JMIR mHealth and uHealth最新文献

{"title":"Long-Term Engagement With a Physical Activity App Among Gynecologic Cancer Survivors in the LETSGO Trial: 12-Month Prospective, Multicenter, Quasi-Experimental Study.","authors":"Sindre Herskedal Fosstveit, Ingvild Vistad, Mette Skorstad, Sveinung Berntsen","doi":"10.2196/84838","DOIUrl":"10.2196/84838","url":null,"abstract":"<p><strong>Background: </strong>Physical activity (PA) alleviates many treatment-related side effects in gynecologic cancer survivors, yet long-term PA levels remain low. Mobile health interventions can support self-management and increase PA levels; however, evidence from real-world, year-long engagement with smartphone apps in this population is still limited.</p><p><strong>Objective: </strong>The aim of this study is to describe 12-month user engagement with the PA component of a smartphone app implemented within a partially nurse-led routine follow-up in a real-world cohort of gynecologic cancer survivors.</p><p><strong>Methods: </strong>This descriptive study analyzed server-generated log data from the intervention arm of the prospective, multicenter, quasi-experimental LETSGO (Lifestyle and Empowerment Techniques in Survivorship of Gynecologic Oncology) trial (NCT04122235). Between December 2019 and July 2022, 378 cancer survivors (ovarian, endometrial, cervical, vulvar, or vaginal cancer) from 5 Norwegian hospitals were enrolled in the intervention arm and were offered the app plus a Garmin Vivofit 4 activity tracker alongside standard consultations. Primary outcomes for this study were (1) weekly PA registrations (objective step counts from the activity tracker and self-reported PAs) and (2) temporal patterns of step logging during each cancer survivor's first 52 weeks postenrollment. Secondary analyses compared baseline characteristics of app users (≥2 wk of PA logging) and nonusers.</p><p><strong>Results: </strong>Of 378 eligible participants (mean age 63, SD 13 y; BMI 28.5, SD 6.4 kg/m²), 272 (72%) logged at least 2 weeks of PA, and 225 (60%) synchronized objective step data. Mean daily steps were 5657 (SD 2799; median 5533, IQR 3499-7498). Step tracking dominated app use (mean 21, SD 16 logged wk), followed by self-reported walking (mean 23, SD 19 wk) and resistance training (mean 15, SD 16 wk). Weekly step-logger counts fell around study weeks 16, 32, and 44, but rebounded by 30 to 50 participants within 3 weeks, indicating episodic rather than permanent disengagement. App users were younger (mean difference -6.7 y, 95% CI -9.6 to -3.9; P<.001), more often employed (χ²1=12.7; P<.001), and more likely to have higher education (χ²2=13.6; P<.001) than nonusers. Tumor type and treatment modality were not associated with engagement.</p><p><strong>Conclusions: </strong>In a routine-care setting, nearly three-quarters of gynecologic cancer survivors engaged repeatedly with an app-supported PA module over 12 months, although mean PA levels were modest and participation was more prevalent among younger, employed, and more highly educated participants. Engagement followed an ebb-and-flow pattern, suggesting that built-in re-engagement prompts and equity-focused onboarding are needed to sustain and broaden participation. These findings support the feasibility of blended mobile health follow-up while highlighting the importance of adaptive strat","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"14 ","pages":"e84838"},"PeriodicalIF":6.3,"publicationDate":"2026-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13472232/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148760997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Conceptualization From the Sensors to Suicide-Related Outcomes: Scoping Review Based on Layered Hierarchical Sensemaking Framework.","authors":"Sohee Kim, Jinyeong Kim, Wai Tong Chien, Tzu Tsun Luk, Yu Zhang, Zhen Yang Abel Tan, Eunju Park, Heejung Kim","doi":"10.2196/98616","DOIUrl":"10.2196/98616","url":null,"abstract":"<p><strong>Background: </strong>Suicide is a leading cause of preventable mortality worldwide, with more than 700,000 deaths annually. Although suicidal ideation fluctuates rapidly, conventional risk assessments rely on retrospective self-report collected infrequently, and the detection of short-term suicide risk remains limited. Passive digital sensing using smartphones and wearable devices enables continuous monitoring of behavioral and physiological signals associated with suicide-related outcomes. However, current evidence remains fragmented, without a clear framework for translation into clinically interpretable risk indicators.</p><p><strong>Objective: </strong>This scoping review synthesized and mapped passive digital markers associated with suicide-related outcomes via the layered hierarchical sensemaking framework (LHSF), which structures information from raw sensor data to high-level behavioral markers. We aimed to illustrate a clinically interpretable mapping of digital markers for suicide-specific digital phenotyping.