Background: People with chronic diseases can benefit from wearable devices in managing their health and encouraging healthy lifestyle habits. Wearables such as activity trackers or blood glucose monitoring devices can lead to positive health impacts, including improved physical activity adherence or better management of type 2 diabetes. Few literature reviews have focused on the intersection of various chronic diseases, the wearable devices used, and the outcomes evaluated in intervention studies, particularly in the context of primary health care. Objective: This study aims to identify and describe (1) the chronic diseases represented in intervention studies, (2) the types or combinations of wearables used, and (3) the health or health care outcomes assessed and measured. Methods: We conducted a scoping review following the Joanna Briggs Institute guidelines, searching the MEDLINE and Web of Science databases for studies published between 2012 and 2022. Pairs of reviewers independently screened titles and abstracts, applied the selection criteria, and performed full-text screening. We included interventions using wearables that automatically collected and transmitted data to adult populations with at least one chronic disease. We excluded studies with participants with only a predisposition to develop a chronic disease, hospitalized patients, patients with acute diseases, patients with active cancer, and cancer survivors. We included randomized controlled trials and cohort, pretest-posttest, observational, mixed methods, and qualitative studies. Results: After the removal of 1987 duplicates, we screened 4540 titles and abstracts. Of the remaining 304 articles after exclusions, we excluded 215 (70.7%) full texts and included 89 (29.3%). Of these 89 texts, 10 (11%) were related to the same interventions as those in the included studies, resulting in 79 studies being included. We structured the results according to chronic disease clusters: (1) diabetes, (2) heart failure, (3) other cardiovascular conditions, (4) hypertension, (5) multimorbidity and other combinations of chronic conditions, (6) chronic obstructive pulmonary disease, (7) chronic pain, (8) musculoskeletal conditions, and (9) asthma. Diabetes was the most frequent health condition (18/79, 23% of the studies), and wearable activity trackers were the most used (42/79, 53% of the studies). In the 79 included studies, 74 clinical, 73 behavioral, 36 patient technology experience, 28 health care system, and 25 holistic or biopsychosocial outcomes were reported. Conclusions: This scoping review provides an overview of the wearable devices used in chronic disease self-management intervention studies, revealing disparities in both the range of chronic diseases studied and the variety of wearable devices used. These findings offer researchers valuable insights to further explore health care outcomes, validate the impact of concomitant device use, and expand their use to other chronic diseases. Trial Registration: Open Science Framework Registries (OSF) s4wfm; https://osf.io/s4wfm

Background: Managing chronic diseases remains a critical challenge in primary health care (PHC) across the Organization for Economic Co-operation and Development countries. Electronic patient-reported outcome measures (ePROMs) are emerging as valuable tools for enhancing patient engagement, facilitating clinical decision-making, and improving health outcomes. However, their implementation in PHC remains limited, with significant variability in effectiveness and adoption. Objective: This systematic review aimed to assess the implementation and effectiveness of ePROMs in chronic disease management within PHC settings and to identify key barriers and facilitators influencing their integration. Methods: A mixed methods systematic review was conducted following the Cochrane Methods and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. We included studies that implemented ePROMs among adults for chronic disease management in PHC. The extracted data included patient health outcomes, provider workflow implications, implementation factors, and cost considerations. The reach, effectiveness, adoption, implementation, and maintenance framework was used. Results: Our search yielded 12,525 references, from which 22 (0.18%) studies were included after screening and exclusions. These studies, primarily conducted in the United States (n=9, 41%) and Canada (n=8, 36%), covered various chronic diseases and used diverse ePROM tools, predominantly mobile apps (n=9, 41%). While some studies (n=10, 45%) reported improvements in patient health outcomes and self-management, others (n=12, 55%) indicated no significant change. Key barriers included digital literacy gaps, integration challenges within clinical workflows, and increased provider workload. Facilitators included strong patient-provider relationships, personalized interventions, and technical support for users. While some studies (n=10, 45%) demonstrated improved patient engagement and self-management, long-term cost-effectiveness and sustainability remain uncertain. Conclusions: Success in implementing ePROMs in PHC appears to hinge on addressing digital literacy, ensuring personalization and meaningful patient-provider interactions, carefully integrating technology into clinical workflows, and conducting thorough research on their long-term impacts and cost-effectiveness. Future efforts should focus on these areas to fully realize the benefits of digital health technologies for patients, providers, and health care systems. Trial Registration: PROSPERO CRD42022333513; https://www.crd.york.ac.uk/PROSPERO/view/CRD42022333513 International Registered Report Identifier (IRRID): RR2-10.2196/48155

