JMIR mHealth and uHealth最新文献

{"title":"User-Reported Issues With Mental Health Apps: Machine-Assisted Topic Analysis of Social Media Posts.","authors":"Jack Bolter, Trisevgeni Papakonstantinou, Paulina Bondaronek","doi":"10.2196/85575","DOIUrl":"10.2196/85575","url":null,"abstract":"<p><strong>Background: </strong>Mobile apps marketed to support mental health have become increasingly popular in recent years. Given their widespread use, it is important to identify issues that users experience while using such apps. Understanding these issues may provide insight into the safety and suitability of these apps for individuals seeking mental health support.</p><p><strong>Objective: </strong>Unlike existing research, where user experience issues have been identified through researchers' direct analysis of apps, this study aimed to generate themes relating to user experience issues using comments from app users themselves. An additional aim was to evaluate a human-in-the-loop machine learning approach using structural topic modeling (STM) to analyze vast volumes of data gathered from X (formerly Twitter, developed by Twitter, Inc).</p><p><strong>Methods: </strong>Data relating to five of the most popular mental health apps were collected from the X API using R. A machine-assisted thematic analysis approach combined STM with human qualitative analysis to interpret user-generated posts. An unsupervised topic-modeling approach was tested using models with 5-40 topics and differing covariates (ultimately, a model without covariates was selected). Two researchers independently conducted thematic analysis to interpret and contextualize model outputs. A structural topic model with 10 topics, each comprising 20 X posts, was selected as most appropriate for generating insights.</p><p><strong>Results: </strong>Using R (developed by the R Core Team), 79,703 X posts were collected via the X API relating to five popular mental health apps. After negative sentiment filtering, 19,603 posts remained. Posts spanned March 2006 (the launch of X/formerly Twitter) to December 2022. Researchers collaboratively labeled the 10 topics to identify the primary user experience issue represented in each. Topic 3 was discarded due to low coherence and inconsistency in relation to app user experience, and Topic 5 was discarded because posts reflected app X account activity rather than user experience of the apps. The remaining eight topics were organized into four themes. The first theme, guidance shortfall, included difficulties following guided meditations, challenges selecting appropriate content from large libraries, and incompatibility between app use and home environments. The second theme, technical difficulties, involved subscription access issues and technical faults within apps. The third theme, heightened emotions related to app-affiliated celebrities, captured both over-excitement linked to celebrity involvement and anger directed toward specific celebrities. The final standalone theme, negative impacts of sleep self-monitoring, demonstrated users reporting that tracking sleep adversely affected sleep experience.</p><p><strong>Conclusions: </strong>The combination of STM and human qualitative analysis of X posts identified several user-experienced iss","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"14 ","pages":"e85575"},"PeriodicalIF":6.3,"publicationDate":"2026-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13388529/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148536003","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":"The Efficiency and Cost-Effectiveness of Wearable Sensors in a Digital Physiotherapeutic Total Hip Arthroplasty-Specific Training System for Patients After Total Hip Arthroplasty: Randomized Controlled Trial.","authors":"Chenyi Jiang, Yun Shen, Lihua Huang, Yanhong Ma, Shengdi Lu, Jimin Yin","doi":"10.2196/93050","DOIUrl":"10.2196/93050","url":null,"abstract":"<p><strong>Background: </strong>With total hip arthroplasty (THA) volumes rising worldwide, scalable home rehabilitation strategies are needed. Home-based digital physiotherapy can improve recovery after THA, and adding wearable motion sensor feedback may further enhance exercise performance and adherence. However, the impact of sensor-augmented digital rehabilitation on patient outcomes and cost-effectiveness remains unclear.</p><p><strong>Objective: </strong>This study aimed to evaluate the clinical effectiveness (including adherence) and cost-effectiveness of adding wearable sensor feedback to a home-based digital THA rehabilitation program compared with the same digital program without sensors.