Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
Showing 39 appraisals
Simulation in healthcare : journal of the Society for Simulation in Healthcare
Future of Biometric Technology in Healthcare Simulation
Biometric technology shows substantial promise to enhance patient safety and transform provider training. In patient care, biometric technology enables outpatient providers to optimize chronic disease by alerting providers to changes in patient conditions with real-time data. In provider training, biometric technology can inform training environments and curriculum. Certainly, there are hurdles to technology implementation including hardware fragility, cost, and software integration. Despite challenges, biometric technology has been effectively implemented in simulations and real patient settings. Looking forward, future developments focused on data security and privacy, standardizing data collection, and improving system compatibility will facilitate the wider adoption of biometric technology and improve health care quality, especially in resource-limited settings. Collaborative efforts among informatics experts, patient safety advocates, and health care providers are essential to overcome challenges and fully leverage biometric technology's potential in enhancing patient outcomes. The purpose of this commentary is to review current applications, identify key challenges, and offer recommendations to the simulation community for testing biometric technology, use in training programs, and facilitating systems integration to improve outcomes.
2 Aug 2026
Read appraisal →European journal of pediatrics
Health-related quality of life and associated factors in children with bronchiectasis: A systematic review
UNLABELLED: This systematic review aimed to summarize the current evidence on health-related quality of life (HRQoL) and its associated factors in children with bronchiectasis. Following the PRISMA guidelines, we systematically searched PubMed, Embase, Web of Science, ScienceDirect, CINAHL, CENTRAL, CNKI, WanFang, VIP, and CBM published from inception to October 2025. Two reviewers independently screened studies, extracted data, and assessed quality using standardized tools. Descriptive synthesis was performed. Nine studies were included, with overall moderate to high quality. HRQoL scores in children with bronchiectasis were significantly lower than those in healthy controls across most scales, though findings varied across physical and psychosocial domains. Parent-proxy scores were generally lower than child self-reports. Lower HRQoL was associated with impaired lung function, frequent exacerbations, higher symptom burden, and anxiety/depression. CONCLUSION: HRQoL is substantially impaired in children with bronchiectasis. Routine assessment of HRQoL and integrated interventions addressing both physical and psychosocial aspects are warranted in clinical practice. WHAT IS KNOWN: • Bronchiectasis is a chronic respiratory disease that causes coughing and breathing difficulties in children. • Previous studies have reported inconsistent findings on quality of life in children with bronchiectasis. WHAT IS NEW: • This systematic review consolidates evidence from nine studies, confirming that children with bronchiectasis have significantly lower quality of life than healthy children. • Poor lung function, frequent exacerbations, and anxiety/depression are key determinants; parents tend to rate their child's quality of life lower than the children themselves, underscoring the need for integrated care including psychological support.
31 July 2026
Read appraisal →JMIR nursing
Effectiveness of Artificial Intelligence-Based Nursing Interventions for Chronic Illness Care: Umbrella Review
BACKGROUND: Artificial intelligence (AI)-based nursing interventions are increasingly being used to manage chronic illnesses; however, their definitive impact on clinical outcomes remains inconclusive, necessitating a comprehensive evidence synthesis. OBJECTIVE: This umbrella review aimed to synthesize the evidence regarding the effectiveness of AI-based nursing interventions for chronic illness care and their subsequent impact on health care outcomes in clinical settings. METHODS: We conducted an umbrella review and prospectively registered the protocol. A systematic search of 5 electronic databases (PubMed, CINAHL, Cochrane Library, Scopus, and Web of Science) was performed to identify systematic reviews and meta-analyses published in English between 2021 and 2025. The methodological quality of the included studies was evaluated using the Joanna Briggs Institute (JBI) Critical Appraisal Checklist. RESULTS: Eight high-quality systematic reviews were included, with machine learning identified as the predominant technology. Three primary outcome domains emerged: predictive, psychosocial, and hospital utilization. Due to measurement heterogeneity, the results were synthesized narratively. Our findings demonstrated that AI-based nursing interventions are effective in predicting adverse clinical events, unplanned hospital utilization, and health care costs. However, evidence regarding psychosocial outcomes remains insufficient. CONCLUSIONS: This review provides systematic evidence supporting the utility of AI in chronic illness management, particularly for improving predictive and utilization outcomes. These findings offer actionable insights for nursing leaders to integrate AI into clinical practice and education. Future research should prioritize rigorous empirical designs to further strengthen the evidence base for AI-driven nursing care.
17 July 2026
Read appraisal →Journal of medical Internet research
Patients' Experiences of Nurse-Led eHealth Interventions for Chronic Heart Failure: Qualitative Systematic Review and Meta-Synthesis
BACKGROUND: Chronic heart failure (CHF) is a major chronic condition in the context of global population aging and is associated with high prevalence, frequent rehospitalization, and high mortality. Self-management is widely recognized as an important factor influencing prognosis and quality of life among patients with CHF. Nurse-led eHealth interventions have been increasingly used in postdischarge CHF management and have shown potential for improving adherence and health-related behaviors. However, existing studies have predominantly focused on objective outcomes, and limited systematic synthesis has examined patients' subjective experiences, which may restrict the patient-centered optimization and sustainable implementation of these interventions. OBJECTIVE: This study aimed to systematically synthesize patients' experiences of nurse-led eHealth interventions for CHF, identify facilitators and barriers to engagement and implementation, and inform the patient-centered optimization of intervention design through a qualitative systematic review and meta-synthesis. METHODS: This qualitative systematic review and meta-synthesis was conducted in accordance with the Joanna Briggs Institute methodology for qualitative systematic reviews. A comprehensive search was performed in PubMed, Web of Science, Embase, the Cochrane Library, CINAHL, CNKI, WanFang, and VIP from database inception to April 30, 2026, supplemented by manual searches of the reference lists of the included studies. Following methodological quality appraisal, the findings of the included studies were extracted and synthesized using thematic synthesis. RESULTS: A total of 23 studies involving 424 patients with CHF were included, comprising 17 qualitative studies and 6 mixed methods studies. Four synthesized themes and 12 subthemes were generated: (1) patient empowerment and enhanced self-management, (2) sense of security and continuity of care under professional support, (3) variations in acceptance and emotional responses, and (4) barriers and challenges in implementing eHealth interventions. CONCLUSIONS: Nurse-led eHealth interventions may provide important support for CHF management from the patient perspective by promoting empowerment and extending care support beyond hospital settings. The findings suggest that future intervention design should better address patient heterogeneity, technological usability, and long-term sustainability. Further efforts are needed to strengthen individualized adaptation and technological optimization to enhance the accessibility, acceptability, and patient-centered implementation of these interventions.
7 July 2026
Read appraisal →BMJ health & care informatics
Predicting health and disease: a conceptual framework for AI in preventive and precision medicine
The conventional medical approach of treating symptoms as they appear with restricted screening often limits intervention to slowing disease progression rather than fully reversing it. A new approach leveraging artificial intelligence (AI) and computational technologies across expanding multimodal biomedical datasets holds the promise to enable predicting actionable future changes in health before symptom onset. This article presents a conceptual framework for a preventive paradigm in precision medicine and healthcare, integrating recent advancements in AI and biomedical datasets. Key remaining challenges facing computational systems, real-world clinical validation and implementation, and preventive interventions together with recommendations and prioritised future directions are highlighted. Such an approach could pave the way for more proactive and preventive medical interventions to effectively address the growing burden of chronic disease.
