Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
Showing 86 appraisals
PloS one
Factors associated with resilience among parents of children with autism spectrum disorder: A systematic review
Parents of children with autism spectrum disorder (ASD) experience ongoing caregiving demands and challenges that may contribute to their general well-being. Research has shown that resilience enables parents to adapt to these challenges; however, existing evidence on associated factors toward resilience among these parents remains fragmented. This systematic review aimed to identify factors associated with resilience among parents of children with ASD. We conducted a PRISMA 2020-guided systematic review on studies published between January 2019 and May 2025 using Web of Science, Scopus, and PubMed by applying predefined search terms and Boolean operators. Studies examining factors associated with resilience among parents of children with ASD aged under 18 years were included in this review. We also used the Mixed Methods Appraisal Tool 2018 to assess the quality of these studies. Findings were synthesised narratively using thematic analysis. From the 13 selected studies, five themes were identified as determinants of resilience among parents, i.e., sociodemographic and economic factors; child-related characteristics; parenting well-being and distress; psychological factors and coping styles; and social support and family relationships. Most included studies were cross-sectional and utilised different measurement tools, which may limit causal inference and comparability. As a conclusion, parental resilience was found to be influenced by psychological, social, and contextual factors. Strengthening coping resources and social support may enhance parental adaptation and family well-being. Along these lines, multi-level and culturally sensitive interventions are thus needed to inform strategies to foster resilience among parents of children with ASD. The review was registered with PROSPERO (CRD420251034348). The author(s) received no specific funding for this work.
23 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 →Human vaccines & immunotherapeutics
Immunogenicity and safety of AS03-adjuvanted A/Astrakhan/3212/2020 (H5N8)-like influenza vaccine in adults: Phase 1/2, observer-blinded, randomized trial
Influenza pandemics arise from novel influenza A viruses. Recent emergence of a new clade (2.3.4.4.b) of the highly pathogenic H5N1 in animals and humans highlighted its pandemic potential. We evaluated the immunogenicity and safety of GSK's AS03-adjuvanted H5N8 vaccine in adults. In this phase 1/2, observer-blinded, age-stratified, randomized trial, healthy US adults (age, ≥18 y) received two intramuscular doses of hemagglutinin antigen (3.75 or 7.50 μg) with AS03A or AS03B, administered 21 d apart. Immunogenicity - seroprotection rates (SPRs), seropositivity, geometric mean titers (GMTs), geometric mean fold rise (GMFR), and seroconversion rates (SCRs) - was evaluated on day 43 using hemagglutination inhibition (HI) and microneutralization (MN) assays. Safety was monitored throughout the study. Of 520 enrolled participants, 518 were vaccinated. On day 43, the US Food and Drug Administration's (FDA) Center for Biologics Evaluation and Research criteria for influenza vaccines were met. HI SPRs, seropositivity rates, SCRs, GMTs, and GMFR appeared to be higher in the AS03A vs AS03B group. Immune responses were generally higher in younger (aged 18-64 y) vs older (aged ≥65 y) adults. Immune responses were also detected in MN assays, with a correlation between HI and MN responses on day 43 across age groups and vaccine formulations. Safety was acceptable, with no increase in adverse events post-dose 2. Reactogenicity appeared more common in younger adults. The antigen-sparing potential of AS03 was demonstrated, with an acceptable safety profile. The benefit/risk profile was favorable for all formulations tested, including 3.75 µg AS03A (licensed in the US).ClinicalTrials.gov registration: NCT05975840. Influenza pandemics occur when new influenza viruses emerge, causing widespread illness. A recent study investigated a new vaccine, GSK’s AS03-adjuvanted H5N8 influenza vaccine, for its ability to trigger an immune response and its safety in adults aged 18–64 y and older adults aged ≥65 y. Overall, 518 participants received at least one dose of the vaccine, with different amounts of hemagglutinin antigen (3.75 or 7.50 µg) combined with different concentrations of AS03 adjuvant. Immune responses were assessed at multiple time points, with the primary endpoint measured on day 43 post-vaccination. The vaccine produced a strong immune response in both age groups, with younger adults showing slightly better responses than older adults. The vaccine met the required standards for an immune response set by the US Food and Drug Administration (FDA). AS03A typically induced greater immune response than AS03B. Safety monitoring showed that the vaccine was generally well tolerated, with the most common side effects being mild, such as injection-site pain and muscle ache. This study confirmed that the AS03-adjuvanted H5N8 vaccine has the potential to provide protection against influenza with an acceptable safety profile, making it a valuable candidate for pandemic preparedness.
14 June 2026
Read appraisal →Journal of global health
Residential green space mitigates genetic susceptibility to incident irritable bowel syndrome in a prospective cohort of 376 749 individuals
BACKGROUND: Environmental exposures may influence irritable bowel syndrome (IBS) pathogenesis, but the interplay between genetic risk, residential green/blue space, and IBS incidence remains unexplored. METHODS: We aimed to study the association between green/blue space and incident IBS, and to assess effect modification by genetic susceptibility. The study included 376 749 UK Biobank participants at baseline. Residential green space was measured using the normalised difference vegetation index (NDVI), and blue space was defined by distance to the nearest water bodies. For time-to-event analyses, we used Cox proportional hazards models, polygenic risk scores (PRS), and mediation analysis to test gene-environment interactions. Results are presented as hazard ratios (HRs) with 95% confidence intervals (95% CIs). RESULTS: During a follow-up of 11.73 years, 7091 incident IBS cases were documented. Higher residential green space exposure was associated with reduced risk of incident IBS. Specifically, within a 1000 m buffer, each interquartile range (IQR) increase in NDVI corresponded to a 5% lower IBS risk (HR = 0.95; 95% CI = 0.91-0.98), with consistent effects observed at 800 m and 500 m buffers. Conversely, a greater distance to water bodies was associated with reduced IBS risk. Stratification by PRS revealed a significant interaction: increased green space (1000 m buffer) reduced IBS risk by 8% exclusively among high-genetic-risk individuals (HR = 0.92; 95% CI = 0.88-0.96), whereas no interaction was observed for blue space. Moreover, physical activity mediated the association between green space and IBS. CONCLUSIONS: Increased residential green space exposure is associated with reduced IBS incidence, particularly among individuals with high genetic susceptibility. These findings underscore the importance of urban greening as a public health strategy to mitigate IBS risk, highlighting the potential for targeted environmental interventions to offset genetic predispositions.
13 June 2026
Read appraisal →BMJ open
Diabetic retinopathy treatment cascade and care continuum in the USA: a systematic review
OBJECTIVES: To characterise engagement across the diabetic retinopathy (DR) care continuum in the USA using a cascade-of-care framework and identify gaps contributing to preventable vision loss. DESIGN: Systematic review. DATA SOURCES: From September to November 2025, with an updated search in March to April 2026 using the same eligibility criteria, we systematically searched Ovid MEDLINE and Ovid Embase supplemented by reviewing reference lists of relevant articles and opportunistic searches of the Centers for Disease Control and Prevention publications. ELIGIBILITY CRITERIA: We included English-language US-based cross-sectional, cohort and case-control studies and systematic reviews containing US-based data published between 1 January 2018 and 31 December 2025 relevant to one of the defined DR cascade stages: (1) diagnosis of diabetes, (2) adherence to DR screening, (3) diagnosis of DR, (4) adherence to DR care and (5) DR-related blindness. We included systematic reviews only to inform DR-related blindness, where primary data were limited and excluded them from other stages to avoid double-counting. Exclusion criteria included studies not relevant to one of the defined DR cascade stages and editorial, perspective or commentary pieces. DATA EXTRACTION AND SYNTHESIS: Two reviewers independently screened studies, extracted data and assessed risk-of-bias using the Newcastle-Ottawa Scale and Risk of Bias in Systematic Reviews tool. We synthesised data narratively and organised via the DR treatment cascade framework. RESULTS: Of 14 893 studies screened, 46 met the inclusion criteria. Cascade analysis revealed substantial losses in patient engagement at three stages: (1) only 15.5%-78.7% (median 59.4%, IQR 33.9%-74.0%) of individuals with diabetes obtain biennial DR screening; (2) a substantial 54.9%-88.5% (median 70.1%, IQR 62.5%-79.3%) of individuals with DR are unaware of their diagnosis; (3) only 30.9%-62.7% (median 52.0%, IQR 40.9%-59.1%) of individuals diagnosed with DR are initially linked to care and 55.3%-77.8% (median 70.3%, IQR 59.2%-77.7%) have a lapse in DR follow-up. CONCLUSIONS: This review identifies major gaps in the DR care continuum, particularly in diagnosis awareness, linkage to care and follow-up adherence. The cascade framework highlights key points of disengagement and provides a basis for prioritising future research.
13 June 2026
Read appraisal →Journal of epidemiology and community health
Incidence of physical non-communicable disease in people who have experienced imprisonment compared with the general population in high-income countries: a systematic review and meta-analysis
BACKGROUND: Non-communicable diseases (NCDs) represent a significant cause of morbidity and mortality globally. Despite a strong evidence base outlining increased risk of communicable diseases and poor mental health in people who have experienced imprisonment, the risk of NCDs has not been quantified in previous reviews. This study aimed to describe the incidence of morbidity and mortality of physical NCDs in people who have experienced imprisonment compared with the general population in high-income countries. METHODS: We searched MEDLINE, Embase, CINAHL and SocINDEX (PROSPERO CRD42024540173) for comparative studies of morbidity or mortality from NCDs. Articles were assessed against predefined criteria to select studies that included people with experience of imprisonment; measured NCD incidence; compared incidence to a general population; and were conducted in a high-income country. Two reviewers conducted independent risk of bias assessment using an adapted version of the Newcastle-Ottawa Scale. Data were synthesised using random-effects meta-analyses and vote counting based on effect direction. Meta-regression and subgroup analysis investigated heterogeneity. RESULTS: Of 3085 articles screened, 32 were included providing 341 datapoints. Meta-analysis showed a higher risk of mortality from several diseases, including respiratory disease (risk ratio (RR) 2.38 (95% CI 1.18 to 4.80), I2=97%), cardiovascular disease (RR 1.80 (95% CI 1.32 to 2.46), I2=99%), liver disease and cirrhosis (RR 2.50 (95% CI 1.08 to 5.77), I2=99%), digestive disease (RR 2.92 (95% CI 1.09 to 7.78), I2=99%), neurological disease (RR 1.94 (95% CI 1.09 to 3.44), I2=92%), head and neck cancer (RR 21.31 (95% CI 4.32 to 105.14), I2=97%), liver cancer (RR 4.07 (95% CI 2.34 to 7.08), I2=94%), cervical cancer (RR 3.95 (95% CI 3.11 to 5.01), I2=0%) and lung cancer (RR 1.95 (95% CI 1.34 to 2.85), I2=0%). Synthesis without meta-analysis also indicated imprisonment was associated with increased morbidity from multiple NCDs. CONCLUSIONS: Several NCDs, including multiple cancers, cardiovascular disease, respiratory disease and liver disease, are substantially more common in people who have experienced imprisonment compared with the general population, highlighting a need for primary prevention and NCD management.
13 June 2026
Read appraisal →International journal of biometeorology
Integrating google trends and hybrid statistical-machine learning models for dengue surveillance in an inland vietnamese province: a 94-month evaluation (2013-2021) with search-signal anomaly screening
Dengue transmission in inland Southeast Asia shows strong seasonality and short-term surges that challenge timely public-health response. We assessed whether province-level Google search activity can support short-horizon dengue monitoring in Dong Nai, Vietnam. Monthly reported dengue cases from July 2013 to April 2021 were aligned with the Google Trends index (GTI) for "Sốt xuất huyết". Models were evaluated using leakage-free rolling-origin expanding-window cross-validation with 3-month validation blocks. We compared a negative binomial (NB) autoregressive baseline, NB models incorporating GTI, tree-based machine-learning models using the same covariates, and a simple NB-random-forest ensemble. Predictive performance was assessed using root mean squared error (RMSE), mean absolute error (MAE), R2, and discrimination for 95th-percentile outbreak exceedance. Cross-correlation peaked at lag 0, indicating that GTI functioned primarily as a contemporaneous nowcasting signal rather than a long-lead predictor. NB models incorporating GTI showed competitive calibration, while boosted tree models achieved the lowest point-estimate errors; XGBoost achieved RMSE ≈ 40.95 and R2 ≈ 0.861 compared with RMSE ≈ 45.23 and R2 ≈ 0.823 for NB with GTI. Adding GTI to the autoregressive NB baseline reduced RMSE by 11.77%, but the 95% confidence interval crossed zero, indicating modest and statistically non-significant incremental gain. Search-signal anomaly screening suggested that GTI spikes largely coincided with epidemic peaks and did not clearly inflate out-of-sample errors. Overall, GTI provides operational value for dengue nowcasting and alert triage in inland provinces, while future systems should integrate climate, vector, mobility, and media-monitoring data.
9 June 2026
Read appraisal →PloS one
Reinforcement learning for policymaking in epidemic control: A scoping review
BACKGROUND: Managing an epidemic demands policies that respond at the pace of the outbreak. Conventional rule‑based interventions struggle to keep up, prompting interest in reinforcement learning (RL) for designing non‑pharmaceutical interventions (NPIs). However, current evidence is fragmented across diverse models and reporting styles. OBJECTIVES: To systematically map how RL is applied for epidemic NPI design, describe modeling choices, algorithm architectures, evaluation practices, and identify trends and research gaps. METHODS: Peer-reviewed studies (2014-2025, English) that applied deep RL to select NPIs were retrieved from IEEE Xplore, ACM Digital Library, ScienceDirect, and Scopus, searched on December 23, 2025. Reference list scanning supplemented database results. Predefined data items (bibliographic details, epidemic and RL model characteristics, experiments, validation methods, outcomes) were charted and summarized descriptively. RESULTS: Of 512 retrieved records, 10 met the inclusion criteria, and three additional studies were identified via reference-list scanning, yielding 13. Five employed value‑based methods, four policy‑gradient, and four hybrid; one study additionally incorporated model-based planning. Six simulations relied on compartmental models, six on agent‑based models, and one on a hybrid model. Action spaces were predominantly discrete restriction levels. Five studies incorporated sequence-modeling techniques to include temporal context into a state space. Eleven studies designed reward functions as a trade-off between pandemic severity and socio-economic cost. According to the reviewed studies, RL policies across various settings outperform heuristic, rule-based, and historical baselines in reducing infections, deaths, or lockdown duration while limiting economic loss. CONCLUSIONS: RL shows promise for adaptive epidemic control. Comparison is hampered by simplified economic costs, inconsistent calibration rigor, varied evaluation metrics, and limited uncertainty or policy robustness analysis. Future work should establish common benchmark environments and reporting standards, incorporate empirically grounded economic and behavioral models, adopt uncertainty-aware and probabilistic RL, develop more sophisticated control spaces, investigate more advanced algorithms, and validate learned policies prospectively to enable real-world deployment.
9 June 2026
Read appraisal →Archives of microbiology
AI-driven big data analysis and predictive modeling of infectious disease immunity: from correlates to causal, multiscale understanding
The ability to reliably predict protective immunity against infectious diseases remains a central challenge in immunology, vaccine development, and public health. Despite major advances in immunological measurement, immunity prediction has historically relied on simplified correlates most notably antibody titers that often fail to generalize across pathogens, populations, and time. The emergence of large-scale, high-dimensional immune datasets spanning multi-omics, longitudinal cohort studies, electronic health records, and pathogen genomics has created new opportunities for artificial intelligence (AI)-driven modeling. However, early applications reveal that predictive accuracy alone is insufficient and is frequently undermined by spurious correlations, limited generalizability, and a lack of biological interpretability. This review synthesizes current advances and limitations in AI-based immunity prediction, arguing that meaningful progress requires embedding machine learning within immune biology, causal reasoning, and rigorous validation frameworks. We examine the biological foundations of immunity relevant to modeling including innate immune programming, trained immunity, adaptive immune dynamics, and immune memory and map these processes to appropriate data modalities and model classes. We critically evaluate predictive tasks across individual and population scales, from early infection outcomes and vaccine responsiveness to immunity waning and herd-level protection. Emphasis is placed on validation beyond internal cross-validation, on interpretability grounded in immune mechanisms, and on robustness under demographic diversity and pathogen evolution. We conclude that immunity is best understood and predicted as a dynamic, probabilistic, and multiscale system rather than as a static trait. AI has substantial potential to improve infectious disease preparedness and clinical decision-making.