</p><p><strong>Methods: </strong>We conducted a single-center randomized controlled trial in Shanghai from June 2023 to June 2024. A total of 240 patients who had undergone primary THA were randomized (1:1) to a 12-week home exercise program delivered via a mobile app either with wearable motion sensors for real-time feedback (intervention) or without sensors (control). Both groups received identical exercise content and weekly teleconsultations. Outcomes were assessed at 6, 12, and 24 weeks by blinded evaluators. The primary outcome was the Hip Disability and Osteoarthritis Outcome Score (HOOS) at 24 weeks. Secondary outcomes included HOOS subscales, timed up-and-go (TUG), Berg Balance Scale, 36-item Short Form Health Survey (SF-36) physical and mental scores, Hospital Anxiety and Depression Scale (HADS) anxiety/depression, patient satisfaction, adherence metrics, and total 24-week costs. Intention-to-treat analyses were used. Mixed effects models and χ² tests were used for group comparisons. Cost-effectiveness was evaluated from a societal perspective.</p><p><strong>Results: </strong>The sensor-based rehabilitation group showed significantly greater improvement in the primary outcome (HOOS overall) than the control group at 24 weeks (P=.01). Early postoperative gains were larger: At 6 weeks, 4 of the 5 HOOS subscales, TUG time, and all patient-reported outcomes remained significant after Bonferroni correction for 47 secondary comparisons (adjusted P<.001). By 24 weeks, hip-specific functional differences had narrowed, but SF-36 physical and mental scores (both P<.001) and HADS anxiety and depression scores (both P<.001) remained significant after correction. Total 24-week costs were similar between the groups (¥87,967 vs ¥94,396 [US $12,879.80 vs $13,821.10] per patient; P=.32). The sensor intervention was associated with numerically lower costs on average (¥6428.98 [US $941.31] less per patient), yielding negative incremental cost-effectiveness ratios, though the cost difference was not statistically significant. Adherence was high in both groups but higher with sensors: The intervention group completed more exercise sessions (P=.002) and showed greater participation in weekly assessments and follow-up calls (both P<.001). Adverse events were uncommo","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"14 ","pages":"e93050"},"PeriodicalIF":6.3,"publicationDate":"2026-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13387417/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148549140","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":"Effects of Remote, Virtual, or Hybrid Cardiac Rehabilitation Supported by mHealth in Patients With Heart Failure: Systematic Review and Meta-Analysis.","authors":"Kaidong Shao, Chunqiu Liu, Tianshu Li, Huiyan Qu, Hua Zhou","doi":"10.2196/90422","DOIUrl":"10.2196/90422","url":null,"abstract":"<p><strong>Background: </strong>Structured exercise is a key component of cardiac rehabilitation (CR) for patients with heart failure (HF), but access to center-based cardiac rehabilitation (CBCR) is often limited. Mobile health (mHealth) platforms enable remote, virtual, or hybrid cardiac rehabilitation (RVH-CR) delivery.</p><p><strong>Objective: </strong>This study aimed to evaluate the effectiveness and safety of structured, exercise-focused RVH-CR supported by mHealth compared with usual care or CBCR in patients with heart failure with reduced ejection fraction (HFrEF) or in HF populations predominantly comprising patients with HFrEF.</p><p><strong>Methods: </strong>We searched PubMed, Web of Science, MEDLINE via Ovid, Cochrane CENTRAL, and CINAHL Complete from inception to April 27, 2026. Randomized controlled trials comparing mHealth-supported RVH-CR with usual care or CBCR were included. The primary outcome was exercise capacity, assessed by peak oxygen uptake (VO2 peak) and 6-minute walk distance (6MWD). Secondary outcomes included health-related quality of life and safety. Data were pooled using random-effects meta-analysis stratified by comparator. Risk of bias was assessed with the Cochrane Risk of Bias Tool version 2, and evidence certainty was evaluated using GRADE (Grading of Recommendations Assessment, Development, and Evaluation).</p><p><strong>Results: </strong>Eight randomized controlled trials with 1368 patients were included. In the CBCR comparison, mHealth-supported RVH-CR showed a statistically significant greater improvement in VO2 peak than CBCR (mean difference [MD] 0.82, 95% CI 0.06-1.57; P=.03), although this finding was based on a limited number of trials. Compared with usual care, mHealth-supported RVH-CR was associated with improved 6MWD (MD 22.99, 95% CI 1.15-44.82; P=.04). Single-trial estimates suggested improvements in VO2 peak (MD 2.50, 95% CI 0.88-4.12) and Minnesota Living with Heart Failure Questionnaire scores (standardized MD -0.57, 95% CI -0.98 to -0.17; P<.01) versus usual care. The certainty of evidence ranged from low to moderate. No intervention-related deaths or serious adverse events were reported, but sparse events and short follow-up limited conclusions regarding safety.</p><p><strong>Conclusions: </strong>The effects of structured RVH-CR supported by mHealth differed according to comparator type, but the certainty of evidence ranged from low to moderate. Compared with usual care, mHealth-supported RVH-CR was associated with improved 6MWD. Compared with CBCR, mHealth-supported RVH-CR showed a significantly greater improvement in VO2 peak in a limited number of trials, but superiority, equivalence, or noninferiority to CBCR cannot be concluded. Because usual care and CBCR are clinically distinct comparators, no single overall effect across comparator types should be inferred. Future studies should assess long-term outcomes and standardize structured exercise protocols across RVH-CR models.