Ignite Creation Date:
2025-12-24 @ 6:31 PM
Ignite Modification Date:
2025-12-24 @ 6:31 PM
Study NCT ID:
NCT04198857
Status:
RECRUITING
Last Update Posted:
2025-09-17
First Post:
2019-11-26
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Development and Testing of a Mobile Health Application for Management of Gestational Diabetes
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D016640', 'term': 'Diabetes, Gestational'}], 'ancestors': [{'id': 'D011248', 'term': 'Pregnancy Complications'}, {'id': 'D005261', 'term': 'Female Urogenital Diseases and Pregnancy Complications'}, {'id': 'D000091642', 'term': 'Urogenital Diseases'}, {'id': 'D003920', 'term': 'Diabetes Mellitus'}, {'id': 'D044882', 'term': 'Glucose Metabolism Disorders'}, {'id': 'D008659', 'term': 'Metabolic Diseases'}, {'id': 'D009750', 'term': 'Nutritional and Metabolic Diseases'}, {'id': 'D004700', 'term': 'Endocrine System Diseases'}]}, 'interventionBrowseModule': {'meshes': [{'id': 'D013812', 'term': 'Therapeutics'}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'RANDOMIZED', 'maskingInfo': {'masking': 'NONE'}, 'primaryPurpose': 'SUPPORTIVE_CARE', 'interventionModel': 'PARALLEL', 'interventionModelDescription': 'A user-centered design approach, here we propose to develop a culturally-appropriate smartphone application (app) to support self-management of GDM (GDM-DH), and test its usability and preliminary efficacy, among patients in a tertiary level hospital.'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 220}}, 'statusModule': {'overallStatus': 'RECRUITING', 'startDateStruct': {'date': '2021-10-18', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-09', 'completionDateStruct': {'date': '2026-12-18', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-09-10', 'studyFirstSubmitDate': '2019-11-26', 'studyFirstSubmitQcDate': '2019-12-11', 'lastUpdatePostDateStruct': {'date': '2025-09-17', 'type': 'ESTIMATED'}, 'studyFirstPostDateStruct': {'date': '2019-12-13', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2026-04', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Maternal blood glucose levels at 6 weeks postpartum', 'timeFrame': 'up to 22 weeks after recruitment', 'description': 'Six weeks after delivery, all participants will undergo 100-g OGTT. From blood samples collected, fasting and 2-hour glucose levels will be measured in the hospital laboratory using standard laboratory methods.'}, {'measure': 'Neonatal birth weight', 'timeFrame': 'up to 16 weeks after recruitment', 'description': 'prior to discharge, less than 24 hours after delivery, birthweight will be obtained from the medical records'}, {'measure': 'Primary cesarean delivery', 'timeFrame': 'up to 16 weeks after recruitment', 'description': 'Primary cesarean delivery (yes/no) will be abstracted from the medical records at delivery.'}, {'measure': 'Neonatal hypoglycemia', 'timeFrame': 'up to 16 weeks after recruitment', 'description': 'Proportion of neonates with neonatal hypoglycemia will be compared between the two treatment groups. The data will be abstracted from the medical records at delivery.'}], 'secondaryOutcomes': [{'measure': 'Maternal gestational weight gain', 'timeFrame': 'up to 16 weeks after recruitment', 'description': "The absolute weight gained by the pregnant mother over pregnancy will be calculated by subtracting the measured weight at or before 12 weeks' gestation from last measured weight before delivery. These weights will be abstracted from the medical records at delivery."}, {'measure': 'Usability of the GDM app', 'timeFrame': 'up to 22 weeks after recruitment', 'description': 'App usability will also be assessed through a mHealth app usability questionnaire (MAUQ). Out of the four versions of MAUQ previously validated for usability studies, the version we will be using is specifically designed for patient feedback on an interactive mHealth app. The users will completed the 21 questions and the average score will be determined, with higher score indicating higher user usability of the app.'}, {'measure': 'Acceptability', 'timeFrame': 'up to 22 weeks after recruitment', 'description': 'At six weeks postpartum, the Oxford Maternity Diabetes Treatment Satisfaction Questionnaire (OMDTSQ), a validated tool will be administered to assess general satisfaction and acceptability of technology use for diabetes care. This questionnaire comprises of 9 questions designed to assess general satisfaction with treatment, the acceptability and reliability of the technology, and the perceived relationship with the treatment team. Women will be asked to score their agreement with statements on a 7-point Likert-type scale, ranging from +3 (strongly agree) to -3 (strongly disagree).'