Abha Shrestha

Background: The prevalence of gestational diabetes mellitus (GDM) is increasing, particularly in low- and middle-income countries (LMICs) like Nepal. GDM self-management, including intensive dietary and lifestyle modifications and blood glucose monitoring, is critical to maintain glycemic control and prevent adverse outcomes. However, in resource-limited settings, several barriers hinder optimal self-management. Mobile health (mHealth) technology holds promise as a strategy to augment GDM treatment by promoting healthy behaviors and supporting self-management, but this approach has not yet been tested in any LMIC. Objective: This report describes the protocol to develop a culturally tailored mHealth app that supports self-management and treatment of GDM (GDM–Dhulikhel Hospital [GDM-DH] app, phase 1) and test its usability and preliminary efficacy (phase 2) among patients with GDM in a periurban hospital setting in Nepal. Methods: The study will be conducted at Dhulikhel Hospital in Dhulikhel, Nepal. In the development phase (phase 1), a prototype of the GDM-DH app will be developed based on expert reviews and a user-centered design approach. To understand facilitators and barriers to GDM self-management and to gather feedback on the prototype, focus groups and in-depth interviews will be conducted with patients with GDM (n=12), health care providers (n=5), and family members (n=3), with plans to recruit further if saturation is not achieved. Feedback will be used to build a minimum viable product, which will undergo user testing with 18 patients with GDM using a think-aloud protocol. The final GDM-DH app will be developed based on user feedback and following an iterative product design and user testing process. In the randomized controlled trial phase (phase 2), newly diagnosed patients with GDM (n=120) will be recruited and randomized to either standard care alone or standard care plus the GDM-DH app from 24-30 weeks gestation until delivery. In this proof-of-concept trial, feasibility outcomes will be app usage, self-monitoring adherence, and app usability and acceptability. Exploratory treatment outcomes will be maternal glycemic control at 6 weeks post partum, birth weight, and rates of labor induction and cesarean delivery. Qualitative data obtained from phase 1 will be analyzed using thematic analysis. In phase 2, independent 2-tailed t tests or chi-square analyses will examine differences in outcomes between the 2 treatment conditions. Results: As of July 2024, we have completed phase 1. Phase 2 is underway. The first participant was enrolled in October 2021, with 99 participants enrolled as of July 2024. We anticipate completing recruitment by December 2024 and disseminating findings by December 2025. Conclusions: App-based lifestyle interventions for GDM management are not common in LMICs, where GDM prevalence is rapidly increasing. This proof-of-concept trial will provide valuable insights into the potential of leveraging mHealth app–based platforms for GDM self-management in LMICs. Trial Registration: ClinicalTrials.gov NCT04198857; https://clinicaltrials.gov/study/NCT04198857 International Registered Report Identifier (IRRID): DERR1-10.2196/59423

BACKGROUND The prevalence of gestational diabetes mellitus (GDM) is increasing, particularly in low- and middle-income countries (LMICs) like Nepal. GDM self-management, including intensive dietary and lifestyle modifications and blood glucose monitoring, is critical to maintain glycemic control and prevent adverse outcomes. However, in resource-limited settings, several barriers hinder optimal self-management. Mobile health (mHealth) technology holds promise as a strategy to augment GDM treatment by promoting healthy behaviors and supporting self-management, but this approach has not yet been tested in any LMIC. OBJECTIVE This report describes the protocol to develop a culturally tailored mHealth app that supports self-management and treatment of GDM (GDM–Dhulikhel Hospital [GDM-DH] app, phase 1) and test its usability and preliminary efficacy (phase 2) among patients with GDM in a periurban hospital setting in Nepal. METHODS The study will be conducted at Dhulikhel Hospital in Dhulikhel, Nepal. In the development phase (phase 1), a prototype of the GDM-DH app will be developed based on expert reviews and a user-centered design approach. To understand facilitators and barriers to GDM self-management and to gather feedback on the prototype, focus groups and in-depth interviews will be conducted with patients with GDM (n=12), health care providers (n=5), and family members (n=3), with plans to recruit further if saturation is not achieved. Feedback will be used to build a minimum viable product, which will undergo user testing with 18 patients with GDM using a think-aloud protocol. The final GDM-DH app will be developed based on user feedback and following an iterative product design and user testing process. In the randomized controlled trial phase (phase 2), newly diagnosed patients with GDM (n=120) will be recruited and randomized to either standard care alone or standard care plus the GDM-DH app from 24-30 weeks gestation until delivery. In this proof-of-concept trial, feasibility outcomes will be app usage, self-monitoring adherence, and app usability and acceptability. Exploratory treatment outcomes will be maternal glycemic control at 6 weeks post partum, birth weight, and rates of labor induction and cesarean delivery. Qualitative data obtained from phase 1 will be analyzed using thematic analysis. In phase 2, independent 2-tailed t tests or chi-square analyses will examine differences in outcomes between the 2 treatment conditions. RESULTS As of July 2024, we have completed phase 1. Phase 2 is underway. The first participant was enrolled in October 2021, with 99 participants enrolled as of July 2024. We anticipate completing recruitment by December 2024 and disseminating findings by December 2025. CONCLUSIONS App-based lifestyle interventions for GDM management are not common in LMICs, where GDM prevalence is rapidly increasing. This proof-of-concept trial will provide valuable insights into the potential of leveraging mHealth app–based platforms for GDM self-management in LMICs. CLINICALTRIAL ClinicalTrials.gov NCT04198857; https://clinicaltrials.gov/study/NCT04198857 INTERNATIONAL REGISTERED REPORT DERR1-10.2196/59423

