A scoping review on using real-world data to evaluate the effectiveness of mHealth applications - npj Digital Medicine npj Digital Medicine - A scoping review on using real-world data to evaluate the effectiveness of mHealth applications

A scoping review on using #RealWorldData to evaluate the effectiveness of #mHealth applications. 72 studies show predominant #userinput data use, limited device/system data and mostly low-evidence pre-post designs.
www.nature.com/articles/s41...

Family-involvement in #mHealth-based Physical Activity Interventions for Improving Physical Performance among Community-dwelling Older Adults: A Systematic Review Date Submitted: Apr 8, 2026. Open Peer Review Period: Apr 9, 2026 - Jun 4, 2026.

Reminder>> Family-involvement in #mHealth-based Physical Activity Interventions for Improving Physical Performance among Community-dwelling Older Adults: A Systematic Review (preprint) #openscience #PeerReviewMe #PlanP

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Evaluating an Incentive-Based mHealth App for Physical Activity Promotion Using the Obesity-Related Behavioral Intervention Trial Model: Small Cohort Study Background: Physical inactivity remains a public health concern, with 42% (around 1 in 2) of women and 34% (around 1 in 3) of men in the United Kingdom, for example, failing to meet moderate-to-vigorous physical activity guidelines. To promote physical activity (PA) at scale, smartphone-based mHealth (mobile health) software apps offer a promising solution. Objective: This study aims to evaluate the #feasibility of implementing an mHealth app offering very small (“micro”) financial incentives for PA in Leeds, United Kingdom. Methods: A 5-week single-arm proof-of-concept study was conducted with rolling recruitment among Caterpillar Health app users between September 12 and December 12, 2022 (Obesity-Related Behavioral Intervention Trial model, phase IIa). Users earned microincentives in the form of “points,” redeemable for consumer rewards (eg, movie tickets and gym passes), for meeting personalized daily step goals (US $0.13 per goal achieved; set using data from a 5-day baseline) and completing educational quizzes (US $0.33 per quiz). Descriptive statistics assessed #feasibility outcomes (ie, reach, recruitment, retention, engagement, and acceptability) and preliminary effectiveness. Paired-samples tests (

JMIR Formative Res: Evaluating an Incentive-Based mHealth App for Physical Activity Promotion Using the Obesity-Related Behavioral Intervention Trial Model: Small Cohort Study #PhysicalActivity #mHealth #HealthPromotion #IncentiveBased #MobileHealth

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Effectiveness of #mHealth-Based Nutritional Interventions on Iron Status of Pregnant Women: Systematic Review of Randomized Controlled Trials Background: Anemia is a global #Health concern. It is disproportionately prevalent among pregnant women in low-resource regions, where iron deficiency is the leading cause. Given the multifactorial nature of anemia, a range of nutritional interventions is recommended. However, effective implementation is often hindered by limited #Health care access, poor adherence to supplementation, and gaps in nutrition knowledge and counseling. To address these challenges and optimize hemoglobin (Hb) levels among pregnant women, #Mobile #Health (#mHealth)−based nutritional interventions offer a promising alternative. Objective: The aim of the study is to review available evidence on the effectiveness of #mHealth-based nutritional interventions on iron status (Hb and/or serum ferritin concentration) among pregnant women. Methods: Searches were conducted in Embase, CINAHL, Cochrane Library, PubMed, Web of Science, and Scopus, and supplemented by snowballing to identify additional relevant studies from citation lists. The key search strings comprised 4 concepts: “#Mobile #Health,” “nutritional intervention,” “Hb, anemia or iron deficiency anemia,” and “pregnant women.” Predefined inclusion and exclusion criteria were applied during screening. The methodological quality of included studies was assessed using the Risk of Bias 2 tool. The primary end point was the change in mean Hb concentration or serum ferritin level. Effect sizes (ESs) were calculated as standardized mean differences, including Cohen and Hedges . Results: Of the 14,284 studies identified, only 11 randomized controlled trials were included. These studies used various modes of delivery, including #Mobile phone calls (n=1), SMS text messaging (n=3), and #Mobile apps (n=4), with some using more than 2 modes (n=3). The effect of #mHealth-based nutritional interventions on iron status varied significantly. In total, 4 studies demonstrated a large ES (>0.8), with 3 relying on WhatsApp Messenger as an #mHealth delivery mode. Approximately 82% (9/11) of the included studies reported a positive effect ( values ranging from 95%), attributed to variations in #mHealth delivery modes, functions, and interactive features across the included studies, meta-analysis could not be performed. Conclusions: This review demonstrates that #mHealth-supported nutritional interventions effectively optimize Hb concentration in pregnant women. While SMS text messaging was less effective in improving Hb concentration, combining it with another #mHealth delivery mode, such as phone calls, improved intervention effectiveness. However, the variability in #mHealth delivery modes, functions, and interactive features underscores the need for tailored strategies that account for context-specific challenges, #Digital literacy, and access to technology to enhance effectiveness. Trial Registration: PROSPERO CRD42025627769; https://www.crd.york.ac.uk/PROSPERO/view/CRD42025627769

