JMIR mHealth and uHealth

The ManageHF Just-in-Time Adaptive Mobile App Interventions to Promote Self-Management and Improve Outcomes in Heart Failure: Randomized Controlled Trial

2026-07-28T15:00:05-04:00

Background: Heart failure (HF) is a major health care challenge in the United States, with approximately 900,000 older adults hospitalized annually. Gaps in self-management, including unrecognized worsening symptoms and failure to adhere to dietary sodium restriction, can reduce quality of life and precipitate hospital admissions. Existing mobile health approaches to HF self-management have produced mixed results, highlighting the need for innovative strategies to improve postdischarge outcomes in at-risk patients. Objective: The ManageHF trial aimed to evaluate the effectiveness of 2 just-in-time adaptive interventions delivered via a mobile app to enhance HF self-management. The interventions focused on symptom recognition and lower dietary sodium restriction, with the goal of reducing readmissions and improving health-related quality of life (HRQOL) over a 12-week period. Methods: The trial was a 2×2 factorial, double-blind, randomized controlled study conducted across several US institutions. Participants recently hospitalized for acute HF were randomized into 4 groups: both interventions, either intervention alone, or an active control. The primary outcome was a composite measure assessing time to all-cause death, time to first HF readmission, and HRQOL changes, using the Minnesota Living with HF Questionnaire. Results: Recruitment was hindered by the COVID-19 pandemic, leading to the early discontinuation of the trial. Of the 62 participants enrolled, 43 completed the study. Participants were diverse, with a mean age of 55 (SD 14.4) years, 32% (20/62) were female, and 55% (34/62) identified as Black or African American. Most had HF with reduced ejection fraction. However, due to the early termination and small sample size, the ability to detect statistically significant differences was limited. Conclusions: The ManageHF trial highlighted the potential of mobile health technology to support HF management, particularly in enhancing HRQOL. Future studies using more effective recruitment and retention strategies are crucial for establishing the efficacy of these interventions with greater certainty. Trial Registration: ClinicalTrials.gov NCT04755816; https://www.clinicaltrials.gov/study/NCT04755816

Mobile Phone Access, Usage Patterns, and Perceptions of Adolescents Living With HIV on the Use of Gamified Interventions to Improve Antiretroviral Therapy Adherence in Eswatini: Qualitative Study

2026-07-24T16:00:03-04:00

Background: Adolescents living with HIV often experience poor antiretroviral therapy (ART) outcomes due to multiple barriers affecting medication adherence. Effective self-care interventions are needed to address these challenges. Mobile phones are widely used by the adolescent population and therefore present an opportunity to enhance ART adherence using mobile phone–based interventions. However, research on mobile phone access among adolescents living with HIV, usage patterns, and perceptions of mobile phone–based interventions is limited in Eswatini. Objective: This study aimed to explore these aspects to inform effective mobile health strategies for enhancing ART adherence among adolescents living with HIV. Methods: We conducted a qualitative study using in-depth interviews in December 2023. A total of 29 adolescents living with HIV aged 10 to 19 years and enrolled on ART were purposively sampled and interviewed from 5 Teen Clubs in the Hhohho region of Eswatini. Interviews were audio-recorded and transcribed verbatim. Topic areas covered were mobile phone accessibility, usage patterns, and perceptions on the use of mobile phones to facilitate ART adherence. The data were analyzed using the deductive-inductive coding approach. Results: Of the 29 participants, 15 (52%) were female, and 19 (65.5%) were aged between 15 and 19 years. The study findings indicated high mobile phone access among participants, with primary usage focused on making and receiving calls, as well as engaging with social media. Three themes emerged regarding the use of gamified interventions to support ART adherence. First, the use of gamified interventions aimed at ART adherence among adolescents living with HIV was deemed feasible based on mobile phone access and past experiences with mobile games. Second, 3 main qualities of successful gamified interventions were identified as being supportive, being educational, and ensuring secure and confidential connections with other players. Finally, confidentiality and mobile phone access factors were highlighted as potential concerns when designing gamified ART adherence interventions. Conclusions: The findings suggest potentially high access and usage of mobile phones among adolescents living with HIV on ART in Eswatini. This provides an opportunity to leverage mobile technology to enhance ART adherence through gamified interventions. However, it is essential to carefully consider the specific needs and concerns of adolescents living with HIV in the design of these interventions to ensure their successful uptake and sustainability.

