Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
Showing 101 appraisals
Journal of affective disorders
The role of treatment expectancy in lifestyle interventions for depression.
BACKGROUND: Treatment expectancy is a key mechanism underlying placebo. While well-documented in psychopharmacology and psychotherapy, its role in lifestyle-based interventions for mental disorders is uncertain. Given the emerging role of lifestyle-based mental health care, a comprehensive evaluation of the role of treatment expectancy has not yet been explored, especially when compared to other more established therapies. The potential for genuine treatment efficacy to be masked by placebo response may bring into question the magnitude of effects of this treatment. METHODS: We sought to: 1) investigate the role of treatment expectancy as a moderator of depression treatment outcomes in a completed randomised controlled trial of psychotherapy versus lifestyle therapy (the CALM trial); and 2) provide guidance on measuring and reporting expectancy effects in future trials. CALM was a two-arm, parallel-group, non-inferiority randomised controlled trial, comparing lifestyle therapy (delivered by accredited dietitians and exercise physiologists) and psychotherapy (facilitated by psychologists). A total of 182 participants (91 per arm) experiencing psychological distress (equivalent to 'indicative depression') during the COVID-19 pandemic were randomised. We assessed associations of expectancy (measured prior to randomisation using the Credibility-Expectancy Questionnaire) with reductions in depressive symptoms (as measured by the PHQ-9). RESULTS: Expectancy scores did not differ between treatment groups at baseline (β = 1.14; 95%CI = -1.93, 4.22). Both arms reduced PHQ-9 between baseline and 8-weeks (lifestyle mean difference = -30.25%, SD = 58.23%; psychotherapy mean difference = -22.46%, SD = 66.87%). However, higher expectancy was associated with a greater reduction in depression only in the psychotherapy arm: for every 1-unit increase in expectancy score depressive symptoms reduced by an additional 3.21% for psychotherapy compared to lifestyle therapy (95%CI = -5.77, -0.65). CONCLUSIONS: In this study we showed that participants' expectations about treatment at enrolment were only associated with treatment response in psychotherapy. These findings highlight the need to account for modality-specific drivers of expectancy when evaluating all treatments for depression, and support the inclusion of expectancy in reporting guidelines for future trials. REGISTRATION: The trial was registered with the Australian New Zealand Clinical Trials Registry (ACTRN12621000387820; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=380897).
16 June 2026
Read appraisal →Sexual health
A systematic review of barriers to cervical cancer screening among Thai women based on the social ecological model: a multi-level analysis of local evidence
BACKGROUND: Cervical cancer is a significant public health issue in Thailand. Despite the implementation of a national screening program, its coverage remains suboptimal. This study aims to systematically review local Thai evidence and comprehensively analyze the multi-level barriers affecting women's participation in cervical cancer screening using the social ecological model (SEM). METHODS: Systematic searches were conducted in PubMed, Scopus, CINAHL and ThaiJO databases from inception to 2025. Literature was screened according to pre-defined inclusion and exclusion criteria, resulting in the inclusion of 11 studies. The Newcastle-Ottawa scale and a mixed-methods assessment tool were used for rigorous quality appraisal. Thematic synthesis was used to categorize screening barriers into five levels: individual, interpersonal, community, health system and public policy. RESULTS: The key obstacles identified include: at the individual level, lack of knowledge, fear, shame and insufficient risk perception; at the interpersonal level, the influence of family and social norms; at the community level, cultural, religious and regional factors; at the health system level, poor service accessibility and system inefficiencies; and at the public policy level, incomplete health insurance coverage and insufficient awareness campaigns. Many of these obstacles show distinct characteristics of Thai society and culture. CONCLUSION: Barriers to cervical cancer screening among Thai women constitute a complex, multi-level system. Future intervention strategies must move beyond single-level health education, and should develop cross-level, culturally-appropriate, comprehensive measures. These include promoting HPV self-sampling, conducting community empowerment education, optimizing the health service system and strengthening policy support to systematically increase screening participation.
16 June 2026
Read appraisal →Journal of affective disorders
MDD-thinker: A reasoning-enhanced large language model for diagnosis of major depressive disorder.
BACKGROUND: Major depressive disorder (MDD) is a leading cause of global disability and poses a substantial public health burden. However, current diagnostic approaches largely rely on subjective assessments and lack the ability to integrate heterogeneous clinical and sociodemographic information. Recent advances in large language models (LLMs) offer new opportunities to support MDD diagnosis through reasoning over complex data, yet their clinical applicability is constrained by challenges related to interpretability, hallucinations, and reliance on synthetic data. METHODS: We propose MDD-Thinker, an LLM-based diagnostic system that integrates supervised fine-tuning (SFT) and reinforcement learning (RL) to enhance reasoning and interpretability under the evaluated conditions. Using the UK Biobank dataset, we constructed 40,000 structured reasoning samples and incorporated an additional 10,000 records from publicly available mental health datasets. MDD-Thinker was trained on these heterogeneous textual data and evaluated against conventional machine learning models, deep learning methods, and representative LLM baselines in terms of diagnostic performance and interpretability. RESULTS: MDD-Thinker achieved high performance in MDD diagnosis, with an accuracy of 0.8268 and an F1-score of 0.8081, showing better performance than conventional machine learning models, deep learning approaches, and representative LLM baselines on the evaluated dataset. Beyond predictive accuracy, it consistently produced structured reasoning paths that were clinically coherent, enabling transparent interpretation of diagnostic decisions in the evaluated experiments. The integration of SFT and RL contributed to notable improvements in both diagnostic reliability and reasoning quality. CONCLUSION: MDD-Thinker demonstrates the potential of reasoning-enhanced LLMs for large-scale MDD diagnosis under the evaluated settings. By jointly optimizing accuracy, interpretability, and efficiency, the proposed system provides a scalable and explainable approach for intelligent psychiatric assessment within the scope of the study, highlighting the potential of reasoning-oriented LLMs in mental health care.
15 June 2026
Read appraisal →Scandinavian journal of primary health care
The diagnostic accuracy of AI-assisted diabetic retinopathy screening in primary care: a prospective validation study
OBJECTIVES: This study investigated the diagnostic accuracy of AI-assisted diabetic retinopathy screening in primary care, using ophthalmologist-led screening as the reference standard. METHODS: Patients with type 2 diabetes attending routine appointments at 10 primary care clinics underwent AI-assisted screening, followed by re-screening at an ophthalmology clinic. The quality of fundus images captured in primary care was independently assessed, and diagnostic accuracy was evaluated by comparing AI-assisted results with ophthalmologist results, including sensitivity, specificity, PPV, NPV, and AUC. Two analyses were conducted: one including all images and one excluding those of poor quality. RESULTS: Among 183 patients (336 images), 18.6% of images were classified as poor quality. When all images were included, the AI-assisted screening achieved a sensitivity of 73.7%, specificity of 90.2%, PPV of 31.1%, NPV of 98.3%, and AUC of 0.82. Excluding poor-quality images improved sensitivity to 80.0%, NPV to 98.7%, and AUC to 0.84. Additional ocular findings unrelated to diabetic retinopathy were observed in 96 patients, including confirmed or non-specific signs of glaucoma, cataract, age-macular degeneration, benign nevus and reduced visual acuity. CONCLUSION: AI-assisted screening in primary care shows potential for clinical application, but further validation in larger populations and improvements in image quality are needed before clinical implementation.
14 June 2026
Read appraisal →JMIR cancer
Identification of Early Signs of Mental Health Disorders in Older Survivors of Cancer Using Patient-Generated Health Data: Observational Study
BACKGROUND: Older survivors of cancer face heightened risk of depression and anxiety related to cancer experiences, fear of recurrence, and aging-related difficulties. Conventional mental health monitoring approaches, such as clinical assessments and even electronic patient-reported outcomes, are limited by recall bias, patient burden, and infrequent data collection. Emerging patient-generated health data from wearables and smart home devices offer passive, low-burden, continuous monitoring, but their ability to capture mental health risks in older survivors of cancer remains unclear. OBJECTIVE: This study aims to explore whether patient-generated health data collected in the wild, either passively or actively, can classify older survivors of cancer as having or not having signs of anxiety and depression based on Patient Health Questionnaire-4 (PHQ-4) scores and to assess the potential added value of passive monitoring modalities, such as smart plugs. METHODS: This study recruited 41 older survivors of cancer (mean age 72.3, SD 6.81 years) from the LifeChamps project. Over a 12-week period, participants were monitored using an activity tracker to measure physical activity, sleep, and physiological metrics; a smart scale to capture weight and body composition; and a smart plug to track television use as a proxy for sedentary television viewing. Mental health status was self-reported via the PHQ-4 questionnaire in a mobile app. Machine learning models were trained to classify mental health risk based on features derived from each sensor modality, both independently and in combination. RESULTS: Tree-based gradient boosting models showed good performance in classifying PHQ-4-defined mental health risk. The best-performing configuration, combining smart plug and smart scale features, achieved a mean F1-score of 0.77 (SD 0.15) and a mean area under the receiver operating characteristic curve (AUC) of 0.85 (SD 0.10) across 3 repeated train-test splits. Standalone smart plug models, based solely on passive television use patterns, achieved a mean F1-score of 0.66 (SD 0.04) and a mean AUC of 0.71 (SD 0.06), outperforming models that relied only on activity tracker data (mean F1 0.59, SD 0.2). Multimodal combinations tended to improve average performance but did not consistently yield large gains over the strongest single-modality configurations, likely reflecting adherence-related data loss for wearables and scales. Crucially, passive monitoring of television use patterns emerged as a promising behavioral proxy measure of mental health states. CONCLUSIONS: This study pioneers the use of passively collected data (eg, smart plugs) for mental health monitoring in older survivors of cancer, demonstrating their potential. Smart plugs capture behavioral patterns without user burden, with reasonable standalone performance (mean AUC 0.71, SD 0.06), positioning them as a promising low-burden modality. Future work should validate findings in larger independent cohorts and in prospective clinical workflows. Such technologies could transform monitoring for vulnerable populations, enabling scalable, inclusive care while reducing health care burdens.
14 June 2026
Read appraisal →Journal of medical Internet research
Experiences of Home-Dwelling Older Adults and Their Family Caregivers With Digital Health Services: Qualitative Study
BACKGROUND: As the population ages, demand for health services among older adults and caregivers increases. Digital health services help meet this demand. However, acceptance and experiences differ between older adults and caregivers. OBJECTIVE: This study aims to explore the specific experiences of home-dwelling older adults and their caregivers with digital health services, identify their willingness to use these services and the factors influencing their adoption, and identify their service needs to inform the subsequent design and optimization of digital health products and services. METHODS: From December 2023 to February 2024, a descriptive qualitative study was conducted. Researchers used purposive and maximum variation sampling to recruit 18 home-dwelling older adults and 17 family caregivers, including 10 matched dyads. Participants came from 7 community health service centers and a tertiary hospital in Hefei, China. Open-ended, semistructured, face-to-face interviews were conducted separately. Data were analyzed using conventional content analysis. RESULTS: Four main themes emerged. The first were the application characteristics, including usage situations and preferred functions. The second theme described specific service experiences, both positive and negative. The third was the influencing factors. Promoting factors included health needs, user experience, and subjective norms. Obstructive factors differed between groups and included low digital literacy, weak economic foundation, service security concerns, and lack of time. The fourth theme covered suggestions and expectations for improvement. Older adults appreciated the advantages but often had suboptimal experiences due to complex designs and threats to personal dignity. Conversely, caregivers valued efficiency but reported low use, hindered by time constraints and concerns about privacy and safety. CONCLUSIONS: This study reveals a critical gap between the potential and actual use of digital health services. Older adults face barriers with usability and digital literacy. Caregivers struggle to integrate these services and have trust issues. Future optimization requires action at several levels. Government support is needed through policies, authoritative platforms, and subsidies. Service providers should offer age-friendly, personalized design, and continuous support. Social support systems are also essential, such as digital reciprocity from family and peer help. These strategies are critical for enhancing user experience, bridging the digital divide, and enabling both older adults and their caregivers to fully benefit from digital health technologies.
14 June 2026
Read appraisal →Family practice
Current state of electronic problems lists in primary care: a rapid scoping review
BACKGROUND: Electronic problem lists (PLs) are central to the problem-oriented medical record and increasingly underpin clinical decision support (CDS), interoperability, and emerging artificial intelligence applications in primary care. However, persistent concerns regarding PL accuracy, completeness, and governance limit their clinical value. OBJECTIVE: To update the foundational framework proposed by Hodge and Narus by synthesizing contemporary evidence on electronic PLs in primary care and primary care-relevant settings. METHODS: We conducted a rapid scoping review following Joanna Briggs Institute guidance and PRISMA-ScR reporting standards. MEDLINE (Ovid) was searched for peer-reviewed studies published between March 2016 and May 2026. Eligible studies examined digital PLs or extractable PL-related practices relevant to primary care. Findings were synthesized using a hybrid inductive-deductive approach and mapped to the seven Hodge and Narus themes. RESULTS: A total of 103 studies were included. Across settings, PLs were widely recognized as foundational for longitudinal care, safety, and coordination. However, incomplete, outdated, or inconsistently maintained PLs remained common. Persistent challenges included unclear ownership, workflow misalignment, and variability in what constitutes a "problem." Emerging technologies-including CDS, natural language processing, and machine learning-were increasingly used to support PL generation, curation, reconciliation, and organization, with greatest benefit when embedded within clinician-led workflows. CONCLUSION: Despite technological advances, the clinical value of electronic PLs in primary care continues to depend on governance, workflow integration, and shared accountability. Updating the Hodge and Narus framework highlights the need for sociotechnical approaches to PL improvement as PLs become integral to CDS and artificial intelligence-enabled care. Problem lists (PL) are a key part of electronic health records. They provide clinicians with a quick overview of a patient's important health issues—such as long-term conditions, past diagnoses, and current concerns—and help support safe and informed care. When PLs are accurate and up to date, they can improve communication and decision-making. However, in everyday clinical practice, many PLs are incomplete, outdated, or difficult to maintain. As electronic health records are increasingly used to support clinical decision support tools and new digital technologies, the quality of PLs has become more important than ever. Poor-quality PLs can lead to missed information, duplicated work, or unsafe care decisions. To better understand how PLs are working in modern healthcare, we conducted a rapid scoping review of research published between 2016 and 2026. We examined studies that looked at how PLs are used, how accurate they are, what challenges clinicians face in keeping them updated, and what solutions have been proposed. In total, 103 studies were included. Across these studies, several common problems were identified. Important health conditions were often missing or out of date, and clinicians were frequently unsure who was responsible for updating the PL. Time pressures and busy clinical workflows made regular maintenance difficult. Some studies explored new digital tools, such as automated text analysis, to help identify or update problems, but these approaches are still developing and require careful evaluation. Improving PLs will require clearer standards, shared responsibility among healthcare teams, and EHRs that make updating information easier. Thoughtful use of new technologies may also help reduce clinician workload while improving patient safety. This review highlights where PLs are working well and where improvements are still needed, offering guidance for future research, technology design, and improvements in primary care practice.
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 →JMIR cardio
Experiences of Patients With Atrial Fibrillation Using Technology to Personalize Self-Care Decision-Making: Interpretive Description Study
BACKGROUND: Atrial fibrillation (AF) is the most common sustained heart rhythm disorder and is a challenging chronic disease to manage. Patients' daily self-care decisions are associated with improved AF outcomes, quality of life, and decreased hospital use and cost. However, many patients find these real-world or naturalistic decisions difficult, often because of their inherent complexity and ambiguity, coupled with the uncertainty of AF. Intervention research using technology to support AF self-care has largely emphasized making decisions with clinicians. Patients with AF are increasingly using consumer technology; yet, little is known about the use of technology by patients with AF in independent self-care decision-making. Addressing this gap will facilitate developing interventions that better leverage technology to enhance patients' naturalistic decision-making. OBJECTIVE: This study aimed to explore the experiences of older adult patients in using technology to support self-care decision-making. METHODS: Following an interpretive descriptive qualitative approach, older adult patients with AF were recruited from 3 specialty heart function clinics in a Western Canadian province to participate in 1 of 6 facilitated virtual focus groups for 1.5 hours. Patients were asked about their self-care decision-making since AF diagnosis, their AF-specific technology use and its use in making self-care decisions, their technology motivations, benefits, constraints, and other possibilities for use. Inductive thematic analysis was used to code the transcribed data, moving from open coding to clustering of common codes into categories, looking for patterns of meaning between and across categories to iteratively arrive at main themes and subthemes. RESULTS: Thirty patients (n=15, 50% women) with AF (mean age, 73, SD 5.7 years; range 63-85 years) participated in the focus groups. Participants' experiences of using technology to make daily self-care decisions were highly variable but centered on its personalized use to meet their individualized needs, preferences, and life context. The personalizing process of technology use in decision-making was characterized by three themes: (1) beginning technology use in their own times and ways, during their AF trajectory-pre-, at the time, at some point AF post diagnosis, and could be either self-initiated and/or provider recommended or influenced; (2) developing patterns of AF self-care decision-making using technology, including establishing their personal baseline, keeping out of the danger zone, watchful waiting, and seeking decision-making support; and (3) finding the place for technology in normalizing daily life, either settling on or limiting its use to normalize life. CONCLUSIONS: Findings expand understandings of naturalistic decision-making by elucidating the personalized process of technology use in AF self-care.
13 June 2026
Read appraisal →JMIR formative research
User Perspectives on a Clinical Decision Tool to Support Individualized Exercise Prescriptions for Breast Cancer Survivors Not Meeting Exercise Guidelines: Cross-Sectional Survey
BACKGROUND: More than 80% of breast cancer survivors do not meet the recommended levels of exercise, and <50% of health care providers promote exercise as part of survivorship care. Patient-provider communication may enhance exercise engagement by increasing patients' understanding of exercise benefits and linking patients to resources, such as rehabilitation and exercise programs. OBJECTIVE: This study aimed to explore perspectives on a novel clinical decision tool designed to support individualized exercise discussions and prescriptions among breast cancer survivors who do not meet exercise guidelines and health care providers who primarily treat such survivors. METHODS: We conducted a cross-sectional online survey among US breast cancer survivors and health care providers. Participants were (1) female breast cancer survivors aged ≥35 years engaging in ≤150 minutes/week of moderate-intensity aerobic exercise or ≤2 days/week of muscle-strengthening exercise and (2) health care providers who had cared for breast cancer survivors within the past 12 months and reported below-average guideline adherence among their patients. Respondents reviewed a paper draft of a web-based clinical decision prototype tool for supporting individualized exercise discussions and prescriptions based on patients' demographic, clinical, and contextual characteristics. We assessed perceived usefulness, potential uses (eg, counseling), preferred timing of access within clinical encounters, and preferences for tool characteristics (inputs/outputs). RESULTS: The analytic sample comprised 26 breast cancer survivors and 69 health care providers. The survivors' median age was 48 (IQR 37-65) years. Providers included patient navigators/social workers/nurses (29/69, 42.0%), breast oncologists (13/69, 18.8%), and occupational/physical therapists (12/69, 17.4%). The majority of providers (62/69, 89.9%, 95% CI 80.2%-95.8%) and survivors (23/26, 88.5%, 95% CI 69.8%-97.6%) reported that they would find the tool useful. Similarly, 85.5% of providers (59/69, 95% CI 75.0%-92.8%) and 84.6% of survivors (22/26, 95% CI 65.1%-95.6%) reported that the tool would increase their confidence to discuss exercise in a clinical setting. Both groups preferred that survivors access the tool with staff after a medical appointment (survivors: 20/26, 76.9%, 95% CI 56.4%-91.0%; providers: 58/67, 86.6%, 95% CI 76.0%-93.7%). Both groups also endorsed treatment history and readiness to exercise to consider as key inputs and improved quality of life and reduced treatment-related side effects as exercise benefits to communicate as tool outputs. CONCLUSIONS: The prototype tool concept was well received, with high endorsement of individual characteristics to consider and clinical benefits of exercise to communicate. Findings will inform refinement of the tool and future implementation testing in an understudied population of breast cancer survivors.
11 June 2026
Read appraisal →BMJ open
Can digital self-screening improve identification of chronic dyspnoea in Australian general practice? A proof-of-concept protocol for the BREATHE SMART trial.
INTRODUCTION: Chronic dyspnoea is a prevalent and clinically significant symptom, often indicative of underlying cardiorespiratory disease. It is frequently under-reported by patients and under-recognised in primary care, with these challenges exacerbated in rural and remote communities where disease burden is greater and patients experience barriers to timely diagnosis and management. The BREATHE SMART trial aims to implement and evaluate an innovative, fully digital self-screening system for chronic dyspnoea, integrated into general practice workflows and information technology infrastructure. This approach seeks to enhance early detection and management of chronic cardiorespiratory conditions across diverse practice settings. METHODS AND ANALYSIS: This multisite proof-of-concept study will test a software platform delivering a preconsultation self-screening questionnaire across 40 general practices in urban, rural and remote Australia. The system identifies eligible patients (≥18 years, consenting to SMS communication with their practice), issues an automated SMS that administers a validated dyspnoea screening questionnaire, and summarises responses for integration into the electronic medical record. Process evaluation will assess acceptability and utility using deidentified audit data, software metrics and qualitative feedback from patients, staff and general practitioners (GPs) via surveys, interviews and focus groups. Approximately 12 000 patients will be screened over 12 months. Primary outcomes will include the proportion completing self-screening and prevalence of chronic dyspnoea and secondary outcomes will include the rate of newly diagnosed chronic dyspnoea-related conditions (ie, asthma, chronic obstructive pulmonary disease and heart failure) in the preceding 12 months and during the intervention period. ETHICS AND DISSEMINATION: Ethics approval was granted by the University of New South Wales Human Research Ethics Committee (HREC) (iRECS6645) and the University of Notre Dame Australia HREC (2024-155). Participating practices and each GP will provide written, informed consent. All patients being screened will provide electronic informed consent. Results of the study will be disseminated through various forums, including peer-reviewed publications and presentation at national and international conferences. Following the study, participating practices will be provided with a summary of the findings of the study, together with a full copy of any publications and a plain language statement for participants, which will be made available in the practices. TRIAL REGISTRATION NUMBER: ACTRN12624001451594.
1 June 2026
Read appraisal →BMC health services research
Does an app make patients happy? Impact of a novel medical history app on patient satisfaction in urgent care consultations in Germany: cluster-randomized interventional trial 'DASI'.
BACKGROUND: Patient satisfaction is an important indicator of healthcare quality. However, time constraints in primary care limit effective communication and history-taking. Digital medical history systems have the potential to improve the quality of medical consultations by enabling patient preparation and providing physicians with comprehensive pre-consultation information. This study aimed to evaluate the impact of a novel medical history-taking app (DASI app) on patient satisfaction in out-of-hours practices (OOHP) in Germany. METHODS: We conducted a two-center, cluster-randomized trial over 12 months. Within each practice, weeks were randomized to either an intervention or control group, resulting in a cluster-randomized trial (CRT) with clustering in weeks within the same practice. Patients either used the DASI app before consultations (intervention group) or received standard care (control group). The DASI app is a patient-facing tool that guides patients through a dynamic questionnaire adapted to the selected complaints and previous answers. Patient satisfaction was measured using 17 items from the EUROPEP instrument covering relation and communication, medical care, and information and support. Additionally, we collected sociodemographic data. Statistical analyses included Mann-Whitney U tests for individual items and t-tests for domain scores. Analyses were performed with R, version 4.5.2. RESULTS: Among 1,460 approached patients, 1,040 (71%) were enrolled and 1,034 included in analyses. Patient median age was 31 years, with 60% female participants. Patients in the intervention group (n = 496) showed significantly better ratings in 12 of 17 EUROPEP items compared to controls (n = 538) and demonstrated significantly higher satisfaction across all three EUROPEP domains. Between 78 and 96% of patients rated care as excellent or very good, with intervention group patients more likely to select top-level evaluations in 9 of 17 items. CONCLUSIONS: Digital medical history taking significantly enhanced patient satisfaction in urgent care settings. The app likely improved satisfaction through multiple pathways including increased patient empowerment, better consultation preparation, and more efficient physician-patient interactions. These findings demonstrate that user-friendly digital tools can meaningfully enhance patient experience without disrupting existing workflows, supporting healthcare digitalization efforts while maintaining high-quality patient-centered care. TRAIL REGISTRATION: German register for clinical trials (DRKS00026659; date of registration: 2021-11-03).
