Development and acceptability of a gestational diabetes mellitus prevention system (Better pregnancy) based on a user-centered approach: A clinical feasibility study

被引:0
|
作者
Duan, Beibei [1 ,2 ]
Zhou, Zheyi [3 ]
Liu, Mengdi [1 ]
Liu, Zhe [1 ]
Zhang, Qianghuizi [1 ]
Liu, Leyang [1 ]
Ma, Cunhao [1 ]
Gou, Baohua [4 ]
Liu, Weiwei [1 ]
机构
[1] Capital Med Univ, Sch Nursing, 10 Youanmen Outer West 1st St, Beijing 100069, Peoples R China
[2] Capital Med Univ, Beijing Shijitan Hosp, Beijing, Peoples R China
[3] Melbourne Med Sch, Dept Western Hosp Gen Surg, Melbourne, Australia
[4] Capital Med Univ, Friendship Hosp, Dept Obstet & Gynecol, Beijing, Peoples R China
来源
DIGITAL HEALTH | 2024年 / 10卷
基金
中国国家自然科学基金;
关键词
Diabetes; gestational; prevention; mobile applications; health belief model; user-centered design; acceptability; RANDOMIZED CONTROLLED-TRIAL; PHYSICAL-ACTIVITY; WEIGHT-GAIN; INTERVENTIONS; EXERCISE; OUTCOMES; PROGRAM; WOMEN; RISK;
D O I
10.1177/20552076241266056
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Background: Gestational diabetes mellitus (GDM) can increase the risk of adverse outcomes for both mothers and infants. Preventive interventions can effectively assist pregnant women suffering from GDM. At present, pregnant women are unaware of the importance of preventing GDM, and they possess a low level of self-management ability. Recently, mHealth technology has been used worldwide. Therefore, developing a mobile health app for GDM prevention could potentially help pregnant women reduce the risk of GDM. Objective: To design and develop a mobile application, evaluate its acceptance, and understand the users'using experience and suggestions, thus providing a valid tool to assist pregnant women at risk of GDM in enhancing their self-management ability and preventing GDM. Methods: An evidence-based GDM prevent app (Better pregnancy) was developed using user-centered design methods, following the health belief model, and incorporating GDM risk prediction. A convenient sampling method was employed from June to August 2022 to select 102 pregnant women at risk of GDM for the pilot study. After a week, the app's acceptability was evaluated using an application acceptance questionnaire, and we updated the app based on the feedback from the women. We used SPSS 26.0 for data analysis. Results: The application offers various functionalities, including GDM risk prediction, health management plan, behavior management, health information, personalized guidance and consultation, peer support, family support, and other functions. In total, 102 pregnant women consented to participate in the study, achieving a retention rate of 98%; however, 2% (n = 2) withdrew. The Better pregnancy app's average acceptability score is 4.07 out of 5. Additionally, participants offered several suggestions aimed at enhancing the application. Conclusions: The Better pregnancy app developed in this study can serve as an auxiliary management tool for the prevention of GDM, providing a foundation for subsequent randomized controlled trials.
引用
收藏
页数:14
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