Mechanisms of Engagement With Mobile Health Apps for Adults With Long-Term Conditions: Overview of Systematic Reviews

2026-07-24T11:00:17-04:00

Background: Engagement is a necessary precondition for the effectiveness of mobile health (mHealth) apps for long-term physical health conditions (LTCs), particularly as health systems increasingly prioritize the deployment of scalable, self-guided digital interventions. Outside controlled research settings, where clinician involvement often drives engagement, little is known about whether, how, and why people engage with mHealth apps based on intrinsic motivation alone. Existing systematic reviews have cataloged behavioral engagement indicators but rarely assess the mechanisms underlying engagement. Objective: This overview of systematic reviews aimed to (1) synthesize evidence on how engagement with mHealth apps for LTCs is defined, measured, and associated with health outcomes, (2) explore intrinsic and extrinsic motivational processes underlying engagement, and (3) provide practical guidance for developing scalable, user-centered digital health interventions that sustain sufficient engagement with minimal reliance on external drivers. Uniquely, we interpreted modifiable barriers and facilitators through a motivational lens that distinguishes extrinsic from intrinsic motives, mapping intrinsic motives onto autonomy, competence, and relatedness, as proposed by Self-Determination Theory (SDT). Methods: Searches of MEDLINE, Web of Science, Epistemonikos, and gray literature (inception to June 9, 2025) identified systematic reviews reporting engagement indicators, engagement-outcome associations, or barriers and facilitators among adults with LTCs. Quantitative reviews were appraised using AMSTAR 2 (A Measurement Tool to Assess Systematic Reviews 2), and qualitative and mixed methods reviews were appraised using CASP (Critical Appraisal Skills Programme). A narrative synthesis was undertaken, and modifiable barriers and facilitators were independently mapped by 2 reviewers to extrinsic and intrinsic motivation and, for intrinsic factors, to the SDT constructs of autonomy, competence, and relatedness. Discrepancies were resolved through discussion with the wider research team. Results: Nineteen reviews (12 quantitative, 5 mixed methods, and 2 qualitative) were included from 4684 records. Fourteen (74%) reviews did not define engagement, and the remaining 5 equated it with “usage” or “adherence,” precluding meta-analysis. Fourteen reviews reported microlevel behavioral indicators, but none captured macrolevel or effective engagement. Eight assessed engagement-outcome links; 7 reported positive associations, and 1 reported no effect. Seven reviews included nonmodifiable factors that influence engagement (eg, ethnicity), while 13 included modifiable factors. SDT mapping revealed that modifiable factors influencing autonomy (eg, personal relevance, flexibility), competence (eg, usability, technical support), and relatedness (eg, clinician endorsement, peer connection) underpin intrinsic engagement, whereas extrinsic barriers include restrictions to access (including cost). Conclusions: Current evidence on engagement with mHealth apps remains conceptually inconsistent and methodologically fragmented, but motivational patterns are clear: engagement depends largely on intrinsic motives once external conditions are satisfied. Applying SDT provides the first mechanism-oriented explanation of how engagement operates, enabling practical recommendations for evaluating existing apps and designing future mHealth interventions that support autonomy, competence, and relatedness. Trial Registration: PROSPERO CRD42024604784; https://tinyurl.com/57prxa3d

Exploring the Design Space of Glanceable Smartwatch Feedback Displays: Experimental Study

2026-07-23T16:30:03-04:00

Background: Self-monitoring technologies are commonly used to promote health behavior change, with glanceable displays offering continuous feedback throughout the day. Yet, it is still unclear how various aspects of these glanceable representations affect their interpretability and usability. Objective: This study aimed to investigate the effects of 3 design factors—stylization, granularity, and salience—on users’ ability to understand glanceable smartwatch-based feedback on daily step goals. Methods: We conducted an online simulation study to examine how 3 design dimensions—stylization, salience, and granularity—influence the effectiveness of glanceable feedback displays. Stylization and salience were crossed in a 2×2 factorial design, while granularity varied from 1% to 20% progress increments. A total of 202 Amazon Mechanical Turk participants were randomly assigned to 1 of 16 smartwatch display conditions. In each condition, participants viewed feedback on daily step progress and estimated the level of progress shown. We measured estimation error and questionnaire-assessed perceived usability and acceptability. The collected data were analyzed using generalized estimating equations and linear regression. Results: High stylization reduced accuracy (+4.52 error points; P<.001) and negatively affected perceptions across 6 dimensions, including comprehension (P=.003), complexity (P<.001), and usability (P=.001). Granularity had a nonlinear effect: error was lowest around 5%-10%, with sharp increases at 20%. The 10% level also received the most favorable ratings, for example, comprehension (+0.656; P=.003). Salience had no effect. Previous smartwatch users were less accurate than never-users (+7.46 points) but rated displays as more useful (P=.002) and easier to focus on (P<.001). Current users gave similarly positive ratings on attention and usefulness. Conclusions: These findings could help researchers design effective glanceable smartwatch feedback displays and expand the design space for glanceable feedback.