New in JMIR mhealth: Effectiveness of #mHealth-Based Nutritional Interventions on Iron Status of Pregnant Women: Systematic Review of Randomized Controlled Trials

A #TextMessaging #mhealth–Based Program to Transition From Basal Insulin to Glucagon-Like Peptide-1 Receptor Agonists in Safety-Net Diabetes Care: Pilot Quality Improvement Intervention Study Background: Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) and basal insulin both lower blood sugar, but while insulin puts people at risk of hypoglycemia and weight gain, GLP-1 RAs do not. In addition, GLP-1 RAs have added cardiometabolic and renal benefits. For these reasons, when possible, many primary care providers prefer their patients with type 2 diabetes to be from basal insulin to a GLP-1 RA. This transition process can be labor intensive, requiring multiple dosing adjustments and a watchful eye for hypoglycemia and hyperglycemia. The Mobile Insulin Titration Intervention (MITI)–GLP1 program uses SMS #TextMessaging #mhealth–based technology to support a streamlined and supervised transition process from basal insulin to a GLP-1 RA. This program takes place at a multilingual safety-net clinic. Objective: Our objectives were to assess program #feasibility and acceptability to determine whether the intervention was doable, practical, and worthy of further investigation via a larger controlled trial. Preliminary clinical outcomes are also discussed in this paper. Methods: Patients were enrolled on a secure web platform that sent them a daily SMS text message asking the following: “What was your fasting blood sugar this morning?” Each weekday, texted responses containing patients’ fasting blood sugar levels were checked for alarm values, and once weekly, patients were called and advised on whether and how to lower their basal insulin and increase their GLP-1 RA dose. The program was co-run by general internal medicine physicians and nurses and continued until the patient had their insulin stopped completely and/or their GLP-1 RA dose reached the maximum, or 16 weeks elapsed. All enrolled patients were included in the analyses. Results: A total of 72 patients completed the pilot program. #feasibility and acceptability were high. Of 3671 SMS text messages sent by the program, 3520 (95.89%) received a response from patients. Of 719 cumulative weeks in which Thursday titration phone calls were attempted, successful connections with patients were made in 649 (90.26%) instances. Preliminary clinical outcomes were promising. Insulin doses were meaningfully reduced (55/72, 76.39% had their basal insulin reduced by at least 50%; 45/72, 62.5% had their insulin stopped completely). GLP-1 RA doses were meaningfully increased (64/72, 88.89% had their GLP-1 RA dose increased by ≥1 level; 45/72, 62.5% were discharged on the maximum dose of their GLP-1 RA). There was minimal hypoglycemia (5/3520, 0.14% of the SMS text messages reported a value of 400 mg/dL). Conclusions: A general internal medicine–run MITI-GLP1 pilot program using SMS #TextMessaging #mhealth and interdisciplinary teamwork between internists and nurses is a feasible and acceptable intervention for safely and effectively transitioning people with well-controlled type 2 diabetes away from basal insulin and toward a GLP-1 RA.

