AUD) and post-traumatic stress disorder (PTSD) are thought to be significant global contributors to the burden of mental illness. According to recent WHO epidemiological estimates, 3.9% of people worldwide have experienced PTSD at some point in their lives; this number rises to roughly 5.6% among those who have experienced trauma. NAC has shown promise in reducing PTSD symptoms and cravings in veterans, according to recent trials. Our analysis aims to resolve the conflict between results and determine whether NAC is an effective add-on therapy for PTSD, AUD, and co-occurring PTSD/AUD. METHODS: We conducted this study in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, following our protocol (CRD420251170956). We searched PubMed, Scopus, Cochrane CENTRAL, Embase, EBSCO, and the Web of Science for relevant studies. Only randomized placebo-controlled trials were included. The primary outcomes were severity of PTSD and alcohol craving, while secondary outcomes were anxiety, depression, and alcohol use patterns and biomarkers. RESULTS: Seven randomized, double-blind, placebo-controlled trials were included in this meta-analysis, enrolling a total of 566 participants. There were no significant differences between NAC and placebo in craving (SMD= -0.40, 95% CI [-1.05, 0.25], P = 0.22, I² = 56.1%). Regarding PTSD severity, the PCL scale pooled analysis demonstrated no significant difference between NAC and placebo (SMD = 0.04, 95% CI [-0.40, 0.48], P = 0.8) (I² = 65.9%, P = 0.05), while the CAPS scale pooled analysis demonstrated no significant difference between NAC and placebo (SMD = -0.13, 95% CI [-0.50, 0.24], P = 0.49) (I² = 54.8%, P = 0.109). Leave-one-out sensitivity analysis showed that exclusion of the Back et al. (2025) study resulted in a significant effect favoring NAC (SMD = -0.35, 95% CI [-0.70, -0.01], P = 0.04), with no observed heterogeneity (I² = 0%). CONCLUSION: Our meta-analysis indicates that N-acetylcysteine, when compared to placebo, does not demonstrate consistent efficacy in reducing the primary symptoms of AUD or PTSD in broad patient populations. However, the treatment is relatively safe. A noteworthy signal of potential efficacy for PTSD symptoms emerged in a sensitivity analysis, suggesting that the therapeutic promise of NAC should not be entirely dismissed. CLINICAL TRIAL NUMBER: Not applicable.
14 May 2026
Read appraisal →American journal of epidemiology
Building the mountain mama & baby cohort: study design, protocol, and early prenatal clinic-based recruitment outcomes
Prenatal e-cigarette and cannabis use are increasing. Though concerning, the risks associated with these emerging exposures are unclear due to methodological limitations of available research. To address these gaps, the Mountain Mama & Baby Study prospectively enrolled a cohort of pregnant women in their first trimester during their initial telehealth visit with a nurse navigator at West Virginia University Medicine obstetric clinics. The study's goals were to (1) demonstrate the feasibility of our recruitment methodology and the representativeness of the sample, (2) establish first and third trimester exposure rates and describe the epidemiology of prenatal e-cigarette and cannabis use, and (3) explore associations between prenatal e-cigarette and cannabis exposure and adverse maternal-infant outcomes. This report describes the rationale, study design, protocol, and the feasibility and generalizability of recruitment. We enrolled 417 of 920 eligible participants (45.3%; 95% CI, 42.1% to 48.6%), exceeding our 20% benchmark. Enrolled participants and those nonenrolled were similar across most sociodemographic characteristics (eg, age, race/ethnicity, marital status, rurality, area deprivation). The Mountain Mama & Baby Study will provide clinicians, pregnant women, and public health practitioners with critical information on the potential harms of prenatal e-cigarette and cannabis use, guiding the design of interventions and recommendations.
12 May 2026
Read appraisal →Tobacco control
Impact of Instagram and TikTok influencer marketing on perceptions of e-cigarettes and perceptions of influencers in young adults: a randomised survey-based experiment
BACKGROUND: Pairing e-cigarettes with healthy lifestyle contexts in influencers' promotional social media posts may increase e-cigarette use risk among young adults. This study examined the effects of e-cigarette and healthy lifestyle content on young adults' perceptions of influencer credibility, harm perceptions of, and susceptibility to use, e-cigarettes. METHODS: In this survey-based online, repeated-measures experiment (2023), California young adults (N=1494, Mage=23 (SD=1.8); 63% female, 51% Hispanic) were randomly shown 10 (total) Instagram and TikTok videos, featuring influencers promoting e-cigarettes alongside healthy lifestyle activities (experimental group), or a healthy lifestyle activity alone (control). After watching each video, participants rated perceived influencer credibility (eg, honesty). After watching all videos, harm perceptions of e-cigarettes were assessed among all participants and susceptibility to e-cigarette use was assessed among e-cigarette never-users. Harm perceptions and susceptibility outcomes were compared between groups (experimental vs control) and between participants who perceived influencers as credible versus non-credible, using binomial generalised linear mixed effects models. RESULTS: Participants in the experimental group were more likely to report lower harm perceptions (adjusted OR (AOR) 1.12; 95% CI 1.03; 1.21) and higher susceptibility to e-cigarette use (AOR 1.22, 95% CI 1.11; 1.34), than participants in the control condition. Similar results were found when influencers were perceived as credible, but not when they were perceived as non-credible. CONCLUSIONS: Social media influencers' posts promoting e-cigarette use along with healthy activities may contribute to young adult e-cigarette use. Decreasing perceived credibility of influencers could decrease the negative effects of their promotional posts. TRIAL REGISTRATION NUMBER: NCT06433466.