1 June 2026
Read appraisal →mSphere
Novel machine learning-based approach to identify viral biomarkers of human respiratory emissions from oral and nasal metagenomes
Humans spend approximately 90% of their lives in built environments, making virus transmission indoors a key determinant of health. Environmental sampling of respiratory viral pathogens is often challenging because of frequent non-detect measurements. Non-detect measurements do not differentiate between samples containing low or no pathogens from samples that simply lack respiratory expulsions altogether. This ambiguity can be resolved by scanning samples for a biomarker of human respiratory emissions. To do so, reliable biomarkers for environmental monitoring need to be identified. Ideal biomarkers are prevalent across individuals, abundant, and unique to the human respiratory tract. Here, we present a new machine learning-based approach to query for suitable biomarker candidates from publicly available metagenomes and apply it to identify viral biomarkers of healthy oral and nasal microbiomes. Twelve viral biomarker candidates were selected from 1,232 curated viral operational taxonomic units. The viral biomarker candidates had as much as 63% prevalence across respiratory metagenomes, and prevalence was further increased to 77%-81% by combining two or three biomarkers. Real-time PCR confirmed that these viral biomarkers were prevalent and abundant in nasal swabs and saliva samples. Notably, top candidate biomarkers remained stable and detectable through multiple lab purification steps, increasing confidence in their viral origins and demonstrating their suitability for environmental monitoring. These findings demonstrate that existing metagenomes can be used to identify effective biomarker candidates for environmental sampling.IMPORTANCEDeveloping non-pharmaceutical interventions to reduce virus transmission indoors relies on robust environmental monitoring methods. Monitoring viral pathogens is challenging because of frequent non-detect measurements that introduce uncertainty. For instance, a non-detect measurement could indicate either the absence of the pathogen or simply the lack of human respiratory activity and, thus, exposure. To aid in distinguishing these scenarios, this study identifies viruses from the human respiratory tract using publicly available sequencing data that can be incorporated into environmental monitoring as biomarkers of human respiratory activity. These viral biomarkers will improve indoor monitoring to help enact interventions to mitigate virus transmission. Furthermore, our approach to identify biomarkers from existing metagenomes can be adapted for future biomarker identification in any system.
28 May 2026
Read appraisal →The Science of the total environment
Ambient and personal air monitoring using low-cost sensors to identify elevated air pollution in vulnerable communities
In the United States, regulatory air monitoring networks are designed to assess regional air quality but do not capture neighborhood-level variability in pollutant concentrations. Low-cost air monitors may be one approach to address these gaps. The objective of this study was to evaluate whether neighborhood-level and personal monitoring identified increased concentrations of fine particulate matter (PM2.5) exposures in the neighborhood of Lower Price Hill (LPH), Cincinnati, Ohio, compared with regional regulatory monitors. We deployed a network of 12 PurpleAir monitors across LPH from April-June 2022 and calibrated measurements to a nearby U.S. EPA regulatory monitor. PM2.5 concentrations and Air Quality Index (AQI) values measured by the PurpleAir sensors were compared with two EPA monitoring sites. Additionally, three residents conducted 7-day personal monitoring using wearable AirBeam devices. Calibrated PurpleAir data demonstrated significantly increased PM2.5 concentrations at four of the 12 PurpleAir sites and increased AQI at 11 of the 12 PurpleAir sites in LPH compared to EPA regulatory sites. PurpleAir data also found that LPH experienced up to six days where AQI exceeded healthy levels (>50) but the EPA regulatory monitor did not exceed 50. Personal monitoring revealed substantial variability, with two of three participants exceeding the EPA 24-hour outdoor PM2.5 standard (>35 μg/m3) on all study days, indicating exposures not measured by outdoor stationary monitoring. Overall, regulatory monitoring may underestimate neighborhood-level and personal PM2.5 exposures in LPH. Community-based and personal monitoring provides novel insights into localized exposure disparities and may improve risk communication and inform interventions in vulnerable communities.
25 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
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
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 →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 infodemiology
Japanese-Language AI Agent System for Human Papillomavirus Vaccine Infoveillance and Public Communication: Development and Feasibility Evaluation
BACKGROUND: Human papillomavirus (HPV) vaccine hesitancy remains a significant public health challenge in Japan, where proactive vaccination recommendations were suspended between 2013 and 2021. The resulting information gap between medical institutions and vaccine-hesitant populations is exacerbated by misinformation on social media platforms. Traditional public health communication strategies cannot address individual queries while simultaneously monitoring population-level discourse. OBJECTIVE: This study aimed to develop and conduct a feasibility evaluation of a dual-purpose artificial intelligence agent system that delivers verified HPV vaccine information to the public through a conversational interface while generating infoveillance reports for medical institutions based on user interactions and social media discourse. METHODS: We implemented a system with 3 components: a vector database integrating 139,803 documents, including academic papers, Japanese government sources, news media, and social media posts; a retrieval-augmented generation chatbot using a ReAct agent architecture with iterative multitool orchestration across 5 specialized knowledge sources; and an automated report generation system with modules for news analysis, research synthesis, social media sentiment analysis, including stance classification and topic modeling, and user interaction pattern identification. System performance was assessed using both automated and manual evaluation protocols on a scale from 0 to 5. RESULTS: The entire system functioned as expected. For single-turn evaluation, the chatbot achieved mean scores of 4.83 (SD 0.67; 95% CI 4.71-4.93) for relevance, 4.89 (SD 0.53; 95% CI 4.79-4.97) for routing, 4.50 (SD 1.29; 95% CI 4.27-4.70) for reference quality, 4.90 (SD 0.62; 95% CI 4.78-4.99) for correctness, and 4.88 (SD 0.54; 95% CI 4.78-4.96) for professional identity, with an overall mean of 4.80. Multiturn evaluation yielded higher mean scores: 4.94 for context memory (SD 0.25; 95% CI 4.84-5.00) and an overall mean of 4.98, with topic centering and identity achieving 5.00. The report generation system achieved high scores across all sections: 4.83 for completeness (SD 0.37; 95% CI 4.73-4.94), 4.88 for correctness (SD 0.33; 95% CI 4.77-4.96), and 4.12 for helpfulness (SD 0.48; 95% CI 3.98-4.27). Reference validity achieved perfect scores (5.00) across all periods, with citation correctness averaging 4.21 (SD 0.58; 95% CI 3.96-4.46). CONCLUSIONS: This feasibility study demonstrated that an integrated artificial intelligence agent system can support both public HPV vaccine communication and social media infoveillance in a Japanese-language context. Prospective deployment with real users is needed to assess actual public health impact.
22 May 2026
Read appraisal →Biochemistry
Antimycobacterial Peptides: From Natural Product Discovery to AI Guided Design
Mycobacterial pathogens remain major global health threats, exacerbated by both rapid acquisition of antibiotic resistance and the formidable drug diffusion barrier presented by the rigid mycomembrane. These challenges have renewed interest in antimycobacterial peptides (AMyPs), a diverse class of short amphiphilic sequences capable of rapidly killing both drug-sensitive and drug-resistant mycobacteria. Beyond their intrinsic potency, AMyPs can synergize with existing antibiotics and exhibit markedly slower resistance development relative to conventional small molecules. In this review, we synthesize recent advances spanning natural bioprospecting, mechanism-guided rational design, and chemical optimization strategies that have yielded increasingly potent and selective AMyP candidates. We further highlight the rapid emergence of artificial intelligence-driven discovery platforms, which leverage machine-learning models trained on curated, mycobacteria-specific data sets to predict and refine novel AMyPs with growing accuracy. Together, these technologic, biologic, and computational advances outline a rapidly expanding landscape for AMyP-based therapeutic development and establish a foundation for next-generation antimycobacterial drug design.
21 May 2026
Read appraisal →Scientific reports
Analysis, control, and forecasting the dynamics of SIRD models with saturated treatment and nonlinear incidence
This study addresses the challenge of managing complex epidemic dynamics exhibited by a novel Susceptible-Infected-Recovered-Deceased (SIRD) model. The introduced model incorporates a biologically and behaviorally mediated nonlinear incidence rate alongside a saturated treatment function, realistically capturing both physical transmission risks and the human behavioral responses during an outbreak. Our comprehensive analysis establishes the mathematical rigor of the system through positivity, boundedness, and a detailed investigation of equilibrium points and bifurcations (transcritical, saddle-node, and Hopf), which reveal the potential for complex, oscillatory, and chaotic epidemic patterns. To mitigate the disease burden, we apply Pontryagin's Maximum Principle to derive optimal time-dependent prevention and treatment control strategies. Furthermore, we introduce a highly efficient machine learning framework based on a Logistic-Map Reservoir Computer (LMRC) for accurate, real-time forecasting of these complex dynamics. Numerical simulations validate the theoretical findings and reveal the model's rich dynamical behaviors, including stable limit cycles and chaotic regimes driven by parameter variations. The integrated analytical, control, and machine learning approach provides a robust toolkit for public health policymakers, offering data-driven insights crucial for designing adaptive, cost-effective interventions that directly support the achievement of Sustainable Development Goal 3 (Good Health and Well-being).
21 May 2026
Read appraisal →JMIR medical informatics
Extracting Social Determinants of Health From Electronic Health Records: Development and Comparison of Rule-Based and Large Language Model Methods
BACKGROUND: Social determinants of health (SDoH) are critical drivers of health outcomes but are often underdocumented in structured electronic health record (EHR) data. Instead, SDoH are more commonly recorded in unstructured clinical notes, and unlocking this information could have far-reaching implications for advancing population health research and informing clinical decision-making. OBJECTIVE: This study develops and systematically evaluates cost-efficient methods for extracting SDoH information from unstructured clinical text using rule-based natural language processing (NLP) and large language model (LLM)-based approaches. METHODS: We constructed a gold-standard annotated corpus comprising clinical text segments from 171 patients in the Mass General Brigham Research Patient Data Registry, covering 7 SDoH domain categories and 23 subcategories. A rule-based system (RBS) was developed and evaluated alongside 7 OpenAI GPT models (GPT-4o, 4.1, 4.1-mini, o4-mini, GPT-5, GPT-5-mini, and o3) under zero-shot and few-shot settings using multiple prompting strategies. We additionally implemented late-fusion ensemble approaches that combined outputs from rule- and LLM-based methods. Performance was assessed using precision, recall, and F1-score, alongside qualitative error analysis. RESULTS: The RBS achieved high precision for SDoH domain categories (0.96) but substantially lower recall (0.68). GPT-based models consistently outperformed the RBS in overall recall and F1-scores. The best domain-level performance was observed for GPT-5 and GPT-5-mini in few-shot settings (F1-score=0.89), while o4-mini achieved the highest subcategory-level performance (F1-score=0.88). A late-fusion ensemble integrating RBS and GPT outputs further improved domain-level performance (F1-score=0.92), with balanced precision (0.93) and recall (0.90), but did not improve subcategory-level performance. CONCLUSIONS: Recent GPT models with advanced reasoning capabilities, including the newly released mini models (eg, o4-mini and GPT-5-mini), demonstrated strong performance for SDoH extraction without task-specific fine-tuning and consistently outperformed the rule-based NLP system. Integrating rule- and LLM-based methods via late fusion further enhanced domain-level extraction performance. Our results demonstrate a cost-efficient framework for the accurate identification of SDoH from clinical text, facilitating downstream population health research and clinical informatics applications.
20 May 2026
Read appraisal →Revista do Instituto de Medicina Tropical de Sao Paulo
Treatment of brucellosis in pregnant women: a systematic review and analysis of current gaps and future perspectives
Human brucellosis is a globally prevalent bacterial disease with significant implications during pregnancy due to obstetric complications. Despite the importance of early diagnosis and treatment, the lack of therapeutic consensus and robust evidence underscores the need for systematic evaluation to guide clinical practice. This study systematically reviewed the literature to identify and summarize available drug therapy options for brucellosis in pregnant women, focusing on efficacy, safety, and obstetric outcomes. The review followed PRISMA and Cochrane Handbook guidelines. Searches were conducted in MEDLINE, Embase, Cochrane Library, LILACS, and gray literature for references indexed up to September 15, 2025. Eligible studies reported therapeutic interventions in pregnant women with brucellosis. Risk of bias was assessed using the JBI Critical Appraisal tool, and data on participants, interventions, and outcomes were extracted. Of 737 records screened, six studies met the inclusion criteria, comprising retrospective and prospective reports published between 1991 and 2020, totaling 403 pregnant women. Therapeutic regimens varied, with sulfamethoxazole-trimethoprim (SMX-TMP) plus rifampicin being the most frequently used combination. Adverse obstetric outcomes associated with this regimen occurred in 16% (95%CI: 8%-30%) of cases. Overall, abortion occurred in 94 (23.3%) women, 20 preterm births were reported, and 10 newborns had low birth weight. Recurrence was observed in only 3% of cases. Heterogeneity in outcomes and definitions limited comparability. In conclusion, there is no standardized treatment for brucellosis during pregnancy. Adverse obstetric outcomes remain frequent, highlighting the need for controlled studies to establish safe and effective therapeutic protocols.
20 May 2026
Read appraisal →Human vaccines & immunotherapeutics
Coverage and determinants of childhood immunization in Somalia: A systematic review and meta-analysis
Childhood immunization is a cost-effective public health intervention, yet coverage remains suboptimal in Somalia. This systematic review and meta-analysis aimed to pool childhood immunization coverage and its determinants in Somalia. The electronic database search strategy yielded 11 eligible cross-sectional studies conducted between 2010 and 2025. Using Comprehensive Meta-Analysis Version 5 (Biostat, Englewood, NJ, USA), the pooled coverage for receiving at least one vaccine was 57.9%, while completion of the four basic vaccines was 16.1%, Full immunization coverage was 42.2%. Children born in health facilities were more likely to be immunized than home births (AOR = 2.10; 95% CI: 1.87-2.35). Unexpectedly, mothers with ≥4 ANC visits had lower odds of child immunization (AOR = 0.27; 95% CI: 0.24-0.30). Maternal education increased immunization likelihood (AOR = 1.14; 95% CI: 1.09-1.20). Children in rural areas were likely to be immunized than urban counterparts (AOR = 1.55; 95% CI: 1.49-1.61). These findings highlight the urgent need to strengthen integrated maternal and child health services.
19 May 2026
Read appraisal →Expert review of vaccines
Approaches to observational study designs and analytical options to evaluate the safety of multi-dose vaccines: a systematic review
INTRODUCTION: Observational studies require careful considerations when evaluating the safety of multidose vaccines. We reviewed design and analytical approaches in observational studies evaluating the safety of multidose vaccines in the post-licensure phase. METHODS: EMBASE, MEDLINE, Web of Science, and Scopus (2018-2022) were searched for hypothesis-testing studies evaluating the safety of multidose vaccines. Key features from frequently used designs were extracted. RESULTS: Among 123 eligible studies, cohort (46%) and self-controlled case series (SCCS)/self-controlled risk interval (SCRI) (40%) followed by case-control (12%) were the most common designs, and 15% of studies used multiple designs. Among cohort studies evaluating multiple doses, vaccination date (36%) and cohort entry with time-updated exposure status (32%) were frequent approaches used to define time zero. Twenty-eight percent of cohort studies did not report time zero; all but one evaluated COVID-19 vaccine effect on post-delivery and fertility-related outcomes. For SCCS/SCRI, 64% of studies accounted for event-dependent exposures, mainly by including pre-exposure periods (53%) and modified SCCS model (48%), while 20% employed multiple correction strategies. Among studies using multiple designs, 68% reached consistent conclusions. CONCLUSIONS: SCCS/SCRI and cohort designs dominate multidose vaccine safety studies. Clear reporting on time zero in pregnancy and fertility-related cohort studies, and on addressing event-dependent exposures in SCCS/SCRI studies is needed, along with guidance on interpreting results from multiple designs. Observational studies are important for assessing safety of vaccines especially for rare health outcomes that cannot be easily detected in randomized trials. Commonly used approaches include comparing these health outcomes between vaccinated and unvaccinated individuals or between different time points in relation to vaccination timing within individuals. However, both approaches have important design challenges. For example, comparison between vaccinated and unvaccinated individuals requires careful consideration of alignment of the time of starting to observe outcomes with the time when individuals become eligible and vaccination time for both comparison groups (time zero). Within-individual comparison requires that earlier occurrence of health outcomes does not influence whether someone receives later vaccine dose(s). These challenges become more complex to address when vaccines are given in multiple doses.In this review, we assessed how important design and analytical issues are handled and reported in published studies evaluating the safety of multidose vaccines and assessed agreement between different study designs when more than one is used.We found that 28% of studies comparing vaccinated and unvaccinated groups did not clearly report time alignment (time zero) mostly with studies on pregnancy and fertility outcomes. Similarly, about one-third of studies using within-individual comparison did not report checking and addressing the possibility that earlier outcomes could influence future vaccinations. When multiple designs were used, two-thirds of studies reached similar conclusions, although comparisons were mainly qualitative. Future work is needed to guide clear reporting of these issues to improve transparency in design and analysis and when comparing results across different designs.
19 May 2026
Read appraisal →Drug discoveries & therapeutics
Trends in the prescription of constipation medications in Japan (fiscal years 2019-2023): A nationwide baseline study prior to the 2023 clinical guidelines.
Constipation is a common gastrointestinal disorder that markedly affects health and quality of life. In Japan, magnesium-based and contact laxatives have long been widely prescribed. Since the launch of lubiprostone in November 2012, several new agents with novel mechanisms have been introduced, and their use has increased. However, to our knowledge, no nationwide study has examined their use. This study aimed to analyze nationwide trends and regional differences in the prescription of medications for constipation. We used data from the Japanese National Health Insurance Claims and Specific Health Checkup Database Open Data from fiscal years (FYs) 2019 to 2023, covering the period when all currently available constipation medications were on the market in Japan, and prior to the inclusion of the drug selection flowchart in the Evidence-Based Clinical Guidelines for Chronic Constipation 2023. Prescription trends were evaluated using defined daily doses per 1,000 inhabitants per day (DID), and regional variations were assessed using standardized claim ratios (SCRs). The DID for contact laxatives decreased during the study period, whereas the DID for other constipation medications increased. Magnesium oxide showed the smallest regional variation, whereas polyethylene glycol and linaclotide showed the largest variations in FY 2019 and FY 2023, respectively. Throughout the 5-year period, the highest SCRs for contact laxatives were observed in Akita, Iwate, and Aomori prefectures. Our findings provide a comprehensive nationwide picture of evolving constipation treatment patterns and regional variations in Japan, establishing baseline data for evaluating the impact of guideline dissemination and evidence accumulation on clinical practice.