1 June 2026
Read appraisal →BMJ open
Patterns and determinants of primary care virtual health service use among rural Aboriginal and Torres Strait Islander adults with chronic diseases: a cross-sectional study
OBJECTIVE: To examine virtual health service (VHS) device usage patterns and identify factors associated with VHS engagement among Indigenous Australian adults with chronic conditions. DESIGN: Cross-sectional survey. SETTING: An Aboriginal Community Controlled Health Organisation providing primary healthcare services across rural and remote Queensland, Australia. PARTICIPANTS: 74 consenting Indigenous Australian adults with at least one chronic condition who were registered VHS users. METHODS: Participants completed surveys assessing their use of four Bluetooth-enabled monitoring devices (pulse oximeter, blood glucose monitor, blood pressure monitor, weight scale) over a 2-week recall period. The primary outcome was VHS device usage status, categorised as active versus inactive users. Active users were defined as participants who reported any frequency of device use, while those reporting no use were classified as inactive users. All participants had access to Indigenous health coach support as part of the VHS model. Binary logistic regression was used to identify sociodemographic and geographical factors associated with VHS engagement. RESULTS: Sixty-four per cent (n=47) were active users, with 73% of these using all four devices concurrently. Among active users, blood pressure monitors showed the highest utilisation (98%), followed by weight scales (91%), blood glucose monitors (89%) and pulse oximeters (86%). Three factors were significantly associated with VHS usage using binary logistic regression: residing in medium rural towns (adjusted OR 4.71, 95% CI 1.23 to 17.94, p=0.02), age 18-65 years (adjusted OR 3.59, 95% CI 1.05 to 12.22, p=0.04) and having multiple chronic conditions (adjusted OR 10.95, 95% CI 1.25 to 95.87, p=0.03) compared with those in more remote areas, aged ≥66 years and with single condition, respectively. CONCLUSION: Indigenous-led VHS achieve substantial engagement through culturally grounded health coach support. However, addressing digital connectivity in remote areas, age-appropriate support for older adults and Indigenous workforce development is essential to ensure equitable access and sustained engagement.
31 May 2026
Read appraisal →PloS one
Effect of digitizing Community Health Information System on the delivery and use of maternal and child health services: Propensity score matching analysis
INTRODUCTION: In 2018, Ethiopia's government digitized its Community Health Information System (eCHIS) to enhance Health Extension Program service delivery. However, the impact of eCHIS on health outcomes remains unclear. This study, therefore, examined the effects of eCHIS on the uptake of maternal and child health services. METHODS: A post-test-only, non-equivalent group household survey design was used, collecting data from July to August 2024 in rural communities with and without eCHIS. A stratified multistage sampling technique was employed to recruit respondents. A sample of 1,728 women of reproductive age (271 in eCHIS and 1,457 in non-eCHIS woredas), 1,118 women with children ages 0-11 months (188 in eCHIS and 930 in non-eCHIS), and 569 women with children ages 12-23 months (301 in eCHIS and 268 in non-eCHIS) were included in this study. Propensity scores were used to match intervention and comparison communities based on women's age, religion, parity, education, household wealth, distance to health facilities, and autonomy. A modified Poisson regression analysis, adjusting for covariates, was conducted to estimate the adjusted prevalence ratios (PR) for maternal and child health outcomes. RESULTS: Modern contraceptive use was 66% in intervention areas versus 56% in comparison areas. Institutional delivery rates were 95% in intervention and 79% in comparison areas. In intervention areas, 94% of children received the first dose of the Pentavalent vaccine compared to 83% in comparison areas, while 85% and 68%, respectively, received the third dose. Adjusted analyses showed that eCHIS intervention areas had statistically significant increases in contraceptive use (13.0 percentage points; PR: 1.25; p-value < 0.01) and institutional deliveries (8.9 percentage points; PR: 1.18; p-value < 0.01) compared to comparison areas. Similarly, the average treatment effect of eCHIS on Pentavalent 1, Pentavalent 3, and full vaccination coverage showed significant increases of 10.3 (PR: 1.13; p-value < 0.01), 13.6 (PR: 1.26; p-value < 0.01), and 14.6 (PR: 1.36; p-value < 0.01) percentage points, respectively. CONCLUSION: This study underscores the transformative potential of eCHIS in improving maternal and child health outcomes in Ethiopia. Sustained investment in digital health systems can help scale effective health care services to rural and underserved communities.
31 May 2026
Read appraisal →BMJ open
Impacts of human and digital scribes on improving physician wellness and reducing administrative burden: a scoping review protocol
INTRODUCTION: The rise in administrative burden on physicians is becoming increasingly recognised as a significant contributor to burnout and job dissatisfaction among primary care practitioners. Human scribes (HS) and digital/artificial intelligence scribes (DS) have emerged as potential tools to reduce clerical workload and improve physician well-being. There has been extensive research conducted on HS, and DS show promise but require validation across diverse healthcare settings. This scoping review aims to assess the effects of HS and DS in primary care settings to evaluate their impact on administrative work, job satisfaction, burnout and clinical operational efficiency. METHODS AND ANALYSIS: This review will follow the Arksey and O'Malley framework with enhancements from Levac et al, along with Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) reporting guidelines. A comprehensive search strategy was developed, including Ovid MEDLINE, Ovid Embase and Scopus databases in June 2025 with an academic health sciences librarian. Database searches will be conducted between March and June 2026. The inclusion criteria consist of empirical research on licensed physicians in primary care settings that implement HS or DS systems and measure physician-related outcomes. Two researchers will review and extract data independently using Covidence. The results will be analysed through thematic methods followed by descriptive summarisation. ETHICS AND DISSEMINATION: This review conducts an analysis of existing publications without needing ethical clearance. Findings will be disseminated through peer-reviewed publications and presented at academic conferences where possible. The research team will make supporting materials accessible via the Open Science Framework. TRIAL REGISTRATION NUMBER: https://doi.org/10.17605/OSF.IO/T5BHY.
31 May 2026
Read appraisal →The British journal of general practice : the journal of the Royal College of General Practitioners
General practice incentives: a review of the international literature.
BACKGROUND: In Australia, the general practice sector faces significant challenges, leading to a re-evaluation of its predominantly fee-for-service (FFS) funding models. AIM: To conduct a systematic review of reviews that evaluated the efficacy of funding models in general practice on quality outcomes in multidisciplinary primary and preventive care for people with complex chronic conditions, as well as the contextual factors that have influenced their implementation. DESIGN AND SETTING: Only systematic reviews and meta-analyses were included. Search terms covered funding mechanisms, primary care, and general practice. The review followed PRISMA guidelines for systematic reviews. METHOD: PubMed, Cochrane, Embase, CINAHL, PsycInfo, PAIS, and Web of Science databases were searched in November 2023 for publications from 2010 onwards. RESULTS: Twenty reviews were included. Blended payment models incorporating pay-for-performance (P4P) with either capitation payments or FFS were associated with small improvements in quality outcomes, particularly in multidisciplinary settings. Changes in intermediate health outcomes and process measures for people with complex chronic conditions were most evident in diabetes care but inconclusive for other health outcomes and conditions. Improvements were mainly observed in incentivised activities and in less rigorously designed studies, with ceiling effects and variation reported across healthcare systems. There was no evidence that introducing capitation payments as part of blended payments improved quality of care. CONCLUSION: Although blended payment models show promise, evidence for the effectiveness of models including P4P is highly variable. If adopted, careful evaluation of each incentive's impact on both quality and equity will be essential.
31 May 2026
Read appraisal →JMIR formative research
Real-World Implementation of EndoConnect in Brazilian Primary Care: Formative Study of Usability, Engagement, and Equity in Digital Endometriosis Care
BACKGROUND: Endometriosis is a chronic gynecological condition affecting approximately 10% of women of reproductive age worldwide and is associated with chronic pelvic pain, infertility, and reduced quality of life. In Brazil's Unified Health System (Sistema Único de Saúde [SUS]), diagnostic delays frequently range from 7 to 10 years and disproportionately affect socially vulnerable populations, including rural, low-income, Black, and Indigenous women. Digital health interventions have been proposed as scalable solutions; however, most available applications are developed in high-income settings and do not align with the structural and operational realities of low- and middle-income countries (LMICs). OBJECTIVE: This study aimed to evaluate feasibility, usability, acceptability, and user engagement associated with the real-world implementation of EndoConnect Alpha in primary health care settings, and to explore preliminary patterns of change in symptom burden, knowledge, and care navigation. METHODS: A single-arm, prospective, formative implementation study was conducted in 10 primary health care units in Ceará, Brazil. A convenience sample of 60 participants, including women with suspected or confirmed endometriosis and primary care professionals, used the platform over an 8-week period under real-world conditions. Usability (assessed using the System Usability Scale), acceptability (assessed using the Technology Acceptance Model), engagement metrics, and exploratory outcomes were assessed. All analyses were exploratory, with no control group and no causal inference. RESULTS: High usability and acceptability were observed, with strong user engagement, including a 79% completion rate of educational modules and consistent platform use. Observed decreases in pelvic pain and anxiety were identified, alongside increases in disease-related knowledge, self-reported therapy adherence, and reported gynecological referrals. A positive association between usability and acceptability was also observed. These findings should be interpreted as exploratory signals given the study design. Descriptive subgroup analyses suggested more pronounced trends among rural participants and those with a lower education level. CONCLUSIONS: The real-world implementation of EndoConnect Alpha demonstrated high feasibility, usability, and acceptability within a public primary care setting in a middle-income country. Observed trends suggest potential benefits, particularly among underserved populations; however, causal inference cannot be established. These findings support further controlled evaluation and highlight the relevance of equity-oriented digital health strategies tailored to LMIC contexts.
30 May 2026
Read appraisal →PLoS neglected tropical diseases
Feasibility study of an AI-powered mobile app to support cutaneous leishmaniasis diagnosis in the Brazilian Amazon
BACKGROUND: Cutaneous leishmaniasis (CL) remains a major public health challenge, especially in Brazil's Amazon, where environmental and economic pressures sustain transmission. Delayed diagnosis drives morbidity, stigma, and costs. Community health workers are pivotal yet under-equipped for early triage. Artificial intelligence, effective in dermatologic imaging, is underused for CL; feasible, offline clinical tools could accelerate referral and timely care. This study aimed to evaluate the feasibility of an AI-assisted tool for early CL triage in the Brazilian Amazon by: (i) developing an AI model for CL identification from clinical skin lesion images; (ii) integrating the model into an offline-optimized mobile application for resource-limited settings; and (iii) conducting initial, real-world clinical validation. METHODS: Exploratory, IRB-approved feasibility study. Retrospective images from Brazilian Amazon sites informed a two-stage AI pipeline (lesion segmentation+classification) integrated into an offline mobile app. Multicenter validation in ideal- and real-world scenarios. Primary metric AUC-ROC; secondary sensitivity/specificity. One-sided tests: AUC-ROC [Formula: see text]0.70; ideal-world sensitivity [Formula: see text]0.75. RESULTS: For the Classification Model, 64 images were assigned to the test set while 1,160 were used for training and validation (80:20 split), with DenseNet121 yielding the highest accuracy of 0.88. The full AI pipeline (Segmentation and Classification models) achieved an accuracy of 0.81, an F1-score of 0.80, an AUC-ROC of 0.90, and a sensitivity of 0.76. In the ideal-world analysis, sensitivity reached 0.92, the F1-score was 0.84, and specificity was 0.42. CONCLUSIONS: We demonstrate the feasibility of an offline, AI-assisted mobile tool to support triage and referral for cutaneous leishmaniasis in the Brazilian Amazon. Performance reflects preliminary, descriptive point estimates from an initial diagnostic accuracy assessment and should be interpreted with caution; the tool is not intended for standalone diagnosis. Next steps include prospectively powered clinical validation, usability refinements, and regulatory evaluation, including alignment with ANVISA requirements in Brazil. Overall, this work represents an initial step toward closing the gap in clinically supported diagnostic tools for neglected tropical diseases in resource-constrained settings.
30 May 2026
Read appraisal →JMIR aging
Developing Customized Personas to Capture Intrinsic Capacity Profiles and Digital Monitoring Intentions in Older Adults: Mixed Methods Study
BACKGROUND: Integrated Care for Older People (ICOPE), focused on monitoring and optimizing the intrinsic capacity (IC) of older adults, is a new model of geriatric care that is currently being accelerated globally. Digital health technologies are recommended for longitudinal IC monitoring to provide precise and timely interventions. However, little is known about the psychological intentions of engaging in digital monitoring of IC according to the profile heterogeneity of IC among older adults. OBJECTIVE: This study aims to map a set of customized personas to capture the profiles of IC and match psychological intentions that support personalized digital IC monitoring. METHODS: An explanatory sequential mixed methods study was conducted at 16 sites in Beijing, China. Older adults aged ≥60 years (n=481) were selected to complete the quantitative survey. Latent profile analysis, descriptive statistics, and logistic regression analyses were performed to cluster subgroups using Mplus (Muthén & Muthén) and SPSS (IBM Corp). A subsample of participants from each profile (n=25) was purposively sampled for semistructured interviews. An inductive-deductive content analysis was used to identify similar attributes and to affirm the personas gradually. A joint statistical and thematic visualization method was used to integrate the customized personas. RESULTS: Three profiles of IC patterns emerged: "multisubdomain decline-IC imbalance group," "multisubdomain moderate-sensory deficit group," and "multisubdomain robust-whole balance group." The distribution of latent profiles was influenced by age, education, monthly per capita household income, self-rated health, and number of chronic diseases, while positively impacting older adults' functional ability. The following customized personas were captured regarding established themes: "affects my mood-anxious evader," characterized by avoidance and anxiety, low digital interest, and perceived social isolation; "capitalize on what comes-accommodative adopter," pragmatically oriented toward disease detection, with moderate digital openness but limited self-efficacy; and "more autonomy-active improver," who exhibited proactive engagement, high digital literacy, and motivation rooted in self-management and social participation. CONCLUSIONS: This study is the first to integrate latent profile analysis with customized qualitative personas to link the heterogeneity of IC with the psychological intentions underlying digital monitoring. The resulting personas model provides an actionable framework for tailoring digital IC monitoring strategies in community-based integrated care. The findings emphasize the need to align monitoring approaches with older adults' IC characteristics, psychological readiness, digital literacy, and social support to enhance engagement in digital IC monitoring.
29 May 2026
Read appraisal →JMIR formative research
Self-Monitoring Risk Factors for Diabetic Foot Ulceration With the Feetchecker App: Mixed Methods Study
BACKGROUND: A prevalent and serious complication of diabetes mellitus is the development of diabetic foot ulcer (DFU). There is a need for effective solutions that help prevent DFU to support our increasingly stressed health care systems. The use of mobile health (mHealth) tools has been shown to improve awareness and effective self-care management skills in people at risk of developing diabetic foot ulceration. OBJECTIVE: In this study, we aimed to investigate the perceived usefulness, engagement, and overall user experience of the Feetchecker app, a self-monitoring mHealth app for people at risk of DFU. METHODS: A total of 24 patients (mean age 71, SD 8.6 years) with type 2 diabetes mellitus at risk of developing diabetic foot ulceration completed a 3-month evaluation period (70 recruited, 36 included, 12 dropped out) of a self-monitoring mobile app called Feetchecker app. A mixed methods approach was used to combine insights from app data with qualitative data from a pre- and postsurvey as well as interviews with patients and involved podiatrists. Data were analyzed using descriptive statistics and thematic analysis. We evaluated overall use of the app, patient engagement, and user experiences. RESULTS: Patients who fully completed the study conducted 393 feetchecks. In total, 7 patients sent in 9 pictures; all 7 were called for follow-up by a podiatrist. Overall, patients had a positive experience with the app and perceived the Feetchecker app as a valuable tool to monitor their feet for potential risk factors of DFU. Ease of use in performing a feetcheck and sending the podiatrist a picture was described as an important feature. Three main types of engagement with the Feetchecker app emerged: continuous, frequent, and no to little engagement. These patterns highlight enablers for self-monitoring such as ease-of-use, easy access to a podiatrist, and social support, as well as barriers such as digital skills and sustained engagement. Podiatrists highlighted the benefits of having patients report potential issues quicker and the ability to monitor their patients remotely. Challenges remain in integrating the promotion of the Feetchecker app into their consultations. CONCLUSIONS: The Feetchecker app supported patients in self-monitoring risk factors associated with DFU through routine checks and quick contact with a health care professional in case of a potential issue. Overall, patients described a positive user experience and considered the app helpful. While mHealth tools are not for everyone, user engagement for many patients was high and shows that such apps can offer support for people able to use them. Future research should focus on improving usability and engagement with the app as well as extend the way patients can communicate with health care professionals beyond a picture.
29 May 2026
Read appraisal →JMIR research protocols
Evaluating the Effectiveness of an Enhanced Early Childhood Development Program Integrated Into Primary Health Care in China: Protocol for a Cluster Randomized Controlled Trial
BACKGROUND: Early childhood development (ECD) programs refer to policies and programs aimed at protecting young children's rights to achieve their full potential. Parenting interventions are effective at improving children's cognitive development and overall well-being. However, there is limited evidence on how to effectively implement and integrate such programs into routine service delivery at scale. The Government of China launched the ECD program in 2013 and the ECD scale-up program in 2023. OBJECTIVE: Our study aims to design, implement, and evaluate an enhanced ECD program embedded in the primary health care system in order to provide ECD policy recommendations for future national scale-up. METHODS: This study involves a multicenter cluster randomized controlled superiority trial in 3 counties with different levels of socioeconomic development in China. Fifty-eight clusters will be randomly assigned in a 1:1 ratio to intervention and control groups, stratified by county. In each cluster, 18 families with children aged 6-23 months will be recruited. Our intervention aims to implement an enhanced ECD program in primary care facilities. Intervention group participants will receive usual care alongside enhanced ECD services, including improved facilities, capacity building, and improved ECD services (age-adapted clinical consultations on nutrition and stimulation, age-specific parenting group sessions, home visits, and referrals for children in need). Moreover, an electronic data platform will be used. Control group participants will receive usual care. Our primary outcome is children's overall development, as measured by the Global Scale of Early Development combined form at 12 months of follow-up. Evaluation data will be collected in both arms. Additionally, a process evaluation and an incremental cost-effectiveness analysis will be conducted. Primary analysis will follow the intention-to-treat principle, and it will use generalized estimating equations to assess the population average intervention effect, with adjustment for corresponding baseline outcomes, selected individual variables, county, cluster variables, and variables differing at baseline. Qualitative data will be collected through semistructured interviews and focus groups, guided by the Capability, Opportunity, Motivation, and Behavior framework to explore implementation-related factors. Data will be transcribed for analysis using NVivo 14 (Lumivero). Ethical approval has been obtained from the Institutional Review Board of Shanghai Children's Medical Center Affiliated to Shanghai Jiao Tong University School of Medicine. RESULTS: This study was funded in 2023 and registered in April 2024. The recruitment of 1044 participants was completed on September 14, 2024. Data collection was completed on January 31, 2026. CONCLUSIONS: We aim to design an enhanced ECD service delivery model that can be embedded into the routine primary health care system. The study findings will guide government policies and reforms for strengthening the health system to scale up ECD services. Furthermore, this project may provide policy evidence to support countries in establishing or expanding their ECD services.
29 May 2026
Read appraisal →Journal of medical Internet research
Rerouting Eye Care: How AI and Telemedicine Are Reshaping Ophthalmology Patient Journeys in the United Kingdom and Germany
Artificial intelligence (AI) as a medical device is now progressively entering routine ophthalmic care, yet its impact is still mostly evaluated in terms of diagnostic performance rather than how it reshapes patient care pathways. This viewpoint argues that careful pathway design is crucial to implementing AI in ophthalmology so that it translates into real, practical benefits for patients and services. We propose a framework that classifies AI- and telemedicine-enabled eye care pathways by the initial point of contact and the role of AI: from direct human assessment to grader- or telemedicine-based use to AI-first contact and fully autonomous AI gatekeeping. We apply this framework to 2 contrasting health systems, the United Kingdom and Germany, focusing on common retinal diseases and cardiovascular risk assessment from retinal images. In the United Kingdom, AI is being introduced mainly as a modular upgrade to standardized programs layered onto a gatekeeper model centered on community optometrists and general practitioners. In Germany, direct access to office-based ophthalmologists, opportunistic screening, and commercial retail offerings are producing more fragmented clinician- and market-driven AI adoption. Our comparison shows that the same AI technologies can generate very different patient journeys across health systems. Therefore, their value depends not only on diagnostic performance but also on intentional pathway design, including clear escalation rules and structured information transfer. This includes appropriate task shifting from ophthalmologists to trained staff or new roles, such as image grading, tele-ophthalmology triage, or pathway management. Without such design, AI risks duplicate testing, incomplete or poorly coordinated referrals, and further fragmentation of care.
29 May 2026
Read appraisal →European respiratory review : an official journal of the European Respiratory Society
The evolution of scientific knowledge in childhood asthma over time
Paediatric asthma management has undergone a significant transformation from rudimentary assessments in the early 20th century to sophisticated diagnostic and therapeutic approaches today. Early clinical observations lacked paediatric specificity, but mid-20th-century studies introduced functional assessments, spirometry and recognition of asthma as a chronic inflammatory condition. The introduction of inhaled corticosteroids transformed long-term management, offering targeted control with reduced systemic risks. Advances in noninvasive diagnostics, such as fractional exhaled nitric oxide, induced sputum analysis, exhaled breath condensate and electronic nose technology, have improved inflammation monitoring, phenotype classification and therapeutic responsiveness. The integration of omics technologies, i.e. genomics, proteomics and metabolomics, has enabled deeper insights into disease mechanisms and facilitated early, individualised interventions. Concurrently, artificial intelligence (AI) and machine learning are emerging as tools for predicting exacerbations, identifying clinical subtypes and enhancing decision-making through large-scale data integration. Despite these advancements, challenges remain around standardisation, data quality and ensuring equitable access. This narrative review synthesises decades of progress in paediatric asthma care, emphasising the transition from empirical treatment to personalised, biomarker-driven strategies. It highlights current gaps, particularly in algorithm transparency, paediatric-specific validation and holistic care integration. As asthma management enters an era of digital health and AI-assisted precision medicine, future success will depend on interdisciplinary collaboration, real-world validation and policies that close care disparities.
29 May 2026
Read appraisal →Journal of medical Internet research
Artificial Intelligence in Patient-Centered Care and Macro-, Meso-, and Micro-Level Determinants of Rehumanization and Dehumanization: Qualitative Interview Study
BACKGROUND: Patient-centered care remains a foundational principle of modern health care. The digital transformation of health systems has accelerated the adoption of artificial intelligence (AI) across diagnostic, predictive, and communicative functions, with implications for efficiency and clinical workflows. At the same time, AI integration raises concerns regarding transparency, equity, accountability, and trust, positioning it as a potential driver of both rehumanizing and dehumanizing dynamics in health care practice. OBJECTIVE: This study examines how the adoption of AI in health care may influence patient-centered care, exploring its potential to promote rehumanization or contribute to dehumanization. The objective is to identify the factors that shape these outcomes at the macrolevel (policy and infrastructure), mesolevel (institutional practices), and microlevel (individual behaviors and interactions). METHODS: This study adopts an exploratory qualitative design informed by grounded theory principles, drawing on 20 semistructured interviews with health care leaders, clinicians, researchers, legal experts, and industry consultants who have substantial professional experience across European health care systems, with some participants also contributing experience from the US health care context. To enhance analytical rigor and transparency, the study applied the Gioia methodology, enabling inductive coding from first-order concepts to second-order themes and aggregate dimensions. This multistakeholder approach facilitated a nuanced examination of how AI integration is perceived and experienced across macro-, meso-, and microlevels of health care. RESULTS: The analysis identified key system-level factors shaping rehumanizing or dehumanizing outcomes of AI integration. At the macrolevel, 8 factors-including regulatory frameworks, policy priorities, and infrastructure-were identified as influencing whether efficiency pressures outweigh patient-centered values. At the mesolevel, 5 factors related to institutional strategies, workflows, and leadership shape how AI tools are embedded into care delivery. At the microlevel, 7 factors related to individual behaviors, trust, and doctor-patient interaction dynamics influence whether AI supports empathy and engagement or diminishes them. Rehumanizing potentials include reduced administrative burden, improved care pathways, clearer health communication, and enhanced decision-making, while risks include shorter consultations, reduced empathy, overreliance on automation, and erosion of professional identity. Without deliberate alignment with patient-centered principles, efficiency gains risk undermining the human dimensions of care. CONCLUSIONS: This study represents one of the first empirical examinations of how AI shapes health care practices through rehumanizing and dehumanizing dynamics. The findings demonstrate that outcomes depend not only on technical capabilities but also on regulatory frameworks, institutional strategies, and cultural adaptation. By systematically mapping influencing factors across macro-, meso-, and microlevels, the research provides actionable insights for decision-makers to ensure that efficiency gains remain aligned with patient-centered principles. Realizing AI's promise requires coordinated action to preserve empathy, trust, and interpersonal connection, ensuring that innovation strengthens rather than weakens the human dimensions of care.
