JMIR Publications

ABSTRACT

Background:

The use of mobile health apps (mHealth apps) can assist with the management of gestational diabetes. Although a number of studies have demonstrated their efficacy in improving maternal–foetal outcomes, opinions differ regarding their usability and overall quality. Poorly designed apps, with ill-conceived features or inappropriate content, may pose a threat to patient safety. Nevertheless, very few studies provide in-depth evaluations of app-design quality, and the diversity of features and techniques employed remains insufficiently explored.

Objective:

To evaluate the quality of commercially available mHealth apps for gestational diabetes, in terms of app features and content tailored specifically to the GDM population, as well as general functionality which affects the use of apps.

Methods:

This systematic evaluation was guided by the TECH framework and the PRISMA 2020 checklist. Searches were conducted on the Apple Store and Google Play (June 2024). Apps were screened by name, description, and full navigation to identify inclusions. The quality and content of the apps were evaluated using the MARS (Mobile App Rating Scale) and IMS (IMS Institute for Healthcare Informatics Functionality Score). App features and techniques were extracted and evaluated based on ABACUS (App Behavior Change Scale), NICE (National Institute for Health and Care Excellence) 2015 guidelines and previous studies.

Results:

The search identified 23 commercially available apps suitable for gestational diabetes management in the UK’s major app stores. The evaluation gave information on app characteristics, and evaluated apps using GDM-Adapted Features and Techniques (32 items) and general functionality (13 items). On average, the apps applied 17.95±7.31 of all 45 items, with 10.82±5.3 for GDM-Adapted Features and Techniques, and 7.13±2.58 for general functionality evaluation. This study suggested that education and data management features were predominantly employed but addressed in a basic manner. Apps tended to provide essential educational information about the meaning of GDM diagnosis and healthy food choices, and allow blood glucose data entry. The techniques usually included text and manual operation, which were the most widely used in delivering information and assisting self-monitoring.

Conclusions:

The study suggests that while basic educational content and blood glucose data recording are widely adopted in mHealth apps, there remain opportunities to enhance advanced features, such as the use of AI and automated features, to actively assist women’s behaviour changes. Additionally, insufficient emphasis on pregnancy-relevant information and progression highlights the need for future improvements in mHealth app development for supporting women with gestational diabetes.