#MobileHealth

JMIR Publications

@jmirpub.bsky.social

2 days ago

Locomotive Syndrome Digital Therapeutics Provided via a Smartphone App: Proof-of-Concept Single-Group Trial Study Background: Individuals with locomotive syndrome (LS) have muscle weakness and reduced motor function due to musculoskeletal disorders that cause reduced mobility and physical function. In Japan, musculoskeletal disorders are the most common reason for requiring home support or nursing care, highlighting the need for preventing and ameliorating LS. Middle-aged and older adults sometimes encounter difficulty making a habit of exercise therapy (the mainstay of LS treatment). Objective: We investigated whether digital therapeutics (DTx) can prevent or ameliorate LS in middle-aged and older adults. Methods: We conducted a prospective, longitudinal, nonrandomized, single-group study of Japanese aged 40 years and older who were eligible for LS checkups (N=47). Each participant underwent an 8-week locomotion training intervention based on DTx supervised by medical staff. We objectively assessed the participants’ subjective and objective motor abilities and motor awareness with the Timed Up and Go (TUG) test, 25-question Geriatric Locomotive Function Scale (GLFS-25), and Behavioral Regulation in Exercise Questionnaire-3 at baseline (before the DTx), an interim point (4 wk after the DTx initiation), and a final evaluation (8 wk post-DTx initiation). We compared the scores of the 3 tests at the 3 time points as dependent variables in a 3-factor ANOVA with Bonferroni correction (significance defined as 0.05/3=0.0167). Results: No increase in amotivation to exercise or refusal to exercise was observed. Significant improvements at 8 weeks versus the baseline were observed in the TUG scores (baseline: 9.0, 95% CI 8.4‐9.6; 8 wk: 7.5, 95% CI 7.1‐8.0; =.001) and GLFS-25 results (baseline: 18.7, 95% CI 14.5‐22.8; 8 wk: 11.7, 95% CI 8.8‐14.7; =.004). The Behavioral Regulation in Exercise Questionnaire-3 and its subscale data did not differ significantly at any assessment time point. Conclusions: These results indicate that an 8-week locomotive training intervention using DTx significantly improved middle-aged and older adults’ TUG and GLFS-25 scores and will help prevent and ameliorate LS and establish better exercise habits among them. Trial Registration: University Hospital Medical Information Network Clinical Trial Registry UMIN000053922;

New in JMIR Aging: Locomotive Syndrome Digital Therapeutics Provided via a Smartphone App: Proof-of-Concept Single-Group Trial Study #LocomotiveSyndrome #DigitalTherapeutics #ExerciseTherapy #MusculoskeletalHealth #MobileHealth

JMIR Publications

@jmirpub.bsky.social

3 days ago

Designing an mHealth App to Encourage Uptake of Muscle-Strengthening Exercise in Older Adults: Co-Design Focus Group Study Background: Sarcopenia, the age-related decline in muscle mass and strength, poses a significant threat to functional independence in older adults. Despite strong evidence supporting resistance training as a preventive and therapeutic strategy, adherence to muscle-strengthening guidelines remains low. Mobile health (mHealth) technologies offer a promising avenue to bridge this gap; however, few apps are tailored to older adults or designed with their input. Objective: This study aimed to identify key features that a muscle-strengthening exercise app should include to enhance engagement and uptake among older adults. Secondary aims were to explore perceived barriers and facilitators to app use and to inform the development of an evidence-based, co-designed mHealth intervention. Methods: We used a qualitative co-design approach, involving 4 focus groups with 18 older adults (aged 60-83 years); each group comprised 3 to 6 older adults, stratified by experience with mHealth apps. Sessions were conducted online via Microsoft Teams and guided by a semistructured protocol informed by prior mHealth research and behavior change theory. Transcripts were analyzed using deductive thematic analysis, underpinned by the Technology Acceptance Model, focusing on perceived usefulness and perceived ease of use. Results: A total of 4 overarching themes and 10 subthemes were identified. Theme 1, mHealth as a tool for supporting health and well-being, highlighted participants’ recognition of digital tools in promoting activity and overcoming accessibility barriers. Theme 2, motivation and engagement through app features, revealed the importance of reminders, progress tracking, and feedback, although views on gamification were mixed. Theme 3, drawbacks of current mobile apps, captured concerns around complexity, poor usability, and lack of age-appropriate content, with skepticism regarding safety and evidence base. Theme 4, desired app elements and features, emphasized the need for customizable reminders, clear instructional videos, adaptable exercise options, and optional social features. Participants stressed the importance of simplicity, personalization, and relatable content to foster trust and sustained engagement. Conclusions: Older adults are receptive to mHealth interventions for muscle-strengthening when design is user centered and grounded in their lived experiences. This study provides a framework for future app development, highlighting the need for intuitive interfaces, personalized features, and credible educational content. By aligning design with Technology Acceptance Model constructs and co-design principles, mHealth apps can better support healthy aging and sarcopenia prevention. These findings offer actionable guidance for developers and researchers aiming to enhance digital health equity and effectiveness in older populations. Clinical Trial: Open Science Framework 10.17605/OSF.IO/J64ER; https://osf.io/j64er/overview