28 May 2026
Read appraisal →JMIR medical informatics
Usability and Usefulness of Machine Learning-Based Clinical Decision Support Software in Primary Care: Survey of Users in a Prospective Observational Study
BACKGROUND: The successful implementation of decision support systems promises to enhance high-quality care. However, the successful implementation of a clinical decision support system (CDSS) depends on user acceptance and adoption. A machine learning (ML)-based CDSS to assist primary care professionals treating urinary tract infections (UTIs) was implemented, and usability and usefulness were assessed through a questionnaire. OBJECTIVE: This study aimed to assess the system's usability by examining users' experiences with the software. A secondary goal was to assess users' attitudes toward evidence-based practice and innovation in health care. METHODS: In collaboration with the Netherlands Institute for Health Services Research (NIVEL) and Leiden University Medical Center (LUMC), Pacmed Ltd developed the CDSS. The cohort was mostly recruited at the care group level; practices within participating care groups were required to participate. Health insurers partly funded the research. Practitioners participated in the implementation study for 4 months. A survey based on the Unified Theory of Acceptance and Use of Technology (UTAUT) was sent to 263 general practitioners and assistants shortly after the implementation period. Furthermore, usage data were analyzed. RESULTS: Of the 34 participating practices that used the software, 30 (88%) submitted at least one survey response, with a mean of 2.23 responses per practice (SD 1.43). The CDSS was used throughout the pilot period, and 31 practices continued using the tool, with 9% dropping out during the first 8 weeks. Sixty-seven percent of respondents trusted the tool's output, and 73% found it understandable how the algorithm came to predictions. Sixty-five percent of respondents indicated that the information provided was useful in addition to the available guidelines, and 52% agreed that it supported their decision-making. However, many respondents were uncertain whether the tool improved patient care (46%) or patient outcomes (66%). Forty-eight percent of respondents found the software easy to integrate into their clinical workflow. CONCLUSIONS: The CDSS was perceived as trustworthy and easy to use. However, users were unable to determine whether the CDSS improved patient outcomes. In addition, the CDSS development could have benefited from including assistants as well as general practitioners more in the design phase of the software. Because assistants play an important role in UTI care, designing the software to better fit existing workflows may reduce the perceived time investment associated with using the tool. Finally, respondents reported strong motivation to contribute to further research in this field and indicated willingness to embrace change in health care delivery, which may also reflect selection bias in our sample.
28 May 2026
Read appraisal →BMJ open
Assessment of patient preferences in digital health trials: procedure development and implementation in a preference-based trial
OBJECTIVES: To develop and evaluate a standardised, fully automated assessment procedure for patient treatment preferences suitable for use in randomised controlled trials (RCTs) with remote or digital health interventions. DESIGN: Multiphase developmental study followed by implementation in a fully randomised preference trial (FRPT). SETTING: University and outpatient cancer care settings in Switzerland; implementation in RCTs with a remote digital health intervention. PARTICIPANTS: 50 medical students for pilot testing; 11 patients with cancer for qualitative testing; 124 adult patients with cancer experiencing fatigue or sleep problems in an FRPT with a remote digital health intervention. PRIMARY AND SECONDARY OUTCOME MEASURES: Primary outcome: feasibility and applicability of a standardised digital preference assessment procedure. SECONDARY OUTCOMES: distribution and strength of treatment preferences, reasons for preference. RESULTS: A procedure with three items for assessing treatment preferences was developed and refined based on pilot testing, stakeholder meetings and patient interviews. The stepwise procedure ensured that study participants with an initially unclear preference were finally able to report their preference. The majority of students (91.7%) indicated their preference already in the first assessment step. Similar in the RCT phase, 110 of 124 participants (88.7%) indicated their preference in the first step. Preference drivers included interest, perceived ease and conceptual appeal in addition to expected treatment benefits. CONCLUSIONS: Our fully automated standardised preference assessment with three items appears feasible in trials with digital health interventions. Future trials with two active treatment conditions should consider implementation of such a preference assessment to evaluate non-specific treatment effects driven by the match of patients' preferences with the respective treatment. TRIAL REGISTRATION NUMBERS: DRKS00035596; DRKS00035541; SNCTP000006209.
28 May 2026
Read appraisal →Annals of family medicine
Association of Advanced Access With Primary Care Performance: A Systematic Review
PURPOSE: Timely access to primary care remains a major challenge. Advanced access, an organizational model for appointment management, aims to improve accessibility by allowing patients to consult their health care professional in a timely manner. This systematic review evaluated its association with several key dimensions of primary care performance. METHODS: We conducted a comprehensive search in MEDLINE, Embase, Web of Science, CINAHL, and the Cochrane Library from inception to May 10, 2025. Randomized intervention studies, nonrandomized intervention studies, and observational studies comparing advanced access with traditional scheduling systems among patients in primary care were eligible. Outcomes were the wait time to an appointment, continuity of care, emergency department (ED) use, and patient satisfaction. Two independent reviewers selected studies, extracted data, and assessed risk of bias. We performed a narrative synthesis, separately analyzing universal and non-universal health care systems. RESULTS: Among 7,595 unique records identified, 29 studies were included. Of these, 23 evaluated appointment wait time, 13 examined continuity of care, 3 assessed ED use, and 13 evaluated patient satisfaction. Appointment wait time decreased in all 23 studies assessing this outcome, with 13 reporting statistically significant reductions. Continuity of care improved in 11 of 13 studies, of which 7 reported statistically significant improvements. All 3 studies evaluating ED use reported reductions in ED visits, although none demonstrated statistical significance. Patient satisfaction improved in 8 studies, with 3 reporting statistically significant improvements. Overall, findings were consistent across universal and non-universal health care systems. CONCLUSIONS: Advanced access appears to improve appointment timeliness, continuity of care, and patient satisfaction, and may help reduce avoidable ED use across diverse health care systems.
28 May 2026
Read appraisal →Clinical and experimental dermatology
A systematic review of the barriers to diagnosis of vulval lichen sclerosus in primary care
BACKGROUND: Vulval lichen sclerosus (VLS) is a chronic, inflammatory genital skin condition causing itch, pain, anatomical changes and increased risk of vulval cancer. Diagnostic delay and misdiagnosis are common. Once diagnosed, VLS can be effectively treated using very strong topical corticosteroids. Most women with symptoms of VLS first present to primary care in the UK. OBJECTIVES: To identify patient and professional perspectives on barriers to diagnosis of VLS in primary care through systematic review and thematic synthesis of the literature. METHODS: Separate literature searches of seven databases relevant to patient and professional perspectives were conducted. Two reviewers screened titles and abstracts, with one performing a full text review. Data extracted were coded 'line by line', codes were organized into descriptive themes and subsequently developed into analytical themes. RESULTS: We identified 2468 references; a total of 56 studies met inclusion criteria. Six analytical themes were developed: (i) a medically challenging diagnosis; (ii) cultural and social taboos; (iii) education and knowledge gaps; (iv) feelings and attitudes; (v) inadequate health systems; and (vi) challenges in female genital examination. CONCLUSIONS: This review highlights obstacles for women in achieving a diagnosis of VLS. Education and knowledge gaps were reported by clinicians and patients. Clinicians lack knowledge of vulval skin disease and patients lack knowledge of vulval anatomy. Targeted, comprehensive education for clinicians could expedite diagnosis. Dismissive clinician attitudes compound patient feelings of anxiety and embarrassment, reinforcing taboos and stigma. Acknowledgement of embarrassment and stigma validates feelings, improving patient interactions. Future research priorities should include the development of a diagnostic tool and implementation of a complex intervention to expedite diagnosis.
27 May 2026
Read appraisal →Science advances
Generalizability of an AI-based mammogram risk score (MRS) for breast cancer among diverse populations of women
Conventional prediction models incorporating genetic and clinical factors including breast density underperform in non-European populations. We investigated an artificial intelligence-derived mammogram risk score (MRS), a summary of texture features that captures intrinsic breast-tissue characteristics-the substrate for cancer development. This study leveraged data from two North American screening cohorts totaling >226,000 women, including non-Hispanic white, non-Hispanic Black, East Asian, South Asian, and Indigenous women. MRS distributions showed nonsignificant shifts (and similar SDs) between cohorts and across race and ethnic subgroups. MRS increased with age and was significantly associated with breast cancer risk, with hazard ratios per SD ranging from 2.24 [95% confidence interval (CI), 2.03 to 2.46] to 2.32 (95% CI, 2.25 to 2.39) after age adjustment. Associations remained significant within all subgroups. Calibration was excellent across the racial and ethnic groups and across full-field digital mammograms and tomosynthesis. These findings establish MRS as a strong predictor that is independent of race or ethnicity, demonstrating its potential for broader clinical utility.
24 May 2026
Read appraisal →PloS one
Views, barriers, and facilitators of people living with human immunodeficiency virus and healthcare professionals regarding the use of a mobile health application to improve HIV self-care in Malaysia
AIM: The views, barriers, and facilitators of people living with HIV (PLWH) and healthcare professionals (HCPs), regarding the use of a mobile health application (m-HA) to improve HIV self-care were explored. SUBJECT AND METHODS: Seventeen PLWH, nine doctors and two nurses who owned a smartphone and understood English or Malay were recruited from the infectious disease clinic of a tertiary hospital in Malaysia. Semi-structured in-depth interviews were conducted face-to-face using a topic guide, audio-recorded and transcribed verbatim. Data was analysed using reflexive thematic analysis. Two researchers independently coded transcripts and met to resolve discrepancies and develop themes. Data collection continued until thematic saturation was achieved. RESULTS: Three themes emerged: (1) Perceived benefits and concerns regarding m-HA usage: participants perceived m-HA could improve knowledge, but expressed concerns regarding information overload. Participants viewed m-HA as a means to enhance access to hospital services like clinic visits, medication refills, communication with HCPs, and medical records documentation. However, concerns regarding misuse, data confidentiality and security remained. (2) Perceived motivators of m-HA: participants perceived that high utilitarian and hedonic motivators increase m-HA usage. (3) Perceived influences to use m-HA: participants believed PLWH would use m-HA if introduced by their peers or HCPs. CONCLUSION: These findings provided information for developing a patient-centred m-HA to improve HIV self-care in Malaysia.
24 May 2026
Read appraisal →BMJ paediatrics open
Enhancing parental health knowledge through digital knowledge mobilisation tools: a randomised controlled trial and qualitative study
OBJECTIVE: To assess the effectiveness of blogshots (ie, image-based digital knowledge mobilisation tools) to increase knowledge and manage expectations with respect to six Choosing Wisely Canada (CWC) recommendations about common childhood conditions. DESIGN: Multimethod study including a non-pharmacological randomised controlled trial and qualitative interviews. SETTING: Online questionnaires and semistructured interviews across Canada. PARTICIPANTS: Parents or legal guardians of children under 5 years. INTERVENTION: Participants were randomly allocated to receive one of two sets of blogshots whereby a blogshot on a new CWC topic was delivered weekly over 3 weeks (Group A: pharyngitis (diagnosis), common cold, asthma; Group B: pharyngitis (treatment), bronchiolitis, otitis media). Study investigators were blinded to participant allocation. Baseline and follow-up (week 5, month 3, month 6) questionnaires were administered. Qualitative interviews contextualised intervention data. MAIN OUTCOME MEASURES: The primary outcome was change in knowledge. Secondary outcomes were change in expectations, intentions, actions over time and usability of the blogshots. RESULTS: 167 participants (n=133 (80%) mothers) were included in the final analysis (group A, n=85; group B, n=82). Baseline knowledge scores did not differ between groups. At follow-up 1, those who received the blogshot for a given topic scored significantly higher (p<0.001, d=0.30) on knowledge questionnaires, compared with those that did not. No differences were observed in knowledge scores between groups at follow-up 2 and 3. Participants expressed intentions to use the blogshots (eg, share with friends, physicians), as well as actions (eg, wait/watch approach vs seek healthcare) to manage their child's condition. Qualitative data (n=13 interviews) showed that blogshots are aesthetically pleasing and contain easy to read and understandable information. CONCLUSIONS: Blogshots can be an effective tool to disseminate child health information to parents. Due to the online dissemination, this approach could be scaled to a broader international level and applied to different health topics that are relevant across the world. TRIAL REGISTRATION NUMBER: NCT06005337.
24 May 2026
Read appraisal →Studies in health technology and informatics
Accessibility of Digital Health and Welfare Services Among Immigrants in Finland
Digital health and welfare services support the delivery of the services. However, the health benefits are mixed at the population level, and further research is needed to better understand the driving factors of healthcare inequalities, particularly among vulnerable subgroups, e.g., immigrants. This qualitative study aimed to understand equality in service accessibility among immigrants, especially from the informational, experiential, and institutional perspectives. Five focus group interviews were conducted for immigrants. Data was analysed with deductive content analysis. Barriers for informational accessibility included linguistic challenges and inadequate digital literacy (DL); for experiential accessibility, usability challenges and disrespectful phone services; for institutional accessibility, challenges with electronic authentication identification for personalized digital services. Facilitators for the use of digital health and welfare services included linguistic improvements of services and support for DL. Further research, including interventions with participatory design and linguistic and digital support, is needed to improve accessibility of digital services for immigrants.
24 May 2026
Read appraisal →JMIR research protocols
Effect of a Personalized Mobile Health Intervention Using Artificial Intelligence (the WARIFA App) Versus a Nonpersonalized Intervention on User-Defined Objectives, Healthy Lifestyles, and Management of Type 1 Diabetes (T1D): Protocol for a Randomized Controlled Trial
BACKGROUND: Noncommunicable diseases are the leading cause of death worldwide. Cardiovascular and respiratory diseases, cancer, and type 2 diabetes share common risk factors that can be addressed: physical activity, a healthy diet, and avoiding smoking and alcohol. The Watching the Risk Factors (WARIFA) mobile health app was created for general health awareness and to support users in adopting healthier behaviors, as well as to support type 1 diabetes (T1D) self-management. OBJECTIVE: This study aims to evaluate the effectiveness of the WARIFA app with personalized artificial intelligence (AI)-driven messages, compared to a nonpersonalized version, in promoting health-related behavior change among the general population and individuals with T1D. METHODS: A total of 108 European participants, including individuals with T1D, were to be randomized (computer-generated sequence, double-blind, 1:1 ratio) to an intervention or control group. In the intervention group, participants used the WARIFA app with personalized messages and the use of AI. This applied to certain functionalities, such as providing recommendations on healthy dietary habits based on food logging and offering advice and encouragement through daily step tracking. It also provided risk predictions for cardiovascular and respiratory diseases, cancer, and type 2 diabetes. Participants with T1D were offered glucose predictions based on previous measurements. In the control group, participants used a WARIFA app without personalized messages or AI. Both WARIFA app versions offered access to air quality and UV index information for the geographical area, as well as displaying physical activity in the form of daily steps and sleep hours, as well as glucose results for participants with T1D. Both groups were provided with an activity monitor and used the WARIFA app for 8-12 weeks. The primary outcome is a self-defined goal, chosen from a set of proposed objectives at baseline and assessed at the end of the study using a Likert scale (1 to 10 points, 0 being no achievement at all and 10 being full achievement of the objective). Secondary outcomes include: engagement with the app, changes in lifestyle behavior, body composition, lipid profile, glycated hemoglobin (T1D only), hypoglycemic events (T1D only), and health-related quality of life, as well as acquired knowledge, self-efficacy, and usability. RESULTS: The clinical trial took place between January and June 2025. A total of 88 participants were finally recruited. The data are being analyzed, and the results are expected to be published in 2026. CONCLUSIONS: There is evidence that improving lifestyle behavior can prevent noncommunicable diseases. In this study, we aim to evaluate the effectiveness of the WARIFA app to improve lifestyle behaviors and T1D management. TRIAL REGISTRATION: ClinicalTrials.gov NCT06918444; https://clinicaltrials.gov/study/NCT06918444. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/84510.
23 May 2026
Read appraisal →JMIR human factors
Development and Psychometric Validation of a Usability Instrument Based on ISO 25010 for Electronic Health Record Systems in Peruvian Health Care Settings: Methodological Study
BACKGROUND: The usability of electronic health records influences patient safety, clinical efficiency, and the sustainable digital transformation of health care. While tools such as the System Usability Scale exist, few are based on structured software quality models or align with local regulatory frameworks, particularly in low- and middle-income countries. OBJECTIVE: This study aims to develop and psychometrically validate an instrument to assess electronic health record usability, based on the ISO 25010 (International Organization for Standardization) quality model, and in accordance with the Peruvian Technical Health Standard (Norma Técnica de Salud [NTS]). METHODS: A 3-stage methodological study was conducted following COSMIN (Consensus-based Standards for the Selection of Health Measurement Instruments) guidelines. First, a 23-item instrument was developed, grouped into 7 usability dimensions based on ISO 25010. Second, content validity was assessed using a modified Delphi method with 10 experts, using Aiken's V coefficient. Third, structural validity and reliability were evaluated in 115 participants (physicians, nurses, and administrative staff) using confirmatory factor analysis and Cronbach α. Additionally, the module's functional compliance with the NTS was verified. RESULTS: The instrument demonstrated excellent psychometric properties among 115 participants (53 physicians, 48 nurses, and 14 administrative staff); high content validity (Aiken's V=0.95; 95% CI 0.84-0.98), excellent internal consistency (α=.968), and optimal factor fit (Comparative Fit Index=1.000; Tucker-Lewis Index=1.001). Overall usability was perceived as very high by 94 of 115 users (81.7%), and high by 21 of 115 users (18.3%), with no perceptions at lower levels. The module met 28 of 35 requirements (80%) of the Peruvian Technical Health Standard. Administrative staff reported higher satisfaction (13/14, 93% rated it as very high) compared with clinical professionals (81/101, 80% rated it as very high), particularly in the dimensions of error protection and operability. CONCLUSIONS: This study provides the first fully psychometrically validated instrument in Spanish based on ISO 25010, System Usability Scale, and other theoretical foundations for evaluating the usability of information systems. The results highlight the importance of considering both international standards and local regulatory requirements (NTS) in the design of digital health systems. The instrument is applicable in Spanish-speaking contexts and can serve as a reference for future usability evaluations in the region as well as in low- and middle-income countries.
23 May 2026
Read appraisal →Journal of medical Internet research
Measuring eHealth Literacy in the European Economic Area, Switzerland, and the United Kingdom: Scoping Review
BACKGROUND: Digital tools continue to evolve and have the potential to improve health care delivery. However, they are associated with challenges, including accessibility issues and health misinformation. Individuals need eHealth literacy (eHL) to reliably use these tools, and providers require appropriate eHL measurement approaches to offer targeted solutions. For around 2 decades, researchers have been operationalizing and measuring eHL. OBJECTIVE: This paper aims to provide an up-to-date overview of how eHL has been assessed in recent years in the European Economic Area, Switzerland, and the United Kingdom and which methodological limitations need to be considered. METHODS: A scoping review was conducted. Records were searched via CINAHL, PubMed, and Google Scholar on January 31, 2025, and January 28, 2026. Peer-reviewed empirical papers published in German or English since 2020 that measured eHL in the European Economic Area, Switzerland, or the United Kingdom were included. The synthesis covered the publication trend, eHL measurement approaches and associated limitations reported in the included papers, eHL measurement frequency, countries and languages, and samples. RESULTS: In the final analysis, 132 papers published between 2020 and 2025 were included. The number of publications per year showed an overall upward trend (2020: 11/132, 8.33%; 2025: 35/132, 26.52%). Nine self-report eHL measurement instruments were used, the eHealth Literacy Scale being the most frequent (94/132, 71.21%). All included papers (132/132, 100%) reported data collection via surveys, and digital surveys were common (71/132, 53.79%). Reported limitations included potential self-report biases (37/132, 28.03%), selection biases due to the data collection modes (26/132, 19.70%), and limitations specific to 5 eHL measurement instruments (18/132, 13.64%). Most included papers (121/132, 91.67%) reported eHL results from a single measurement per participant. Data were collected in 22 countries within the target regions. The distribution of eHL measurement instruments varied considerably between countries. Data were collected in 22 languages within the target regions. Patients or individuals with health problems were a frequent target group (64/132, 48.48%). Most papers (104/132, 78.79%) described studies covering broad adult age ranges. Sample sizes ranged from ≤50 (7/132, 5.30%) to >2000 participants (8/132, 6.06%). CONCLUSIONS: To our knowledge, this is the first scoping review synthesizing eHL measurement limitations reported in empirical papers from the European Economic Area, Switzerland, and the United Kingdom. The identified limitations reported in the included papers potentially lead to biased results. Therefore, health care providers and researchers should take various factors into account when selecting eHL measurement approaches, such as eHL measurement purpose, target population, and data collection setting. Future research should address these constraints by adapting and developing new or revised eHL measurement instruments, including translated and culturally adapted versions. Policymakers should encourage health care providers to conduct methodologically well-founded eHL measurements as a basis for targeted solutions.
23 May 2026
Read appraisal →BMJ open
Australian key stakeholder views regarding implementation of atrial fibrillation screening: a qualitative evaluation
OBJECTIVE: To understand the issues impacting atrial fibrillation (AF) screening and what needs to be considered for a successful national screening programme in Australia. DESIGN: Qualitative design using semistructured interviews and thematic analysis. SETTING: Australian Health. PARTICIPANTS: Six broad stakeholder groups were identified: charities/patient support, healthcare providers, professional bodies, government, research (including Indigenous health) and industry. METHODS: Semistructured interviews were conducted with 25 representative participants. Iterative thematic analysis was used. Coding was driven by the research questions (the current context; is a national screening programme warranted and approaches to a national screening programme) and an inductive approach where novel groupings of information were identified. FINDINGS: The key findings are grouped into four areas. (1) Current opportunistic general practitioner-led screening is ad hoc and fragmented. ISSUES: poor remuneration; lack of health sector collaboration and prioritisation; consumers lack awareness. (2) Systematic screening of all in-scope patients not considered feasible and concerns over lack of evidence. (3) Alternative approaches to increase screening include innovative approaches inside and outside general practice and use of smart technology. (4) Recommendations: (a) Support general practices and address remuneration and workflows; (b) Ensure a clear pathway to treatment; (c) Address data security, management and integration and sensitivity issues with wearable devices; (d) Promote collaboration between key organisations; (e) Address research gaps and (f) Generate culturally appropriate consumer education to promote consumer demand. CONCLUSIONS: Most stakeholders were broadly supportive of AF screening but agreed that current approaches were fragmented and not sufficient. If the forthcoming research evidence supports screening effectiveness on major outcomes, stakeholders envisaged a semi-systematic approach tailored to specific health settings, rather than a formalised systematic national screening programme.
23 May 2026
Read appraisal →Journal of medical systems
Advances in Technology-Assisted Visual Rehabilitation Therapies: Scoping Review
Visual impairment (VI) is a growing condition associated with aging, neurological diseases, and chronic eye conditions. In 2023, more than 2.2 billion people experienced VI, and at least 1 billion could have been prevented or remain untreated. Visual rehabilitation (VR) is essential for optimizing residual vision and promoting functional independence; however, only a minority have access to these services. In recent years, the development of technologies such as artificial intelligence (AI), mobile applications, and virtual reality (VRt) has transformed VR, offering accessible and personalized alternatives. This scoping review aimed to map and categorize the available evidence on technology-assisted visual rehabilitation therapies, identifying the types of technologies used, their applications, and reported clinical and functional outcomes. A scoping review was conducted following the Joanna Briggs Institute (JBI) methodology and PRISMA-ScR guidelines to map the literature published between 2015 and 2025 on technology-assisted VR therapies in adults with VI worldwide. Twenty-five studies, mainly from developed countries, were included. Interventions included videoconferencing, computerized systems, portable devices, VRt, artificial vision (AV), and smart sensors. Overall, digital technologies were shown to improve visual function, autonomy, and quality of life, with high patient satisfaction and adherence. Telerehabilitation (TR), understood as the remote delivery of visual rehabilitation services through videoconferencing and digital monitoring platforms, has emerged as a viable and cost-effective strategy. In contrast, immersive virtual reality technologies (VRt), head-mounted display systems, and multisensory integration devices have demonstrated potential to stimulate neuroplasticity and enhance functional visual outcomes.Telerehabilitation platforms, immersive virtual reality systems, portable electronic vision enhancement devices, artificial vision technologies, and sensor-based monitoring tools are emerging as promising interventions. These technologies have demonstrated improvements in visual acuity, reading performance, visual field sensitivity, patient adherence, and functional autonomy, although most studies remain small-scale and geographically concentrated in high-income settings.
