Please use this identifier to cite or link to this item: https://doi.org/10.2196/preprints.25820
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dc.titleA Personalized Mobile Health Program for Type 2 Diabetes During the COVID-19 Pandemic: Single-Group Pre–Post Study (Preprint)
dc.contributor.authorAng, Ian Yi Han
dc.contributor.authorTan, Kyle Xin Quan
dc.contributor.authorTan, Clive
dc.contributor.authorTan, Chiew Hoon
dc.contributor.authorKwek, James Wei Ming
dc.contributor.authorTay, Joanne
dc.contributor.authorToh, Sue Anne
dc.date.accessioned2023-05-22T09:24:32Z
dc.date.available2023-05-22T09:24:32Z
dc.date.issued2020-12-01
dc.identifier.citationAng, Ian Yi Han, Tan, Kyle Xin Quan, Tan, Clive, Tan, Chiew Hoon, Kwek, James Wei Ming, Tay, Joanne, Toh, Sue Anne (2020-12-01). A Personalized Mobile Health Program for Type 2 Diabetes During the COVID-19 Pandemic: Single-Group Pre–Post Study (Preprint). JMIR Diabetes 6 (3). ScholarBank@NUS Repository. https://doi.org/10.2196/preprints.25820
dc.identifier.issn2371-4379
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/239649
dc.description.abstractBackground: With increasing type 2 diabetes prevalence, there is a need for effective programs that support diabetes management and improve type 2 diabetes outcomes. Mobile health (mHealth) interventions have shown promising results. With advances in wearable sensors and improved integration, mHealth programs could become more accessible and personalized. Objective: The study aimed to evaluate the feasibility, acceptability, and effectiveness of a personalized mHealth-anchored intervention program in improving glycemic control and enhancing care experience in diabetes management. The program was coincidentally implemented during the national-level lockdown for COVID-19 in Singapore, allowing for a timely study of the use of mHealth for chronic disease management. Methods: Patients with type 2 diabetes or prediabetes were enrolled from the Singapore Armed Forces and offered a 3-month intervention program in addition to the usual care they received. The program was standardized to include (1) in-person initial consultation with a clinical dietitian; (2) in-person review with a diabetes specialist doctor; (3) 1 continuous glucose monitoring device; (4) access to the mobile app for dietary intake and physical activity tracking, and communication via messaging with the dietitian and doctor; and (5) context-sensitive digital health coaching over the mobile app. Medical support was rendered to the patients on an as-needed basis when they required advice on adjustment of medications. Measurements of weight, height, and glycated hemoglobin A1c (HbA1c) were conducted at 2 in-person visits at the start and end of the program. At the end of the program, patients were asked to complete a short acceptability feedback survey to understand the motivation for joining the program, their satisfaction, and suggestions for improvement. Results: Over a 4-week recruitment period, 130 individuals were screened, the enrollment target of 30 patients was met, and 21 patients completed the program and were included in the final analyses; 9 patients were lost to follow-up (full data were not available for the final analyses). There were no differences in the baseline characteristics between patients who were included and excluded from the final analyses (age category: P=.23; gender: P=.21; ethnicity: P>.99; diabetes status category: P=.52, medication adjustment category: P=.65; HbA1c category: P=.69; BMI: P>.99). The 21 patients who completed the study rated a mean of 9.0 out of 10 on the Likert scale for both satisfaction questions. For the Yes-No question on benefit of the program, all of the patients selected “Yes.” Mean HbA1c decreased from 7.6% to 7.0% (P=.004). There were no severe hypoglycemia events (glucose level <3.0 mmol/L) reported. Mean weight decreased from 76.8 kg to 73.9 kg (P<.001), a mean decrease of 3.5% from baseline weight. Mean BMI decreased from 27.8 kg/m2 to 26.7 kg/m2 (P<.001). Conclusions: The personalized mHealth program was feasible, acceptable, and produced significant reductions in HbA1c (P=.004) and body weight (P<.001) in individuals with type 2 diabetes. Such mHealth programs could overcome challenges posed to chronic disease management by COVID-19, including disruptions to in-person health care access.
dc.publisherJMIR Publications
dc.sourceElements
dc.subjecttype 2 diabetes
dc.subjectprediabetic state
dc.subjecttext messaging
dc.subjectmobile applications
dc.subjectglycated hemoglobin A
dc.subjectHbA1c
dc.subjectblood glucose
dc.subjectbody mass index
dc.subjectmHealth
dc.subjectCOVID-19
dc.subjectdiabetes
dc.subjectintervention
dc.subjectself-management
dc.subjectchronic disease
dc.subjectoutcome
dc.typeArticle
dc.date.updated2023-05-19T09:51:30Z
dc.contributor.departmentDEAN'S OFFICE (SSH SCH OF PUBLIC HEALTH)
dc.contributor.departmentMEDICINE
dc.contributor.departmentSAW SWEE HOCK SCHOOL OF PUBLIC HEALTH
dc.description.doi10.2196/preprints.25820
dc.description.sourcetitleJMIR Diabetes
dc.description.volume6
dc.description.issue3
dc.published.statePublished
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