</p><p><strong>Methods: </strong>Following Arksey and O'Malley and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines, this scoping review was conducted using the population-concept-context framework (population: not restricted; concept: passively collected digital data from smartphones or wearable devices; and context: suicide-related outcomes). PubMed, CINAHL, PsycINFO, and IEEE Xplore were searched for studies published between 2015 and 2025. Studies were included if they (1) collected passive digital data from smartphones or wearable devices, and (2) measured suicide-related outcomes. Narrative mapping was conducted using LHSF to distinguish between low-level features (ie, measurable properties extracted from sensors) and high-level behavioral markers (ie, clinically meaningful constructs interpreted from low-level features).</p><p><strong>Results: </strong>Of 626 studies identified, 14 (2.2%) met inclusion criteria. Six (42.9%) used predictive modeling, and 8 (57.1%) conducted correlational analyses. Among predictive studies (area under the curve [AUC]=0.56-0.89), a lower heart rate variability predicted an elevated suicide risk in 1 study (AUC=0.89). Of correlational studies, 7 (87.5%) of 8 reported at least one significant association between passive sensor data and suicide-related outcomes. Mapped to the LHSF, low-level features spanned 7 domains, linked to high-level markers, such as autonomic dysregulation, sleep disturbance, social withdrawal, smartphone use patterns, and suicide-related expression. Physiological indicators of autonomic regulation were associated with suicide-related outcomes in all 4 studies examining them and achieved the highest predictive performance (AUC=0.89). Smartphone use metrics were significantly associated in both studies, whereas linguistic (2/3 studies, 66.7%) and location-based features (2/2 studies, 100%) ","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"14 ","pages":"e98616"},"PeriodicalIF":6.3,"publicationDate":"2026-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13472982/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148760208","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design Preferences for Mental Health Apps Among Nondigitally Native Adults With Chronic Pain: Qualitative Analysis.","authors":"Abby L Cheng, Christine Y Gou, Adriana Martin, Sarah M Hartz, Joanna Abraham","doi":"10.2196/87358","DOIUrl":"10.2196/87358","url":null,"abstract":"<p><strong>Background: </strong>On a population level, mental health apps are accessible and effective. However, nondigitally native adults with chronic pain are a large and growing population who have been neglected during the development process of these interventions. Although technology use is rapidly growing among this population, their engagement with mobile health-related apps is lagging because usability is often not optimized for their needs and preferences.</p><p><strong>Objective: </strong>This study aimed to identify design preferences and determinants of engagement with mental health apps by nondigitally native adults who have chronic pain and coexisting symptoms of depression or anxiety.</p><p><strong>Methods: </strong>In this qualitative study, participants completed a semistructured interview regarding their experience with, and perceptions of, mobile devices, apps, and digital health interventions. Participants were 45 years or older; scored ≥10 on the 9-item Patient Health Questionnaire, 7-item Generalized Anxiety Disorder, or both; endorsed pain on most days or every day in the past 3 months; and were living in the United States. The interview guide was informed by the Consolidated Framework for Implementation Research and the Behavioral Intervention Technology model. Codes were organized into themes. Recruitment continued until thematic saturation was achieved.</p><p><strong>Results: </strong>A total of 42 participants were interviewed (mean age 57, SD 8 years; n=32, 76% women). Participants strongly preferred apps that are free, describe strong privacy policies, and add functional value to their lives. They were more motivated by \"real-life\" goal achievement and tangible health improvements than by gamification within an app, and many were wary of allowing apps to passively collect certain types of data, especially to make inferences about their mental health. Most participants were unaware of apps designed to address chronic pain, but they were interested in the concept, particularly to help track their mood and pain and then identify associations between their symptoms, app activity, and other life events. Despite their daily use of apps, many participants described frequent challenges related to app navigation. While on-demand access to app tools was preferred, most participants appreciated the potential value of occasional push notifications if their timing was thoughtful and customizable. Participants cautioned against an overly cheerful, \"infantile,\" or informal tone for an app that addresses serious issues such as mental health and chronic pain.