Patient Perceptions of Artificial Intelligence in Diabetes Self-Management: Cross-Sectional Survey Study

Area of Science:

• Digital Health
• Artificial Intelligence in Healthcare
• Chronic Disease Management

Background:

• Artificial intelligence (AI) offers potential in diabetes management for data interpretation, clinical decisions, and patient engagement.
• Limited evidence exists on patient perceptions of AI's role in shared decision-making (SDM) and the patient-provider relationship.

Purpose of the Study:

• Explore patient perceptions of AI usefulness in diabetes self-management tasks.
• Examine preferences for AI versus healthcare provider (HCP) involvement.
• Identify predictors of AI preference and propose an AI-integrated SDM model.

Main Methods:

• Cross-sectional online survey of adults with diabetes in New Zealand.
• Participants rated AI usefulness and preferences for AI vs. HCP involvement across 7 self-management tasks.
• Regression analyses identified predictors of AI preference.

Main Results:

• AI perceived as moderately useful, especially for data tracking and interpretation.
• Patients preferred HCP involvement for treatment decision-making and personal reflection.
• Perceived AI usefulness predicted AI preference for data collection, interpretation, treatment decisions, and lifestyle management.

Conclusions:

• Patients show task-specific acceptance of AI in diabetes management, favoring AI for data-intensive tasks.
• Findings support developing AI-integrated SDM models for chronic care.
• Further research on technology, relationships, and collaborative decision-making is crucial.