New in JMIR Aging: Designing an mHealth App to Encourage Uptake of Muscle-Strengthening Exercise in Older Adults: Co-Design Focus Group Study #mHealth #ElderlyFitness #Sarcopenia #MobileHealth #ResistanceTraining

Driving Health Forward

@dhfcampaign.bsky.social

1 week ago

For decades, organizations like Children’s Health Fund have demonstrated what community-centered care can achieve. Sustained investment in mobile health and policy support is essential to ensure these models remain accessible to the families who rely on them.

#MobileHealth #HealthEquity

JMIR Publications

@jmirpub.bsky.social

3 weeks ago

Co-Designed Mental Health Screening App (Here for You) for University Students: Pilot #feasibility Mixed Methods Study Background: Mental health disorders are a growing public health concern among university students globally and in India, exacerbated by stigma and limited access to care. Mobile health (mHealth) apps offer a potential solution, but user engagement and cultural relevance remain key challenges. This pilot study evaluated Here for You, a mental health screening app co-designed with Indian university students to provide accessible, nonstigmatizing support. Objective: This mixed methods study aimed to (1) describe the user-centered codevelopment and pilot testing process of the Here for You app; (2) evaluate the app’s #feasibility, user acceptability, and engagement; and (3) assess the concurrent validity of the app’s screening tool, the Depression, Anxiety, and Stress Scale-21 (DASS-21) against established clinical measures (Hamilton Depression Rating Scale [HAM-D], Hamilton Anxiety Rating Scale [HAM-A], and Perceived Stress Scale [PSS]). Methods: This study used a 4-phase user-centered design involving students with lived mental health experience, clinicians, and developers. A purposive sample of 30 university students (mean age 21, SD 1.8 years; n=15, 50% female) diagnosed with depression, anxiety, or stress participated. Participants completed the DASS-21 via the app and underwent clinical assessments using the HAM-D, HAM-A, and PSS scales. User experience was evaluated using the User Mobile App Rating Scale and qualitative feedback. Data analysis included Pearson correlation coefficients and thematic analysis. Results: App-based DASS-21 scores showed strong correlations with clinician-administered scales: HAM-D (r=0.819; P

JMIR Formative Res: Co-Designed Mental Health Screening App (Here for You) for University Students: Pilot #feasibility Mixed Methods Study #MentalHealth #UniversityStudents #MobileHealth #MentalHealthApp #UserEngagement

Driving Health Forward

@dhfcampaign.bsky.social

3 weeks ago

We’re proud to welcome Project Happy Face to Driving Health Forward.
Their mobile dental programs bring preventive care, education, and treatment directly to children and communities facing access barriers.
🔗 Learn more: www.projecthappyface.org
#MobileHealth #OralHealth #DrivingHealthForward