</p><p><strong>Conclusions: </strong>Mental health apps for nondigitally native adults should highlight tangible health improvements that can be achieved from app engagement (more so than gamification), potentially using a multidomain tracking feature, if appropriate. This population is available to receive just-in-time adaptive interventions, but the frequency and timing should","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"14 ","pages":"e87358"},"PeriodicalIF":6.3,"publicationDate":"2026-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13507721/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148712421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characteristics of Tailored Text Messages Associated With Increased Physical Activity Among Cardiac Rehabilitation Enrollees: Secondary Analysis of a Microrandomized Trial.","authors":"Namratha Atluri, Kashvi Gupta, Tanima Basu, Evan Luff, Jieru Shi, Thomas Boyden, Bhramar Mukherjee, Sachin Kheterpal, Predrag Klasnja, Walter Dempsey, Brahmajee K Nallamothu, Jessica R Golbus","doi":"10.2196/79792","DOIUrl":"10.2196/79792","url":null,"abstract":"<p><strong>Background: </strong>Emerging data suggest that text message-based mobile health interventions may enhance physical activity levels in patients with cardiovascular disease enrolled in cardiac rehabilitation. The optimal characteristics of texts that lead to maximal patient engagement and drive meaningful behavioral change are not well understood.</p><p><strong>Objective: </strong>This study aimed to understand how text- and participant-level characteristics impact physical activity levels after text delivery.</p><p><strong>Methods: </strong>The VALENTINE (Virtual Application-Supported Environment to Increase Exercise) study was a randomized controlled trial designed to evaluate a mobile health intervention delivered to low- and moderate-risk adults enrolled in cardiac rehabilitation. Embedded within this study was a microrandomized trial focused on the effect of texts on physical activity levels among intervention participants. Participants in the intervention group received texts through a smartwatch (Apple Watch or Fitbit Versa) that were tailored to the time of day, day of the week (weekday vs weekend), weather, and time since enrollment in cardiac rehabilitation. Texts also differed in content type (walking vs antisedentary) and in the level of personalization (inclusion of the participant's name or not). Delivery was randomized at 4 user-selected time points daily, with participants having a 25% probability of receiving a text at any time point. The primary outcome was step count 60 minutes after a decision point. This analysis focuses on the text- and participant-level factors that moderated the intervention's effect on the primary outcome. Given potential measurement differences determined a priori, analyses were stratified by device type and phase of cardiac rehabilitation and adjusted for age, sex, and baseline activity status using a generalization of regression analysis.</p><p><strong>Results: </strong>More than 70,552 randomizations occurred in 108 participants (mean age 59.5, SD 10.7 years; n=36, 33.3% female; n=19, 17.6% non-White; n=68, 63% Apple Watch users) over 6 months. Overall, no text characteristics (including personalization with the participant's name) or participant characteristics (including baseline physical activity) consistently impacted text responsiveness for either device type. Although the findings were not consistently significant between device types and across phases of the trial, there was a trend toward increased responsiveness to texts that promoted walking (compared to antisedentary texts) and that were delivered to younger (aged <65 years) and male participants.</p><p><strong>Conclusions: </strong>In this randomized clinical trial, we found that tailored texts improved physical activity levels among cardiac rehabilitation enrollees in the initiation phase, but this effect was not explained by text- or participant-level moderators. Additional work is needed to explore the impact of tailoring base","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"14 ","pages":"e79792"},"PeriodicalIF":6.3,"publicationDate":"2026-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13507717/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148712457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Functionality Review of Mobile Apps for the Tracking and Self-Management of Fatigue: Systematic Search in App Stores and Content Analysis.","authors":"Amr Diouf Abdulla, Corina Sas, Gavin Doherty","doi":"10.2196/84755","DOIUrl":"10.2196/84755","url":null,"abstract":"<p><strong>Background: </strong>Fatigue and chronic fatigue syndrome (CFS) have a considerable impact on quality of life, thus motivating people to develop skills for better management of their fatigue. While the number of commercial apps in this domain has increased, there has been limited exploration of their functionalities.</p><p><strong>Objective: </strong>This paper aims to address this research gap through a functionality review of 17 top-rated iOS and Android apps for fatigue, with the aim to articulate design implications for technologies focused on supporting the management of fatigue.