Background: Chronic diseases represent a significant global burden of mortality, exacerbated by behavioral risk factors. Artificial intelligence (AI) has transformed health promotion and disease reduction through improved early detection, encouraging healthy lifestyle modifications, and mitigating the economic strain on health systems. Objective: The aim of this study is to investigate how AI contributes to health promotion and disease reduction among Organization for Economic Co-operation and Development countries. Methods: We conducted a rapid review of the literature to identify the latest evidence on how AI is used in health promotion and disease reduction. We applied comprehensive search strategies formulated for MEDLINE (OVID) and CINAHL to locate studies published between 2019 and 2024. A pair of reviewers independently applied the inclusion and exclusion criteria to screen the titles and abstracts, assess the full texts, and extract the data. We synthesized extracted data from the study characteristics, intervention characteristics, and intervention purpose using structured narrative summaries of main themes, giving a portrait of the current scope of available AI initiatives used in promoting healthy activities and preventing disease. Results: We included 22 studies in this review (out of 3442 publications screened), most of which were conducted in the United States (10/22, 45%) and focused on health promotion by targeting lifestyle dimensions, such as dietary behavior (10/22, 45%), smoking cessation (6/22, 27%), physical activity (4/22, 18%), and mental health (3/22, 14%). Three studies targeted disease reduction related to metabolic health (eg, obesity, diabetes, hypertension). Most AI initiatives were AI-powered mobile apps. Overall, positive results were reported for process outcomes (eg, acceptability, engagement), cognitive and behavioral outcomes (eg, confidence, step count), and health outcomes (eg, glycemia, blood pressure). We categorized the challenges, benefits, and suggestions identified in the studies using a Strengths, Weaknesses, Opportunities, and Threats analysis to inform future developments. Key recommendations include conducting further investigations, taking into account the needs of end users, improving the technical aspect of the technology, and allocating resources. Conclusions: These findings offer critical insights into the effective implementation of AI for health promotion and disease prevention, potentially guiding policymakers and health care practitioners in optimizing the use of AI technologies in supporting health promotion and disease reduction.

Background: Interactive conversational agents (chatbots) simulate human conversation using natural language processing and artificial intelligence. They enable dynamic interactions and are used in various fields, including education and healthcare. Objective: This systematic review aims to identify and synthesize studies on chatbots for women and expectant parents in the preconception, pregnancy, and postnatal period through 12 months postpartum. Methods: We searched in six electronic bibliographic databases (MEDLINE (Ovid), CINAHL (EBSCO), Embase, Web of Science, Inspec, and IEEE Xplore) using a pre-defined search strategy. We included sources if they focused on women in the preconception period, pregnant women and their partners, mothers, and fathers/coparents of babies up to 12 months old. Two reviewers independently screened studies and all disagreements were resolved by a third reviewer. Two reviewers independently extracted and validated data from the included studies into a standardized form and conducted quality appraisal. Results: Twelve studies met the inclusion criteria. Seven were from the USA, with others from Brazil, South Korea, Singapore, and Japan. The studies reported high user satisfaction, improved health intentions and behaviors, increased knowledge, and better prevention of preconception risks. Chatbots also facilitated access to health information and interactions with health professionals. Conclusion: We provide an overview of interactive conversational agents used in the perinatal period and their applications. Digital interventions using interactive conversational agents have a positive impact on knowledge, behaviors, attitudes, and the use of health services. Interventions using interactive conversational agents may be more effective than those using methods such as individual or group face-to-face delivery.