JMIR Publications

@jmirpub.bsky.social

3 weeks ago

#feasibility of a Noncontact Photoplethysmography–Based Mobile App for Noninvasive Hemoglobin Monitoring: Exploratory Observational Study Background: Anemia is a widespread global health issue. Hemoglobin (Hb) concentration measurement remains the most common method for anemia screening and diagnosis. In recent years, there has been growing interest in the development of noninvasive point-of-care technologies that eliminate the need for blood sampling. Objective: This pilot study explores the #feasibility of using a noncontact photoplethysmography–based mobile app for Hb monitoring. Methods: Adult volunteers aged 18 years and older, of both sexes, were consecutively recruited. Participants were seated and allowed a 2-minute rest before measurements. During testing, they faced a smartphone running comestai.app which used the front-facing camera to capture facial videos. Simultaneous readings were collected for Hb over approximately 90 seconds using the app. Ambient lighting was standardized for all remote photoplethysmography recordings. No medical decisions were made based on the app-generated data. A complete blood count, including Hb levels, was used as a reference for comparison with the data collected using comestai.app. Results: A total of 555 (female: n=313, 56.4%; male: n=242, 43.6%) individuals participated in the study. The app achieved a mean absolute error of 1.46, a mean absolute percentage error of 11.26, a mean error of −0.67, and a root mean square error of 1.88. The Bland-Altman plot evaluated the agreement between the app-based and laboratory-based Hb measurements, with the mean difference between the 2 methods being −0.70 g/dL. The method demonstrated an overall accuracy of 75%. The area under the curve was 0.701 (95% CI 0.655-0.745). Conclusions: Comestai.app offers an innovative approach to wellness monitoring by providing noninvasive Hb estimation using the smartphone’s front-facing camera. Continued development, including algorithmic refinement and larger-scale validation in diverse populations, will be key to enhancing accuracy and broadening its utility. By leveraging the ubiquity of smartphones, comestai.app contributes meaningfully to the democratization of health monitoring and the promotion of proactive self-care. Trial Registration: ClinicalTrials.gov NCT06427564; https://clinicaltrials.gov/study/NCT06427564

JMIR Formative Res: #feasibility of a Noncontact Photoplethysmography–Based Mobile App for Noninvasive Hemoglobin Monitoring: Exploratory Observational Study #NoninvasiveMonitoring #Hemoglobin #AnemiaAwareness #MobileHealth #HealthTech

JMIR Publications

@jmirpub.bsky.social

3 weeks ago

Autonomous Motivation Trajectory Following Adoption of a Team-Based Gamification App Among Adults With Diabetes: 1-Year Formative Longitudinal Study Background: Autonomous motivation, grounded in self-determination theory, is important for sustaining diabetes self-care behaviors. Although mobile health interventions, gamification, and peer support are increasingly used to enhance motivation in diabetes care, evidence on how motivation evolves over time remains limited. Specifically, it is unclear whether motivational change follows a linear pattern or a nonlinear trajectory, such as an initial increase followed by a subsequent decline. Clarifying these temporal patterns is critical for informing the design of adaptive diabetes self-care interventions. Objective: The objective of this study was to characterize the 1-year developmental trajectory of autonomous motivation following the real-world introduction of a commercially available team-based gamification app. Methods: This prospective, single-arm longitudinal study involved adults with diabetes (predominantly type 2) recruited from outpatient clinics in Japan. Participants were instructed to use a team-based gamification app designed to promote desirable habits through peer support and social comparison for at least 7 days. The primary outcome, autonomous motivation, was assessed using the Treatment Self-Regulation Questionnaire–Autonomous Motivation subscale (TSRQ-AM; score range 7-49) at baseline, 6 weeks, 6 months, and 1 year. Secondary measures included hemoglobin A1c (HbA1c), body weight, triglycerides, and psychological scales (eg, Self-Efficacy Scale for Diabetes Self-Care, Summary of Diabetes Self-Care Activities, Problem Areas in Diabetes scale, and World Health Organization–Five Well-Being Index). To analyze the trajectory, we used linear mixed-effects models with random intercepts for participants. The final model included fixed effects for time (as both linear and quadratic terms), age, sex, employment status, family structure, baseline BMI, and baseline HbA1c. Results: Of 32 consenting participants, 29 (90.6%) were included in the primary analysis; clinical data at 1 year were available for 26 (81.3%) participants. In exploratory analyses, mean TSRQ-AM scores increased from baseline (37.4, SD 7.9) to 6 months (39.5, SD 7.4; Cohen d=0.47). Over the 1-year period, body weight decreased significantly (b=−0.39; P=.01), whereas HbA1c (P=.40) and triglycerides (P=.14) showed no significant changes. The TSRQ-AM score showed a significant nonlinear change over time. A model including a quadratic time term fit significantly better than a linear-only model (χ21=4.1; P=.04), with a significant quadratic effect (b=−7.26; P=.045), indicating an inverted U-shaped trajectory peaking at 6 months. Higher baseline BMI was associated with lower TSRQ-AM scores (b=−1.00; P=.001). Conclusions: This formative study provides preliminary evidence of a nonlinear, 1-year trajectory of autonomous motivation following the introduction of a team-based app. The observed curvilinear pattern suggests that autonomous motivation during the intervention may peak at around 6 months, underscoring the importance of adaptive intervention designs to maintain engagement over time. The accompanying reduction in body weight suggests potential physiological relevance that warrants further investigation in controlled studies. Trial Registration: UMIN Clinical Trials Registry UMIN000044874; https://tinyurl.com/59bzb68k