12 May 2026
Read appraisal →Tobacco control
Vaping cessation interventions: a systematic review and meta-analysis
OBJECTIVE: Electronic nicotine delivery systems (ENDS), such as e-cigarettes, have surged in popularity. While long-term risks remain unclear, known dangers include nicotine addiction, E-cigarette or Vaping Use-Associated Lung Injury and potential extrapulmonary effects on the heart, immune system and neurodevelopment. Addressing ENDS addiction may require strategies akin to smoking cessation. However, evidence is lacking; there are no currently approved vaping-cessation aids. The objective of this review is to summarise the available literature addressing interventions for vaping cessation. DATA SOURCES AND STUDY SELECTION: A librarian-assisted search was conducted in MEDLINE, Embase and Scopus, as well as preprints in Europe PMC, Open Science Framework, and the grey literature searches until January 2024. Six included studies used self-report methods to determine the abstinence rate, while one study used cotinine-level-verified self-reported abstinence. We included randomised controlled trials (RCTs) that examine 'rates of vaping cessation' outcomes. An intention-to-treat approach was used for data extraction, and random-effects meta-analyses models were applied. DATA SYNTHESIS: Seven RCTs were included, which studied pharmacological therapy, digital interventions and/or educational content. The primary meta-analyses demonstrated a statistically significant increase in the odds of achieving 7-day point prevalence abstinence (PPA) (OR 1.52, 95% CI 1.15 to 2.01, number of participants=3244, moderate-certainty) and continuous abstinence (OR 2.71, 95% CI 1.31 to 5.61, number of participants=164, low-certainty) following intervention. A non-significant increase in odds was noted at 30-day PPA (OR 1.32, 95% CI 0.72 to 2.42, number of participants=1994, very low certainty). CONCLUSIONS: Vaping cessation interventions increase 7-day PPA rates at 1-12 months follow-up and this was consistent across prespecified subgroup analyses of the intervention type, outcome and duration of follow-up. More high-quality studies with reproducible findings are needed to enhance the certainty of the evidence and guide clinical interventions. PROSPERO REGISTRATION NUMBER: CRD42022383670.
11 May 2026
Read appraisal →Behavioral and brain functions : BBF
Neuropeptide S modulation of learning and memory: a systematic review
BACKGROUND: In the last two decades, Neuropeptide S (NPS) has been identified as a key bioactive peptide in the mammalian brain, influencing fear, anxiety, wakefulness, reward, and learning. While some reviews have addressed its role in reward-seeking and anxiety, few have addressed its particular role in learning and memory. The neuropeptide S receptor 1 is highly expressed in key areas for learning processing, such as the hippocampus, cortex, thalamus, and amygdala. This review aims to examine evidence from human and animal studies that focused on the NPS system's role in modulating learning and memory. A special focus is given to experiments addressing the impact of NPS on associative learning leading to addiction and in fear conditioning, pointing to its potential therapeutic value in associated pathologies. MAIN BODY: An advanced search was conducted using the databases PubMed, Google Scholar, Web of Science, and Scopus, focusing on memory and Neuropeptide S. The reviewed data suggest that NPS modulation occurs at all memory phases, including acquisition, consolidation, and retrieval, and in extinction learning, whether motivated by appetitive or aversive stimuli. The summarized evidence shows that the NPS system interferes with working and short-term memory, mitigates learning impairments, enhances spatial and object memory consolidation, supports fear extinction learning and inhibitory avoidance consolidation, and reinstates drug-seeking behaviors. The NPS system closely interacts with key neuromodulators, including orexinergic, dopaminergic, and noradrenergic systems, in influencing memory. CONCLUSION: The Neuropeptide S system emerges as a critical modulator of memory processes. The NPS signaling may preferentially influence learning that involves emotionally or motivationally relevant stimuli. This highlights the NPS system's potential as a target for therapeutic interventions for particular memory impairments.
