Perceptions, Attitudes, and Use of AI by Medical Students: Mixed Methods Study

Area of Science:

• Medical Education
• Artificial Intelligence in Healthcare
• Digital Health

Background:

• Artificial intelligence (AI) is increasingly integrated into medicine, offering benefits like enhanced care and reduced administrative burden.
• However, AI presents challenges such as lack of clinical context awareness, data dependency, and absence of ethical judgment.
• Medical students, as future practitioners, require preparation for AI integration, yet current understanding of their actual AI use is limited.

Purpose of the Study:

• To explore French medical students' perceptions, attitudes, and utilization of artificial intelligence (AI).

Main Methods:

• A 2025 mixed-methods study surveyed French medical students using online questionnaires with open-ended and Likert scale questions.
• Quantitative analysis involved Kruskal-Wallis tests, chi-square tests, and multivariable linear regression.
• Qualitative thematic analysis was performed on open-text responses regarding AI perceptions, feelings, training, and use.

Main Results:

• Of 1342 students, only 5% correctly defined AI, yet 57.4% provided incorrect definitions.
• Attitudes toward AI were generally positive (median score 7/10), though a correct AI definition was not significantly associated with higher scores.
• Students expressed nuanced optimism, concerns about dehumanization and skill loss, and a preference for AI training outside the formal curriculum (48.5%).

Conclusions:

• Medical students exhibit positive but varied attitudes toward AI despite limited foundational knowledge.
• Concerns regarding ecological impact, skill degradation, and ethics coexist with significant self-directed AI use for learning.
• Findings establish a baseline for evaluating AI training, emphasizing critical appraisal, ethical considerations, and self-directed AI application.