JMIR Formative Res: Autonomous Motivation Trajectory Following Adoption of a Team-Based Gamification App Among Adults With Diabetes: 1-Year Formative Longitudinal Study #DiabetesCare #Gamification #MobileHealth #SelfDetermination #Motivation

Driving Health Forward

@dhfcampaign.bsky.social

3 weeks ago

Mobile health expands access — policy must catch up.
New brief + Feb 26 webinar:
📄 drivinghealthforward.org/policy-advocacy
🗓 us06web.zoom.us/webinar/regi...
#MobileHealth #HealthPolicy #DrivingHealthForward

RE.DOCTOR

@re.doctor

1 month ago

How RE.DOCTOR Vitals is Revolutionizing Telehealth: Remote Vital Sign Monitoring Made Easy Discover how RE.DOCTOR Vitals transforms telehealth consultations with accurate, camera-based vital sign monitoring. No wearables needed—just your smartphone.

Healthcare should be accessible to everyone, everywhere. 🌍

Discover how we're making vital sign monitoring effortless: re.doctor/vital-sign-m...

#HealthEquity #DigitalHealth #TelehealthMonitoringMadeEasy #MobileHealth #HealthForAll

Driving Health Forward

@dhfcampaign.bsky.social

1 month ago

Mobile health expands access to care — policy must keep pace.
A Georgetown CHIR policy scan explores how federal and state policy can support and scale mobile health nationwide.
Explore the research and register: chir.georgetown.edu/mobile-health
#MobileHealth #HealthPolicy #DrivingHealthForward

Driving Health Forward

@dhfcampaign.bsky.social

1 month ago

Mobile health has the evidence — policy needs to catch up.
New blog with Maanasa Kona (Georgetown CHIR) on scaling mobile care through policy.
🔗 www.drivinghealthforward.org/post/new-mobile-healthcare-policy-report
#MobileHealth #HealthPolicy

Driving Health Forward

@dhfcampaign.bsky.social

1 month ago

Mobile health expands access to care, policy must keep pace.

A new policy scan from Georgetown CHIR examines how federal and state policy can better support mobile health.

