Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Sep 28, 2024
Date Accepted: Feb 25, 2025
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
A scoping review of fear, resilience, reluctance, scepticism and anxiety towards medical AI among medical professionals and suggestions for successful implementation of AI into medical practice
ABSTRACT
Introduction: The rapid progress in the development of artificial intelligence (AI) is having a substantial impact on healthcare (HC) delivery and the doctor-patient interaction. This scoping review seeks to offer a thorough analysis of the current status of integrating AI into medical practice and the apprehensions expressed by healthcare professionals (HPs) over its application.
Methods:
This scoping review utilized the PRISMA-ScR method to examine papers that investigate the apprehensions of HPs about medical AI. Following the application of inclusion and exclusion criteria, a total of 32 studies were selected for the final analysis. Our objective was to develop an attitude measure that accurately captures the unfavorable attitudes of HPs towards medical AI. We achieved this by selecting attitudes and then ranking them on a scale that represents the degree of aversion, ranging from mild skepticism to intense fear. The ultimate depiction of the scale is as follows: Skepticism, reluctance, anxiety, resistance, and fear.
Results:
Three themes were identified through the process of thematic analysis. National surveys performed among HPs aim to comprehensively analyze the current emotions, worries, and attitudes regarding the integration of AI in the medical industry. Research on technostress primarily focuses on the psychological dimensions of adopting AI, examining the emotional reactions, fears, and difficulties experienced by human participants when they encounter AI-powered equipment. The high-level perspective category includes studies that take a broad and comprehensive approach to evaluating overarching themes, trends, and implications related to the integration of AI technology in HC. Discussion: We have discovered a total of 15 concerns, which we have classified into 2 distinct groups. We have designated these two classifications as intrinsic and extrinsic. The initial group focuses on HP's inherent professional identity, encompassing their tasks and capacities. Conversely, the second group pertains to their patients and the influence of AI on patient care. Next, we examine the shared themes and made suggestions to potentially tackle the discovered problems. Ultimately, we analyze the results in relation to the attitude scale, assessing the degree to which each attitude is portrayed.
Conclusions:
The solution to addressing resistance towards medical AI appears to be centered around comprehensive education, the implementation of suitable legislation, and the delineation of roles. Due to the current prominence and extensive research on regulation, we suggest that future studies should focus on education.
Citation
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Copyright
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