Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
Showing 23 appraisals
Science advances
Human-inspired time-series health evaluation with an adaptive multimodal electronic skin
Electronic skin powered with artificial intelligence could enable next-generation robotic and medical devices, yet integrating multimodal sensors and analyzing heterogeneous, multifrequency time series remain challenging. Most wearable machine learning architectures are time-invariant and trained for a specific task, limiting transfer across modalities and users. We present a multimodal electronic skin that captures diverse physiological signs with an adaptive learning framework that rapidly generalizes to unseen tasks with minimal labeled data. Our streamlined end-to-end framework uses a spectral variational autoencoder to denoise and compress multifrequency biosignals into a shared, unified second-wise latent space that preserves the spectral-temporal structure, followed by a transformer to capture temporal dependencies to support diverse downstream tasks with data-efficient learning. We demonstrate robust adaptation with 94.7% accuracy in activity recognition and 90.2% precision in fatigue assessment across various users and daily activities regardless of device and user variations, highlighting a scalable route to generalized physiological time-series analytics and human performance assessments.
3 Aug 2026
Read appraisal →PloS one
Does delayed exercise-based priming improve subsequent athletic performance? A systematic review and multilevel meta-analysis.
This systematic review and multilevel meta-analysis examined whether delayed exercise-based priming improves subsequent athletic performance. Following PRISMA 2020 principles, 3,095 records were identified; after removing 1,107 duplicates, 1,988 unique records were screened, 212 full-text reports were assessed, 186 reports were excluded at eligibility, and 26 studies were included. Eighteen studies contributed 46 effect sizes to the quantitative synthesis. Risk of bias was assessed with RoB 2 principles calibrated for crossover exercise trials, and certainty was evaluated using GRADE. A three-level random-effects model showed a small positive average effect of delayed priming on subsequent performance (g = 0.232, 95% CI [0.092, 0.372], p = .002), with cluster-robust inference supporting the same conclusion (p = .004). The prediction interval crossed zero (-0.265 to 0.730), and the overall certainty of evidence was low. Delayed exercise-based priming can be used as a practical competition-day strategy when embedded in planned preparation windows, although protocol selection and athlete response should be checked in training before competition use.
31 July 2026
Read appraisal →PloS one
Analysis of swimming teaching programs, aquatic competencies and specific skills in school settings from early childhood to secondary education: A systematic review.
The teaching of swimming in school contexts has become increasingly important due to the benefits in the integral development of students and the prevention of aquatic accidents.This study analyses, by means of a systematic review, the aquatic teaching programmes and Competencies implemented in school settings over the last 25 years, from infant to secondary education. The Methodological approach was based on the PRISMA guidelines, with searches in scientific databases (PubMed, Scopus, Sport Discus and Web of Science) and secondary sources. Sixteen studies were selected according to the PICOS model, assessed with the STROBE and TREND tools. The results show a predominance of technical-utilitarian approaches focused on specific swimming skills, with little curricular integration and limited involvement of PE teachers. Most of the studies focused on infant and primary school, being scarce in secondary school. A high variability in duration, frequency, Contents and Assessment instruments was evidenced. The studies highlight the need for greater inclusion of swimming in school curricula, with more comprehensive pedagogical approaches adapted to each stage. It is concluded that although progress has been made, systematic implementation is still limited, requiring greater institutional support, teacher training and methodological coherence.
25 July 2026
Read appraisal →ACS applied materials & interfaces
Bioinspired Ionic Biogels for Conformal On-Skin Wearable Bioelectronics
Conductive gels are promising materials for on-skin wearable bioelectronics owing to their softness, ionic conductivity, and tissue-like interfacial characteristics. However, conventional preformed conductive gels often cannot fully accommodate complex and dynamically deforming skin surfaces, thereby limiting their interfacial adhesion and signal-transmission performance. Inspired by the reversible mechanical switching behavior of sea cucumbers, we developed a thermoresponsive ionic biogel (IBG) composed of gelatin, water, and 1-ethyl-3-methylimidazolium ethyl sulfate. In this system, gelatin forms a physical network with reversible sol-gel transition behavior, while the ionic liquid modulates the network through hydrogen bonding and electrostatic interactions and provides mobile ions for charge transport. This design integrates mechanical compliance, skin adhesion, water retention, and electrical functionality. The IBG can be directly coated onto skin in a flowable state and subsequently undergo mild in situ gelation, forming a soft, adaptive, and ion-conductive bioelectronic interface. The optimized IBG43 exhibits a low modulus, high stretchability, strong adhesion, and good environmental stability, together with stable strain sensing, reliable electrophysiological signal acquisition, and potential for self-powered sensing. This work presents a simple and effective strategy for constructing in situ formable skin-interfaced bioelectronic materials.