4 July 2026
Read appraisal →Journal of medical Internet research
Using a Large Language Model to Support Thematic Analysis of Patient Experiences in Chronic Illness Management: Comparative Qualitative Study
BACKGROUND: Qualitative health research often focuses on how patients experience and manage chronic illnesses, a topic that has been extensively studied in the literature. With the emergence of large language models (LLMs), such as Claude (Anthropic PBC) and ChatGPT (OpenAI), new opportunities are arising to support and scale the thematic analysis of narrative health data. However, their role and added value compared to traditional human-led approaches remain underexplored, particularly in complex clinical contexts such as multimorbidity. OBJECTIVE: We aim to evaluate the methodological contribution of LLM-assisted analysis by examining its ability to replicate and extend established qualitative insights, in comparison with traditional thematic analysis. METHODS: Semistructured interviews were conducted with 30 individuals living with two or more chronic illnesses. Transcripts were analyzed using both manual thematic coding and Claude 3.5 Sonnet. A structured comparison was conducted to identify shared and unique themes across the two approaches. The analysis examined thematic overlap, differences in subtheme identification, and variation in the level of detail between the methods. RESULTS: Both approaches identified similar core themes related to the patient experience, including health care navigation and challenges, support systems and family dynamics, and emotional challenges and coping. Manual analysis produced more contextually detailed interpretations, while the LLM approach identified a larger number of subthemes. Each method also revealed distinct themes: the manual analysis included themes such as faith, caregiving roles, and a proactive mindset, whereas the LLM identified themes such as future planning and multiple health conditions. The findings show both similarities and differences between the two approaches. The LLM analysis also demonstrated efficiency in processing large volumes of qualitative data. CONCLUSIONS: A hybrid approach that integrates artificial intelligence-assisted and human-led thematic analysis can enhance both analytical depth and scalability. These findings support the use of LLMs as a complementary tool in qualitative research, while highlighting the importance of combining automated pattern detection with human interpretation.
30 June 2026
Read appraisal →BMJ open
Effectiveness and safety of pharmacist prescribing: a systematic review
OBJECTIVE: To examine the effectiveness and safety of pharmacist prescribing across multiple healthcare settings. DESIGN: A systematic review of quantitative studies. ELIGIBILITY CRITERIA FOR THE SELECTION OF STUDIES: Quantitative studies assessing the effectiveness and safety of pharmacist prescribing compared with non-pharmacist prescribing in any healthcare setting and for any healthcare population. A clear statement of pharmacists' prescriptive authority was required for inclusion in this systematic review. DATA SOURCES: A systematic search was conducted using six electronic databases: Embase (Ovid), MEDLINE (EBSCO), SCiELO, Dimensions AI, Cochrane Library and Epistemonikos. Database searches were conducted from database inception to 29 January 2025. Additional grey literature searches were conducted using Google and DuckDuckGo. Both backward and forward citation chasing were conducted for all included studies. DATA EXTRACTION AND SYNTHESIS: Data were extracted using standardised bespoke data extraction forms. The revised Cochrane Risk of Bias 2 tool for randomised controlled trials and the Risk of Bias in Non-Randomised Studies of Interventions tool were used to assess risk of bias. A narrative synthesis approach was applied following the Synthesis Without Meta-analysis guideline. The Grading of Recommendations Assessment, Development and Evaluation approach was used to assess the level of certainty of the evidence. RESULTS: Of the 39 included studies, 32 studies reported on effectiveness and 20 studies reported on safety across 15 health conditions. Healthcare settings included outpatient (n=14), primary care (n=10), community pharmacy (n=6), inpatient (n=5), emergency department (n=1) and long-term care (n=3). These studies were based in the USA (n=26), Canada (n=5), the UK (n=4), Australia (n=2) and Singapore (n=2). In total, there were 153 outcomes related to safety and effectiveness. For 74 outcomes, no significant difference was reported between pharmacist prescribing and non-pharmacist prescribing, while 46 outcomes were significantly improved with pharmacist prescribing. Four outcomes reported in favour of non-pharmacist prescribing. Inferential statistics were not reported for 29 outcomes, meaning we cannot comment on their statistical significance. The certainty of evidence was low or very low for all outcomes. CONCLUSIONS: The consistency of effectiveness and safety findings across studies, showing either no significant difference (indicating equivalence of care and outcomes) or significant improvement in pharmacist prescribing groups, suggests it is a potential policy option. Future research on implementation, public and patient preferences and cost-effectiveness would provide valuable insights into the potential benefits of pharmacist prescribing at a health system level.
28 June 2026
Read appraisal →Journal of health organization and management
Unlocking potential: impact of mHealth affordance realization on patient well-being
PURPOSE: This study investigates how realized affordances of mobile health technologies influence the relationship between technology use, patient empowerment and well-being in diabetes self-management. DESIGN/METHODOLOGY/APPROACH: The research proposes a technology use-empowerment-well-being (TEW) model based on affordance theory. Data were collected through a survey of 257 diabetes patients using mobile technologies for self-management and analyzed using structural equation modeling with SmartPLS. FINDINGS: Results indicate that patient empowerment fully mediates the relationship between mobile technology use and patient well-being. Importantly, realized affordances moderately strengthen the relationship between technology use and patient empowerment, demonstrating that patients derive greater benefits when they actively utilize technology's capabilities for diabetes management. RESEARCH LIMITATIONS/IMPLICATIONS: Reliance on self-reported data and the cross-sectional design limit causal inferences about the evolution of technology-empowerment-well-being relationships over time. PRACTICAL IMPLICATIONS: Healthcare technology designers should focus on creating clear, tangible benefits for patients that support specific self-management behaviors. Healthcare providers should educate patients about the benefits of technology and support them in realizing these affordances through training and ongoing assistance. ORIGINALITY/VALUE: This study integrates affordance theory with patient empowerment concepts, providing empirical evidence that realized affordances - not merely technology availability - are critical for improving self-management outcomes. The TEW model introduces a novel framework for understanding how technology empowers patients and enhances well-being in chronic disease management.
27 June 2026
Read appraisal →Journal of medical Internet research
Personal Health Large Language Models and the Negotiation of Medical Authority in Clinical Care: Opportunities, Risks, and Governance
Personal health large language models (PH-LLMs) are patient-facing conversational systems that synthesize user-entered information, patient-generated health data, wearable data, and selected personal health records-where users choose to connect them-into personalized, longitudinal, action-oriented health narratives. Unlike generic health chatbots that mainly provide one-off responses to isolated questions, PH-LLMs may generate continuing interpretations, priorities, and candidate next steps that patients bring into clinical encounters. In contrast to electronic health record-tethered clinical artificial intelligence (AI), they often originate outside institutional oversight and may be selected, used, or trusted by patients before professional review. This viewpoint examines how PH-LLMs may reshape the negotiation of medical authority by contributing to a shift from the traditional dyadic clinician-patient relationship toward a triadic model of negotiated authority, in which clinicians may increasingly need to mediate among clinical evidence, patient values, and algorithmic narratives. PH-LLMs may support patient participation by organizing symptoms, contextualizing home-monitoring and wearable data, improving health literacy, assisting chronic disease self-management, and preparing patients for more collaborative visits. Patient-facing AI narratives may also introduce distinct risks. At the individual level, these include inaccurate or incomplete responses arising from imprecise queries or missing context, misinterpretation of otherwise accurate information in the absence of clinical context, and contextually biased or poorly matched advice across demographic, cultural, linguistic, disability-related, or socioeconomic contexts. At the system level, they include authority conflict when AI recommendations diverge from clinical judgment, fragmentation of clinical truth, privacy and data-governance concerns, diffusion of accountability when harm results from advice produced outside clinical governance, and inequitable access to premium tools and continuous monitoring devices. To address these challenges, we propose a 3-layer clinical governance framework for patient-brought PH-LLM narratives. The first layer, evidence and provenance, makes AI-generated narratives epistemically legible by clarifying platform identity, data sources, temporal anchoring, uncertainty, and privacy-relevant data-use and retention conditions. The second layer, clinical arbitration and workflow integration, uses risk-stratified intake, proportionate documentation, escalation triggers, and equity-preserving workflows to embed PH-LLM outputs into routine care. The third layer, competence and accountability, defines the communication competencies, AI literacy supports, institutional responsibilities, vendor accountability, and risk-proportionate verification duties needed for triadic care. This framework is a conceptual and governance-oriented proposal rather than a validated clinical protocol. Future empirical work should evaluate its feasibility, documentation burden, equity effects, clinical safety impact, and acceptability among patients, clinicians, and health systems. Governed through these interdependent layers, PH-LLMs may serve as supporting infrastructure for safer, person-centered longitudinal care.