JMIR Formative Res: A #TextMessaging #mhealth–Based Program to Transition From Basal Insulin to Glucagon-Like Peptide-1 Receptor Agonists in Safety-Net Diabetes Care: Pilot Quality Improvement Intervention Study #DiabetesCare #GLP1RA #TextMessaging #mHealth #Insulin

What is HealthMpowerment? HealthMpowerment (HMP) is a state-of-the-art Digital Health Intervention platform built on the latest behavior change research and advances in Human-Computer Interaction (HCI) and Artificial Intelligence (AI).​ Easy to adapt for various populations and health topics, the HMP mobile app can be branded and tailored to your individual project.​ Projects can choose to turn on/off features based on specific needs​. Our model is akin to a community co-op. Everyone buys into the digital health platform, and everyone shares the enhancements and bug fixes made by the community at large.

Register for our 3-day academic workshop today! bit.ly/DHI2026

Whether you’re launching your first #mHealth study or scaling an established program, this intensive offers practical tools, expert insights, and hands-on experience to help you transform bold ideas into meaningful impact.

#digitalhealth #innovation #research #FSU #science #technology #health

Family-involvement in #mHealth-based Physical Activity Interventions for Improving Physical Performance among Community-dwelling Older Adults: A Systematic Review Date Submitted: Apr 8, 2026. Open Peer Review Period: Apr 9, 2026 - Jun 4, 2026.

Family-involvement in #mHealth-based Physical Activity Interventions for Improving Physical Performance among Community-dwelling Older Adults: A Systematic Review (preprint) #openscience #PeerReviewMe #PlanP

📢 New at #IJBNPA! Can a #mHealth self-managed intervention help patients with #Parkinsons improve #PhysicalActivity and #Nutrition? Learn more about the results of this RCT.
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link.springer.com/article/10.1186/s12966-0...

#mHealth-Enabled Stroke Screening for #Pediatric Sickle Cell Disease in Low-Resource Settings: Systematic Literature Review of Critical Barriers, Emerging Technologies, and AI-Driven Solutions Background: Sickle cell disease (SCD) is a genetic blood disorder affecting millions globally, with life-threatening complications, and most patients live in sub-Saharan Africa. Particularly, #Children with SCD have a high risk of stroke. Although early screening for stroke could help prevent many cases, access to effective stroke screening remains limited in low-resource settings (LRS). Existing traditional approaches are highly operator-dependent, costly, resource-intensive, or difficult to deploy at scale in #Pediatric care. These limitations highlight the urgent need for accessible, scalable, and #Child-appropriate stroke screening and assessment tools suitable for low-resource health care contexts. Objective: The aims of this systematic literature review are to (1) uncover system-level barriers affecting stroke screening accessibility for patients with #Pediatric sickle cell disease (PSCD) in LRS, including underserved contexts within high-income countries; (2) identify existing and emerging stroke screening and assessment technologies and their implementation characteristics, such as feasibility, scalability, portability, and training requirements; and (3) propose a user-centered mobile health (#mHealth) framework for stroke screening that improves accessibility and feasibility in resource-constrained health care settings. Methods: PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were followed to organize the search process. A systematic search was conducted using an advanced query and defined eligibility criteria in the academic databases of PubMed, IEEE Xplore, Wiley Online Library, and Google Scholar. Studies published in English between January 1, 2021, and October 31, 2025, were selected. Collected data were arranged in a preformatted Microsoft Excel spreadsheet for analysis. Risk-of-bias assessment was performed using various risk-of-bias assessment tools because of the heterogeneity of the included studies. Narrative synthesis was used for data synthesis. Results: The literature search initially identified 1465 studies, of which 28 (2%) were selected for analysis. Among the 28 studies, 10 (36%) focused on stroke screening accessibility for patients with PSCD in either low- and middle-income countries or other income-level countries for LRS, and 18 (64%) outlined key features and the feasibility of stroke screening technologies. Identified barriers were organized into 4 major categories (workforce and training constraints, health care system and infrastructure barriers, sociocultural and awareness factors, and economic and logistical constraints), emphasizing difficulties in accessing stroke screening in LRS. Additionally, existing and emerging stroke screening technologies were classified into 5 groups: nonimaging, imaging, light-based optical spectroscopy, biomarker-based, and artificial intelligence– and machine learning–based #mHealth wearable approaches. Finally, a comprehensive #mHealth app is proposed for an easy-to-use screening experience to address stroke screening challenges for patients with PSCD in LRS. Conclusions: This study contributes to identifying major barriers to stroke screening in LRS and highlights key characteristics of stroke screening solutions that can be used in the future. It also contributes to the design of a holistic #mHealth solution for implementing stroke screening clinical care for patients with PSCD in LRS. Trial Registration: PROSPERO 2025 CRD420251172487; https://tinyurl.com/3djampu6

