Accepted for/Published in: JMIR Formative Research
Date Submitted: Aug 26, 2025
Date Accepted: Jan 10, 2026
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Exploring patient perceptions of artificial intelligence (AI) in diabetes self-management: foundations for an AI-integrated shared decision-making model
ABSTRACT
Background:
Artificial intelligence (AI) offers new opportunities to support chronic disease self-management and expand shared decision-making (SDM) frameworks beyond the traditional patient-clinician dyad.
Objective:
This study explored patient perceptions of AI across key diabetes self-management tasks and examined task-specific preferences for AI versus healthcare provider (HCP) involvement. The findings aim to lay the groundwork for future models integrating AI into SDM processes.
Methods:
A cross-sectional online survey of adults with diabetes in New Zealand assessed preferences for AI or HCP support across seven diabetes self-management tasks. Participants rated perceived HCP involvement, perceived usefulness of AI, comfort with HCP use of AI, and their preference for AI versus HCP involvement for each task. Stepwise linear regression was used to examine predictors of AI preference for each task.
Results:
Participants (N=48) rated HCP involvement as moderate to low across most self-management tasks. In contrast, AI was rated as moderately useful, especially for data-driven tasks such as tracking and interpreting health information, though actual usage remained limited. HCPs were preferred for tasks involving clinical judgment and personal reflection. Perceived usefulness of AI was a significant predictor of preference for AI involvement in self-management. Notably, participants rated HCP involvement in personal reflection as low but still strongly preferred HCPs over AI for this domain. Collaboration between AI and HCPs was not viewed as a key factor influencing preferences.
Conclusions:
Patients demonstrate task-specific openness to AI involvement in diabetes management, particularly for structured, data-intensive activities. These findings lay a foundation for future development and evaluation of AI-integrated SDM models. A broader exploration of technology types, relationship dynamics, and collaborative decision-making will be essential as AI becomes increasingly embedded in chronic care management.
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.