</p>","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"14 ","pages":"e90422"},"PeriodicalIF":6.3,"publicationDate":"2026-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13387639/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148549187","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":"Outcomes of Mobile Health Use in Sinonasal Surgery: Retrospective Cohort Study.","authors":"Heli Majeethia, Akshay R Prabhakar, Justina R Varghese, Najm S Khan, Roshan Dongre, Vincent Provasek, Faizaan I Khan, Zain Mehdi, Omar G Ahmed, Masayoshi Takashima","doi":"10.2196/75403","DOIUrl":"10.2196/75403","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Mobile health (mHealth) technologies are increasingly integrated into perioperative care to enhance patient engagement and communication. Prior studies in surgical and medical specialties suggest that mHealth platforms may be associated with reductions in hospital stay and readmissions; however, evidence supporting their impact in otolaryngology, particularly in sinonasal surgery, remains limited.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;The aim of this study was to evaluate the association between perioperative enrollment in CareSense, a patient-facing mHealth platform, and postoperative health care utilization outcomes, including hospital readmissions, emergency department (ED) visits, and length of stay (LOS), among adults undergoing sinonasal surgery.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;This is a retrospective cohort study performed at a single tertiary care academic medical center between May 2021 and January 2024. All adult patients (≥18 years) who underwent sinonasal surgery with two fellowship-trained rhinologists during the study period were included. CareSense was offered to all patients at the time of surgical scheduling, and enrollment was voluntary. Patients were categorized into CareSense participants and nonparticipants. Primary outcomes were all-cause hospital readmissions and ED visits within 30, 60, and 90 days following surgery. Secondary outcomes included the length of hospital stay among readmitted patients. Clinical, demographic, and outcome data were obtained through retrospective electronic health record review. Univariate analyses compared outcomes between groups, and multivariable logistic regression using generalized estimating equations was performed to estimate the association between CareSense participation and outcomes while adjusting for age, sex, hypertension, and diabetes.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;A total of 1135 patients were included, of whom 340 (30%) enrolled in CareSense and 795 (70%) did not. Compared with nonparticipants, CareSense participants had lower adjusted odds ratio (OR) for readmission for any cause at 30 days (OR 0.24, 95% CI 0.08-0.75; P=.007), 60 days (OR 0.40, 95% CI 0.19-0.83; P=.01), and 90 days (OR 0.54, 95% CI 0.29-0.99; P=.04). Among patients who were readmitted, mean LOS was shorter in the CareSense group than in the nonparticipating group (0.17 vs 1.68 d; P&lt;.001). The majority of readmissions in both cohorts were unrelated to complications of the index sinonasal procedure.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;This study demonstrates the benefit of CareSense in lowering postoperative readmission rates and LOS for sinonasal surgery patients, illustrating the role of medical health technology in improving patient care and quality outcomes. Perioperative enrollment in a patient-facing mHealth platform was associated with lower postoperative health care utilization and shorter hospital length of stay following sinonasal surgery. Given the voluntary nature of enroll","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"14 ","pages":"e75403"},"PeriodicalIF":6.3,"publicationDate":"2026-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13386657/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148535951","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":"A Personal Health App and Wearable Co-Design Framework for Rare and Complex Diseases: User-Centered, Collaborative Co-Design Study.","authors":"Sarah Margaret Goodday, Emma Karlin, Madeleine Sorensen, Robin Yang, Paul Gordon, Caresse Opoku, Daniel Vuong, Jenee Wilson, Diane McKenzie, Jules Piccotti, Massimiliano Tavanti, Megan Fitzgerald, Yochai Re'em, Hannah Wei, Megan Golden, Daniel Morgan, Michele Manion, Ricardo Mosquera, Tricha Shivas, Elise Hoover, Allison Peck, Nathan Peck, Zollie Yavarow, Heidi Bjornson-Pennell, Andra Stratton, Samali Anova Sahoo, Douglas Arbittier, Elizabeth Arbittier, Renee Goff, Donna Harvin-Graham, Nancy Howard, Camille Knudsen, Mary Oldham, Stephen Friend","doi":"10.2196/85425","DOIUrl":"10.2196/85425","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;End user co-design in the personal digital health technology space is underdeveloped. Clinical uptake of personal digital health technologies has been poor, highlighting a need to cocreate solutions with end users.