JMIR Pediatrics: #mHealth-Enabled Stroke Screening for #Pediatric Sickle Cell Disease in Low-Resource Settings: Systematic Literature Review of Critical Barriers, Emerging Technologies, and AI-Driven Solutions

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Smart Technology–Assisted Patient-Centered Management in Venous Thromboembolism: Pilot Study on Anticoagulation Adherence Background: Achieving optimal adherence to anticoagulation therapy is a major challenge in the management of venous thromboembolism (VTE). Mobile health (mHealth) technologies may offer a scalable approach to supporting medication adherence and self-management. Objective: This pilot study aimed to assess the #feasibility and preliminary impact of a smart technology–assisted, patient-centered care mHealth app for managing VTE (mVTEA) on short-term anticoagulation adherence among patients with VTE or at moderate-to-high risk of VTE. Methods: Baseline medication adherence and beliefs were assessed using the Chinese versions of the 8-item Morisky Medication Adherence Scale and the Beliefs about Medicines Questionnaire–Specific to characterize baseline status only. The primary outcome was perfect adherence at 1 month, assessed through structured telephone interviews, outpatient visits, and the mVTEA physician-patient communication module. During follow-up, researchers verified current medication regimens, recorded missed doses, assessed therapy continuation, and whenever possible, confirmed adherence through pharmacy refill records or remaining medication packaging. Secondary outcomes included the mVTEA check-in rate and clinical safety events (VTE recurrence, major bleeding per International Society on Thrombosis and Haemostasis criteria, VTE-related hospitalizations, VTE-related rehospitalizations, all-cause mortality). Results: In total, 45 participants completed the study (mean age 60.80, SD 15.20 years; n=16, 36% female). Baseline 8-item Morisky Medication Adherence Scale scores indicated suboptimal adherence (mean 6.24, SD 1.80), with 29% (13/45) classified as good adherence and 71% (32/45) as moderate or poor adherence. The primary contributors to nonadherence were forgetting to take medication. Baseline Beliefs about Medicines Questionnaire–Specific scores showed stronger beliefs in medication necessity than concerns (17.58, SD 2.52 vs 14.56, SD 3.34;

JMIR Formative Res: Smart Technology–Assisted Patient-Centered Management in Venous Thromboembolism: Pilot Study on Anticoagulation Adherence #HealthTech #VenousThromboembolism #Anticoagulation #mHealth #MedicationAdherence

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The Coordination on Mobile Pandemic Apps Best Practice and Solution Sharing (COMPASS) Framework: Holistic Approach to Pandemic mHealth Apps The #covid19 pandemic has highlighted the crucial role of smartphone apps in public health, but it has also revealed challenges in terms of user acceptance and trust, as well as the secure integration of medical data. To overcome these, the COMPASS initiative (Coordination on Mobile Pandemic Apps Best Practice and Solution Sharing)—part of the German Network University Medicine (NUM) program—developed a structured framework for the coordinated development and delivery of pandemic apps, with a focus on #usability, accessibility, security, and scalability. By incorporating expertise from 9 university hospitals and external partners, COMPASS provided a modular approach to pandemic app development that balances technology, regulation, and public acceptance. The framework includes governance, best practices, compliance, research compatibility, interoperability, and a scalable technology platform. In addition, standardized app components and templates were created to support an effective pandemic response. Real-world validation was provided by study-specific apps such as the Mainz Gutenberg Study #covid19 app (University Medical Center Mainz) and the SentiSurv app (University Medical Center Mainz), which generated nearly 1 million data points from over 25,000 participants. COMPASS successfully developed study-specific apps, improved core functionalities, and contributed to larger digital health projects such as the InnovationHub CAEHR. Beyond its immediate applications, COMPASS serves as a scalable blueprint for future mobile health solutions, with a focus on data protection, user trust, and open-source collaboration. By integrating important technological, ethical, and user-oriented considerations, it sets a new standard for digital health innovation and ensures sustainable and widely accepted pandemic preparedness.