Explore the research:
chir.georgetown.edu/mobile-health

#MobileHealth #HealthPolicy #DrivingHealthForward

JMIR Publications

@jmirpub.bsky.social

1 month ago

Acceptance of Men Living With HIV Toward Treatment-Supportive Mobile Apps Using the Unified Theory of Acceptance and Use of Technology: Cross-Sectional Study Background: Despite a 40-year prevalence of the human immunodeficiency virus (HIV) the acquired im-munodeficiency syndrome (AIDS) epidemic prevails. Effective AIDS treatment requires spe-cialist care and high adherence often hindered by structural issues in care access. Innovative eHealth solutions like a treatment-supportive mobile applications, can help address these is-sues. Successful implementation depends on user acceptance. Acceptance can be opera-tionalized as behavioral intention and measured through the Unified Theory of Acceptance and Use of Technology (UTAUT). Objective: This study examines the acceptance of a therapeutic app and factors influencing its use among men living with HIV. Methods: A cross-sectional study was conducted among 172 men living with HIV between September 2021 and April 2024. In addition to the collection of sociodemographic, medical and eHealth-related data, acceptance and its influencing factors were assessed by applying the UTAUT model. A multiple hierarchical regression analysis was conducted. Results: High acceptance of treatment-supportive mobile applications in men living with HIV was re-ported by 45.3% (n = 78) of the participants. Significant predictors of acceptance were Age (β = -.27, p < .001), Health literacy regarding disease (β = .11, p < .001), eHealth literacy (β = .10, p = .001), Internet anxiety (β = -.18, p = .041), and the UTAUT predictors Effort expec-tancy (β = .38, p < .001), Performance expectancy (β = .24, p < .001) and Social influence (β = .40, p < .001). The UTAUT model explained 72% of the variance in acceptance. Conclusions: Since the acceptance of eHealth services is a reliable indicator of the actual usage behavior, the results of this study are a promising basis for the successful implementation of eHealth offerings in the group of men living with HIV.

JMIR Formative Res: Acceptance of Men Living With HIV Toward Treatment-Supportive Mobile Apps Using the Unified Theory of Acceptance and Use of Technology: Cross-Sectional Study #HIVAwareness #AIDSAwareness #eHealth #MobileHealth #HealthTech

Driving Health Forward

@dhfcampaign.bsky.social

1 month ago

Driving Health Forward will be featured at the 2026 NACHC Policy & Issues Forum.
Nicky Goren and Don Blanchon will speak on “The Time for Mobile is Now!”. Don also serves as Interim Director of the Mobile Healthcare Association.Feb 10 · 1:30–2:30 PM · Gaylord Center

#PIForum26 #NACHC #MobileHealth

Driving Health Forward

@dhfcampaign.bsky.social

1 month ago

Heart health starts with access.
Mobile clinics bring BP screenings & prevention into communities where barriers are highest. ❤️🚐
#AmericanHeartMonth #DrivingHealthForward #MobileHealth

JMIR Publications

@jmirpub.bsky.social

1 month ago

Designing a Case Management Mobile Health App for Violence Intervention Programs: Mixed Methods Human-Centered Design Study Background: Hospital-based violence intervention programs (HVIPs) have shown promise in mitigating the effects of violence, but their impact is limited by time constraints and inefficient practices faced by the Violence Prevention Professionals (VPPs) who function as case managers. Mobile health applications (mHealth apps) offer the potential to enhance communication and service delivery between VPPs and clients, but few have been specifically designed for vulnerable populations. Objective: To design a mHealth app to improve communication and access to resources between survivors of violence and their VPPs using Human-Centered Design (HCD) and iterative prototyping methods. Methods: HCD methodology was used, including rounds of Participatory Design, Low-fidelity Prototype Testing, and High-fidelity Prototype Testing. The Participatory Design phase included in-depth interviews and co-design, followed by inductive qualitative analysis to inform the mHealth app’s initial low-fidelity design. The Low-fidelity Prototype Testing phase included in-depth interviews with probing questions about the low-fidelity design, followed by inductive qualitative analysis to inform the mHealth app’s initial high-fidelity design. The High-fidelity Prototype Testing phase utilized the Rapid Iterative Testing and Evaluation (RITE) method and inductive qualitative analysis to rapidly collect and integrate VPP feedback into the mHealth app’s final design approved for implementation. Results: Eight VPPs participated in three rounds of testing and feedback. Participatory Design identified four key themes: (1) trust, (2) personal connection, (3) tailored resource curation, and (4) management of administrative burdens. Low-fidelity Prototype Testing identified three additional key themes: (5) intuitive and comprehensive design, (6) dynamic journey and sense of progress, and (7) standardization of verbiage and design choices. High-fidelity Prototype Testing through RITE identified 181 actionable issues, with 133 addressed, achieving a 73% impact ratio (used to measure the effectiveness of #usability improvements). High-fidelity Prototype Testing identified nine key themes, reaffirming five themes from prior testing sessions (theme 2, theme 3, theme 5, theme 6, and theme 7), and uncovering four novel themes: (8) control over boundaries, (9) celebration of client successes, (10) client empowerment, and (11) warm hand-off. The final mHealth app version adapted from 3 low-fidelity digital representations (wireframes) to 25 high-fidelity wireframes of a mHealth app to support case management. Conclusions: The combination of HCD and RITE methodologies resulted in a mHealth app tailored to the needs of VPPs working with survivors of violence. This approach may be transferable to the development of other mHealth apps for specialized populations, though further research with larger samples would be needed to establish generalizability. Clinical Trial: N/A