</p><p><strong>Methods: </strong>We conducted a systematic search on the 2 most common app marketplaces, which resulted in the initial identification of 427 Apple apps and 1218 Google apps. From these, 17 apps were selected for review after applying a screening process to shortlist the top-rated apps. The functionalities of these apps were then coded through a week-long usage of each app for an expert evaluation leveraging authors' human-computer interaction (HCI) expertise. We looked for functionalities such as tracking and visualization seen in previous research on functionality reviews, in addition to interventional functionalities, which were informed by research on fatigue.</p><p><strong>Results: </strong>Findings reveal the prevalence of functionalities for tracking fatigue (8/17, 47%), related symptoms (8/17, 47%), for visualizing tracked content (10/17, 59%), for assessing the user's condition (2/17, 12%), and for providing interventions for the management of fatigue (12/17, 71%). Functionalities providing interventions for self-management of fatigue are surprisingly limited, with the most relevant ones including pacing (2/17, 12%) alongside energy estimation (2/17, 12%).</p><p><strong>Conclusions: </strong>The top-ranked apps for fatigue in the major marketplaces support 3 main functionalities under the scope of tracking fatigue along with related data, and visualizing such data, with limited provision of self-management interventions. Drawing from these findings, we articulate implications for the sensitive design of technologies to support the management of fatigue, including supporting hybrid tracking, combined visualizations to support sense-making of fatigue data with related factors, and supporting energy estimates and pacing interventions.</p>","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"14 ","pages":"e84755"},"PeriodicalIF":6.3,"publicationDate":"2026-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13460801/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148712406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Patient-Reported and Technology-Assisted Monitoring in Orthotic Management of Adolescents With Idiopathic Scoliosis: Scoping Review.","authors":"Anna Mathew, Kamila Sykorova, Nenad Pavel, Marianne Bakke Johnsen, Minna Pikkarainen, Sadeeq Ali, Mette Fløystad Kvammen, Parisa Gazerani","doi":"10.2196/88880","DOIUrl":"10.2196/88880","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Orthotic treatment for adolescents diagnosed with idiopathic scoliosis is long-term and often associated with challenges related to treatment adherence. Traditional patient monitoring strategies include clinical visits combined with patient discussions, clinical examination reports, and the use of standard questionnaires. Sensor-assisted monitoring is explored to improve treatment outcomes, with technology influencing different aspects of the health care system.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;The scoping review aimed to map evidence based on 3 research questions (RQs), namely user experience and perception, monitoring tools, and technology-assisted approaches, including smart orthoses with sensors, during orthotic treatment for an adolescent patient (aged 10 to 17.11 y) diagnosed with idiopathic scoliosis.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;A systematic search was conducted in MEDLINE, Embase, PsycINFO, Cochrane Library, CINAHL, Web of Science, and Scopus as 2 complementary search components. The primary search targeted studies on smart orthoses, also called braces, and scoliosis, while the secondary search focused on user experiences with orthotic treatment to capture all 3 RQs. PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-analyses extension for Scoping Reviews) guidelines and checklist supported searching, analyzing, and reporting the results systematically. Predefined inclusion and exclusion criteria were followed for screening. All articles published up to May 2024 were included. Moreover, 2 independent reviewers screened 2088 articles in 2 stages of screening. Data coding was conducted using the 3 RQs by data extraction and its synthesis.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;A total of 88 articles met the inclusion criteria. Evidence from user experience studies highlighted discomfort, psychosocial burden, and demand for real-time feedback. Monitoring relied primarily on patient-reported outcome measures (PROMs) such as questionnaires and logbooks. Culturally adapting to patients' diverse global needs helps capture richer and more candid user perspectives. Sensor-based systems used temperature, force, or pressure, electromyography, and motion sensors to track orthosis wear time, pressure distribution, activity, and posture. Two overarching monitoring themes emerged: subjective (patient-reported or user experience) and objective (technology-assisted or sensor-based) monitoring. Integrated approaches synthesize both.