JMIR Formative Res: The Coordination on Mobile Pandemic Apps Best Practice and Solution Sharing (COMPASS) Framework: Holistic Approach to Pandemic mHealth Apps #COVID19 #PublicHealth #mHealth #PandemicApps #DigitalHealth

User Testing an mHealth Behavioral Health App for Hopi/Tewa Youth During the #covid19 Pandemic: #usability Study Background: American Indian/Alaska Native (AI/AN) people represent a culturally diverse people group within the United States. AI/AN people experience some of the most severe health disparities in the United States, including behavioral health. A quarter of AI/AN people in the United States live on tribal lands, experiencing significant barriers to mental health resources and broadband infrastructure for telehealth. We developed Amplifying Resilience Over Restricted Internet Access (ARORA)—a mobile health (mHealth) smartphone app, promoting mindfulness practices and community building through AI/AN culture and values. Originally co-designed with both Hopi/Tewa and Navajo youth and adults, this study evaluated app resonance among Hopi/Tewa youth, supporting its iterative design. While we initially planned in-person user testing, this was moved online due to the #covid19 pandemic. Objective: This study assessed the potential and acceptability of an mHealth app supporting Hopi/Tewa youth practicing mindfulness inspired by their culture, values, and beliefs. This research served as preliminary work for an ongoing, iterative participatory action research study, identifying points of improvement to align with our partner community’s goals. Methods: After meeting with 6 community advisory board members and focus groups prior to this study, we developed a prototype for ARORA. This study evaluated intuitiveness and #usability through testing and interviews with Hopi/Tewa youth. All meetings with stakeholders were moved online due to the #covid19 pandemic. Using screen-sharing via Zoom (Zoom Communications, Inc) and Android emulators, we received feedback for the iterative design process. Results: This study involved 9 participants aged 16-24 years. Of these participants, 1 was male and 8 were female; all identified as Hopi/Tewa and/or Tewa. This study included a quantitative assessment using a modified version of the User Version of the Mobile Application Rating Scale. The mean score across all questions was 3.71 (SD 0.427), suggesting generally positive reception. Qualitative results from thematically analyzing open-ended focus group data produced 5 open codes and 12 axial themes, reaching thematic saturation after engaging with 9 participants. Qualitative feedback revealed that while its use was generally enjoyable, the ARORA app could be more specific to Hopi/Tewa culture. Finally, we reflect on adaptations made to our initial protocol in response to the #covid19 pandemic, offering guidelines for future mHealth work involving rural or hard-to-reach communities. Conclusions: In this evaluation and #usability testing of the ARORA prototype, participants expressed interest and engagement in the mindfulness activities. Participants also identified spaces in which the app could improve, both in #usability and in cultural groundedness, especially with the visual dimensions of the app. Reflecting on our experience in facilitating remote user testing, we encourage future work in rural mHealth to consider practices for conducting research when in-person meetings are not feasible.