18 May 2026
Read appraisal →Journal of global health
Unveiling the gap in heart failure: a Brazilian Unified Health System study.
BACKGROUND: Heart failure (HF) decompensation is the leading cause of hospitalisations in developed countries and the third most common cause in Brazil. Underdiagnosis or misdiagnosis thereof remains a critical challenge and with significant implications. At the patient level, it delays appropriate treatment and disease management. At the health system level, it leads to inefficient population health strategies, distorted epidemiological estimates, and suboptimal resource allocation. Addressing this hidden HF population is therefore essential for improving disease surveillance, optimising care pathways, and supporting more effective and equitable health system planning in Brazil. In this sense, we aimed to quantify underreporting of HF in individuals in Brazil and to estimate their mortality trends. METHODS: We identified potential HF patients using a guideline-based flowchart that combines ICD-10 codes (e.g. I21, I25, I42) and HF-related procedures (e.g. echocardiography, B-type Natriuretic Peptide (BNP) testing). Then, we developed a machine learning model for early prediction of HF using the Brazilian Department of Informatics of the Unified Health System (Departamento de Informática do Sistema Único de Saúde) mortality information system and ambulatory information system records, 2018-2022. A CatBoost algorithm was trained on a balanced cohort of patients (10 000 with HF and 9 995 without HF), restricting predictors to ≥12 months before the first I50 code to prevent leakage. Key predictors included age, chronic kidney disease, echocardiography, and lipoprotein disorders. We validated model performance in independent cohorts, including a low-prevalence cohort (~2% HF). Finally, we derived underreporting estimates via deterministic sensitivity analysis across scenarios from 0-100%. RESULTS: The proxy identified approximately 54 000 potential HF cases/y that were unreported in ambulatory data, with deterministic analysis suggesting 12-41% underestimation. Mortality analysis showed that around 200 000 deaths could be linked to unreported HF. The CatBoost model achieved an area under the curve (AUC) of 0.91 (balanced cohort; accuracy = 0.82, recall = 0.81, F1 = 0.82) and maintained strong discrimination in low-prevalence settings (AUC = 0.84, sensitivity = 0.82), with excellent calibration (Brier = 0.124-0.136; ECE = 0.01-0.03). CONCLUSIONS: We found that HF underreporting in Brazil is substantial and carries significant mortality implications. Our ML model demonstrates high accuracy in early risk stratification using routine administrative data, aligning with clinical pathways. Implementing it as a screening tool could optimise resource allocation, but ethical considerations around false positives warrant careful deployment. Future work should focus on clinical validation and cost-effectiveness analysis within the Brazilian Unified Health System. Furthermore, our findings highlight significant implications for public health and clinical HF management, emphasising the necessity of strategies that promote early detection of HF and precise case recording. Addressing underestimation is crucial to optimise healthcare resources and improve patient outcomes. The results underscore the importance of accurate diagnosis and comprehensive management approaches for better HF case tracking. Further research should explore the public health impact of these underestimations in Brazil, particularly regarding its health system's financial resources.
18 May 2026
Read appraisal →Environmental pollution (Barking, Essex : 1987)
A systematic review of low-level ambient fine particulate matter (PM2.5) exposures and adverse cardiovascular health outcomes
Associations between exposure to fine particulate matter and impacts in the cardiorespiratory system are well-established, but associations are expected to vary based on exposure duration and concentration. Domestic and international agencies set standards and guidelines for PM2.5 in part to protect public health. This systematic review explores if associations exist between adverse cardiovascular endpoints and PM2.5 exposure when the concentrations are below regulatory standards. In total, 1349 documents were screened, with 95 articles meeting criteria (i.e. peer-reviewed, PM2.5 concentrations reported, cardiovascular endpoints measured). Of the included articles, 67% (64 articles) observed significant associations with adverse cardiovascular endpoints with variable findings based on specific cardiovascular endpoints (e.g. direct measurements - 69% of articles, cardiovascular endpoints - 44% of articles, events and mortality - 76% of articles, and biomarkers - 67% of articles). While not universally consistent, significant associations were observed between PM2.5 exposure and adverse cardiovascular effects, even at levels deemed compliant with current regulations. This review highlights the necessity for further research across diverse geographical settings and populations to clarify the implications of low-level PM2.5 exposure on cardiovascular health. The findings advocate for a review of regulatory standards for PM2.5 exposure in the context of cardiovascular health.
17 May 2026
Read appraisal →International journal of food microbiology
Machine learning-based modeling for monitoring and predicting the detection rate and severity of pathogenic microorganisms in seafood
Pathogenic microbial contamination in seafood presents persistent risks to food safety and public health. Conventional monitoring methods frequently lack adequate sensitivity and specificity, particularly under dynamic environmental conditions. To address these limitations, this study developed a machine learning (ML) framework utilizing microbial testing data from seafood samples collected in Yantai, China (2014-2024), with 2025 data reserved for external validation. The framework simultaneously predicts pathogen prevalence and severity levels. And, exploratory data analysis assessed variable distributions and statistical associations with detection rates. Time series analysis identified significant long-term trends and seasonal patterns, while spatial analysis revealed heterogeneity in contamination risk across administrative regions, particularly in coastal economic zones and major ports. Applying a dynamic threshold optimization strategy, detection rates were predicted using six ML algorithms: ROSE-LASSO, LightGBM, XGBoost, k-NN, CART, and SVM. LightGBM demonstrated optimal performance with 97.6% specificity and 99.9% positive predictive value (PPV) at an optimized threshold of 0.157. External validation confirmed its robustness, yielding 91.2% sensitivity, a 92.4% F1 score, and 93.6% PPV. For three-class severity classification, XGBoost achieved 93.7% overall accuracy and high sensitivity (80.0%) for high-risk samples, with an AUC of 0.989. By integrating spatiotemporal environmental features with adaptive thresholding, this framework provides a scalable approach for pathogen risk identification within coastal seafood supply chains, supporting early warning systems and evidence-based resource allocation.
17 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 →African journal of reproductive health
Domestic violence during pregnancy and its maternal and reproductive health consequences in mainland China: A systematic review and meta-analysis
Domestic violence during pregnancy represents a serious public health concern. This study conducted a systematic review of quantitative data to examine its prevalence, factors influencing it, and associated health outcomes in Mainland China. Following PRISMA 2020 guidelines, a meta-analysis of 25 studies was performed using random-effects models, alongside assessments of heterogeneity (I²) and publication bias. The analysis revealed a pooled prevalence of approximately 20%, with psychological violence identified as the most prevalent form. Key contributing factors included socio-economic disadvantage, restricted decisionmaking autonomy, and risky behaviors by partners. Exposure to domestic violence substantially heightened the likelihood of antenatal depression or anxiety, pregnancy complications, and negative birth outcomes such as low birth weight and preterm delivery. Although some heterogeneity was noted, the associations were consistently observed. These findings highlight the significant prevalence and severe health impacts of domestic violence during pregnancy, emphasizing the urgent need for comprehensive maternal healthcare approaches in China. Such strategies should integrate domestic violence screening, mental health services, and initiatives promoting socio-economic empowerment. La violence domestique pendant la grossesse constitue un problème de santé publique grave. Cette étude a réalisé une revue systématique des données quantitatives pour examiner sa prévalence, les facteurs l'influençant et les conséquences sanitaires associées en Chine continentale. Conformément aux directives PRISMA 2020, une méta-analyse de 25 études a été effectuée en utilisant des modèles à effets aléatoires, ainsi que des évaluations de l'hétérogénéité (I²) et du biais de publication. L'analyse a révélé une prévalence globale d'environ 20 %, la violence psychologique étant identifiée comme la forme la plus répandue. Les principaux facteurs contributifs comprenaient les désavantages socio-économiques, une autonomie décisionnelle restreinte et les comportements à risque des partenaires. L'exposition à la violence domestique augmentait considérablement la probabilité de dépression ou d'anxiété anténatales, de complications de la grossesse et d'issues défavorables à la naissance, telles qu'un faible poids de naissance et un accouchement prématuré. Bien qu'une certaine hétérogénéité ait été notée, les associations ont été constamment observées. Ces résultats soulignent la prévalence significative et les impacts sanitaires graves de la violence domestique pendant la grossesse, mettant en évidence le besoin urgent d'approches globales en matière de soins de santé maternelle en Chine. De telles stratégies devraient intégrer le dépistage de la violence domestique, des services de santé mentale et des initiatives favorisant l'autonomisation socio-économique.
16 May 2026
Read appraisal →Environmental research
Mental health benefits of specific blue space types and characteristics: A systematic evidence map.
Natural environments support mental health and wellbeing, yet limited evidence exists about which types or characteristics are most beneficial. This is particularly true for blue spaces (natural or manmade outdoor environments featuring water). This evidence map investigates the mental health and wellbeing benefits associated with specific blue space types (e.g. coast, river) and characteristics (e.g. sounds). Following PRISMA guidelines, specific keywords were used to search for articles published from inception to March 2025. A total of 139 papers were included, examining the relationships between specific blue space types or characteristics and mental health. Coastal environments were the most frequently studied blue space (94 studies). Affect was the most assessed mental health outcome (74 studies). Most studies were conducted in European and Asian countries. Most studies compared blue spaces to urban or a green space environments, rather than other blue spaces. Only six studies directly compared different blue space types within the same study. Overall, the current evidence base does not allow for comparisons between different blue space types or characteristics, due to the limited number of direct comparisons and substantial heterogeneity across study designs, outcome measures, geographical contexts, blue space descriptions, and study populations. Future research should prioritize direct comparisons between different blue spaces, preferably including the detailed descriptions and analyses of specific characteristics, and examine the role of amount and type of exposure to better inform evidence-based recommendations for blue spaces and mental health.
16 May 2026
Read appraisal →BMJ global health
Integrated mass drug administration for yaws eradication: evidence from a comparative observational study in Papua New Guinea and a systematic review with network meta-analysis
BACKGROUND: Yaws is a chronic infectious disease that disproportionately affects under-reached communities. In 2023, Papua New Guinea (PNG) reported 100 165 suspected yaws cases, accounting for 45% of cases reported worldwide. The WHO targets yaws eradication by 2030, primarily through mass drug administration (MDA) of azithromycin. This study evaluates the impact of an integrated MDA programme in PNG and reviews global evidence on optimal MDA strategies through a network meta-analysis (NMA). METHODS: A comparative observational study was undertaken analysing outpatient department (OPD) attendances between West New Britain province (WNB; intervention) and New Ireland province (NIP; comparator) from November 2023 to August 2024. The intervention in WNB involved a single-round, integrated four-drug MDA provided in December 2023, comprising azithromycin, ivermectin, diethylcarbamazine and albendazole. Temporal trends in OPD attendances were analysed using negative binomial regression. A Bayesian NMA of six studies identified through a systematic review compared the effectiveness of azithromycin-based regimens for yaws eradication. RESULTS: Between Q3 2023 and Q1 2024, yaws-related OPD attendances in WNB declined significantly, with a 41% (p<0.0001) reduction relative to the comparator province (NIP). This reduction was sustained for at least 6 months following MDA. Over the same period, a 33% decline in total skin-related outpatient attendances was observed. In the NMA, three rounds of azithromycin MDA were associated with lower odds of active yaws at follow-up than observation (OR 0.04, 95% CrI 0.005 to 0.24) and had the highest probability of being ranked most effective. Single-round azithromycin MDA was also associated with reduced odds of active yaws at follow-up (OR 0.15, 95% CrI 0.05 to 0.45). CONCLUSION: In a high-burden setting, a single round of integrated MDA was associated with substantial early reductions in yaws burden. Multi-round azithromycin strategies, particularly three-round regimens, were associated with larger and more sustained reductions in community prevalence. These findings inform considerations for yaws control efforts in settings with persistent transmission.
15 May 2026
Read appraisal →Journal of the American College of Cardiology
Global Hypertension 2000 to 2020: Trends, Disparities, and Progress in Awareness, Treatment, and Control
BACKGROUND: Hypertension is the leading preventable risk factor for premature death worldwide. Accurate estimates of prevalence and control are critical for developing public health priorities. OBJECTIVE: This study sought to examine global variations in hypertension prevalence, awareness, treatment, and control by world economic region and compare secular changes from 2000 to 2020. METHODS: A systematic search of MEDLINE from January 1995 to November 2024 was supplemented with manual searches of article references. Population-based cross-sectional surveys reporting age- and sex-specific hypertension prevalence and using standardized blood pressure measurement methods were included. Sex- and age-specific prevalence by country was applied to population counts to calculate the number with hypertension regionally and worldwide. Country-specific percentages of awareness, treatment, and control were applied to numbers of adults with hypertension to obtain regional and global estimates. Hypertension was defined as mean systolic blood pressure ≥140 mm Hg, diastolic blood pressure ≥90 mm Hg, or use of antihypertensive medication. RESULTS: We included 287 studies conducted in 6,060,567 adults from 119 countries. In 2020, 33.0% (95% CI: 32.5%-33.5%), or 1.71 (95% CI: 1.65-1.77) billion, of the world's adults had hypertension: 30.1% (95% CI: 29.4%-30.9%), or 395 (95% CI: 394-396) million, in high-income countries and 33.4% (95% CI: 32.8%-33.9%), or 1.32 (95% CI: 1.26-1.38) billion, in low- and middle-income countries. From 2000 to 2020, age-standardized prevalence decreased by 2.7% and absolute burden increased by 76 million in high-income countries compared with increases of 5.8% in prevalence and 651 million in absolute burden in low- and middle-income countries. From 2000 to 2020 in high-income countries, awareness increased from 57.7% to 69.2%, treatment from 42.9% to 66.3%, and control from 16.4% to 40.2%. More modest increases were observed in low- and middle-income countries: awareness from 29.1% to 46.1%, treatment from 20.7% to 30.8%, and control from 6.4% to 13.6%. CONCLUSIONS: The burden of hypertension is increasing, as are disparities between high-income countries and low- and middle-income countries. Urgent efforts are needed to address hypertension worldwide, particularly in low- and middle-income countries.
15 May 2026
Read appraisal →Journal of the American College of Cardiology
Behavioral Economics and Medication Adherence for Hypertension: A Randomized Clinical Trial
BACKGROUND: Nonadherence to antihypertensive medications is common. Mobile health (mHealth)-based behavioral economic interventions may improve adherence, but remain largely untested, especially in vulnerable populations. OBJECTIVE: The study sought to test whether an mHealth incentive lottery would lower systolic blood pressure (SBP) and improve adherence. METHODS: BETTER-BP (Behavioral Economics Trial To Enhance Regulation of Blood Pressure) was a randomized trial conducted in 3 safety-net clinics in New York City. Eligible participants were adults with hypertension prescribed at least 1 antihypertensive medication, with SBP >140 mm Hg, and poor self-reported adherence. In the intervention arm, an incentive lottery was administered via SMS messaging. All participants received passive adherence monitoring. The intervention lasted 6 months, with continued monitoring until 12 months. The primary clinical endpoint was change in SBP at 6 months. The primary process endpoint was adequate antihypertensive medication adherence (≥80% days adherent) from baseline to 6 months. RESULTS: Four-hundred participants (265 intervention:135 control) were enrolled with median age 57 years, 60.5% women, 61.5% Hispanic, and 20.3% non-Hispanic Black. Over 70% had Medicaid or no insurance. At 6 months, intervention arm participants were twice as likely to achieve adequate adherence (71% vs 34%; adjusted risk ratio: 2.04; 95% CI: 1.58-2.63), but there was no significant change in mean SBP (-6.7 mm Hg intervention vs -5.8 mm Hg control; P = 0.62). From 6 to 12 months, adherence was similar (31% intervention vs 26% control; adjusted risk ratio: 1.17; 95% CI: 0.83-1.65). CONCLUSIONS: In a diverse safety-net population, the BETTER-BP intervention doubled the rate of adequate antihypertensive medication adherence but did not reduce SBP at 6 months.
14 May 2026
Read appraisal →PloS one
Healthy living environments create healthy physical activity-related habits (ELEVATE): A protocol for a smartphone-based mixed-method study
Physical inactivity remains a key risk factor for adverse public health outcomes, disproportionately burdening lower socioeconomic groups. While individual-level interventions may temporarily increase walking-related physical activity (WPA) for some, they rarely achieve population-wide benefits. In contrast, built and natural environments are better positioned to support sustained WPA at the population level. Despite the importance of the environment to WPA, state-of-the-art research has limitations: it often relies on cross-sectional self-reports, uses coarse, simplistic environmental indicators, and focuses narrowly on residential neighborhoods, overlooking the diverse streetscapes people encounter in daily mobility. Using a transdisciplinary approach, ELEVATE addresses these gaps by 1) assessing how adults perceive and experience the built and natural streetscape environment during their WPA, 2) longitudinally assessing the relationships between streetscape environments and WPA, and 3) developing an artificial intelligence-powered system to suggest place-based environmental interventions that promote WPA. ELEVATE will employ a mixed-methods study design grounded in participatory co-creation, on-site and walk-along interviews to capture the everyday practices and experiences of WPA. We will use deep learning to extract objective environmental features and perceived streetscape qualities from street view images. A sample of approximately 200 adults residing in Amsterdam, The Netherlands, will be recruited. To examine relationships between micro-scale streetscape features and WPA, we will collect seven days of intensive longitudinal data using smartphones, including global positioning system (GPS)-based mobility and step counts. We will use spatiotemporal clustering to identify where people are most and least physically active, and mixed models to assess associations between these environmental measures and step counts. Qualitative and quantitative results will be triangulated in co-created focus groups. Finally, to support evidence-based public health and urban planning interventions, we will develop an AI-powered recommender system that generates context-sensitive (re)design guidelines framing the built and natural environment as a modifiable determinant of WPA. This study will generate evidence on how micro-scale built and natural street environments encountered during daily mobility are associated with WPA in adults. The findings are expected to inform place-based public health strategies by identifying modifiable environmental characteristics associated with physical activity and socioeconomic inequalities in urban settings.