Background: Digital health literacy (DHL), recognized as a key determinant of health, can influence health and well-being, improve health equity, and reduce health disparities. However, DHL is often limited among forced migrant populations, who usually lack the skills to understand and evaluate health information or to access and use digital health resources appropriately. Objective: We aimed to (1) identify effective interventions designed to improve DHL among forced migrant populations and (2) categorize and describe the characteristics of interventions that aim to improve the abilities of forced migrants or adapt digital health services to meet the needs and expectations of forced migrant populations limited by low levels of DHL. Methods: We conducted a mixed methods systematic review according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines, involving an iterative process among the authors. A medical information specialist assisted in developing a search strategy for the 6 most relevant databases (MEDLINE, Embase, CINAHL, Web of Science, Academic Search Premier, and PsycINFO) and the Google Scholar search engine, covering studies published between 2000 and 2022. Pairs of reviewers selected, individually and independently, titles, abstracts, and then full texts. Data extraction and quality assessment were performed by 2 reviewers and validated by a senior researcher. We used narrative synthesis to provide a comprehensive overview of effective DHL interventions for forced migrant populations, highlighting their success factors. Results: We identified 1845 studies, of which only 6 (0.33%) were finally selected for narrative synthesis. Studies were excluded due to irrelevance, lack of primary data, or low methodological quality. The analysis revealed a diverse methodological landscape with a predominance of qualitative approaches aimed at understanding the challenges and needs of forced migrants concerning DHL. The main challenges were associated with cultural, linguistic, and practical contexts. Interventions targeted various groups, including older adults, individuals with low literacy or education, and those with limited digital experience. We identified 4 effective educational intervention categories to enhance DHL among forced migrants: education and training; education and social support; enabling and education; and social, educational, technological, and infrastructural support. Overall, most of the studies (5/6, 83%) reported positive results in terms of improving DHL among forced migrants. Conclusions: This systematic review highlights the importance of improving DHL among forced migrant populations to promote their health and well-being. In addition, it provides comprehensive knowledge about effective interventions conducted with these groups. These findings can inform stakeholders, particularly policy makers, of the need to address low DHL among forced migrant populations. Going forward, these stakeholders need to develop innovative initiatives that rely on holistic approaches and are based on the specific needs of forced migrants to improve equity and health outcomes. Trial Registration: PROSPERO CRD42022373448; https://www.crd.york.ac.uk/PROSPERO/view/CRD42022373448 International Registered Report Identifier (IRRID): RR2-10.2196/50798

Background: Digital health literacy is considered a health determinant that can influence improved health and well-being, health equity, and the reduction of social health inequalities. Therefore, it serves as an asset for individuals to promote their health. However, low digital health literacy is a major problem among forced migrant populations. They do not always have the capacity and skills to access digital health resources and use them appropriately. To our knowledge, no studies are currently available to examine effective interventions for improving digital health literacy among forced migrant populations. Objective: This paper presents the protocol for a systematic review that aims to assess the effectiveness of digital health literacy interventions among forced migrant populations. With this review, our objectives are as follows: (1) identify interventions designed to improve digital health literacy among forced migrant populations, including interventions aimed at creating enabling conditions or environments that cater to the needs and expectations of forced migrants limited by low levels of digital health literacy, with the goal of facilitating their access to and use of eHealth resources; (2) define the categories and describe the characteristics of these interventions, which are designed to enhance the abilities of forced migrants or adapt digital health services to meet the needs and expectations of forced migrant populations. Methods: A mixed methods systematic review will be conducted according to the PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) checklist. The research will be conducted in an iterative process among the different authors. With the help of a medical information specialist, a specific search strategy will be formulated for the 6 most relevant databases (ie, MEDLINE, Embase, CINAHL, Web of Science, Academic Search Premier, PsycINFO, and the Google Scholar search engine). A literature search covering studies published between 2000 and 2022 has already been conducted. Two reviewers then proceeded, individually and independently, to conduct a double selection of titles, abstracts, and then full texts. Data extraction will be conducted by a reviewer and validated by a senior researcher. We will use the narrative synthesis method (ie, structured narrative summaries of key themes) to present a comprehensive picture of effective digital health literacy interventions among forced migrant populations and the success factors of these interventions. Results: The search strategy and literature search were completed in December 2022. A total of 1232 articles were identified. The first selection was completed in July 2023. The second selection is still in progress. The publication of the systematic review is scheduled for December 2023. Conclusions: This mixed methods systematic review will provide comprehensive knowledge on effective interventions for digital literacy among forced migrant populations. The evidence generated will further inform stakeholders and aid decision makers in promoting equitable access to and use of digital health resources for forced migrant populations and the general population in host countries. International Registered Report Identifier (IRRID): DERR1-10.2196/50798