11 May 2026
Read appraisal →CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne
Screening for high-risk drinking and alcohol use disorder: update of the 2023 national clinical practice guideline
BACKGROUND: Current screening tools for harmful alcohol consumption have fallen out of step with recent guidance on the health risks of alcohol. To address this gap, the Canadian Research Initiative in Substance Matters updated the screening recommendations for high-risk drinking and alcohol use disorder (AUD) in the 2023 national clinical practice guideline. METHODS: Following a systematic review of literature published between Jan. 1, 2013, and Feb. 24, 2023, that examined screening tools for high-risk drinking and AUD, the updated recommendations were developed by a multidisciplinary national committee, which included people with lived and living experience. We scored the recommendations and certainty of evidence using the Grading of Recommendations, Assessment, Development, and Evaluation tool. We used the Appraisal of Guidelines for Research and Evaluation II instrument and the Guidelines International Network's principles for disclosure of interests and management of conflicts to ensure the update met international standards for transparency, high quality, and methodological rigour. RECOMMENDATIONS: Acknowledging that time constraints are the most commonly reported barrier to universal alcohol screening, we developed 5 recommendations involving a simple screening method, to identify and address both unhealthy alcohol consumption and more serious problems related to alcohol. The recommendations include asking all patients about alcohol consumption and providing educational support to all those who drink above Canada's Guidance on Alcohol and Health's low-risk threshold. We propose a simple screening algorithm to optimize and tailor further intervention, including when to assess for possible AUD. INTERPRETATION: The revised screening recommendations represent a timesaving and pragmatic approach intended to be a resource for universal screening for alcohol risks and problems. The recommendations streamline the process of identifying and addressing the health needs of those who consume alcohol in a hazardous way or may have more serious problems related to alcohol.
11 May 2026
Read appraisal →European journal of pediatrics
The effect of motivational interviewing on internet addiction and digital game addiction in adolescents: a randomized controlled trial
UNLABELLED: The purpose of this study was to measure the effect of motivational interviewing on both reducing internet addiction and digital game addiction in adolescents. A parallel-group randomised controlled trial was adopted. The study population consisted of ninth-grade (14-15 years of age) high school students in a city in Turkiye. The study was completed by 88 participants (experimental: 44; control: 44). The data were collected using a Personal Information Form, the Young Internet Addiction Test, and the Digital Game Addiction Scale. The experimental group received a preparatory session and five weekly motivational interviewing sessions. Instruments were administered to both groups before (pre-test) and after the intervention (post-test), and at follow-up tests 3 and 6 months after the final session. The data were analysed using the two-way mixed design and the Bonferroni Comparison Test. The mean scores of internet addiction and digital game addiction decreased significantly after the motivational interviewing in the experimental group compared to the control group (p < 0.001) in both the post-test and follow-up tests. CONCLUSION: The present study concluded that motivational interviewing may be associated with reductions in mitigating symptoms of internet addiction and digital game addiction behaviours among adolescents. Motivational interviewing could be implemented to reduce internet addiction and digital game addiction behaviours. Trial registration: The study was registered on a clinical trial database (NCT06721702). The study started on December 11, 2023 (actual date on which the first participant was enrolled). WHAT IS KNOWN: • Internet addiction and digital game addiction are two increasingly important problems among adolescents. • Digital games and online activities negatively affect adolescents' physical, social, and psychological health. WHAT IS NEW: • Motivational interviewing was an effective technique to reduce online gaming and internet addiction. • A motivational interviewing program comprising at least six sessions could be implemented to promote behavioural change in adolescents.
10 May 2026
Read appraisal →Lancet (London, England)
Once-weekly semaglutide versus placebo in patients with alcohol use disorder and comorbid obesity: a randomised, double-blind, placebo-controlled trial
BACKGROUND: Alcohol use disorder accounts for 5% of deaths worldwide annually, and there is an urgent need for new therapeutic interventions. Preclinical and initial human studies indicate that the GLP-1 receptor agonist semaglutide might reduce alcohol drinking. This study evaluated the efficacy of semaglutide once-weekly in treatment-seeking patients with alcohol use disorder and comorbid obesity. METHODS: In a 26-week, single-centre, randomised, double-blinded, placebo-controlled trial, treatment-seeking participants with moderate to severe alcohol use disorder and comorbid obesity were assigned (1:1) to receive once-weekly semaglutide (2·4 mg subcutaneously) or placebo (saline subcutaneously), in addition to standard cognitive behavioural therapy. The primary endpoint was a reduction in the number of heavy drinking days assessed after 26 weeks of intervention, analysed with an ANCOVA model. Analysis adhered to the intention-to-treat principle, and missing outcome data were addressed using multiple imputations. Safety was assessed in all treated patients. The trial is registered at ClinicalTrials.govNCT05895643, and is complete. FINDINGS: From June 10, 2023, to Feb 4, 2025, 108 participants (53 women and 55 men) were enrolled, with 54 participants in each of the semaglutide and placebo treatment groups, and all were included in the data analysis. Overall, 88 participants (81%) completed the full intervention. Semaglutide was associated with a reduction in heavy drinking days (-41·1 percentage points from baseline, 95% CI -48·7 to -33·5) compared with placebo (-26·4, -34·1 to -18·6; estimated treatment difference -13·7 percentage points, -22·0 to -5·4; p=0·0015), and had substantial effects on multiple secondary alcohol-related and somatic outcomes. Adverse events were transient, generally mild to moderate gastrointestinal effects, and occurred more frequently in the semaglutide group. INTERPRETATION: Semaglutide showed robust therapeutic effects in treatment-seeking participants with obesity and alcohol use disorder and this trial supports previous preclinical and clinical findings suggesting GLP-1 receptor agonists as a potential novel treatment target for alcohol use disorder. FUNDING: The Research Foundation, Mental Health Services (Capital Region of Denmark), the Novo Nordisk Foundation, the Novavi Foundation, the Hartmann Foundation, and the Augustinus Foundation.
