ArticleBMC medical education2025
Medical students and ChatGPT: analyzing attitudes, practices, and academic perceptions.
Article in BMC medical education, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 2 of them syntheses that pooled it.
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Who cites it
31 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Medical Students' Attitudes, Perceptions, and Self-Reported Familiarity With AI in Health Care: Systematic Review and Meta-Analysis.JMIR medical education · 2026Pooled it
- The impact of generative artificial intelligence tools on assessment equity for non-native English-speaking medical students: a systematic review.BMC medical education · 2026Pooled it
- Integrating large language models into prostate cancer training: evidence from comparative benchmarking and a pilot randomized trial.BMC medical education · 2026Trial
- Generative Artificial Intelligence Use and Learning Engagement Among Medical Undergraduates: Statistical Indirect and Configurational Associations Involving Basic Psychological Need Satisfaction.Behavioral sciences (Basel, Switzerland) · 2026Article
- Artificial intelligence in reproductive medicine and education: current evidence, challenges, and future directions.Journal of assisted reproduction and genetics · 2026Review
- Measuring health professional students' willingness to use AI chatbots in learning: A fuzzy-set qualitative comparative analysis.Anatomical sciences education · 2026Article
- Current Status of Generative Artificial Intelligence Utilization in Medical Education: A Cross-Sectional Survey of Medical Students and Faculty.JMA journal · 2026Article
- From hype to reality: the feasibility, dilemmas, and solutions of Gen AI in medical education from students' perspectives.BMC medical education · 2026Article
- Principles for medical students' responsible use of generative AI: a student-partnered Delphi study.BMC medical ethics · 2026Article
- Deciphering AI-chatbots utilization in clinical practice, research and education among Chinese medical students in generative AI era: a cross-sectional study.BMC medical education · 2026Article
- AI in the Classroom: Observing Preclinical Students' Use of ChatGPT During Case-Based Learning at a UK Medical School.The clinical teacher · 2026Article
- Adoption of generative AI chatbots among medical postgraduates at two universities in China: patterns, attitudes, and concerns.BMC medical education · 2026Article
- Article
- Utilization of AI Among Medical Students and Development of AI Education Platforms in Medical Institutions: Cross-Sectional Study.JMIR human factors · 2026Article
- Nursing students' experiences with using generative artificial intelligence: a descriptive qualitative study.Frontiers in medicine · 2026Article
- An Alternative Approach in Anatomy Education: Design of a Learning Environment Based on Artificial Intelligence-Supported Virtual Manipulatives and Investigation of Its Effectiveness.Clinical anatomy (New York, N.Y.) · 2026Article
- Use and Perceptions of Generative Artificial Intelligence Tools Among First-Year Medical Students: A Cross-Sectional Survey.Advances in medical education and practice · 2026Article
- Comprehensive Evaluation of Large Language Models on Four Core Medical School Courses: A Cross-Sectional Comparative Study.Advances in medical education and practice · 2026Article
- Awareness, attitudes, and utilization of large language models among healthcare students in Saudi Arabia: a cross-sectional analysis.Frontiers in medicine · 2026Article
- Causal Inference, Statistical Assumptions, and Natural-Language-Processing Artefacts in Evaluating Medical Students' Use of Generative Artificial Intelligence [Letter].Advances in medical education and practice · 2026Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundChatGPT, a chatbot launched by OpenAI in November 2022, has generated both excitement and concern within the healthcare education, research, and practice communities. This study aimed to explore the knowledge, perceptions, attitudes, and practices of undergraduate medical students regarding the use of ChatGPT and similar chatbots in their academic work.
methodsAn anonymous, structured questionnaire was developed using Google Forms and administered to medical students as part of a cross-sectional study. The survey targeted undergraduate medical students from four governorates in Egypt. The questionnaire link was distributed through social media platforms, including Facebook and WhatsApp. The survey comprised four sections: socio-demographic characteristics, perceptions, attitudes, and practices.
resultsThe survey achieved a response rate of 96%, with 614 out of 640 approached students participating. Prior to the study, most respondents (78.5%) had personal experience using it. Overall, respondents demonstrated positive perceptions, attitudes, and practices toward ChatGPT, with mean scores exceeding 3 for all three variables: 3.99 ± 0.60 for perceptions, 3.01 ± 0.46 for attitudes, and 3.55 ± 0.55 for practices. In general, the students exhibited a high degree of trust in the model, with approximately half trusting the accuracy and reliability of the information provided by ChatGPT. However, more than two-thirds expressed apprehension about its potential misuse in medical education, and around 60% were concerned about the accuracy of information ChatGPT might generate on complex medical topics.
conclusionsMedical students show strong interest and trust in using ChatGPT and similar chatbots for academic purposes but have concerns about the reliability of the information and potential misuse in medical education. The use of AI tools should follow ethical guidelines set by academic institutions, with regular updates to keep pace with technological progress. Future research should focus on the impact of AI on education and personal development, especially among young people.
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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.