13 May 2026
Read appraisal →PloS one
Burden and predisposing factors of physical inactivity among adults in Africa: Systematic review and Meta-analysis
INTRODUCTION: Physical inactivity is a primary driver of global mortality, data on its specific impact in Africa remains fragmented. We conducted this study to provide the first comprehensive pooled prevalence and identify predisposing factors contributing to physical inactivity among African adults. METHOD: We searched PubMed, Scopus, Embase, and Google Scholar for studies published between March 1, 2010, and March 31, 2025. A quality assessment of the studies was performed through the Newcastle-Ottawa Scale (NOS). The random-effect (DerSimonian) model was used to calculate the aggregated rates of physical inactivity among adults and their predisposing factors. Heterogeneity was assessed using the I2 statistic, along with subgroup and sensitivity analyses. Publication bias was evaluated using Egger's test, and all analyses were performed in STATA, version 17. RESULTS: This systematic review and meta-analysis included 34 studies with a total of 41,521 participants. The pooled prevalence of physical inactivity was 45% (95% CI: 35%-55%), and there was considerable heterogeneity (I2 = 98.4%). The highest prevalence of 57% (95% CI: 0.33, 0.81) I2 = 97.7 seen in 2013 and the lowest prevalence 28% (95% CI: 0.03, 0.53) I2 = 94.3%) observed in 2011. This study identified that, being female (OR = 1.87; 95% CI: 1.55, 2.25), Adults aged ≥ 60, (OR=2.18; 95% CI:1.98,4.77), being obese (OR=3.52; 95% CI: 2.26,5.49), urban dweller (OR=1.91, 95% CI:1.24,2.95), being overweight (OR=2.03; 95% CI: 1.61,2.68), depression symptom (OR= 1.34;95% CI: 1.07,1.68) and more drinking of alcohol (OR=1.73; 95% CI: 1.18,2.64), were significant predisposing factors associated with prevalence of physical inactivity. CONCLUSION: A high level of physical inactivity was observed amongst the African adults. Our findings indicate that female gender, older age, being overweight and obese, high levels of alcohol consumption and depression are significant predictors of physical inactivity in the African population. Promoting awareness about the positive impacts of regular exercise on health among women and an elderly age group could effectively lower the chances of hypokinetic diseases.
13 May 2026
Read appraisal →Journal of computer-aided molecular design
Ensemble learning-guided discovery of anti-tuberculosis phytochemicals: computational prediction and mechanistic insights
Tuberculosis (TB) remains a major global health challenge driven by persistent Mycobacterium tuberculosis infection and increasing drug resistance. Phytochemicals represent a structurally diverse and underexplored chemical space for anti-TB drug discovery, yet systematic prioritization strategies integrating machine learning and structure-based validation are limited. A curated phenotypic anti-TB dataset of 425,180 compounds was used to train ensemble ExtraTrees models based on ECFP4 fingerprints and physicochemical descriptors. The models achieved strong predictive performance (ROC-AUC up to 0.983; MCC up to 0.871). SHAP analysis enabled mechanistic interpretation by identifying the key molecular descriptors and fingerprint features driving anti-TB activity predictions. The validated ensemble was applied to screen 4707 phytochemicals, yielding 3209 predicted actives, of which 778 satisfied applicability domain criteria. High-confidence candidates were subsequently evaluated by molecular docking against twelve structurally validated essential M. tuberculosis targets spanning cell wall biosynthesis, energy metabolism, nucleotide synthesis, and cofactor pathways. Docking analysis identified 486 phytochemicals with favorable predicted binding affinities, including 193 compounds exhibiting multi-target engagement. Several top-ranked candidates reproduced canonical interaction patterns of co-crystallized inhibitors, supporting mechanistic plausibility. This integrated chemoinformatics and structure-based framework enables robust prioritization of phytochemicals with biologically meaningful and multi-target antitubercular potential. The study provides a computationally grounded strategy for accelerating lead identification against drug-resistant TB.
13 May 2026
Read appraisal →Lancet (London, England)
Long-term effects of colonoscopy screening on colorectal cancer incidence and mortality: a multicountry, population-based randomised controlled trial
BACKGROUND: We previously reported the 10-year effects of colonoscopy screening on colorectal cancer incidence and mortality. Here, we report the effects after 13 years of follow-up. METHODS: In this multicountry, population-based randomised controlled trial, 84 583 men and women aged 55-64 years at enrolment from Norway, Poland, and Sweden were randomly allocated (1:2) to colonoscopy screening or no screening and analysed. The primary outcomes were colorectal cancer incidence and mortality after 10-15 years of follow-up in intention-to-screen analyses, with first analysis after 10 years, and repeated every other year or at longer intervals. This trial is registered with ClinicalTrials.gov, NCT00883792, and is ongoing. FINDINGS: At 13 years of follow-up, colorectal cancer incidence was 375 colorectal cancers (1·46%) of 28 217 individuals in the screening group and 912 colorectal cancers (1·80%) of 56 366 individuals in the no-screening group. The risk ratio (RR) was 0·81 (95% CI 0·71-0·90) in intention-to-screen analyses and 0·55 (0·33-0·81) in per-protocol analyses. The risk for proximal colorectal cancer was 129 (0·51%) in the screening group versus 283 (0·56%) in the no-screening group (RR 0·91 [0·71-1·09]), and the risk for distal colorectal cancer was 224 (0·87%) in the screening group versus 563 (1·11%) in the no-screening group (RR 0·79 [0·65-0·89]; interaction p<0·0001). In men, the colorectal cancer risk was 214 (1·69%) of 14 154 in the screening group and 541 (2·19%) of 28 247 in the no-screening group (RR 0·77 [0·64 to -0·88]); in women, the risk was 161 (1·24%) of 14 063 in the screening group versus 371 (1·43%) of 28 119 in the no-screening group (RR 0·87 [0·70 to 1·02]; interaction p<0·0001). Colorectal cancer mortality was 106 (0·41%) of 28 217 in the screening group and 236 (0·47%) of 56 366 in the no-screening group (intention-to-screen RR 0·88 [0·68-1·08], per-protocol RR 0·70 [0·26-1·25]). The observed colorectal cancer mortality in the non-screening group (0·47%) was substantially lower than expected at the time of designing the trial (0·82%). INTERPRETATION: One colonoscopy significantly reduced colorectal cancer incidence but not mortality over 13 years. Colorectal cancer mortality was lower in both study groups than when the trial was designed. FUNDING: The Norwegian Research Council, the Nordic Cancer Union, the Norwegian Cancer Society, and the Health Fund of South-East Norway.
13 May 2026
Read appraisal →Expert review of vaccines
Population-level impact of HPV vaccination: a global systematic review of ecological, cross-sectional, and cohort studies
BACKGROUND: Human papillomavirus (HPV) causes approximately 4.5% of cancers globally, with the highest burden in low- and middle-income countries (LMICs). Since their introduction in 2006, HPV vaccination programs have led to substantial declines in HPV-related outcomes, although impact varies across settings. RESEARCH DESIGN AND METHODS: We conducted a systematic review to evaluate the population-level impact of HPV vaccination on HPV infection, cervical intraepithelial neoplasia grade 2 or higher (CIN2+), genital warts, invasive cervical cancer (ICC), and oropharyngeal cancer (OPC), and examined the influence of coverage, age at initiation, and vaccine type. The review followed PRISMA 2020. RESULTS: Of 13,549 records screened, 63 were included: 9 assessed HPV infection, 24 on CIN2+, 25 on genital warts, and 7 on ICC. Greatest reductions were observed in settings with at least 70% coverage and early vaccination prior to sexual debut, typically achieved through school-based programs. Reported declines ranged from 58-100% for HPV infection, 30-88% for CIN2+, 60-90% for genital warts, and 70-88% for ICC. CONCLUSIONS: HPV vaccination offers strong protection, especially when delivered early and at high coverage within schools. Expanding access and prioritizing underserved populations are essential to achieving global cancer prevention goals. Limitations include heterogeneity across designs, outcome definitions, and follow-up.
13 May 2026
Read appraisal →Vaccine
The immune response of the mRNA vaccine CS-2034 as a heterologous booster before and after breakthrough infection: A follow-up study.
BACKGROUND: The emergence of highly mutated SARS-CoV-2 variants challenges vaccine protection. Evaluating long-term immune protection from boosters is crucial. The experiment compares neutralizing antibody dynamics and ACE2-RBD binding inhibition induced by mRNA and inactivated vaccine boosters, and assesses the impact of breakthrough infections and age on immune responses. METHODS: This study is based on a previous randomized, double-blind, parallel controlled trial. Healthy participants aged ≥18 who had received ≥3 inactivated COVID-19 vaccine doses. Volunteers (32 aged 18-59 and 32 ≥ 60) were stratified by age and vaccine type (24 mRNA, 8 inactivated in each age group). Pregnant women, those with severe chronic diseases or a history of allergies are excluded. Neutralizing antibodies were measured via microneutralization assay, and ACE2-RBD binding inhibition by high-sensitivity electrochemiluminescence. The study assessed changes in antibody levels and ACE2-RBD binding inhibition pre- and post-infection across age groups to evaluate vaccine efficacy and durability. (Registed number: ChiCTR2200064575). RESULTS: The neutralizing antibody titers from mRNA vaccine showing stronger and more consistent responses against the original strain and variants like XBB and BA.5. After breakthrough infections, mRNA-vaccinated individuals show a significant and lasting boost in antibodies, while the increase in inactivated vaccine recipients is modest. By age, mRNA-vaccinated people over 60 experience a faster antibody decline post-vaccination, whereas the inactivated vaccine group sees an initial rise at three months before declining. For ACE2-RBD binding inhibition, mRNA vaccines maintain higher early-phase rates, while inactivated vaccines show a delayed rise at three months followed by decline. CONCLUSIONS: mRNA vaccines induce stronger neutralizing antibodies and broader immunity than inactivated vaccines. Breakthrough infections boost antibody levels more in mRNA recipients than in inactivated vaccine recipients. Antibody decline is faster with mRNA vaccines in people over 60, while inactivated vaccines show a modest but weaker antibody increase against variants in the elderly.
13 May 2026
Read appraisal →Vaccine
Factors affecting human papillomavirus vaccination: A review of individual, interpersonal, and structural factors affecting vaccine uptake among adolescents.
BACKGROUND: Human papillomavirus (HPV) related cancers, particularly cervical cancer, remain a major public health challenge in low- and lower-middle-income countries (LLMICs), which bear a disproportionate share of global HPV-attributable mortality. Despite the availability of safe and effective vaccines for nearly two decades, vaccination coverage remains low in LLMICs. Several barriers ranging from health misinformation to systemic delivery challenges have hindered efforts to scale up vaccination programs in these settings. OBJECTIVES: This systematic review aims to identify and synthesize the behavioral and structural factors influencing HPV vaccine uptake among adolescents in LLMICs. Guided by a multi-level behavioral health framework, findings were categorized across: individual, interpersonal, and structural domains. METHODS: A comprehensive search of seven databases identified 639 records, of which 34 empirical studies met inclusion criteria. Eligible studies focused on HPV vaccination uptake among adolescents in World Bank-defined LLMICs and were assessed for thematic relevance. Data extraction emphasized barriers and facilitators to uptake. RESULTS: Individual-level barriers included limited awareness, misconceptions about HPV and the vaccine, and fear of side effects. Interpersonal dynamics-particularly parental consent, gendered norms, and community endorsement-shaped adolescent vaccine decision-making. Structural barriers included vaccine stock-outs, weak delivery infrastructure, and limited reach among out-of-school youth. School-based delivery models, trusted healthcare workers, and community sensitization emerged as key facilitators. CONCLUSIONS: Improving HPV vaccine coverage in LLMICs requires coordinated, multi-level interventions that simultaneously address behavioral and structural determinants. Findings highlight the critical role of community engagement, flexible delivery models, and long-term sustainability planning to ensure effective implementation. These insights have direct implications for national immunization policy, health system strengthening, and achievement of global cervical cancer elimination targets in resource-limited settings. Tailoring implementation to the contextual realities of LLMICs will be essential to advancing equity in HPV-related cancer prevention.
13 May 2026
Read appraisal →Immunologic research
An integrated AI-driven vaccine design process: a systematic review of workflows from generative design to translational prediction
Traditional vaccine development faced significant hurdles, including lengthy timelines and high costs, which hindered rapid responses to pathogens. Although the emergence of AI offered transformative potential, the necessity for a fully integrated workflow was often overlooked in studies focusing on individual tools. This review addressed a critical gap by synthesizing AI technologies across the vaccine design process, focusing on the integrated workflow from antigen discovery to clinical translation. A systematic framework was required to connect disparate tools and ensure seamless transitions. Consequently, this study provided a comprehensive roadmap for pandemic preparedness and vaccine discovery. A systematic analysis based on the PRISMA framework (2015-2024) was conducted, and 19 landmark articles were reviewed.It was demonstrated that the paradigm shift from predictive to generative AI offered unprecedented opportunities for developing novel antigens and adjuvants with superior immunogenicity. Synthesis of the literature revealed rapid progress toward sophisticated deep learning. Transformer models and Protein Language Models emerged as dominant for epitope prediction, while AlphaFold2 became the standard for structural modeling. The advent of generative AI for de novo antigen design represented the leading edge of the discipline. Additionally, AI-enhanced molecular dynamics and digital twin simulations accelerated clinical validation and manufacturing scalability. The "Integrated AI Workflow for Vaccine Design and Development" was emphasized as a comprehensive system and a prerequisite for sustainable innovation. Overall, this analysis served as a strategic roadmap for utilizing AI as a transformative framework for next-generation vaccine discovery and pandemic preparedness.
12 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 →Journal of medical Internet research
The Digital Exposome: A Life Course Framework for Health in the Digital Age
Digital technologies are reshaping human behavior, health care delivery, and population health; however, their cumulative effects across the lifespan remain underexplored. This viewpoint argues that exposures arising from interactions with digital technologies should be formally integrated into exposome science as a distinct, measurable component of the human environment. Our aims are to (1) redefine the digital component of the exposome (the digital exposome) within the broader exposome framework, (2) examine its life course implications for health and equity, and (3) outline a research and policy agenda to enable its systematic measurement and integration into clinical and public health practice. Digital technology-related exposures can confer benefits such as enhanced health monitoring, personalized interventions, improved access to care, and the promotion of healthy behaviors. However, they may also introduce potential risks, including mental health challenges, cognitive and circadian disruptions, sedentary lifestyles, exposure to misinformation, and widening inequities among vulnerable populations. Despite their ubiquity, digital technology-related exposures remain poorly integrated into clinical medicine, epidemiology, or public and global health policies. Drawing on interdisciplinary evidence from exposure science, epidemiology, and digital phenotyping research, we propose a refined conceptual definition of the digital exposome grounded in the classical exposome domains. We propose redefining the digital exposome as the full spectrum of exposures resulting from interactions or proximities with digital technologies and their combined influence on health across the lifespan. This framework conceptualizes digital technology-related exposures as a dynamic set of environmental influences operating through sociotechnical, behavioral, and biological pathways over the life course. To operationalize this framework, we discuss practical approaches using validated behavioral instruments, objective device use logs, ecological momentary assessments, smartphone-based digital phenotyping, and wearable sensing technologies. Systematic measurement, large-scale longitudinal studies, and harmonized exposure metrics are needed to characterize the cumulative health impacts of digital environments more accurately. Emerging tools such as digital markers or biomarkers and digital phenotypes offer promising opportunities to link real-world technology use with physiological and biological outcomes, thereby supporting precision medicine and population health strategies. Ethical governance, privacy safeguards, and equity considerations must be embedded from the start, drawing on emerging exposomethics frameworks. Recognizing the digital exposome as a modifiable determinant of health offers a foundation for evidence-based guidance, prevention strategies, and policy interventions suited to increasingly digital societies. By integrating digital technology-related exposures into exposome science, clinical practice, and public health research, this viewpoint seeks to foster interdisciplinary dialogue, guide future empirical work, and support the development of safer and more equitable digital environments across the lifespan.