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;The study aimed to describe an \"end user\" co-design framework in the development of 5 prototype personal health apps for patients with different rare or complex diseases.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;A patient-led, user-centered, collaborative personal health app plus wearable plug-in co-design methodology was developed. Five prototype apps were developed for end users with long COVID-19, pancreatitis, primary ciliary dyskinesia, sarcoidosis, and valosin-containing protein disease by a multidisciplinary partnership including patients, app design and development experts, user experience experts, clinicians, and patient-driven organizations. Phase 1 involved a 6-month co-design process with 5 modules involving patient-driven organizations that included the codevelopment of specifications through group workshops and independent exercises that defined the goals, content, features, and user experience of each app. Phase 2 involved app build-out, internal alpha testing, and beta study preparations. Phase 3 involved a usability beta testing study in which end users used the app and associated wearable/smart devices (Oura ring, Lumia ear device, Empatica EmbracePlus, and MIR Spirobank Spirometer) for up to 5 months. Participant feedback was documented continuously and systematically, centering on the following themes: functionality, usability, harms, benefits, self-explorations, and beta testing study details related to retention and adherence.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;While unique app goals were codeveloped by each disease group, a central goal across groups was to develop a personal health app enabling users to track subjective, self-reported symptoms, objective measures of health, and unique modifiers of symptoms. A total of 239 end user participants participated in the beta testing pilot study. Enrollment and retention rates were high, ranging from 94% to 100% and 92.2% to 100%, respectively. All active participants gave some form of feedback: there were 257 unique participant suggestions of how to specifically modify or improve the study app experience. Participant feedback themes commonly centered around customization to reduce daily burden and improve personal tailoring of the app. Participants' desires surrounding symptom displays were heterogeneous.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Personal health app co-design is rooted in a complex digital landscape that requires a significant amount of up-front effort and time. However, the up-front investment of time can result in rich and diverse end user feedback that could save time in the app development trajectory to implementation. This paper provides a co-design framework and the building blocks of 5 prototype pe","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"14 ","pages":"e85425"},"PeriodicalIF":6.3,"publicationDate":"2026-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13434255/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148535994","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":"mHealth Technologies for the Care of Children With Congenital Heart Disease: Scoping Review.","authors":"Mingzhu Wang, Qiuyin Pan, Shengrong Tan, Yuanchun Kong, Zhengling Dai, Jiao Cai, Duoqin Bi, Jiali Zhou","doi":"10.2196/83385","DOIUrl":"10.2196/83385","url":null,"abstract":"<p><strong>Background: </strong>Mobile information technology (IT) is increasingly being used in the health care sector, and it can play a critical role in both the care of children with congenital heart disease (CHD) and the quality of life of their families.</p><p><strong>Objective: </strong>This study aimed to conduct a scoping review of the application of mobile health (mHealth) technologies in the care of children with CHD. We summarized the forms of mHealth interventions and effects on CHD to provide a reference for future research in this field.</p><p><strong>Methods: </strong>We searched PubMed; Embase; Web of Science; the Cochrane Library; CINAHL; China National Knowledge Infrastructure; Wanfang Data; the Chinese Biomedical Database; VIP Chinese Science and Technology Journal Database; National Guideline Clearinghouse of the United States; the website of the Registered Nurses' Association of Ontario, Canada; the Guidelines International Network; the American Heart Association; and the American Association of Cardiovascular and Pulmonary Rehabilitation. The search period was from the establishment of the databases to June 12, 2025. The retrieved literature was screened and analyzed.