25 July 2026
Read appraisal →Current obesity reports
A Systematic Review of Community-based Interventions to Promote Physical Activity or Reduce Sedentary Behavior among Adults in Low- and Middle-Income Countries
PURPOSE OF REVIEW: Community-based interventions (CBIs) are widely used to address behavioral risk factors for non-communicable diseases, yet evidence of their effectiveness in low- and middle-income countries (LMICs) remains limited. This study systematically reviewed evidence on the effectiveness of CBIs promoting physical activity (PA) and/or reducing sedentary behavior (SB) among community-dwelling adults in LMICs. We searched PubMed, Embase, Scopus, and the Cochrane Library (2000-2024) for CBIs in LMICs. Primary outcomes were changes in PA and/or SB. Descriptive and graphical depictions were used to draw inferences. RECENT FINDINGS: We selected 24 studies (11 RCTs) from 15,396 for review. Most studies (n = 16) reported significant improvements in PA outcomes. Changes were observed in Metabolic Equivalents (+ 100 - +2,700), moderate-to-vigorous PA (+ 7 to + 60 min/week), and steps/day (+ 3,000). Broadly, interventions were delivered using digital/technology format (n = 10), peer-led/community health worker-facilitated (n = 8), and Environmental restructuring (n = 6), with the digital interventions depicting the most consistent significant improvements. Two studies directly measured SB as a primary outcome. Short- (≤ 6 months; n = 11) and medium-duration (6-12 months; n = 4) interventions more frequently reported significant PA improvements than long-duration interventions (> 12 months; n = 9). PA/SB-focused CBI demonstrated proportions of significant effects similar to those of broader lifestyle interventions (88.9% and 53.3%, respectively). CBIs can be effective in improving PA in LMICs, although evidence is heterogeneous and SB is less addressed. Digital interventions show more consistent positive signals, but high heterogeneity in studies precludes firm conclusions. The impact of duration on effectiveness looks counterintuitive but underscores the need for more rigorous evaluation of longer-duration interventions and SB outcomes. PROSPERO registration number: CRD42024579461.
23 July 2026
Read appraisal →Biomedical physics & engineering express
Benchtop validation of a low-cost wearable triaxial accelerometer
Wearable inertial sensors have become a cornerstone technology for detecting fall-related events, such as tripping while walking, in older adults. However, low-cost devices must undergo rigorous validation to ensure fidelity and stability in measurement. This study aimed to evaluate the concurrent validity of a newly developed, low-cost triaxial accelerometer by comparing its linear acceleration measurements with those obtained from a widely used commercial reference sensor (RS). A methodological validation study was conducted to assess the accuracy and precision of the proposed accelerometer. Triaxial linear acceleration data were simultaneously collected from the new device (sensor under test, SUT) and a commercial RS (Physilog®5, GaitUp, Lausanne, Switzerland). Measurements were obtained across three independent axes from 49 SUT units, with three repeated trials performed for each axis. The RS exhibited a more negative mean bias on the mediolateral (x) axis and a slightly larger mean bias on the vertical (y) axis. The SUT showed a greater mean bias (offset) on the anteroposterior (z) axis. Root mean squared error values were highly similar between thexandyaxes (<3.2% difference), while thez-axis presented moderately larger errors (∼9%). Mean absolute error was similar in thexandyaxes, whereas thez-axis was slightly higher. Visual waveform comparisons demonstrated strong overlap in mean time-series profiles, and near-unity correlations indicated high correspondence in signal variation. Bland-Altman analysis confirmed minimal bias and narrow limits of agreement for thexandyaxes, with greater variability observed along thezaxis, but no evidence of substantial systematic deviation. Overall, the low-cost accelerometer (∼60 USD) showed strong agreement with the commercial reference device (>1 000 USD), supporting its validity for three-dimensional linear acceleration measurement under controlled laboratory conditions. This low-cost device represents a promising solution for scalable motion monitoring and fall-related event detection.