23 May 2026
Read appraisal →Current environmental health reports
Industrial Pollution and Health in Louisiana: A Systematic Review of Quantitative and Qualitative Studies
PURPOSE OF REVIEW: Louisiana has one of the largest concentrations of petrochemical industry in the USA. Many studies have assessed patterns of industrial pollution and health in Louisiana; we aim to systematically review this evidence. We systematically searched PubMed, Web of Science, Embase, APA PsycInfo, and GreenFILE for peer-reviewed papers published 1999-2024 that reported geographical variation in health or industrial pollution, and/or tested for an association between the two in Louisiana. We used Covidence to support standardized review and extraction. RECENT FINDINGS: We identified 2485 non-duplicate papers in our search; 53 met the inclusion criteria. Most reported quantitative findings. All studies of industrial pollution described air pollution (some also described other pollution). Studies described various health outcomes, including cancer, respiratory health, mortality, and COVID-19. Overall, people who lived closer to industrial activity had higher pollution exposure and worse health. Black and lower-income residents were exposed to more industrial activity than white and higher-income residents. Twenty-one studies assessed statistical associations between industrial pollution and health; many found an association. Twenty-one studies were quantitative and adjusted for confounding, 29 studies did not adjust for confounding (including qualitative studies), and three studies did not adjust for confounding and had authors with industry ties. Evidence suggests that there is a higher burden of air pollution and worse health outcomes in industrialized areas of Louisiana. While there was some evidence of significant associations between industrial pollution and health outcomes, research with larger sample sizes and improved pollution exposure measurements could be informative.
23 May 2026
Read appraisal →BMJ open
Toolkit to prompt and support stopping antidepressants in general practice: an interview study exploring patient participants' experiences in the RELEASE trial.
OBJECTIVE: To explore patient experiences with the RELEASE (Redressing long-term antidepressant use) toolkit resources, including antidepressant hyperbolic tapering plans designed to minimise withdrawal symptoms as part of the RELEASE trial's implementation evaluation to understand what aspects of the toolkit work well and identify areas where refinement could enhance future implementation. The RELEASE intervention, a multistrategy intervention codesigned with general practitioners (GPs) and patients to prompt and support stopping long-term (>12 months) antidepressants, is being evaluated in an effectiveness-implementation hybrid type-1 cluster randomised controlled trial in general practice. STUDY DESIGN: One-to-one semistructured qualitative interviews using reflexive thematic analysis to identify patterns of shared meaning. SETTING: General practice, south-east Queensland, Australia. PARTICIPANTS: Adult participants (aged 18 years or older) taking an antidepressant long-term allocated to the intervention arm of the RELEASE trial. RESULTS: 31 participants with an average duration of antidepressant use of 16.5 years (range 1-30 years) were interviewed. Seven themes were identified. Across seven themes, participants described how the RELEASE toolkit resources prompted reflection on their antidepressant use, supported informed conversations with GPs, and offered tapering plans that were both structured enough to instil confidence and flexible enough to help participants feel in control of their tapering journey. They also identified barriers, including beliefs that very small tapering doses were unnecessary, difficulty accessing the mini-doses required for hyperbolic tapering and the challenge of managing withdrawal symptoms. For those who successfully stopped, the transition was associated with a renewed sense of autonomy. Participants also offered practical suggestions to strengthen the toolkit and its broader implementation. CONCLUSIONS: The RELEASE toolkit resources played a meaningful role in prompting and supporting informed shared decision-making and guiding attempts to stop antidepressants. Clearer messaging about the potential for withdrawal symptoms and access to mini-doses for tapering are needed to support patients to safely stop antidepressants. TRIAL REGISTRATION NUMBER: ACTRN12622001379707p; Pre-results.
23 May 2026
Read appraisal →JMIR formative research
MyLungHealth, a Patient-Facing Education Tool for Lung Cancer Screening: Qualitative User-Centered Design Study
BACKGROUND: Lung cancer remains the leading cause of cancer-related mortality worldwide, with low-dose computed tomography screening demonstrating an approximately 20% reduction in mortality among high-risk individuals. Despite this benefit, screening prevalence remains suboptimal, with often less than 20% of eligible individuals reported to be up to date on screening. Shared decision-making is essential for effective lung cancer screening (LCS) implementation, with decision aids shown to enhance patient knowledge and engagement. OBJECTIVE: The aim of this study is to identify patient preferences, concerns, and design considerations through qualitative evaluation of MyLungHealth, a personalized patient-facing educational tool for LCS integrated with electronic health records, and to describe how these findings informed iterative design modifications. METHODS: We employed qualitative research methods through focus groups (n=34) and individual interviews (n=18) with individuals who met screening eligibility criteria. Participants were recruited from the University of Utah Health and New York University Langone Health between May and December 2023. Feedback was analyzed using Braun and Clarke's thematic analysis principles. RESULTS: Six themes were organized into three overarching domains. Domain A included interpretation and impact of personalized risk information: theme 1, difficulties interpreting risk information, and theme 2, varied impacts of risk information on motivation. Domain B included autonomy, privacy, and user interface preferences: theme 3, desire for autonomy and control over personal health data, and theme 4, preference for straightforward language and multiple information formats. Domain C included integration with clinical workflows and patient portal systems: theme 5, expectations for integration with health care provider workflows, and theme 6, mixed experiences with personal health record systems. These insights led to key design modifications, including simplified risk presentation, multimodal content delivery options (video and text), and implementation of electronic health record alerts for clinicians. CONCLUSIONS: The user-centered design process for MyLungHealth revealed important considerations for developing effective patient education tools for LCS. The findings highlighted the need for simplified risk presentation, personalized information delivery, and integration with clinical workflows. These findings underscore the importance of balancing comprehensive risk communication with user accessibility.
23 May 2026
Read appraisal →JMIR formative research
Conceptualizing Acceptance and Knowledge as Process Variables in Internet-Delivered and Therapist-Supported Cognitive Behavioral Therapy and Acceptance and Commitment Therapy in Primary Care for Insomnia: Pilot Feasibility and Process-Oriented Randomized Controlled Trial
BACKGROUND: Internet-based interventions for insomnia show promise, but understanding the process variables, such as knowledge acquisition and psychological acceptance, is crucial for enhancing digital adherence and clinical effectiveness. OBJECTIVE: This study aimed to evaluate the feasibility, adherence, and preliminary clinical signals of 2 therapist-assisted interventions-internet-delivered cognitive behavioral therapy (iCBT) and internet-delivered acceptance and commitment therapy (iACT)-for insomnia in a primary care setting. METHODS: This was a pilot randomized controlled trial. Adults seeking help for insomnia (n=18) were recruited via primary care and randomized to either a 5-module iCBT or iACT program delivered via a secure digital platform with weekly therapist feedback. Blinding of participants and therapists was not possible due to the nature of the interventions. Primary outcomes included the Insomnia Severity Index; secondary outcomes included the 9-item Patient Health Questionnaire, 7-item Generalized Anxiety Disorder, and WHO Disability Assessment Schedule. A novel sleep knowledge test was used as a process variable. The data were analyzed using split-plot analyses of variance (intention-to-treat or last observation carried forward and complete case analysis) and nonparametric Friedman and Kruskal-Wallis tests. RESULTS: A total of 18 participants were randomized (iCBT: n=9; iACT: n=9). High attrition was observed, with only 33.3% (n=3) of iCBT and 55.6% (n=5) of iACT participants completing all modules. The iACT group demonstrated a significant within-group reduction in insomnia severity (P=.01, Friedman test), whereas iCBT results were nonsignificant (P=.10, Friedman test). No significant between-group differences were found for any clinical or process variables. Participants rated both treatments as credible (Credibility/Expectancy Questionnaire scores remained stable), though qualitative feedback indicated a need for more flexible, less burdensome content. CONCLUSIONS: This pilot study demonstrates that while internet-delivered insomnia treatments are feasible and credible in primary care, high attrition remains a significant barrier. Preliminary signals suggest that iACT may be a viable alternative to iCBT, potentially offering better adherence. Larger, fully powered pilot randomized controlled trials (estimated N=404) with refined recruitment and automated retention strategies are required to determine definitive comparative efficacy and the mediating role of sleep knowledge and acceptance.
22 May 2026
Read appraisal →Journal of medical Internet research
Efficacy of Internet-Based Self-Help Interventions for Irritable Bowel Syndrome: Systematic Review and Meta-Analysis of Randomized Controlled Trials
BACKGROUND: Irritable bowel syndrome (IBS) is a common functional gastrointestinal disorder that reduces quality of life and causes a heavy medical burden. Internet-based self-help interventions are flexible and scalable, showing potential for IBS symptom improvement, but relevant evidence is fragmented and lacks systematic review. OBJECTIVE: This systematic review aimed to comprehensively evaluate the effects of internet-based self-help interventions on symptom severity, quality of life, and visceral sensitivity, as well as comorbid depressive and anxiety symptoms, in individuals with IBS. METHODS: Only randomized controlled trials evaluating internet-based self-help interventions for individuals with IBS were included. A literature search was conducted across PubMed, Embase, Web of Science, CINAHL Complete, PsycINFO, the Cochrane Library, and 4 Chinese databases on June 25, 2025, with an updated search on March 9, 2026. Risk of bias was assessed using the Cochrane Risk of Bias 2.0 tool. Meta-analyses were performed with the Hartung-Knapp-Sidik-Jonkman-adjusted random-effects model. Effect sizes were reported as standardized mean differences (SMDs) with 95% CIs, and evidence certainty was evaluated using GRADE (Grading of Recommendations Assessment, Development, and Evaluation) criteria. RESULTS: A total of 17 randomized controlled trials from 7 countries were included, involving 2289 participants (predominantly female). Compared with control groups, internet-based self-help interventions were associated with a statistically significant improvement in IBS symptom severity (SMD -0.52, 95% CI -0.78 to -0.26, 95% prediction interval [PI] -1.46 to 0.42), quality of life (SMD 0.57, 95% CI 0.23 to 0.90, 95% PI -0.41 to 1.54), visceral sensitivity (SMD -0.55, 95% CI -0.89 to -0.21, 95% PI -1.43 to 0.33), and depressive symptoms (SMD -0.14, 95% CI -0.27 to -0.01, 95% PI -0.27 to -0.01). However, no statistically significant improvement was observed in anxiety symptoms (SMD -0.03, 95% CI -0.34 to 0.27, 95% PI -0.78 to 0.71). The certainty of evidence was rated as moderate to very low for all outcomes. CONCLUSIONS: This review synthesizes the latest evidence on internet-based self-help interventions for individuals with IBS disease-specific and comorbid psychological symptoms. It stands out by encompassing a diverse range of such interventions and incorporating visceral sensitivity as a key outcome. In doing so, it establishes a more comprehensive multi-outcome evidence base for IBS digital interventions, advancing the field by clarifying the potential of these interventions as viable alternatives to conventional treatments. For real-world practice, these findings can inform targeted strategies for primary care and telemedicine platforms, especially in resource-limited regions. However, this review is limited by moderate bias risk, high heterogeneity, and moderate to very low GRADE evidence certainty. A wide 95% PI suggests that effect variability is linked to contextual and population factors, so findings should be interpreted cautiously. Future research should prioritize technical support, patients' digital health literacy, and standardized intervention protocols to further validate clinical utility.
22 May 2026
Read appraisal →Chinese medical journal
Estimating minimal, moderate, and marked clinically important differences for patient reported outcome measure in randomised controlled trial
BACKGROUND: Patient-reported outcome measures (PROMs) are increasingly used in clinical trials, yet thresholds that define clinically important difference (CID) within patients and treatment effects beyond placebo remain inconsistently reported, limiting its utility in clinical research and practice. Using chronic pelvic pain and its core PROM as a worked example, the study aims to present a structured framework for CID thresholds that separates within-group change from between-group difference in treatment effect, each further stratified as minimal, moderate, and marked. METHODS: We used data from a multicenter randomized controlled trial of acupuncture vs . sham acupuncture in 440 men with chronic prostatitis (CP)/chronic pelvic pain syndrome (CPPS) conducted from October 2017 to April 2019. National Institutes of Health Chronic Prostatitis Symptom Index (NIH-CPSI) served as the PROM and the Patient Global Impression of Change (PGI-C) as the anchor. CIDs were estimated using a linear mixed-effects model to assess changes in NIH-CPSI scores across PGI-C categories. RESULTS: At the end of treatment, 12.3% (51/414) participants reported no change, 34.1% (141/414) slight improvement, 32.1% (133/414) moderate improvement, and 19.6% (81/414) marked improvement; and 1.9% (8/414) reported worsening. The estimated Clinically important within-group difference (CIDs within-group ) in NIH-CPSI total score was 4.6 points for minimal, 6.0 points for moderate, and 7.3 points for marked improvement. The corresponding Clinically important between-group difference (CIDs between-group ) were 1.4, 2.7, and 4.1 points, respectively. CONCLUSIONS: In this methodological study, we proposed a pragmatic and scalable operational framework to derive thresholds for minimal, moderate, and marked CIDs. By explicitly distinguishing CIDs within-group and CIDs between-group , the approach clarifies two frequently conflated terms that serve distinct purposes in interpretation and decision-making. This framework offers benchmarks to strengthen inference on treatment response, trial design, and guideline decision thresholds.
21 May 2026
Read appraisal →Brazilian oral research
Effect of strict oral hygiene on self-rated halitosis and quality of life in patients with periodontitis: a secondary randomized controlled trial analysis
This single-blind, randomized clinical trial evaluated the impact of a strict oral hygiene (OH) phase on self-reported halitosis and quality of life (QoL) in patients with periodontitis. This study reports a secondary analysis of a single-blind randomized controlled trial (parallel, 1:1), registered at RBR-5jmx32v. The study included 24 individuals diagnosed with periodontitis who were randomly assigned to the intervention group (IG; n = 12) and the no-intervention group (NIG; n = 12). After receiving personalized OH instructions, the IG participants followed a rigorous OH phase for 45 days, whereas the NIG participants received no guidance during this period. The halitosis-associated QoL test (HALT) was administered at baseline and after 45 days. Data were analyzed using t-tests, chi-square tests, and multilevel linear regression, with significance set at p < 0.05. The average age of the study participants was 47.2 years, with a balanced sex distribution and no differences in income or education. Self-reported halitosis decreased from 100% to 50% in the IG after 45 days, whereas it remained at 91.6% in the NIG (p = 0.034). The IG also showed a mean HALT score reduction of 11.9 points (-11.88; 95% CI: -19.40 to -4.36), with significant improvements in social impact and self-esteem (p < 0.05). Clinically, BOP (p < 0.001) and VPI (p = 0.03) improved significantly in the IG, with no significant changes in NIG. This exploratory trial demonstrates that implementing a strict OH phase in patients with periodontitis may help reduce self-reported halitosis, improve HALT scores, and improve clinical outcomes, supporting its role as an adjunctive strategy in periodontal care.
21 May 2026
Read appraisal →Sexually transmitted infections
Complex role of digital health literacy in awareness and use of digital sexually transmitted and blood-borne infections testing: a structural equation modelling analysis of the 2022 GetCheckedOnline survey
BACKGROUND: Although digital health literacy (DHL) is recognised as a determinant of access to digital sexually transmitted and blood-borne infection (STBBI) testing, empirical evidence about its contribution to access disparities remains limited. We applied multidimensional DHL measures to examine inequities in awareness and use of GetCheckedOnline, British Columbia's (BC) publicly funded digital STBBI testing service. METHODS: We analysed data from GetCheckedOnline's 2022 community survey of English-speaking BC residents aged ≥16 years who were sexually active in the past year. Outcomes were awareness and use of GetCheckedOnline (yes/no). DHL was measured using latent factors from the eHealth Literacy Scale: Information Navigation, Resource Appraisal and Confidence in Use. Structural equation modelling (SEM) was used to estimate associations and mediation pathways between DHL, sociodemographic characteristics and service outcomes. Model fit was assessed using standard SEM indices. RESULTS: Among 1657 respondents (mean age 33 years, SD 11.77), Information Navigation was positively associated with awareness (β=0.162, p<0.001) and use (β=0.063, p=0.020) of GetCheckedOnline. Confidence in Use was positively associated with awareness (β=0.206, p=0.014) and use (β=0.115, p=0.020). In contrast, Resource Appraisal was negatively associated with awareness (β=-0.263, p=0.006) and use (β=-0.150, p=0.010). DHL factors mediated the effects of age, income, education and digital access on both outcomes. CONCLUSIONS: DHL operates as a multidimensional and socially patterned determinant of access to digital STBBI testing services. While information navigation and confidence in use facilitate access, higher resource appraisal may reduce use, potentially reflecting concerns about service fit, privacy or trust. Findings highlight the need for digital interventions that are not only accessible but also contextually relevant, trusted and responsive to the needs of diverse users.
20 May 2026
Read appraisal →Journal of the American Heart Association
Determinants of Successful Implementation: A Mixed-Methods Evaluation of a Team-Based Telehealth Hypertension Management Program for Underserved Patients
BACKGROUND: Hypertension management using home blood pressure monitoring-guided pharmacotherapy is more effective than clinic-based care, but the benefit is attenuated in underserved patients. We evaluated implementation determinants of a team-based telehealth hypertension management program providing home blood pressure monitoring-guided pharmacotherapy and self-management and social support. METHODS: We used Exploration, Preparation, Implementation and Sustainment, and Health Equity Implementation Frameworks for semistructured interviews and inductive/deductive coding using thematic analysis of qualitative data and quantitative analysis to evaluate team-based telehealth hypertension management program implementation facilitators, barriers, acceptability, appropriateness, and feasibility. We purposefully sampled 20 patients with hypertension and 16 clinic key players from 2 safety-net clinics in North Carolina. Quantitative measures were Acceptability of Intervention Measure, Intervention Appropriateness Measure, Feasibility of Intervention Measure, Patient Assessment of Chronic Illness Care, Organizational Readiness for Implementing Change (all measures' score ranged 1-5; higher score is better). We used concurrent embedded mixed methods (qualitative + quantitative) for convergence and complementarity. RESULTS: Five qualitative themes emerged around (1) staffing barriers, coordinated teamwork, and friendly study tools; (2) the program's patient and provider centeredness; (3) ease of home blood pressure monitoring; (4) personalized, comprehensive self-management calls; and (5) social support. Patients and clinic key players found the program acceptable (mean±SD, 4.42±0.84 and 4.56±0.59), appropriate (4.42±0.86 and 4.61±0.50), and feasible (4.40±0.89 and 4.44±0.53), respectively. Patient Assessment of Chronic Illness Care and Organizational Readiness for Implementing Change scores were 4.22±1.01 and 4.11±0.78, respectively. CONCLUSIONS: Implementing a team-based telehealth hypertension management program depends on its tailoring to patients and providers and having their endorsement; a user-friendly and trust-promoting model; and having a viable financial plan. Future studies should assess clinical and cost effectiveness of the program. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT05424744.
20 May 2026
Read appraisal →The British journal of dermatology
Burden and risk of asthma and rhinitis in people with atopic dermatitis: global estimates from a hierarchical Bayesian model
BACKGROUND: Atopic dermatitis (AD) is a chronic inflammatory skin disease often associated with asthma and rhinitis. However, epidemiological evidence on these comorbidities remains fragmented and is largely limited to high-income countries. OBJECTIVES: To provide comprehensive global, regional and country-level estimates of the prevalence and odds ratios (ORs) of asthma, rhinitis and their subtypes among individuals with AD. METHODS: We systematically reviewed 278 studies retrieved from PubMed, Embase, Web of Science and CNKI (China National Knowledge Infrastructure). Standardized prevalence estimates and ORs were derived using a Bayesian hierarchical linear mixed-effects model. RESULTS: Among individuals with AD, the global prevalence estimate of asthma, rhinitis, allergic rhinitis, rhinoconjunctivitis, and coexisting asthma and rhinitis was 20.1% (ranging from 2.5% in Israel to 59.4% in India), 45.1% (ranging from 7.8% in Israel to 82.7% in India), 41.4% (ranging from 6.8% in Israel to 80.3% in India), 30.7% (ranging from 4.3% in Israel to 71.9% in India) and 10.4% (ranging from 1.1% in Israel to 40.8% in India), respectively. Estimates were higher when restricted to patients with AD diagnosed by dermatologists or physicians. The highest comorbid prevalence rates were found for India, Cuba, Finland and Puerto Rico. Compared with healthy control individuals, AD was associated with higher odds of asthma (OR 2.73; ranging from 1.59 in China to 6.64 in Ethiopia), rhinitis (OR 2.98; ranging from 1.73 in China to 7.23 in Ethiopia), allergic rhinitis (OR 2.42; ranging from 1.41 in China to 5.89 in Ethiopia), rhinoconjunctivitis (OR 4.21; ranging from 2.45 in China to 10.19 in Ethiopia), and coexisting asthma and rhinitis (OR 2.42; ranging from 1.41 in China to 5.89 in Ethiopia). CONCLUSIONS: This study provides the first globally standardized estimates of respiratory comorbidities in AD, and can inform clinical practice and public health policy. Atopic dermatitis is a common long-term inflammatory skin disease. It is also called eczema. It affects more than 200 million children and adults worldwide. People with the disease often have other conditions, particularly asthma and rhinitis. Asthma affects breathing and rhinitis causes sneezing or congestion. Most studies on these conditions have been in wealthy countries. They have also used a range of different research methods. This makes it difficult to compare and understand the global situation. In this study, researchers in China and the USA analysed data from 278 studies from around the world. We estimated how common asthma and rhinitis are in people with eczema in different regions and countries. We found that about 1 in 5 people with eczema have asthma and almost half have rhinitis. We also found that people with eczema are 2 to 4 times more likely to have these conditions than people without eczema. Some countries showed particularly high rates of these conditions. Our findings suggest that asthma and rhinitis are common problems for people with eczema. This is true no matter where they live. The information from this study may help doctors recognize and manage these conditions in people with eczema. These findings could also support future research to improve disease prevention and patient care.
20 May 2026
Read appraisal →Cancer causes & control : CCC
Prediction models for early detection and diagnosis of lung cancer in people who have never smoked: a systematic review and critical appraisal
BACKGROUND: Never-smokers can develop lung cancer, but this possibility is often overlooked by patients and physicians. We conducted a systematic review to identify existing prediction models that could be implemented in primary care or at a population level to facilitate early detection and diagnosis of lung cancer in never-smokers. METHODS: This study was registered on PROSPERO (ref: CRD42023374471). We systematically searched literature on the Medline, Embase, PsycINFO, and CINAHL databases published before 22 January 2025, with additional hand searching. Primary care or population-level data from subjects including never-smokers had to be used for model derivation. Studies involving specialized tests (radiological or genetic) were excluded. We used CHARMS to guide data extraction and critical appraisal, the TRIPOD statement for model evaluation, and PROBAST for risk of bias assessment. RESULTS: Among 2,431 studies retrieved, 31 models were included. Eight models were developed exclusively for never-smokers, but none were at low risk of bias. Among 23 models derived from never- and ever-smokers, five were at low risk of bias. Two were diagnostic models with 1-2 years prediction horizons, and three were prognostic models with 2-10 years prediction horizons. Methodological issues from the included studies were identified, analyzed, and discussed. CONCLUSION: This systematic review critically appraises and summarizes key information from currently available prediction models for lung cancer in never-smokers. The findings can inform future research to improve care and services for this underserved population.
20 May 2026
Read appraisal →BMJ quality & safety
Patient safety measures for virtual consultations in primary care: a systematic review
OBJECTIVES: With the growing adoption of virtual consultations in primary care, the need for tailored metrics to evaluate their safety became increasingly urgent. This systematic review seeks to identify and review existing safety measures that could be used for safety evaluation of virtual consultations in primary care. METHODS: This has been conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and followed a published protocol. A systematic literature search was performed in Ovid MEDLINE/PubMed, Embase and Cochrane Library databases from 2014 to 2024. Studies comparing virtual consultations with face-to-face consultations in the primary care setting were included. An inductive thematic analysis was performed to systematically extract and group the safety measures into overarching themes, with a narrative synthesis to summarise the results. RESULTS: A total of 47 studies (31 experimental and 16 observational studies) were included (n=2 223 697 patients). All studies assessed the safety of virtual versus face-to-face consultations via one or both of the following domains: (1) factors that influence the safety of virtual consultations and (2) tangible outcomes of virtual care safety. The former were categorised into provider-related, patient-related and system-related factors. Tangible outcomes were evident through three subthemes-adverse events, health outcomes and patient perception of safety. CONCLUSIONS: This review provides a systematic synthesis of measures for the safety evaluation of virtual consultations. Further research into patient and physician perspectives is needed to identify aspects and indicators not captured in this study, followed by a consensus study to finalise safety metrics. Ultimately, having a robust methodology for safety evaluation of virtual consultations in place will enable safety monitoring, root cause analyses and safety improvement. PROSPERO REGISTRATION NUMBER: PROSPERO CRD42023464878.
