Principles and Practices of Community Engagement in AI for Population Health: Formative Qualitative Study of the AI for Diabetes Prediction and Prevention Project
Our study offers useful insights for community-focused AI deployment that centers the values of patients and communities. The identified principles can guide meaningful engagement on the use of AI in health systems, while future research can operationalize the conceptual framework.
Authors
- Remziye Zaim (ORCID: https://orcid.org/0000-0002-1796-5592)
- Ijeoma Uchenna Itanyi (ORCID: https://orcid.org/0000-0002-4958-6319)
- Kathy Kornas (ORCID: https://orcid.org/0000-0002-5832-7335)
- Victoria Chui (ORCID: https://orcid.org/0000-0002-6126-1779)
- Laura C. Rosella (ORCID: https://orcid.org/0000-0003-4867-869X)
- Ibukun‐Oluwa Omolade Abejirinde (ORCID: https://orcid.org/0000-0003-0139-0541)
- Lorraine Lucille Lipscombe (ORCID: https://orcid.org/0000-0001-7412-7993)
- James Shaw (ORCID: https://orcid.org/0000-0002-9522-0756)
- Shion Guha (ORCID: https://orcid.org/0000-0003-0073-2378)
Institutions
- University of Toronto (CA)
- Trillium Health Centre (CA)
- Women's College Hospital (CA)
- Public Health Ontario (CA)
- Institute for Clinical Evaluative Sciences (CA)
Publication Details
- Journal
- Journal of Participatory Medicine
- Published
- 2025-08-18
- DOI
- https://doi.org/10.2196/69497
- Citations
- 3
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 1.96