ArticleDigital health
Acceptability of an AI-enabled family module in a mobile app for enhanced diabetes management: Patient and family perspectives.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Artificial intelligence in chronic disease self-management: current applications and future directions.Frontiers in public health · 2025Review
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: To explore the acceptability of family support through an AI-enabled mobile app and identify preferences for its novel family module features among patients with type 2 diabetes (T2DM) and family members. Methods: Semi-structured interviews were conducted with patients with T2DM and family members. A mock wireframe of the FAMILY module was created to help participants visualize the module features. All interviews were audio-recorded and transcribed verbatim. Inductive thematic analysis using the constant-comparative method was performed to identify and interpret patterns within the data. Results: A total of 25 patients with T2DM and 25 family members participated in the study. Participants viewed the FAMILY module as a valuable tool for reinforcing patients' self-discipline. However, some patients expressed concerns about family involvement, particularly among those who preferred greater control and autonomy over their self-management plan. Family members also raised concerns about caregiving burden and feelings of self-blame if they were unable to provide adequate support. Regarding module features, participants appreciated algorithm-driven nudges and in-app interactions but emphasized the importance of controlling the frequency of nudges. Features such as collaborative goal setting, report cards, and AI-powered smart logging were found useful. However, family members expressed a need for more personalized in-app advice on patient data and medical terminology to better support patient's self-care. In-app family resources should be tailored to meet the needs of first-time caregivers to enhance the module's usability. Conclusion: The insights from this study will guide the development of the novel FAMILY module and inform targeted interventions aimed at mitigating risks, managing T2DM-related comorbidities, and enhancing self-care.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.