JMIR Formative Res: User Testing an mHealth Behavioral Health App for Hopi/Tewa Youth During the #covid19 Pandemic: #usability Study #mHealth #BehavioralHealth #IndigenousHealth #MentalHealth #Telehealth

Assessing the Implementation and Potential Effects of the Nishauri #mHealth Intervention on HIV Care Among Men in Homa Bay County, Kenya: #Protocol for a Mixed Methods #Study Background: About 2.4% of Kenyan people (approximately 1.3 million people) are living with HIV. Despite advances in antiretroviral therapy, men continue to experience disproportionately poor engagement in HIV care due to entrenched masculine norms, stigma, and lack of tailored interventions. Mobile health (#mHealth) platforms offer a promising strategy to improve care engagement, but evidence on its implementation and impact among men living with HIV is limited. Objective: This #Study aims to assess the implementation and potential effects of the Nishauri #mHealth intervention on HIV care and treatment outcomes among men in Western Kenya. Specifically, it seeks to (1) analyze its effects on HIV care engagement and treatment outcomes, (2) explore the role of masculine identity in modifying acceptability and uptake, and (3) identify barriers and facilitators of adoption, use, and sustainment. Methods: We will use a mixed methods design combining a stepped-wedge cluster approach and a pre- and postimplementation assessment across 4 health facilities in Homa Bay County, Kenya. Approximately 347 men receiving HIV treatment who own a #Smartphone #mHealth will be enrolled. The stepped-wedge design will sequentially introduce the intervention across the 4 facilities in 2-month intervals following baseline assessments, allowing each site to serve as its own control. Surveys will collect data on sociodemographics, masculinity, intervention acceptability and uptake, and HIV clinical outcomes using validated measures. Intervention effects on pre- and postbinary outcomes will be assessed using the McNemar test, while generalized estimating equations (=.05; =.2; 95% CI) will account for clustering and repeated measures in the stepped-wedge analysis. Focus group discussions (n=5-6) will be conducted with men living with HIV, health care providers, and #App developers to explore barriers and facilitators of implementation and adoption. Focus group discussions will be audio-recorded, transcribed, coded, and analyzed thematically. Results: This #Study received institutional review board approval in July 2025 and was registered on ClinicalTrials.gov in August 2025. Recruitment began in September 2025 and concluded in November 2025. A total of 307 men living with HIV were recruited across the 4 clinics for the pre- and postquantitative assessment. Preliminary findings will describe implementation outcomes and early effects on HIV care engagement. Conclusions: This trial will use a stepped-wedge design to evaluate the implementation and effects of the Nishauri #mHealth intervention on antiretroviral therapy adherence and clinic attendance among men in Homa Bay County. By examining both clinical outcomes and the influence of masculine norms on intervention uptake, it will provide robust evidence on the effectiveness of #mHealth strategies tailored for men in low-resource, high–HIV-burden settings. Findings will inform the design, scalability, and optimization of similar interventions by identifying key implementation barriers and facilitators. Trial Registration: ClinicalTrials.gov NCT07116538; https://clinicaltrials.gov/#Study/NCT07116538 International Registered Report Identifier (IRRID): DERR1-10.2196/85279

JMIR Res Protocols: Assessing the Implementation and Potential Effects of the Nishauri #mHealth Intervention on HIV Care Among Men in Homa Bay County, Kenya: #Protocol for a Mixed Methods #Study