26 June 2026
Read appraisal →Journal of global health
mHealth for chronic disease management: effects on adherence in Ghanaian patients with diabetes and hypertension
BACKGROUND: Medication non-adherence remains a major barrier to effective chronic disease management, particularly in low- and middle-income countries. In Ghana, limited access to continuous care and patient engagement tools contributes to poor adherence among individuals living with type 2 diabetes and hypertension. Mobile health interventions, including smartphone applications, may offer scalable solutions to support long-term medication use and self-management. Here, we assess the effect of a smartphone-based intervention on medication adherence among adults with these conditions. METHODS: We conducted a quasi-experimental study among 874 adults with type 2 diabetes or hypertension in Ghana. Participants were assigned to either a smartphone-based intervention, which included medication reminders, educational content, and self-monitoring tools, or standard care involving routine outpatient management and follow-up without access to the smartphone-based intervention. We measured medication adherence at baseline and six months using the Medication Adherence Rating Scale and assessed it through generalised estimating equations and difference-in-differences analyses, adjusting for baseline adherence, age, sex, and treatment setting. RESULTS: Use of the smartphone application was associated with a greater improvement in medication adherence over six months in the overall study population (adjusted beta coefficient (aβ) = 0.062; 95% confidence interval (CI) = 0.010-0.123). Similar improvements were observed among participants with type 2 diabetes (aβ = 0.067; 95% CI = 0.012-0.135) and hypertension (aβ = 0.068; 95% CI = 0.005-0.134). However, there was no statistically significant difference in adherence between the intervention and control groups at six months. CONCLUSIONS: Smartphone-based interventions were associated with modest improvements in medication adherence over time, although between-group differences at follow-up were not statistically significant. As access to mobile technology expands across Africa, such interventions may provide scalable strategies to support chronic disease management.
14 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 →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 →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 →BMJ open
Self-management experiences and needs in patients with chronic obstructive pulmonary disease: a meta-synthesis of qualitative studies
OBJECTIVES: To systematically review qualitative studies on the self-management experiences and needs of patients with chronic obstructive pulmonary disease (COPD) and to provide evidence for developing needs-based self-management intervention strategies. DESIGN: A systematic review and meta-aggregation of qualitative studies conducted in accordance with the Enhancing Transparency in Reporting the Synthesis of Qualitative Research statement. DATA SOURCES: PubMed, Cochrane Library, Web of Science, Scopus, CINAHL, Embase, CNKI, Wanfang Database, VIP Database and CBM were searched from database inception to March 2025 for qualitative studies on COPD self-management experiences and needs. ELIGIBILITY CRITERIA: Qualitative studies involving adults (≥18 years) with a confirmed diagnosis of COPD that reported patients' real feelings, experiences and needs during the self-management process in any setting (hospital, community or home). Studies were excluded if the full text could not be obtained or data were incomplete, if they were duplicate publications or if they were not published in Chinese or English. DATA EXTRACTION AND SYNTHESIS: Two reviewers independently screened titles, abstracts and full texts, extracted data using a standardised form and assessed methodological quality using the 2016 Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Qualitative Research. Findings (participants' quotations and authors' interpretive statements) were synthesised using a JBI meta-aggregation approach to develop categories and overarching synthesised findings. RESULTS: 15 qualitative studies were included, comprising 251 patients with COPD. A total of 52 findings were identified, grouped into 13 categories and synthesised into 4 overarching findings: (1) physical symptom burden strongly shapes psychological well-being during COPD self-management; (2) patients face multiple and interrelated barriers to effective self-management; (3) some patients develop active coping strategies and self-management resources; and (4) patients express multidimensional and continuing support needs. CONCLUSIONS: Patients with COPD experience substantial physical and psychological distress and face multiple challenges in the self-management process. Healthcare professionals should prioritise patients' lived experiences, establish comprehensive and coordinated support systems and develop diversified, needs-based intervention strategies to address patients' multidimensional needs, thereby enhancing self-management capacity and improving quality of life. PROSPERO REGISTRATION NUMBER: CRD42024607051.
29 May 2026
Read appraisal →BMJ open
Protocol for evaluating the effects of the intelligent multimodal symptom assessment and response system in patients with pemphigus vulgaris: a randomised controlled trial
INTRODUCTION: Pemphigus vulgaris is a rare autoimmune blistering disease characterised by recurrent mucocutaneous erosions, high symptom burden and unpredictable relapse. Current management relies mainly on pharmacological therapy and hospital-based follow-up, with limited real-time monitoring and individualised support in home-based disease management. To address these challenges, this trial aims to evaluate the effectiveness of an Intelligent Multimodal Symptom Assessment and Response System, integrating patient-reported outcomes, wearable physiological data and image-based lesion assessments, to improve symptom management and quality of life in pemphigus vulgaris patients. Primary objective is to evaluate the effectiveness of the Intelligent Multimodal Symptom Assessment and Response System in improving symptom alerting and symptom management outcomes in patients with pemphigus vulgaris. Secondary objectives are to enhance patients' self-management ability in symptom monitoring and control, to improve treatment adherence throughout the follow-up period, to promote health-related quality of life among pemphigus vulgaris patients, to assess the usability and acceptability of the system from the patients' perspective. METHODS AND ANALYSIS: This is a multicentre, parallel-group, randomised controlled trial. 160 participants will be randomly assigned to either the intervention group (receiving the Intelligent Multimodal Symptom Assessment and Response System) or the control group (receiving standard care). Eligible participants will be adults aged 18 years or older with a confirmed diagnosis of pemphigus vulgaris and active skin or mucosal lesions, who are able to use digital devices and provide written informed consent. Individuals with severe comorbidities, concurrent participation in other clinical trials or cognitive impairments that may interfere with study adherence will be excluded. The intervention will be delivered via a digital platform, integrating electronic patient-reported outcomes, wearable physiological data and lesion images over a 12-week follow-up period. ETHICS AND DISSEMINATION: Ethical approval was obtained from the Institutional Review Board of the School of Nursing, Fudan University (IRB 2025-07-13), the Medical Ethics Committee of the Institute of Dermatology, Chinese Academy of Medical Sciences (2025-KY-034) and the Ethics Committee of Ruijin Hospital, Shanghai Jiao Tong University School of Medicine (2025-452). Approvals were granted on 10 September, 18 July and 23 July 2025, respectively. This protocol is based on V1.0, 13 July 2025 of the protocol. The results of this study will be disseminated through peer-reviewed publications and academic conferences. TRIAL REGISTRATION NUMBER: ChiCTR2500109711.
29 May 2026
Read appraisal →European respiratory review : an official journal of the European Respiratory Society
Implementation of long-term noninvasive positive airway pressure therapy in patients with COPD: a systematic review and meta-analysis of acceptance and adherence
BACKGROUND: Long-term noninvasive positive airway pressure (PAP) therapy is an effective, albeit complex, intervention for obstructive sleep apnoea (OSA) and/or chronic hypercapnic respiratory failure (CHRF) in patients with chronic obstructive pulmonary disease (COPD). PAP uptake and use is often reported in studies designed for other purposes. Systematic review methods were used to summarise acceptance of and adherence with PAP therapy. METHODS: A systematic search for studies that reported the proportion of patients that either declined or accepted PAP therapy and/or objective use of newly prescribed PAP therapy in patients with COPD was conducted according to a predefined protocol (PROSPERO CRD42021259262). Meta-analysis and meta-regression techniques were used to establish summary effect estimates and explore heterogeneity. RESULTS: On average, PAP therapy was declined or discontinued by 14% (95% CI 10-19) of participants, often within 6 weeks of initiation among studies reporting repeated measures. The pooled median adherence was 6.3 h·day-1 (95% CI 5.9-6.6). While meta-regression found higher acceptance (p=0.03) and shorter use per day (p<0.01) for the indication of OSA versus CHRF, this explained only some heterogeneity in the summary effect estimates. Summary of study-level variables associated with acceptance or adherence highlighted limitations in the available literature. CONCLUSIONS: An anticipated six out of seven patients with COPD newly prescribed PAP therapy will be successful using therapy; however, heterogeneity was substantial among studies, and only partly explained by indication for use. Prospective studies to explore barriers to use and detailed reporting of acceptance and adherence in studies on PAP therapy in patients with COPD are needed.
