Understanding device integrations within diabetes apps: Mixed methods analysis of app features and user reviews.

Turner, Jessica and Stawarz, Katarzyna ORCID: https://orcid.org/0000-0001-9021-0615 2025. Understanding device integrations within diabetes apps: Mixed methods analysis of app features and user reviews. JMIR Diabetes 10 , e62926. 10.2196/62926

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Abstract

Diabetes management involves a large degree of data collection and self-care in order to accurately administer insulin. Several mobile apps are available that allow people to track and record various factors that influence their blood sugar levels. Existing diabetes apps offer features that enable integrations with various devices that streamline diabetes management, such as continuous glucose monitors, insulin pumps, or regular activity trackers. While this reduces the tracking burden on the users, the research highlighted several issues with diabetes apps, including issues with reliability and trustworthiness. As pumps and continuous glucose monitors are safety-critical systems-where issues can result in serious harm or fatalities-it is important to understand what issues and vulnerabilities could be introduced by relying on popular diabetes apps as an interface for interacting with such devices. As there is a lack of research examining in detail the integrations and potential suitability of apps as part of a wider self-management ecosystem, our goal was 2-fold. First, we aimed to understand the current landscape of device integrations within diabetes apps and how well they meet users' needs. Second, we identified the key issues users of the most popular apps face currently and what features are the source of these issues. Through searches in Android and iPhone app stores, we systematically identified 21 diabetes apps that offer integrations. We conducted a detailed analysis of 602 user reviews. For each review, we recorded its sentiment, features and issues, and additional contextual information provided by the review writers. We used descriptive statistics to analyze the features and issues. We also analyzed the reviews thematically to identify additional trends related to the context of use and the consequences of issues reported by the users. The reviews focused on key features that users found the most important, including device integrations (n=259, 43%), tracking (n=194, 32.2%), data logging (n=86, 14.3%), and notifications (n=70, 11.6%). We found that 327 (54.3%) of the reviews were negative versus 187 (31.1%) positive and 88 (14.6%) neutral or mixed, and the majority of reviews (n=378, 62.8%) mentioned issues. The biggest issues related to device integrations included inability to connect with external devices (n=95, 25.1%), inability to store, manage, or access data (n=49, 22%), unreliable notifications and alerts (n=35, 9.2%), issues caused by or related to software updates (n=31, 8.5%), hardware issues (n=24, 6.4%), and issues with accessing the app, related services, or associated hardware (n=12, 3.2%). Apps for diabetes management are a useful part of self-care only if they are reliable and trustworthy, reduce burden, and increase health benefits. Our results provide a useful overview of desired features for diabetes apps alongside key issues for existing integrations and highlight the future challenges for artificial pancreas system development. [Abstract copyright: © Jessica Turner, Katarzyna Stawarz. Originally published in JMIR Diabetes (https://diabetes.jmir.org).]

Item Type:	Article
Date Type:	Published Online
Status:	Published
Schools:	Schools > Computer Science & Informatics
Publisher:	JMIR Publications
Date of First Compliant Deposit:	9 June 2025
Date of Acceptance:	20 March 2025
Last Modified:	09 Jun 2025 13:15
URI:	https://orca.cardiff.ac.uk/id/eprint/178915

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