BackgroundNeuromuscular activation disorders are frequently observed in patients with musculoskeletal pain and may contribute to persistent symptoms and delayed functional recovery. Neurocognitive approaches combining mindfulness and motor imagery have been proposed to target central mechanisms involved in motor control and pain modulation. Digital health tools offer an opportunity to standardize and disseminate such interventions in real-world settings.ObjectiveThe aim of this study is to describe a neuromuscular reactivation method combining mindfulness and guided motor imagery and its digital implementation via the Yuzit app and to report preliminary observational data from real-world use.MethodsThis paper primarily presents a detailed description of the intervention and its digital delivery. The protocol consists of a brief mindfulness phase followed by guided motor imagery exercises targeting specific muscle groups. In addition, we report exploratory observational data derived from the first 30 consecutive users who completed the program in routine conditions. Data were retrospectively collected through the app, including visual analogue scale (VAS) and single assessment numeric evaluation (SANE) scores, as well as user satisfaction. Analyses were descriptive and exploratory.ResultsAmong the first 30 users (mean age 50, SD 15.4 y; female: n=19, 63%), preliminary observations showed a reduction in VAS scores (from 5.62, SD 1.97 to 4.00, SD 2.15) and an increase in SANE scores (from 51.8, SD 17.2 to 65.1, SD 18.9) after completion of the program. Overall satisfaction was high or very high in 83% (n=25) of users. These findings are descriptive and should be interpreted as exploratory only.ConclusionsThis study describes a standardized digital intervention combining mindfulness and motor imagery for neuromuscular reactivation. Preliminary real-world observations suggest the feasibility of the approach and its potential to generate patient-reported outcome data. However, no conclusions regarding efficacy can be drawn. Further controlled studies are required to evaluate clinical effectiveness.

Quality care for pediatric type 1 diabetes (T1D) requires frequent, multidisciplinary visits. Technological and clinical innovation have led to changes in T1D management, resulting in increasing data exchange required during these visits. Capturing comprehensive personal health and diabetes-related information discretely and integrating it into the clinical workflow is critical for optimal T1D care but is time-consuming. Time spent on data transfer often results in less time for holistic care and can lead to unmet needs for patients, families, and health care providers, as well as increased time pressures in clinic. To address this, the Children's Hospital of Eastern Ontario developed a caregiver proxy-reported questionnaire distributed via the MyChart patient portal, allowing families to input care information ahead of visits with the aim of dedicating more clinic time to personalized care. The launch of this tool, which integrates caregiver-entered information into the physician's documentation workflow, brings the opportunity to systematically evaluate its impact on care quality and efficiency, with potential implications for broader adoption. Our objective is to evaluate the impact of a caregiver proxy-reported, electronic health record-integrated preclinic questionnaire (MyChart questionnaire) on the quality of care in a pediatric diabetes clinic, through measurement of its impact on caregiver-perceived quality of care compared to the standard of care using 2 validated measures of care quality. We also aim to explore the impact of the intervention on glycemic control and visit efficiency. We conducted a single-center, parallel-group randomized controlled trial designed for 222 children with T1D. Participants were randomly allocated in a 1:1 ratio to either the intervention (MyChart questionnaire) or standard care. Our primary outcome is caregiver-perceived quality of care, as measured by the Patient's Evaluation of the Quality of Diabetes Care at 8 months, administered with caregivers serving as proxy respondents for patients. Secondary outcomes are the Patient's Evaluation of the Quality of Diabetes Care at 4 months and Perceived Quality of Medical Care at 4 and 8 months. Tertiary outcomes include glycemic control and physician-reported visit efficiency at 4 and 8 months. Analysis of covariance models will be used to assess changes between baseline and postintervention outcomes across treatment groups. Recruitment for this study began in April 2023 and was completed in February 2024, with a total of 139 participants enrolled. Data collection has concluded, and the first results are expected in the spring of 2026. This study is the first randomized trial to assess the impact of a caregiver proxy-reported, electronic health record-integrated, preclinic questionnaire distributed via a patient portal on caregiver-perceived quality of care in a pediatric care setting. The results will guide changes in health service infrastructure and delivery to enhance comprehensive data capture and improve care quality within and beyond pediatric T1D.