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Subjective clinical tools and objective technologies help monitor orthosis wear of adolescent patients with idiopathic scoliosis. Co-design of a user-centered scoliosis management system for adolescents that integrates PROMs with measured sensor data could provide a multidimensional view of orthosis adherence along with psychosocial and clinical effectiveness. Future research will focus on user-centered care, with real-time integrated monitorin","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"14 ","pages":"e88880"},"PeriodicalIF":6.3,"publicationDate":"2026-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13455584/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148700452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Patient-Facing AI-Enabled Digital Health Technologies and Quality of Life in Cancer: Systematic Review and Exploratory Meta-Analysis.","authors":"Anica Ilic, Lene Kristine Juvet, Patrick Cairns, Kristen Elizabeth Thompson Thornton, Hanne Cathrine Lie","doi":"10.2196/94793","DOIUrl":"10.2196/94793","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Cancer affects multiple physical, psychological, and social aspects of an individual's life. Cancer survivors frequently report unmet needs long after diagnosis and require ongoing support. AI is increasingly embedded in patient-facing digital health technologies (DHTs) in oncology, yet its impact on different domains of patients' and survivors' health-related quality of life (HRQOL) remains unclear.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This systematic review aims to (1) examine how AI has been integrated into patient-facing DHTs designed to support cancer survivors, (2) narratively synthesize the potential effects of these technologies on HRQOL and provide preliminary quantitative estimates through an exploratory meta-analysis, and (3) explore broader changes in additional patient-reported outcomes (PROs; secondary aim).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;PubMed, PsycINFO, Embase, Scopus, CINAHL, and the Cochrane Library were searched for articles published between January 2020 and August 2025. Reference lists of included articles were hand-searched for additional eligible studies. Eligible studies enrolled cancer survivors of any age and disease stage, evaluated a patient-facing DHT with AI components, and assessed HRQOL. Nonoriginal research and non-English reports were excluded. Risk of bias was assessed in all controlled studies using RoB 2 (revised Cochrane risk of bias 2) or ROBINS-I V2 (Risk of Bias in Non-Randomized Studies-of Interventions, Version 2), according to study design. Data on HRQOL and other PROs were synthesized narratively, and exploratory random-effects meta-analyses were conducted for HRQOL domains.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Eight reports from 7 studies from China and the United States (N=2867 participants) met the inclusion criteria, and 3 (n=292 participants) contributed to the exploratory meta-analysis. All studies included adults with various cancers at different stages and times since diagnosis. Most studies showed low risk of bias or some concerns (RoB 2), but one was evaluated as having a serious risk of bias (ROBINS-I V2). AI applications ranged from symptom monitoring to targeted education. The narrative synthesis suggested positive effects on selected HRQOL domains, particularly general health, with more pronounced effects in studies conducted in China. Exploratory meta-analyses demonstrated provisional moderate positive effects on global health (Hedges g=0.77, 95% CI 0.15-1.40) and social functioning (Hedges g=0.75, 95% CI 0.08-1.42), but no effects on physical functioning, role functioning, or emotional well-being. Other PROs indicated generally high user satisfaction and adherence, improved mental health outcomes, and reductions in physical symptoms. Only minor and mild adverse events were reported.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Current evidence, although limited, suggests that AI-enabled patient-facing DHTs may benefit survivors' HRQOL and other PROs, particularly in ear","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"14 ","pages":"e94793"},"PeriodicalIF":6.3,"publicationDate":"2026-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13456306/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148705702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Behavioral Mechanisms of a Digital Health Intervention for Self-Management in Type 2 Diabetes Mellitus: Prospective Longitudinal Cohort Study.","authors":"Yibo Wu, Yang Ni, Yang Jiang, Zijie Xu, Hewei Min, Ping Chen, Xinbao Gu, Bingyang Kong, Yadi Gan, Pei Li, Mingzi Li, Xiaohui Guo, Xuxi Zhang, Aijuan Ma, Xinying Sun","doi":"10.2196/79081","DOIUrl":"10.2196/79081","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Sustaining self-management is critical for optimizing clinical outcomes in individuals with type 2 diabetes mellitus (T2DM). Although digital health interventions (DHIs) have shown benefits for glycemic control and self-care, much of this evidence has focused on efficacy, and the behavioral mechanisms through which DHIs produce sustained effects remain insufficiently understood. Clarifying these mechanisms could inform the development of theory-driven interventions.