Why AI Monitoring Faces Resistance and What Healthcare Organizations Can Do About It: An Emotion-Based Perspective
- ,
- Lan Cao,
- Eun Hee Park,
- Balasubramaniam Ramesh
- ,
- Old Dominion University,
- Georgia State University
Research Output:
Journal Article or Conference Article in Journal
Journal article
Peer-reviewOpen access
Publication Information
Output type
Research Output:
Journal Article or Conference Article in Journal
Journal article
Peer-reviewOriginal language
EnglishArticle number
e51785Journal (Volume, Issue Number)
Journal of Medical Internet Research (Volume 27, Issue 1)Publication milestones
- Published - 31/01/2025
Publication status
Published - 31/01/2025
ISSN
1438-8871Publication IDs
- Scopus: 85216930654
Abstract
Continuous monitoring of patients' health facilitated by Artificial Intelligence (AI) has enhanced the quality of health care, that is, the ability to access effective care. However, AI monitoring often encounters resistance in adoption by decision makers. Healthcare organizations frequently assume that the resistance stems from patients’ rational evaluation of the technology's costs and benefits. Recent research challenges this assumption and suggests that the resistance to AI monitoring is influenced by the emotional experiences of patients and their surrogate decision makers. We develop a framework from an emotional perspective, provide important implications for healthcare organizations, and offer recommendations to help reduce resistance to AI monitoring.
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