Attitudes toward and readiness for medical artificial intelligence among medical and health science students

Abstract

Purpose: This study assessed general attitudes toward artificial intelligence and medical artificial intelligence readiness among medical and health sciences students and examined the factors that influence the medical artificial intelligence readiness of the students. Methods: A descriptive cross-sectional quantitative online survey was conducted among medical and health sciences students. We employed the 'General Attitudes Toward Artificial Intelligence Scale' (GAAIS) to assess students' artificial intelligence attitudes and the 'Medical Artificial Intelligence Readiness of Students Scale for Medical Students' (MAIRS-MS) to measure student readiness for medical artificial intelligence. Results: Nearly all students did not receive/ attend any experience of artificial intelligence education from medical school (95.3%) or outside of medical school (85.0%), and most of them received information about artificial intelligence from the media (74.8%). The students reported a poor knowledge of artificial intelligence and its application in healthcare. The students demonstrated a negative to neutral general attitude towards artificial intelligence and poor overall readiness for medical artificial intelligence. Knowledge of artificial intelligence applications in healthcare care and a generally positive attitude toward artificial intelligence were associated with increased readiness for medical artificial intelligence among students. Conclusion: The study findings can inform education policymakers and medical and health science professors about creating, introducing, and integrating new curricular content involving artificial intelligence in medical schools. Including medical artificial intelligence content in medical and health science curricula will increase students’ readiness and improve its use for more advanced patient care.

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