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 →Journal of global health
The effectiveness and cost-effectiveness of cash plus interventions to prevent acute malnutrition in Somalia: evidence from an adaptive cluster randomised control trial
BACKGROUND: Acute malnutrition affects millions of children aged <5 years, as well as pregnant and lactating women globally, especially in humanitarian settings. Although cash plus interventions - cash or food transfers combined with complementary components - are widely implemented, evidence remains limited on which combinations and durations are most effective at preventing acute malnutrition. METHODS: We conducted a three-arm cluster-randomised trial within the 'Save the Children's Cash Plus for Nutrition' programme in Somalia. Monthly support was provided as cash alone (arm 1), cash plus social and behaviour change communication (arm 2), or cash plus an additional cash top-up (arm 3). Further, we randomised 33 villages across arms, targeting approximately 1500 households. Primary outcomes included the prevalence and incidence of acute malnutrition in children aged 6-59 months and in mothers, assessed at baseline, midline (three months), and endline (six months). We also conducted market monitoring, qualitative data collection, and analysis. RESULTS: Child acute malnutrition prevalence was approximately 15.0% in each arm at baseline. After three months, prevalence declined by 2.0 percentage points in arm 1 to 13.0% (95% confidence interval (CI) = 10.3, 16.1), representing a relative reduction of 13.3%. In arm 2, prevalence declined by 5.9 percentage points to 9.1% (95% CI = 6.8, 11.8), a relative reduction of 39.3%. In contrast, prevalence in arm 3 remained essentially unchanged, increasing to 15.1% (95% CI = 12.1, 18.6). By endline, there was little change from midline in all arms. Maternal malnutrition improved most in arm 2, but differences were not statistically significant. All arms showed improvements in dietary diversity and food security, but only arm 2 achieved sustained nutrition gains. Household livelihood conditions appeared to improve overall, though monthly expenditures nearly doubled. Arm 2 was the most effective and cost-effective. CONCLUSIONS: Adding social and behaviour change communication to cash transfers significantly improved child nutrition compared to cash alone, highlighting that integrated approaches can enhance nutritional outcomes and at minimal additional cost in humanitarian settings. REGISTRATION: ClinicalTrials.gov: NCT06642012.
12 May 2026
Read appraisal →Environmental health : a global access science source
Building the model: a review of input structures in extreme temperature-health
BACKGROUND: The health impacts of extreme temperatures have been extensively studied through epidemiological models. However, limited attention has been paid to the specification of these models, particularly regarding input structure and model selection. Although exposure metrics and statistical techniques have evolved over time, a comprehensive synthesis of the variables included in these models, and the rationale behind their inclusion, is still lacking. This gap limits the comparability of studies and may compromise the robustness of temperature-health evidence. METHODS: We conducted a systematic review of peer-reviewed studies published between 2014 and 2024 that employed quantitative epidemiological models to estimate the association between extreme temperatures and health outcomes. Following PRISMA guidelines, we selected 119 studies through searches conducted in Scopus, PubMed, and Web of Science. Each study was analysed in terms of spatial coverage, modelling framework, and model inputs. Inputs were classified into six functional groups: thermal exposures; environmental covariates (including both non-thermal meteorological variables and air pollutants); temporal controls; socio-demographic factors; health system indicators; and built environment characteristics. RESULTS: Substantial heterogeneity was observed in both input selection and model specification. Daily mean temperature was the dominant exposure metric, though rarely justified over alternatives. Environmental covariates were inconsistently included: while relative humidity was frequent, other meteorological modifiers and air pollutants were often omitted without clear rationale. Temporal adjustments were common but heterogeneous. Distributed lag non-linear models were the prevailing framework, varying greatly in lag structure, spline specification, and covariate integration. Socio-economic, health, and infrastructural indicators appeared in less than one third of studies, typically as effect modifiers in meta-regression analyses, highlighting uneven integration of contextual determinants. No consensus currently exists on what constitutes a minimum model specification necessary to ensure reliable and interpretable effect estimates. CONCLUSIONS: Current temperature and health modelling remains fragmented, with notable variability in input specification and transparency. Strengthening methodological coherence through clearer guidance on input selection is essential. Greater integration of socio-economic and infrastructural variables would further enhance models' capacity to capture contextual vulnerability. To ensure reliability and policy relevance, future research should develop shared guidelines for input specification, define minimum modelling standards, and promote transparent reporting of analytical decisions.
11 May 2026
Read appraisal →Journal of medical Internet research
Effects of Stand-Alone Digital Lifestyle Interventions on Weight-Related Outcomes in Adults With Overweight or Obesity: Systematic Review and Meta-Analysis of Randomized Controlled Trials
BACKGROUND: Obesity is a major global health concern, and scalable digital solutions are urgently needed. While digital lifestyle interventions (DLSIs) have shown promise, prior meta-analyses often included hybrid formats with human support, limiting insights into the effectiveness of fully digital interventions. OBJECTIVE: This study aimed to evaluate the independent effects of standalone DLSIs-defined as interventions delivered exclusively via digital platforms without in-person or adjunctive support-on anthropometric and dietary outcomes in adults with overweight or obesity. METHODS: We searched MEDLINE, Embase, PsycINFO, Web of Science, and the Cochrane Library from inception through March 4, 2026. Eligible studies were randomized controlled trials (RCTs) evaluating stand-alone DLSIs in adults with overweight or obesity. Interventions were included if they targeted diet or physical activity exclusively through digital platforms. We included fully automated, asynchronous, or one-to-many synchronous systems without individualized support. Studies involving hybrid interventions, including one-to-one synchronous human interaction, nonadult populations, or non-RCT designs, were excluded. Two independent reviewers performed study selection and data extraction. Risk of bias was assessed using the Cochrane Risk of Bias 2.0 tool (Cochrane Bias Methods Group). Meta-analysis used a random-effects model with the Hartung-Knapp-Sidik-Jonkman method, and heterogeneity was assessed using I2 statistics. The certainty of evidence was evaluated using the Grading of Recommendations, Assessment, Development, and Evaluation approach. RESULTS: A total of 19 RCTs involving 3556 participants were included. Stand-alone DLSIs significantly improved anthropometric outcomes compared to controls (standardized mean difference 0.26, 95% CI 0.14-0.38; 95% prediction interval [PI] -0.16 to 0.68; P<.001; 19 studies; n=3556; I2=56.1%), corresponding to an additional weight loss ranging from 2.62 kg to 6.55 kg, depending on the baseline body weight. Significant improvements were also found in dietary outcomes (standardized mean difference 0.26, 95% CI 0.04-0.48; 95% PI -0.29 to 0.81; P=.008; 8 studies; n=1365; I2=57.5%). Subgroup analyses for anthropometric outcomes revealed significant differences only by control group type (P<.001), with waitlist controls showing the largest effect. For dietary outcomes, no significant subgroup differences were found (P>.05). While most studies showed a low risk of bias, substantial statistical heterogeneity was observed in some outcomes. Consequently, the certainty of evidence for both outcomes was rated as moderate. CONCLUSIONS: This review is innovative as it is the first to isolate the pure efficacy of stand-alone DLSIs by excluding synchronous human support. Our findings provide moderate-certainty evidence that these tools are effective for weight management and dietary improvement without human intervention. While stand-alone DLSIs offer a highly scalable, cost-effective first-step intervention, the PIs included zero, and substantial heterogeneity was observed, suggesting that benefits may vary across settings. Future research should identify user characteristics that maximize engagement with unguided digital tools.
11 May 2026
Read appraisal →BMJ open
Does previous pregnancy experience improve folic acid supplementation uptake? A systematic review and meta-analysis.
OBJECTIVE: To examine whether multiparous women have more or less folic acid uptake than primiparous women. OUTCOMES: Preconceptional, periconceptional and postconceptional folic acid use among all pregnant women and high risk pregnant women. DESIGN: Systematic review and meta-analysis. DATA SOURCES: MEDLINE-Ovid, CINAHL Ultimate, Scopus and ProQuest Medical. ELIGIBILITY CRITERIA: Observational epidemiological studies comparing folic acid use between primiparous and multiparous women, published in English from January 1994 to June 2024. DATA EXTRACTION AND SYNTHESIS: Two reviewers screened all papers meeting the eligibility criteria. One reviewer completed data extraction and assessed study quality using an adapted version of the Newcastle-Ottawa Scale. Three other reviewers independently assessed 10% of the studies as a quality check. Random-effects (DerSimonian and Laird) meta-analyses combined results for each outcome. Heterogeneity, risk of publication bias and certainty of evidence were assessed. RESULTS: Of the 10 982 records identified, 81 studies involving 826 855 women were included in the review. 27 studies were conducted in Europe, 22 in Asia, 11 in North America, 7 in Africa, 7 in Australia, 5 in the Middle East and 2 in South America. Multiparous women were consistently less likely to take folic acid before and during pregnancy than primiparous women. For preconceptional use, the odds were 29% lower among multiparous women (adjusted OR (aOR): 0.71; 95% CI 0.64 to 0.78; n=25 studies; I2=88.67%), and 58% lower in multiparous high-risk women (aOR: 0.42, 95% CI 0.27 to 0.64; n=3 studies; I2=27.28%). For periconceptional use, the odds were 32% lower among multiparous women (aOR: 0.68; 95% CI 0.63 to 0.74; n=28 studies; I2=85.46%). Postconception, the odds were 21% lower among multiparous women (aOR: 0.79; 95% CI 0.74 to 0.85; n=33 studies; I2=85.91%). By the second trimester, there was no significant difference between the two parity groups (aOR: 0.96; 95% CI 0.87 to 1.05; n=4 studies; I2=0.00%). The certainty of evidence was low for preconceptional, periconceptional and postconceptional uptake due to heterogeneity, and moderate for preconceptional uptake among high-risk women. CONCLUSIONS: Multiparous women were less likely to take folic acid preconceptional, periconceptional and postconceptionally, despite their previous pregnancy experience. Barriers to folic acid supplement uptake among multiparous women need to be identified, and strategies to address them in preconception, antenatal and interconception care should be investigated. PROSPERO REGISTRATION NUMBER: CRD42024553241.
11 May 2026
Read appraisal →Archives of orthopaedic and trauma surgery
Healthcare utilization following hip fractures based on social vulnerability status in the US: an analysis of 2016-2020 nationwide readmissions data
INTRODUCTION: Social vulnerability (SV) influences rehabilitation and postoperative care for patients with hip fracture. However, most previous work relies on area-level measures that overlook interindividual variation. The recent adoption of ICD-10 Z-codes allows clinical identification of patient-level SV and may offer a better understanding of its impact. This study aimed to evaluate healthcare utilization, including readmissions, discharge disposition, and length of stay (LOS) in surgically treated hip fracture patients with and without clinically acknowledged SV. METHODS: Adults surgically treated for hip fracture between 2016 and 2020 were included from the Nationwide Readmissions Database. SV was defined as having at least one documented relevant ICD-10 Z-code. Primary outcome measures included complications, LOS, discharge disposition, and 30- and 90-day readmissions, stratified by SV and evaluated using chi-square analyses. Multivariable logistic regression assessed long LOS (≥ 5 days) and discharge to home, adjusting for age, insurance/income status, and substance use. RESULTS: Patients with SV were younger (35.6% with SV vs. 50.1% without SV were 81+), had a lower median household income (38.8% with SV vs. 25.7% without SV were in the lowest quartile), and were more often insured by Medicaid (19.3% vs. 3.8%). Alcohol/drug use disorders were significantly more prevalent in patients with SV (18.5% vs. 4.5%). SV was associated with 47% higher odds for long LOS (1.47, 1.41-1.54) and 23% higher odds for discharge to home (1.23, 1.16-1.30) but comparable 90-day readmissions (21.2% vs. 19.8%). CONCLUSION: Among surgically treated hip fracture patients, SV was associated with higher odds of long LOS and discharge to home but no meaningful difference in readmissions. The small number of patients with clinically documented SV highlights the limited reporting by healthcare workers. This analysis of a nationwide all-payer database highlights the need to identify these higher risk patients and implement appropriate care pathways to reduce healthcare utilization.
10 May 2026
Read appraisal →Annals of epidemiology
Population-based clustering of co-occurring social determinants: An application of unsupervised machine learning
PURPOSE: This study aimed to develop a cluster-based measure of multiple co-occurring social determinants of health by applying unsupervised machine learning to a population-based cohort, offering a data-driven approach to organize complex social exposures. METHODS: Unsupervised clustering was applied to a population-based cohort of Ontario respondents to six-cycles of the Canadian Community Health Survey (2001-2012) linked to the Canadian census and vital statistics data. Clusters were evaluated using internal metrics, visualization techniques, descriptive analysis and theoretical considerations to determine the optimal number of clusters. Sensitivity analyses were integrated across the iterative clustering process. Premature mortality rates were generated assess validity. RESULTS: Optimal clustering solutions included 4-clusters and 6-clusters. Both cluster solutions revealed distinct social typologies. The 6-cluster solution offered greater granularity and theoretical interpretability. The 4-cluster solution showed greater heterogeneity within certain marginalized groups. Premature mortality rates differed meaningfully across clusters, supporting the clustering approach in capturing risk associated with social exposure. CONCLUSIONS: Unsupervised machine learning methods identified meaningful population subgroups reflecting complex patterns of social exposures. This approach offers a flexible, data-driven method for characterizing social exposures that can be considered alongside theoretical frameworks and used for equity monitoring, intervention planning and policy development.
6 May 2026
Read appraisal →JMIR public health and surveillance
Integrating AI Into Governmental Public Health Decision Making: Challenges, Considerations, and a Path Forward
Public health emergencies such as pandemics, natural disasters, and epidemics may require rapid, high-stakes decisions often made by elected officials with limited public health training. Artificial intelligence (AI) holds significant promise to enhance the quality, transparency, and timeliness of governmental decision-making during such crises. This paper examines the potential of AI as a decision-support tool for elected officials while identifying key technical, logistical, ethical, and policy challenges. Technical considerations include model accuracy, data representativeness, and privacy protection, while ethical imperatives center on fairness, transparency, and accountability to prevent amplification of existing health disparities. The paper further explores workforce development needs, emphasizing AI literacy and cross-sector collaboration to enable informed use of AI insights. This viewpoint presents a novel AI Decision Support Lifecycle framework specifically designed for governmental public health emergency response, mapping six phases from problem definition through post-emergency evaluation. We provide stakeholder-specific recommendations for model developers, health agencies, and elected officials, and illustrate practical application through a detailed case example and use cases. Drawing on empirical evidence regarding digital health technologies and AI governance, we emphasize that technology deployment alone is insufficient. Successful implementation requires complementary investments in organizational capacity, data infrastructure, workforce training, community engagement, and continuous evaluation. AI integration also requires robust governance frameworks, continuous model evaluation, and alignment with existing crisis management structures. Policy recommendations highlight the importance of ethical AI frameworks, risk assessments, and public engagement to foster trust. Ultimately, AI can strengthen public health decision-making if developed and implemented responsibly within transparent and equitable systems.
2 May 2026
Read appraisal →The Korean journal of gastroenterology = Taehan Sohwagi Hakhoe chi
Toward Precise Risk Stratification after the Functional Cure of Chronic Hepatitis B
Chronic hepatitis B remains a major global health challenge despite the advances in antiviral therapy. Although hepatitis B surface antigen (HBsAg) seroclearance is considered a functional cure, liver-related complications, particularly hepatocellular carcinoma, may still occur after viral clearance. This residual risk reflects the lasting impact of host and liver factors rather than ongoing viral activity. Conventional prediction models have attempted to stratify the residual risk after a functional cure but remain limited in their ability to guide individualized management. Recent advances in machine learning have enabled more precise risk stratification by capturing complex host-driven determinants of the long-term outcomes. These approaches support a shift from uniform surveillance toward risk-adaptive monitoring strategies. Nevertheless, post-cure management is emerging as a new clinical priority as more patients achieve a functional cure. Therefore, a functional cure should be viewed not as the end of the disease, but as the beginning of a phase requiring personalized risk assessment and surveillance.
28 Apr 2026
Read appraisal →BMJ open
Breastfeeding initiation and continuation among women on medicines: a systematic review and meta-analysis
OBJECTIVES: Breastfeeding provides essential health benefits for infants and mothers, yet initiation and continuation can be influenced by maternal medication use. Uncertainty regarding medication safety may lead to early discontinuation or avoidance of necessary treatment. We conducted a systematic review and meta-analysis to estimate the prevalence of breastfeeding initiation and continuation at 6 months post partum among women using medications. DESIGN: Systematic review and meta-analysis using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach. DATA SOURCES: PubMed, Web of Science, Academic Search Premier (EBSCO) and Google Scholar were searched up to 30 November 2024. ELIGIBILITY CRITERIA: For selecting studies: We included cohort, cross-sectional and observational studies reporting breastfeeding initiation at birth and continuation at 6 months post partum among women aged ≥18 years using medications during pregnancy or post partum. Studies reporting medication type and duration of breastfeeding were prioritised. DATA EXTRACTION AND SYNTHESIS: Two independent reviewers screened, extracted and coded data using standardised methods. Risk of bias was assessed using validated tools. Pooled prevalence estimates were calculated using a random effects meta-analysis and meta-regression was performed to explore factors associated with breastfeeding outcomes. Findings were summarised in GRADE evidence profiles and synthesised qualitatively. RESULTS: Of 286 retrieved articles, 29 met the inclusion criteria and 28 were included in the meta-analysis. 14 (48%) were cohort studies reporting breastfeeding prevalence while using medications. The pooled prevalence of breastfeeding initiation among women on medication during pregnancy or post partum was 75.2% (95% CI 69.8% to 80.7%; range 14-98%), with high heterogeneity (I²=99.2%, p<0.001). Overall prevalence of breastfeeding at 6 months post partum was 53.2% (95% CI 43% to 63%). Meta-regression showed that women in high-income countries were less likely to initiate (β=-0.27, 95% CI -0.54 to -0.00, p=0.04) or continue breastfeeding at 6 months (β=-0.27, 95% CI -0.54 to -0.01, p=0.04). Women using antidepressants (β=-0.45, 95% CI -0.87 to -0.02, p=0.04) and opioids (β=-0.50, 95% CI -0.93 to -0.08, p=0.02) were less likely to continue breastfeeding at 6 months. Women living with HIV on ART in low- and middle-income countries had higher continuation rates, likely due to supportive public health programmes. CONCLUSION: Breastfeeding initiation among women using medications is generally high, but continuation declines substantially, particularly among women on psychotropic, opioid or antiepileptic drugs. HIV status, medication type, healthcare support and national guidelines influence breastfeeding outcomes. Targeted interventions, including provider education, medication-specific lactation guidance and supportive workplace policies, are essential to promote sustained breastfeeding among women using medications.