JMIR Formative Res: Designing a Case Management Mobile Health App for Violence Intervention Programs: Mixed Methods Human-Centered Design Study #MobileHealth #ViolenceIntervention #HumanCenteredDesign #HealthApp #CaseManagement

RE.DOCTOR

@re.doctor

1 month ago

AI-Powered Health Monitoring Monitor your vital signs anytime, anywhere with re.doctor's AI-powered health technology. Track heart rate, blood pressure, oxygen saturation, and respiratory rate using just your smartphone camera—no wearables required. Medical-grade accuracy meets everyday convenience. Learn more: https://re.doctor #HealthTech #AIHealthcare #VitalSigns #DigitalHealth #HealthMonitoring #Telemedicine #MobileHealth #WellnessTech #HealthcareInnovation #SmartHealthcare

AI-Powered Health Monitoring
Monitor your vital signs anytime, anywhere with re.doctor's AI-powered health technology.

Learn more: re.doctor

#HealthTech #AIHealthcare #VitalSigns #DigitalHealth #HealthMonitoring #Telemedicine #MobileHealth #WellnessTech #HealthcareInnovation #SmartHealthcare

Driving Health Forward

@dhfcampaign.bsky.social

1 month ago

Access gets someone in the door.
Trust brings them back.
That’s why mobile health changes outcomes. 🚐💙
#DrivingHealthForward #MobileHealth #HealthEquity

Driving Health Forward

@dhfcampaign.bsky.social

1 month ago

Mental wellness requires access.
Mobile clinics deliver behavioral support, addiction care & follow-up where stigma blocks it. 💙
#DrivingHealthForward #MentalWellnessMonth #MobileHealth

Driving Health Forward

@dhfcampaign.bsky.social

1 month ago

Healthcare regs assume care happens in buildings—limiting mobile health expansion. Our new brief examines how outdated regulatory frameworks create barriers and explores how states can modernize them.
📖 Full brief→ www.drivinghealthforward.org
#MobileHealth #HealthPolicy #DrivingHealthForward

Driving Health Forward

@dhfcampaign.bsky.social

1 month ago

Driving Health Forward | Bringing essential care to you Driving Health Forward is a national campaign that aligns different perspectives, voices, and lived experiences around the central organizing principle of expanding access to essential care through mo...

