ArticleBMC medical education2025
Status and perceptions of ChatGPT utilization among medical students: a survey-based study.
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 26 papers, 1 of them a synthesis that pooled it.
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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
26 citing papers in PubMed, 1 synthesis or guideline 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
- Integrating large language models into prostate cancer training: evidence from comparative benchmarking and a pilot randomized trial.BMC medical education · 2026Trial
- Artificial intelligence in reproductive medicine and education: current evidence, challenges, and future directions.Journal of assisted reproduction and genetics · 2026Review
- Generative AI in medicine: use and acceptance among professionals in orthopedics and traumatology: a survey-based analysis in Germany.Scientific reports · 2026Article
- AI Tool Use Among Osteopathic Medical Students: Pilot Digital Diary Study.JMIR formative research · 2026Observational
- Is artificial intelligence getting better at anatomy? A two-year review of ChatGPT's free public versions.Anatomical sciences education · 2026Article
- Performance of multimodal large language models on image-based surgical anatomy, anatomical pathology, and radiology questions.Anatomical sciences education · 2026Article
- Clinical Evaluation of an AI-Assisted Decision Support System for General Anesthesia Management Based on Data From 6 Centers: Comparative Study.Journal of medical Internet research · 2026Article
- Medical students' attitudes, usage patterns, and associated factors with DeepSeek adoption in education: a cross-sectional study in China.BMC medical education · 2026Article
- Principles for medical students' responsible use of generative AI: a student-partnered Delphi study.BMC medical ethics · 2026Article
- Acceptance and use of GenAI among medical and health sciences students in Saudi Arabia: an extended TAM study.BMC medical education · 2026Article
- The role of AI-mediated learning contexts in the personality-self-directed learning relationship among Chinese medical undergraduates: a cross-sectional study.BMC medical education · 2026Article
- Awareness and knowledge gaps about pediatric rare disease among anesthesia practitioners in China: a survey-based study.BMC pediatrics · 2026Article
- The application of large language models in orthopedic postgraduate education: potentials, challenges, and future prospects.Journal of orthopaedic surgery and research · 2026Review
- Article
- Adoption of generative AI chatbots among medical postgraduates at two universities in China: patterns, attitudes, and concerns.BMC medical education · 2026Article
- Perceptions and Attitudes of Medical Students Toward the Integration of Large Language Models in Medical Education: Cross-Sectional Survey in China.JMIR medical education · 2026Article
- Assessment of ChatGPT-5 as an Artificial Intelligence Tool for Exploring Emerging Dimensions of Clinical Simulation: A Proof-of-concept Study.Journal of medical systems · 2026Article
- Article
- Whose Voice is it Anyway?Perspectives on medical education · 2026Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
backgroundThe integration of ChatGPT with educational settings is happening at an unprecedented rate, and there is a growing trend for students to use ChatGPT for various academic work. Although numerous studies have evaluated the knowledge, attitudes, and practices related to ChatGPT among students in diverse medical fields, there remains a notable absence of such research within the Chinese context.
methodsThe questionnaire survey was conducted to a sample of 1,133 medical students from various medical colleges across Sichuan Province, China, between May 2024 and November 2024 to explore the awareness and attitudes of medical students towards ChatGPT. Descriptive statistics were used to tabulate the frequency of each variable. A chi-square test and multiple regression analysis were employed to investigate the factors influencing participants' positive attitudes toward the prospective use of ChatGPT.
resultsThe findings revealed that 62.9% of participants had employed ChatGPT in their medical studies, with 16.5% having utilized the tool in a published article. Participants primarily used ChatGPT for searching information (84.4%) and completing academic assignments (60.4%). However, concerns were expressed regarding the potential for ChatGPT to disseminate misinformation (76.9%) and facilitate plagiarism or complicate its detection (65.4%). Despite these concerns, 64.4% of respondents indicated a willingness to use ChatGPT to seek assistance with learning problems. Overall, a majority of participants (60.7%) maintained a positive attitude on the future use of ChatGPT in the medical field.
conclusionOur research showed that while most medical students perceived ChatGPT as a valuable tool for academic study and research, they remained cautious about its potential risks, particularly regarding misinformation and plagiarism concerns. Despite these reservations, a majority participants indicated a willingness to incorporate ChatGPT into their academic workflow, specifically for problem-solving tasks, and maintained optimistic perspectives regarding its potential integration into medical education and clinical practice. It is therefore essential to improve student literacy about AI, develop clear guidelines for its acceptable use, and implement support systems to ensure that medical students are fully prepared for the upcoming integration of AI into medical education.
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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.