Background: Mobile apps can aid with the management of gestational diabetes mellitus (GDM) by providing patient education, reinforcing regular blood glucose monitoring and diet/lifestyle modification, and facilitating clinical and social support. Objective: This study aimed to describe our process of designing and developing a culturally tailored app, Garbhakalin Diabetes athawa Madhumeha—Dhulikhel Hospital (GDM-DH), to support GDM management among Nepalese patients by applying a user-centered design approach. Methods: A multidisciplinary team of experts, as well as health care providers and patients in Dhulikhel Hospital (Dhulikhel, Nepal), contributed to the development of the GDM-DH app. After finalizing the app’s content and features, we created the app’s wireframe, which illustrated the app’s proposed interface, navigation sequences, and features and function. Feedback was solicited on the wireframe via key informant interviews with health care providers (n=5) and a focus group and in-depth interviews with patients with GDM (n=12). Incorporating their input, we built a minimum viable product, which was then user-tested with 18 patients with GDM and further refined to obtain the final version of the GDM-DH app. Results: Participants in the focus group and interviews unanimously concurred on the utility and relevance of the proposed mobile app for patients with GDM, offering additional insight into essential modifications and additions to the app’s features and content (eg, inclusion of example meal plans and exercise videos).The mean age of patients in the usability testing (n=18) was 28.8 (SD 3.3) years, with a mean gestational age of 27.2 (SD 3.0) weeks. The mean usability score across the 10 tasks was 3.50 (SD 0.55; maximum score=5 for “very easy”); task completion rates ranged from 55.6% (n=10) to 94.4% (n=17). Findings from the usability testing were reviewed to further optimize the GDM-DH app (eg, improving data visualization). Consistent with social cognitive theory, the final version of the GDM-DH app supports GDM self-management by providing health education and allowing patients to record and self-monitor blood glucose, blood pressure, carbohydrate intake, physical activity, and gestational weight gain. The app uses innovative features to minimize the self-monitoring burden, as well as automatic feedback and data visualization. The app also includes a social network “follow” feature to add friends and family and give them permission to view logged data and a progress summary. Health care providers can use the web-based admin portal of the GDM-DH app to enter/review glucose levels and other clinical measures, track patient progress, and guide treatment and counseling accordingly. Conclusions: To the best of our knowledge, this is the first mobile health platform for GDM developed for a low-income country and the first one containing a social support feature. A pilot clinical trial is currently underway to explore the clinical utility of the GDM-DH app.

BACKGROUND Mobile apps can aid with the management of gestational diabetes mellitus (GDM) by providing patient education, reinforcing regular blood glucose monitoring and diet/lifestyle modification, and facilitating clinical and social support. OBJECTIVE This study aimed to describe our process of designing and developing a culturally tailored app, Garbhakalin Diabetes athawa Madhumeha—Dhulikhel Hospital (GDM-DH), to support GDM management among Nepalese patients by applying a user-centered design approach. METHODS A multidisciplinary team of experts, as well as health care providers and patients in Dhulikhel Hospital (Dhulikhel, Nepal), contributed to the development of the GDM-DH app. After finalizing the app’s content and features, we created the app’s wireframe, which illustrated the app’s proposed interface, navigation sequences, and features and function. Feedback was solicited on the wireframe via key informant interviews with health care providers (n=5) and a focus group and in-depth interviews with patients with GDM (n=12). Incorporating their input, we built a minimum viable product, which was then user-tested with 18 patients with GDM and further refined to obtain the final version of the GDM-DH app. RESULTS Participants in the focus group and interviews unanimously concurred on the utility and relevance of the proposed mobile app for patients with GDM, offering additional insight into essential modifications and additions to the app’s features and content (eg, inclusion of example meal plans and exercise videos).The mean age of patients in the usability testing (n=18) was 28.8 (SD 3.3) years, with a mean gestational age of 27.2 (SD 3.0) weeks. The mean usability score across the 10 tasks was 3.50 (SD 0.55; maximum score=5 for “very easy”); task completion rates ranged from 55.6% (n=10) to 94.4% (n=17). Findings from the usability testing were reviewed to further optimize the GDM-DH app (eg, improving data visualization). Consistent with social cognitive theory, the final version of the GDM-DH app supports GDM self-management by providing health education and allowing patients to record and self-monitor blood glucose, blood pressure, carbohydrate intake, physical activity, and gestational weight gain. The app uses innovative features to minimize the self-monitoring burden, as well as automatic feedback and data visualization. The app also includes a social network “follow” feature to add friends and family and give them permission to view logged data and a progress summary. Health care providers can use the web-based admin portal of the GDM-DH app to enter/review glucose levels and other clinical measures, track patient progress, and guide treatment and counseling accordingly. CONCLUSIONS To the best of our knowledge, this is the first mobile health platform for GDM developed for a low-income country and the first one containing a social support feature. A pilot clinical trial is currently underway to explore the clinical utility of the GDM-DH app.