27 Apr 2026
Read appraisal →PloS one
Resilient road safety modeling through spatially disaggregated explainable AI
Understanding spatial disparities in traffic accident severity is essential not only for improving transport safety but also for advancing sustainable and inclusive transportation systems. Road crashes represent a persistent public health and equity challenge, directly linked to the United Nations Sustainable Development Goals (SDG 3: Good Health and Well-Being and SDG 11: Sustainable Cities and Communities). This study proposes an explainable, spatially segmented machine learning framework to examine urban-rural heterogeneity in crash outcomes, using disaggregated accident data from Kent, UK (2022-2024). By treating urban and rural systems as separate analytical units, the study captures risk heterogeneity that conventional pooled approaches often obscure. Among five tested models, Random Forest achieved the best performance and was further interpreted using SHapley Additive exPlanations (SHAP) to uncover how key factors differ in influence across spatial contexts. The results reveal a behavioral risk profile dominating in urban areas and infrastructure-driven risks in rural environments. These findings highlight the need for context-sensitive, evidence-based interventions that ensure transport equity across regions. Additionally, the study contributes to sustainable governance frameworks, enabling spatially adaptive risk mitigation, inclusive policy design and the long-term resilience of transport infrastructures.
27 Apr 2026
Read appraisal →Journal of medical Internet research
Effectiveness of Digital Serious Games on Knowledge and Attitudes in Public Health Education: Systematic Review and Bayesian Network Meta-Analysis of Randomized Controlled Trials
BACKGROUND: Inadequate health literacy and low engagement challenge public health education. Digital serious games show potential to enhance health knowledge and attitudes. However, the comparative effectiveness of different game formats is unclear. OBJECTIVE: This study aimed to evaluate and compare the effectiveness of different digital serious game formats in improving public health knowledge and attitudes. METHODS: This systematic review and Bayesian network meta-analysis followed PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines. Seven databases (PubMed, CINAHL, Embase, PsycINFO, Cochrane Library, Scopus, and Web of Science) were searched from January 2000 to October 2025. An updated search in February 2026 identified no additional studies. Eligible studies were randomized controlled trials (RCTs) involving nonprofessional participants comparing digital serious games with traditional or noninteractive education. Standardized mean differences and 95% credible intervals were pooled using Bayesian network models with random effects. Subgroup analyses examined population characteristics, intervention duration, health topic, and delivery format. Risk of bias was assessed using the Cochrane risk-of-bias tool, and evidence certainty was rated using the Grading of Recommendations Assessment, Development and Evaluation. RESULTS: Forty randomized controlled trials from 19 countries (N=8764 participants) were included. Digital serious games significantly improved knowledge (standardized mean difference 0.66, 95% CI 0.32-0.99; I²=89.1%) and attitudes (standardized mean difference 0.50, 95% CI 0.27-0.76; I²=80.7%) compared with traditional education. Multisession interventions showed larger effects than single-session interventions for knowledge (0.76 vs 0.43) and attitudes (0.53 vs 0.30), with greater improvements among adolescents, nonpatient populations, and Asian studies. Network meta-analysis showed low heterogeneity (I²=8% for knowledge; 3% for attitudes). Mobile app-based, computer-offline, and web-based games ranked highest for knowledge; computer-offline, web-based, and virtual reality games ranked highest for attitudes. Evidence certainty was moderate for knowledge and low-to-moderate for attitudes. CONCLUSIONS: Digital serious games improve public health knowledge and attitudes across diverse contexts. Using a Bayesian network meta-analysis of randomized controlled trials, this review compares the relative effectiveness of different game formats. Mobile app-based, computer-offline, and web-based games most improved knowledge; computer-offline, web-based, and virtual reality formats most improved attitudes. Multisession interventions were more effective than single-session ones, particularly for adolescents and nonpatient populations. These findings guide scalable digital health education strategies. Future research requires adequately powered trials, longer follow-up, and standardized frameworks.
27 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 medical informatics
Modeling Diabetes Risk and Progression With Public Health Data: Ontology-Guided, Simulation-Capable Digital Twin Study
BACKGROUND: Digital twins (DTs) offer a paradigm for health care by enabling data-driven, simulation-capable representations of individual health trajectories. However, DT development remains limited by the scarcity of standardized, temporally structured, and multidomain data suitable for modeling chronic disease progression. Most existing DT studies rely on narrowly scoped or proprietary datasets, restricting generalizability. Public health datasets, such as the Midlife in the United States study, provide rich biopsychosocial information but are underused due to structural complexity and lack of semantic integration frameworks. OBJECTIVE: This study aimed to develop and evaluate an ontology-guided, agent-orchestrated framework for constructing offline, simulation-capable, and progression-aware DTs from public health datasets. Using diabetes as a case study, the framework integrates agent-based orchestration, medical ontologies, and large language model (LLM)-assisted semantic reasoning with machine learning to support explainable feature structuring, risk prediction, and predictive "what-if" progression analysis. METHODS: A 6-stage DT framework was developed and applied to Midlife in the United States wave 2 (baseline) and wave 3 (follow-up) data. Ontology- and LLM-assisted feature selection identified predictors across biological, behavioral, psychosocial, and socioeconomic domains. Cleaned and harmonized data were used to train predictive models (random forest, eXtreme gradient boosting, and logistic regression) to estimate diabetes onset at follow-up. A state-transition simulator was implemented to model between-wave progression dynamics, quantify transitions across low-, medium-, and high-risk states, and evaluate predictive "what-if" scenarios such as weight reduction and lifestyle improvement. Model performance was assessed using accuracy, F1 score, area under the receiver operating characteristic curve (AUC), and calibration metrics. RESULTS: From 9976 candidate variables, ontology- and LLM-guided selection retained the top 200 relevant predictors spanning biological, behavioral, psychosocial, and socioeconomic domains. Predictive modeling achieved strong discrimination, with random forest (AUC=0.82, accuracy=0.76) and eXtreme gradient boosting (AUC=0.81, accuracy=0.75) outperforming logistic regression (AUC=0.78). The state-transition simulator reproduced realistic progression patterns: 33.9% (1414/4174) of participants changed risk states between waves, and the high-risk group increased from 10.8% (451/4174) to 32.2% (1344/4174). Next-state prediction accuracy reached 92.5%. Predictive "what-if" analyses showed that with a simulated 10% weight reduction, model-estimated diabetes cases decreased by 98 (from 576 to 478). A placebo test (0% weight change) produced less than 0.3% difference in risk distribution, confirming model stability. CONCLUSIONS: This study presents a foundational, ontology-guided, and agent-orchestrated framework for constructing offline, simulation-capable, and progression-aware DTs from public datasets. By combining semantic reasoning, multidomain predictors, and predictive "what-if" progression simulation, the framework transforms static population data into longitudinal, interpretable representations of individual health trajectories. The proof-of-concept application to diabetes demonstrates that public health data can support robust and explainable DT models for exploratory risk analysis and hypothesis generation, without implying causal intervention effects or direct clinical decision support.
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 →The Analyst
Third-generation nanopore sequencing: advancing real-time pathogen detection and antimicrobial resistance surveillance in food safety applications
Foodborne diseases impact 600 million people annually, causing 420 000 deaths and over $110 billion in economic losses. Conventional pathogen detection methods take 3-7 days and lack sensitivity for low-abundance pathogens and antimicrobial resistance (AMR) genes. This review evaluates nanopore sequencing's potential in food microbiology, analyzing real-time pathogen detection, AMR surveillance, and performance versus traditional methods. A systematic review of 80 studies (2015-2025) revealed nanopore sequencing reduces detection time to <24 hours with 95-98% species identification accuracy and >90% AMR gene sensitivity, at $50-200 per sample versus $300-800 for traditional whole-genome sequencing. It enables multiplex pathogen detection, viable but non-culturable organism identification, and real-time AMR profiling. However, challenges include error rates of 8-15% in homopolymeric regions and the need for bioinformatics expertise. Addressing challenges, including error rates of 8-15% in homopolymeric regions and the need for bioinformatics expertise, requires strategic mitigation approaches. Despite limitations, advances in base-calling and workflows make nanopore sequencing a transformative tool for next-generation food safety surveillance.
23 Apr 2026
Read appraisal →Infectious diseases of poverty
Progress and challenges in development of minimum essential dataset for disease surveillance through a One Health lens: a scoping review
BACKGROUND: Minimum essential dataset (MED) enables One Health surveillance by facilitating cross-sectoral data sharing. Yet, existing MED research represents insufficient integration of the One Health concept, and its progress in disease surveillance remains unclear. This study aims to evaluate the current progress and gaps in MED research in disease surveillance through a One Health lens. METHODS: This scoping review systematically searched Embase, PubMed, Scopus, and Web of Science from the inception of databases to November 30th, 2024 to identify studies published in English. Studies were independently screened by two reviewers for inclusion based on their relevance to the development of MEDs for disease surveillance. The progress and challenges were synthesized based on data extracted from eligible studies. RESULTS: This review includes 28 eligible studies for analysis, all of which focused on infectious diseases. MED development is predominantly concentrated on the human health interface (89.3%), whereas animal and environmental interfaces are comparatively limited (≤ 10.7%). The One Health concept has been adopted in 16 of the eligible studies; however, there is still insufficient interdisciplinary and cross-sectoral collaboration (57.1%). Meanwhile, numerous methods have been employed in the development of MEDs, with qualitative approaches being the most prevalent (42.9%), while data-driven approaches remain scarce. The absence of a standardized approach is recognized as a primary barrier. Thus, we propose a pathway and operational tool to detail the specific steps, which could facilitate future research on MED. CONCLUSION: This review highlights critical gaps in MED development at the human-animal-environment interface, and proposes a pathway and operational tool to inform future development of MED, including scope identification, establishment, modification and improvement. This study promotes the improvement of disease surveillance system and provides insights to enhance future preparedness for reducing the global public health burden.
23 Apr 2026
Read appraisal →Medicine
Trends and determinants of tuberculosis incidence in Turkey: A secondary data analysis
Tuberculosis remains a major public health concern, with incidence rates influenced by social determinants of health. Although tuberculosis incidence in Turkey has declined markedly in recent decades, the factors associated with this decline have not been comprehensively evaluated at the country-level. This study aimed to examine trends in tuberculosis incidence in Turkey from 1982 to 2021 and to identify determinants of tuberculosis incidence rates between 2000 and 2021, considering variables categorized under composite development, economic indicators, population, and health services. A longitudinal ecological study was conducted using secondary data to examine trends and determinants of tuberculosis incidence in Turkey. Univariate and multivariable linear regression were employed to evaluate the associations between tuberculosis incidence rates and 10 selected variables. Tuberculosis incidence in Turkey declined substantially over the 40-year period analyzed, with an overall decrease of 86.6% and sharper reductions observed in certain intervals. In multivariable linear regression, only the Human Development Index remained independently associated with tuberculosis incidence (β = -1.041, P < .001), indicating that higher Human Development Index values were associated with lower tuberculosis incidence rates in Turkey. These findings indicate that tuberculosis incidence in Turkey has declined alongside changes in human development, as reflected by the composite Human Development Index.
20 Apr 2026
Read appraisal →Global health action
Lifestyle interventions to prevent gestational and type 2 diabetes among migrant women from low- and middle-income countries: a systematic review.
Migrant women from low- and middle-income countries (LMICs) living in high-income settings experience disproportionately high risk of gestational diabetes mellitus (GDM) and type 2 diabetes mellitus (T2DM). This review aimed to identify and synthesise culturally adapted lifestyle interventions for preventing or managing GDM and T2DM among migrant women from LMICs, focusing on intervention components, cultural adaptation strategies, and behavioural and metabolic outcomes. Five databases (PubMed, Embase, Scopus, CINAHL, Cochrane Central) were searched using Preferred Reporting Items for Systematic reviews and Meta-Analysis 2020 guidelines. Eligible studies included experimental designs involving lifestyle interventions delivered to migrant women from LMICs in high-income countries, reporting outcomes related to GDM or T2DM targeting behaviour change. Data were synthesised narratively; study quality was appraised using RoB2 for RCTs and a structured narrative approach for non-randomised designs. Certainty of evidence was evaluated using GRADE. Eight studies met the inclusion criteria. Sample sizes ranged from 28 to 641 participants. Intervention duration varied from 6 weeks to 12 months. Most interventions incorporated atleast one culturally tailored component, such as bilingual delivery, culturally adapted dietary education, or community-based engagement. Improvements were reported across dietary behaviours, physical activity, glycaemic measures, or diabetes-related knowledge; however, effect sizes were modest and inconsistent. Interventions combining dietary modification, physical activity, and culturally adapted delivery demonstrated greater improvements than exercise-only or digital-only programmes. Overall certainty of evidence ranged from low to moderate. Culturally adapted, multi-component lifestyle interventions show promise for improving behavioural and metabolic outcomes among migrant women from LMICs; however, the evidence base remains limited. Main findings: Culturally adapted, multi-component lifestyle interventions show modest but inconsistent improvements in behavioural and metabolic outcomes among migrant women from low- and middle-income countries with overall low-to-moderate certainty of evidence.Added knowledge: This review highlights cultural adaptation as a key feature of intervention effectiveness and identifies important evidence gaps, including limited high-quality studies and challenges in comparing heterogeneous interventions.Global health impact for policy and action: Policies should prioritise scalable, culturally responsive interventions – such as bilingual and community-based approaches – to reduce diabetes disparities and improve maternal health outcomes in migrant populations.
19 Apr 2026
Read appraisal →PloS one
Operationalization of Severe Maternal Morbidity surveillance in administrative databases of the Brazilian public and private health systems: Brazil 2015-2022
The study of severe maternal morbidity (SMM) is an important strategy for improving the quality of obstetric care. The objective of this study is to assess SMM cases recorded in the Hospital Information System of the Unified Health System (SIH/SUS), which contains public funded hospitalizations, and in the database of the National Supplementary Health Agency (ANS), which contains hospitalizations paid for by health plans. This is a cross-sectional study using obstetric hospitalizations of women aged 10-49 years from both databases in the period 2015-2022. We assessed SMM cases using the World Health Organization's criteria for potentially life-threatening conditions (PLTC). Of the 26 PLTC criteria, 22 were operationalized through diagnoses during hospitalization, using International Classification of Diseases-10 codes, or medical procedures, using specific codes of each database. We estimated the frequency and odds ratio of death for each isolated criterion, for grouped criteria and for the total number of SMM cases, as well as the frequency of deaths according to the number of SMM criteria. We identified 18,807,757 obstetric hospitalizations in the SIH/SUS and 3,776,986 in the ANS database. The estimated proportion of SMM was 8.51% and 7.30% in SIH/SUS and ANS, respectively. Most cases presented only one criterion. Differences were observed among sectors, with a higher frequency of procedure-based criteria in the ANS database, compatible with the greater availability of resources in private services. The proportion of deaths increased with the increase in the number of criteria, and more severe criteria presented a higher odds ratio of death. The results indicate that it is possible to estimate the number of SMM cases in the country, both in public and private hospitalizations. Continued investment in the quality of recording in both databases are necessary so that the estimates can truly reflect the maternal morbidity of Brazilian women.
18 Apr 2026
Read appraisal →JMIR human factors
Interactive, Personalized Patient Decision Aid for COVID-19 Vaccination in Canada: User-Centered Design Approach
BACKGROUND: The COVID-19 pandemic highlighted the need for practical digital health tools to support informed decision-making amid rapidly evolving evidence and widespread misinformation. OBJECTIVE: We iteratively developed and refined VaxDA-C19, a bilingual (English and French) web-based patient decision aid designed to support informed decision-making in Canada about COVID-19 vaccination. VaxDA-C19 integrates interactive and personalized features aimed to enhance vaccine confidence, reduce cognitive overload, and respond to diverse informational needs. METHODS: VaxDA-C19 was developed using an iterative, user-centered design approach. Throughout the development process, we involved a citizen panel, health care professionals, user experience designers, and scientific experts to guide refinements. We also conducted usability testing sessions with adults in Canada, using semistructured interviews, comparative testing, and think-aloud protocols with thematic analysis. We ultimately conducted 4 design cycles in total with adults in Canada (users) and expert reviewers (experts). Cycle 1 involved 9 people (9 users), cycle 2 involved 22 people (22 users), cycle 3 involved 9 people (3 users and 6 experts), and cycle 4 involved 9 people (9 experts). RESULTS: In cycle 1, user feedback guided design decisions about how to present quantitative information and technical vaccine descriptions more simply. In cycle 2, while most users (9/11, 82%) favored in-depth explanations of vaccine development, a few raised concerns about content that could be perceived as politically charged. Cycle 3 identified usability improvements, including more explicit navigation controls, simplified medical terminology, and optimized interactive components (avatars and sliders). Expert reviews in cycle 4 refined linguistic consistency, mobile responsiveness, content transparency, and scientific accuracy, emphasizing explicit instructional guidance and bilingual accessibility. CONCLUSIONS: Our iterative process produced a personalized, bilingual digital decision aid to support evidence-informed, values-congruent decisions about COVID-19 vaccination. A randomized controlled trial will further evaluate VaxDA-C19's impact on vaccination intentions, knowledge retention, emotional responses, decisional conflict, and decisional regret. If it proves effective, the patient decision aid may also be used as a platform to support other vaccine decisions, namely, influenza, measles, shingles, pertussis, and potentially other emerging infectious diseases.