29 May 2026
Read appraisal →BMJ open
Voice-assisted artificial intelligence in cardiovascular disease management: a systematic review and meta-analysis protocol
INTRODUCTION: Cardiovascular disease (CVD) remains a leading cause of global morbidity and mortality, with self-management playing a pivotal role in improving outcomes. Voice-assisted artificial intelligence (AI) technologies such as virtual assistants and voice-controlled applications have emerged as innovative tools for healthcare delivery. While the technologies show promise in areas like primary prevention and chronic disease management, their effectiveness in supporting self-management for patients with CVD remains underexplored. This study aims to evaluate the impact of voice-assisted AI technologies on CVD self-management, specifically focusing on cardiovascular-related mortality, health-related quality of life (HRQoL) and adherence to lifestyle modifications. METHODS AND ANALYSIS: A systematic review and meta-analysis will be conducted following the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols. A comprehensive search will be performed across databases such as MEDLINE, Scopus, Embase and Cochrane Central Register of Controlled Trials (CENTRAL), from 2010 to 2025. The review will include randomised controlled trials (RCTs), non-RCTs and observational studies that evaluate voice-assisted AI interventions (eg, voice-controlled fitness apps, smart health assistants) aimed at CVD self-management. The primary outcome will be cardiovascular-related mortality. Secondary outcomes will include HRQoL, clinical outcomes (eg, high blood pressure), lipid profiles (eg, cholesterol and glucose levels) and lifestyle modifications (eg, dietary habits and levels of physical activity). Data management and analysis will be conducted using Comprehensive Meta-Analysis software V.2.0. The methodological quality of the included studies will be assessed using the Cochrane Risk of Bias tool for RCTs and the Newcastle-Ottawa Scale for observational studies. The meta-analysis will use random-effects models, with heterogeneity assessed using Q and I² statistics. Subgroup analyses and meta-regression will be conducted to explore potential sources of heterogeneity. ETHICS AND DISSEMINATION: No formal ethical assessment is required, as this study involves analysis of publicly available secondary data. Findings will be disseminated through publications in peer-reviewed scientific journals, conference presentations and media coverage to inform healthcare providers, policymakers and patients. PROSPERO REGISTRATION NUMBER: CRD42024568702.
29 May 2026
Read appraisal →Lasers in medical science
Acute effect of photobiomodulation therapy in quadriceps strength, fatigue and pain of patients with chronic kidney failure: a randomized, double-blind, placebo controlled crossover clinical trial
Patients with chronic kidney failure (CKF) present changes in physical capacity and low exercise tolerance. Photobiomodulation therapy (PBMT) has shown an ergogenic effect on exercise in studies with different populations and may be an adjuvant treatment in rehabilitation programs for CKF patients. This study aimed to evaluate the acute effects of different doses of PBMT on quadriceps strength, fatigue and muscle pain in CKF patients. This study is a randomized, placebo-controlled, double-blind, crossover clinical trial. Adult patients with CKF received four PBMT applications with different energy doses (30J, 60J, 90J, or placebo), administered in a random order. A one-week interval was maintained between each dose, and an 830nm laser was applied to six points of the quadriceps muscle. Immediately after PBMT, maximal isometric quadriceps muscle strength was assessed by dynamometry. Before the intervention and after the assessment of muscle strength, muscle fatigue (Borg rating of perceived exertion scale and blood lactate) and pain perception in the lower limbs (visual analogue scale) were measured. Fifteen patients were randomized and fourteen completed the study. There was no significant difference between the doses tested for maximal isometric muscle strength in the right (p=0.053) and left (p=0.509) quadriceps. The perception of fatigue assessed by the modified Borg scale was not altered (p=0.703) nor were blood lactate levels, regardless of the PBMT dose and measurement time (t0: p=0.126; t3: p=0.667; t6: p=0.700). There was no change in pain perception after quadriceps irradiation for any of the PBMT doses tested (p=0.566). A single application of PBMT with a dose of 30J, 60J, or 90J did not alter maximal isometric quadriceps muscle strength, fatigue, or muscle pain perception in the lower limbs of CKF patients on HD.
24 May 2026
Read appraisal →JMIR formative research
Patients' mHealth Apps Usage and Data Privacy, Security, and Confidentiality Concerns: Exploratory Study
BACKGROUND: The Technology Adoption Model (TAM) offers a potential framework for elucidating the relationships between data privacy or security concerns and behavioral intention, perceived usefulness (PU), and perceived ease of use (PEOU) of mobile health (mHealth) apps, particularly for patients' self-care management. In Saudi Arabia, limited information is available on these pertinent research areas despite the government's relentless efforts to bolster the use of mHealth apps. OBJECTIVE: This study applies the TAM and the psychosociocultural framework to explore the influence of patients' data privacy and security concerns on the PU, PEOU, and behavioral intention to use mHealth apps for self-care management in Saudi Arabia. METHODS: A cross-sectional study was conducted by recruiting patients using mHealth apps for self-care from various provinces in Saudi Arabia. Research instruments were developed based on the components of 2 theories: the psychosociocultural framework and TAM, which were then piloted, validated, and distributed to participants via Google Forms. Linear regression models were performed to test the hypothesized relationships. RESULTS: Overall, 567 patients using mHealth apps participated in the study. Slightly more than one-third (217/567, 38.2%; range 35.6%-41.4%) of the participants expressed a high level of concern regarding data privacy, confidentiality, and security, with significant predictors being female gender, higher educational qualifications, and younger age groups (<46 years). About 18% to 25% of the variance in PU, PEOU, and behavioral intention to use mHealth apps was explained by the tested factors. Patients were more likely to have higher PU following a unit decrease in data confidentiality (β=.31; P=.01) and security concerns (β=.47; P=.01). The PEOU of mHealth apps increased as users demonstrated less concern regarding data privacy (β=.18; P=.001), confidentiality (β=.24; P<.001), and security (β=.43; P=.02). Likewise, behavioral intention to use mHealth apps also increased significantly following a reduction in respondents' concerns toward data privacy (β=.18; P=.02), confidentiality (β=.24; P=.03), and security issues (β=.36; P=.01). CONCLUSIONS: Specific demographic factors and concerns regarding data security and privacy influence patients' PU, PEOU, and behavioral intention to use mHealth apps for self-care management. Targeting the age-, education-, and gender-based differences regarding the usage of mHealth apps. Health care providers and policymakers may consider age-, education-, and gender-based differences when developing strategies to improve the adoption of mHealth apps among the Saudi patient population.
22 May 2026
Read appraisal →Journal of medical Internet research
Understanding Remission of Long-Term Conditions Through Electronic Health Records: Scoping Review
BACKGROUND: Multiple long-term conditions (MLTCs) require complex and prolonged treatment regimens. Remission in long-term conditions (LTCs) is important for understanding disease progression and evaluating treatment effectiveness. Electronic health records (EHRs) are increasingly used to monitor clinical outcomes, but how remission is defined within EHRs remains unclear. OBJECTIVE: This study aimed to summarize and collate the previous literature on how remission of LTCs has been defined in EHRs. METHODS: Systematic electronic searches were performed on OVID MEDLINE, Embase, CINAHL EBSCO, the Cochrane Library, and the Bielefeld Academic Search Engine for eligible studies published from inception to November 27, 2025. Quantitative studies, published in any language, on adult populations, and using EHRs to assess remission of LTCs, were eligible for inclusion. Studies that did not clearly define remission and studies on cancer remission were excluded. Data were extracted from each eligible study using a structured table. Risk of bias was not assessed, in line with scoping review methodology. A narrative approach was taken to summarize and present data from the included studies. The number and characteristics of studies were described, both overall and by condition. Findings were discussed with clinicians and data experts to ensure applicability in clinical practice. RESULTS: Ninety-one studies were included. Sample sizes ranged from 12 to 72.9 million adults. Studies were conducted in 18 countries, with the majority being from the United States. The majority of included studies used a cohort study design. Studies assessed how remission was defined in 12 LTCs, including inflammatory bowel disease (41/91, 45.1%), type 2 diabetes (n=15, 16.5%), depression (n=15, 16.5%), alcohol or drug misuse (n=8, 8.8%), asthma (n=3, 3.3%), multiple sclerosis (n=3, 3.3%), epilepsy (n=1, 1.1%), anemia (n=1, 1.1%), chronic kidney disease (n=1, 1.1%), autoimmune pancreatitis (n=1, 1.1%), hypertension (n=1, 1.1%), heart failure (n=1, 1.1%), and MLTC (n=1, 1.1%). Remission was typically defined using a combination of clinical codes (n=7, 7.7%), validated rating scales (n=56, 61.5%), biochemical markers (n=29, 31.9%), absence of symptoms (n=10, 11%), absence of condition-specific events (eg, hospital admissions; n=4, 4.4%), and cessation of pharmacological treatments (n=26, 28.6%). There was substantial variation in the criteria and duration of follow-up used to define remission across studies. CONCLUSIONS: This review demonstrates that remission of LTCs can be identified and operationalized within EHRs, although remission criteria varied across studies. The review extends the literature on remission in EHRs by combining evidence synthesis and consultation with clinical and data experts to propose standardized comprehensive definitions to reliably define and implement remission of multiple LTCs in EHR-based research. This will allow cross-study comparisons and present an opportunity to advance understanding of disease trajectories and improve evaluation and monitoring of patient outcomes. Further research may apply, compare, and evaluate standardized definitions across different data sources to assess generalizability and further improve our understanding of remission of LTCs.