Healthcare regs assume care happens in buildings—limiting mobile health expansion. Our new brief examines how outdated regulatory frameworks create barriers and explores how states can modernize them.
📖 Full brief→ www.drivinghealthforward.org
#MobileHealth #HealthPolicy #DrivingHealthForward

Driving Health Forward

@dhfcampaign.bsky.social

1 month ago

Mobile health isn’t a pilot; it’s becoming infrastructure.
States are investing in care models that go to the patient, not the other way around.
That’s real momentum. 💙🚐
#DrivingHealthForward #MobileHealth #HealthEquity

JMIR Publications

@jmirpub.bsky.social

2 months ago

Preferences for an Experience Sampling Method–Based Tool as an Adjunct to Usual Treatment in Patients With Problem Substance Use: Qualitative Study Background: Mobile health tools that use the Experience Sampling Method (ESM) appear to be a promising tool to streamline and improve the treatment of substance use disorders. However, patient involvement in the development of these tools is uncommon, and research on the preferences of people being treated for substance use disorders has been scarce. In the scope of the European Union IMMERSE (Implementing Mobile Mental health Recording Strategy for Europe) consortium, an ESM-based tool for Digital Mobile Mental Health (DMMH) was first codeveloped and later tested in 4 European countries. Objective: This study aimed to achieve an understanding of preferences for features of DMMH among mental health service users with problem substance use. Methods: In 4 European countries, service users were recruited for a semistructured qualitative interview, which started with the presentation of a prototype of the DMMH. Data analysis was performed through directed qualitative content analysis. Results: The analytical sample consisted of 12 (5 female, 6 male, and 1 nonbinary person) participants with problem substance use aged 18-50 years. There were 4 participants from Slovakia, 3 from Belgium, 4 from Germany, and 1 from Scotland. Patient preferences were classified into 7 categories: notifications, questions, user interface, functionality changes, visualizations, sharing data with clinicians, and sharing data with others. The proposed intensive notification schedule was deemed acceptable by service users as long as the questionnaire is short. Participants expressed a preference for open-text response options, Ecological Momentary Interventions, and options for individual customization of several elements of the tool. Data visualization was considered an important aid for communication with clinicians, with whom all participants wanted to share data obtained with DMMH. The possibility of sharing data with other people depended on the quality of the relationship with them. Conclusions: In the development of ESM-based mobile health tools for people with problem substance use, their preferences for content, functionality, and appearance of the tools should be considered so they match patients’ treatment needs.

JMIR Formative Res: Preferences for an Experience Sampling Method–Based Tool as an Adjunct to Usual Treatment in Patients With Problem Substance Use: Qualitative Study #MentalHealth #SubstanceUse #MobileHealth #ExperienceSamplingMethod #DigitalHealth

JMIR Publications

@jmirpub.bsky.social

2 months ago

Support Community Formation on a Mobile App for People Living With HIV and Substance Use Disorder: A Computer-Mediated Discourse Analysis Background: People with HIV and substance use disorders (SUD) have complex healthcare needs requiring adaptive and effective support systems. While mobile health applications can foster virtual communities grounded in shared lived experiences, little is known about the dynamics within these digital spaces. Objective: We examined the formation of a virtual community on the Addiction Comprehensive Health Enhancement Support System (A-CHESS) message board, a mobile app designed to support HIV care engagement among individuals with HIV and SUD. Methods: We conducted a computer-mediated discourse analysis of A-CHESS message board posts to examine communication patterns, interaction structures, and engagement dynamics. Quantitative comparisons were used to assess differences between posters and non-posters using t-tests and chi-square tests. We then applied qualitative coding to categorize messages by type, speaker, and function to understand how staff and participants co-constructed a supportive virtual environment. Results: Among 208 participants, 87 (42%) posted at least once on the A-CHESS message board, contributing 1,834 messages between April 2019 and May 2021. Posters and non-posters did not differ significantly in age (t(206) = –0.64, p = .52), gender (χ²(1) = 0.14, p = .71), or race (χ²(1) = 0.52, p = .47). We identified three distinct message types: premeditated, adlib, and participant-driven. Staff initially led with premeditated messages (e.g., recovery stories, HIV risk information, and “Thought of the Day” inspiration), which participants often interpreted and adapted to their own SUD recovery. Over time, staff incorporated adlib messaging styles using personalized narratives and polls to sustain engagement. Participants then developed their own posts using similar formats, incorporating Alcoholics Anonymous literature, sharing legal and personal challenges, and suggesting new app features (e.g., medication check-ins to support adherence). Conclusions: Staff adapted communication styles to increase engagement, while participants appropriated these forms to reflect personal goals and lived experiences. Mobile health interventions may benefit from design elements that support participant-led discourse and customization, fostering ownership, support, and relevance within virtual care communities.

