ArticleJournal of medical Internet research2025
Health Care Professionals' Concerns About Medical AI and Psychological Barriers and Strategies for Successful Implementation: Scoping Review.
Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 3 of them syntheses that pooled it.
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Who cites it
28 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Responsible artificial intelligence integration framework for psychiatric guidelines.The international journal of neuropsychopharmacology · 2026Guideline
- Adoption of artificial intelligence in primary health care: systematic synthesis of stakeholder perspectives.BMC primary care · 2026Pooled it
- Value of Machine Learning Models for Cell-Free DNA-Based Multi-Cancer Early Detection: A Systematic Review and Meta-Analysis.Technology in cancer research & treatmentPooled it
- Identifying factors influencing acceptance of artificial intelligence among general practitioners in Danish general practice: a cross-sectional web-based survey study.Scandinavian journal of primary health care · 2026Article
- Healthcare Providers' Perspectives on the Role of Artificial Intelligence in the Care of Patients with Inflammatory Bowel Disease: An International Survey.Digestive diseases and sciences · 2026Article
- Hospital Human Resource Managers' Perspectives on Organizational Readiness for Generative AI Skills: Qualitative Descriptive Study.JMIR medical informatics · 2026Article
- AI-Empowered Nuclear Medicine Education, Part 2: Practical AI Applications for Educators.Journal of nuclear medicine technology · 2026Article
- Integrating Participatory Social Innovation Into Requirements Engineering for AI Health Care Solutions: Case Study.Journal of medical Internet research · 2026Article
- Navigating the AI era in dietetics: a qualitative analysis of professional identity, ethical concerns, and future projections in Türkiye.BMC health services research · 2026Article
- Impact of a Practical, Hands-On, Continuing Professional Development Course About AI in Health Care Professions Education on the Perceptions and Behaviors of Health Care Educators: Qualitative Case Study.JMIR medical education · 2026Article
- The influence of AI literacy on fear of negative evaluation among students and researchers: a multisite cross-sectional study.BMC medical education · 2026Article
- Generative AI's Impact on the Mental Health of Medical Students: Scenario Analysis.JMIR medical education · 2026Article
- Sequencing AI Automation and Data Interoperability in Oncology Using a Scenario-Planning Framework Coupled With Discrete-Event Simulation: Proof-of-Concept Study.Journal of medical Internet research · 2026Article
- Cognitive differences and ethical concerns in artificial intelligence in healthcare: a comparative text mining study of public and healthcare professional discussions.BMC medical ethics · 2026Article
- Assessing Primary Care Physicians' Readiness for AI-Based Adaptive Learning: Perceptions, Barriers, and Learning Needs in Northern Saudi Arabia.Healthcare (Basel, Switzerland) · 2026Article
- Artificial intelligence self-efficacy and attitudes among nursing students: a multicenter network analysis of educational stratification.BMC medical education · 2026Article
- Artificial intelligence and ChatGPT literacy among surgical healthcare professionals: knowledge, attitudes, and perceived clinical utility.Frontiers in digital health · 2026Article
- Generative Artificial Intelligence in Healthcare: Automation Bias, Deskilling, and Cognitive Implications - A Systematic Review.Journal of healthcare leadership · 2026Review
- Mediating effect of technostress on the relationship between artificial intelligence literacy and attitude toward digital technology among health profession students: a structural equation modeling approach.Journal of Yeungnam medical science · 2026Article
- Artificial Intelligence perception and its influence on the Psychological Distress of Healthcare Professional.Pakistan journal of medical sciences · 2026Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe rapid progress in the development of artificial intelligence (AI) is having a substantial impact on health care (HC) delivery and the physician-patient interaction.
objectiveThis 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.
methodsThis 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.
resultsIn 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.
conclusionsThe 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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.