</p><p><strong>Results: </strong>A total of 519 Chinese- and English-language articles were identified, with 44 (8.5%) studies meeting the inclusion criteria. The primary forms of mHealth interventions for patients with CHD included mobile apps, wearable devices, and remote monitoring equipment. The findings indicated that mHealth technologies could improve exercise capacity, nutritional status, psychological well-being, and quality of life in children with CHD.</p><p><strong>Conclusions: </strong>The application of mHealth in the care of children with CHD is feasible and demonstrates positive effects. Future research should emphasize peer education and patient privacy protection while further exploring remote education and health management based on theoretical frameworks and intelligent ITs to enhance quality of life for both children with CHD and their parents.</p>","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"14 ","pages":"e83385"},"PeriodicalIF":6.3,"publicationDate":"2026-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13379060/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148470729","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":"Tailored and Interactive Mobile Telehealth Contraceptive Counseling Compared With In-Person Care: Systematic Review and Meta-Analysis of Randomized Controlled Trials.","authors":"Maja Weinryb, Wilhelmus Ja Grooten, Andrea Koris, Margit Endler","doi":"10.2196/88887","DOIUrl":"10.2196/88887","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Use of effective contraceptive methods (ECMs) reduces maternal mortality. Person-centered counseling increases uptake, but barriers to high-quality counseling persist. Telehealth may improve access to comprehensive contraceptive care, but its effectiveness remains unclear.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study assesses the effectiveness and acceptability of tailored, interactive telehealth contraceptive counseling (TECC) compared with in-person counseling.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We conducted a systematic review and meta-analysis of English-language randomized controlled trials (RCTs) comparing TECC with in-person counseling for women and girls of any age and setting. We searched MEDLINE, Embase, Web of Science, and the Cochrane Library from inception through October 15, 2025. Outcomes were use of ECM less than 6 months from intervention (primary outcome); use of ECM at 6-12 months; use of long-acting reversible contraception (LARC); choice of ECM; choice of LARC; satisfaction with counseling; and method switching. Two researchers assessed risk of bias (RoB) using Cochrane RoB 2, certainty of evidence using GRADE (Grading of Recommendations Assessment, Development, and Evaluation), and performed meta-analysis using a random-effects model. The protocol was registered with PROSPERO (International Prospective Register of Systematic Reviews) a priori (CRD42023404402). No specific funding was received.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Eight RCTs (RoB: low, n=4; moderate, n=2; and high, n=2) and 1 cluster RCT (moderate-to-high RoB) were included in the review, with 5353 participants across all included studies. Eight studies evaluated TECC as an adjunct to in-person care (hybrid model) and 1 as a standalone model, of which 7 and 1, respectively, contributed outcome data for the meta-analyses. Certainty of evidence was low to very low. The pooled effect of 4 studies of TECC on ECM use less than 6 months showed no clear evidence of an effect (relative risk [RR] 1.10; 95% CI 0.95-1.29). The pooled effect of 4 studies of TECC on choice of ECM (RR 1.07; 95% CI 0.96-1.18) likewise showed no clear effect. The pooled effect of 4 studies of TECC on ECM use at 6-12 months showed a small but statistically significant (P=.04) effect in favor of TECC, narrowly excluding the null (RR 1.07; 95% CI 1.002-1.130). Because of high statistical and clinical heterogeneity (I2=87%-96%), results for LARC choice (2 studies) and LARC use at 0-6 months (2 studies) and 6-12 months (2 studies) were narratively described. The evidence for these outcomes was very uncertain. Narrative analysis of satisfaction across 2 studies showed no difference in effect. There were no data on method switching to support the analysis.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Current evidence suggests, with low certainty, that adjunct TECC, when delivered alongside in-person care, shows little to no effect on contraceptive use compared with in-person care. Fo","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"14 ","pages":"e88887"},"PeriodicalIF":6.3,"publicationDate":"2026-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13424753/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148470679","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":"Efficacy of a Mobile Phone-Based Life-Skills Training Program for Addiction Prevention Optimized Among Adolescents With Low Program Engagement: Cluster-Randomized Controlled Trial.","authors":"Severin Haug, Nikolaos Boumparis, Olivia Studhalter, Andreas Wenger, Michael P Schaub, Nikolai Kiselev","doi":"10.2196/78081","DOIUrl":"10.2196/78081","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Previous studies demonstrated the effectiveness of SmartCoach, a mobile phone-based life-skills training program for addiction prevention among adolescents. However, socially stratifying factors, such as educational level or migration background, were associated with lower program engagement and participation. To address these disparities, we optimized and tailored program elements, particularly for subgroups with low engagement, using qualitative interview data.