10 May 2026
Read appraisal →JMIR mHealth and uHealth
Alcohol Use Trajectories During the First 72 Weeks of WHOOP Wearable Platform Membership: Observational Cohort Study
Among 30,000 new wearable device users (11.6 million person-days), self-reported alcohol consumption significantly declined over 72 weeks, with the daily probability of drinking decreasing by 5.8 percentage points (P<.001) and reductions across age and biological sex.
2 May 2026
Read appraisal →Behavioural brain research
Non-pharmacotherapy for craving in methamphetamine use disorder: A systematic review and network meta-analysis of randomised controlled trials
OBJECTIVES: We evaluated the effects of non-pharmacotherapy on quality of life (QOL) and craving in individuals with methamphetamine use disorder (MUD), ranking the efficacy of various protocols. METHODS: We searched multiple databases for randomized controlled trials from inception to Dec 2025. The analysis included 53 studies with 3174 participants, investigating interventions such as exercise, transcranial magnetic stimulation (TMS), transcranial direct current stimulation, behavioral therapy, and acupuncture. The protocol was prospectively registered in PROSPERO (CRD42023443291). RESULTS: For craving reduction, both exercise and TMS demonstrated statistically significant benefits compared to conventional rehabilitation. Combined aerobic/resistance exercise and 10 Hz repetitive TMS targeting the left dorsolateral prefrontal cortex emerged as the most effective specific protocols within their respective categories. Furthermore, preliminary evidence from a limited number of studies indicated that exercise, acupuncture, and behavioral therapy improved patients' QOL. CONCLUSION: This study confirms that several non-pharmacotherapies are effective for managing craving in MUD. Exercise and TMS are particularly promising for reducing craving. The findings, synthesized within a novel "Intervention-Circuit-Symptom" integrative framework, provide a robust evidence base to inform clinical decision-making and guide the future development of MUD treatment guidelines.
1 May 2026
Read appraisal →Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco
ACT on Vaping: Pilot Randomized Controlled Trial of a Novel Digital Health App With Text Messaging for Young Adult Vaping Cessation
BACKGROUND: There is no published evidence to support the efficacy of any digital vaping cessation program for young adults (YAs) at differing levels of readiness to quit. In this pilot randomized controlled trial, we evaluated the preliminary acceptability and efficacy of a program for vaping cessation based on acceptance and commitment therapy (ACT on Vaping), delivered via a smartphone app and text messaging. METHODS: YAs aged 18-30 (n = 61) were randomized 1:1 to ACT on Vaping (n = 31) or incentivized text message control (n = 30). Outcome data were collected at 3 months post-randomization. Results were compared against a priori benchmarks for acceptability (satisfaction of ≥3.5 on 5-point scale) and efficacy relative to control (meeting at least one of three): ≥1-point difference in Contemplation Ladder change scores; ≥5 percentage difference in 24-hour quit attempts, ≥5 percentage difference in cotinine-confirmed 30-day point prevalence abstinence (PPA) from all non-therapeutic nicotine/tobacco. RESULTS: Satisfaction with ACT on Vaping averaged 3.8, exceeding the acceptability benchmark. A higher proportion of participants in the ACT on Vaping arm reported a 24-hour quit attempt (87.5% vs. 75.9%), exceeding the efficacy benchmark. Both changes in quit readiness (+0.96 in ACT on Vaping vs. +0.72 in control) and cotinine-confirmed 30-day PPA (4.2% in ACT on Vaping vs. 0% in control) were descriptively higher for ACT on Vaping but did not reach the benchmark level for efficacy. CONCLUSIONS: ACT on Vaping had promising acceptability and preliminary efficacy. A fully powered trial of ACT on Vaping is warranted to evaluate its efficacy. IMPLICATIONS: Digital interventions are a promising yet under-researched approach for reaching and supporting YAs to quit vaping. This proof-of-concept pilot randomized controlled trial evaluated a novel mobile health application and associated text messaging program (ACT on Vaping) for young adult vaping cessation and found preliminary evidence for acceptability and efficacy relative to an incentivized text message control arm, warranting evaluation in a fully powered trial as a next step. TRIAL REGISTRATION: NCT05897242.