20 May 2026
Read appraisal →European journal of preventive cardiology
Elevated blood pressure levels among 533 167 adults living in Sub-Saharan Africa: a systematic review and meta-analysis
AIMS: Synthesizing contemporary data from sub-Saharan African countries, we did a systematic review and meta-analysis of blood pressure (BP) levels and hypertension among adults living in the region. METHODS AND RESULTS: We searched PubMed and other databases to identify studies published from 1 January 2010 to 31 December 2021. We used a random-effects model to estimate the pooled-prevalence of hypertension and mean systolic/diastolic BP overall and on a sex- and age-specific basis. Heterogeneity (I²) was assessed via the χ² test on Cochran's Q statistic. We identified 170 high-quality studies (195 samples) comprising 533 167 adults living in 26 countries. The pooled prevalence of hypertension was 30.5% (95% CI 28.4-32.6%). Overall mean systolic/diastolic BP was 128 (95% CI 127-129)/80 (95% CI 79-80) mmHg, with males recording higher mean BP levels (3.10 [95% CI 2.30-3.90]/0.69 [95% CI 0.10-1.29] mmHg) compared with females. Reflecting increasingly higher BP levels with age, the pooled estimates of hypertension prevalence initially rose three-fold (from 10.6% [95% CI 8.2-13.0%] to 30.9% [95% CI 27.8-34.0%]) in those aged 21-30 to 41-50 years, and then two-fold to 66.4% (95% CI 64.2-68.7%) among those aged 71-80 years, respectively. Hypertension prevalence was lower in healthy weight [28.4% (95% CI 26.1-30.6%)] compared with overweight [35.8% (95% CI 31.4-40.1%)] adults. Regionally, prevalent hypertension was lowest in those living in Eastern Africa [27.2% (95% CI 24.8-29.7%)]. CONCLUSION: Our findings suggest a steep age-related pattern of increasing BP levels in the region that will adversely affect millions of people within the next 10-20 years without urgent intervention. A detailed review and analysis of 170 studies involving more than half a million adult men and women living in 26 sub-Saharan Africa countries, revealed that one in three have elevated blood pressure/hypertension.Elevated blood pressure levels, and the markedly increased risk of suffering a debilitating or fatal cardiovascular event at an early age, rose steeply from around one in ten affected at age 20–30 years to around one in three by the age of 50 years.Beyond the influence of age, the risk of having elevated blood pressure was different, given it increased markedly for overweight men and women, whilst those living in (mainly poorer) Eastern African countries had the lowest blood pressure levels.
16 May 2026
Read appraisal →The British journal of general practice : the journal of the Royal College of General Practitioners
Which transitions count? A systematic hermeneutic review of the literature on transitions of care.
BACKGROUND: Transitions of care are defined as critical moments along the care continuum for patients as they navigate changes in their health status or level of care. Researchers suggest that the existing research on transitions of care is largely descriptive and lacking in theoretical depth, which limits its application to different clinical contexts. AIM: We therefore aim to review the existing literature and theoretical frameworks on transitions of care, with a focus on primary care settings. METHOD: We undertook a systematic hermeneutic review - an approach that emphasises analytical reading, including identifying key concepts and building interpretations across a large and heterogeneous body of literature. Our initial search yielded 1640 articles, and we included 54 sources in our review. RESULTS: Despite interdisciplinary discussions, the main narratives of transitions of care centered around hospitals, with limited consideration for transitions in community settings. Moreover, using re-hospitalisation admission rates as the primary metric to measure the effectiveness of transitions of care initiatives fails to capture the negotiations required by patients and staff. This highlights the undercurrent of a positivist and biomedical approach, and the influence of broader health policy in shaping the methods and narratives used to define transitions. CONCLUSION: We consider this gap pertinent, given the increasing complexity of care delivered in community settings through remote chronic care models. In response, we suggest further engagement with theory to deconstruct our focus on settings and re-conceptualise transitions of care, which are also marked by changes in practices, materials, and people.
16 May 2026
Read appraisal →The British journal of general practice : the journal of the Royal College of General Practitioners
Perinatal mental health training and supervision for primary care and community-based staff: a systematic review
BACKGROUND: Perinatal mental health problems are common yet often under-detected and under-treated in primary care and community services. International guidelines call for integration of mental health into perinatal care, but clarity is lacking on how best to equip non-specialist providers. Training and supervision programmes exist but vary widely in content and delivery, and their effectiveness and feasibility across settings are not comprehensively synthesised. AIM: To evaluate the effectiveness of perinatal mental health training for primary care and community-based providers on provider competence, maternal outcomes, and implementation in routine care. METHOD: Seven databases and grey literature were systematically searched to September 2025. Eligible studies evaluated training delivered to health or community providers involved in perinatal care. Due to heterogeneity, findings were narratively synthesised. Risk of bias was assessed using RoB-2 and ROBINS-I; certainty of evidence appraised using GRADE. RESULTS: Of 707 citations screened, 39 studies were included, spanning high- and low-income countries and involving over 10,000 providers. Interventions varied in intensity and modality, including novel approaches such as extended reality simulation and cascade 'train-the-trainer' models. Training consistently improved provider knowledge, skills, attitudes, and confidence, and was associated with increased screening and referral, particularly when supported by supervision or system-level integration. Patient outcomes were less frequently assessed; where reported, some studies showed reductions in depressive symptoms and improvements in broader maternal outcomes, though findings were mixed. CONCLUSION: Training enhances provider capacity in perinatal mental health, but evidence on patient impact, sustainability, cost-effectiveness, and equity remains limited, highlighting priorities for future research and policy.
16 May 2026
Read appraisal →BMJ open
AI chatbots for health information seeking among Chinese patients with precancerous ENT lesions: a descriptive qualitative study
OBJECTIVE: To explore how Chinese patients with precancerous ear, nose and throat (ENT) lesions experience using artificial intelligence (AI)-driven chatbots for health-related information seeking, with particular attention to perceived benefits, challenges and influences on information-seeking practices. DESIGN: Descriptive qualitative study. SETTING: Department of Otolaryngology, West China Hospital, Sichuan University, China. PARTICIPANTS: 12 adult patients with clinically diagnosed precancerous ENT lesions who had used AI-driven chatbots at least three times in the previous 30 days to seek health-related information about their condition were purposively recruited. Face-to-face, semistructured interviews were conducted between 11 October 2024 and 10 November 2024. RESULTS: Interviews were analysed using Colaizzi's method. Four themes were identified. First, participants described AI chatbots as an immediate and accessible source of health information, particularly when questions arose outside clinical encounters or during periods of uncertainty. Second, many reported moving away from conventional search engines towards conversational information seeking, valuing direct and synthesised responses over link-based retrieval. Third, participants emphasised that obtaining useful answers depended on learning to ask clear and specific questions, suggesting that effective prompting was an important user skill. Fourth, some participants perceived chatbot interaction as emotionally safer than asking healthcare professionals certain questions, particularly when they felt embarrassed, worried about asking repetitive questions or feared being judged. CONCLUSIONS: Among this sample of Chinese patients with precancerous ENT lesions, AI-driven chatbots were perceived as a convenient and conversational supplementary source of health information. Participants valued their accessibility and interactional ease, but also indicated that their usefulness depended partly on users' ability to formulate effective prompts. Some participants additionally perceived chatbots as a more comfortable channel for asking sensitive or basic questions. The findings suggest that AI chatbots may have a complementary role in patient information support, but further research is needed to evaluate response accuracy, safety and appropriate integration into clinician-led care.
15 May 2026
Read appraisal →Journal of cross-cultural gerontology
Mapping the Use of Information and Communication Technologies in Health Interventions for Older Adults: A Rapid Review
This rapid review mapped how information and communication technologies (ICTs), particularly digital health applications, are being used within healthcare services for adults aged 55 years and older. Following the Joanna Briggs Institute methodology and guided by the Population-Concept-Context framework, studies published between 2016 and 2024 were identified and reported in accordance with the PRISMA extension for scoping reviews, based on a previously published protocol registered on the Open Science Framework. Nineteen studies were included after critical appraisal. The findings indicate that ICT use is most frequently associated with improved accessibility and coordination of healthcare services, support for health professionals' training and care management practices, and positive health-related outcomes for older adults, particularly in the domains of mental health, social participation, and self-care. However, the evidence remains heterogeneous and often limited in its reporting of design and implementation processes, highlighting the need for further context-sensitive research that addresses ethical, equity, and implementation considerations in the use of digital health technologies for older populations.
14 May 2026
Read appraisal →JMIR medical informatics
Scalable Identification of Clinically Relevant Chronic Obstructive Pulmonary Disease Documents in Large-Scale Electronic Health Record Datasets With a Lightweight Natural Language Processing Model: Retrospective Cohort Study
BACKGROUND: The widespread adoption of electronic health records has resulted in the generation of large volumes of clinical notes. Learning algorithms and large language models can be trained on these resources, but they are susceptible to noise-irrelevant or noninformative data. This sensitivity can lead to significant challenges, including performance degradation and the generation of inaccurate predictions or "hallucinations." This study addresses a critical challenge in clinical informatics: efficiently filtering millions of documents for relevance before advanced language model processing, particularly in resource-constrained environments. OBJECTIVE: We present a novel framework for determining document relevance in clinical settings using a chronic obstructive pulmonary disease (COPD) dataset. METHODS: We developed a novel framework using weak supervision and domain-expert heuristics to generate "silver standard" labels for training data and gold standard expert-annotated labels, creating 2 datasets to optimize the model during the development phase and subsequent testing phase. Various text representation techniques (bag of words, term frequency-inverse document frequency, lightweight document embeddings, compression-based features, and Unified Medical Language System concept extraction) were evaluated. These representations were used to train random forest, extreme gradient boosting, and k-nearest neighbor classifiers. Models were optimized on a small expert-annotated dataset and evaluated on a held-out test set. RESULTS: The combination of lightweight document embedding with a random forest classifier demonstrated the best performance, achieving a precision of 0.73, recall of 0.86, and F1-score of 0.80 (95% CI 0.76-0.87) for identifying relevant COPD documents. This significantly outperformed baseline heuristics (precision=0.70; recall=0.38; F1-score=0.50, 95% CI 0.43-0.56) and other tested methods. CONCLUSIONS: Our study presents a novel framework for identifying COPD-relevant clinical documents using lightweight embedding and machine learning. This approach effectively filters pertinent documents, enhancing information retrieval precision. The framework's scalability and minimal annotation needs make it promising for diverse health care applications, potentially optimizing clinical outcomes through efficient document selection for data-driven decision support systems.
14 May 2026
Read appraisal →Current nutrition reports
Digital Solutions for the Control of Lifestyle Parameters in Individuals With High Cardiometabolic Risk: a Scoping Review
BACKGROUND: Digital technologies are increasingly used to promote healthier behaviors and prevent noncommunicable diseases (NCDs). Diet and physical activity are key determinants of cardiometabolic health, where digital tools can support self-monitoring and behavior change. OBJECTIVE: This scoping review aimed to evaluate the effectiveness of digital health technologies in improving diet quality and adherence, assessing body composition, and promoting physical activity among adults at cardiometabolic risk. METHOD: A systematic search was performed in Web of Science and PubMed (2000-2025) following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews (PRISMA-ScR) guidelines and the PICo framework. Inclusion criteria focused on digital solutions for diet and exercise in adults with overweight, obesity, or metabolic complications. RESULTS: 15 studies were included (8 randomized controlled trials, 2 pilot studies, and 5 validation studies). Most intervention studies reported significant improvements in weight reduction, body mass index, or waist circumference, especially when mobile applications or wearable devices were combined with personalized feedback. Validation studies confirmed a high reliability of AI-based image analysis tools for estimating body composition compared with DXA. Improvements in dietary adherence and physical activity levels were also observed in several studies. However, heterogeneity in study design, short follow-up duration, and variability in outcome measures limited comparability across studies. Major gaps included limited long-term evidence, scarce use of AI-driven personalized interventions, insufficient reporting of measurement validity, and underrepresentation of vulnerable populations. CONCLUSION: Digital health technologies, including mobile apps, wearables, and AI-based systems, show promising potential as a complementary tool to clinician-guided care. They can enhance dietary adherence, promote self-monitoring, and support healthier lifestyles, although their long-term effectiveness remains to be confirmed. Future research should prioritize long-term randomized trials, standardized outcomes measures, validation of AI-based tools in diverse populations, and structured integration of digital interventions into clinical pathways.
14 May 2026
Read appraisal →JMIR research protocols
Evaluating Patient-Entered Electronic Health Data as a Strategy to Improve Quality of Care in a Diabetes Clinic: Protocol for a Randomized Controlled Trial
BACKGROUND: Quality care for pediatric type 1 diabetes (T1D) requires frequent, multidisciplinary visits. Technological and clinical innovation have led to changes in T1D management, resulting in increasing data exchange required during these visits. Capturing comprehensive personal health and diabetes-related information discretely and integrating it into the clinical workflow is critical for optimal T1D care but is time-consuming. Time spent on data transfer often results in less time for holistic care and can lead to unmet needs for patients, families, and health care providers, as well as increased time pressures in clinic. To address this, the Children's Hospital of Eastern Ontario developed a caregiver proxy-reported questionnaire distributed via the MyChart patient portal, allowing families to input care information ahead of visits with the aim of dedicating more clinic time to personalized care. The launch of this tool, which integrates caregiver-entered information into the physician's documentation workflow, brings the opportunity to systematically evaluate its impact on care quality and efficiency, with potential implications for broader adoption. OBJECTIVE: Our objective is to evaluate the impact of a caregiver proxy-reported, electronic health record-integrated preclinic questionnaire (MyChart questionnaire) on the quality of care in a pediatric diabetes clinic, through measurement of its impact on caregiver-perceived quality of care compared to the standard of care using 2 validated measures of care quality. We also aim to explore the impact of the intervention on glycemic control and visit efficiency. METHODS: We conducted a single-center, parallel-group randomized controlled trial designed for 222 children with T1D. Participants were randomly allocated in a 1:1 ratio to either the intervention (MyChart questionnaire) or standard care. Our primary outcome is caregiver-perceived quality of care, as measured by the Patient's Evaluation of the Quality of Diabetes Care at 8 months, administered with caregivers serving as proxy respondents for patients. Secondary outcomes are the Patient's Evaluation of the Quality of Diabetes Care at 4 months and Perceived Quality of Medical Care at 4 and 8 months. Tertiary outcomes include glycemic control and physician-reported visit efficiency at 4 and 8 months. Analysis of covariance models will be used to assess changes between baseline and postintervention outcomes across treatment groups. RESULTS: Recruitment for this study began in April 2023 and was completed in February 2024, with a total of 139 participants enrolled. Data collection has concluded, and the first results are expected in the spring of 2026. CONCLUSIONS: This study is the first randomized trial to assess the impact of a caregiver proxy-reported, electronic health record-integrated, preclinic questionnaire distributed via a patient portal on caregiver-perceived quality of care in a pediatric care setting. The results will guide changes in health service infrastructure and delivery to enhance comprehensive data capture and improve care quality within and beyond pediatric T1D.
13 May 2026
Read appraisal →JMIR mHealth and uHealth
Efficacy and Safety of a Telemedicine System in Patients With Gestational Diabetes Mellitus (TELEGLAM): Single-Center, 2-Arm, Randomized, Open-Label, Parallel-Group Study
BACKGROUND: In the management of gestational diabetes mellitus (GDM), the usual medical treatment requires frequent visits for glucose monitoring and insulin dose adjustment, and this imposes significant physical, psychological, and economic burdens on pregnant women. As mobile health platforms become increasingly integrated into diabetes care, telemedicine may help alleviate these burdens; however, evidence evaluating its effectiveness as a replacement for routine in-person GDM care remains limited. OBJECTIVE: This study aims to evaluate the impact of telemedicine on the quality of life and costs for patients with GDM requiring insulin therapy. METHODS: This single-center, 2-arm, randomized, open-label, parallel-group study included patients with GDM who started insulin injection therapy. Participants were randomized to either the telemedicine or standard face-to-face care groups for 10 (SD 2) weeks. The telemedicine intervention used a smartphone-linked platform that enabled the automatic transfer of glucose data from connected glucose meters and facilitated real-time video consultations. Primary end points included costs and patient satisfaction. Costs were assessed using claims data, transportation calculations, and wage-based productivity losses, while patient satisfaction was evaluated through changes in the Problem Areas in Diabetes Survey and Diabetes Therapy-Related Quality of Life questionnaire scores. Secondary outcomes included glycemic control and perinatal outcomes. RESULTS: In total, 38 participants were included, with 18 assigned to the telemedicine group and 20 to the standard care group. Total costs (32,712, 95% CI 15,412-50,013 vs 59,202, 95% CI 42,603-75,800 Japanese yen; $284, 95% CI 134-435 vs $515, 95% CI 370-659, purchasing power parity [PPP]-adjusted; P=.01), direct non-health care costs (922, 95% CI -240 to 2084 vs 2561, 95% CI 1447-3676 yen; $8, 95% CI -2 to 18 vs $22, 95% CI 13 to 32 PPP-adjusted; P=.02), and indirect costs (8981, 95% CI -7119 to 25,082 vs 32,832, 95% CI 17,384-48,279 yen; $78, 95% CI -62 to 218 vs $285, 95% CI 151-420 PPP-adjusted; P=.01) reduced significantly in the telemedicine group compared with the standard care group. The improvements in the Problem Areas in Diabetes Survey (-7.6, 95% CI -13.7 to -1.4; P=.02) and Diabetes Therapy-Related Quality of Life domain 1 (10.5, 95% CI 0.9-20.1; P=.03) scores from the baseline were significantly greater in the telemedicine group than that in the standard care group. Nonetheless, glycemic control and frequency of perinatal complications were comparable between the 2 groups. Consultation time was similar across groups, suggesting no added workload for clinicians. CONCLUSIONS: In this randomized trial, mobile health-enabled telemedicine safely replaced routine in-person visits for patients with GDM requiring insulin therapy. Telemedicine significantly reduced psychological and economic burdens without compromising glycemic or perinatal outcomes, demonstrating its value as a patient-centered and cost-efficient model of care. These findings support the broader implementation of mobile-based telemedicine approaches in GDM management.
12 May 2026
Read appraisal →JMIR medical informatics
Machine Learning-Based Multidimensional Oximetry for Obstructive Sleep Apnea Screening: Development and External Validation
BACKGROUND: Obstructive sleep apnea (OSA) affects nearly one billion people globally and poses a substantial public health threat. Effective and accessible methods for OSA risk identification are urgently needed. OBJECTIVE: This study aims to develop and externally validate a machine learning model derived from multi-parameter pulse oximetry (SpO2) for OSA screening, and to evaluate its performance, interpretability, and robustness across sex and age subgroups. METHODS: Of 4156 screened participants, 2195 underwent polysomnography (internal cohort) and 446 received home sleep apnea testing (external cohort). Eight SpO2-derived parameters, including oxygen desaturation index (ODI), hypoxic burden (HB), and ST90 (percentage of sleep time with SpO2 < 90%), were used to construct models. Six machine learning algorithms were trained, with F1-score as the primary metric and area under the curve as the secondary metric. Model interpretability was assessed using Shapley additive explanations and intrinsic feature importance scores. RESULTS: Nonlinear parameter-risk relationships were observed between oximetry indices and OSA probability. The 4-parameter ODI-HB-MinSpO2-ST90 model achieved optimal performance (F1-score = 0.9516, area under the curve = 0.9879), surpassing all single-parameter models. Shapley additive explanations analysis identified ODI, HB, and MinSpO2 as key predictors. The ODI-HB-MinSpO2-MeanSpO2 configuration demonstrated superior performance in female and younger subgroups, whereas the ODI-HB-MinSpO2-ST90 model remained optimal for male and older participants. Categorical boosting outperformed other algorithms across multiple metrics and remained robust in both subgroup and external validation analyses. CONCLUSIONS: The multi-parameter oximetry model based on the categorical boosting algorithm provides a simple and accurate tool for OSA screening. Sex- and age-stratified strategies can further enhance its clinical applicability.
12 May 2026
Read appraisal →Scandinavian journal of primary health care
Identifying factors influencing acceptance of artificial intelligence among general practitioners in Danish general practice: a cross-sectional web-based survey study
BACKGROUND: Despite rapid advances in artificial intelligence (AI), its adoption in Danish general practice remains limited and decentralized, relying on individual general practitioners' (GPs') decisions. This study aimed to evaluate Danish GPs' acceptance of AI and the importance of factors derived from established technology-acceptance models. METHODS: A cross-sectional web survey was conducted from mid-September 2024 to March 2025, using a culturally adapted version of a previously validated tool. The survey included 42 items: nine background items and 33 items covering 11 factors, including Medical and Non-Medical Performance Expectancy, Effort Expectancy, Social Influence (Medical and Patient), Facilitating Conditions, Perceived Trust, Anxiety, Professional Identity, Innovativeness and Behavioral Intention. Descriptive statistics, subgroup comparisons and Cronbach's alpha were provided. RESULTS: A total of 109 GPs and residents responded, with 84.4% (n = 92) completing the survey. Attitudes toward AI were generally neutral to positive, with mean scores above neutral in seven of the 11 factors. The most positive factors measured were Medical and Non-Medical Performance Expectancy. Scores related to Behavioral Intention were also high. Lower scores appeared in Perceived Trust, Facilitating Conditions and Anxiety. Older GPs (60 years and above) reported lower scores on Non-Medical Performance Expectancy and Social Influence (Medical); GPs in smaller cities showed more positive attitudes across several factors. Cronbach's alpha indicated good internal consistency on all but two scales. CONCLUSION: In summary, Danish GPs demonstrate a strong intention to adopt AI. However, issues persist as significant barriers regarding Anxiety, Perceived Trust and Facilitating Conditions. Implementation strategies considering context and clinician demographics are recommended.
11 May 2026
Read appraisal →Monaldi archives for chest disease = Archivio Monaldi per le malattie del torace
Prevalence of urinary incontinence in patients with chronic cough: a systematic review
Chronic cough-related diseases increase the risk of urinary incontinence (UI) due to repeated intra-abdominal pressure affecting the pelvic floor. Existing studies focus on specific diseases rather than UI as a broader consequence. To determine the prevalence of UI in patients with chronic cough-related diseases and compare it with the prevalence in healthy populations. A systematic review was conducted using Medline, Embase, Cochrane, OVID, Scopus, ProQuest, PEDro, and EBSCO. Two independent reviewers screened studies using predefined criteria in a Microsoft Excel spreadsheet. Only prevalence studies were included. Data were extracted, synthesized, and assessed using the GRADE approach for evidence quality and the STROBE checklist for reporting quality. Prevalence estimates varied widely based on demographic characteristics. UI prevalence ranged from 2.2% to 45% in pediatric patients, 30.4% to 74% in adult women, and 2.4% to 39% in adult men. The quality of evidence was low, while reporting quality was acceptable. UI is a common complication in patients with chronic cough, with a higher prevalence than in healthy populations. Due to the stigma surrounding urogenital disorders, clinicians should actively inquire about UI during patient history-taking and refer affected individuals for appropriate treatment.
11 May 2026
Read appraisal →BMJ open
Potential harms of social prescribing: a global umbrella review and dark logic model
OBJECTIVES: Social prescribing has provided a lifeline to people, capturing the importance of quality support offered via community connections. It has not been exempt from difficulties, resulting in low-quality evidence on effectiveness in part due to high drop-out rates and lack of controls. While these have been the focus of recent research, less attention has been paid to the safety implications of social prescribing. This review aims to understand safety implications of social prescribing interventions and to build a dark logic model of how harms are produced. DESIGN: Using review of review (umbrella) methodology, we searched nine databases to June 2024. DATA SOURCES: Medline/Ovid, Embase, PsycINFO, Cochrane Library/Wiley, Web of Science and Scopus) were searched from 1 January 2010 to 3 June 2024. ELIGIBILITY CRITERIA: Included reviews were systematic/scoping/narrative reviews or meta-analyses, which synthesised primary data collected from any person in receipt, involved in delivery or the commissioning of social prescribing interventions. The context of the review was social prescribing interventions/services based in primary healthcare (statutory) or third sector (non-statutory) in any country. Only reviews that were published in English and in peer-reviewed journals were included. DATA EXTRACTION AND SYNTHESIS: Two independent reviewers extracted data from included reviews using the Typology of Harms Framework (which includes five categories of harms associated with interventions: physical, psychological, group/social, equity and opportunity harms) and to build a dark logic model to understand what contributes to these harms. RESULTS: Sixteen reviews were included, reporting on social prescribing research including a link worker. Of the identified harms, we found that opportunity harms (harm related to the cost, inappropriate or ineffective interventions) were most reported. There was also evidence extracted to suggest plausible psychological, equity (impact caused by inequity in provision, delivery or access) and group/social harms (impact that overly or inadvertently excludes a person). No physical harms were identified. CONCLUSIONS: Social prescribing, as with any delivery of care, has the potential to cause harm. We identified a range of potential harms (psychological, group/social, equity or opportunity harm) from social prescribing; however, it is unlikely to be an exhaustive list. We provide two clear outcomes: (1) the need for robust design of social prescribing research, including collection of data on the incidence and prevalence of harms, (2) recognition of the potential for harm from social prescribing and to address these where practicable.