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study aimed to test whether the optimized program version was superior to the original one in terms of efficacy and program use. We hypothesized that optimization and advanced tailoring would result in increased program efficacy and engagement.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;A 2-arm, parallel-group, double-blind, cluster-randomized controlled trial was conducted with assessments at baseline and follow-up after 6 months. Secondary and upper secondary school classes were randomized into two groups: (1) an intervention group receiving the optimized program version and (2) a control group receiving the original version. Participants in both groups received up to 4 weekly SMS text messages over 4 months to stimulate (1) self-management skills to cope with stress, (2) self-efficacy to resist social pressure, (3) observational learning, and (4) self-regulation. The optimized program version included additional reminders, extended time for challenges, simplified language, different days for weekly messages, and additional tailoring for participants with personal or parental backgrounds from non-German-speaking countries. This subgroup received shorter video clips and information on additional stressors, including acculturation and family conflicts. The primary outcomes of this trial were the quantity of alcohol use, the number of days per month that nicotine-containing products were smoked, and cannabis use days.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;A total of 1175 students from 67 Swiss secondary and upper secondary school classes were invited to participate in the study between September 2023 and September 2024. Of these 1175 students, 890 (75.7%; mean age 14.9, SD 1.3 y; women: n=511, 57.4%; men: n=379, 42.6%; nonbinary: n=0, 0.0%) participated in the study. Six-month follow-up assessments were completed by 552 (62.0%) of the 890 study participants. On average, program use did not differ between the study groups, with 12.6 (SD 12.8) of 38 possible activities completed in the intervention group and 12.5 (SD 12.7) activities in the control group (P=.18). The results concerning efficacy showed no significant differences between the study groups regarding the main outcomes of alcohol use quantity (P=.91), nicotine use days (P=.45), and cannabis use days (P=.67). Similarly, no significant group differences were observed for changes in perceived stress (P=.77) and social skills (P=.45).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;The result","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"14 ","pages":"e78081"},"PeriodicalIF":6.3,"publicationDate":"2026-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13372074/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148455890","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":"Passive Screening for Depressive Symptoms Using Daily Wrist Actigraphy and Deep Learning: Model Development and Validation Study.","authors":"Doljinsuren Enkhbayar, Somin Oh, Jinhee Lee, Min-Hyuk Kim, Erdenebayar Urtnasan, Jaehong Key","doi":"10.2196/91479","DOIUrl":"10.2196/91479","url":null,"abstract":"<p><strong>Background: </strong>Depressive symptoms are common yet often underrecognized in routine care, underscoring the need for scalable screening approaches beyond episodic self-report assessments. Wearable actigraphy can passively and continuously capture daily activity and 24-hour rest-activity rhythms associated with depressive symptom burden. However, the performance of artificial intelligence (AI) models that leverage actigraphy data for depressive symptom screening remains insufficiently established.</p><p><strong>Objective: </strong>This study aimed to develop and evaluate AI-based models for passive screening of depressive symptoms from daily wrist actigraphy data.</p><p><strong>Methods: </strong>We analyzed actigraphy recordings from 1160 Hispanic/Latino adults in the Hispanic Community Health Study/Study of Latinos who completed the 10-item Center for Epidemiologic Studies Depression scale (CESD-10), a self-reported depressive symptom screening scale. Multichannel actigraphy data, including activity counts, light exposure, and wake status, were used as inputs to 5 deep learning architectures to classify CESD-10-defined depressive symptom groups, comparing mild and higher symptoms with the normal group.