20 July 2026
Read appraisal →JMIR cardio
Mobile Apps for Heart Rate Variability: App Store Search and Content Analysis
BACKGROUND: Heart rate variability (HRV) is a noninvasive indicator of autonomic nervous system activity that is increasingly used for health and performance monitoring. Digital and mobile technologies are increasingly providing opportunities for remote HRV monitoring outside of laboratory-based settings. OBJECTIVE: This study aimed to describe the landscape of mobile apps that measure, analyze, and provide feedback on HRV, with a focus on how HRV is measured, analyzed, interpreted, and communicated to users. A secondary aim was to assess the transparency of these apps, including the extent to which they disclose the evidence underpinning their HRV metrics and feedback. METHODS: This study was an app store search and content analysis. Searches were conducted in the Google Play Store and Apple iTunes Store. Apps were eligible for inclusion if they had functionality to record, analyze, or provide feedback on HRV and were available in English. Data were extracted from app descriptions, screenshots, websites, and, where necessary, contact with developers. Data were extracted on app metadata (developer, release and update dates, and pricing), alongside information about HRV measurement, analysis, and feedback. This included the type of sensor used; HRV measurement characteristics (sensor placement, recording duration, and body position or standardization procedures); methods to calculate and interpret HRV (ie, metrics derived and how they were interpreted for users); and additional app functionality such as reminders, the ability to log self-reported stressors, and the type of feedback or guidance provided based on HRV. We used previously published criteria for assessing the quality of information on the internet, which included authorship, scientific attribution, currency of updates, and data privacy. RESULTS: Of 746 apps identified, 206 met eligibility criteria. Of these, 132 were primary measurement apps, 59 were aggregators, and 15 were hybrid. Photoplethysmogram was the most common sensing modality (n=117, 56.8%), followed by multiple sensors (n=60, 29.1%). Full data extraction across app metadata and HRV measurement and analysis data was only achievable for 93 (45.1%) apps, representing a transparent subset with sufficient available information for content analysis. The most commonly reported HRV metrics were root mean square of successive differences (n=51) and SD of normal-to-normal intervals (n=48), while frequency-domain power (n=22) and low frequency to high frequency ratios (n=15) were less common. Most apps presented data as personalized trends or individualized ranges (76/93, 81.7%), emphasizing user-specific context rather than isolated values. Although 86% (80/93) offered contextual guidance (eg, readiness or recovery scores), many relied on proprietary algorithms that were not transparently described, limiting independent assessment of how these scores were derived and validated. CONCLUSIONS: Consumer HRV apps are widely available but vary considerably in how data are collected, processed, and contextualized. While many offer personalized trends and guidance, methodological transparency is often limited, particularly regarding the proprietary algorithms underlying the feedback scores.
20 July 2026
Read appraisal →Scientific reports
Integrating skeleton based representations for robust yoga pose classification using deep learning models
Yoga is a popular form of exercise worldwide due to its spiritual and physical health benefits, but incorrect postures can lead to injuries. Automated yoga pose classification has therefore gained importance to reduce reliance on expert practitioners. While human pose keypoint extraction models have shown high potential in action recognition, systematic benchmarking for yoga pose recognition remains limited, as prior works often focus solely on raw images or a single pose extraction model. In this study, we introduce a curated dataset, "Yoga-16", which addresses limitations of existing datasets, and systematically evaluate three deep learning architectures-VGG16, ResNet50, and Xception-using three input modalities: direct images, MediaPipe Pose skeleton images, and YOLOv8 Pose skeleton images. Our experiments demonstrate that skeleton-based representations outperform raw image inputs, with the highest accuracy of 96.09% achieved by VGG16 with MediaPipe Pose skeleton input. Additionally, we provide interpretability analysis using Grad-CAM, offering insights into model decision-making for yoga pose classification with cross validation analysis.