Artificial intelligence (AI) has the potential to enhance patient safety, particularly in the prevention of in-hospital falls. Recent advances in sensor-based AI systems allow for the analysis of complex, multimodal data to generate real-time alerts, enabling health care professionals to intervene before a fall occurs. By shifting from reactive responses to proactive risk management, these technologies may enable reductions in fall incidence and improvements in care outcomes. As a result, hospitals across Europe are increasingly adopting such systems. Nevertheless, empirical evidence concerning their routine implementation remains limited, particularly concerning their impact on patient safety, clinical workflows, and the usage of health care resources. Addressing these gaps is essential for effective and sustainable integration into hospital care. This paper outlines the protocol for the multicenter, multimethod project SAFE (Safe AI-Assisted Fall Prevention Through Evidence), which investigates the implementation and impact of AI-assisted fall prevention in Swedish hospitals. The research project is a collaboration between Halmstad University and hospitals in the Västra Götaland Region (VGR) and will, during 2026-2028, investigate an ongoing large-scale AI system implementation in VGR hospitals, covering up to 2400 patient beds. Using surveys, interviews, observations, and a retrospective study, it will track the implementation and impact over time. Two learning laboratories involving patients, their relatives, and health care professionals will be conducted to codevelop strategies for the implementation of AI-assisted fall prevention. The project will provide evidence-based insights and practical guidance on AI-assisted fall prevention. The findings will be relevant not only to patients, health care professionals, and hospital organizations, but also to policymakers and stakeholders involved in the digital transformation of health care. Although VGR serves as the primary research setting, the project's results will inform future similar initiatives in Sweden and offer transferable lessons for other health care systems internationally. This study will contribute to the evidence base on AI-assisted fall prevention in health care, supporting the responsible and scalable integration of such systems across diverse health care environments.

Accreditation programs are used by hospitals and health services to be independently reviewed against established safety and quality standards and have been a feature of global health systems for over a century. While evidence that accreditation programs directly improve patient safety and quality outcomes exists, the findings of various researchers remain mixed. Inefficiencies and a culture of "gaming" the system have also been observed, raising questions about the overall effectiveness of accreditation programs and assessment processes. Consequently, exploration of other formats of accreditation assessment, such as short-notice accreditation assessment, has arisen. From July 1, 2023, the Australian Commission on Safety and Quality in Healthcare mandated that Australian public and private hospitals must engage in short-notice accreditation assessment. This study aims to explore the impact of short-notice accreditation assessment on hospitals, both in terms of safety and quality indicators, and organizational culture. A mixed methods design will be used to investigate these impacts. Quantitative safety and quality indicators will be drawn from a regional health service prior to and following its first short-notice accreditation assessment cycle. From the same site, staff will be invited to complete the Patient Safety Culture Survey and participate in semistructured interviews. Using Schein's Culture Framework as an organizational culture model, the study will examine observable outcomes (artifacts, behaviors, and indicators) alongside staff perceptions and experiences (norms and values) to form an understanding of underlying assumptions and beliefs about short-notice accreditation assessment processes. Quantitative data will be analyzed through cross-tabulation, trend analysis, and other statistical techniques, while qualitative data will be synthesized to provide a comprehensive understanding. This protocol outlines the planned evaluation of short-notice accreditation assessment and its influence on patient safety and quality culture within a regional health service. Data collection is underway, with preintervention surveys being completed, and recruitment open for postintervention interviews. The study is expected to generate new knowledge on how this accreditation assessment process affects patient safety and quality culture of a regional and a rural hospital. The findings will inform health policy on the suitability and long-term viability of short-notice accreditation assessment as an approach to ensuring safe, high-quality health care.