</p><p><strong>Results: </strong>Actigraphy-derived behavioral markers differed across depressive symptom groups, showing lower daytime activity and altered circadian rest-activity organization with increasing symptom burden. Among the 5 deep learning architectures evaluated, the long short-term memory model consistently demonstrated the strongest overall discrimination. In held-out testing, the long short-term memory model achieved a macro-averaged area under the receiver operating characteristic curve of 0.80, with the strongest discrimination observed for the higher depressive symptom group (area under the receiver operating characteristic curve 0.889). These findings indicate improved model discrimination with increasing symptom severity, although false-positive rates remained notable across both classification tasks.</p><p><strong>Conclusions: </strong>Our study suggests that actigraphy-derived data can support AI-based classification of depressive symptoms. An actigraphy-based AI model may serve as a scalable, passive, and noninvasive complementary signal to aid early screening alongside traditional depressive symptom assessments before clinical diagnosis.</p>","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"14 ","pages":"e91479"},"PeriodicalIF":6.3,"publicationDate":"2026-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13372263/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148455813","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":"Frontline Health Workers' Perspectives of the World Health Organization Skin Neglected Tropical Diseases App in Kenya: Qualitative Study on AI-Embedded mHealth Implementation.","authors":"Emily E V Quilter, Ruth Nyangacha, Esther Kinyeru, Aïna Fuster Casanovas, Amberly Brigden, Kenton O'Hara, Diana Atieno, José A Ruiz-Postigo, Carme Carrion","doi":"10.2196/81829","DOIUrl":"10.2196/81829","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Skin neglected tropical diseases (NTDs) pose significant diagnostic and management challenges in resource-limited settings due to constrained dermatological expertise, frontline health worker (FHW) training, and limited access to diagnostic resources. Mobile health apps with artificial intelligence (AI)-enabled diagnostic imaging capabilities have the potential to enhance clinical decision-making and professional development at the primary care level. The World Health Organization (WHO) skin NTD mobile app uses convolutional neural networks to analyze images of skin lesions and generate differential diagnoses, intended to be used alongside clinical history and examination, to support FHWs in identifying 12 skin NTDs and 24 common skin conditions. Beyond clinical decision support, the app also aims to upskill FHWs in the recognition and management of these diseases. However, the success of such tools depends on understanding users' needs and the realities of implementation in diverse clinical contexts.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study aimed to explore FHWs' perspectives on the real-world use and impact of the AI-embedded WHO Skin NTDs app on diagnostic workflows, dermatological understanding, clinical decision-making, and FHW-patient interactions across diverse health care delivery settings in Kenya.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;This qualitative study involved 36 FHWs from 5 skin NTD-endemic counties in Kenya. Following a training workshop, FHWs integrated the app into routine clinical workflows from June to October 2024. Data were collected through 15 semistructured interviews (each 30-45 minutes) and 4 focus group discussions (1-1.5 hours) exploring FHW experiences across diverse health care delivery contexts. All sessions were audio-recorded, transcribed verbatim, and thematically analyzed using NVivo (QSR International), using a bottom-up inductive coding approach.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;FHWs reported that the app facilitated a shift from habitual referral to more proactive case management at the local-level facility, reinforcing clinical ownership and positioning them as local dermatology reference points. It was perceived to enhance diagnostic confidence, strengthen patient trust, and encourage community engagement. Some FHWs described how the app helped mitigate situations for patient stigma due to decreased reliance on public colleague consultations. However, technical limitations (eg, internet dependency and algorithmic errors) constrained consistent use. While most FHWs used the app in line with its intended role as an assistive tool, a minority reported situations of diagnostic deferral to the AI output, highlighting potential considerations of clinical autonomy.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;The WHO Skin NTDs app shows strong potential to strengthen frontline dermatological capacity that aligns with WHO strategies to decentralize NTD care and promote \"skin health for all.\" O","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"14 ","pages":"e81829"},"PeriodicalIF":6.3,"publicationDate":"2026-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13367759/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148446371","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}