Abstract
ABSTRACTDespite an increasingly diverse population, an unmet demand for undergraduates from underrepresented racial and ethnic minority (URM) backgrounds exists in the field of medicine as a result of financial hurdles and insufficient educational support faced by URM students in the premedical journey. With the capacity to provide highly individualized and accessible no- or low-cost dynamic instruction, large language models (LLMs) and their chatbot derivatives are posed to change this dynamic and subsequently help shape a more diverse future physician workforce. While studies have established the passing performance and insightful explanations of one of the most accurate LLM-powered chatbots to date—Chat Generative Pre-trained Transformer (ChatGPT)—on standardized exams such as medical licensing exams, the role of ChatGPT in premedical education remains unknown. We evaluated the performance of ChatGPT on the Medical College Admission Test (MCAT), a standardized 230-question multiple choice exam that assesses a broad range of competencies in the natural, physical, social, and behavioral sciences as well as critical analysis and reasoning. Depending on its visual item response strategy, ChatGPT performed at or above the median performance of 276,779 student test takers on the MCAT. Additionally, ChatGPT-generated answers demonstrated both a high level of agreement with the official answer key as well as insight into its explanations. Based on these promising results, we anticipate two primary applications of ChatGPT and future LLM iterations in premedical education: firstly, such models could provide free or low-cost access to personalized and insightful explanations of MCAT competency-related questions to help students from all socioeconomic and URM backgrounds. Secondly, these models could be used to generate additional test questions by test-makers or for targeted preparation by pre-medical students. These applications of ChatGPT in premedical education could be an invaluable, innovative path forward to increase diversity and improve equity among premedical students.
Publisher
Cold Spring Harbor Laboratory
Reference23 articles.
1. Diversity pipelines: The rationale to recruit and support minority physicians
2. Toretsky C , Mutha S , Coffman J. Breaking barriers for underrepresented minorities in the health professions. https://healthforce.ucsf.edu/sites/healthforce.ucsf.edu/files/publication-pdf/Breaking%20Barriers%20for%20Underrepresented%20Minorities%20in%20the%20Health%20Professions%20.pdf. Accessed February 28, 2023.
3. Institute of Medicine (US) Committee on Institutional and Policy-Level Strategies for Increasing the Diversity of the U.S. Healthcare Workforce; Smedley BD , Stith Butler A , Bristow LR , editors. In the Nation’s Compelling Interest: Ensuring Diversity in the Health-Care Workforce. Washington (DC): National Academies Press (US); 2004. 3, Costs and Financing of Health Professions Education. Available from: https://www.ncbi.nlm.nih.gov/books/NBK216015/
4. Improving Underrepresented Minority Student Persistence in STEM
5. Deep learning
Cited by
16 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献