Assessment of the Iranian Medical Students’ Attitudes and Readiness Toward Artificial Intelligence: A Cross-Sectional Study

Document Type : Original Article

Authors

1 Student Research Committee, Faculty of Medicine, Mazandaran University of Medical Sciences, Sari, Iran

2 Student Research Committee, Babol University of Medical Sciences, Babol, Iran

3 Department of Biostatistics and Epidemiology, Faculty of Health, Mazandaran University of Medical Sciences, Sari, Iran

4 Department of Radiopharmacy, Faculty of Pharmacy, Pharmaceutical Sciences Research Center, Mazandaran University of Medical Sciences, Sari, Iran

5 Pediatric Infectious Diseases Research Center, Communicable Diseases Institute, Mazandaran University of Medical Sciences, Sari, Iran

Abstract

Background: Artificial Intelligence (AI) is increasingly reshaping healthcare through advancements in diagnosis, therapeutic decision-making, and patient care management. This study designed to evaluate the attitudes and readiness of medical science students toward AI, to inform and improve AI-related educational programs.
Methods: This cross-sectional study was carried out at Mazandaran University of Medical Sciences (MAZUMS), Iran, between December 2023 and March 2024. A total of 637 students enrolled in medical and health sciences programs were recruited through convenience sampling via online platforms. Data were collected using a 31-item online questionnaire captured demographic information, exposure to AI-related education, and readiness for AI. The study utilized the validated Persian version of the Medical Artificial Intelligence Readiness Scale for Medical Students (MAIRS-MS). Statistical analyses were performed using SPSS version 22, with a significance threshold set at p < 0.05.
Results: In total, 637 Iranian medical sciences students participated. Of these, 54.2% were in preclinical training and 45.8% were in clinical phases. Most participants (80.7%) reported gaining knowledge about AI primarily through media sources. Radiology, general surgery, and diagnostic decision-making were identified as the disciplines most influenced by AI. According to MAIRS-MS results, students demonstrated the highest readiness in ethical aspects and the lowest in cognitive domains. The mean overall readiness score was 63.19±12.86 (out of 100). Participants with previous AI-related education achieved significantly higher readiness scores compared with those without such training (β = 6.36, p < 0.001).
Conclusion: Iranian medical students showed substantial interest in AI, although their levels of readiness varied, with stronger ethical understanding and weaker cognitive competencies. Exposure to prior AI education was linked to higher readiness scores, emphasizing the necessity of incorporating structured AI instruction into medical curricula. Overall, these results underscore the importance of targeted curriculum development to equip future healthcare professionals with the skills required for effective AI integration.

Highlights

Pooria Sobhanian (Google Scholar)

Sara Eslami (Google Scholar)

Keywords

References

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History

  • Receive Date: 09 September 2025
  • Revise Date: 08 January 2026
  • Accept Date: 18 January 2026
  • Publish Date: 01 March 2026

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