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Cited by 57Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AIElectronic Health Records Systems

Health Care Professionals’ Concerns About Medical AI and Psychological Barriers and Strategies for Successful Implementation: Scoping Review

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Arvai, Nora, Katonai, Gellért, Mesko, Bertalan·2025·Journal of Medical Internet Research
DOI 10.2196/66986PMC PMC12059500

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Abstract

Background: The rapid progress in the development of artificial intelligence (AI) is having a substantial impact on health care (HC) delivery and the physician-patient interaction. Objective: This scoping review aims to offer a thorough analysis of the current status of integrating AI into medical practice as well as the apprehensions expressed by HC professionals (HCPs) over its application. Methods: This scoping review used the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines to examine articles that investigated the apprehensions of HCPs about medical AI. Following the application of inclusion and exclusion criteria, 32 of an initial 217 studies (14.7%) were selected for the final analysis. We aimed to develop an attitude range that accurately captured the unfavorable emotions of HCPs toward medical AI. We achieved this by selecting attitudes and ranking them on a scale that represented the degree of aversion, ranging from mild skepticism to intense fear. The ultimate depiction of the scale was as follows: skepticism, reluctance, anxiety, resistance, and fear. Results: In total, 3 themes were identified through the process of thematic analysis. National surveys performed among HCPs aimed to comprehensively analyze their current emotions, worries, and attitudes regarding the integration of AI in the medical industry. Research on technostress primarily focused on the psychological dimensions of adopting AI, examining the emotional reactions, fears, and difficulties experienced by HCPs when they encountered AI-powered technology. The high-level perspective category included studies that took a broad and comprehensive approach to evaluating overarching themes, trends, and implications related to the integration of AI technology in HC. We discovered 15 sources of attitudes, which we classified into 2 distinct groups: intrinsic and extrinsic. The intrinsic group focused on HCPs’ inherent professional identity, encompassing their tasks and capacities. Conversely, the extrinsic group pertained to their patients and the influence of AI on patient care. Next, we examined the shared themes and made suggestions to potentially tackle the problems discovered. Ultimately, we analyzed the results in relation to the attitude scale, assessing the degree to which each attitude was portrayed. Conclusions: The solution to addressing resistance toward medical AI appears to be centered on comprehensive education, the implementation of suitable legislation, and the delineation of roles. Addressing these issues may foster acceptance and optimize AI integration, enhancing HC delivery while maintaining ethical standards. Due to the current prominence and extensive research on regulation, we suggest that further research could be dedicated to education.

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Cited by

Sorted by citations

Authors
Arvai, N., Katonai, G., & Mesko, B.
Affiliations
Semmelweis University (HU)
ORCID
Venue
Journal of Medical Internet Research
Publisher
JMIR Publications Inc.
Published
2025-04-23
Volume
27
Pages
e66986
ISSN
1438-8871 (ISSN-L)
DOI
10.2196/66986
PMC
PMC12059500
OpenAlex
W4407922620
Cited by
57
References
13
Citations by year
2026: 48 · 2025: 9
FWCI
3.37
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Journal of Medical Internet Research (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
  • Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
Keywords
artificial intelligence in healthcare, clinician attitudes, technostress, resistance to AI adoption, psychological barriers, physician-patient interaction, AI implementation strategy, professional identity, AI regulation, artificial intelligence in education
MeSH terms
Artificial Intelligence, Attitude of Health Personnel, Health Personnel, Humans

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