}, {'measure': 'Usability of telemonitoring', 'timeFrame': 'up to 22 weeks after recruitment', 'description': 'At 6 weeks postpartum, the System Usability Scale (SUS), a 10-item 5-point Likert scale questionnaire on usability and human-computer interaction, will be administered to assess the perceived usability of the telemonitoring system. Good usability is indicated by SUS score of above 65 (maximum score 100; scores range 0-100).'}, {'measure': 'Self-monitoring blood pressure adherence', 'timeFrame': 'recruitment to delivery', 'description': 'Self-monitoring adherence will be measured by the number of blood pressure entries in the app over the entire monitoring period'}, {'measure': 'Self-monitoring glucose adherence', 'timeFrame': 'recruitment to delivery', 'description': 'Self-monitoring adherence will be measured by the number of blood glucose entries in the app over the entire monitoring period'}, {'measure': 'App Usage', 'timeFrame': 'recruitment to delivery', 'description': 'App usage will be defined as the number of times the app was opened over the entire monitoring period.'}, {'measure': 'Antenatal care adherence', 'timeFrame': 'recruitment to delivery', 'description': 'Antenatal care adherence will be measured by the number of prenatal appointments attended over the entire monitoring period'}, {'measure': 'Apgar scale', 'timeFrame': 'up to 16 weeks after recruitment', 'description': 'The average Apgar score of the neonates will be compared between the two treatment groups. The data will be abstracted from the medical records of the patients in both treatment groups at delivery.'}, {'measure': 'NICU admittance', 'timeFrame': 'up to 16 weeks after recruitment', 'description': 'will be abstracted from the medical records at delivery.'}, {'measure': 'Proportion of insulin prescription', 'timeFrame': 'up to 16 weeks after recruitment', 'description': 'The number of patients whose diabetes progresses to higher levels, needing insulin for sugar control will be compared between the two treatment conditions. Information about progression to insulin therapy will be abstracted from the medical records of the patients in both the treatment groups at delivery.'}, {'measure': 'Induction of labor', 'timeFrame': 'up to 16 weeks after recruitment', 'description': 'Induction of labor (yes/no) will be abstracted from the medical records at delivery.'}, {'measure': 'Glucose readings over glycemic target', 'timeFrame': 'up to 16 weeks after recruitment', 'description': 'Frequency of glucose levels above the glycemic target will be compared between the two groups over the course of their pregnancy. To determine the frequency, the number of fasting glucose levels taken pre-meal and 2 hours post meal that surpass the glycemic targets will be divided by the total number of entries. The glycemic targets are \\</=5.5 mmol/L pre-meals, \\</= 6.6 mmol/L at 2 hours post meals. Glucose levels will be extracted from the app.'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['Diabetes, Gestational', 'Telemedicine']}, 'referencesModule': {'references': [{'pmid': '39432898', 'type': 'DERIVED', 'citation': 'Berube LT, Shrestha A, Shrestha A, Daneault JF, Shakya PR, Dhimal M, Shrestha R, Rawal S. Development and Testing of a Mobile App for Management of Gestational Diabetes in Nepal: Protocol for a User-Centered Design Study and Exploratory Randomized Controlled Trial. JMIR Res Protoc. 2024 Oct 21;13:e59423. doi: 10.2196/59423.'}]}, 'descriptionModule': {'briefSummary': 'Adequate control and management of gestational diabetes mellitus (GDM) during pregnancy is critical to mitigate its short- and long-term health consequences in women and their children and may serve as a key strategy to curb the escalating type 2 diabetes epidemic in low- and middle-income countries (LMICs). Taking a user-centered design approach, here the study investigators propose to develop a culturally-appropriate smartphone application (app) to support self-management of GDM, and additionally, test its usability and preliminary efficacy, among patients in a peri-urban hospital setting in Nepal. App-based lifestyle interventions for GDM management are not common, especially in LMICs where its prevalence is rapidly increasing, and as such, study findings will have important public health relevance for a broader population.', 'detailedDescription': "The prevalence of gestational diabetes mellitus (GDM) is rapidly increasing worldwide, particularly in low- and middle-income countries (LMICs). Tight glycemic control via diet and lifestyle modification is critical to treating GDM and preventing its adverse health consequences, including increased risk of type 2 diabetes (T2D), in women and their children. However, in many resource-limited countries including Nepal, time for