Women’s Usage Behavior and Perceived Usefulness with Using a Mobile Health Application for Gestational Diabetes Mellitus
Mixed-Methods Study
Bibliographic Data
| ID | 15514503 |
|---|---|
| Authors | Shilpa Surendran (0000-0001-9534-2166, National University Health System, corresponding author), Chang Siang Lim (0000-0001-9818-6058, National University Health System), Gerald Choon Huat Koh (0000-0002-6453-6897, National University Health System), Tong Wei Yew (0000-0002-7349-3841, National University of Singapore), E Shyong Tai (0000-0003-2929-8966, National University of Singapore), Pin Sym Foong (0000-0002-4437-8326, National University Health System) |
| Year | 2021 |
| Volume | 18 |
| Issue | 12 |
| Pages | 6670-6670 |
| Publication date | 2021-06-21 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Environmental Research and Public Health (JOURNAL) |
| Journal identifiers | ISSN: 1661-7827 • E-ISSN: 1660-4601 |
| Publisher | Multidisciplinary Digital Publishing Institute (PUBLISHER • CH) |
| DOI | 10.3390/ijerph18126670 |
| PMID | 34205744 |
| OpenAlex | W3174858625 |
| Language | EN |
| References cited | 40 |
The prevalence of gestational diabetes mellitus (GDM) is increasing, and only a few mobile health (mHealth) applications are specifically designed to manage GDM. In this mixed-methods study, a follow-up study of a randomized controlled trial (RCT) analyzed a largely automated mHealth application-based lifestyle coaching program to (a) measure the application's usage behavior and (b) explore users' perceptions of its usefulness in GDM management. Quantitative data were collected from the 170 application users who had participated in the intervention arm of the RCT. Semi-structured interviews (n = 14) captured users' experiences when using the application. Data were collected from June 2019 to January 2020. Quantitative data were analyzed descriptively, and interviews were analyzed thematically. Only 57/170 users (34%) logged at least one meal, and only 35 meals on average were logged for eight weeks because of the incorrectly worded food items and limited food database. On the contrary, an average of 1.85 (SD = 1.60) weight values were logged per week since the weight tracking component was easy to use. Many users (6/14 (43%)) mentioned that the automatic coach messages created an immediate sense of self-awareness in food choices and motivated behavior. The findings suggest that for GDM management, a largely automated mHealth application has the potential to promote self-awareness of healthy lifestyle choices, reducing the need for intensive human resources. Additionally, several gaps in the application's design were identified which need to be addressed in future works
Coaching · Gestational diabetes · Health coaching · Meal · mHealth · Obesity · Pregnancy · Psychological intervention · Randomized controlled trial · Weight loss · Weight management · Applied Psychology · Breastfeeding Practices and Influences · Computer Science · Gestational Diabetes Research and Management · Medicine · Mobile Health and mHealth Applications · Nursing · Psychology
The Science of Real-Time Data Capture
Three techniques for integrating data in mixed methods studies
Historical Origins of the Health Belief Model
Food, culture, and identity in multicultural societies
Using thematic analysis in psychology
Naturalistic inquiry
Theoretical Sampling and Category Development in Grounded Theory
| Citation velocity | historical |
|---|---|
| Highly cited | No |