26 Apr 2026
Read appraisal →Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco
Health Hazards of E-Cigarettes and Heated Tobacco Products: a Comprehensive Analysis of Hazardous Substances and Regulatory Gaps
INTRODUCTION: Ingredients and products of electronic cigarettes (ECs) and heated tobacco products (HTPs) formed during heating are aerosolized and inhaled. Hazard information on ingredients and emissions is often unavailable. Our objective was to identify and classify substances in the ingredients and emissions of ECs and HTPs based on scientific hazard classifications. METHODS: Ingredient data were collected from the European Union (EU) Common Entry Gate, a mandatory notification system for tobacco and related products. Substances in ECs and HTPs emissions were identified with a systematic literature review and classified into three categories based on existing health hazard classifications. Category 1 substances (i.e., highest potential health hazard) were regarded as high-priority substances for research and quantification. Categories 2 and 3 included potentially harmful substances and substances lacking sufficient toxicological data respectively. RESULTS: A total of 134 of the 1740 identified substances were classified in Category 1. Several substances possess Carcinogenic, Mutagenic, or Reprotoxic properties, prohibited as tobacco additives. Most substances lacked sufficient toxicity data and were classified in Category 3. CONCLUSION: Our classification can be used for monitoring and enforcement, ensuring proactive management of potential risks. Therefore, we recommend strengthening the enforcement of existing bans. Implications: This study identifies and classifies 1740 substances found in the ingredients and emissions of ECs and HTPs, including 134 hazardous chemicals, among which are carcinogens, mutagens, and reproduction toxicants. This indicates regulatory gaps and the need for stricter enforcement of existing bans. The findings provide a valuable tool for policymakers and public health professionals for monitoring and mitigating risks.
24 Apr 2026
Read appraisal →JMIR formative research
Effects of a Modified Exposure Claim for an e-Cigarette on Claim Comprehension, Behavioral Intentions, and Risk Perceptions Among US Adult Tobacco Users and Nonusers: Randomized Experimental Study
BACKGROUND: Effective communication about the relative risks of cigarettes and e-cigarettes can help increase switching away from cigarettes while minimizing unintended use. OBJECTIVE: This study examined comprehension of a proposed modified exposure claim (MEC) about an e-cigarette (IQOS VEEV, the study product [SP]) and the effects of claim exposure on SP use intentions and risk perceptions among adult tobacco users and nonusers. METHODS: Adult smokers with no intention to quit smoking (S-NIQ, n=606), adult smokers with an intention to quit smoking (S-IQ, n=600), adult e-cigarette users (ECU, n=630), adult former smokers (FS, n=619), adult tobacco and nicotine products (TNP) never-users aged 18-24 years (n=648), and adult TNP never-users aged 25 years and older (n=749; total N=3852) participated in a randomized between-groups online experimental study. Participants viewed a marketing brochure for the SP with (test condition) or without (control condition) an embedded MEC. Outcome measures included claim comprehension, intention to use the SP regularly, and perceived health risk to self from using the SP or smoking cigarettes. RESULTS: Most participants were female (n=2110, 54.8%), had a mean age of 40.2 (SD 14.93) years, and were equally split across the 4 US regions. S-IQ and S-NIQ were long-term, frequent cigarette smokers, while 91.4% (566/619) of FS were long-term quitters. ECU on average used e-cigarettes ≥15.2 times per day, and the majority of them (552/630, 87.6%) had started using e-cigarettes more than 12 months before. Most participants correctly understood the key elements of the claim: the SP produces lower levels of harmful chemicals compared to cigarettes (1818/1926, 94.4%), and switching completely from cigarettes to the SP reduces exposure to harmful chemicals (1832/1926, 95.1%). In both conditions, positive intention to use the SP was high among ECU (control: 238/314, 75.8% vs test: 249/315, 79%; P=.33), moderate among S-IQ (control: 127/299, 42.5%; test: 166/299, 55.5%; P<.001) and S-NIQ (control: 140/299, 46.8%; test: 166/307, 54.1%; P=.07), low among FS (control: 28/306, 9.2%; test: 33/312, 10.6%; P=.55), and very low among adult TNP never-users aged 18-24 years (control: 3/330, 0.9%; test: 8/318, 2.5%; P=.11), and adult TNP never-users aged 25 years and older (control: 5/373, 1.3% vs test: 12/375, 3.2%; P=.09). All groups understood that the SP posed a lower health risk compared to cigarettes. In all groups, claim exposure was associated with significantly lower risk perception of the SP relative to cigarettes (all comparisons, P<.001). CONCLUSIONS: The tested MEC has the potential to benefit public health by simultaneously increasing already high levels of SP use intention and reducing SP risk perceptions relative to cigarettes among adult tobacco users while generating low levels of use intention among tobacco nonusers.
