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Medical Students' Perceptions of Large Language Models in Healthcare: A Multinational Cross-Sectional Study
Faiza Ejas1,2, Sameer Asim Khan1,2, Amina Mujahid1,2
1College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, United Arab Emirates.
Background:
Artificial intelligence (AI) and large language models (LLMs), are potential tools for enhancing healthcare delivery and clinical research. Presently, there is a scarcity of research regarding the viewpoints of medical students toward LLMs. This study aims to explore the perceptions of LLMs and their applications among this demographic.
Methods:
A cross-sectional study was done using an online survey. It was designed using Google Forms and circulated from July 2023 to August 2023. The target population included medical students from Ecuador, Ethiopia, India, Mauritius, Pakistan, United Arab Emirates (UAE), and the United States (USA).
Results:
A total of 1180 responses were collected from 10 medical colleges across 7 countries. The UAE had the largest number of responses (31.7%), followed by Ecuador (17.6%), and Mauritius (13.7%). And 77.4% respondents were already aware about LLMs before attempting the survey, most popularly, ChatGPT. Participants were most familiar with the specific use of LLMs in research (46%), and the lowest familiarity was seen in the use of LLMs in healthcare (37%). More than half of the participants (52%) support the use of LLMs healthcare, yet a significant number of them remained neutral (37%) or disagreed (31%) on LLMs being safe in this context.
Conclusion:
While most of the medical students are aware of LLMs and their applications, the multinational survey demonstrated hesitancy among medical students in fully adopting LLMs into healthcare practice and clinical research. This study prompts further exploration of medical students' attitudes and acceptance concerning the integration of LLMs for research methodologies, ethical considerations, and healthcare practice.
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