20 May 2026
Read appraisal →JMIR human factors
A Chronic Pain Self-Management Mobile App (Dolodoc): Cross-Sectional Acceptability Study
BACKGROUND: Approximately 19% of adults in Europe are affected by chronic pain, which reduces the quality of life. Pain-management mobile health (mHealth) apps offer a promising solution for self-management, but user engagement and adherence can limit their clinical impact. User experience design and research play a crucial role in optimizing usability and long-term adoption of digital health interventions. OBJECTIVE: This study aims to evaluate the user experience of Dolodoc, a mobile app for chronic pain self-management, using a mixed methods approach that assesses acceptability through a content quality survey and examines use by analyzing overall use patterns. METHODS: A cross-sectional acceptability study of the main content of Dolodoc was conducted among patients with chronic pain recruited from the Geneva University Hospitals pain center and through snowball sampling. Participants rated 84 evidence-based self-management strategies by using a 5-point Likert scale based on 5 acceptability criteria: understandability, motivation, feasibility, relevance, and alignment with the related quality-of-life dimension. To reduce participant fatigue and avoid random responses, the 84 strategies were randomly divided across survey versions. Use was assessed through metrics collected over 6 months with Piwik PRO Analytics to observe real-world use behaviors among Dolodoc users. RESULTS: In the acceptability study, 33 participants rated the self-management strategies positively across all dimensions. On a scale from -2 to 2, the strategies were well understood (mean 1.47, SD 0.76), motivational (mean 1.12, SD 0.96), feasible (mean 1.01, SD 1.05), relevant (mean 0.99, SD 1.09), and aligned with the dimensions (mean 1.33, SD 0.89). The use study demonstrated that 60% (486/802) of the patients used Dolodoc only once, indicating that long-term adherence remains a challenge. Within Dolodoc, pain tracking, useful links, and medication logging were the most actively used features. CONCLUSIONS: This study highlights the gap between acceptability and long-term adherence to mHealth solutions. Improving personalization and accessibility could increase user engagement and long-term adherence. Future iterations of the app should incorporate tailored interventions and real-time feedback mechanisms. In addition, leveraging a digital navigation follow-up could facilitate user adoption and sustained engagement.
17 May 2026
Read appraisal →PloS one
Effect of intra-dialytic pedaling exercise on dialysis adequacy: A randomized controlled trial
BACKGROUND: In patients with chronic kidney disease undergoing hemodialysis, physical activity and rehabilitation are crucial for preventing declines in muscle strength and functional capacity. This study aimed to assess the impact of physical activity during hemodialysis on dialysis adequacy in patients undergoing hemodialysis. METHODS: This randomized controlled trial (RCT) investigated the impact of pedaling exercise on dialysis effectiveness in 84 hemodialysis patients at hospitals in Bushehr. Participants were randomly assigned to either an experimental group (n = 42) that performed 30 minutes of pedaling exercise during their 4-hour dialysis sessions or a control group (n = 42) that received routine hemodialysis. Dialysis adequacy was assessed by comparing pre- and post-dialysis blood samples obtained from the arterial line. A conservative intradialytic exercise protocol, blood samples, and patient weight were measured using a calibrated digital scale. Data analysis was performed using SPSS version 24 software. RESULTS: The experimental and control groups were similar in demographic characteristics, except for age (X2 = -3.84, p = 0.001) and education levels (X2 = 10.100, p = 0.006). While there was no significant difference in weight between the groups before and after the intervention (t = 0.223, p = 0.82 before; t = 0.203, p = 0.84 after), both groups showed a substantial weight reduction overall (p < 0.0001). There were no statistically significant differences in weight change (t = 0.80, p = 0.25), BUN (t = 0.13, p = 1.52), or Kt/V (t = 1.62, p = 0.11) between the experimental and control groups. CONCLUSION: This study found that incorporating pedaling exercise during hemodialysis did not significantly improve dialysis effectiveness, as measured by weight change, BUN levels, or Kt/V. While both groups showed weight loss, there were no statistically significant differences between them. However, the study was limited by its small sample size and the specific exercise protocol employed. Further research with larger cohorts and a broader range of physical activities is needed to determine whether physical activity during hemodialysis can improve dialysis adequacy and overall patient outcomes. TRIAL REGISTRATION: IRCT code number 20150529022466N15 and trial Code of Ethics IR.BPUMS.REC.1398.130E.
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 →BMJ open
Developing and validating an electronic health record-embedded AI model for managing multimorbid hospitalisation risk in patients with chronic RESpiratory disease (AiRES): a study protocol
BACKGROUND: Chronic respiratory diseases (CRDs), such as asthma and chronic obstructive pulmonary disease (COPD), are heterogeneous conditions with a high multimorbidity burden. However, existing risk assessment instruments prioritise physiological measures while overlooking systemic comorbidities. We aim to develop and validate an electronic health record (EHR)-embedded artificial intelligence (AI) model-AiRES (AI in patients with RESpiratory disease)-to predict the 30-day, 90-day and 180-day risks of all-cause and index-disease hospitalisations. This model represents a first step towards a clinical decision support tool for personalised multimorbidity management in patients with CRD. METHOD AND ANALYSIS: Patients aged ≥18 years with a validated case definition of asthma and COPD will be identified from Singapore health administrative data (2012-2020). Candidate predictors will include age, sex, ethnicity, housing type, and comorbidities, measured across multiple care settings as visit frequency, grouped at quarterly intervals in Year 1 and annually for Years 2 and 3 over a 3-year lookback window. We will predict 30-day, 90-day, and 180-day risks of (1) all-cause and (2) asthma/COPD-specific hospital admissions using up to five randomly selected index dates per individual. Three machine learning algorithms-logistic regression (LR) with Lasso regularisation, eXtreme Gradient Boosting, and Categorical Boosting-will be trained using 10-fold cross-validation (CV) with an ensemble feature selection strategy. The optimal model, selected based on performance and feature importance, will be benchmarked against two reference models: a full LR and a Zero-Inflated Negative Binomial regression with hospitalisation history as the sole predictor. Discrimination and calibration will be assessed using internal-external cluster-based and temporal CV. Clinical utility will be evaluated using decision curve analysis. ETHICS AND DISSEMINATION: This study obtained ethics approval from the National University of Singapore (NUS-IRB-2024-849). Results will be published in international peer-reviewed journals.