23 Apr 2026
Read appraisal →Tobacco control
Generative AI in a new era of computer model-informed tobacco research: a short report
BACKGROUND: Social media influencers who promote e-cigarettes on Instagram or TikTok for tobacco brands use marketing tactics to increase the appeal of their promotional content, for example, depicting e-cigarettes alongside healthy lifestyle or entertainment imagery that could decrease youths' risk perceptions of e-cigarettes. Monitoring the prevalence of such content on social media using computer vision and generative AI (artificial intelligence) can provide valuable data for tobacco regulatory science (TRS). METHODS: We selected 102 Instagram and TikTok videos posted by micro-influencers in 2021-2024 who promoted e-cigarettes alongside posts featuring four themes: cannabis, entertainment, fashion or healthy lifestyle. We used OpenAI's GPT-4o multimodal large-scale visual linguistic model to detect the presence of nicotine vaping, cannabis vaping, fashion, entertainment and healthy lifestyle. The model did not require any additional training and improved its performance as we modified the text prompt. RESULTS: The model's accuracy was 87% for nicotine vaping, 96% for cannabis vaping, 99% for fashion, 96% for entertainment and 98% for healthy lifestyle. CONCLUSIONS: Generative AI can achieve accurate object detection with zero-shot learning (no additional training of the pretrained model). This model can be applied to big data-scale sample sizes of images and videos to detect e-cigarette-related and other substance-related promotional content and contexts (eg, healthy lifestyle) used for the promotion of these products on social media, providing valuable data for TRS.
15 Apr 2026
Read appraisal →BMJ health & care informatics
Supporting street medicine through medical informatics: a manifesto on research needs
Homeless individuals face major barriers in accessing regular healthcare, leading to the development of street medicine as a distinct humanitarian field. To enhance continuity and quality of care, consistent documentation is crucial. However, electronic health records are rarely used in European street medicine. An interdisciplinary European workshop identified four key research fields for medical informatics in street medicine: (1) Research ethics: The creation of ethical guidelines that promote co-creation and active communication with patients. (2) System development: Designing a secure, anonymous and European Health Data Space-compliant personal Electronic Health and Social Record (pEHSR), establishing standardised health and social care datasets, and implementing dynamic consent management methods. (3) Education and training: Developing targeted programmes to improve digital and health literacy among street medicine clients and training professionals in the effective use of the pEHSR system. (4) Management and evaluation: Creating management structures and evaluation frameworks suited to the unique challenges of street medicine.This manifesto calls for internationally coordinated scientific efforts to build effective, integrated digital health solutions for vulnerable populations. It encourages researchers and practitioners from medical informatics and related fields to engage with these priorities and support innovation that advances equitable healthcare access.
15 Apr 2026
Read appraisal →Tobacco control
Cigarette filter ventilation, product appeal and regulatory options: a review of the influence of ventilation on consumers' sensory and risk perceptions
OBJECTIVE: Cigarette filter ventilation may enhance product appeal, support initiation and sustained smoking, and increase smoking prevalence. We reviewed recent evidence on how filter ventilation affects consumers' perceptions of product appeal and considered product use preferences to inform regulatory options. DATA SOURCES: PubMed, Embase and PsycINFO databases were searched up to December 2023. Systematic search strategies used terms based on cigarette filter ventilation, and multiple constructs comprising product appeal and user perceptions. STUDY SELECTION: Two reviewers screened all 917 retrieved titles and abstracts independently and applied a consensus strategy to identify 16 articles that met eligibility criteria. DATA EXTRACTION: Extracted data focused on study design, dependent variables or outcomes, and major conclusions. DATA SYNTHESIS: While remaining popular, awareness and risk perception of ventilated cigarettes is generally low. Cigarettes with filter ventilation are perceived as smoother and less irritating than non-ventilated cigarettes. These modified sensory experiences shape perceptions of reduced health risks. Pack text descriptors and colours convey further information to consumers about smoothness, supporting lowered risk perceptions. CONCLUSIONS: Filter ventilation and its associated marketing continue to influence consumers' perceptions of smoothness creating misperceptions about health risks. Standardised ('plain') packaging regulations are recommended to restrict communication of ventilation themes as well as evidence-based health communications to correct consumer misperceptions about smoothness and health risks. Since filter ventilation has no benefits for public health, policy makers could consider banning filter ventilation or even disallowing filters.
15 Apr 2026
Read appraisal →Tobacco control
Nitrosamine and nicotine exposure after switching from filtered to unfiltered cigarette smoking: a cross-over clinical trial
BACKGROUND: The cellulose acetate filter is a plastic attachment on nearly all commercial cigarettes sold worldwide. It is the main component of discarded cigarette butts, and the most prevalent waste item collected during urban and beach cleanups. This waste leaches toxic chemicals, including nicotine, metals and tobacco-specific nitrosamines and contributes to environmental microplastic pollution. There is growing international interest in reducing plastic waste from single-use, non-essential products such as cellulose acetate cigarette filters. Public health and environmental advocates recommend a ban on the sale of filtered cigarettes to reduce environmental pollution caused by discarded cigarette butts and to discourage cigarette smoking. RESEARCH QUESTION: What potential health and behavioural implications might arise among people who smoke if filtered cigarettes are removed from the market. METHODS: We conducted a cross-over, randomised clinical trial of 29 people who smoke to evaluate changes in biomarkers for nicotine and tobacco-specific nitrosamine exposure when switching between filtered and unfiltered cigarette smoking. RESULTS: Although unfiltered smoking showed a higher trend in the geometric means of 4-[(methylnitrosamino])-1-[3-pyridyl]-1-butanol (NNAL) compared with filtered cigarettes, regression models for urinary cotinine and NNAL showed no significant differences when switching between filtered and unfiltered cigarettes. CONCLUSION: This proof-of-principle study suggests there is no increased risk to people who smoke when switching to unfiltered cigarette smoking. Although larger studies might provide more evidence regarding unfiltered cigarette smoking, banning the sale of filtered cigarettes may be an important policy intervention to both reduce hazardous tobacco waste and discourage smoking.
