ArticleBMC medical education2024
Global cross-sectional student survey on AI in medical, dental, and veterinary education and practice at 192 faculties.
Article in BMC medical education, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers, 3 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
52 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Reimagining writing assessment for the AI era: a systematic review on balancing AI support and authentic skill growth.Frontiers in psychology · 2026Pooled it
- The effectiveness of GAI-assisted teaching methods in medical education: a systematic review and meta-analysis.Frontiers in public health · 2026Pooled it
- Effectiveness of generative artificial intelligence-based teaching versus traditional teaching methods in medical education: a meta-analysis of randomized controlled trials.BMC medical education · 2025Pooled it
- Use, Concerns, and Perspectives on AI in Health Care Among French Health Professionals and Students: Web-Based Cross-Sectional Survey.JMIR medical education · 2026Article
- Effectiveness of an AI-augmented teacher feedback model in improving medical students' clinical documentation skills: a retrospective cohort study.BMC medical education · 2026Article
- Current Status of Generative Artificial Intelligence Utilization in Medical Education: A Cross-Sectional Survey of Medical Students and Faculty.JMA journal · 2026Article
- Knowledge, Attitudes, and Practices Related to AI in Learning and Research Among Medical Students in Vietnam: Cross-Sectional Study.JMIR formative research · 2026Article
- From Tradition to Future in Veterinary Public Health Education: Students' Attitudes, Anxiety and Experiences With AI-Supported Learning.Veterinary medicine and science · 2026Article
- AI integration into undergraduate health education streams- a multicenter study in Sri Lanka.BMC medical education · 2026Observational
- Medical students' attitudes toward socioscientific issues in female reproductive anatomy teaching: a cross-sectional study.BMC medical education · 2026Article
- How crucial is research philosophy in designing an AI study in medical education?BMC medical education · 2026Article
- AI Integration in Spanish Undergraduate Medical Education: National Cross-Sectional Study.JMIR medical education · 2026Article
- Knowledge, Attitude, and Perception of Medical Students Toward AI-Based Learning: A Cross-Sectional Study.Public health challenges · 2026Article
- The AI adoption paradox in Chinese medical education: a multi-institution cross-sectional study of usage patterns, critical literacy gaps, and adoption profiles among 3,194 undergraduate medical students.BMC medical education · 2026Article
- Moving beyond one-size-fits-all education approaches for artificial intelligence in healthcare.PLOS digital health · 2026Article
- Health Professional Students' Use of Generative Artificial Intelligence During Clinical Placements: Cross-Sectional Online Survey Study.JMIR medical education · 2026Article
- Adoption of generative AI chatbots among medical postgraduates at two universities in China: patterns, attitudes, and concerns.BMC medical education · 2026Article
- Nursing Students' Experiences With Artificial Intelligence: A Qualitative Study on Education, Clinical Practice, and Future Expectations.Journal of evaluation in clinical practice · 2026Article
- Psychiatry in transition: an assessment in the context of societal change.Annals of general psychiatry · 2026Article
- Artificial Intelligence in Medical Education: Transformative Potential, Current Applications, and Future Implications.JMIR medical education · 2026Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
backgroundThe successful integration of artificial intelligence (AI) in healthcare depends on the global perspectives of all stakeholders. This study aims to answer the research question: What are the attitudes of medical, dental, and veterinary students towards AI in education and practice, and what are the regional differences in these perceptions?
methodsAn anonymous online survey was developed based on a literature review and expert panel discussions. The survey assessed students' AI knowledge, attitudes towards AI in healthcare, current state of AI education, and preferences for AI teaching. It consisted of 16 multiple-choice items, eight demographic queries, and one free-field comment section. Medical, dental, and veterinary students from various countries were invited to participate via faculty newsletters and courses. The survey measured technological literacy, AI knowledge, current state of AI education, preferences for AI teaching, and attitudes towards AI in healthcare using Likert scales. Data were analyzed using descriptive statistics, Mann-Whitney U-test, Kruskal-Wallis test, and Dunn-Bonferroni post hoc test.
resultsThe survey included 4313 medical, 205 dentistry, and 78 veterinary students from 192 faculties and 48 countries. Most participants were from Europe (51.1%), followed by North/South America (23.3%) and Asia (21.3%). Students reported positive attitudes towards AI in healthcare (median: 4, IQR: 3-4) and a desire for more AI teaching (median: 4, IQR: 4-5). However, they had limited AI knowledge (median: 2, IQR: 2-2), lack of AI courses (76.3%), and felt unprepared to use AI in their careers (median: 2, IQR: 1-3). Subgroup analyses revealed significant differences between the Global North and South (r = 0.025 to 0.185, all P < .001) and across continents (r = 0.301 to 0.531, all P < .001), with generally small effect sizes.
conclusionsThis large-scale international survey highlights medical, dental, and veterinary students' positive perceptions of AI in healthcare, their strong desire for AI education, and the current lack of AI teaching in medical curricula worldwide. The study identifies a need for integrating AI education into medical curricula, considering regional differences in perceptions and educational needs.
trial registrationNot applicable (no clinical trial).
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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.