Effects of the #mHealth Supportive Care Program for Family Caregivers of Individuals With Dementia and #Diabetes: Pilot Randomized Controlled Trial Background: The comorbidity of dementia and type 2 #Diabetes mellitus exacerbates the burden on family caregivers (FCGs). #Mobile #Health (#mHealth) technology offers a promising alternative to overcome the spatiotemporal limitations of traditional interventions, but evidence for its efficacy in supporting dementia–type 2 #Diabetes mellitus caregivers remains scarce. Objective: This study aimed to evaluate the effectiveness of an #mHealth supportive care program for FCGs of individuals with dementia and #Diabetes, focusing on caregiver burden, social support, and dementia care knowledge. Methods: A 2-arm, parallel-group randomized controlled trial was conducted. Between September 2022 and January 2023, FCGs were recruited from 5 urban and 10 rural communities under a community #Health center in Xiamen, China. Eligible caregivers were legally related to the patient, providing care for more than 8 hours per day for at least 1 month, conscious adults with basic literacy, owning and able to use a smartphone, and willing to provide informed consent. Their care recipients met diagnostic criteria for both dementia and type 2 #Diabetes, aged more than 60 years. Participants were randomly allocated (1:1) to intervention (n=30) or wait-list control (n=30). The intervention group received a 12-week #mHealth supportive care program via the “Xiamen i-#Health” platform, comprising 6 core modules (updated biweekly) and on-demand #Teleconsultation, in addition to conventional offline #Health education. The control group received conventional monthly 1-hour home-visit #Health education only. The primary outcome was caregiver burden measured by the Caregiver Burden Inventory (CBI). Secondary outcomes included social support (Social Support Rating Scale; SSRS) and dementia care knowledge (Dementia Care Knowledge Scale; DCKS). Assessments were performed at baseline (T0) and 3-month postintervention (T1). Only data collectors and statistical analysts were blinded. Results: Of 108 potential participants, 60 were randomly assigned. Per-protocol analysis included 55 participants (intervention group n=28 and control n=27). Postintervention, the intervention group showed a significantly greater reduction in CBI scores compared to the control group (between-group difference, =−3.534,

New in JMIR mhealth: Effects of the #mHealth Supportive Care Program for Family Caregivers of Individuals With Dementia and #Diabetes: Pilot Randomized Controlled Trial

Factors Contributing to the Establishment of Out#Patient #Smartphone #mHealth-Based Barcode #Medication Administration: A Work-System Analysis Date Submitted: Mar 7, 2026. Open Peer Review Period: Mar 19, 2026 - May 14, 2026.

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Integrating #Wearable-enabled #mHealth Reports into Recovery High School Care Planning: A Mixed Methods Pilot #Study Date Submitted: Mar 17, 2026. Open Peer Review Period: Mar 17, 2026 - May 12, 2026.

Reminder>> Integrating #Wearable-enabled #mHealth Reports into Recovery High School Care Planning: A Mixed Methods Pilot #Study (preprint) #openscience #PeerReviewMe #PlanP

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Families Moving Forward Connect #mHealth Intervention for Caregivers of Children With Fetal Alcohol Spectrum Disorders: Randomized Controlled Trial Background: Fetal alcohol spectrum disorders (FASD) affect 1.1% to 5% of the general population. Yet, most children with FASD and their families cannot access evidence-based interventions. #Mobile #Health (#mHealth) interventions have the potential to increase access to care on a broad scale. While numerous self-directed parenting apps exist, none have been tested for FASD. The FMF (Families Moving Forward) Connect #App is a self-directed intervention derived from an empirically supported intervention for caregivers raising children with FASD. FMF Connect is the first self-directed parenting #App for FASD, and also one of the first parenting apps to be systematically developed and tested. Objective: This study aimed to test the efficacy of FMF Connect for caregivers raising children with FASD on targeted primary (child behavior, caregiver attributions, parenting efficacy and satisfaction, FASD knowledge, and family needs met) and secondary (child adaptive behavior, caregiver self-care, and #App satisfaction) outcomes. Methods: This study involved a 3-arm randomized controlled trial with equal allocation to groups (1) FMF Connect+coaching, (2) FMF Connect, or (3) waitlist control. Participants from the United States were recruited online through an open access website. Recruitment materials were distributed by the Collaborative Initiative on FASD, FASD listserves, and social media. In total, 129 caregivers of children (aged 3‐12 y) with FASD or prenatal alcohol exposure (PAE) were enrolled. Online surveys were administered at baseline, 6 weeks, and 12 weeks. Data were analyzed with linear mixed modeling, linear regressions, and structural equation modeling using SPSS (version 29.0; IBM) and Mplus 8 (Muthén & Muthén). Results: A total of 43 participants were randomized to each group. Caregivers were predominantly White adoptive mothers. Of the total, 64% (n=83) of participants were retained through the 12-week follow-up. Groups did not differ in terms of demographic characteristics, baseline levels of functioning, or attrition. Usage patterns were similar across groups, suggesting coaching did not increase engagement. Given a few differences, #App intervention groups were combined for analyses. Relative to the waitlist group, caregivers in the FMF Connect group evidenced greater improvements in FASD knowledge, child behavior attributions, family needs met, and self-care after 12 weeks (=.01-.048). After controlling for multiple comparisons, differences in FASD knowledge, self-care, and family needs met approached significance (=.06-.07). Groups did not differ in parenting satisfaction, child behavior problems, or adaptive functioning. More #App usage is related to greater changes in parenting efficacy. Caregiver behavior attributions at 6 weeks did not mediate intervention effects. Conclusions: This study demonstrated initial efficacy of the FMF Connect #App for targeted caregiver outcomes, with small to medium effect sizes. As an #mHealth #App, the FMF Connect intervention has potential for scalability and accessibility. This could lead to a substantial public #Health impact, particularly for families who face challenges accessing evidence-based resources or encounter other barriers to care. Trial Registration: ClinicalTrials.gov NCT05028517; https://clinicaltrials.gov/NCT05028517