Despite the growing emphasis on open science and equity in research, qualitative data capturing diverse human experiences and perspectives are rarely reused beyond the original study. Increasingly, data repositories are used to make these data publicly available, but it is unclear whether these data can be effectively identified by researchers interested in secondary data analysis. We describe a protocol for identifying and characterizing archived qualitative datasets in leading public repositories, developing an artificial intelligence-based tool to enhance qualitative data reuse, and validating that tool using existing data. We will search 4 leading repositories to assess the scope and identifiability of existing publicly available qualitative datasets. We will subsequently build the Human Experiences and Reflections (HEARs) Archive, a directory of deidentified study data that is only accessible indirectly through the use of the HEARs Portal. The HEARs Portal will be supported by large language model-based tools using the retrieval-augmented generation framework. The artificial intelligence tools' performance will be assessed across 3 domains: relevance of identified studies, validity as evaluated by comparison with human qualitative data analysis, and robustness against the addition of irrelevant information. A preliminary review of existing data repositories has begun. The anticipated study completion date is December 31, 2026. The proposed project will provide evidence regarding the existing capacity for identifying and accessing qualitative data through leading repositories. It will also provide evidence on the validity of the HEARs Data Connector for identifying and describing qualitative datasets in ways that can assist researchers interested in secondary analysis. Establishing the validity of the HEARs Data Connector and developing an evidence-based ongoing improvement and monitoring strategy will be essential for establishing trust within the qualitative research community.

As a prevalent side effect, chemotherapy-induced nausea and vomiting (CINV) imposes a burden on the daily lives of patients with breast cancer. Multiple clinical trials have suggested the validity of acupuncture in alleviating CINV; however, the optimal acupuncture modality remains unclear. This protocol describes a systematic review and network meta-analysis to investigate the efficacy and safety of distinct acupuncture interventions for treating CINV in patients with breast cancer. Eight databases (PubMed, Embase, Web of Science, the Cochrane Library, China National Knowledge Infrastructure, VIP Database, Wanfang Database, and the Chinese Biomedical Literature Database) will be searched for eligible studies from their respective inception to July 31, 2025. The language of published studies is limited to English and Chinese. Primary outcomes are CINV intensity and clinical effectiveness rates. Secondary outcomes include recurrence rates, safety outcomes, and quality of life. Risk of bias will be assessed using the Cochrane risk of bias tool. Pairwise meta-analysis will be conducted in Stata using random-effects models with Hartung-Knapp-Sidik-Jonkman CIs. Network meta-analysis will be conducted using Bayesian Markov chain Monte Carlo methods in R software. Convergence will be assessed using Gelman-Rubin statistics and trace plots. Heterogeneity will be summarized using τ2 and τ, along with prediction intervals, when applicable. Consistency between direct and indirect evidence will be evaluated using the node-splitting method and design-by-treatment interaction test. Small-study effects will be assessed via comparison-adjusted funnel plots and the Egger test in Stata. Where feasible, subgroup analyses and meta-regression analyses will be performed. The certainty of evidence will be evaluated using the Grading of Recommendations Assessment, Development, and Evaluation framework. A preliminary scoping search was completed in August 2025, and this protocol was finalized in October 2025. The comprehensive literature search and study selection are expected to be completed by June 2026, followed by data extraction by August 2026. Data synthesis and final manuscript preparation are scheduled to be completed by December 2026. This analysis will expand the range of evidence-based acupuncture options available to clinicians for treating CINV in patients with breast cancer.