Effects of Remote, Virtual, or Hybrid Cardiac Rehabilitation Supported by mHealth in Patients With Heart Failure: Systematic Review and Meta-Analysis

2026-07-21T16:30:14-04:00

Background: 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. Objective: 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. Methods: 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 (VO 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). Results: Eight randomized controlled trials with 1368 patients were included. In the CBCR comparison, mHealth-supported RVH-CR showed a statistically significant greater improvement in VO peak than CBCR (mean difference [MD] 0.82, 95% CI 0.06-1.57; =.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; =.04). Single-trial estimates suggested improvements in VO 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; <.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. Conclusions: 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 VO 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. Trial Registration: PROSPERO CRD420251162078; https://www.crd.york.ac.uk/PROSPERO/view/CRD420251162078

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

2026-07-21T14:00:20-04:00

Background: 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. Objective: 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. Methods: 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 ² tests were used for group comparisons. Cost-effectiveness was evaluated from a societal perspective. Results: The sensor-based rehabilitation group showed significantly greater improvement in the primary outcome (HOOS overall) than the control group at 24 weeks (=.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 <.001). By 24 weeks, hip-specific functional differences had narrowed, but SF-36 physical and mental scores (both <.001) and HADS anxiety and depression scores (both <.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; =.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 (=.002) and showed greater participation in weekly assessments and follow-up calls (both <.001). Adverse events were uncommon in both groups (5.8% vs 7.5%) and mostly minor, with no serious events reported. Conclusions: Augmenting home-based digital rehabilitation with wearable sensor feedback led to statistically significant improvements in the primary hip function outcome and in patient-reported quality of life and psychological outcomes that persisted after Bonferroni correction through 24 weeks. Several early hip-specific secondary outcome differences did not survive correction for multiple comparisons. The between-group HOOS differences were below the established minimal clinically important difference. Exercise adherence was significantly higher in the sensor group. These benefits were achieved with no increase in cost, suggesting the sensor-enhanced program is a safe and feasible approach to THA rehabilitation that enhances adherence and accelerates early recovery. Trial Registration: Chinese Clinical Trial Registry ChiCTR2500103894; https://tinyurl.com/yy5mt2ed

Outcomes of Mobile Health Use in Sinonasal Surgery: Retrospective Cohort Study

2026-07-21T09:30:12-04:00

Background: 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. Objective: 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. Methods: 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. Results: 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; =.007), 60 days (OR 0.40, 95% CI 0.19‐0.83; =.01), and 90 days (OR 0.54, 95% CI 0.29‐0.99; =.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; <.001). The majority of readmissions in both cohorts were unrelated to complications of the index sinonasal procedure. Conclusions: 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 enrollment and the observational design, these findings should be interpreted as observation findings and hypothesis-generating for prospective studies to more definitively assess the causal impact of mHealth interventions and to identify which components of digital perioperative care most effectively improve outcomes in otolaryngologic surgery.

User-Reported Issues With Mental Health Apps: Machine-Assisted Topic Analysis of Social Media Posts

2026-07-21T09:30:12-04:00

Background: 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. Objective: 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). Methods: 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. Results: 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. Conclusions: The combination of STM and human qualitative analysis of X posts identified several user-experienced issues associated with popular mental health apps, often linked to negative outcomes. This study provides evidence that STM can be combined with qualitative methods to rapidly analyze large-scale social media data and generate insights into user experience of mass-reach digital health interventions.

A Personal Health App and Wearable Co-Design Framework for Rare and Complex Diseases: User-Centered, Collaborative Co-Design Study

2026-07-20T16:00:03-04:00

Background: 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. Objective: 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. Methods: 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. Results: 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. Conclusions: 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 personal health apps with publicly available open-source code on GitHub. These prototypes could be leveraged for improving understanding of, communicating symptoms of, and providing n-of-1 suggestions for rare or complex diseases, providing benefit to patient communities and individual patients. Trial Registration:

mHealth Technologies for the Care of Children With Congenital Heart Disease: Scoping Review

2026-07-17T15:15:10-04:00

Background: 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. Objective: 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. Methods: 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. Results: 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. Conclusions: 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.