Medical Students' Perceptions of Large Language Models in Healthcare: A Multinational Cross-Sectional Study.

Area of Science:

• Medical Education
• Artificial Intelligence in Healthcare
• Clinical Research

Background:

• Artificial intelligence (AI) and large language models (LLMs) offer potential benefits for healthcare delivery and clinical research.
• Limited research exists on medical students' perspectives regarding LLMs.
• This study investigates medical students' perceptions of LLMs and their applications.

Purpose of the Study:

• To explore medical students' awareness and perceptions of large language models (LLMs).
• To assess the familiarity of medical students with LLM applications in healthcare and research.
• To understand medical students' support and concerns regarding LLM integration in medical practice.

Main Methods:

• A cross-sectional study utilizing an online survey distributed via Google Forms.
• Survey conducted between July and August 2023, targeting medical students across seven countries.
• Data collected from 1180 respondents across 10 medical colleges.

Main Results:

• Over 77% of respondents were aware of LLMs, with ChatGPT being the most recognized.
• Familiarity with LLM applications was higher in research (46%) than in healthcare (37%).
• While 52% supported LLM use in healthcare, significant portions remained neutral (37%) or disagreed (31%) on their safety.

Conclusions:

• Most medical students are aware of LLMs, but a notable hesitancy exists regarding their full adoption in healthcare and research.
• The study highlights the need for further investigation into medical students' attitudes towards LLM integration.
• Exploring ethical considerations and acceptance of LLMs in medical education and practice is crucial.