15 May 2026
Read appraisal →European respiratory review : an official journal of the European Respiratory Society
Evolution of body image across treatment eras: a systematic review in young people and adults living with cystic fibrosis
OBJECTIVES: Advancements in treatments for cystic fibrosis (CF) have improved prognosis, but variant-specific therapies have also driven weight gain. Traditional challenges to maintain weight are now less prevalent, with new body image concerns potentially emerging. This review aims to synthesise quantitative and qualitative evidence on body image in adults and young people (aged ≥16 years) with CF. METHODS: Systematic search of MEDLINE, Embase, the Cumulative Index to Nursing and Allied Health, the Allied and Complementary Medicine Database and the Cochrane Library (January 2011 to August 2025) using CF-related keywords including body image and physical appearance. RESULTS: Searches retrieved 29 eligible studies (26 quantitative, two qualitative, one mixed methods). The Cystic Fibrosis Questionnaire - Revised (CFQ-R) and Cystic Fibrosis Quality of Life Questionnaire (CFQoL) questionnaires assessed body image quantitatively (0-100). 15 studies reported CFQ-R body image scores (58±19 to 78±23) and five reported CFQoL body image scores (21±26 to 76). Pre-modulator era (≤2012) scores ranged from 64±27 to 70±27; initial rollout phase (2012-2019) scores ranged from 58±19 to 81 (post-ivacaftor); and in the widespread modulator era (2020 to present) were 63±32 to 67 (31). Gender effects were inconsistent. Higher body mass index, weight, and body fat were linked to better body image in some studies; psychological wellbeing and lower anxiety/depression consistently correlated with body image. Ivacaftor and life coaching improved body image, while elexacaftor/tezacaftor/ivacaftor, cognitive behavioural therapy, and self-management programmes showed no effect. Functional health was strongly linked to body image.Qualitative findings highlighted influences of gender, weight change, functional and mental health, social support, early eating experiences, and limited clinician-initiated body image discussions. CONCLUSION: This is the first systematic review of body image in CF since new drug regimens emerged. Emerging body image disturbance patterns highlight the need for clinical strategies to screen for and address body image issues in CF care.
15 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 →Vaccine
Enhancing uptake of respiratory vaccinations in asthma and chronic obstructive pulmonary disease (COPD) patients: a systematic review.
INTRODUCTION: Despite influenza, pneumococcal and COVID vaccines being widely recommended for patients with chronic respiratory disease, vaccination rates in this cohort remain low. The aim of this systematic review is to identify interventions which are effective in increasing respiratory vaccination rates in adults with chronic obstructive pulmonary disease (COPD) or asthma. METHODS: The inclusion and exclusion criteria for the study can be found in the PROSPERO protocol (PROSPERO registration no: CRD42025588565). A search was run across four databases (MEDLINE, Embase, CENTRAL and ClinicalTrials.gov) in February 2025, which returned 2537 studies. Eleven studies were deemed to meet the study inclusion/exclusion criteria and these were narratively synthesised: four randomised clinical trials (RCTs), six longitudinal studies and one observational cohort study. Risk of bias was assessed using the Cochrane's Risk of Bias (RoB-V2) and ROBIN-I-V2 tools. Studies were categorised according to the COM-B model of behaviour change. RESULTS: All 11 studies consisted of COPD populations, with four studies also including asthma patients. Interventions focused on patient education, with/without involvement of a healthcare professional (HCP). Nine of the eleven studies showed a statistically significant improvement in influenza and/or pneumococcal vaccination rate with an intervention. No studies assessing COVID vaccine uptake in this population were suitable for inclusion. Most studies targeted patients' capability to get vaccinated through improving patients' and HCPs' knowledge. Fewer studies focused on social opportunity (e.g. support from other patients/HCPs) or automatic motivation (e.g. reminders). DISCUSSION: The published literature in this area is currently limited. Most studies are non-randomised and are at high-risk of bias, making meta-analysis not possible. Further research should assess the practicalities (physical opportunity) of vaccination, especially in low-income economies (where most respiratory patients reside) and standardising research methods to allow for future meta-analysis. OTHER: There is no funding for this review.
12 May 2026
Read appraisal →Journal of medical Internet research
Rheumatic Digital Twin: Proposed Machine Learning-Based Multimodal Framework to Inform Clinical Decision-Making
Rheumatic diseases are chronic, immune-mediated conditions characterized by significant heterogeneity in presentation and disease course. However, current clinical approaches often rely on snapshot-based assessments that fail to capture the complex longitudinal evolution of these conditions. To address these limitations and support the implementation of precision medicine, we present the design for the Rheumatic Digital Twin, a novel, modular conceptual framework intended to integrate heterogeneous multimodal data, ranging from electronic health records and clinical notes to imaging and omics, into a dynamic, computational representation of the patient journey. Our theoretical architecture addresses challenges related to data silos and variable availability of data modalities through a multistage approach that envisions the use of domain-specific foundation models to independently process distinct data modalities. To effectively model the temporal progression inherent in chronic diseases, the proposed design utilizes Transformer architectures, leveraging self-attention mechanisms to treat patient events, such as lab results or medication changes, as sequential data tokens. We describe how these unimodal representations would subsequently be fused via joint embedding techniques to construct a shared, multimodal representational space. Envisioned to function analogously to a recommender system, the Rheumatic Digital Twin framework is modeled to map patients into a latent space where proximity reflects clinical and biological similarity. By identifying "nearest neighbors," historical patients with comparable trajectories, the system aims to enable in silico cohorting, theoretically allowing clinicians to forecast key clinical events, predict treatment responses, and identify likely disease courses based on the outcomes of similar peers.
11 May 2026
Read appraisal →European respiratory review : an official journal of the European Respiratory Society
Rural versus urban living and COPD: a systematic review
Chronic obstructive pulmonary disease (COPD) is a leading cause of global morbidity and mortality. Emerging evidence suggests disparities in COPD outcomes between rural and urban populations, but no prior review has synthesised these differences globally. Five databases (Medline, Embase, Emcare, CINAHL and Cochrane Central) were searched in May 2025. Eligible peer-reviewed studies directly compared rural and urban populations in at least one of four measures of COPD burden: prevalence, symptom burden, exacerbations or mortality. Study quality was assessed and narrative synthesis was conducted due to heterogeneity in outcome measures. Of 1339 screened studies, 32 met inclusion criteria, spanning 13 countries. COPD prevalence was higher rurally in 83% (15/18) of studies, with 11/15 demonstrating statistical significance. This pattern was consistent across geographical distributions. Total exacerbation rates were higher rurally in 60% (3/5) of studies, although hospitalisations varied significantly. 50% (6/12) of studies reported higher hospitalisation rates in urban areas and 5/12 studies reporting higher rates in rural areas. 86% (6/7) of studies demonstrated higher mortality rurally and symptom burden was higher amongst rural residents in 67% (4/6) of studies; however, the majority of these were conducted in the USA. This review highlights consistent rural-urban inequalities in COPD prevalence and outcomes, reflecting the impact of healthcare inequities, socioeconomic deprivation and environmental exposures on COPD burden in rural areas. Targeted interventions promoting equitable healthcare access, health education, transition to cleaner fuels and rural access to smoking cessation and pulmonary rehabilitation services are essential to mitigate these disparities and improve outcomes in rural populations.
3 May 2026
Read appraisal →Journal of medical Internet research
Exploring Patient Perspectives on the Use of Artificial Intelligence to Inform Joint Decision-Making for Patients With Multiple Conditions in Primary Care in the United Kingdom: Qualitative Study
BACKGROUND: Multimorbidity, living with 2 or more long-term health conditions, is increasing globally and now affects over one-quarter of adults in England. People with multiple long-term conditions (MLTC) face complex health and treatment challenges, often experiencing fragmented care within systems oriented toward single-disease management. Artificial intelligence (AI) has the potential to support clinicians and patients by analyzing complex health data, optimizing treatment strategies, and predicting disease trajectories. OBJECTIVE: The OPTIMAL (Optimizing Therapies, Disease Trajectories, and AI-Assisted Clinical Management for Patients Living with Complex Multimorbidity) project aims to develop AI-enabled tools to support shared decision-making in primary care. This study explored how patients with MLTC perceive the use of AI to inform joint decision-making in primary care. METHODS: Semistructured interviews were conducted via telephone or video call with 29 adults living with MLTC between July and November 2023. Participants were recruited through general practitioner practices via the Clinical Practice Research Datalink and community-based organizations across the West Midlands. Interviews were transcribed verbatim and analyzed thematically using an inductive approach. Members of a patient advisory group were involved in developing study materials, refining the interview guide, and reviewing emerging findings to ensure relevance and authenticity. RESULTS: Participants identified potential benefits of AI in enhancing consultation efficiency and accuracy, improving access to information for patients and clinicians, promoting early detection of health changes, and reducing health care inequalities. However, concerns were raised about the loss of human interaction, data privacy and security, transparency of algorithms, and the potential for bias and inequity in AI systems. Trust and acceptance varied by age and familiarity with technology. Some participants expressed uncertainty about what AI entails and how it could be used in primary care. CONCLUSIONS: Patients with MLTC viewed AI-assisted decision-making in primary care with cautious optimism. While many recognized potential benefits for coordination and personalization of care, others expressed reservations about privacy, fairness, and the risk of diminished human connection.