15 Apr 2026
Read appraisal →JMIR mHealth and uHealth
Promoting Self-Regulated Social Media Use on Smartphones With a Mobile Intervention App (Wellspent): Randomized Controlled Trial
BACKGROUND: Problematic social media use has been linked to reduced well-being and impulse control difficulties. While digital self-control apps show potential for reducing general app usage, they often lack customization, leading to limited effectiveness and increased user resistance. Their impact on problematic social media use remains uncertain. OBJECTIVE: This study evaluates the effectiveness of the Wellspent app, a customizable mobile intervention app designed to promote self-regulated social media use by targeting user-defined problematic app use and offering tailored behavioral nudges. METHODS: In a 3-week randomized controlled trial, 70 iPhone users (mean age 26.2, SD 5.6 years; 47/70, 67% female), regularly using at least 1 social media app, were randomly assigned to an intervention (n=35) or control group (n=35). The intervention group received personalized full-screen reminders with the option to quit or continue social media app use whenever an app session exceeded a self-defined time limit. Participants completed weekly online surveys measuring problematic social media use, problematic smartphone use, self-efficacy, and daily screen time on their most problematic app. Linear mixed models tested intervention effects. RESULTS: While no significant reduction in problematic social media use or increase in self-efficacy was observed, the intervention group showed a significant reduction in daily screen time on their most problematic app by approximately 29 minutes (estimate=-29.35, SE 6.84, 95% CI -42.79 to -15.99; P<.001), and a significant decrease in perceived problematic smartphone use (estimate=-0.46, SE 0.18, 95% CI -0.80 to -0.11; P=.01). CONCLUSIONS: The Wellspent app demonstrated short-term efficacy in reducing problematic smartphone use. By allowing users to tailor interventions to their personal goals, the app shows promise as a self-directed tool to support healthier digital habits. Further research should explore long-term effects and feature-specific impacts.
9 Apr 2026
Read appraisal →Proceedings of the National Academy of Sciences of the United States of America
AI-derived therapeutic development of a serotonin receptor-targeting drug for the treatment of opioid use disorder
The opioid epidemic has led to a devastating loss of life nationwide. Of those dependent on opioids, many individuals desire to quit or reduce use, but their efforts are often unsuccessful given the powerful reinforcing properties associated with opioid drugs, including fentanyl. Here, we developed a therapeutic drug based on an AI-based platform, which was rationally designed to identify markers of dysregulation from human drug user postmortem brain tissue. Two top candidate compounds, GATC-021 and GATC-1021, were synthesized and validated with in vitro screening for target specificity. Thereafter, the drug candidates were examined for their effectiveness in modulating opioid reinforcement and intake. GATC-1021 emerged as the most efficacious compound as it significantly decreased fentanyl intake in both male and female rats, without any notable side effects. GATC-1021 was further found to modulate gene expression patterns in addiction-relevant brain regions following fentanyl-induced alterations. These findings validate GATC's AI-based platform with its polypharmacy-focused drug development approach and further support the clinical potential of GATC-1021 as a promising therapeutic for those suffering from opioid use disorder.
7 Apr 2026
Read appraisal →Journal of behavioral addictions
When rejection backfires: Social exclusion and economic decision-making in gamblers
BACKGROUND AND AIMS: Economic decision-making deviates from rational choice models and is influenced by social factors, particularly fairness considerations and belonging needs. Social exclusion and altruistic punishment are intended to promote behavioral conformity, yet paradoxically may exacerbate rather than correct targeted behaviors among individuals with addictions already experiencing chronic rejection. Several preliminary studies show that social exclusion increases money desirability in general populations, however, the interaction between acute social exclusion and economic decision-making among individuals with gambling disorders (PGs)-marked by aberrant financial decision-making-remains unexplored. METHODS: In a field study, 203 gamblers were recruited outside gambling venues and randomized to experience either social inclusion or exclusion via Cyberball, a virtual ball-tossing paradigm. Participants then completed an ultimatum game, making accept/reject decisions on fair and unfair monetary offers, followed by the Problem Gambling Severity Index. RESULTS: Social exclusion increased unfair offer acceptance among PGs but had no effect on low- and moderate-risk gamblers. PGs accepted more unfair offers following exclusion than inclusion. Gambling severity had no effect on unfair offers acceptance. Neither social exclusion nor gambling severity affected fair offer acceptance. DISCUSSION AND CONCLUSIONS: Social exclusion triggered utilitarian decision-making only among PGs. This selective effect suggests rejection compromises PGs' economic decision-making processes, shifting priorities toward immediate monetary gains over equitable outcomes. These findings reveal how social punishment creates self-reinforcing cycles where exclusion triggers the utilitarian mindset characterizing problematic gambling. Treatment and societal approaches relying on social consequences may inadvertently strengthen harmful patterns, highlighting the need for inclusion-based interventions.