17 July 2026
Read appraisal →Journal of medical Internet research
User Acceptability and Adoption of AI-Generated Lifestyle Intervention Recommendations: Scoping Review and Theoretical Integration
BACKGROUND: Artificial intelligence (AI)-generated lifestyle recommendations are increasingly used to support health behavior change. However, AI advice does not necessarily mean that users will accept or adopt those recommendations. Although prior reviews have examined AI-enabled lifestyle interventions and health behavior technologies, fewer have focused on whether users accept and adopt AI-generated recommendations. OBJECTIVE: This scoping review aimed to map user acceptability and adoption of AI-generated lifestyle recommendations in user-facing systems used by end users or caregivers. Objectives were to characterize systems and evaluation contexts, clarify how recommendation-level outcomes were conceptualized and measured, synthesize shaping factors, and develop an evidence-informed framework to guide future research, evaluation, and design. METHODS: Following JBI (Joanna Briggs Institute) guidance and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews), we searched Ovid MEDLINE, Ovid Embase, APA PsycInfo via ProQuest, Web of Science Core Collection, Scopus, ACM Digital Library, and IEEE Xplore from database inception to May 5, 2026. The initial search was conducted on November 21, 2025, and an updated search was conducted on May 5, 2026. Eligible studies reported empirical end-user or caregiver data, evaluated AI-generated lifestyle recommendation content delivered without manual review or editing, and reported an acceptability or adoption outcome linked to recommendations. English empirical papers and conference papers were included. Data were charted on study, system, outcome, measurement, factor, and theoretical characteristics. Quality was assessed with the Mixed Methods Appraisal Tool. Findings were synthesized descriptively and through evidence mapping. RESULTS: Searches yielded 12,997 records; 8570 unique records were screened, and 21 studies were included. Most were published in 2025 or 2026 (17/21, 81%). Large language model-centered systems were the most common format (12/21, 57.1%). Outcomes were concentrated in acceptability-related perceptions, such as satisfaction or enjoyment, perceived quality or fit, and persuasiveness, whereas adoption-related outcomes were assessed less often and mainly reflected intention, in-study uptake, or short-term enactment. Factors clustered across system capabilities, content properties, individual states and capacities, and contextual constraints. Findings informed an integrative perception-intention-enactment framework positioning acceptability and adoption as a system-content-user-context process. CONCLUSIONS: This review extends prior AI and digital health reviews by shifting attention toward how users perceive, intend to follow, and enact AI-generated lifestyle recommendations. Acceptability and adoption appear to depend on systems eliciting and adapting to context, content being actionable and credible, users having the capacity to interpret, trust, and engage with recommendations while retaining control, and resources, routines, and social contexts allowing enactment. The framework can guide theory-driven evaluation, outcome selection, and system design by identifying where recommendation processes may succeed or fail, but should be interpreted as preliminary and evidence-informed rather than causal. By integrating implementation, behavioral, and human-AI perspectives, this review provides a foundation for moving AI-generated lifestyle recommendations from technically plausible outputs toward user-centered, context-sensitive, and behaviorally actionable support.
16 July 2026
Read appraisal →Journal of epidemiology and community health
Analysis of the potential association between physical activity and skin autofluorescence: a systematic review.
INTRODUCTION: Accumulation of advanced glycation end products, measured by skin autofluorescence (SAF), has been shown to be associated with several chronic non-communicable diseases, particularly cardiovascular diseases (CVDs). The promotion of physical activity (PA) as a strategy for the prevention of CVD by modifying healthy habits has been widely studied. AIM: To assess the evidence for the association between PA and SAF in the general adult population. METHODS: A systematic review was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and the Synthesis Without Meta-analysis framework. A search was performed in MEDLINE (via PubMed), Web of Science, Scopus, Cochrane Library and SportDiscuss (via EBSCOhost), from inception to September 2024. Study quality was assessed using the National Heart, Lung and Blood Institute tools and the certainty of evidence was evaluated with Grading of Recommendations, Assessment Development and Evaluation. Vote counting based on the direction of effect was used as the standardised synthesis metric. RESULTS: In the systematic review, 17 studies were included. The qualitative synthesis showed a predominant consistency in favour of a beneficial association. Specifically, 58.8% of the studies reported a statistically significant inverse association, indicating that higher levels of PA or exercise frequency are correlated with lower SAF levels. The remaining studies (41.2%) reported non-significant results, though several showed favourable trends. No studies reported a positive association between PA and SAF. The quality of the studies was generally fair, and the certainty of evidence low. CONCLUSIONS: PA is inversely associated with SAF. Therefore, while causality cannot be proven, it is hypothesised that PA may reduce SAF and thus have a positive impact on health.
11 July 2026
Read appraisal →Forensic science international
Is my smartwatch a valid witness? A systematic review and meta-analysis.
Wearable devices are being increasingly used not only in traditional research fields (e.g. clinical, health) but also in innovative ones such as digital forensics. Modern commercial smartwatches, equipped with sensors like accelerometers, gyroscopes, and photoplethysmographs, can record activity, heart rate, sleep, and other physiological parameters that may support forensic investigations, given that their data is valid. To perform a first step in studying such validity, this article presents a systematic review and meta-analysis summarizing the available studies validating data collected from smartwatches, focusing on their potential use in forensic investigations. The review examined studies evaluating smartwatches from four major brands, comparing their outputs, such as activity classification, step count, distance, heart rate, energy expenditure, and sleep metrics, against established gold-standard measures. We found that not all brands of smartwatches and not all outcomes were equally studied, with varying results in terms of accuracy, protocols, and reporting of results. Heart rate resulted the most studied (and most accurate) measure. Most studies validated smartwatches in healthy populations and performed validation in laboratory settings. Overall, while smartwatches show promise for enhancing digital forensic analyses, their current validation evidence is heterogeneous. The findings highlight the need for more extensive and standardized validation efforts, larger and more diverse study populations, and improved transparency from manufacturers. These conclusions are not only relevant for forensic applications but also extend to broader domains, such as clinical and health research, where the reliability of wearable-derived data is equally critical.