Introduction: Postnatal care services helps in detecting and subsequently managing life threatening complications. With the ubiquitous use of the mobile phone in Nepal, social media based postpartum education has the potential to increase PNC knowledge among pregnant women. This study aimed to assess the effect of social media-based health education program on PNC knowledge among pregnant women attending Dhulikhel hospital, Nepal. Materials and methods: We conducted a two-arm open-label randomized controlled trial among literate pregnant women visiting Dhulikhel hospital for ANC check-up from May to August, 2021. A computer-based program allocated 229 pregnant women owning smartphones with internet connectivity in a 1:1 ratio to either intervention (n = 109) or usual care (n = 120). We assessed PNC knowledge in the participants by interviewing in-person or via phone. The intervention group received a 16 minutes video on PNC and the participants were reminded to view the video every week via telephone for a month. Control group received usual care. The primary outcome of the study was change in PNC knowledge score. We utilized intent-to-treat analysis and measured the effect of the intervention on PNC knowledge score using simple linear regression analysis. Results and discussion: The mean PNC knowledge score increased by additional 8.07 points among pregnant women in the intervention group compared to the control group (95% CI: 2.35: 13.80; p-value = 0.006). The maternal care attribute knowledge increased by 4.31 points (95% CI: 1.51–7.10, p-value = 0.03) and newborn care attribute knowledge increased by 3.39 points (95% CI: 0.41–6.37, p-value = 0.02) among pregnant women in the intervention compared to the control group. Conclusion: A social media-based health education is effective in improving PNC knowledge score among pregnant women. Further research is needed to evaluate if this increased knowledge is translated into the increased utilization of PNC care. Trial registration: ClinicalTrials.gov ID: NCT05132608.

Mobile apps can aid with the management of Gestational Diabetes Mellitus (GDM) by providing patient education, and reinforcing daily glucose monitoring and diet/lifestyle modification. Here we describe our process of applying a user-centered design approach in developing a culturally-appropriate app (GDM-DH) to support the management of GDM among patients in Dhulikhel Hospital, Nepal. A multidisciplinary team including experts in GDM, mHealth, and behavior and implementation sciences, as well as health providers and patients at Dhulikhel Hospital, contributed to the development of the GDM-DH app. After finalizing the app's content and features, we created the app's wireframe, which illustrated the app's proposed interface, navigation sequences, and features and functions. This was followed by key informant interviews with healthcare providers (n = 5), focus groups, and in-depth interviews with GDM patients (n = 12) in which they were asked to provide feedback on the features and functions of the wireframe. Incorporating their input, we built the minimum viable product, which was user-tested with 6 GDM patients, and further refined for the final version of the GDM-DH app. Qualitative findings from the user research affirmed the potential utility and usability of our target app and provided insight into app features and design elements that needed to be added or modified. Consistent with the Social Cognitive Theory, the final version of the GDM-DH app supports GDM self-management by providing health education and allowing patients to record and self-monitor blood glucose levels, carbohydrate intake, physical activity, and gestational weight gain. The app uses innovative features to minimize the self-monitoring burden and uses automatic feedback and data visualizations. Healthcare providers can use the web-based admin portal of the GDM-DH app to enter/review glucose readings, track patient progress, and guide treatment and counseling accordingly. To our knowledge, this is the first mHealth platform for GDM developed for a low-income country, and the first one containing a feature to aid with carbohydrate estimation in meals. A pilot clinical trial is currently underway to explore the clinical utility of the GDM-DH app. NIH/FIC.