11 May 2026
Read appraisal →JMIR formative research
The Role of Trust in Text Messaging for Promoting Patient Portal Activation Among Low-Income Patients: Quality Improvement Project
BACKGROUND: The increasing reliance on patient portals for electronic health records has widened the digital health care access gap, particularly among low-income and Medicaid-insured populations. However, resources exist to assist low-income patients with portal enrollment; in obtaining a free smartphone; and, in New York, in obtaining low-cost internet. Automated bidirectional SMS text messaging offers a scalable and cost-effective strategy for identifying low-income patients' digital health needs and eligibility for resources by using screening questions and providing tailored information on how to access available resources. OBJECTIVE: This study aimed to increase portal access among low-income patients using automated bidirectional SMS text messaging and assess its feasibility and acceptability. METHODS: This quality improvement initiative involved sending automated, bidirectional SMS text messages in English to 12,381 Medicaid-insured and/or low-income patients from a primary care practice. Messages assessed patients' digital health needs and provided adaptive, personalized resources and assistance for enrolling in the patient portal and for accessing digital technology. We assessed response rates and follow-up portal enrollment rates. We surveyed participants regarding the acceptability, appropriateness, and usability of the SMS text messaging intervention, as well as their subsequent use of the patient portal. We performed descriptive statistics and a binomial probability test. RESULTS: In total, 9.2% (1140/12,381) of patients responded to the SMS text messages, with 3.9% (481/12,381) opting out and 5.3% (659/12,381) actively engaging. Among respondents, 71.1% (469/659) completed the follow-up survey. Respondents were predominantly female (336/469, 71.6%), with ages ranging from 18 to 65 years or older. Most respondents rated the message's clarity (420/469, 89.6%), its usefulness (400/469, 85.2%), and the demonstration of care by their health team (350/469, 74.6%) favorably. Concerns regarding privacy (61/469, 13%) and trustworthiness (71/469, 15%) were noted. Notably, 71% of initially unenrolled patients activated their patient portals after the intervention (P=.007), exceeding the hypothesized expectations. CONCLUSIONS: Automated bidirectional SMS text messaging had mixed effects on promoting patient portal use among low-income patients. Response rates to SMS text messages were low when delivered from an unknown phone number. Among responders, most reported that these messages were useful and that they would recommend them to others. Research is needed to determine optimal strategies for introducing the program and vendor phone numbers to patients to improve engagement.
11 May 2026
Read appraisal →Scientific reports
Hybrid deep learning and YAMNet features for asthma diagnosis from respiratory sounds
A prompt and precise diagnosis is necessary to lessen the worldwide burden of asthma, a common chronic respiratory condition. Spirometry is one of the resource-intensive conventional methods that frequently misclassifies cases because of overlapping symptoms with other respiratory illnesses. The Asthma Detection Dataset v2, which is openly accessible and comprises actual audio recordings of respiratory noises, is used in this work to demonstrate a hybrid deep learning architecture for automated asthma detection. After applying thorough preprocessing, which includes denoising, segmentation, and augmentation, the suggested pipeline employs a dual-path feature extraction technique that combines pretrained YAMNet embeddings with handmade acoustic descriptors (MFCCs, chromagram, ZCR, and spectral features). Atrous Spatial Pyramid Pooling (ASPP) and Squeeze-and-Excitation (SE) modules are used to further improve these embeddings, and a Multi-Layer Perceptron is used for classification. The proposed model achieved high performance, with an accuracy of 98.6% ± 0.14, an F1-score of 97.5% ± 0.14, and a macro-AUC of 99.1% ± 0.14 using stratified 5-fold cross-validation. SHAP-based interpretability and visualization (waveforms, spectrograms, t-SNE) verified that the model records clinically significant auditory biomarkers such as crackles and wheezes. These results indicate the potential of the proposed model as an explainable and scalable computer-aided asthma diagnostic tool.
3 May 2026
Read appraisal →JMIR aging
The Effectiveness of Digital Interventions to Increase Preventive Care Uptake in Older Adults: Systematic Review
BACKGROUND: Older adults face increasing health risks associated with aging and chronic disease; yet, uptake of recommended clinical preventive services remains low. Digital health interventions have the potential to enhance access and engagement, but their effectiveness in older adult populations remains unclear. OBJECTIVE: This systematic review aimed to examine the range and types of digital clinical preventive service interventions and assess their impact on preventive care uptake among older adults. METHODS: We conducted a systematic review of peer-reviewed research literature published since 2014. Eligible studies included experimental and quasi-experimental designs evaluating digital interventions targeting community-dwelling adults aged 60 years and older. Interventions focused on high-priority preventive services, including cancer screening and adult immunizations. Data were extracted using a standardized form and synthesized narratively due to heterogeneity in study designs and outcomes. RESULTS: In total, 24 studies involving over 1.3 million participants from 11 countries were included. Interventions used a range of digital tools, including telephone calls, SMS text messages, patient portals, and video-based education. While some digital and automated interventions demonstrated modest improvements in preventive services uptake, results were mixed. Interventions incorporating personalized elements (eg, tailored telephone counseling or in-person education) were generally more effective than generic, automated communications. Few studies reported on digital literacy support or intervention reach, and engagement with digital platforms was often low. CONCLUSIONS: Digital interventions can support modest improvements in preventive services uptake among older adults, particularly when personalized or combined with human interaction. However, assumptions of digital fluency and limited reporting on engagement constrain generalizability. Future research should prioritize inclusive design, detailed reporting, and strategies that address digital equity to better support older adult populations.
3 May 2026
Read appraisal →European respiratory review : an official journal of the European Respiratory Society
Oscillometry for the diagnosis of asthma in children: a systematic review
BACKGROUND: Diagnosing asthma in children and young people (CYP) remains challenging. Oscillometry is a promising tool and is feasible from 2 years of age. European Respiratory Society (ERS) technical standards and bronchodilator response (BDR) oscillometry thresholds have been published, but diagnostic accuracy is not established. METHODS: We systematically reviewed studies comparing oscillometry and spirometry in CYP under investigation for asthma. Reference standards were positive BDR or positive methacholine challenge test (MCT). Primary aims were to investigate the sensitivity and specificity of current ERS oscillometry thresholds (>40% decrease in resistance at 5 Hz (R 5), >50% increase in reactance at 5 Hz (X 5) or >80% decrease in the area under the reactance curve); secondary aims were to identify oscillometry threshold values optimising both sensitivity and specificity. RESULTS: 11 studies were included; six (n=992 CYP) utilised BDR and five (n=531 CYP) MCT as reference standard. Meta-analysis was not possible due to heterogeneity of results reported. In two studies using current ERS BDR thresholds, zero sensitivity and high specificity (>85%) were observed. In weighted regression analyses of BDR studies, a 17.0% decrease in resistance at 5-6 Hz had sensitivity and specificity of 71.6% (95% CI 69.7-73.7%); a 20.2% increase in X 5 had sensitivity and specificity of 68.6% (95% CI 66.6-70.8%). Similarly, 27.7% increase in R 5 had sensitivity and specificity of 73.6% (95% CI 71.9-75.3%) for MCT. CONCLUSION: Currently recommended ERS thresholds for oscillometry BDR have low sensitivity. Proposed thresholds for defining positive BDR and MCT by oscillometry require prospective validation and adoption of standards for measuring and reporting oscillometry parameters in future diagnostic comparative studies.
3 May 2026
Read appraisal →JMIR medical informatics
Leveraging MedlinePlus to Improve Health Information Access Among Patients and Caregivers: Systematic Literature Review
BACKGROUND: MedlinePlus, developed by the National Library of Medicine (NLM) in the United States, is one of the most widely used, authoritative, consumer-grade health information resources on the web. Although extensively used and discussed in scholarly work for health literacy and patient education, it is unclear how MedlinePlus has been integrated into clinical care or embedded within health informatics applications. OBJECTIVE: This study aimed to understand how MedlinePlus has supported patients and caregivers by increasing access to health information for clinical care and illness management. The insights on this topic will inform the design and development of patient-facing digital health intervention tools for improved health communication, decision engagement, informed decision-making, and health outcomes. METHODS: We conducted a systematic literature review following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. First, we developed a comprehensive literature search strategy, searched 9 citation databases, and aggregated and deduplicated search results before importing them into Covidence for manual screening using predefined inclusion and exclusion criteria. Second, reviewers independently assessed all studies at the title-abstract and full-text levels, resolving discrepancies through ongoing discussions. Third, we applied the PICO (problem/population, intervention, comparison, and outcome) and the Collaborative Chronic Care Model as guiding frameworks for data extraction and analysis. All included studies underwent quality assessment using the Mixed Methods Appraisal Tool. RESULTS: In total, 28 studies reported in 27 sources met our inclusion criteria. We categorized the extracted data into 4 areas. First, regarding bibliometrics, the studies were reported between 2004 and 2024, with 2010 having the highest number of studies. Of these studies, 25 were conducted in the United States, 2 were conducted in Iran, and 1 was conducted in Argentina. Health informatics journals and conference proceedings, as well as library science journals, were prominent publishing venues. The NLM funded half of the studies. Second, regarding participants, most studies focused on outpatients. Other participant roles included physicians, nurses, hospital staff, pharmacists, and librarians. Fewer than half of the studies addressed the social determinants of health. Third, regarding intervention, most studies implemented MedlinePlus information interventions within clinical settings. Other interventions occurred in community pharmacies, community organizations, libraries, online health platforms, or patient portals. Fourth, regarding outcome, only 4 studies assessed clinical outcomes, and the findings were mixed and inconsistent. However, 24 of 28 studies reported positive nonclinical outcomes, including improved attitudes toward and satisfaction with MedlinePlus and enhancements in patients' information-seeking behaviors, confidence, and willingness to engage in decision-making, physician-patient communication, self-management, and self-efficacy. CONCLUSIONS: This systematic literature review is the first comprehensive examination of how MedlinePlus has been integrated into clinical care, supporting patients and caregivers with enhanced access to health information. Our findings offer evidence and insights through the Collaborative Chronic Care Model lens and can guide the development of digital health interventions to improve patient health.
3 May 2026
Read appraisal →Scandinavian journal of primary health care
Overdiagnosis in atrial fibrillation screening with wearables
PURPOSE: Wearable technologies are increasingly used to screen for atrial fibrillation (AF), often outside formal clinical pathways. While this holds promise for early detection, the impact on patient outcomes remains unclear. We aimed to examine the hypothesis whether intermittent and continuous AF screening using wearable-like technologies leads to overdiagnosis in asymptomatic, high-risk individuals. METHODS: This hypothesis-generating analysis draws on available RCTs screening asymptomatic, high-risk individuals for AF using wearable-like ECG technologies. It is not a systematic review, as the field remains too early-stage for formal evidence synthesis. Eligible studies included either intermittent (≥10 recordings) or continuous monitoring for ≥1 week, reflecting typical smartwatch use. Primary outcomes included AF diagnoses, anticoagulant use, and adverse events. Overdiagnosis was inferred when excess AF detection did not translate into improved clinical outcomes. Analyses used Mantel-Haenszel random-effects models. RESULTS: Continuous screening nearly tripled AF diagnoses (OR 2.84; 95% CI, 1.61-5.02) and doubled anticoagulant use compared to controls. Intermittent screening showed a non-significant 1.8-fold increase. Neither method significantly reduced adverse outcomes. A pooled analysis revealed a marginal reduction in negative events (OR 0.94, 95% CI 0.90-0.99). Overdiagnosis estimates varied by method, ranging from 8-29% based on persistent differences in cumulative incidence after the screening period has ended and 47-65% based on increased diagnoses and treatment during the screening phase that are not followed by improved patient-relevant outcomes. CONCLUSION: Wearable-enabled screening for AF in high-risk patients increases diagnosis and treatment without clear benefit in clinical outcomes. These findings support the hypothesis of overdiagnosis and findings highlight the need for cautious integration of consumer technologies into primary care. Further trials with extended follow-up in low-risk populations are needed to clarify when AF detection improves outcomes versus when it leads to unnecessary medicalisation and harm.
30 Apr 2026
Read appraisal →BMJ health & care informatics
i-MoMCARE: AI-enabled mobile app for maternal and child health care in Cambodia - a pilot implementation and evaluation study
OBJECTIVES: In Cambodia, village health support groups (VHSGs) are central to maternal and child health (MCH) service delivery, yet maternal mortality remains high with regional disparities. Although digital health solutions show promise, their real-world use is underexplored. This study therefore aims to evaluate the i-MoMCARE app in supporting VHSGs and health centre staff for delivering MCH services. METHODS: A mixed-methods approach guided by the Reach, Effectiveness, Adoption, Implementation and Maintenance (RE-AIM) framework was used. Reach was assessed using programme records (number of users trained and MCH cases managed). Effectiveness and adoption were evaluated using the mHealth App Usability Questionnaire (MAUQ) and qualitative data on user experience and intention to use. Implementation was examined through system usage monitoring and feedback on workflow integration. Maintenance was explored using qualitative insights on long-term use, barriers and recommendations. RESULTS: 44 VHSGs and 10 health centre staff were trained, and 96 MCH cases were managed with the app. Usefulness was rated highly (MAUQ 5.58, SD 1.04), with users appreciating the user-centric design that improved usability and integration into daily workflows. Effectiveness was similarly high (MAUQ 5.50, SD 0.95); the clinical decision support system and point-of-care alerts were valued as reliable decision-support tools, and the electronic medical record (EMR) was seen as a secure data repository. However, adoption was hindered by hardware and software limitations (MAUQ 5.79, SD 0.75), including device availability and low digital literacy. DISCUSSION: Our findings highlight the value of the i-MoMCARE app in supporting VHSGs, particularly those with limited training, by enhancing their decision-making. The study also lays the groundwork for a unified EMR in primary care. However, concerns around hardware and software limitations hinder adoption and sustained use. CONCLUSION: To enable scale-up, we recommend reducing access barriers and supporting sustained use through diversifying the platform's design and implementing phased incentivisation strategies.
27 Apr 2026
Read appraisal →JAAPA : official journal of the American Academy of Physician Assistants
Barriers to hearing aid adoption in hearing loss
More than one-fifth of the US population has hearing loss, a condition associated with higher risk of falls, depression, isolation, cognitive decline, dementia, and all-cause mortality. Treatment of hearing loss has been shown to correlate with decreased risk of cognitive decline, dementia, and mortality, as well as an improved quality of life. Surprisingly, however, fewer than 1 in 10 Americans with hearing loss use hearing aids. As the prevalence and burden of hearing loss grow, clinicians must understand factors influencing hearing aid use to increase treatment rates. This article reviews key barriers to hearing aid adoption-including low hearing health knowledge, inadequate screening, stigma, cost, and difficulty of use-and discusses recent changes that may influence these barriers.
27 Apr 2026
Read appraisal →Journal of medical Internet research
Exploring Attitudes Toward AI-Based Contactless Sensors in Health Among Five Stakeholder Groups: Qualitative Study
BACKGROUND: The rapid rise of artificial intelligence-based contactless sensors (AI-CS) is expected to significantly transform how patients are measured, monitored, and understood through a versatile, noninvasive approach to data collection and health assessment. However, there is a lack of empirical research specifically focusing on AI-CS in health. Moreover, existing studies tend to focus on medical or patient perspectives, while neglecting other stakeholders such as researchers, political actors, or the general public. OBJECTIVE: The study aims to provide an in-depth empirical ethical analysis and, through a multistakeholder approach, a uniquely comprehensive overview by addressing the research question: what are the attitudes of different stakeholders (patients, health care professionals, researchers, political stakeholders, and the general public) toward AI-CS and their applications in health? METHODS: We conducted a cross-sectional study with 104 participants using a semistructured interview guide. Interviews were analyzed using qualitative content analysis with ATLAS.ti software (ATLAS.ti Scientific Software Development GmbH), following a 3-component model of feelings, thoughts, and behavioral aspects. RESULTS: The results of the study provide an in-depth analysis of attitudes toward AI-CS in health among different stakeholders. Overall, the results show a high level of openness to AI-CS in health across all stakeholder groups. In terms of feelings and their correlation with behavioral aspects, 2 key trends emerged: first, greater experience and knowledge correlated with a reduced tendency to react emotionally. Second, participants with positive experiences with technologies were generally more open and positive toward contactless sensors. The combined findings on thoughts and behavioral aspects highlighted 3 key tensions-around contact(lessness) and the importance and ambivalence of touch, between protection and surveillance (particularly regarding path- and context-dependency) and between the benefits and challenges of unobtrusiveness (especially in relation to control and governance implications). In addition, the analysis revealed the need for information and consent about AI-CS and clarified possible technical implementations and fields of application. CONCLUSIONS: This study provides a comprehensive and empirically grounded ethical analysis of stakeholder attitudes toward AI-CS in health. The findings offer valuable guidance for the responsible development, implementation, and governance of AI-CS in health care contexts.
27 Apr 2026
Read appraisal →European journal of preventive cardiology
Economic evaluation of alternative cardiac rehabilitation programmes compared to centre-based cardiac rehabilitation programmes: a systematic review.
AIMS: Traditional centre-based cardiac rehabilitation (CBCR) has several drawbacks, including high costs, limited accessibility, and low utilisation rates. As a result, alternative cardiac rehabilitation programmes (ACRPs), such as home-based rehabilitation and telerehabilitation, have been developed. This systematic review aims to synthesise existing evidence on the economic evaluation of ACRPs compared to CBCR. METHODS AND RESULTS: We searched databases of MEDLINE, Embase, CINAHL, Cochrane CENTRAL, Web of Science, and EconLit, as well as trials registers of Clinicaltrials.gov, International Clinical Trials Registry Platform, and EU Clinical Trials Register. The last search date was 20 March 2025. We included randomised controlled trials that directly compared ACRP with CBCR in terms of cost and effectiveness. Study quality was assessed using the Cochrane Risk of Bias tool and the Drummond 10-item checklist. Both qualitative and quantitative syntheses were conducted, with random-effects models applied in the meta-analysis. Thirteen studies met the inclusion criteria, comprising 2040 participants. Meta-analysis showed a non-significant trend favouring CBCR over ACRP for EQ-5D (SMD = -0.32; 95% CI: -0.71 to 0.06; I2 = 79%). For QALY, there was no difference between ACRP and CBCR (SMD = -0.02; 95% CI: -0.19 to 0.15; I2 = 0). Ten of the thirteen studies reported lower costs for ACRP compared with traditional CBCR. Three of five economic evaluations found ACRP to be cost-effective. CONCLUSION: ACRPs demonstrate cost-effectiveness comparable to traditional CBCR. This review highlights the potential of ACRPs, such as home-based rehabilitation and telerehabilitation, as solutions for broader implementation in CR practice. This study reviewed existing research to compare the cost and effectiveness of alternative cardiac rehabilitation programmes with traditional centre-based programmes.Alternative cardiac rehabilitation programmes provide similar health benefits to centre-based programmes.They are often less expensive, with most studies showing lower costs.
26 Apr 2026
Read appraisal →JMIR mental health
Expected Competencies and Personal Attributes of Digital Health Navigators to Support Digital Mental Health Care: Focus Group and Interview Study With Patients and Health Care Professionals
BACKGROUND: Digital mental health apps (DMHAs), and in particular digital therapeutics (DTx), offer promising opportunities to support mental health care. However, their effective use in outpatient settings in Germany remains limited. To overcome this gap, the role of digital health navigators (DHNs) has been introduced. DHNs are trained individuals who support patients and health care professionals in selecting, using, and integrating DMHAs into care. Despite increasing interest in this role, there is limited evidence on the competencies, knowledge, and personal attributes required for DHNs to work effectively in mental health settings. OBJECTIVE: The study aims to explore the expected competencies, knowledge areas, and personal attributes that DHNs need to effectively support the implementation and use of DTx in outpatient mental health care. METHODS: As part of the prestudy of the Digital Navigators for Acceptance and Competence Development with Mental Health Apps (DigiNavi) study, a qualitative study was conducted involving 35 participants (7 general practitioners, 8 patients in general practice, 11 outpatient psychiatrists/psychologists, and 9 patients in psychiatric outpatient clinics) from different general practices and psychiatric outpatient clinics in Germany. A total of 17 semistructured interviews and 4 focus groups were conducted to explore expectations of DHNs. Data were analyzed using qualitative content analysis. RESULTS: Participants emphasized that DHNs should combine strong interpersonal skills (empathy, patience, and sensitive communication) with technical and basic clinical competencies. Most favored DHNs as integrated clinical team members (eg, medical assistants), citing their existing patient relationships, but noted time and training constraints. Key expectations included the ability to support patients with DTx use, adapt communication to individual needs, and convey data privacy information clearly. Foundational knowledge of mental health conditions and sensitivity to crises were considered important for identifying warning signs and escalating concerns. While DHNs were seen as essential intermediaries between patients, health care professionals, and DTx, participants highlighted the necessity for clearly defined roles, structured training, and realistic expectations to prevent role overload and enable sustainable implementation in outpatient mental health care. CONCLUSIONS: DHNs require a specialized skill set that bridges clinical understanding, digital expertise, and interpersonal competence. Our results lay the groundwork for developing training curricula and implementation strategies that align with real-world expectations for the DHN role. Defining these core competencies is essential for supporting the sustainable and effective integration of DMHAs into mental health care.
26 Apr 2026
Read appraisal →BMJ open
Effects of nurse-led shared decision-making on low-dose CT uptake and screening outcomes in high-risk populations: a systematic review and meta-analysis
OBJECTIVES: To evaluate the effects of nurse-led shared decision-making (SDM) on lung cancer screening outcomes, including low-dose CT (LDCT) uptake, benign findings, early cancer detection and willingness to participate among high-risk populations. DESIGN: Systematic review and meta-analysis. DATA SOURCES: PubMed, Medline via OvidSP, Cochrane Central Register of Controlled Trials, EMBASE via OvidSP, Web of Science, Scopus, grey literature databases and clinical trial registries were searched from inception to March 2025. ELIGIBILITY CRITERIA: Studies evaluating nurse-led SDM interventions in high-risk lung cancer populations, reporting outcomes including LDCT uptake rates, screening results (Lung-RADS (Lung Imaging Reporting and Data System) classifications), early-stage cancer detection or willingness to participate. Randomised controlled trials, quasi-experimental studies and observational studies were included. DATA EXTRACTION AND SYNTHESIS: Two reviewers independently extracted data and assessed risk of bias using the Risk of Bias in Non-randomised Studies of Interventions (for non-randomised studies) and Cochrane Risk of Bias 2.0 (for randomised controlled trials). Meta-analyses were conducted using random-effects models. Meta-regression explored sources of heterogeneity. RESULTS: 13 studies (n=13 608 participants) were included, comprising 10 single-arm studies and three comparative studies. In single-arm studies without control groups, nurse-led SDM programmes achieved a pooled LDCT uptake rate of 98% (95% CI 28% to 100%; I²=99%), and willingness to participate was 68% (95% CI 24% to 93%; I²=98%). In comparative studies, nurse-led SDM showed no significant difference in LDCT uptake compared with usual care (RR 1.00, 95% CI 0.99 to 1.02; I²=0%), suggesting non-inferiority rather than superiority. Among individuals who completed screening, 81% (95% CI 77% to 85%) had benign or low-risk findings (Lung-RADS [Lung Imaging Reporting and Data System] I/II), and 2% (95% CI 1% to 3%) were diagnosed with early-stage lung cancer, rates consistent with benchmark screening trials. Meta-regression identified female sex as positively associated with uptake (β=0.54, p<0.001), while current tobacco use was negatively associated (β=-0.37, p=0.033). The risk of bias was moderate to serious across studies. CONCLUSIONS: Comparative evidence suggests that nurse-led SDM achieves equivalent LDCT uptake to standard care approaches, indicating feasibility as an alternative service delivery model. However, the predominance of single-arm studies, high heterogeneity and moderate-to-serious risk of bias limit causal inference. High uptake rates in single-arm studies likely reflect selection bias rather than intervention effectiveness. Current evidence supports the feasibility but not the superiority of nurse-led SDM. Well-designed randomised controlled trials are needed to establish comparative effectiveness and cost-effectiveness before recommending widespread integration of nurse-led SDM into lung cancer screening programmes. TRIAL REGISTRATION NUMBER: PROSPERO CRD420251033595. https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=1033595.
26 Apr 2026
Read appraisal →Journal of medical Internet research
Perspectives Regarding the Privacy, Security, and Confidentiality of Data Collected via mHealth Apps in Saudi Arabia: Qualitative Analysis
BACKGROUND: As Saudi Arabia aims to enhance the adoption and utilization of mobile health (mHealth) apps in the health care sector, it is vital to identify the potential challenges that may be faced in the process and how to address them. OBJECTIVE: This study aimed to explore patients' and stakeholders' perspectives regarding the privacy, security, and confidentiality of data collected via mHealth apps in Saudi Arabia. METHODS: A qualitative research design was used by conducting an in-depth interview with 25 participants, comprising health care workers (HCWs), patients, and mHealth app developers. The interview questions focused on awareness of mHealth apps and issues relating to data security, privacy and confidentiality, benefits of mHealth apps, challenges faced, and features that may improve the utilization of such digital health technologies. Thematic analysis was performed using NVivo software (version 12; QSR International). RESULTS: Patients were relatively less informed regarding events associated with data privacy and security than HCWs. Specific factors were identified to influence patient awareness with HCWs, suggesting the need for patient education and collaboration with cybersecurity organizations. Participants posited that advanced security features, user-friendly features, online consultation for emergencies, remote monitoring features, and taking patient needs into account are important facilitators of mHealth apps. Shared experiences mainly revolved around the accessibility to information and reliability of mHealth apps, while the challenges were related to poor usability, technical difficulties, data security, and data breaches. Patient autonomy, remote monitoring, self-care management, medical adherence, and time and cost-saving summed up the perceived benefits of the mHealth app. CONCLUSIONS: These findings may assist policymakers in developing strategies to improve Saudi users' and patients' adoption of mHealth apps and address the concerns raised to benefit significantly from these advanced health care modalities.