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study examined the longitudinal behavioral pathways through which Artificial Intelligence-based Health Education Accurately Linking System, a WeChat (Tencent)-based digital health program, influences T2DM self-management, using the Extended Multi-Theory Model (MTM) of health behavior change.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;An explanatory sequential mixed methods prospective longitudinal cohort study was conducted among adults with T2DM (aged ≥18 y and proficient in WeChat use), recruited from 45 primary health care institutions in Beijing, China, between July 2023 and July 2024. Self-management behavior was assessed as the primary outcome using the Summary of Diabetes Self-Care Activities, and psychosocial determinants using the Extended MTM Scale and the Diabetes-related Skills Scale. Exploratory and confirmatory factor analyses assessed the construct validity of the Extended MTM Scale. Structural equation modeling examined longitudinal pathways among Artificial Intelligence-based Health Education Accurately Linking System users across baseline and 3, 6, and 12 months. For the qualitative phase, a purposive subsample was selected through maximum variation sampling based on baseline glycated hemoglobin; interviews were analyzed thematically until thematic saturation, and integrated with quantitative findings using a joint display.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Of the 406 enrolled participants, 391 completed baseline assessments. The Extended MTM Scale demonstrated a 6-factor, 22-item structure with excellent internal consistency (Cronbach α=0.928) and satisfactory construct validity. The structural equation modeling showed satisfactory fit (CFI=0.984, RMSEA=0.036). Changes in the social environment (β=0.23, 95% CI 0.07-0.38; P=.003) and physical environment (β=0.25, 95% CI 0.10-0.40; P=.001) at baseline, and diabetes-related skills at month 6 (β=0.16, 95% CI 0.03-0.29; P=.01), were directly associated with self-management behavior at month 12, whereas behavioral confidence and emotional transformation showed no significant direct effects. Social environment changes were indirectly associated with behavioral confidence through participatory dialogue at month 3 (β=0.20, 95% CI 0.04-0.36; P=.01; β=0.66, 95% CI 0.57-0.74; P&lt;.001). Thematic analysis of 17 interviews identified 3 domains: environmental context, cognitive processes, and attitudes and skills. Environmental factors converged across both data strands, whil","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"14 ","pages":"e79081"},"PeriodicalIF":6.3,"publicationDate":"2026-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13455579/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148700454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Barriers and Enablers to Integrating Patient-Generated Health Data in Shared Decision-Making From Health Care Professional and Patient Perspectives: Scoping Review.","authors":"Pavithren V S Pakianathan, Devender Kumar, Jayathissa Prabath, Rada Hussein, Josef Niebauer, Albrecht Schmidt, Jan Smeddinck","doi":"10.2196/85197","DOIUrl":"10.2196/85197","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Advances in sensor technologies and increased adoption of wearables and smartphones by individuals have led to an abundance of patient-generated health data (PGHD). This data, when used effectively, could help to further augment the process of shared decision-making (SDM) to enable patient-centered care. However, the possible integration and usage of PGHD introduces complexities and challenges, which warrant considering both health care professional (HCP) and patient perspectives.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;Summarize the relevant works from the past 10 years that reflect the perspectives of both HCPs and patients as key stakeholders on potential barriers and enablers to the integration of PGHD for SDM. We analyzed both perspectives to surface key challenges and opportunities with integrating PGHD throughout patient journeys, as well as clinical workflows.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;Electronic searches were done using 3 databases: PubMed, ACM Digital Library, and IEEE Xplore for papers published between March 2013 and March 2023. Enablers and barriers mentioned by the stakeholders in included papers were extracted and analyzed using thematic analysis. An existing six-stage workflow model for integrating PGHD was used as a reference for deductive coding. Subsequently, considering barriers and enablers faced by both the HCPs and patients uncovered various tensions and alignments of perspectives, which could be addressed in future work and can inform concepts, designs, and development in PGHD for SDM.