ArticleJMIR medical education2022
Readiness to Embrace Artificial Intelligence Among Medical Doctors and Students: Questionnaire-Based Study.
Article in JMIR medical education, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers, 2 of them syntheses that pooled it.
What it found
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Who cites it
53 citing papers in PubMed, 2 syntheses or guidelines pooled it, 107 citations in OpenAlex.
- Medical Students' Attitudes, Perceptions, and Self-Reported Familiarity With AI in Health Care: Systematic Review and Meta-Analysis.JMIR medical education · 2026Pooled it
- AI in Medical Questionnaires: Scoping ReviewJournal of medical Internet research · 2025Pooled it
- Self-Reported Knowledge, Attitudes, Perceptions, and Readiness Regarding AI Among Obstetrics and Gynecology Trainees: Cross-Sectional Study.JMIR formative research · 2026Article
- Value Configurations Associated with Artificial Intelligence Literacy Among Medical Students: Findings from NCA and fsQCA.Behavioral sciences (Basel, Switzerland) · 2026Article
- Saudi Medical Students' Perceptions and Attitudes of Integrating Generative Artificial Intelligence Integration in Medical Education: A Cross-Sectional Study.Health science reports · 2026Article
- Personality traits, technology affinity, and artificial intelligence readiness in medical students: a multinational cross-sectional study.BMC medical education · 2026Article
- Understanding Nurses' Intention to Use Artificial Intelligence Technologies in Their Clinical Practice: A Survey-Based Configurational Analysis.Journal of advanced nursing · 2026Article
- Health Professional Students' Use of Generative Artificial Intelligence During Clinical Placements: Cross-Sectional Online Survey Study.JMIR medical education · 2026Article
- Article
- Public Perceptions of AI in Medicine and Implications for Future Medical Education: Cross-Sectional Survey.JMIR formative research · 2026Article
- Artificial intelligence in blood donor management: A narrative review.Vox sanguinis · 2026Review
- 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 literacy and readiness in future health care professionals: a cross-sectional study.Croatian medical journal · 2026Article
- Questionnaires on Perceptions of Artificial Intelligence in Health Care Among Health Care Students: Cross-Cultural Translation Into French and Linguistic Validation.JMIR medical education · 2026Article
- Dental students' knowledge, perceptions, and educational needs regarding artificial intelligence: a multinational cross-sectional survey.BMC medical education · 2026Article
- The impact of risk perception on perceived benefits of generative artificial intelligence users-an empirical study based on university students.Frontiers in psychology · 2026Article
- Digital health competences and AI beliefs as conditions for the practice of evidence-based medicine: a study of prospective physicians in Canada.Medical education online · 2025Article
- Article
- Individual innovativeness levels and levels of medical artificial intelligence readiness among nursing students: a cross-sectional and correlational study.BMC medical education · 2025Article
- Perception of Medical Undergraduates on Artificial Intelligence in Medical Education: Qualitative Exploration.JMIR medical education · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSimilar to understanding how blood pressure is measured by a sphygmomanometer, physicians will soon have to understand how an artificial intelligence-based application has come to the conclusion that a patient has hypertension, diabetes, or cancer. Although there are an increasing number of use cases where artificial intelligence is or can be applied to improve medical outcomes, the extent to which medical doctors and students are ready to work and leverage this paradigm is unclear.
objectiveThis research aims to capture medical students' and doctors' level of familiarity toward artificial intelligence in medicine as well as their challenges, barriers, and potential risks linked to the democratization of this new paradigm.
methodsA web-based questionnaire comprising five dimensions-demographics, concepts and definitions, training and education, implementation, and risks-was systematically designed from a literature search. It was completed by 207 participants in total, of which 105 (50.7%) medical doctors and 102 (49.3%) medical students trained in all continents, with most of them in Europe, the Middle East, Asia, and North America.
resultsThe results revealed no significant difference in the familiarity of artificial intelligence between medical doctors and students (P=.91), except that medical students perceived artificial intelligence in medicine to lead to higher risks for patients and the field of medicine in general (P<.001). We also identified a rather low level of familiarity with artificial intelligence (medical students=2.11/5; medical doctors=2.06/5) as well as a low attendance to education or training. Only 2.9% (3/105) of medical doctors attended a course on artificial intelligence within the previous year, compared with 9.8% (10/102) of medical students. The complexity of the field of medicine was considered one of the biggest challenges (medical doctors=3.5/5; medical students=3.8/5), whereas the reduction of physicians' skills was the most important risk (medical doctors=3.3; medical students=3.6; P=.03).
conclusionsThe question is not whether artificial intelligence will be used in medicine, but when it will become a standard practice for optimizing health care. The low level of familiarity with artificial intelligence identified in this study calls for the implementation of specific education and training in medical schools and hospitals to ensure that medical professionals can leverage this new paradigm and improve health outcomes.
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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.