24 Apr 2026
Read appraisal →JMIR research protocols
WhatsApp-Led mHealth Intervention for Hypertension Management Among Adults Aged 40 to 59 Years in Kerala, India: Protocol for a Mixed Methods Study
BACKGROUND: Medication adherence and lifestyle modification remain key in the management of hypertension. Leveraging mobile technologies to improve patient adherence has been found to be effective in chronic disease management. Given the high mobile penetration and the opportunities it provides for encouraging lifestyle modification, an app such as WhatsApp, which is a free-to-use and real-time messaging platform, could facilitate patient-clinician interactions. We present a protocol for a WhatsApp-led mobile health (mHealth) intervention to improve adherence to medication and healthy lifestyles among adults aged 40 to 59 years in Kerala, India. OBJECTIVE: The study aims to assess the impact of the WhatsApp-led mHealth strategy on blood pressure measures and adherence to medication and lifestyle modification. The study also focuses on exploring participants' views on feasibility, facilitators, and challenges, as well as their intention to use this WhatsApp-led mHealth strategy. METHODS: The study will follow a multiphase mixed methods (sequential explanatory) design with an initial quantitative phase (quasi-experimental study design) followed by a qualitative phase (phenomenological approach). Multistage cluster sampling will be adopted. Using a survey checklist and blood pressure measurements, community-dwelling adults aged 40 to 59 years will be screened for hypertension. Approximately 120 participants with hypertension will be assigned each to the intervention and control arms. All the participants will be advised to follow routine hypertension care from health care providers. Additionally, participants in the intervention arm will receive regular health messages and reminders over WhatsApp. A baseline survey will be conducted at enrollment, and a follow-up survey will be conducted after 3 months at the end of the intervention. The qualitative phase will involve follow-up interviews. Participants will be selected through quota sampling from those with the lowest and highest adherence to medication and lifestyle modification after receiving the intervention. Statistical analysis for survey data and thematic analysis for qualitative data will be conducted. RESULTS: The study received ethics approval (IHEC/CUK/2024/04) from the Institutional Human Ethics Committee of the Central University of Kerala. All 240 participants were recruited by July 2025. The study completed data collection in August 2025 and is expected to finish data analysis by April 2026. The study results are expected to be submitted for publication in July 2026. CONCLUSIONS: The study will be a potential strategy to address nonadherence to treatment and lifestyle regimens, which is a critical bottleneck to controlling hypertension and preventing complications. The study could be proof for a WhatsApp-led mHealth strategy that can be integrated into hypertension management at the community level, especially for improving hypertension awareness and reminders for behavior change.
22 Apr 2026
Read appraisal →Journal of medical Internet research
Effectiveness of mHealth Interventions for Improving eHealth Literacy Among Patients With Chronic Diseases: Meta-Analysis and Systematic Review
BACKGROUND: With the widespread use of the internet and mobile devices, eHealth literacy promotion is critical for medical equity. Mobile health (mHealth) serves as a pivotal tool for enhancing eHealth literacy by providing accessible, interactive platforms for health information engagement. However, the evidence regarding the effectiveness of mHealth interventions on eHealth literacy among patients with chronic diseases remains inconclusive. OBJECTIVE: This study aimed to evaluate the effectiveness of mHealth interventions on eHealth literacy among patients with chronic diseases based on randomized controlled trials (RCTs) and summarize supportive evidence from quasi-experimental and qualitative studies. METHODS: A comprehensive search strategy was developed, and 8 electronic databases were systematically searched for studies published up to February 12, 2026. Patients with chronic diseases were included based on predefined inclusion criteria. The Cochrane risk of bias 2 tool for RCTs and the ROBINS-I tool for quasi-experimental studies were used to assess the risk of bias. Given the anticipated substantial heterogeneity among the studies included, we used a random-effects model based on the Hartung-Knapp-Sidik-Jonkman method to pool effect sizes. A narrative and quantitative synthesis of the findings was provided where appropriate. RESULTS: A total of 15 studies were included in this review, including 6 RCTs, 5 quasi-experimental studies, and 4 qualitative studies, involving a total of 2884 patients with chronic diseases. Meta-analyses of RCTs suggested that mHealth interventions could improve eHealth literacy, with a pooled mean effect size of standardized mean difference (SMD)=1. 19 (95% CI 0.14-2.23; P=.03; I²=97.75%; PI [prediction interval]=-2.68 to 5.05). Subgroup analyses by intervention targets showed that interventions on targets with specific disease produced larger mean effects (SMD=1.61; 95% CI 0.16-3.06; PI=-5.40 to 8.63), while interventions targeting the population with general chronic diseases produced smaller effects (SMD=0.36; 95% CI 0-0. 73; PI=-0. 21 to 0. 94). Analysis by intervention duration subgroup showed that the combined effect of studies with intervention duration <3 months was statistically significant (SMD=0.61; 95% CI 0.09-1.13; I²=88.04%; PI=-5.72 to 6.95); while the combined effect of studies with intervention duration ≥3 months was not statistically significant. Taking into account bias and the risk of GRADE (Grading of Recommendations, Assessment, Development, and Evaluation), the certainty of RCT evidence was moderate, and the certainty of quasi-experimental evidence was low. CONCLUSIONS: mHealth interventions could improve eHealth literacy among patients with chronic diseases on average. By using prediction intervals, this study reveals that the effectiveness of mHealth interventions is highly context-dependent and closely linked to implementation factors. Advancing beyond prior work, this study centers on eHealth literacy as a core outcome and integrates multiple types of evidence. Meanwhile, this finding emphasizes the need for evidence-based intervention programs and more rigorous implementation of intervention designs in future research.
19 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 medical Internet research
Using Group Chats to Drive Behavior Change in Digital Health Interventions: Scoping Review and Realist Synthesis
BACKGROUND: Group chats on platforms such as WhatsApp (Meta Platforms, Inc), WeChat (Tencent Holdings Limited), and Telegram (Telegram FZ-LLC) are central to everyday communication in many settings, including across low- and middle-income countries and among groups often overlooked by one-to-one or app-based digital health tools. Yet their roles and underlying mechanisms as intentionally designed health interventions have not been comprehensively examined. OBJECTIVE: This scoping review with realist synthesis aimed to map the characteristics and reported outcomes of group chat-based health interventions and contextual conditions shaping their outcomes. It mapped intervention characteristics and identified context-mechanism-outcome (CMO) configurations driving behavior change. METHODS: We included empirical studies in which group chats were the primary digital component of the health intervention. Searches of PubMed, Embase, MEDLINE, Web of Science, and Scopus (2005-2026) and reference screening identified eligible studies. Data were extracted on study characteristics, health domains, settings, participants, platform, intervention features, and outcome domains. For the realist synthesis, CMO configurations were analyzed using reflexive thematic analysis informed by social cognitive theory and synthesized into a final program theory. RESULTS: Eighty-one studies were included. Publications increased sharply after 2020, with evidence clustering in mental health (25/81, 30.9%) and maternal and child health (20/81, 24.7%). Most studies enrolled adult participants, including pregnant or postpartum women, caregivers, and people managing chronic conditions. WhatsApp (38/81, 46.9%) and WeChat (21/81, 25.9%) were the most frequently studied platforms. Interventions were commonly delivered in clinical or community settings and typically involved mixed membership groups that included health professionals alongside participants (68/81, 84.0%). The realist synthesis identified 12 recurring CMO configurations across 5 domains: capability and actionability, confidence and motivation, modeling and norms, safe and supportive environment and access, and self-regulation and maintenance. These mechanisms were activated or suppressed by facilitation quality, group composition, cultural alignment, technological access, and social norms. The final program theory depicts group chats as dynamic systems where access, facilitation, and group structure shape how the domains amplify or dampen one another, explaining shifts from low engagement to high trust spaces sustaining behavior change. CONCLUSIONS: This review integrates descriptive mapping of interventions with realist program theory to explain how context and facilitation activate mechanisms of change, unlike prior reviews that have focused narrowly on effectiveness of digital modalities. This dual approach provides a practical, mechanism-focused basis for designing and scaling group chat interventions in practice, particularly given their potential as a low-cost, high-reach strategy embeddable within broader digital health programs. Realizing this potential depends on treating group chats as purposefully designed social environments, with deliberate attention to facilitation quality, equity-oriented access, and alignment between group structure, norms, and communication practices.
