Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Aug 11, 2023
Open Peer Review Period: Aug 11, 2023 - Oct 6, 2023
Date Accepted: Oct 7, 2024
(closed for review but you can still tweet)
Why AI Monitoring Faces Resistance and What Healthcare Organizations Can Do About It: An Emotion-Based Perspective
ABSTRACT
Continuous monitoring of patients' health, facilitated by Artificial Intelligence (AI), has been shown to enhance the quality of health care. However, health care organizations often attribute the rejection of AI monitoring to the ‘liability of newness’ and assume that the decision to reject AI monitoring is rational. This study challenges such assumptions and reveals that rather than being driven by cognitive assessments of the costs and benefits of the technology, the rejection of AI monitoring is often influenced by the emotional experiences of decision makers. Our findings have important implications for health care organizations. In this viewpoint, we offer recommendations that help reduce the rejection of AI monitoring. First, health care organizations need to be cognizant of anxiety that may result from AI monitoring; second, they need to communicate the risks associated with rejection to decision makers; third, they need to give decision makers a sense of control over the functionalities AI monitoring systems; and fourth, they need to address both the patients’ and their surrogate decision makers’ anxieties.
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.