Despite high pre-exposure prophylaxis (PrEP) awareness and willingness among Chinese men who have sex with men (MSM), actual uptake remains critically low. The health action process approach (HAPA) is a 2-phase theory that addresses both the motivational and volitional phases of health behavior change, making it suitable for tackling the intention-behavior gap in PrEP use. In China, where PrEP is not covered by national health insurance, financial barriers further hinder uptake. Group-based conditional economic incentives (GCEIs) represent an innovative strategy to address cost-related disincentives by leveraging peer influence. This randomized controlled trial aims to evaluate the effectiveness of HAPA-driven interventions, both alone and combined with GCEI, to enhance PrEP initiation and adherence among high-risk, PrEP-naive MSM in China. High-risk HIV-negative MSM naïve to PrEP were recruited via community-based organizations in 3 Chinese cities. Participants underwent individual randomization to 3 arms: (1) HAPA-based cognitive behavioral intervention featuring tailored WeChat messages and 2 structured motivational interviews targeting stage-specific barriers; (2) combined HAPA intervention with GCEI linked to peer group initiation rates, incorporating facilitated offline group activities; or (3) standard care control receiving nonpersonalized HIV prevention information. The physician-prescribed PrEP initiation rate at 3 months serves as the primary outcome. Secondary outcomes include PrEP adherence, HIV risk perception, PrEP-related stigma, and intervention acceptability. Analysis follows intention-to-treat principles using mixed-effects models. The study protocol received ethics approval in December 2024 and was funded in December 2025. As of August 2025, 3 community-based organizations in Mianyang, Zibo, and Hohhot have agreed to participate. Preliminary testing has led to refinements in the WeChat mini-program, questionnaires, and motivational interview scripts. Data collection commenced in October 2025 and is projected to be completed by August 2026. As of February 2026, baseline recruitment is complete, with 381 eligible participants enrolled and randomized. The baseline characteristics were balanced across the 3 arms. Outcome data will be collected after the intervention. Data analysis is ongoing, with full results expected to be published before December 2026. This study rigorously tests a novel intervention integrating the HAPA with a GCEI model. By addressing both individual cognitive-behavioral barriers and financial disincentives within a supportive group context, this approach offers a potentially scalable strategy to bridge the PrEP uptake gap in China. Findings will provide critical evidence on combining theory-driven behavioral techniques with peer-group economic incentives for HIV prevention.

Operational research (OR) in eye care within resource-constrained settings helps develop context-specific solutions to local challenges. Building OR capacity among eye care personnel enables them to independently generate evidence that drives improvements in eye care delivery. This protocol describes the extended phase of the Institutional Operational Research Capacity Building (I-ORCB) program designed to train eye care professionals in the fundamentals and applications of OR. The I-ORCB program will be conducted in collaboration with Seva Canada and the Pragyaan Sustainable Health Outcomes Foundation over 3 years (2024-2027). A total of 10 partner eye hospitals in India and Nepal will participate. The training is organized around 7 work packages covering quantitative and qualitative research methods, data management and analysis, community engagement, scientific writing, grant writing, and ethics. The program will be implemented in two sequential phases: (1) protocol development and ethics committee submission and (2) mentoring, data collection, data analysis, and manuscript preparation. Delivery will include workshops, ongoing mentorship, e-resources, and structured monitoring mechanisms. Evaluation will follow the Kirkpatrick model, and cost-effectiveness will be assessed through the change in knowledge among the participants brought about by the workshops. This program is currently in the implementation phase. As of March 2025, a total of 10 teams have been enrolled in the I-ORCB program. Data collection for program evaluation began in June 2025 and is expected to continue until late 2026. Expected results include enhanced OR competencies among hospital teams, institutional strengthening for research, development of peer-reviewed manuscripts, and improved capacity to apply OR to service delivery challenges. The results of this program are expected to be published in 2027. The I-ORCB program applies a practical, learning-by-doing approach and is grounded in the Cooke framework for research capacity building. By integrating structured mentorship, institutional ownership, and flexible virtual learning components, the program is expected to strengthen OR culture in low- and middle-income countries and improve the delivery of eye care services in South Asia.