1 July 2026
Read appraisal →Diving and hyperbaric medicine
Bipolar spectrum disorders in divers: risks, recognition, and recommendations.
Bipolar disorder is a recurrent psychiatric condition characterised by episodic mood disturbances, residual functional impairment, and high rates of psychiatric and medical comorbidity. While many individuals achieve symptomatic remission, persistent deficits in cognition, emotional regulation, and insight may remain, raising concerns for participation in safety-critical activities such as scuba diving. This systematic review synthesised evidence from psychiatric, occupational, aviation, and diving medicine literature to examine the clinical course of bipolar disorder, treatment considerations, functional outcomes, and safety-relevant factors pertinent to fitness-to-dive assessments. Bipolar disorder exhibits marked heterogeneity in syndromal and functional outcomes. Even during euthymia, subtle impairments in attention, executive functioning, and decision-making may persist. Pharmacological stability is essential for diving, but treatment regimens, particularly lithium use, polypharmacy, and antidepressant therapy, introduce additional considerations. Comorbidity, circadian disruption, sleep deprivation, and reduced insight during early relapse further complicate risk assessment. Empirical data on diving outcomes in individuals with bipolar disorder are scarce, necessitating reliance on expert opinion and extrapolation from related safety-critical domains. Fitness-to-dive assessments in bipolar disorder should prioritise sustained functional stability, reliable treatment adherence, and illness insight over symptom absence alone. A cautious, individualised approach is warranted, incorporating medication effects, comorbidity, operational context, and relapse-prevention planning, supported by collaboration between mental health professionals and diving medical examiners.
30 June 2026
Read appraisal →European journal of pediatrics
Feasibility of image-based 3D avatar anthropometry assessment of pediatric obesity: a pilot study.
UNLABELLED: The purpose of this study is to evaluate the feasibility and validity of 3D avatar-based anthropometry for assessing anthropometric indicators of overweight and obesity in children based on artificial intelligence-derived 3D body reconstruction. This cross-sectional study included 171 children aged 8-10 years from five primary schools in southern Spain. Due to technical constraints of the reconstruction software, 75 children meeting predefined image quality and body weight requirements (≥ 30 kg) were eligible for 3D avatar analysis. Manual anthropometric measurements were obtained following International Society for the Advancement of Kinanthropometry (ISAK) standards and compared with avatar-derived circumferences. Agreement was assessed by using Wilcoxon tests, Spearman correlations, Bland-Altman analyses, and false discovery rate-adjusted comparisons. Avatar-derived circumferences were consistently greater than manual measurements, although waist-to-hip and waist-to-stature ratios demonstrated no significant differences. Avatar and manual circumferences were moderately to strongly correlated (Spearman's ρ = 0.62-0.72; adjusted p < 0.05). However, the mean absolute errors ranged from 6.21 to 7.11 cm, and Bland-Altman analysis revealed systematic overestimation with wide limits of agreement, particularly for waist and hip circumferences. Despite these discrepancies, both methods similarly discriminated between weight status categories. CONCLUSION: Image-based 3D avatar anthropometry is a feasible, noninvasive approach for population-level screening and research in pediatric settings. Although the system reliably captures relative differences and body proportions, its current accuracy is insufficient for individual-level clinical assessment. Further algorithmic refinement and validation in lighter and more diverse pediatric populations are needed before clinical implementation. WHAT IS KNOWN: • Childhood obesity remains a major public health challenge requiring accurate monitoring. • Anthropometric assessment still relies mainly on manual measurements, while AI-based 3D body modeling offers a promising non-invasive alternative. WHAT IS NEW: • Image-based 3D avatar anthropometry is feasible in school settings but is constrained by technical requirements. • Avatar measurements are correlated with manual anthropometry and preserve weight status discrimination but demonstrate systematic overestimation and limited agreement.