diet/lifestyle counseling often competes with other components of antenatal care. Mobile health (mHealth) technology can be leveraged to promote healthy behaviors, and support self-management and treatment of GDM, but this approach has not been tried previously in any LMICs. Taking a user-centered design approach, here the study investigators propose to develop a culturally-appropriate smartphone application (app) to support self-management of GDM (GDM-DH), and test its usability and preliminary efficacy, among patients in a tertiary level, university hospital of Kathmandu University, Nepal. Based on the Social Cognitive Theory framework for behavior change, this app will assist in self-management of GDM by increasing the patient's knowledge and self-efficacy to adhere to the recommended diet and physical activity regimens. The app will also help clinicians by generating easily digestible visual displays of patient data and behaviors, which can aid in their clinical decision-making and counseling. In the requirements gathering phase, 6 GDM patients will be recruited into a focus group to view paper prototypes and provide feedback on its features and functions. Additional questions will be asked about their perceived barriers, facilitators, and strategies for lifestyle modification. Key informant interviews will also be conducted with 5 clinicians (gynecologists, dietician, physical therapist) and 3 family members, asking them to provide feedback on the GDM-DH prototype, especially pertaining to the usefulness and format of the graphic summaries of patient data. After revising paper prototypes and developing the first digital prototype, six additional patients with GDM will be recruited for two rounds of usability testing including think-aloud protocol and focus group discussions. Final prototype will be developed following an iterative process of product design and user testing. After developing the app, the investigators will recruit 120 women who are newly diagnosed with GDM, and randomly assign them to one of two treatment conditions: either (A) standard care + telemonitoring alone, or (B) GDM-DH app + standard care + telemonitoring, from 30 weeks of gestation to delivery. All participants will receive bio-monitoring devices for the self-monitoring of blood pressure and blood glucose. Although the fundamental elements of the telemonitoring support are the same between the two groups, patients in the app group will be able to leverage the technological features in the app to aid with self-monitoring.\n\nIn addition to 120 women with GDM, we will also be enrolling 100 women who do not have GDM but failed the glucose challenge test (GCT) in the first screening step of the 2-step diagnostic test for GDM. Women who had high GCT (thus failed the GCT screening) but are not diagnosed GDM are also at increased risk of adverse pregnancy outcomes and are also recommended to adopt diet/lifestyle modification in our study site (Dhulikhel Hospital). In addition to randomizing 120 GDM women in a clinical trial, we will also randomize 100 high GCT women to one of two treatment conditions: either (A) standard care alone or (B) GDM-DH app + standard care, for the rest of their pregnancies.\n\nBlock randomization will be utilized to split GDM patients and high GCT patients evenly amongst the two treatment groups. The 120 GDM women will be randomized into two groups of 60. The high GCT women will be randomized into two groups of 50. Patients in Treatment A will receive standard care alone, regardless of diagnosis. Patients in Treatment B will receive GDM-DH app + standard care. All women diagnosed with GDM will receive telemonitoring in addition to their standard care, whereas women diagnosed with high GCT only will not."}, 'eligibilityModule': {'sex': 'FEMALE', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'genderBased': True, 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* receive antenatal care at Dhulikhel Hospital\n* receive a GDM diagnosis based on Carpenter-Coustan criteria or fail the Glucose Challenge Test only\n* less than 30 gestational weeks into pregnancy\n* own a smartphone\n* have internet connectivity at home\n* can understand and read Nepali\n\nExclusion Criteria:\n\n• Patients with learning difficulties or vision/hearing impairments'}, 'identificationModule': {'nctId': 'NCT04198857', 'briefTitle': 'Development and Testing of a Mobile Health Application for Management of Gestational Diabetes', 'organization': {'class': 'OTHER', 'fullName': 'Rutgers, The State University of New Jersey'}, 'officialTitle': 'Development and Testing of a Mobile Health Application for Management of Gestational Diabetes', 'orgStudyIdInfo': {'id': 'RUPro2019001883/Pro2019002841'}, 