ArticleHealthcare (Basel, Switzerland)2023
Clinicians' Perceptions of Artificial Intelligence: Focus on Workload, Risk, Trust, Clinical Decision Making, and Clinical Integration.
Article in Healthcare (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers, 2 of them syntheses that pooled it.
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Who cites it
46 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Artificial intelligence in headache medicine: between automation and the doctor-patient relationship. A systematic review.The journal of headache and pain · 2025Pooled 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
- Integrating Artificial Intelligence into Orthopedic Practice: Modeling Attitudes and Intentions to Use AI.Healthcare (Basel, Switzerland) · 2026Article
- Attitudes Toward Large Language Models in Health Care and Preferences for Their Adoption and Oversight Among Health Care Professionals: Cross-Sectional Survey.Journal of medical Internet research · 2026Article
- Machine learning in mitral valve repair: promise, precision, and the challenge of clinical translation.Journal of thoracic disease · 2026Article
- Exploring the Role of Large Language Models in Primary Care: Qualitative Study of Physicians in the United States and the Netherlands.JMIR medical informatics · 2026Article
- Determinants of AI Adoption in Saudi Arabian Healthcare Institutions.Healthcare (Basel, Switzerland) · 2026Article
- Constructs Influencing Patient Perceptions of Use of AI in Medical Imaging Analysis: Systematic Review.Interactive journal of medical research · 2026Review
- Alignment Between Cardiologists and AI-Driven Diagnostic Systems: Mixed Methods Study.Journal of medical Internet research · 2026Article
- Artificial intelligence and person-centred practice: a critical reflection.NPJ digital medicine · 2026Review
- Article
- Evaluating Large Language Models for Transparent Quality-of-Care Measurement in Children with ADHD.medRxiv : the preprint server for health sciences · 2026Article
- Patient perspectives about deployment of artificial intelligence decision support tools in a safety-net healthcare system.JAMIA open · 2026Article
- Review
- Patient Perspectives on AI-Powered Medical Robots in Breast and Prostate Cancer Care: Qualitative Study.JMIR cancer · 2026Article
- Association between artificial intelligence literacy and empathic behavior among nursing interns: adjustment for moral distress and moral resilience.Frontiers in medicine · 2026Article
- Physicians' attitudes and perceptions toward the integration of artificial intelligence into pediatric hematology-oncology in Saudi Arabia.Frontiers in medicine · 2026Article
- Perceptions of Artificial Intelligence in Medical Documentation: A Cross-Sectional Study of Healthcare Professionals.Cureus · 2025Article
- Artificial Intelligence for the Diagnosis and Management of Cancers: Potentials and Challenges.MedComm · 2025Review
- Bridging generative AI and healthcare practice: insights from the GenAI Health Hackathon at Hospital Clínic de Barcelona.BMJ health & care informatics · 2025Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) offers the potential to revolutionize healthcare, from improving diagnoses to patient safety. However, many healthcare practitioners are hesitant to adopt AI technologies fully. To understand why, this research explored clinicians' views on AI, especially their level of trust, their concerns about potential risks, and how they believe AI might affect their day-to-day workload. We surveyed 265 healthcare professionals from various specialties in the U.S. The survey aimed to understand their perceptions and any concerns they might have about AI in their clinical practice. We further examined how these perceptions might align with three hypothetical approaches to integrating AI into healthcare: no integration, sequential (step-by-step) integration, and parallel (side-by-side with current practices) integration. The results reveal that clinicians who view AI as a workload reducer are more inclined to trust it and are more likely to use it in clinical decision making. However, those perceiving higher risks with AI are less inclined to adopt it in decision making. While the role of clinical experience was found to be statistically insignificant in influencing trust in AI and AI-driven decision making, further research might explore other potential moderating variables, such as technical aptitude, previous exposure to AI, or the specific medical specialty of the clinician. By evaluating three hypothetical scenarios of AI integration in healthcare, our study elucidates the potential pitfalls of sequential AI integration and the comparative advantages of parallel integration. In conclusion, this study underscores the necessity of strategic AI integration into healthcare. AI should be perceived as a supportive tool rather than an intrusive entity, augmenting the clinicians' skills and facilitating their workflow rather than disrupting it. As we move towards an increasingly digitized future in healthcare, comprehending the among AI technology, clinician perception, trust, and decision making is fundamental.
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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.