18 Apr 2026
Read appraisal →BMJ open
Comparison of the effects of eHealth-delivered sedentary breaks versus physical activity promotion interventions on sedentary time: protocol for a systematic review and meta-analysis
INTRODUCTION: Prolonged sedentary behaviour (SB) is an independent risk factor for adverse health outcomes, with current WHO guidelines emphasising both increased physical activity (PA) and reduced sitting time. While electronic health (eHealth) interventions offer scalable solutions, the comparative effectiveness of two dominant strategies: sedentary break interventions (frequent interruptions of sitting) versus PA promotion (structured activity sessions) remains unclear. This systematic review and meta-analysis protocol aims to compare the effectiveness of interventions targeting breaks in SB versus increased PA in reducing sedentary time through meta-analysis of randomised controlled trials (RCTs) comparing either intervention to a control condition, while exploring key moderating factors including participant characteristics, intervention type, duration, eHealth delivery mode, theoretical basis, use of behaviour change techniques (BCTs), PA intensity and SB frequency. METHODS AND ANALYSIS: This protocol follows the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) guidelines. A comprehensive search will be conducted in PubMed, Embase, Web of Science and the Cochrane Library from inception to 31 July 2025, with language restrictions limited to English and Chinese publications. RCTs comparing eHealth-delivered interventions promoting sedentary breaks with those increasing PA in adults will be included. The primary outcome is sedentary time (objectively measured or self-reported), and secondary outcomes include health outcomes such as cardiometabolic markers, fatigue and well-being. Two reviewers (SC and XN) will independently screen studies, extract data and assess risk of bias using validated tools. Meta-analyses will be performed if sufficient homogeneous data are available, comparing changes in sedentary time. Subgroup analyses will explore effects by participant characteristics including gender (male vs female), age groups (<60 vs ≥60 years), intervention type (sedentary breaks vs PA), duration (short-term ≤3 months vs medium-term >3 to <6 months vs long-term ≥6 months), eHealth platform/delivery mode (eg, smartphone apps vs websites vs wearable device prompts vs text messages), theoretical basis (eg, theory-driven interventions vs non-theoretical interventions), use of BCTs (eg, interventions incorporating BCTs vs interventions without BCTs), SB break frequency (eg, every 30 min vs every 60 min) and PA promotion intensity (eg, light vs moderate vs vigorous). A narrative synthesis will be conducted for studies unsuitable for quantitative analysis. ETHICS AND DISSEMINATION: Ethical approval is not required as this study involves secondary analysis of published data. Findings will be disseminated through peer-reviewed publication and conference presentations. PROSPERO REGISTRATION NUMBER: CRD420251042994.
18 Apr 2026
Read appraisal →Water research
Representation of urban and rural contexts in the application of wastewater surveillance for antimicrobial resistance: A systematic review.
Wastewater surveillance (WWS) can reveal community health trends through targeted monitoring of sewage. Given concerns regarding the global dissemination of drug-resistant infections, there is growing integration of antimicrobial resistance (AMR) in WWS infrastructure. However, most WWS has focused on highly urbanized sewersheds in resource-rich areas, which may exacerbate disparities in disease burdens and clinical datasets. This work presents both a systematic and scoping review of current published WWS efforts targeting antimicrobial resistance (AMR), with the aim to quantify and compare applied monitoring efforts capturing rural vs. urban areas and lower-income vs. higher-income countries. Of the 2,873 deduplicated manuscripts identified through a systematic search of four databases, 454 examined untreated domestic sewage and were characterized via a brief scoping review. Of these, 48 articles included an explicit focus on monitoring for population health surveillance, and were subject to methodological data extraction and risk of bias assessment. Sampling trends observed in the scoping and systematic review were similar. Only 13-19 % of scoping review sampling sites were classified as rural, and 44 % were located within lower- or middle-income countries (LMICs). Few articles examined AMR within unsewered communities. While analytical methods were similar across income brackets, rural monitoring efforts were more reliant on culture-based techniques than urban efforts. Monitoring in rural sites and LMICs were typically part of multi-site campaigns and featured less longitudinal sampling. Overall, methodological inconsistencies rendered a meta-analysis infeasible. The combined lack of research in rural and low-income areas indicates that key at-risk communities for circulation of AMR are an oversight.
17 Apr 2026
Read appraisal →Emerging microbes & infections
Cross-protection against highly pathogenic avian influenza H5N1 virus from seasonal influenza vaccines: a systematic review and meta-analysis of ferret studies
The recent surge in spillover events of highly pathogenic avian influenza A(H5N1) clade 2.3.4.4b to humans and mammals in North America has raised urgent pandemic concerns. Human H5N1 vaccines are unavailable in most countries. We synthesized data from ferret challenge trials to evaluate whether widely available seasonal influenza vaccines confer cross-protection against lethal H5N1 infection. We systematically searched PubMed, Embase, and Web of Science for ferret studies of lethal H5N1 challenge published up to 5 July 2025 (PROSPERO #CRD42024520346). Random-effects meta-analyses were conducted to compare vaccine efficacy (VE) of seasonal influenza vaccines and H5N1 vaccines against H5N1-related mortality. Seroprotection was defined as a neutralizing antibody titre of ≥1:40. We identified 35 studies (157 trials). Seasonal influenza vaccines without N1 did not confer significant cross-protection (five trials; VE 14.8%, 95% CI -3.6 to 30.0). In contrast, VE was 73% for N1-containing seasonal influenza vaccines (19 trials; 95% CI 54-84) and 77% for H5N1 vaccines overall (133 trials; 95% CI 72-82) (p = 0.52). The VE of N1-containing seasonal influenza vaccines was modestly lower than that of H5N1 vaccines with seroprotection (88%; 66 trials; 95% CI 84-91; p = 0.009), but comparable to H5N1 vaccines that did not achieve seroprotection (63%; 67 trials; 95% CI 52-71; p = 0.29). The VE of seasonal influenza vaccines against H5N1 was robust across sensitivity analyses, with no evidence of publication bias (p = 0.99). Seasonal influenza vaccines significantly reduce H5N1-associated mortality in ferret trials, suggesting the cross-protection potential of currently available vaccines. Human studies are warranted.
16 Apr 2026
Read appraisal →PloS one
Ultra-processed food consumption and the risk of overweight and obesity in adolescents: A systematic review and meta-analysis
INTRODUCTION: Overweight and obesity during early life increase the risk of premature morbidity and mortality. Adolescent obesity raises the likelihood of developing cardiovascular risk factors, including prediabetes, type 2 diabetes, dyslipidemia, hypertension, liver disease, and metabolic syndrome. Sedentary lifestyles and unhealthy diets are major contributors, with one of the fastest-growing unhealthy eating patterns being the consumption of ultra-processed foods (UPFs). No systematic review and meta-analysis has specifically examined the association between UPF consumption and overweight/obesity in adolescents. OBJECTIVE: To systematically review and conduct a meta-analysis of available evidence on the association between UPF consumption and overweight or obesity among adolescents. METHODS: We searched PubMed, ScienceDirect, HINARI, Google, and Google Scholar for primary studies reporting UPF consumption and overweight/obesity outcomes in adolescents, without restrictions on language or study period. Study quality was assessed using the Newcastle-Ottawa Scale. Heterogeneity was evaluated using Cochrane's Q test and the I² statistic. Publication bias and small-study effects were assessed using Egger's regression test (p < 0.05). A random-effects model estimated pooled associations. RESULTS: Twenty-three studies involving 155,000 adolescents were included. Adolescents with higher UPF consumption had 63% greater odds of overweight or obesity compared with those with lower intake (OR = 1.63; 95% CI: 1.36-1.95). CONCLUSION: High UPF consumption is associated with an increased risk of overweight and obesity among adolescents. Public health strategies targeting reduced UPF intake and promotion of healthier diets should be prioritized to prevent adolescent overweight/obesity and associated health risks.
16 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 →Nature communications
A group 1 hemagglutinin stem vaccine elicits broad humoral responses against influenza in phase 1/2a study
Vaccines targeting the conserved stem region of influenza hemagglutinin (HA) may induce broad immunity and reduce reliance on strain-matched seasonal formulations. This Phase 1/2a study evaluates safety and immunogenicity of a universal influenza vaccine component comprising a soluble trimeric stabilized group 1 HA-stem protein (INFLUENZA G1 mHA). Healthy adults aged 18-to-45 received one or two doses at 45 µg or 135 µg, with or without Al(OH)₃. Primary endpoints were safety and reactogenicity. All regimens were well-tolerated with no vaccine-related serious adverse events. Secondary and exploratory endpoints included binding, neutralizing, and ADCC responses compared to a matched quadrivalent seasonal influenza vaccine cohort. A single dose induced robust binding antibody responses to H5 HA and homologous stem HA, with 6.5-16.4-fold increases at Day 29 versus baseline, exceeding responses elicited by the seasonal influenza vaccine. Additionally, we demonstrate broader binding to a panel of group 1 HAs, with responses maintained for at least one year. Neutralizing antibody and ADCC responses at Day 29 showed 7.9-15-fold and 4.9-8.6-fold increases, respectively. Importantly, serum from vaccinated participants protect mice against lethal heterologous H5N1 challenge. This study provides proof of concept that the HA stem vaccine elicits broad and durable influenza A group 1-directed immunity. This trial is registered with ClinicalTrials.gov (NCT05901636).
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 →PloS one
Use of administrative data for evaluating trends in medically-attended Lyme disease, Manitoba, Canada, 2010-2021
While Lyme disease (LD) is the most common tick-borne disease reported to public health surveillance in North America and is increasingly recognized as a public health threat in Canada, it's incidence may be underreported. Our study aims to estimate medically-attended LD incidence in Manitoba, Canada, using administrative health data. We identified medically-attended LD cases in Manitoba from 2010 - 2021 in a claims database (Manitoba Population Research Data Repository), which contains the health records of >95% of the residents of Manitoba, using diagnostic codes, antibiotic dispensations, and laboratory results. The incidence of claims-based LD cases ranged from 8.4 to 28.5 per 100,000 population per year, 5.1 to 11.0 times higher than the incidence of surveillance-reported LD cases. The incidence of claims-based LD cases was particularly higher than the incidence of surveillance-reported LD cases in females and health regions with a low surveillance-reported incidence. Our study suggests that medically attended LD is more common than reported in surveillance. Further study is required to identify barriers to reporting. Interventions are needed to reduce the substantial burden of LD in Manitoba.
15 Apr 2026
Read appraisal →PloS one
Virologic suppression among HIV-positive pregnant and lactating women receiving antiretroviral therapy in Africa: A systematic review and meta-analysis
BACKGROUND: The elimination of mother-to-child transmission of human immunodeficiency virus (HIV) is a key global public health priority. In Africa, virologic failure among people living with HIV continues to pose a significant public health challenge, affecting both individual well-being and community health. Maintaining viral load suppression is crucial to prevent vertical transmission of HIV and to minimize maternal morbidity and mortality. To stop the vertical transmission of HIV and lower the risk of maternal morbidity and mortality, it is important to achieve viral load suppression. Although many African countries have adopted the global 95-95-95 targets, comprehensive data on virologic suppression among pregnant and lactating mothers across the continent remains limited. The objective of this systematic review and meta-analysis was to determine the pooled estimate of virologic suppression and to examine the factors associated with it among HIV-positive pregnant and lactating women on antiretroviral therapy in Africa. METHODS: This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The study protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO; CRD420251186121). We carried out a thorough systematic review by examining PubMed, ScienceDirect, Hinari, and Google Scholar for relevant studies. Data from the studies were retrieved using an Excel sheet and analyzed with STATA version 17. The Joanna Briggs Institute appraisal tool was used to evaluate the methodological quality of studies. A random-effects model with restricted maximum likelihood (REML) was applied to determine the pooled prevalence of virologic suppression (viral load threshold ≤1000 copies/ml) among pregnant and lactating mothers in Africa. A funnel plot and the Egger's test were used to investigate publication bias. Statistical heterogeneity was assessed using the I2 statistic and Cochrane's Q test. RESULTS: A total of 55 eligible studies, comprising 304,883 participants, were included in the quantitative meta-analysis. Accordingly, the overall prevalence of virologic suppression among HIV-positive pregnant and breastfeeding women in Africa was 80.86% (95% CI: 77.63%, 84.09%, I2 = 99.84%). In contrast, the pooled estimate for achieving an undetectable viral load was substantially lower, at 60.92% (95% CI: 52.46%, 69.39%; I2 = 99.91%). Virologic suppression was significantly associated with women's age (15-24 years) (AOR = 0.49; 95% CI: 0.32-0.77), disclosure of HIV status to a partner (AOR = 1.66; 95% CI: 1.31-2.11), first-line antiretroviral therapy regimen (AOR = 6.53; 95% CI: 1.93-22.06), and good antiretroviral drug adherence (AOR = 3.61; 95% CI: 1.18-11.02). In addition, other socio-demographic variables, higher educational level, being married/cohabitant, urban residency, healthcare utilization (time of ANC booking, time of ART initiation, duration of ART), fear of stigma, distance to health facility, shortage of health professionals, ART drug stock-out, and lack of HIV care commodities were significantly associated with virologic suppression among HIV-positive pregnant and lactating women in Africa. CONCLUSION: The pooled estimate of virologic suppression among HIV-positive pregnant and breastfeeding women in Africa was approximately 81%, below the global target of 95% virological suppression. This emphasizes the necessity of targeted strategies for younger HIV-positive women, disclosing HIV status, initiating first-line antiretroviral regimens, and promoting antiretroviral treatment adherence. Upgrading health care systems to enable regular viral load monitoring, as well as addressing socio-demographic and antiretroviral therapy-related variables, are vital steps towards attaining and sustaining VS in these groups of population, ultimately assisting in achieving elimination of MTCT of HIV.
14 Apr 2026
Read appraisal →Global public health
Seroprevalence of hepatitis C virus among refugees, asylum seekers, and internally displaced populations within Africa: A systematic review and meta-analysis
Hepatitis C virus (HCV), an often overlooked public health concern, is highly prevalent among marginalized groups. Refugees, asylum seekers, and internally displaced people (RASIDP) constitute an underserved population in healthcare. Given that displacement rates are increasing and that HCV is endemic to many African countries, we aimed to determine the prevalence of HCV among RASIDP communities in Africa. Studies investigating HCV prevalence within RASIDP communities across Africa were identified via the following database searches: Ovid MEDLINE, EMBASE, Web of Science, APA PsycINFO, and the WHO Africa Index Medicus. Seroprevalence estimates were meta-analysed using a random-effects model, with data stratified by participant region, age, and gender. Across 9 studies, we estimated a pooled HCV seroprevalence of 3.63% (95% CI: 0.54, 9.16) among RASIDP in Africa. Seroprevalence varied by region of origin and age, with those from Northern Africa and those aged > 40 years having the highest seroprevalence, at 10.03% (95% CI:9.03, 11.13) and 5.70% (95% CI: 0.81, 14.21), respectively. RASIDP communities represent a marginalised and vulnerable population that often faces significant barriers to accessing healthcare. Our findings show that HCV seroprevalence within these communities varies by region and age, thus suggesting a need for targeted screening approaches.
12 Apr 2026
Read appraisal →Vaccine
Impact of pharmacy-based interventions on vaccination coverage among vulnerable and underserved populations: a systematic review and meta-analysis
BACKGROUND: Vaccination coverage remains suboptimal among vulnerable and underserved adult populations. We investigated the effectiveness of pharmacy-based interventions in improving vaccine uptake in high-risk groups and the most effective strategies. METHODS: A systematic search (PubMed/MEDLINE, Embase, Scopus; 26 July 2025) identified experimental and observational studies evaluating pharmacy-led vaccination interventions targeting adults ≥65 years or individuals aged 18-64 years with chronic conditions or limited healthcare access. The primary outcome was vaccination coverage. Odds ratios (ORs) were pooled using fixed- and random-effects models. Sensitivity analyses were conducted by intervention type and setting. Risk of bias was assessed using ROBINS-I, RoB 2, and NOS tools. RESULTS: A total of 35 studies were included, encompassing over 1.3 million participants. In pre-post comparisons, pharmacy-based interventions nearly doubled vaccination uptake (random-effects OR = 1.88; 95% CI: 1.68-2.12). In case-control analyses, individuals exposed to pharmacist interventions were almost five times more likely to be vaccinated (random-effects OR = 4.87; 95% CI: 2.23-10.64). Multicomponent strategies and direct vaccine administration by pharmacists produced the most consistent improvements. CONCLUSIONS: Pharmacist-led vaccination interventions significantly increase vaccine uptake among vulnerable adults. The most effective approaches involved pharmacists included eligibility assessment, counselling, administration, and documentation, integrated within routine care workflows.