5 Apr 2026
Read appraisal →Journal of medical Internet research
Effectiveness of the Components of a Digital Multiple Health Behavior Change Intervention Among Individuals Seeking Help Online (Coach): Factorial Randomized Trial
BACKGROUND: Extant digital multiple health behavior change interventions have shown promise in various populations; however, evidence for a broader approach among the general population is lacking. Moreover, existing interventions often contain several components but are typically assessed as a whole, meaning it remains unclear to what extent individual components contribute to intervention effects and how they may interact to influence health outcomes. OBJECTIVE: This study estimates the effects of 6 components of a digital health behavior change intervention on alcohol, diet, physical activity, and smoking outcomes among individuals searching for help online. METHODS: A double-blind randomized factorial trial design with 6 two-level factors was used. Adults from the general public in Sweden who were seeking help to change their behaviors were recruited through web searches and social media. Participants were eligible if they were 18 years or older and had at least one health behavior classified as unhealthy. Effects of 6 components were estimated: screening/feedback, goal-setting/planning, motivation, skills/know-how, mindfulness, and self-authored SMS text messages. Primary outcomes were weekly alcohol consumption and frequency of heavy episodic drinking, average daily fruit and vegetable consumption, weekly moderate-to-vigorous physical activity, and 4-week point-prevalence smoking. RESULTS: A total of 5419 individuals were randomized. Overall, the screening/feedback component was the most effective for changing health behaviors, along with goal-setting/planning and motivation to change. In particular, there was evidence that screening/feedback increased average daily portions of fruit and vegetables at 2 months (mean difference 0.17, compatibility interval [CoI] 0.09-0.25, probability of effect [POE] >99.9%) and at 4 months (mean difference 0.13, CoI 0.04-0.21, POE 99.9%) and reduced the frequency of heavy episodic drinking at 4 months (incidence rate ratio 0.91, CoI 0.81-1.03, POE 94.2%). Components also interacted to further improve health outcomes, most notably the combination of screening/feedback with motivation to change, which further increased fruit and vegetable consumption (2 months: mean difference 0.20, CoI 0.09-0.30, POE >99.9%; 4 months: mean difference 0.17, CoI 0.05-0.29, POE 99.8%). CONCLUSIONS: The results from this study contribute to the development of more effective interventions by providing novel insights into the effects of individual and pairwise components of complex digital health behavior change interventions. TRIAL REGISTRATION: ISRCTN Registry ISRCTN16420548; http://www.isrctn.com/ISRCTN16420548. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2022-061024.
4 Apr 2026
Read appraisal →Journal of behavioral addictions
Gambling in women: A systematic review of interventions and prevention approaches
BACKGROUND: Gambling disorder (GD) is a behavioral addiction with significant psychological, social, and economic consequences. Despite growing female participation and distinct gambling characteristics, research and interventions largely male-centered, overlooking women-specific factors. OBJECTIVES: This systematic review synthesizes evidence on prevention and treatment interventions for women with GD, assessing their effectiveness on gambling behaviors, cognitive and psychological outcomes, and identifying barriers related to access, adherence, and gender-sensitive design. METHOD: A systematic search in PubMed, PsycINFO, and Web of Science (up to September 2025) identified quantitative studies reporting female-specific outcomes in gambling prevention or treatment. Study quality was appraised using National Heart, Lung, and Blood Institute tools, and data on intervention characteristics, outcomes, and participant profiles were extracted. RESULTS: Eighteen studies met the inclusion criteria (five prevention, thirteen treatment). Prevention programs, mostly universal and adolescent-focused, improved gambling knowledge, cognitive distortions, and short term gambling frequency; however, socioemotional effects were inconsistent. Only one study included follow-up assessment. Treatment studies, predominantly cognitive behavioral therapy (CBT)-based, reduced gambling severity and psychological distress, although dropout and relapse rates were higher among women with greater psychopathology or limited support. Person-centered approaches benefited of tailoring interventions to individual profiles. No studies systematically applied gender-sensitive frameworks or disaggregated outcomes by sex in prevention. DISCUSSION AND CONCLUSION: Prevention and treatment programs can benefit women, but standard interventions insufficiently address their unique needs. Gender-sensitive, individualized strategies, inclusion of socioemotional factors, and long-term evaluations are essential to enhance outcomes and inform inclusive public health policies.
4 Apr 2026
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