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;A total of 53 publications were included in the scoping review. Six main overarching themes for barriers and enablers were identified: (1) patient-provider relationship, (2) patient characteristics, (3) organizational factors, (4) medical ethics and law, (5) data-driven workflow, and (6) design and technology. The 6-stage workflow was further expanded based on the new findings to include 4 additional stages, which include contextual considerations outside of traditional clinical environments. In addition to partially corroborating previously established barriers in the 6-stage workflow model, several new barriers and enablers were identified throughout all stages. This model helps to further align the needs of HCPs and patients beyond the clinical setting and could benefit system designers who plan to integrate PGHD for SDM.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;This scoping review demonstrates that there are several factors to consider for effectively integrating PGHD into health-related SDM. Notably, such factors extend outside the boundaries of traditional clinical settings. Although there is agreement between HCPs and patients on certain factors, there are also tensions to be addressed. Our augmented 10-stage workflow model offers system designers an overview of the challenges and enablers to consider while designing for PGHD integration in clinical workflows and patient journ","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"14 ","pages":"e85197"},"PeriodicalIF":6.3,"publicationDate":"2026-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13456309/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148706588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Brief Web-Based Psychological Intervention for Depressive Symptoms Among Chinese Adolescents: Randomized Controlled Trial.","authors":"Pei Liu, Xinwei Wang, Xiaoxia Duan, Mingjing Situ, Yujie Tao, Zhaozhi Yang, Shengnan Zhao, Lei Li, Sixun Li, Yuchu Jiang, Manxue Zhang, Di Jing, Xinyi Yu, Yi Huang","doi":"10.2196/86134","DOIUrl":"10.2196/86134","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Adolescents with depressive symptoms are at increased risk of social functional impairment and are more likely to develop major depressive disorder. Digital interventions offer advantages, such as high accessibility, especially for adolescents. However, evidence on the effectiveness of web-based psychological interventions in alleviating depressive symptoms among adolescents remains limited.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study aims to develop a brief web-based psychological intervention tailored to the developmental and psychological characteristics of Chinese adolescents and to evaluate its effectiveness and influencing factors.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;In a 2-arm randomized controlled trial, adolescents aged 12 to 18 years with depressive symptoms were recruited from high schools in China. Eligible participants were randomly assigned in a 1:1 ratio to the intervention group (n=212) or the control group (n=224). Participants in the intervention group received a 4-week brief web-based emotional cognitive training program, whereas those in the control group received a web-based psychoeducation program. Nonprofessional helpers provided minimal support through text messages or phone calls. The primary outcome was depressive symptom severity. Secondary outcomes included the depressive symptom remission rate, changes in anxiety symptoms, suicidal ideation, and resilience. Data were collected at baseline (T0), postintervention (T1), and at 1- and 3-month follow-ups (T2 and T3). Statistical analyses included analysis of covariance (ANCOVA), logistic regression analysis, and mediation analysis.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Two-way repeated-measures ANCOVA revealed a significant time effect (F&lt;sub&gt;3,1461&lt;/sub&gt;=82.515; P&lt;.001; η&lt;sup&gt;2&lt;/sup&gt;&lt;sub&gt;p&lt;/sub&gt;=0.140) on depressive symptom severity, with significantly lower scores at T1, T2, and T3 than at T0. No significant group effect (F&lt;sub&gt;1,1461&lt;/sub&gt;=1.039; P=.31; η&lt;sup&gt;2&lt;/sup&gt;&lt;sub&gt;p&lt;/sub&gt;=0.001) or time-by-group interaction (F&lt;sub&gt;3,1461&lt;/sub&gt;=2.424; P=.06; η&lt;sup&gt;2&lt;/sup&gt;&lt;sub&gt;p&lt;/sub&gt;=0.005) for depressive symptom severity was observed. Post hoc exploratory analysis showed that among adolescents with anxiety symptoms, the intervention group exhibited a higher depressive symptom remission rate at T1 than the control group (adjusted odds ratio 1.39, 95% CI 1.05-1.85; P=.02; number needed to treat=7). Additionally, the intervention group showed significantly greater improvements in the interpersonal support dimension of resilience at T1 (least squares mean difference=1.79, 95% CI 0.53-3.06; Cohen d=0.37, 95% CI 0.11-0.63; P=.006; false discovery rate-adjusted P=.04). Exploratory mediation analysis identified a significant indirect effect between the intervention and depressive symptom remission via the interpersonal support dimension of resilience at T1 (indirect effect=0.08, 95% CI 0.02-0.14; P=.009).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;The brief web-based psyc","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"14 ","pages":"e86134"},"PeriodicalIF":6.3,"publicationDate":"2026-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13498909/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148689134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}