'secondaryIdInfos': [{'id': '1R21TW011377', 'link': 'https://reporter.nih.gov/quickSearch/1R21TW011377', 'type': 'NIH'}]}, 'armsInterventionsModule': {'armGroups': [{'type': 'NO_INTERVENTION', 'label': 'Standard Care + Telemonitoring: Control', 'description': 'Standard care for GDM will be modifying diet\\& exercise and/or medication use. Participants will have consultations with a dietitian and a physical therapist to develop a diet and physical activity plan based on pre-pregnancy weight and disease severity. In addition to verbal information about managing GDM with diet and physical activity, patients will be provided with leaflets and brochures. As per the standard care protocol, GDM patients will be asked to visit the OPD for glucose testing every two weeks, and after each testing, blood glucose levels will be recorded in paper booklets assigned to each patient. In addition, the women will be provided with a glucometer and a blood pressure monitor machine. Participants will be taught to use these devices for self-monitoring and will be provided guidelines to follow at home. The OB/GYN physicians will monitor the blood glucose levels across testing, and will prescribe oral hypoglycemic medications or insulin to the patient if needed.'}, {'type': 'EXPERIMENTAL', 'label': 'Standard Care + GDM-DH app + Telemonitoring', 'description': 'In addition to standard care and telemonitoring, this group will use the GDM-DH app. This group will be provided with the same devices as the control group and in addition, the GDM-DH app will be set up in their cellular device. The app will be on their smart phone and will support self-management by: i) providing health education, ii) helping patients identify and set target health goals (for diet, physical activity, and glucose levels), iii) enhancing their self-efficacy to meet target goals, and iv) facilitating desired support from family members. The core component of the GDM-DH app will be to allow GDM patients to record and self-monitor their carbohydrate intake, physical activity and blood glucose levels. Patients will be able to manually enter their weekly blood glucose levels and blood pressure readings on to the app', 'interventionNames': ['Behavioral: Develop a mobile app that supports self- management and treatment for Nepalese GDM patients']}], 'interventions': [{'name': 'Develop a mobile app that supports self- management and treatment for Nepalese GDM patients', 'type': 'BEHAVIORAL', 'description': 'We will use a user-centered design approach to develop a mobile app for GDM (GDM-DH) that matches the needs and technological sophistication of the target users. The goal of the app would be to assist patients in self management of GDM by improving their adherence to the recommended diet and physical activity regimens. The app will be used to collect information such as the carbohydrate consumption, the daily activity status and blood glucose and blood pressure measurements taken at home by the patients. The app will be set up in the phone of the participants and their data will be collected. The participants will be able to assess the usability and feasibility of the app. The app will also help clinicians by generating easily digestible visual displays of patient data and behaviors, which can aid in their clinical decision-making and counseling.', 'armGroupLabels': ['Standard Care + GDM-DH app + Telemonitoring']}]}, 'contactsLocationsModule': {'locations': [{'zip': '45200', 'city': 'Dhulikhel', 'state': 'Kavrepalanchok', 'status': 'RECRUITING', 'country': 'Nepal', 'contacts': [{'name': 'Jyoti Nepal', 'role': 'CONTACT', 'email': 'jyotinepal09@gmail.com', 'phone': '977 9841166333'}], 'facility': 'Dhulikhel Hospital, Kathmandu University Hospital', 'geoPoint': {'lat': 27.6221, 'lon': 85.54281}}], 'centralContacts': [{'name': 'Shristi Rawal, PhD', 'role': 'CONTACT', 'email': 'shristi.rawal@rutgers.edu', 'phone': '973-972-2710'}, {'name': 'Emily N. Peters, MPH', 'role': 'CONTACT', 'email': 'petersen@shp.rutgers.edu', 'phone': '973-972-4778'}], 'overallOfficials': [{'name': 'Shristi Rawal, PhD', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Rutgers University'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Rutgers, The State University of New Jersey', 'class': 'OTHER'}, 'collaborators': [{'name': 'Nepal Health Research Council', 'class': 'OTHER_GOV'}, {'name': 'University of Connecticut', 'class': 'OTHER'}, {'name': 'Fogarty International Center of the National Institute of Health', 'class': 'NIH'}, {'name': 'Dhulikhel Hospital', 'class': 'OTHER'}], 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Assistant Professor', 'investigatorFullName': 'Shristi Rawal, PhD', 'investigatorAffiliation': 'Rutgers, The State University of New Jersey'}}}}