25 Apr 2026
Read appraisal →The Nurse practitioner
Artificial intelligence for early detection of aortic stenosis: The emerging role of NPs.
Aortic stenosis is associated with significant morbidity and mortality if left untreated. Nurse practitioners in primary care are uniquely positioned to identify early signs of this condition and are often the frontline provider for patients. Unfortunately, barriers to screening, diagnosis, referral, and treatment remain significant. Artificial intelligence technologies are emerging to address these barriers. This article highlights the potential impact of artificial intelligence in transforming aortic stenosis management and explores its integration into nurse practitioner practices to improve outcomes.
25 Apr 2026
Read appraisal →BMJ open
Course of psychological symptoms and the initial management strategies in general practice using electronic health records in the Netherlands
BACKGROUND: Patients who consult their GP about psychological complaints, such as feeling anxious or depressed, are often initially given a psychological symptom diagnosis. However, it remains unclear whether these symptoms will develop into psychiatric conditions, which is crucial for informing patients about their prognosis and guiding GPs in their management. AIMS: To explore the course of psychological symptom diagnoses and compare GPs' management strategies for (a) psychological symptom diagnoses that persisted for more than a year and (b) those that changed into psychiatric conditions during the first year of care. METHODS: We performed a retrospective cohort study using the Family-Medicine Network database. We included all episodes of care (EoC) that started with a psychological symptom diagnosis between 2008 and 2021. We performed negative binomial analyses and logistic regression analyses to compare management strategies and number of contacts between EoC that changed into psychiatric conditions and persistent psychological symptoms (>1 year) during the first year of care. RESULTS: Out of the 14 633 EoC that started with a psychological symptom diagnosis, 79.4% resolved within 1 year, 12.8% persisted as psychological symptoms and 7.8% changed into psychiatric conditions. In EoC that changed into psychiatric conditions, as compared with EoC that persisted as psychological symptoms, we observed a significantly higher number of contacts with the GP (RR=1.76, 95% CI 1.63 to 1.91) as well as an increased total number of interventions (RR=1.71, 95% CI 1.58 to 1.84). CONCLUSION: Most psychological symptoms remain for only a short period of time and only a few persist or change into psychiatric conditions. Future research should investigate the factors that influence patients' decisions to seek further help from their GPs as well as those that contribute to the transition from psychological symptom diagnoses to a psychiatric condition.
25 Apr 2026
Read appraisal →Journal of Korean medical science
Comparison of the Hearing Benefits and User Satisfaction With Hearing Aids and Personal Sound Amplification Products: A Multicenter Prospective Randomized Crossover Trial
BACKGROUND: While hearing aids (HAs) remain the primary intervention for hearing loss, their high cost creates barriers to access. Personal sound amplification products (PSAPs) are a more affordable alternative, but few studies have compared their efficacy to those of HAs. This multicenter, prospective, randomized, crossover trial was conducted to compare audiologic performance and user satisfaction between HAs and PSAPs to evaluate PSAP potential as alternatives for hearing rehabilitation. METHODS: A total of 73 participants with sensorineural hearing loss was enrolled. Participants used one hearing device (HA or PSAP) for 3 months before changing to the other for 3 months. Outcome measures were pure-tone audiometry, word recognition score, and Hearing in Noise Test score. Subjective satisfaction was measured using standardized questionnaires-the Abbreviated Profile of Hearing Aid Benefit and the International Outcome Inventory for Hearing Aids-and two custom surveys. RESULTS: HAs showed superior performance in high-frequency functional gain, speech perception in noise, and user satisfaction compared to PSAPs. Premium HAs demonstrated better performance than basic HAs, while basic HAs significantly outperformed both high-end and basic PSAPs. No significant differences were found between high-end and basic PSAPs. CONCLUSION: The superior audiologic performance of and user satisfaction with HAs compared to PSAPs support their continued preference for hearing rehabilitation. Although PSAPs offer a more affordable option, they may not meet the needs of individuals with hearing loss, particularly in terms of high-frequency gain and speech perception. TRIAL REGISTRATION: iCreaT Identifier: C220078.
23 Apr 2026
Read appraisal →Journal of medical Internet research
Facility-Level Associations Between Use of a Digital Health Platform for Voluntary Counseling and Testing and HIV Testing Outcomes in the Urban Primary Health Care Centers of Guangzhou, China: Cross-Sectional Study
BACKGROUND: WellTest, a digital health platform designed to facilitate HIV voluntary counseling and testing (VCT) services, has been widely implemented in Guangzhou, China. However, the extent of its use by primary health care centers (PHCs) and the facility-level associations between WellTest use and HIV testing outcomes remain unclear. OBJECTIVE: This study aimed to assess the use of WellTest at the facility level across PHCs in urban Guangzhou, China, and to explore the associations between WellTest use and HIV testing outcomes. METHODS: We obtained data on VCT services visits from the National HIV/AIDS Prevention and Control Information System and the WellTest platform between January 1 and December 31, 2022. Two facility-level HIV testing outcomes, the HIV testing volume and HIV positivity rate, were calculated for each PHC. A structured questionnaire collected data on the PHCs' characteristics. Multilevel negative binomial regression and zero-inflated gamma models were used to examine associations between WellTest use and 2 HIV testing outcomes at the facility level. RESULTS: A total of 81 PHCs across 5 urban districts in Guangzhou were included. WellTest was used for 7997 active consultations and 7969 HIV tests that resulted in 157 newly diagnosed HIV cases, for an overall positivity rate of 2.0%, during 2022. The median share of clients booking via WellTest was 71% (IQR 34%-98%), and 81% (66/81) of PHCs offered online slots on all service days without mandates. PHCs that actively confirmed appointments had significantly lower HIV testing volumes compared with those that took no actions after clients scheduled appointments (incidence rate ratio 0.75, 95% CI 0.58-0.97; P=.03) but exhibited higher HIV positivity rates (β=.39, 95% CI 0.02-0.76; P=.04). Additionally, PHCs where ≥50% of clients used WellTest to schedule appointments showed higher HIV positivity rates than those with lower uptake (β=1.11; 95% CI 0.82-1.40; P<.001). CONCLUSIONS: WellTest showed substantial use among VCT clients and providers in urban Guangzhou PHCs, with greater use of digital appointments and counselor follow-up linked to increased HIV positivity rates. Strategies to optimize institutional adoption may help address stigma-related barriers, strengthen engagement in HIV testing, and support HIV case finding in primary health care settings.
20 Apr 2026
Read appraisal →BMJ open
Cost-effectiveness of osteoporotic fracture risk assessment in people with intellectual disabilities: a UK NHS modelling study
OBJECTIVES: We compared the cost-effectiveness of alternative fracture risk assessment strategies for people with intellectual disabilities (ID) aged ≥40 years from a UK National Health Services perspective over a lifetime horizon. DESIGN: Cost-effectiveness analysis using a lifetime decision-analytical model. SETTING: UK primary care, with data from literature and national databases. PARTICIPANTS: People with ID. INTERVENTIONS: Three strategies were assessed: (S1) Risk assessment using the UK QFracture score; (S2) use of IDFracture (a fracture risk prediction tool specifically developed for adults with ID); and (S3) conducting a one-time dual-energy X-ray absorptiometry (DXA) scan in all. S1 and S2 were followed by DXA scan for those at risk. At-risk individuals received treatment according to UK practice (bisphosphonates plus vitamin D and calcium for osteoporosis, and vitamin D and calcium alone for osteopenia). PRIMARY OUTCOME MEASURES: Direct healthcare costs and quality-adjusted life years (QALYs), and incremental cost-effectiveness ratio (ICER). RESULTS: In the base case, S2 (ICER: -£2568/QALY) was dominant (ie, less costly and more effective) and S3 (ICER: £1678/QALY) was cost-effective relative to S1 for major osteoporotic fracture (MOF). For hip fracture, S2 (ICER: £32 116/QALY) and S3 (ICER: £49 536/QALY) were not cost-effective relative to S1 under the National Institute for Health and Care Excellence-recommended cost-effectiveness thresholds. Findings from the sensitivity analyses were predominantly consistent with the base-case results. Subgroup analyses showed that age-specific and gender-specific strategies could be used. CONCLUSION: For people with ID aged ≥40 years, a proactive approach to risk assessment for MOF is not only clinically beneficial, but also cost-effective.
20 Apr 2026
Read appraisal →Journal of medical Internet research
Comparing Pulmonary Telerehabilitation and Center-Based Pulmonary Rehabilitation for Effectiveness and Adherence in Chronic Obstructive Pulmonary Disease: Systematic Review and Meta-Analysis of Randomized Controlled Trials
BACKGROUND: Pulmonary rehabilitation (PR) is a cornerstone of chronic obstructive pulmonary disease (COPD) management; however, access to traditional center-based PR (CBPR) remains limited. Digital and remote models, collectively termed pulmonary telerehabilitation (Tele-PR), have increasingly been used, but their heterogeneity in technology use, supervision, and interaction mode may influence effectiveness and sustainability. OBJECTIVE: This systematic review and meta-analysis aimed to compare the effectiveness and adherence of Tele-PR with those of CBPR in adults with COPD while systematically evaluating the impacts of supervision intensity and delivery models on key clinical outcomes. METHODS: This review followed PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 and PRISMA-S (Preferred Reporting Items for Systematic reviews and Meta-Analyses literature search extension) guidelines. PubMed, Embase, the Cochrane Library, and the Web of Science were searched from inception to December 10, 2025, to identify randomized controlled trials comparing Tele-PR or home-based PR (HBPR) with CBPR in adults with COPD. Random effects meta-analyses were conducted using the Hartung-Knapp-Sidik-Jonkman method. Between-study heterogeneity was assessed using τ², I², and 95% prediction intervals. Risk of bias was evaluated with the Cochrane Risk of Bias 2 tool, and certainty of evidence was graded using the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) approach. RESULTS: Seventeen randomized controlled trials involving 1658 participants were included. After intervention, Tele-PR and CBPR showed comparable average effects on exercise capacity by 6-minute walk distance (k=9; n=950, 57.3%; mean difference -5.37 m, 95% CI -15.68 to 4.95; P=.26; τ²=103.97; I²=28.2%; 95% prediction intervals=-32.73 to 22.27). Although pooled effects were not statistically significant, substantial heterogeneity was observed across remote delivery models. Subgroup analyses linked digitally supported, synchronously supervised Tele-PR to less between-study variance across several outcomes, indicating greater consistency in treatment effects across different settings while revealing that low-technology HBPR yielded more variable outcomes, particularly in symptom burden. At long-term follow-up (≥6 mo), between-group differences in functional and symptom outcomes diminished, and short-term gains in exercise capacity did not consistently translate into increased daily physical activity. Certainty of evidence ranged from moderate to very low, mainly downgraded for performance bias, inconsistency across intervention models, and imprecision. CONCLUSIONS: Tele-PR may achieve short-term clinical outcomes comparable to CBPR. Distinct from prior reviews, we stratified remote programs by delivery models and supervision, identifying digitally supported Tele-PR and low-technology HBPR as 2 clinically distinct paradigms with differing consistency of effects. We further propose a structured "supervision gradient" to interpret model-dependent variability in effects across Tele-PR approaches, providing a context-sensitive framework for evidence-informed, model-specific implementation. Future remote rehabilitation should integrate real-time professional supervision and long-term behavioral maintenance to sustain benefits. Tele-PR may be particularly valuable for expanding PR access, while CBPR remains essential for patients requiring close in-person supervision or complex multidisciplinary care.
18 Apr 2026
Read appraisal →Journal of health organization and management
Organisational professional support measures to enhance mental health and wellbeing in female healthcare workers: an umbrella review
PURPOSE: This study aims to synthesise evidence on organisational professional support measures that enhance female healthcare workers' mental health and wellbeing. Female healthcare workers face high rates of mental health challenges, impacting their ability to provide optimal care. DESIGN/METHODOLOGY/APPROACH: This umbrella review adhered to the nine-step pathway to conducting umbrella reviews by Cant et al. (2022) and reported following the Preferred Reporting Items for Overview of Reviews checklist (Pollock, 2019). A search of Embase, Medline, CINAHL via EBSCO and the Cochrane Library for English language papers from January 2011 onwards was conducted (search date: February 2024). Following an identification of relevant papers and data extraction, themes were developed using a narrative synthesis approach. FINDINGS: In total, 32 systematic reviews met the inclusion criteria. From the data synthesis, four themes were developed, namely lack of studies specific to female healthcare workers, diversity and variability of interventions, interventions best related to staff outcomes versus organisational outcomes and social connections at work can be supportive or stressful. ORIGINALITY/VALUE: Evidence supports that person-directed interventions including cognitive-behavioural therapy and relaxation measures may enhance staff-level outcomes. In contrast, organisation-directed interventions such as clinical supervision and mentoring, or a combination of person- and organisation-centred interventions, appear to enhance both staff and organisational outcomes. Limitations in existing studies highlight the need for improved research conduct and reporting.
18 Apr 2026
Read appraisal →Biomedical physics & engineering express
A multimodal attention fusion-based model for pathological voice detection
Pathological voice detection provides a non-invasive and cost-effective approach for the early screening of laryngeal disorders. However, most existing methods rely on single-modal acoustic features and mainly focus on binary classification, which limits their ability to achieve fine-grained discrimination among multiple pathological voice categories. To address these limitations, this paper proposes a Multimodal Fusion Network (MFNet) with attention-based fusion for pathological voice classification. The proposed framework jointly models time-domain and frequency-domain information within a unified architecture. Specifically, SincNet is employed to extract task-relevant narrowband acoustic features directly from raw speech waveforms, while the Tunable Q-factor Wavelet Transform (TQWT) and SKNet are combined to learn multi-scale spectral representations from Mel-spectrograms. In addition, an Attentional Feature Fusion (AFF) module is introduced to adaptively integrate features from the two branches, thereby enhancing the discriminative capability of pathological voice representations. Comparative experiments on three public pathological voice datasets show that the proposed method outperforms representative baseline models and demonstrates strong robustness and generalization across different datasets. Furthermore, ablation studies further validate the effectiveness of the proposed architectural design. These results indicate that MFNet provides an effective solution for pathological voice classification and has promising potential for computer-aided voice disorder screening.
18 Apr 2026
Read appraisal →Sleep
Mamba-based deep learning approach for sleep staging on a wireless multimodal wearable system without electroencephalography
STUDY OBJECTIVES: We investigate a Mamba-based deep learning approach for sleep staging on signals from ANNE One (Sibel Health, Chicago, IL), a non-intrusive dual-module wireless wearable system measuring chest electrocardiography, triaxial accelerometry, chest temperature, and finger photoplethysmography and finger temperature. METHODS: We obtained wearable sensor recordings from 357 adults undergoing concurrent polysomnography at a tertiary care sleep lab. Each polysomnography recording was manually scored, and these annotations served as ground truth labels for training and evaluation of our models. Polysomnography and wearable sensor data were automatically aligned using their electrocardiography channels with manual confirmation by visual inspection. We trained a Mamba-based recurrent neural network architecture on these recordings. Ensembling of model variants with similar architectures was performed. RESULTS: After ensembling, the model attains a 3-class (wake, non-rapid eye movement sleep, rapid eye movement sleep) balanced accuracy of 84.02 per cent, F1 score of 84.23 per cent, Cohen's κ of 72.89 per cent, and a Matthews correlation coefficient (MCC) score of 73.00 per cent; a 4-class (wake, light NREM [N1/N2], deep NREM [N3], REM) balanced accuracy of 75.30 per cent, F1 score of 74.10 per cent, Cohen's κ of 61.51 per cent, and MCC score of 61.95 per cent; a 5-class (wake, N1, N2, N3, REM) balanced accuracy of 65.11 per cent, F1 score of 66.15 per cent, Cohen's κ of 53.23 per cent, MCC score of 54.38 per cent. CONCLUSIONS: Our Mamba-based deep learning model can successfully infer major sleep stages from the ANNE One, a wearable system without electroencephalography, and can be applied to data from adults attending a tertiary care sleep clinic.
17 Apr 2026
Read appraisal →Spine
An Unsupervised Learning Approach for Multimodal Low Back Pain Stratification
STUDY DESIGN: Cross-sectional study. OBJECTIVE: This study proposes a novel stratification framework for individuals with low back pain (LBP). The method integrates Northern Finland Birth Cohort data comprising imaging biomarkers from deep learning (DL)-based analysis of lumbar spine MRI with the data on smoking status, demographics (sex and BMI), self-reported data from Örebro Musculoskeletal Pain Screening Questionnaire (ÖMPSQ) short and the STarT Back Tool (SBT). Furthermore, the utility of this stratified approach was validated by demonstrating a superior net benefit compared with "treat-all" strategy. BACKGROUND: Current risk stratification for individuals with LBP relies on ÖMPSQ short and SBT among others. While these tools are invaluable for capturing psychosocial characteristics predictive of future disability and functional outcomes, LBP's multifactorial nature necessitates a more comprehensive framework for effective risk stratification. MATERIALS AND METHODS: A method for multimodal unsupervised patient stratification has been developed that allows for the integration of imaging biomarkers of disc degeneration (DD) and facet tropism (FT), extracted using DL models, with nonimaging data. The framework utilized robust K-Means clustering to stratify individuals. Clusters were characterized using LBP frequency and bothersomeness, and their robustness was validated with a multi-class logistic regression model. Net benefit was assessed through decision curve analysis. RESULTS: Three distinct subgroups were characterized by LBP frequency and bothersomeness. One subgroup was dominated by psychosocial characteristics (psychosocial risk P < 0.05), the second by physical degenerative changes (DD P < 0.05), and the third by a mix of both. Predictive models for cluster assignment were robust, achieving high mean accuracies (SBT-based: 0.89; ÖMPSQ-short-based: 0.87). The net benefit is superior throughout a range of threshold probabilities compared with a "treat-all" strategy. CONCLUSION: A novel framework was developed that integrates multimodal data to identify distinct subgroups differentiated by their physical and psychosocial characteristics in a population-based cohort, demonstrating potential for advancing personalized care.
17 Apr 2026
Read appraisal →Sleep
Augmenting management of obstructive sleep apnea with consumer wearable devices to increase use of positive airway pressure therapy: a pilot randomized trial
STUDY OBJECTIVES: This pilot randomized trial measured the effects of a consumer-grade wearable-augmented program, which provides nightly pulse oximetry data to patients in a weekly report, on positive airway pressure (PAP) use in adults with obstructive sleep apnea (OSA) recruited from an outpatient sleep center. METHODS: This single-blind, parallel, two-group waitlist-controlled, single-site randomized trial recruited individuals with OSA with insufficient PAP use from a Department of Veterans Affairs medical center and randomized them to immediate participation in the consumer wearable-augmented self-monitoring program versus waitlist. The primary outcome was the change in modem-measured PAP use (mean hours or minutes per night over a 7-day period) from baseline (T1) to T3 assessment, which was 35 days following randomization (7 days post-intervention for the immediate group and prior to intervention for the waitlist group). RESULTS: We randomized 50 participants (mean age 47.9 years [SD 11.4]; 88% male). The change in PAP use was +1.33 hours (+79.8 minutes) for the immediate group and -0.17 hours (-10.2 minutes) for the waitlist control group, with a between-group difference of 1.50 hours (90 minutes) (p = .0097). The change in the number of days PAP was used for 4 hours or more over a 7-day period was +1.32 days for the immediate and 0.12 days for the waitlist control group, with a between-group difference of 1.20 (p = .0401). CONCLUSIONS: This pilot trial demonstrated that the consumer-grade wearable-augmented program is a promising intervention for increasing PAP use. A future full-scale trial that follows participants for a longer period is needed. Statement of Significance This pilot trial tested a novel use of the pulse oximetry feature available on some consumer-grade wearable devices to increase use of positive airway pressure (PAP) devices among adults with obstructive sleep apnea (OSA) and insufficient PAP use. The widespread and growing use of consumer-grade wearable devices offers an opportunity to leverage the features on these devices to tackle a common, problematic issue among individuals with OSA-insufficient use of PAP therapy. The randomized controlled design provides support for future research involving these devices.
17 Apr 2026
Read appraisal →BMJ open
Remote assessment and practice implementation for disorders in ears, nose and throat: a mixed-methodology observational study in the United Kingdom
INTRODUCTION: Ear, nose and throat (ENT) conditions are highly prevalent in primary and secondary care, yet patients frequently face prolonged waits for specialist review. In England, over half of ENT patients wait beyond the NHS 18-week referral-to-treatment target. Many of these cases can be effectively managed with advice and non-surgical interventions, presenting an opportunity for remote service innovation.This study aims to evaluate the clinical effectiveness, cost-effectiveness, acceptability and environmental sustainability of a digitally enabled remote ENT clinic model compared with traditional face-to-face pathways. METHODS AND ANALYSIS: This single-centre, mixed-methods, prospective cohort study will be conducted at University Hospitals Birmingham NHS Foundation Trust. Remote clinics will use trained staff to collect diagnostic data (including endoscopic imaging and boothless hearing tests) for consultant review via secure cloud-based software. Quantitative analysis will assess patient outcomes, costs, waiting times, carbon footprint and satisfaction. Qualitative data from semi-structured interviews with patients, clinicians and managers will explore acceptability, scalability and barriers to implementation. The qualitative data will be analysed using the framework methodology, according to the non-adoption, abandonment, scale-up, spread and sustainability framework, while the strengthening the reporting of observational studies in epidemiology framework will be used to guide the reporting of quantitative data. Cost-effectiveness analyses will follow NICE guidelines, while environmental impact will be measurement will be informed by the sustainability in quality improvement framework. Recruitment will be aiming for 300 completed datasets and 30-35 interviews. ETHICS AND DISSEMINATION: Ethical approval has been granted (IRAS 350908; REC 25/SW/0116). Findings will be disseminated via conferences, peer-reviewed journals and institutional communication channels.
17 Apr 2026
Read appraisal →BMJ open
Generative artificial intelligence-driven chatbots and medical misinformation: an accuracy, referencing and readability audit
OBJECTIVES: Artificial intelligence (AI)-driven chatbots have been rapidly adopted across research, education, business, marketing and medicine. Most interactions, however, come from non-experts using chatbots like search engines, including for everyday health and medical queries. DESIGN: We conducted an original study to audit chatbot responses in health and medical fields prone to misinformation. METHODS: Five popular chatbots were assessed: Gemini (Google), DeepSeek (High-Flyer), Meta AI (Meta), ChatGPT (OpenAI) and Grok (xAI). In February 2025, each chatbot was prompted with 10 questions from five categories: cancer, vaccines, stem cells, nutrition and athletic performance. We deployed an adversarial-like framework, using open- and closed-ended prompts designed to strain models toward misinformation or contraindicated advice. Two experts from each category rated responses as 'non-problematic', 'somewhat problematic' or 'highly problematic' using a coding matrix based on objective, predefined criteria. Citations were scored for accuracy and completeness, and each response was given a Flesch Reading Ease score. RESULTS: Nearly half (49.6%) of responses were problematic: 30% somewhat problematic and 19.6% highly problematic. Response quality did not differ significantly among chatbots (p=0.566) but Grok generated significantly more highly problematic responses than would be expected under a random distribution (z-score +2.07, p=0.038). Performance was strongest in vaccines (mean z-score -2.57) and cancer (-2.12), and weakest in stem cells (+1.25), athletic performance (+3.74) and nutrition (+4.35). Chatbot outputs were consistently expressed with confidence and certainty; from 250 total questions, there were only two refusals to answer (0.8%), both from Meta AI. Reference quality was poor, with a median completeness score of 40% (Q1-Q3: 20-67%). Chatbot hallucinations and fabricated citations precluded any chatbot from producing a fully accurate reference list. All readability scores were graded as 'Difficult' (30-50), equivalent to college sophomore-senior level. CONCLUSIONS: The audited chatbots performed poorly when answering questions in misinformation-prone health and medical fields. Continued deployment without public education and oversight risks amplifying misinformation.
16 Apr 2026
Read appraisal →Journal of affective disorders
What retrospective and dynamic assessments tell us about youth depression: A network analysis perspective.
