Document Type

Article

Publication Date

2025

DOI

10.2196/51785

Publication Title

Journal of Medical Internet Research

Volume

27

Pages

e51785

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 to 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.

Rights

© Karl Werder, Lan Cao, Eun Hee Park, Balasubramaniam Ramesh.

Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 31.01.2025. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research (ISSN 1438-8871), is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.

ORCID

0000-0002-3860-7639 (Cao), 0000-0002-9831-8951 (Park)

Original Publication Citation

Werder, K., Cao, L., Park, E. H., & Ramesh, B. (2025). Why AI monitoring faces resistance and what healthcare organizations can do about it: An emotion-based perspective. Journal of Medical Internet Research, 27, 1-8, Article e51785. https://doi.org/10.2196/51785

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