New in JMIR mhealth: Families Moving Forward Connect #mHealth Intervention for Caregivers of Children With Fetal Alcohol Spectrum Disorders: Randomized Controlled Trial

Factors Contributing to the Establishment of Out#Patient #Smartphone #mHealth-Based Barcode #Medication Administration: A Work-System Analysis Date Submitted: Mar 7, 2026. Open Peer Review Period: Mar 19, 2026 - May 14, 2026.

Factors Contributing to the Establishment of Out#Patient #Smartphone #mHealth-Based Barcode #Medication Administration: A Work-System Analysis (preprint) #openscience #PeerReviewMe #PlanP

mHealth Intervention to Promote Nonexercise Physical Activity in Patients With Type 2 Diabetes: Secondary Analysis and Implementation Study Background: Physical activity (PA) has an important role in the prevention and treatment of type 2 diabetes (T2D). Interventions with mobile-based technology (mobile health [mHealth]) seem promising in PA promotion, but their behavioral framework is often vague, and the implementation is seldom reported. Objective: This paper examines perceived behavior change needs and implementation of an mHealth approach in increasing nonexercise PA in patients with T2D. Methods: A 3-arm mHealth intervention was conducted in primary care. Information on perceived behavior change needs was collected with a modified capability, opportunity, motivation—behavior (COM-B) questionnaire before the intervention from a separate sample of patients with T2D (n=25) and at the intervention baseline (n=119). Implementation evaluation focused on the fidelity and acceptability of the main arm of the intervention (n=39), which included 24-hour accelerometer use, a smartphone app with personal feedback, a PA leaflet, a YouTube video on walking, and individual counseling with 3 face-to-face sessions and 4 telephone contacts. Data on fidelity were accumulated during the intervention through counseling cards and cloud computing. Data on acceptability were collected with a questionnaire at the end of the intervention (Likert scale from 1 to 5). Data analysis was mainly descriptive. Results: The participants’ responses revealed 3 items in capability and 2 in motivation, which stood out as perceived behavior change needs. Moreover, the main intervention arm showed good fidelity (eg, face-to-face sessions: 112/117, 96% and telephone contacts completed: 145/156, 93%; mean weekly accelerometer use 54%; ranging from 80% to 17% during the intervention) and acceptability (mean score ranging from 3.8 to 4.8), although some challenges were also experienced, especially in cloud-computed feedback and accelerometer-app use. Conclusions: The findings on behavior change needs call for additional research since no comparable studies were found. In addition, the explanatory value of the COM-B model and the psychometric properties of the COM-B questionnaire deserve further attention. The main intervention arm seemed applicable to clinical practice. However, the challenges discovered underscore the importance of pretesting technology-based approaches in patients with T2D. Trial Registration: ClinicalTrials.gov NCT04587414; https://clinicaltrials.gov/study/NCT04587414

JMIR Formative Res: mHealth Intervention to Promote Nonexercise Physical Activity in Patients With Type 2 Diabetes: Secondary Analysis and Implementation Study #mHealth #Type2Diabetes #PhysicalActivity #HealthTech #DiabetesCare