29 June 2026
Read appraisal →Journal of special operations medicine : a peer reviewed journal for SOF medical professionals
Prediction Factors Associated with Success in Military Special Operations Courses: A Systematic Review
BACKGROUND: We investigated factors associated with military personnel success in Special Operations courses (course pass or fail). METHODS: A systematic search was conducted across eight databases using the keywords "Special Operations" and "attrition." Sample size and profile data, course characteristics, predictive factors, follow-up, and results were extracted from the studies. We compared the means of the variables associated with success between the groups that completed and did not complete the courses. A meta-analysis was conducted for factors assessed by two or more studies, pooling standardized or weighted mean differences using fixedor random-effects models. RESULTS: A total of 23 studies were included. They were published between 1990 and 2022, included samples from 10 nations, lasted between 5 days and 12 months, and ranged from 11 to 1,138 individuals. VO2max, pull-ups, push-ups, and marching performance showed consistent positive associations with course success, while body fat percentage and sit-up performance did not. Certainty of evidence was rated as low to very low using the Grading of Recommendations Assessment, Development, and Evaluation. CONCLUSION: The factors that increased the probability of success in Special Operations courses were character strengths, recidivism in the course, anthropometric data, performance on physical assessment tests, psychological dissociation, psychosocial resources, blood markers, smoking/alcohol consumption, personality, and psychological strength. These findings support the inclusion of aerobic capacity, muscular endurance, and psychological resilience in early screening and preparatory selection processes.
29 June 2026
Read appraisal →ACS sensors
Lignin-Regulated Amphiphilic Janus Membrane for Eco-Friendly Electronic Skin
Eco-friendly electronic skin fabricated from sustainable natural materials represents a pivotal technology for advancing healthcare and sports-oriented wearable electronics, yet balancing comfort and electronic functionality remains challenging due to inadequate moisture management. Herein, we report an eco-friendly lignin-regulated amphiphilic Janus membrane (LAJM)-based pressure sensor that synergistically integrates unidirectional water transport with exceptional sensing performance. Through sulfonation and fluorination modifications of lignin fractions with distinct hydrophilic and hydrophobic properties, we engineer an electrospun layer with controlled hydrophobic-hydrophilic gradients, enabling unidirectional water transport while maintaining a dry and comfortable microenvironment. Moreover, LAJM demonstrates notable biocompatibility, antibacterial efficacy, and antioxidant properties, positioning it as a promising candidate for intelligent wound care systems. The LAJM-based pressure sensor achieves integrated sensing capabilities through its hierarchical structure, exhibiting a high sensitivity of 23.97 kPa-1 in the 0-20 kPa range, an extended operational range (0-200 kPa), and ultrafast response dynamics (22 ms response/31 ms recovery). These metrics enable robust continuous monitoring of vital signs (e.g., radial pulse waveforms), discrimination of voice patterns, and precise motion trajectory mapping under dynamic conditions. This technological breakthrough in lignin valorization establishes a scalable platform for next-generation breathable epidermal electronics, with transformative implications for AI-driven healthcare diagnostics and adaptive human-machine interfaces.
28 June 2026
Read appraisal →Journal of global health
Habitual physical activity and sarcopenia: a systematic review and meta-analysis of prospective cohort studies
BACKGROUND: Habitual physical activity (HPA) has been associated with a lower risk of sarcopenia by enhancing skeletal muscle protein synthesis and suppressing systemic inflammation. However, the evidence for a long-term protective association remains inconclusive. Therefore, we conducted a systematic review and meta-analysis to quantify the association between HPA and sarcopenia. METHODS: We searched PubMed, the Cochrane Library, EMBASE, Cumulative Index to Nursing and Allied Health Literature, Web of Science, and the China National Knowledge Infrastructure for prospective cohort studies on the relationship between physical activity (PA) and sarcopenia. We selected English and Chinese-language literature published before 6 October 2025, and assessed study quality using the Newcastle-Ottawa Scale. Data were statistically synthesised by calculating pooled relative risks (RRs) and 95% confidence intervals (CIs) using a random-effects model with the generic inverse-variance method. RESULTS: This meta-analysis included nine prospective cohort studies involving 21 265 participants. High levels of HPA were associated with a significantly lower risk of sarcopenia compared to the low levels (RR = 0.55; 95% CI = 0.44-0.67). This protective association remained consistent in subgroup analyses stratified by gender and by compliance with international PA guidelines. Furthermore, moderate HPA was also associated with a reduced risk compared to low HPA levels (RR = 0.73; 95% CI = 0.50-0.96). CONCLUSIONS: Our analysis indicates that moderate to high levels of HPA are independently associated with a lower risk of sarcopenia, serving as a significant protective factor. However, given the methodological heterogeneity in PA measurement, further high-quality prospective studies are needed to clarify the optimal PA dose while accounting for potential reverse causality. REGISTRATION: PROSPERO: CRD420251162529.