JMIR Formative Res: Support Community Formation on a Mobile App for People Living With HIV and Substance Use Disorder: A Computer-Mediated Discourse Analysis #HIVAwareness #SubstanceUseDisorder #MobileHealth #SupportCommunity #DigitalHealth

Driving Health Forward

@dhfcampaign.bsky.social

2 months ago

Mobile healthcare removes economic barriers, care delivered where people live, work & recover.
Healthcare is a right, not a privilege. 💙
#DrivingHealthForward #MobileHealth #HealthEquity

Driving Health Forward

@dhfcampaign.bsky.social

2 months ago

Each mobile clinic = 3,491 visits, $19 ROI, and countless lives changed.
That’s impact in motion. 🚐💙
#DrivingHealthForward #MobileHealth #HealthcareImpact

Driving Health Forward

@dhfcampaign.bsky.social

2 months ago

Mobile clinics make cervical cancer prevention reachable — Pap partnerships, HPV navigation, & screenings where women face barriers.
Access saves lives. 💙
#DrivingHealthForward #CervicalHealth #MobileHealth

RE.DOCTOR

@re.doctor

2 months ago

Vital Signs Scan RE.DOCTOR PPG Vital Signs Scan offers a compelling solution for smartphone, smart ring, smart watch, or fitness tracker based vital sign monitoring.

📱 Health monitoring in seconds, not hours. RE.DOCTOR Vital Signs Scan delivers fast, painless vital sign readings from anywhere. Perfect for tracking trends and staying proactive about your health.
Learn more at re.doctor/vital-signs-...
#MobileHealth #Wellness #Telemedicine #HealthApp

JMIR Publications

@jmirpub.bsky.social

2 months ago

Supporting Dementia Caregiving With a Mobile Care Ecosystem: Development and Mixed Methods Study Background: Dementia presents significant challenges for informal caregivers. A gap remains in technology-driven personalized support tailored to caregivers' needs. Objective: To develop a theory-driven, multi-component mobile application specifically designed for caregivers of individuals with dementia and test its usability among end users. Methods: We developed "CareBuddy," a mobile care ecosystem based on the Stress Process Model and user-centered design. The app includes personalized assessments and tailored solutions, an AI-driven chatbot, GPS-based location monitoring, peer support, a helpline, telemedicine, healthcare provider integration and caregiver self-care resources. Development was informed by interviews with caregivers and stakeholders, followed by two-phase pilot testing to assess usability and acceptability involving 18 and 10 participants respectively. Results: In phase 1, the mean system usability scores (SUS) increased from 65.4 (S.D. 11.8) in round 1 to 73.8 (S.D. 15.9) in round 3, exceeding the benchmark SUS of 68. In phase 2, caregivers rated the app highly with mHealth app usability questionnaire (MAUQ) overall total mean score of 95.4 (SD 8.5). The domains of ease of use (mean 24.1; SD 2.9), user interface and satisfaction (mean 40.3; SD 3.4), and usefulness (mean 31; SD 3.9) received high MAUQ ratings. Participants valued the content focused on dementia management and caregiver well-being. Caregivers appreciated the interactive features -social networking portal, service directory, and conversational large language model. Feedback highlighted areas for improvement, including reducing textual overload and addressing navigational challenges. Conclusions: CareBuddy offers a multifaceted digital solution for dementia caregivers, with high usability and satisfaction. An ongoing trial is evaluating the app’s effectiveness in improving caregiver outcomes.

New in JMIR Aging: Supporting Dementia Caregiving With a Mobile Care Ecosystem: Development and Mixed Methods Study #DementiaCare #Caregiving #MobileHealth #HealthTech #CareBuddy