14 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 →BMJ open respiratory research
What is the evidence for virtual wards or hospital-at-home care pathways for exacerbations of chronic obstructive pulmonary disease? A systematic review and meta-analysis.
OBJECTIVES: Given increasing interest in admission avoidance, we evaluated the evidence to support virtual wards (VW) and hospital at home (HaH) models of care during exacerbations of chronic obstructive pulmonary disease (ECOPD). DESIGN: A systematic review and meta-analysis. A comprehensive search of MEDLINE (1946 to March 2024), Embase (1974 to March 2024) and CENTRAL (searched 22 March 2024) was conducted. Risk of bias and a random effects meta-analysis were performed. POPULATION: Adults with an ECOPD presenting to the hospital or who require hospital-led care. INTERVENTIONS: VW: defined as assessments and interventions delivered remotely or HaH (defined as assessments and interventions delivered by healthcare professionals in patient's homes) care pathways, compared with hospital admission. PRIMARY AND SECONDARY OBJECTIVES: Safety (mortality rate of all causes, in-patient, 7 days and 30 days) and readmission rate in 7 and 30 days. Length of stay in hospital and changes in pulmonary function tests. RESULTS: One study assessed VWs (reported in two publications) and 10 assessed HaH. There were no changes in survival or short-term readmission rates attributable to the interventions and no evidence that VW or HaH care pathways reduced the total time a patient spent under hospital-led care, whether at home or in the hospital. CONCLUSIONS: More evidence is needed to support the widespread roll-out of HaH and especially VW pathways for ECOPD. PROSPERO REGISTRATION NUMBER: https://www.crd.york.ac.uk/PROSPERO/view/CRD42024517565.
12 Apr 2026
Read appraisal →The Tohoku journal of experimental medicine
Age-Specific Trends and Health Status of Children Aged 12-19 Years with Specified Chronic Pediatric Diseases in Japan - Insights from a National Database Study
Japan has a national financial assistance program called the "Specified Chronic Pediatric Diseases of Japan" (SCPDJ; also called "Shouman" in Japanese) for children with chronic diseases designated by the Japanese Ministry of Health, Labour and Welfare. The information of registrants in the system is digitized for research. We utilized the database to clarify the characteristics of children with diseases designated by the SCPDJ program. Analysis was performed with a particular focus on patients aged 12-19 years, which are considered the important ages for transition support from pediatric to adult medical care. The data included 69,061 cases aged 0 to 19 years from April 2016 to March 2017. The number of registrants showed a cumulative increase from 2 years toward adulthood. There were four distribution patterns for registered age and age at onset by disease category: 1) both age and age of onset peaked at age 0; 2) age distribution was mostly flat, while the most common age of onset was age 0; 3) age distribution peaked in older age groups, while age of onset of 0 was most common; and 4) both age and age of onset peaked at older ages. Approximately half of the patients aged 12-19 years were diagnosed after reaching school age. Although the disease condition of most patients remained good, some aged 12-19 years experienced exacerbation. The database was analyzed to provide an overview of children with diseases designated by the SCPDJ program and issues related to transition to adult care systems.
10 Apr 2026
Read appraisal →Journal of medical Internet research
Supporting Access to Care Through Peripheral Devices and Patient-Generated Health Data: Qualitative Study
BACKGROUND: In 2016, the US Department of Veterans Affairs (VA) implemented a national initiative to distribute video-enabled tablets and peripheral devices, such as blood pressure monitors and weighing scales, to patients facing geographic, clinical, or socioeconomic challenges. Such patients could potentially benefit from health monitoring in conjunction with video-based care, as peripheral devices offer opportunities to enrich care received during a video visit and support tracking of health-related data collected outside of clinical care, or patient-generated health data. However, little is known about experiences with the devices and how they could support improved access to care. OBJECTIVE: We explored patients' experiences with VA-issued peripheral devices and their impact on video-based care and health monitoring outside of clinical visits. METHODS: We conducted in-depth semistructured interviews among patients who received VA-issued tablets and peripheral devices between 2023 and 2024. Purposive sampling was used to gather views based on gender, age, race or ethnicity, and rurality. Interviews were transcribed and analyzed using rapid qualitative analysis, guided by the Unified Theory of Acceptance and Use of Technology. RESULTS: Among 25 patients, most received a blood pressure monitor (21/25, 84%), a weight scale (14/25, 56%), and/or a pulse oximetry device (12/25, 48%). The majority reported using their peripheral devices (23/25, 92%) and tablets (19/25, 76%) to monitor their vital signs and attend video visits. Qualitative analysis yielded ten themes reflecting experiences and impacts of the devices, organized by the Unified Theory of Acceptance and Use of Technology constructs: "effort expectancy" consisted of (1) familiar and easy to use devices and (2) challenges of Bluetooth pairing and measurement; "performance expectancy" consisted of (3) integration with video visits, (4) health monitoring for peace of mind, (5) perceptions of improved vital signs and lifestyle behaviors, (6) removing obstacles to in-person care, and (7) desiring an overall picture of health; "social influence" consisted of (8) fostering care team connections and (9) promoting awareness of tablets and peripheral devices; and "facilitating conditions" consisted of (10) supportive help desk infrastructure. Overall, patients described using peripheral devices during virtual visits by syncing data to the tablet for real-time access by their care team. They also reported manually tracking and sharing patient-generated health data with their care team. Despite some challenges with Bluetooth pairing, patients found the devices easy to use and contributed to improved health and motivation. Devices also reduced logistical burdens of in-person visits, especially for those with limited mobility, visual impairments, mental health needs, or transportation barriers. CONCLUSIONS: Patients perceive that peripheral devices can enhance video-based care and support health care access and chronic disease management. Patients reported benefits to health, behavior, and communication with care teams. To maximize the impact, program enhancements should prioritize device interoperability, accessible training, and expanded outreach.
7 Apr 2026
Read appraisal →Journal of telemedicine and telecare
Telemedicine and digital health for chronic conditions in pediatrics: A systematic review
BackgroundThe prevalence of chronic diseases in children and adolescents has significantly increased. The COVID-19 pandemic accelerated telemedicine adoption, leading to improved healthcare access and outcomes. Despite its benefits, telemedicine is still not fully integrated into standard care. Previous reviews have been limited in scope. This systematic review aims to provide a comprehensive overview of recent trials on web or app-based telemedicine for chronically ill children and adolescents, identifying interventions and outcomes for future healthcare strategies.MethodsA comprehensive search was conducted on PubMed on November 21, 2023, and updated on January 9, 2025. Results were filtered to include prospective intervention studies involving children and adolescents with chronic conditions and limited to publications from 2017 onwards. A total of 8699 results were retrieved, and 1506 titles were screened for eligibility, resulting in 116 studies included in the review.ResultsThese studies covered 45 different conditions, with the highest numbers for diabetes, asthma, and obesity. Telemedicine interventions varied, including gamification, video meetings, integrated devices, psychological components, symptom tracking, and educational content. Most studies reported high feasibility and patient satisfaction. Clinical outcomes improved in some cases, and none were worse than standard care. The heterogeneity limited direct comparisons and meta-analysis, and small sample sizes in many studies affected the generalizability and statistical significance of the findings.ConclusionsOur study highlights the potential of telemedicine in managing chronic illnesses among children, emphasizing the need for standardized methodologies, larger sample sizes, and continued investment in infrastructure and equitable policies to fully realize its benefits in improving accessibility, convenience, cost savings, and overall health outcomes.
4 Apr 2026
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