28 June 2026
Read appraisal →Biofabrication
3D printed trichome-inspired permeable bioadhesive for wearable bioelectronics
Wearable bioelectronics that adhere directly to the skin have broad applications. However, achieving optimal breathability remains a significant challenge because of sweat accumulation at the device-skin interface. Conventional approaches, such as porous structures, often limit the functional versatility of wearable bioelectronics. To address this gap, we propose a sweat-removable skin sticker (SRSS) with a hierarchical trichome-inspired channel architecture that rapidly removes sweat from the interface while maintaining robust skin adhesion. The SRSS was fabricated through a hybrid process, in which the trichome-inspired hierarchical microchannel architecture was created by direct ink writing, enabling the controlled deposition of viscous ink with high structural fidelity. Through the multi-level ribs design, the SRSS demonstrated an effective area-normalized horizontal water removal rate (25.6 ml cm-2min-1) significantly higher than the human sweat secretion rate (0.38-2.85 × 10-3ml cm-2min-1)-approximately three orders of magnitude. This feature reduces sweat accumulation in wearable bioelectronics, thereby enhancing user comfort. Unlike conventional porous materials, the SRSS relies on channel based adhesive interface design that remains compatible with attached wearable bioelectronics, such as temperature sensors in real time. This work therefore presents a structurally engineered permeable bioadhesive interface for wearable bioelectronics.
27 June 2026
Read appraisal →Journal of neurology
Exercise- and dietary pattern-based lifestyle interventions and neurocognitive function in adults: a Bayesian multilevel network and dose-response meta-analysis
OBJECTIVE: To systematically review the effects of lifestyle interventions focused on exercise and dietary patterns on neurocognitive function in adults, and to examine their relative effects and dose-response relationships. METHODS: PubMed, Embase, Web of Science, and the Cochrane Library were searched from database inception to March 20, 2026. A total of 23 randomized controlled trials (RCTs) involving 12,286 participants were included. Bayesian multilevel pairwise, network, and dose-response meta-analyses were conducted to evaluate overall cognition, memory, and executive function. RoB 2 and CINeMA were used to assess the credibility of the evidence. RESULTS: Combined interventions yielded small, but statistically significant cognitive benefits (overall cognition: SMD = 0.18; memory: SMD = 0.10; executive function: SMD = 0.09). These benefits were driven primarily by differences between the combined intervention and control or usual care, as well as exercise alone; compared with diet alone, the combined intervention still showed a small advantage for executive function. Network meta-analysis suggested that AE_MIND and AE_RT_MED were more beneficial for overall cognition, AE_RT_MIND and AE_RT_MED for memory, and AE_RT_CR and AE_MIND for executive function. Exploratory dose-response analyses suggested possible curvature in some spline-based models; however, comparison with simpler monotonic specifications did not provide robust evidence for a clinically interpretable non-linear or monotonic dose-response relationship. CONCLUSION: Combined lifestyle interventions may produce statistically significant but modest improvements in cognitive function in adults, with benefits varying across cognitive domains. However, current evidence remains insufficient to support a standardized precision prescription, and high-quality RCTs with long-term follow-up are needed to determine the optimal combinations and dosages.
25 June 2026
Read appraisal →BMJ open
Workplace interventions for chronic musculoskeletal disorders: a systematic review
OBJECTIVES: To provide an updated systematic review of the effectiveness of workplace interventions for chronic musculoskeletal disorders, identify key intervention components and assess their impact on health and work-related outcomes. DESIGN: Systematic review of randomised controlled trials. DATA SOURCES: MEDLINE, EMBASE, CINAHL, PsycINFO, Scopus and Web of Science were searched for studies published between 2018 and 2024. Grey literature sources were also consulted. ELIGIBILITY CRITERIA: Randomised controlled trials and cluster-randomised trials evaluating workplace interventions targeting adults with chronic musculoskeletal disorders were included. Outcomes of interest included pain, functional outcomes, quality of life and work-related outcomes (eg, work ability, productivity, presenteeism and absenteeism). DATA EXTRACTION AND SYNTHESIS: Two reviewers independently screened studies, extracted data and assessed risk of bias using the Cochrane Risk of Bias 2 tool. Due to heterogeneity, only a narrative synthesis was conducted. RESULTS: 23 studies involving 2456 participants were included and classified into physical exercise, ergonomic and multicomponent interventions. Physical exercise interventions consistently improved pain and functional outcomes. Digital delivery of exercise interventions demonstrated comparable effectiveness to face-to-face or workplace-based approaches. Multicomponent interventions, combining exercise with ergonomic strategies, demonstrated the most consistent benefits across outcomes. Evidence for work-related outcomes was limited and inconsistent, and quality of life was assessed in only a small number of studies. CONCLUSIONS: Workplace interventions, particularly multicomponent approaches combining exercise, ergonomics and education, can be effective in improving health outcomes in chronic musculoskeletal disorders. However, evidence on work-related outcomes remains limited and inconsistent. PROSPERO REGISTRATION NUMBER: CRD420261289218.
