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This paper is in the following e-collection/theme issue:

Reviews in Medical Education (300) Digital Health Reviews (3672) Ethics, Privacy, and Legal Issues (812) e-Learning and Digital Medical Education (1593) Artificial Intelligence (4794) Artificial Intelligence (AI) in Medical Education (763) Generative Language Models Including ChatGPT (1530)

Published on in Vol 12 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/79939, first published .
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Application of AI-Generated Content in Medical Education: Systematic Review of the Impact on Critical Thinking Abilities of Medical Students

Application of AI-Generated Content in Medical Education: Systematic Review of the Impact on Critical Thinking Abilities of Medical Students

Authors of this article:

Jinlei Li1, 2 Author Orcid Image ;   Fen Ai2 Author Orcid Image ;   Jueyan Wang1, 2 Author Orcid Image ;   Bingxin Cheng1, 2 Author Orcid Image ;   Yu Li1, 2 Author Orcid Image ;   Zhen Chen2 Author Orcid Image
Article Authors Cited by (12) Tweetations Metrics

Journals

  1. Zhu J, Guan C, Zhang H, Wang L, Zhang Y, Bian X. Examining the association between AI-enhanced education and medical students’ self-directed learning using an integrated TAM-UTAUT2 model. Frontiers in Medicine 2026;13 View
  2. Shvarts Y, Akimova N, Konshina L, Parkhoniuk E. What and how should cardiologists learn in the era of artificial intelligence? Opinion on a problem. Russian Journal of Cardiology 2026;31(2S):6903 View
  3. Glinkowski W, Jacennik B, Jankowska A, Cedro T, Wilk S, Doniec R. AI-Assisted Training for Teleconsultation Competencies in Undergraduate Medical Education: A Narrative Review. Applied Sciences 2026;16(10):4858 View
  4. Jeong I, Kim H, Hwang H. Generative artificial intelligence and large language models in competency-based medical education: applications, challenges, and future directions. Kosin Medical Journal 2026;41(2):114 View
  5. Zhang H, Qu L, Bai H, Chen Y, Ji R, Cheng Z, Yang C. Beyond accuracy: evaluating the reliability of large language models for medical assessment. Frontiers in Artificial Intelligence 2026;9 View
  6. P M S, P D, K H. Dependence on Generative Artificial Intelligence Among Medical Students and Its Association With Critical Thinking: A Cross-Sectional Study. Cureus 2026 View
  7. Zakhari R. Teaching Critical Appraisal in the Age of Generative Artificial Intelligence. CIN: Computers, Informatics, Nursing 2026 View
  8. Botello Jaimes J, Turriago Castañeda A, Alzate Mejía O, Lombana Jimenez A. Generative artificial intelligence and the epistemology of medical learning: from cognitive augmentation to epistemic dependency. Frontiers in Education 2026;11 View
  9. El-Gohary T. Artificial intelligence in rehabilitation education: An assistive tool, not a substitute for scientific judgment. Journal of Musculoskeletal Surgery and Research 2026;0:1 View
  10. Qiu L, Li S, Liang Y, Lu S, Tao P. The Challenges of AI Applications in Health Care: Qualitative Study. Journal of Medical Internet Research 2026;28:e92979 View
  11. Niño D, Masters K, Patel R, Aoun Bahous S, Cheng D, Rossi A. Twelve tips for educators supporting learner-centered AI integration in undergraduate medical education. Medical Teacher 2026:1 View
  12. Sabando-García Á, Llacsaguache-Calle D, Villota-Oyarvide W, Loor-Ávila B, Chunga-Palomino S, Panta-Ipanaqué J, López-López H, Martinez-Aberga W, Lazo-Bravo C, Moreira-Choez J. Critical thinking as a predictor of task functionality and artificial intelligence use among university students. A PLS-SEM approach. Frontiers in Education 2026;11 View