PURPOSE: Traditional assessments of depressive symptoms often rely on retrospective self-reports, which may be affected by cognitive and memory biases. Few studies have compared retrospective and dynamic (real-time) assessments to examine the consistency and structure of depressive symptom reporting. This study aimed to compare retrospective and dynamic assessments of depressive symptoms in youth using network analysis to explore symptom-level associations and clustering. METHODS: Ninety Brazilian adolescents and young adults (mean age = 18 years), with and without depression, completed the Short Mood and Feelings Questionnaire (SMFQ) every other day for 14 days via a smartphone-based chatbot (dynamic assessment). At the end of the 2-week period, they completed the same questionnaire retrospectively. Network analyses were conducted using Exploratory Graph Analysis (EGA) and Dynamic Exploratory Analysis (DEA) to identify symptom communities and compare network structures across both assessment methods. RESULTS: Both retrospective and dynamic assessments revealed three symptom communities; however, the composition and structure of these communities differed. Retrospective assessments showed stronger connections among cognitive symptoms, while dynamic assessments displayed a more balanced distribution, with stronger associations between somatic and affective symptoms. IMPLICATIONS: Findings highlight significant differences in depressive symptom networks between retrospective and dynamic assessments. Dynamic methods may offer less biased and more ecologically valid insights into youth depression, underscoring the importance of real-time data collection in clinical assessment and research.
16 Apr 2026
Read appraisal →International journal of medical informatics
Prioritising digital health technologies in Australian community pharmacy: a delphi study identifying barriers, enablers, and policy implications for implementation
OBJECTIVE: To determine priority digital health technologies for Australian community pharmacies and identify the key barriers, enablers, and policy/funding factors that can inform future implementation planning through expert consensus. METHODS: A two-round Delphi study was conducted with 31 experts representing pharmacy, academia, policy, and digital health. In Round 1, participants identified priority technologies, barriers, and enablers. In Round 2, 27 participants ranked five technologies, nine policy options, and six financial models. Consensus was assessed using descriptive statistics and interquartile ranges (IQRs). RESULTS: E-prescriptions and My Health Record (MyHR) were ranked as top priorities (mean = 1.70 and 2.22; IQR ≤ 1.0). Key barriers included financial constraints, interoperability issues, and digital literacy gaps. Telehealth incentives received the strongest agreement among participants, while reimbursement-based funding and government support were rated as the most supportive financial models for implementation. Broader enablers, such as a national medicine repository and stronger cross-disciplinary collaboration, were also endorsed. CONCLUSION: Digital health adoption in community pharmacy requires prioritisation of core technologies, improved system integration, workforce training, and practical funding mechanisms. These findings offer guidance for policymakers, pharmacy leaders, and digital health stakeholders aiming to embed digital tools more consistently and effectively into pharmacy practice.
15 Apr 2026
Read appraisal →JAMA
A Decision-Support System to Personalize Antidepressant Treatment in Major Depressive Disorder: A Randomized Clinical Trial
IMPORTANCE: Antidepressants for moderate to severe major depressive disorder may be discontinued prematurely because the prescribed antidepressant is not always the most appropriate medication for an individual. Guidelines have recommended more precise targeting of antidepressant treatment. OBJECTIVE: To evaluate the efficacy of a web-based tool to personalize antidepressant treatment. DESIGN, SETTING, AND PARTICIPANTS: This multicenter, randomized clinical trial included persons between the ages of 18 and 74 years with major depressive disorder. The trial was conducted at 47 sites in 3 countries (Brazil, Canada, and the UK). The first participant was screened on November 29, 2022, and the last follow-up visit occurred on January 15, 2025. INTERVENTION: A total of 540 participants were randomized (1:1) to an evidence-based clinical decision-support system (PETRUSHKA tool; n = 271) or usual care (n = 269). MAIN OUTCOMES AND MEASURES: The primary outcome was treatment discontinuation due to any cause at 8 weeks. The secondary outcomes included treatment discontinuation up to 24 weeks due to adverse events and changes in depressive symptoms (measured with the 9-item Patient Health Questionnaire [PHQ-9]; range, 0-27; higher scores indicate more severe depression) and anxiety symptoms (measured with the 7-item Generalized Anxiety Disorder [GAD-7] questionnaire; range, 0-21; higher scores indicate more severe symptoms). RESULTS: Of the 520 eligible participants, 493 were included in the primary analysis (median age, 35 [IQR, 25 to 48] years; 58% female; PHQ-9 mean score, 16.6 [SD, 5.1]; GAD-7 mean score, 11.5 [SD, 4.1]). At 8 weeks, 41 of 241 participants (17%) in the PETRUSHKA group discontinued the prescribed antidepressant due to any cause vs 69 of 252 (27%) in the usual care group (adjusted relative risk, 0.62 [95% CI, 0.44 to 0.88]; P = .007). At 8 weeks, 22 of 241 participants (9%) in the PETRUSHKA group discontinued the prescribed antidepressant due to adverse events vs 39 of 252 (16%) in the usual care group (adjusted relative risk, 0.59 [95% CI, 0.36 to 0.97]; P = .04). For the assessment of depressive symptoms at 24 weeks, the mean PHQ-9 score was 7.1 (SD, 5.4) in the PETRUSHKA group vs 9.2 (SD, 6.5) in the usual care group (n = 129 in each group; adjusted between-group mean difference, -1.92 [95% CI, -3.06 to -0.78]; P < .001). For the assessment of anxiety symptoms at 24 weeks, the mean GAD-7 score was 4.6 (SD, 4.1) in the PETRUSHKA group (n = 133) vs 5.8 (SD, 4.9) in the usual care group (n = 126) (adjusted between-group mean difference, -1.39 [95% CI, -2.26 to -0.52]; P = .002). CONCLUSIONS AND RELEVANCE: Compared with usual care, use of the PETRUSHKA tool increased the number of patients still taking their antidepressant at 8 weeks and improved depressive and anxiety symptoms at 24 weeks. However, lack of a double-blind design and the large amount of missing data limit the validity of these results. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT05608330.
15 Apr 2026
Read appraisal →JMIR cancer
Leveraging Innovative Electronic Health Record Data to Characterize Social Determinants of Health Among Survivors of Cancer in Persistent Poverty Areas: Cross-Sectional Study
BACKGROUND: Residents in persistent poverty areas experience higher cancer mortality due to social determinants of health that negatively affect multiple factors, including health behaviors. OBJECTIVE: This study aimed to characterize demographic, clinical, and social determinant of health factors among survivors of cancer in persistent poverty areas using electronic health record (EHR) data-including an embedded social risk screener and natural language processing (NLP) of social work notes-to inform community-engaged adaptation of lifestyle interventions. METHODS: EHR data from a large multispecialty group practice were extracted for patients with cancer residing in zip codes inclusive of persistent poverty areas targeted for a health behavior intervention and receiving care between January 2018 and November 2023. Self-reported social determinant of health data were obtained using the Protocol for Responding to and Assessing Patients' Assets, Risks, and Experiences (PRAPARE) and through NLP of social histories from a social work visit. RESULTS: We identified 2672 unique patients with cancer, of whom 578 (21.6%) had PRAPARE data and 1597 (59.8%) had social history data available for analysis. The most common cancers among survivors (n=1420, 53.1% female; n=1299, 48.6% Black individuals; mean age 65.2, SD 13.7 years) included breast (n=536, 20.1%), prostate (n=400, 15%), and lymphoid or hematopoietic (n=323, 12.1%) cancer. Among survivors in persistent poverty areas (n=509, 19%; all with a high Social Vulnerability Index), 34.6% (176/509) were single, 55.4% (282/509) had Medicare coverage (with only 73/509, 14.3% having private insurance), 36.5% (186/509) had obesity, 63.9% (325/509) had hypertension, and 31.2% (159/509) had diabetes. Of survivors in persistent poverty areas with PRAPARE data, 15.8% (19/120) lacked transportation, 4.2% (5/120) lived with housing insecurity, and 6.7% (8/120) felt unsafe where they lived. CONCLUSIONS: Innovative EHR and NLP approaches identified several socioeconomic and safety-related challenges along with opportunities for health behavior interventions to leverage Medicare coverage and target multiple comorbidities when adapting interventions for survivors of cancer living in persistent poverty areas.
14 Apr 2026
Read appraisal →Australian journal of primary health
National and international guidelines for preconception care and comparison with Australian guidelines: a systematic review
BACKGROUND: Guidelines for preconception care are resources that are systematically arranged based on evidence and local contexts to enhance the delivery of high-quality and consistent healthcare. The Royal Australian College of General Practitioners Guidelines (RACGP) for preventive activities in general practice (the Red Book) contains specific components of preconception care items, yet this guideline primarily focuses on general preventive healthcare and may not include a comprehensive list of preconception items based on more recent evidence. This review aimed to compare the recent RACGP guidelines (the 2024 Red Book) with national and international guidelines for preconception care. METHODS: Electronic databases, including PubMed, Embase, Web of Science, CINAHL, and Scopus, were systematically searched following Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. We also searched clinical guideline registries on professional organisations' websites. Searches were conducted from May to June 2024 and in July 2025. RESULTS: We identified seven other national and international guidelines that recommended what should be done as part of preconception health in clinical practice. Preconception care elements that were not included in the current RACGP guidelines that have evidence of effectiveness were the inclusion of men in preconception care, screening for intimate partners and domestic violence, screening for chlamydia and gonorrhoea infections, and screening for female genital mutilation as part of preconception care. CONCLUSIONS: This review identified four preconception care elements that may potentially improve the implementation of preconception care in Australian practice. This work informs the next steps towards developing a comprehensive preconception medical record tool for use in general practice.
12 Apr 2026
Read appraisal →BMJ open respiratory research
Parasternal electromyography in participants with mild or moderate chronic obstructive pulmonary disease in primary care: cohort study to assess technical and clinical application
BACKGROUND: Neural respiratory drive (NRD) measurement, reflecting the balance between respiratory muscle load and capacity, is quantified using surface parasternal electromyography (EMGpara). EMGpara tracks recovery from severe exacerbations of chronic obstructive pulmonary disease (COPD). Among stable COPD participants, we hypothesised the existence of a relationship between NRD, breathlessness and airway obstruction. STUDY AIMS: (1) assessing the feasibility of measuring EMGpara in COPD participants with forced expiratory volume in 1 s (FEV1) ≥50% predicted in primary care; (2) investigating relationships between NRD measures, self-reported breathlessness, airflow obstruction severity and health-related quality of life (HRQoL). METHODS: Participants with stable mild/moderate COPD, using inhaled corticosteroid (ICS) therapy, were recruited from 20 general practices. Participants were randomly allocated to continue using ICS (maintenance group) or to withdraw ICS (withdrawal group) over 6 weeks. EMGpara, spirometry, self-reported breathlessness (modified Borg dyspnoea scale), COPD Assessment Test and Chronic Respiratory Disease Questionnaire Self-Administered Standardised were measured at baseline, 3- and 6-month follow-up. Bland-Altman plots examined agreement between serial measurements. RESULTS: Forty COPD participants were recruited: age 70±9.2 years; body mass index 26±5.3 kg/m2; FEV1 1.74±0.54 L; and FEV1% pred 69.6±14.0%. High-quality EMGpara data were obtained from 35 participants at baseline and 31 participants on three occasions. High intra-rater and inter-rater agreement for EMGpara (intraclass correlation coefficient >0.9) and moderate correlation between EMGpara and FEV1% predicted (r=-0.42; p=0.01) were recorded. No correlation was observed between resting EMGpara and breathlessness or HRQoL measures across the three time points. CONCLUSIONS: EMGpara measurement is feasible in primary care. In this group of COPD patients, lung function was stable across the three time points and EMGpara was associated with the degree of airflow obstruction. In the resting stable state in mild/moderate disease, there was no association between EMGpara and participant-reported outcomes. Further work should investigate the utility of EMGpara in mild/moderate COPD participants during acute exacerbation and recovery.
12 Apr 2026
Read appraisal →PloS one
Prevalence and determinants of inadequately controlled diabetes in Qatar's public primary care settings: A cross-sectional study
BACKGROUND: The prevalence of type 2 diabetes mellitus (T2DM) is rapidly increasing worldwide, causing serious morbidity and mortality. Proper management and control of T2DM are essential in slowing and reducing complications. Measuring the adequacy of diabetic control, therefore is one of the ways of evaluating the success of health care system and the individuals in addressing disease morbidity and mortality. This study was proposed to assess the extent of uncontrolled T2DM in ambulatory adults managed in the public primary care settings of Qatar over five years. In addition, it aimed to predict the risk of uncontrolled disease based on age, sex, nationality and comorbidity. METHODS: A cross sectional review of Electronic Health Records of 84,512 adult individuals with T2DM having at least one HbA1c blood test result per year during the 5 years study period (1st January 2018, to 31st December 2022) was analyzed. The term "inadequately controlled" T2DM was used to define an individual with HbA1c measurements of 7% or higher. RESULTS: The yearly prevalence of inadequately controlled T2DM remained stable at a high rate (53%) during the last three years of observations. Aging increases the probability of having inadequately controlled T2DM, but this was attributed to comorbidities. Adjusting for those comorbidities will show that younger ages are the ones at higher risk of being uncontrolled. Additionally, the study reported that hypertension and dyslipidemia are the most frequently prevalent comorbidities, nevertheless retinopathy, although less frequent, was the most important predictor for inadequately controlled T2DM. CONCLUSIONS: The study highlights the significant healthcare challenge posed by T2DM in Qatar due to its high prevalence and associated complications. Males, South Asian ethnic background and Qatari locals have the highest probability of being inadequately controlled. Overall, the study emphasizes the need for targeted interventions to address the challenges of controlling diabetes, particularly among high-risk groups identified in the study.
10 Apr 2026
Read appraisal →Journal of medical Internet research
Innovations in Deaf Health Care Communication: Systematic Review of Sign Language Recognition Systems
BACKGROUND: Deaf individuals often face communication challenges when interacting with those who can hear. Within health care settings, these challenges may pose risks to their safety, potentially resulting in misdiagnoses, treatment errors, and decreased quality of care. OBJECTIVE: This study aims to systematically review the evidence on communication systems reported in the literature that use human-computer interaction techniques to support communication between deaf individuals who use sign language and hearing health professionals in health care settings. The review focuses on systems that are either currently in use or proposed for use in health care and that have been tested using human participants or videos of human users. METHODS: A comprehensive search was performed via MEDLINE, Web of Science, ACM, IEEE Xplore, Scopus, and Google Scholar in March 2025. The inclusion criteria comprised studies developing a sign language recognition system within a health care context and testing with human users. Eligible studies underwent screening by 2 independent investigators (LRV and LMMSR or LFRdO and GTdSS), with any disagreements resolved by a senior researcher (MSM). RESULTS: The search retrieved 21,778 publications, and screening of reference lists identified 2 additional studies, resulting in a total of 23 studies meeting the eligibility criteria. Most systems (15/23, 65.2%) were image-based, while 34.8% (8/23) relied on sensors (glove-based or depth-sensing). Applications varied across health care settings, including general hospital care (10/23, 43.5%), emergencies (8/23, 34.8%), and primary care (4/23, 17.4%). All systems were in the development and testing stage, with no data on security and psychological impacts. Accuracy ranged from 25% to 100% for image-based and 72% to 99.7% for sensor-based systems. Bidirectionality and facial expression recognition, crucial for effective communication, were largely overlooked. CONCLUSIONS: Image-based systems were more common than sensor-based ones, though both showed wide variability in accuracy in recognizing and interpreting signs. Most systems failed to address critical aspects such as bidirectional communication and the recognition of facial expressions, essential for effective communication. None fully addresses the requirements for integration into health care settings. These findings highlight the need for further research on implementation, usability, and impact on the quality of care for deaf patients.
10 Apr 2026
Read appraisal →JMIR human factors
e-Mental Health Intervention Preferences Among Informal Caregivers of Adults Living with Chronic Kidney Disease: Semistructured Interview Study
BACKGROUND: Informal caregivers of people living with chronic kidney disease commonly experience mental health difficulties. However, there is currently limited access to scalable psychological interventions such as those using e-mental health platforms. Furthermore, there is an absence of such interventions tailored for this group of caregivers, which may limit acceptability. OBJECTIVE: To inform future e-mental health intervention development, this study aimed to explore preferences for e-mental health interventions among informal caregivers of people living with chronic kidney disease. METHODS: A total of 13 informal caregivers of people living with chronic kidney disease participated in semistructured interviews. Eligible informal caregivers lived in the United Kingdom and were recruited via nonprofit organizations and social media advertisements. Semistructured interviews followed a topic guide exploring caregivers' e-mental health intervention preferences. Data were analyzed using manifest content analysis. RESULTS: A total of 4 categories and 13 subcategories were generated. "Design preferences" illustrates key intervention design features that were important to caregivers, such as involving caregivers and other interest-holders in the design process. "Content preferences" describes the information caregivers valued in an intervention, such as information about chronic kidney disease and resources to support caregivers. "Support preferences" reflects the characteristics of support caregivers preferred if support was available as part of the intervention, such as peer support and providing support that accommodates individual preferences. Lastly, "Dissemination preferences" describes methods caregivers recommended to promote intervention uptake, such as engaging communication strategies and trusted and accessible sources of information. CONCLUSIONS: Caregivers identified a number of e-mental health intervention design and delivery preferences that should be considered when developing e-mental health interventions for caregivers of people living with chronic kidney disease. To ensure such interventions are acceptable, feasible, and relevant, co-design approaches should be adopted during the intervention development process.
8 Apr 2026
Read appraisal →Physiological measurement
NeuroSleep: neuromorphic event-driven single-channel EEG sleep staging for edge-efficient sensing
Objective. Reliable, continuous neural sensing on wearable edge platforms is fundamental to long-term health monitoring; however, for electroencephalography (EEG)-based sleep monitoring, dense high-frequency processing is often computationally prohibitive under tight energy budgets.Approach. To address this bottleneck, this paper proposes NeuroSleep, an integrated event-driven sensing and inference system for energy-efficient sleep staging. NeuroSleep first converts raw EEG into complementary multi-scale bipolar event streams using Residual Adaptive Multi-Scale Delta Modulation, enabling an explicit fidelity-sparsity trade-off at the sensing front end. Furthermore, NeuroSleep adopts a hierarchical inference architecture that comprises an Event-based Adaptive Multi-scale Response module for local feature extraction, a Local Temporal-Attention Module for context aggregation, and an epoch-leaky integrate-and-fire module to capture long-term state persistence.Main results. Experimental results using subject-independent 5-fold cross-validation on the sleep-EDF expanded sleep-cassette subset (78 subjects, 153 overnight recordings) with single-channel EEG demonstrate that NeuroSleep achieves a mean accuracy of 74.2% with only 0.932 M parameters while reducing sparsity-adjusted effective operations by approximately 53.6% relative to dense processing. Compared to the representative dense Transformer baseline, NeuroSleep improves accuracy by 7.5% with a 45.8% reduction in computational load.Significance. By coupling neuromorphic event encoding with state-aware context modeling, NeuroSleep offers a deployment-oriented framework for single-channel sleep staging that reduces redundant high-rate processing and improves energy scalability for wearable and edge platforms.
8 Apr 2026
Read appraisal →JMIR human factors
Factors Influencing User Satisfaction in Accessing Health Data: Cross-Sectional Survey of United Kingdom Adults
BACKGROUND: While patient health records (PHRs) are becoming ubiquitous, nationwide evidence on the drivers of user satisfaction in the United Kingdom remains scarce. OBJECTIVE: This study aimed to quantify determinants of PHR user satisfaction in a nationally representative sample of United Kingdom adults and to contrast real-world experiences with hypothetical expectations among individuals without PHR exposure. METHODS: We conducted a cross-sectional online survey in March 2022 using stratified quota sampling (eg, age, sex, ethnicity) through the Prolific platform. Of 1001 respondents, 533 (53%) were female (mean age 41, SD13) years, 468 (47%) reported previous PHR use ("experienced" cohort), and 533 (53%) respondents did not ("hypothetical" cohort). Primary outcomes were five satisfaction items (5-point Likert), overall PHR evaluation (0-100), and stated/anticipated PHR functions. Two-sample t-tests with unequal variances examined between-group differences; multivariate analysis of variance (MANOVA) assessed demographic equivalence. Significance was set at P<.05. RESULTS: Respondents with PHR experience rated their record easy-to-use in 79% (370/468) of cases versus an anticipated 93% (498/533) among nonusers (P<.001). Experienced users rated appointment-scheduling time-saving at 68% (319/468) compared with 72% (387/533) of nonusers (P=.17). Mean overall evaluation scores were 71.0 (SD 19.5) versus 74.2 (SD 18.6) (t₉₉₇=2.25, P=.02). MANOVA confirmed demographic balance (Wilks Λ=.99, F₇,₉₉₃=1.48, P=.18). Preferred functions across cohorts were viewing personal health information (experience 81%, hypothetical 90%) and lab results (50% vs 76%). Users lacking experience consistently over-estimated future use of carer-related functions (eg, children's data: 36% vs 12%, P<.001). CONCLUSIONS: Adults in the United Kingdom value PHRs primarily for personal data access and scheduling convenience. Nonusers displayed optimistic expectations about carer-related features and breadth of functionality, indicating an information gap. Enhancing transparency about current capabilities and expanding features that facilitate caregiving could increase satisfaction and adoption.
7 Apr 2026
Read appraisal →JMIR medical informatics
Automated ICD-10-Anchored Classification of Primary Care Text Data: Development and Evaluation of a Custom Multilabel Classifier
BACKGROUND: Electronic medical records are a vast and valuable source of information, useful for tasks such as estimating disease prevalence. However, in routine primary care, much of this information is in free-text format rather than in a structured form and, therefore, not readily amenable to analysis. Manual coding of this textual data is both time-consuming and resource-intensive, making it impractical for large datasets. Although powerful open-source language models offer new opportunities for automated coding, their use on short heterogeneous primary care notes, particularly in German-language settings, remains insufficiently studied. OBJECTIVE: By providing hands-on guidance for applied health researchers, this study aims to demonstrate the effective and accurate automatic classification of free-text notes using a language model fine-tuned for automated International Statistical Classification of Diseases, Tenth Revision (ICD-10) coding. METHODS: Building on the extensive Family Medicine Research Using Electronic Medical Records (FIRE) routine database from the Institute of Primary Care at the University Hospital Zurich and the University of Zurich, we trained a large language model-based multilabel classifier on a dataset of 38,728 free-text notes, which had been manually categorized into 47 classes using specific ICD-10 codes and code ranges or nondiagnostic/ad hoc labels (eg, "unclear diagnosis," "status post"). We stratified the labeled data into training (70%), validation (15%), and posttraining test (15%) sets, ensuring similar label distributions across these sets. Using the Transformers Python library, we trained the model over 10 epochs and evaluated it on the posttraining test dataset. RESULTS: Across 48 classes, the FIRE classifier achieved strong performance on the held-out posttraining set, with F1-scores of 0.85 (micro, overall across all predictions), 0.86 (macro, mean of per-class scores treating classes equally), and 0.84 (weighted, per-class scores weighted by class frequency). CONCLUSIONS: This study demonstrates steps for training open-source large language models and highlights the potential to streamline and scale the extraction of diagnostic information for practical applications. Our model can be robustly deployed, for example, for prescreening and labeling of free-text information, thus potentially reducing the burden of repetitive and error-prone manual handling.
7 Apr 2026
Read appraisal →American journal of human genetics
The Electronic Medical Records and Genomics study: Design and analytic framework for assessing the impact of genome-informed risk assessments.
The Electronic Medical Records and Genomics (eMERGE) Network developed and implemented a genome-informed risk assessment (GIRA) to communicate genomic (polygenic risk scores [PRSs], integrated risk scores [IRSs], and monogenic results), clinical, and family history-based risk for 11 chronic diseases and provide recommended healthcare recommendations. GIRA reports have now been returned to 23,840 participants and their providers in a large prospective cohort study. We present here the study design and analysis framework for assessing the attributable impact of GIRA return. Pre-specified outcomes include (1) provider/participant adoption of recommended healthcare actions, (2) new diagnosis of disease, (3) treatment initiation/intensification, and (4) clinical outcomes (surrogate markers or clinical events). We assess outcomes in high risk vs. not-high-risk participants, adjusting for covariates. We evaluate the effect of PRS/IRS at pre-established high-risk thresholds using regression discontinuity (RD), a quasi-experimental method that mimics randomization near a cutoff, enabling estimation of causal effects and controlling for unobserved confounders. Monogenic and family history-based risk stratification are analyzed using logistic regression. With 23,840 participants and 12 months of follow-up, the study is powered to detect differences of 2%-11% with 80% power (α = 0.05 in the adoption outcome). Longer follow-up will be required to enable assessment of new disease diagnosis, treatment changes, and clinical outcomes. Through innovative RD analyses and defined outcomes and comparison groups, this study will provide new insights into the real-world clinical impact of genomic risk assessment, address critical evidence gaps, advance understanding of genomic medicine outcomes, and inform future research.
5 Apr 2026
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