ArticleJournal of medical Internet research2025
Physicians' Attitudes Toward Artificial Intelligence in Medicine: Mixed Methods Survey and Interview Study.
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 39 papers, 1 of them a synthesis that pooled it.
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Who cites it
39 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Evidence on artificial intelligence-assisted clinical documentation and healthcare workers' emotional wellbeing at work: a scoping review.Frontiers in psychology · 2026Pooled it
- Beyond AI Literacy: Understanding Health Care Workforce AI Enablement in the Generative AI Era.Journal of medical Internet research · 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
- Palliative Care Physicians' Perceptions about Using Artificial Intelligence for Prognostication.Journal of pain and symptom management · 2026Article
- Current Status and Associated Factors of Technophobia Toward Digital Health Technologies Among Older Patients With Stroke: Mixed Methods Study.Journal of medical Internet research · 2026Article
- Integrating Artificial Intelligence into Orthopedic Practice: Modeling Attitudes and Intentions to Use AI.Healthcare (Basel, Switzerland) · 2026Article
- When Do Physicians Trust AI? The Role of Clinical Context in Decision Support: SMART vignette study.Research square · 2026Article
- Between Awareness and Readiness: Perceptions of Artificial Intelligence Among Indonesian Mental Health Professionals.Behavioral sciences (Basel, Switzerland) · 2026Article
- Role-Differentiated AI Competencies and Curriculum Implications for Health Professions Education: Qualitative Study.JMIR medical education · 2026Article
- Clinician Perceptions of AI in Care: Cross-Sectional Survey.JMIR formative research · 2026Article
- Perception and challenges of artificial intelligence (AI) in Emergency Medicine: A multi-country study in Sub-Saharan Africa.African journal of emergency medicine : Revue africaine de la medecine d'urgence · 2026Article
- Artificial intelligence in clinical genetics: Current practice and attitudes among the clinical genetics workforce.Genetics in medicine : official journal of the American College of Medical Genetics · 2026Article
- Article
- Digital Health Competence and Attitudes Toward AI Among Health Care Professionals: Convergent Mixed Methods Study.Journal of medical Internet research · 2026Article
- Use of Computer Vision with Conventional Video Recordings of Gait in Older Adults: A Scoping Review.Healthcare (Basel, Switzerland) · 2026Review
- Artificial Intelligence Legislation Literacy, Governance Readiness, and Adoption Intentions in Romanian Healthcare: A Cross-Sectional Study.Healthcare (Basel, Switzerland) · 2026Article
- Receptiveness of physicians towards artificial intelligence-driven drug prescription: a nationwide survey.npj health systems · 2026Article
- Dual dimensions of artificial intelligence use among medical academia: related knowledge, attitudes and ethical concerns, a national survey, 2025.Scientific reports · 2026Article
- Assessing pediatricians' readiness for artificial intelligence: a cross-sectional study in Istanbul, Türki̇ye.BMC pediatrics · 2026Article
- Artificial intelligence in rheumatology and paediatric rheumatology: insights from an international survey by EMEUNET.EULAR rheumatology open · 2026Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundArtificial intelligence (AI) has the potential to transform clinical practice and diagnostics. Amid workforce shortages, AI-based applications assist in decision-making, patient monitoring, and administrative tasks. However, despite enthusiasm, integration into clinical practice remains limited because of concerns about usability, ethical implications, and physicians' acceptance. Understanding physicians' attitudes and engaging them in AI development may foster acceptance and adoption.
objectiveThis study aimed to comprehensively assess physicians' attitudes toward AI in medicine.
methodsWe conducted a mixed methods study combining a web-based survey and qualitative interviews. The survey explored physicians' perspectives on the advantages and disadvantages of AI, its role in decision-making, and impact on physician-patient communication. Attitudes were measured using a 5-point Likert scale, covering cognitive and affective dimensions. An exploratory factor analysis (EFA) identified underlying attitudinal factors, while the Mann-Whitney U and the Kruskal-Wallis tests examined differences in attitudes based on physicians' age, discipline, AI familiarity, and other variables. Overall, 13 physicians, independent of the survey sample, participated in semistructured interviews, which were analyzed using inductive coding and thematic analysis.
resultsThe survey yielded 498 responses. EFA revealed two factors: (1) AI enthusiasm and acceptance (Cronbach α=0.83) and (2) AI skepticism and apprehension (Cronbach α=0.77). Physicians reported high AI enthusiasm (median 4, IQR 3.57-4.29) and lower skepticism (median 3.62, IQR 3.20-4.20; reverse coded, with higher scores indicating reduced skepticism). Greater AI familiarity, use in daily life or professionally, and involvement in research were strongly associated with greater enthusiasm and lower skepticism. Physicians involved in AI-related research reported significantly higher enthusiasm (mean rank: AI research=111.52; no AI research=54.32; P<.001) and lower skepticism (mean rank: AI research=108.27; no AI research=70.45; P=.01). Those using AI professionally or intending to do so similarly expressed high enthusiasm (mean rank: professional use=253.88; no use=196.17; P=.001) and lower skepticism (mean rank: plan to use=275.93; no use=218.86; P=.001). Greater familiarity with AI tools was also strongly associated with higher enthusiasm (mean rank: very familiar=323.55; not familiar=169.86; P<.001) and lower skepticism (mean rank: very familiar=296.90; not familiar=186.23; P=.008). Chief physicians (mean rank 277.32) were significantly less skeptical than residents (mean rank 210.60; P=.01); however, age and discipline did not influence attitudes. The qualitative analysis identified six themes shaping physicians' attitudes: (1) status quo, (2) AI dependency and negligence, (3) role changes and needs, (4) AI transparency and decision-making, (5) the physician-patient relationship, and (6) a framework for responsible AI integration. These findings led to several key propositions considered critical for AI adoption.
conclusionsAI in medicine is viewed positively, with attitudes shaped more by experience and engagement than by demographic factors. While concerns persist, they diminish with increased familiarity and professional use. These findings highlight the need for targeted education, hands-on training, and standardized implementation strategies to enhance AI engagement and facilitate adoption.
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