Factors for Patient Trust and Acceptance of Medical Artificial Intelligence
In this survey study of patient trust in and choice of medical AI, AI performance, clinician presence, disclosure of representative data, and systemic governance were associated with increased respondent trust in and preference for clinical encounters. These findings suggest that ensuring resource-appropriate combinations of these tools is an important step in helping AI achieve its transformative potential for the health system.
Authors
- Kayte Spector-Bagdady
- Rina Zhang
- Ana Bracic (ORCID: https://orcid.org/0000-0002-1738-4210)
- W. Nicholson Price
- Cornelius A. James
- Sophie Towle
Institutions
- University of Copenhagen (DK)
- University of Michigan (US)
- Michigan State University (US)
Publication Details
- Journal
- JAMA Network Open
- Published
- 2026-03-05
- DOI
- https://doi.org/10.1001/jamanetworkopen.2026.0815
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- University of Michigan
- Novo Nordisk
- Novo Nordisk Fonden
- Michigan Institute for Clinical and Health Research
- National Center for Advancing Translational Sciences