24 June 2026
Read appraisal →Scientific reports
Classifying mental stress from eye tracking data: deep learning approaches for out-of-the-lab conditions
Eye-tracking signals such as pupil diameter and gaze behavior have been widely used for stress detection, yet most approaches rely on task-specific features, controlled laboratory settings, or multimodal sensor combinations, limiting scalability in less controlled environments. This work investigates whether unimodal eye-tracking time-series data can support task-agnostic stress detection beyond static laboratory tasks. We analyze stress classification across two complementary datasets: a virtual reality goalkeeper task with moderate visuomotor activity and stable recording conditions, and a virtual job interview dataset reflecting less controlled settings with uncalibrated signals. The results show that these signals alone contain informative patterns related to stress-associated autonomic and oculomotor responses. Under favorable conditions, performance reaches up to [Formula: see text] macro-averaged F1-score. At the same time, performance varies substantially across datasets, indicating that effective learning depends strongly on data quality, calibration, signal characteristics, and task design. Overall, the findings demonstrate the potential of unimodal eye tracking as a lower-burden alternative to more complex multimodal systems, while highlighting that reliable stress detection is fundamentally conditioned by the interplay of data, signal representation, and modeling approach.
23 June 2026
Read appraisal →BMJ open
Pilates during pregnancy for maternal musculoskeletal pain and discomfort: a systematic review and meta-analysis
OBJECTIVES: The predominant concern during pregnancy is musculoskeletal pain, often accompanied by additional discomforts such as anxiety and insomnia. Pilates, as a low-impact mind-body exercise, may be beneficial in managing musculoskeletal pain and associated symptoms in adults. This systematic review and meta-analysis aimed to synthesise the evidence on the effectiveness of Pilates for alleviating musculoskeletal pain and other discomforts during pregnancy. DESIGN: Systematic review and meta-analysis. DATA SOURCES: PubMed, Scopus, TRIP Medical Database, Web of Science and the Cochrane Central Register of Controlled Trials (CENTRAL) were searched from inception to 14 January 2026. ELIGIBILITY CRITERIA: Randomised controlled trials and prospective non-randomised controlled studies that compared Pilates with other prenatal care modalities for improving musculoskeletal pain and discomfort were eligible. DATA EXTRACTION AND SYNTHESIS: Two researchers independently extracted data using standardised forms with subsequent cross-verification. Risk of bias was assessed using the Cochrane Risk of Bias V.2.0 tool. Meta-analyses were performed using random-effects models. The certainty of evidence was evaluated using the Grading of Recommendations Assessment, Development and Evaluation approach. RESULTS: 13 studies were included in the systematic review, of which 10 contributed data to the meta-analysis. Primary outcomes were pain intensity and disability level. Pain intensity was assessed using Visual Analogue Scale (range 0-10). Moderate-certainty evidence demonstrated that Pilates significantly reduced musculoskeletal pain during pregnancy (mean differences (MD)=-2.59, 95% CI -4.19 to -1.00; I²=91%, p=0.001). Low-certainty evidence suggested that Pilates reduced pregnancy-related disability (standardised mean differences (SMD)=-1.82, 95% CI -2.99 to -0.66; I² = 93%, p=0.002). Secondary outcomes comprised sleep quality and psychological status. Multivariate meta-analysis showed significant improvements in psychological status (SMD=-0.86, 95% CI -1.31 to -0.42; τ²=0.4, I²=86%, p=0.0005) but did not yield statistically significant improvements in sleep quality (MD=-1.93, 95% CI -4.70 to 0.84; I²=93%, p=0.17). Both secondary outcomes were supported by very low-certainty evidence. Risk of bias assessment rated three studies as high risk, three as unclear risk and seven as low risk. Formal assessment of publication bias was not feasible owing to the limited number of studies (fewer than 10 per outcome). CONCLUSION: This meta-analysis demonstrates that, compared with standard care, structured prenatal Pilates significantly alleviates musculoskeletal pain and disability while also enhancing psychological status. PROSPERO REGISTRATION NUMBER: CRD42024628027.
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 →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
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