BackgroundBipolar disorder (BD) affects approximately 40 million people worldwide and is a chronic, potentially disabling mood disorder. Although effective treatments exist, access to evidence-informed psychosocial care remains limited, particularly for culturally and linguistically diverse populations, contributing to persistent global treatment gaps. Digital mental health interventions (DMHIs), such as smartphone apps, offer a promising means to improve access to self-management support and quality of life (QoL), an outcome prioritized by people with BD and in clinical guidelines. However, most apps for BD lack quality and are not culturally adapted or co-designed with people with BD, limiting relevance and engagement. PolarUs (mobile app) is an evidence-informed DMHI developed using co-design with people with BD. The app is structured on the core 14 domains from the Quality of Life in BD scale, the only BD-tailored scale, combined with psychoeducation on self-management strategies and QoL. A recent pilot study demonstrated promising QoL, clinical, and feasibility outcomes.ObjectiveThis study aims to culturally and linguistically adapt the PolarUs app into French, Chinese, and Spanish for the North American context using qualitative and co-design methods.MethodsGuided by community-based participatory research principles, whereby end users are engaged throughout the research process, and the Ecological Validity Framework of Bernal et al, we will engage advisory groups of people with lived experience from each linguistic community throughout the cultural adaptation process. Semimonthly virtual meetings will support systematic cultural adaptation of the self-management strategies, affirmations, and resources while maintaining fidelity to core evidence-based components. This will include cultural tailoring of app content and the identification of culturally appropriate resources. Advisory groups will also contribute to the cointerpretation of findings and the co-design of culturally appropriate recruitment and implementation strategies of PolarUs for a future clinical trial. Meetings will be recorded and coanalyzed as research data with advisory groups using qualitative reflexive thematic analysis to capture advisory group perspectives and experiences.ResultsThis study was funded in October 2024. As of January 31, 2026, we enrolled 7 participants, and the results are expected to be published in the fall of 2026.ConclusionsThe findings will support the development of a culturally appropriate DMHI for BD for additional linguistic communities, advance cultural adaptation methodologies, and inform preparation for a future clinical trial. This study will produce the first culturally adapted, BD-specific DMHI developed through co-design using a community-based participatory research approach with multilingual end users from traditionally underserved communities, advancing equitable access, engagement, and scalability of DMHIs for BD and digital health care more broadly.

BackgroundIncreased life expectancy is associated with increasing multimorbidity and polypharmacy, leading to a heightened risk of drug-drug interactions and adverse events, especially when multiple health care providers are involved. To address the urgent need for safer medication management in this population, tools such as medication plans (MP), electronic prescriptions (e-prescriptions), and clinical decision support systems (CDSS) offer valuable support. These instruments have the potential to enhance medication safety by providing physicians and pharmacists with a comprehensive overview of a patient’s overall medication regimen and by assisting health care professionals in making informed prescribing decisions.ObjectiveThis study aims to improve medication therapy safety by combining e-prescriptions, the use of claims data, MPs, CDSS, and interprofessional communication. To comprehensively evaluate this complex intervention, a holistic multiphase study will be conducted, examining (1) the effectiveness of the intervention and (2) health-economic and (3) implementation-related aspects.MethodsA multiphase study design is used. In the first phase, the intervention is implemented in selected outpatient practices (n=10) and pharmacies (n=10) in 2 regions in Germany as part of a cluster-randomized controlled trial to assess process-related outcomes. The primary outcome is the congruence between the MP and claims data. In phase 2, the intervention is scaled up in 3 regions and evaluated in a quasi-experimental study. The required sample size for the intervention group is 3528 patients, with a synthetic control group matched from existing claims data. The primary outcome is a combined end point of all-cause mortality and hospitalization within 3 months of an index prescription. Quantitative methods (descriptive, regression-based methods using claims data, calculation of the incremental cost-effectiveness ratio, and survey-based analyses of implementation-related aspects) and qualitative methods (interviews and focus groups to capture experiences of health care professionals and patients) are used.ResultsIn phase 1, a total of 187 patients were recruited (74 in the intervention group and 113 in the control group) by June 2025. Phase 2 is currently ongoing, with data collection continuing through December 31, 2025. Final analyses are planned by March 2027.ConclusionsMedication safety in polypharmacy remains a critical challenge in Germany. This study provides multiperspective evidence supporting the nationwide implementation of the eRIKA (e-prescription as an element of interprofessional care pathways for continuous medication therapy management [eRezept als Element interprofessioneller Versorgungspfade für kontinuierliche AMTS]) intervention.