11 Apr 2026
Read appraisal →PloS one
Association between hypertension and impaired lung function among adults: A systematic review and meta-analysis
BACKGROUND: Impaired lung function and hypertension are both significant global public health concerns, and their potential association has recently drawn considerable interest. This systematic review and meta-analysis aims to investigate the association between impaired lung function and hypertension, and vice versa. METHODS: We searched CINAHL (EBSCOhost), MEDLINE (PubMed), Scopus and Web of Science up to 22nd July 2025 for observational studies involving adults (≥ 18 years) reporting hypertension and impaired lung function. Grey literature was also searched, and data extraction was verified independently. The review was registered with PROSPERO (CRD42023427631). Random effects models estimated pooled ORs with 95% CIs. Subgroup analysis and meta-regression were performed to identify potential sources of heterogeneity. Quality assessment was conducted using Newcastle-Ottawa Scale and JBI checklist and publication bias were appraised. RESULTS: This systematic review included 28 articles, of which 26 articles were selected for the meta-analysis. Of these, 17 studies (n = 134823) examined impaired lung function as the exposure, while 9 studies (n = 12522) investigated hypertension as the exposure. Our findings revealed that the pooled unadjusted effect of lung function impairment on hypertension was 1.70 (95% CI: [1.53-1.88]), while the pooled adjusted effect was lower at 1.40 (95% CI: [1.31-1.49]). In contrast, the pooled unadjusted effect of hypertension on lung impairment was 3.00 (95% CI: [1.86-4.82]), but the pooled adjusted effect decreased to 1.94 (95% CI: [1.51-2.50]). The findings indicate that obstructive, restrictive and mixed lung function impairments are significantly associated with hypertension. Restrictive lung impairment consistently shows a stronger association with hypertension compared to obstructive impairment when impaired lung function is the exposure. CONCLUSION: This study concludes that there is a significant positive association between impaired lung function and hypertension in both directions, with stronger temporal evidence suggesting that impaired lung function may precede hypertension, while the reverse causal direction lacks such evidence.
11 Apr 2026
Read appraisal →PloS one
Risk factors for spontaneous abortion following hepatitis E vaccination during and shortly before pregnancy: Further analysis from a cluster-randomized trial
BACKGROUND: A recent randomized trial of Hepatitis E Vaccine (HEV239) found an elevated risk of spontaneous abortion (SAB) in women given HEV239 during or within ninety days before pregnancy. Here we present additional analyses to better understand this risk. METHODS: We investigated whether maternal risk profiles of SAB or gestational age at SAB differed between women receiving HEV239 versus control Hepatitis B vaccine (HBV). We also assessed whether HEV239-vaccinated women who experienced SABs had distinct short-term adverse reactions compared to HEV239-vaccinated women who had live births, exploring potential inflammatory mechanisms. Finally, we assessed maternal exposure to HEV239 in narrowly defined pre-last menstrual period (LMP) windows to more precisely demarcate pre-LMP at which HEV-239 vaccination was associated with an elevated risk of SAB. Chi-square tests and Mann-Whitney U tests were performed for bivariate comparisons. Poisson models were used for multivariable analyses. FINDINGS: Baseline maternal risk factors for SAB (age, body mass index, parity, and histories of SAB, hypertension, or diabetes) were similar between the SABs in HEV239 and HBV groups. Median gestational age at SAB was comparable (10.5 weeks [IQR 10-13] for HEV239 vs. 11 weeks [IQR 9-12.2] for HBV, p = 0.783). No increased short-term adverse events (pain: 9% vs. 9%; fever: 2% vs. 1%) were observed among HEV239 recipients who experienced SABs compared to those who did not. An elevated risk of SAB was observed in HEV239 recipients vaccinated 31-60 days pre-LMP (Relative Risk 4.3 [95% CI 1.3-19.3], p = 0.026). INTERPRETATION: Our analyses did not uncover associations pointing to a biological mechanism underlying the original observation of an increased SAB rate connected to HEV239 vaccination shortly before or during pregnancy. Targeted studies such as placental examinations and genetic testing are needed to investigate potential mechanisms.
11 Apr 2026
Read appraisal →JMIR mHealth and uHealth
Effectiveness of mHealth-Based Nutritional Interventions on Iron Status of Pregnant Women: Systematic Review of Randomized Controlled Trials
BACKGROUND: Anemia is a global health concern. It is disproportionately prevalent among pregnant women in low-resource regions, where iron deficiency is the leading cause. Given the multifactorial nature of anemia, a range of nutritional interventions is recommended. However, effective implementation is often hindered by limited health care access, poor adherence to supplementation, and gaps in nutrition knowledge and counseling. To address these challenges and optimize hemoglobin (Hb) levels among pregnant women, mobile health (mHealth)-based nutritional interventions offer a promising alternative. OBJECTIVE: The aim of the study is to review available evidence on the effectiveness of mHealth-based nutritional interventions on iron status (Hb and/or serum ferritin concentration) among pregnant women. METHODS: Searches were conducted in Embase, CINAHL, Cochrane Library, PubMed, Web of Science, and Scopus, and supplemented by snowballing to identify additional relevant studies from citation lists. The key search strings comprised 4 concepts: "mobile health," "nutritional intervention," "Hb, anemia or iron deficiency anemia," and "pregnant women." Predefined inclusion and exclusion criteria were applied during screening. The methodological quality of included studies was assessed using the Risk of Bias 2 tool. The primary end point was the change in mean Hb concentration or serum ferritin level. Effect sizes (ESs) were calculated as standardized mean differences, including Cohen d and Hedges g. RESULTS: Of the 14,284 studies identified, only 11 randomized controlled trials were included. These studies used various modes of delivery, including mobile phone calls (n=1), SMS text messaging (n=3), and mobile apps (n=4), with some using more than 2 modes (n=3). The effect of mHealth-based nutritional interventions on iron status varied significantly. In total, 4 studies demonstrated a large ES (>0.8), with 3 relying on WhatsApp Messenger as an mHealth delivery mode. Approximately 82% (9/11) of the included studies reported a positive effect (P values ranging from <.001 to .047) of the intervention on Hb level, whereas 2 studies reported no statistically significant association (P=.33 and P=.35, respectively). Notably, interventions with the largest ES achieved clinically significant improvements in Hb concentration, with within- and between-group differences exceeding 1 g/dL. However, including behavioral change theories and nutrition-sensitive components was not consistently associated with larger ESs. Due to high heterogeneity (I2>95%), attributed to variations in mHealth delivery modes, functions, and interactive features across the included studies, meta-analysis could not be performed. CONCLUSIONS: This review demonstrates that mHealth-supported nutritional interventions effectively optimize Hb concentration in pregnant women. While SMS text messaging was less effective in improving Hb concentration, combining it with another mHealth delivery mode, such as phone calls, improved intervention effectiveness. However, the variability in mHealth delivery modes, functions, and interactive features underscores the need for tailored strategies that account for context-specific challenges, digital literacy, and access to technology to enhance effectiveness.
10 Apr 2026
Read appraisal →Microbiology spectrum
Evaluation of contezolid's cerebrospinal fluid concentration and safety in tuberculous meningitis patients
Tuberculous meningitis (TBM) is the most severe form of tuberculosis (TB) with high mortality. This study evaluated the cerebrospinal fluid (CSF) concentration and safety of the novel oxazolidinone contezolid compared to linezolid in TBM patients. In this randomized prospective study, 10 TBM patients received either a linezolid-containing (n = 5) or contezolid-containing (n = 5) anti-TB regimen. CSF and blood concentrations were measured at 2 and 6 h post-dose. Peak (2 h) and trough (6 h) concentrations, area under the concentration-time curve (AUC), and safety were assessed. Contezolid CSF concentrations exceeded the Mycobacterium tuberculosis (Mtb) MIC (0.5 μg/mL) at 2 h (median: 1.0806 μg/mL, range: 0.9295-1.3165 μg/mL) but declined by 6 h (median: 0.7920 μg/mL, range: 0.1867-1.0194 μg/mL). Linezolid CSF concentrations were significantly higher than contezolid at both 2 h (median: 3.251 μg/mL, range: 1.9545-4.9636 μg/mL; P = 0.008) and 6 h (median: 1.623 μg/mL, range: 0.941-1.765 μg/mL; P = 0.016), remaining above MIC in all samples at 6 h. The mean CSF AUC for contezolid (4.637 μg·h/mL, 95% CI: 3.599-5.675) was significantly lower than that for linezolid (12.537 μg·h/mL, 95% CI: 7.8797-17.277; P = 0.008). Blood concentrations were higher than CSF for both drugs at all time points. No serious drug-related adverse events occurred. Contezolid effectively penetrates the blood-CSF barrier in TBM patients, achieving CSF concentrations above the MIC for Mtb. Although its CSF exposure was significantly lower than linezolid, its demonstrated penetration and safety profile suggest contezolid warrants further investigation as a potential treatment option for drug-resistant TBM.IMPORTANCETuberculous meningitis (TBM) is the deadliest form of tuberculosis, especially difficult-to-treat drug-resistant TBM. Finding new, effective, and safe medicines is critical. This study provides evidence in TBM patients that a newer antibiotic, contezolid, successfully reaches the infection site in cerebrospinal fluid (CSF) at levels expected to kill Mycobacterium tuberculosis. While linezolid achieved higher levels in CSF, contezolid still reached concentrations predicted to be effective and caused no serious side effects in our study. This is important because contezolid might offer a safer alternative to linezolid, which can have significant long-term toxicity. These promising results suggest contezolid could become a valuable new weapon against refractory drug-resistant TBM, potentially saving lives where current options are limited or too toxic.
9 Apr 2026
Read appraisal →Global public health
Link between housing and community factors and mental health and psychological well-being of refugee parents and children in high-income countries: A systematic review
Whilst forced migration is known to significantly increase the risk of mental health problems, the influence of post-migration factors for refugee children and parents in high-income countries remains understudied. However, systemic post-migration factors have the potential to be modified by policy and practice to improve outcomes. This systematic review identifies the housing and community factors examined in research and their link to the mental health and psychological well-being of refugee parents and children in high-income countries. Adhering to the PRISMA guidelines, we searched the databases of PubMed, PsycINFO and Embase for studies published in peer-reviewed journals until the 17th of October 2025. Of the 11,588 studies identified, 30 were eligible for inclusion in this review. Our findings particularly suggest favourable mental health outcomes among those living with their families/relatives or foster care as opposed to reception centres, as well as those with social support. Perceived discrimination consistently showed an association with negative mental health outcomes. The findings suggest a gap in the evidence base focusing on parents, education and school-related factors. We recommend that policy makers provide family-based living arrangements and improve access to spaces for social support. Future research in this field will benefit from further sub-group analyses.
8 Apr 2026
Read appraisal →Journal of the American Heart Association
Beyond Composite Indices: Comprehensive Social Determinants Improve Heart Failure Readmission Prediction
BACKGROUND: Heart failure (HF) hospitalization readmissions are associated with a high mortality rate and strain the health care system. Both clinical factors and social determinants of health (SDOH) predict HF readmissions, but the optimal approach to incorporating area-level SDOH data remains unclear. METHODS: We merged census tract- and county-level SDOH measures with electronic health record data in a retrospective cohort of 33 579 Black and White patients with HF (Emory Healthcare, 2010-2018). Six combinations of electronic health record data with 752 area-level SDOH were evaluated using multiple machine learning models (logistic regression, random forest, XGBoost) to predict 30-day HF readmission. Models were assessed for predictive performance using area under the receiver operating characteristic curve and algorithmic fairness across race using the equalized odds ratio. RESULTS: Expanded SDOH predictor sets improved predictive performance and algorithmic fairness compared with traditional SDOH indices. The XGBoost model using expanded SDOH alongside clinical predictors provided better predictive performance (area under the receiver operating characteristic curve, 0.671) and improved algorithmic fairness across patient race (equalized odds ratio, 0.437) than models with traditional indices (area under the receiver operating characteristic curve, 0.632; equalized odds ratio, 0.329). Feature-importance analysis revealed that specific environmental predictors (housing cost burden, air quality) ranked among top predictors alongside clinical biomarkers. County-level SDOH outperformed census tract-level SDOH and matched prediction performance of clinical predictors alone. CONCLUSIONS: Including hundreds of individual SDOH indicators rather than traditional composite indices improves machine learning models' ability to predict 30-day HF readmissions. While performance gains are modest, inclusion of specific environmental factors may provide greater clinical utility and improved equity across racial groups than composite SDOH measures for guiding further research and preventive interventions.
8 Apr 2026
Read appraisal →PloS one
Perception and acceptance of micronutrient-Fortified Bouillon among Non-Index Household Members: A longitudinal sub-study nested within a randomized trial in Northern Ghana
BACKGROUND: Fortified bouillon cubes offer a scalable strategy to address micronutrient deficiencies in West Africa. However, success depends on household members' perceptions and acceptance. This study assessed changes in perception and acceptance of fortified bouillon cubes over time and explored factors influencing these outcomes among non-index household members (NIHMs) from trial households in Northern Ghana. METHODS: This longitudinal mixed-methods study was nested within a double-masked randomised controlled trial. Households received micronutrient-fortified bouillon cubes (vitamin A, vitamin B12, folic acid, iron, zinc, iodine) or control cubes (iodine only) for nine months. One NIHM (≥15 years) per household (n = 1,047) was enrolled. Structured interviews were conducted during early (months 1-2; n = 731) and late (months 7-9; n = 796) phases. Composite perception (8 items) and acceptance (10 items) scores (range: 1-5; higher scores = more positive perceptions/greater acceptance) were derived from an 18-item validated instrument. Bayesian linear mixed-effects models assessed temporal changes and associated individual and household factors. Twenty-four focus group discussions (months 4-5) explored drivers and barriers. RESULTS: Mean age of NIHMs was 40 ± 14.7 years; 59% were female. Perception scores increased over seven months, from 3.4 to 4.1 (adjusted posterior mean difference [aPMD] = 0.69; 95% credible interval [CrI]: 0.57, 0.81). Acceptance remained high (4.59 to 4.58; aPMD = -0.02; 95% CrI: -0.07, 0.03). No differences were observed between trial arms. At early timepoint, perception scores were lower among household heads compared with other household members, and lower among formal employees compared with farmers. Acceptance was higher among individuals from severely food-insecure households and lower among those from mildly food-insecure households. Focus groups revealed that perceived health benefits, sensory appeal, and cultural fit drove acceptance, while infertility-related myths and food colour changes were barriers. CONCLUSION: Fortified bouillon cubes were accepted, with perceptions improving over time. Public education will be essential to address misconceptions. TRIAL REGISTRATION: ClinicalTrials.gov (NCT05178407); Pan-African Clinical Trial Registry (PACTR202206868437931). The authors confirm that all ongoing and related trials for this intervention are registered.
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 →BMJ global health
The effects of antenatal interventions on gestational weight gain in low and middle-income countries: a systematic review
BACKGROUND: Gestational weight gain (GWG) during pregnancy is a critical factor that affects maternal and child health outcomes. The considerable burden of inadequate GWG and the rising tide of excessive GWG are overlooked challenges in low and middle-income countries (LMICs). METHODS: This systematic review assessed the impact of antenatal interventions on GWG in LMICs. Randomised controlled trials (RCTs) on antenatal interventions on GWG in LMICs were included. These interventions included educational, behavioural, nutritional supplementation and pharmacological therapies. A systematic literature search was conducted using PubMed, Embase, Web of Science, CINAHL and the Cochrane Library from the start of each database through September 2025. RESULTS: Out of the 33 642 unique articles identified, 70 articles were included in our systematic review, with 59 individual RCTs and 11 cluster RCTs. Nutritional interventions (31 studies) included food and micronutrient supplementations. Micronutrient supplementation such as multiple micronutrient supplementations was found to reduce the risk of severely inadequate or inadequate GWG among pregnant women compared to iron only or iron and folic acid supplementation (Grading of Recommendations Assessment, Development and Evaluation [GRADE]: moderate certainty). Food supplementation showed mixed results, although most trials demonstrated higher mean GWG among undernourished pregnant women and a greater likelihood of achieving Institute of Medicine-recommended ranges (GRADE: moderate certainty). Behavioural (counselling/education) interventions (20 studies) were associated with significant reductions in excessive GWG among pregnant women with overweight or obesity and improved adequacy of GWG (GRADE: moderate certainty). Physical activity (seven studies) was found to reduce the risk of excessive GWG (GRADE: moderate certainty). Combined dietary and physical activity interventions (six studies) were found to reduce the risk of excessive GWG among pregnant women (GRADE: low certainty). CONCLUSIONS: Well-structured antenatal interventions, initiated before 20 weeks of gestation and continuing beyond this period, tailored to local cultural contexts and available resources, can effectively help pregnant women in LMICs in achieving optimal GWG. PROSPERO REGISTRATION NUMBER: CRD42022366354.
4 Apr 2026
Read appraisal →Nat Med
Feasibility and clinical utility of expanded genomic newborn screening in the Early Check program
Although genomic sequencing presents groundbreaking newborn screening (NBS) opportunities, critical feasibility and utility questions remain. Here we present initial results from the Early Check program-an observational study assessing the feasibility and clinical utility of genomic NBS in North Carolina. Recruitment was statewide through mailed letters with electronic consent. Genome sequencing with analysis of 169 high actionability genes (plus 29 optional lower actionability genes) was performed using residual NBS dried blood spots. In 8 months, 1,979 newborns were screened, with 50 (2.5%) screen positives. Negative results were returned electronically, positive results by genetic counselors. Twenty-eight results (55%) were true positives, all received anticipatory guidance, surveillance and management recommendations, and referral to specialists as appropriate. We report technical feasibility and preliminary clinical utility finding, along with interpretation and follow-up challenges that hinder public health implementation. We propose standardized terminology to facilitate cross-study comparisons and accurate characterization of genomic NBS outcomes.
1 Nov 2025
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