โก Quick Summary
A recent study assessed the AI readiness of medical students at Kermanshah University of Medical Sciences, revealing an overall readiness score of 70.59 out of 110. The findings highlight the necessity for enhanced AI training programs in medical education to better prepare future healthcare professionals.
๐ Key Details
- ๐ Participants: 800 first- to fifth-year medical students
- ๐๏ธ Study Duration: November 2022 to March 2023
- ๐ Tools Used: Demographic checklists and the Persian version of the Medical Artificial Intelligence Readiness Scale (MAIRS-MS)
- ๐ Analysis Method: Independent t-test and ANOVA using SPSS-24
๐ Key Takeaways
- ๐ฉโโ๏ธ Gender Distribution: 56.13% of participants were male.
- ๐ Highest Score: Vision category with a mean score of 9.73 out of 15.
- ๐ Lowest Score: Ability category with a mean score of 25.74 out of 40.
- ๐ Gender Comparison: Female students had a higher mean AI readiness score (71.84) compared to males (69.62), though not statistically significant.
- ๐งโ๐ Age Factor: AI readiness increased with the age of students.
- ๐ซ Recommendations: Establish more AI training centers and integrate AI courses into the medical curriculum.
๐ Background
As artificial intelligence (AI) continues to transform healthcare, it is crucial to evaluate the readiness of future medical professionals to engage with these technologies. Understanding the factors that influence AI readiness among medical students can help shape educational strategies and ensure that graduates are equipped with the necessary skills to thrive in a tech-driven medical landscape.
๐๏ธ Study
This cross-sectional descriptive-analytical study focused on medical students at Kermanshah University of Medical Sciences. By employing a comprehensive questionnaire, the researchers aimed to gauge the current state of AI readiness and identify factors that could enhance students’ preparedness for integrating AI into their future practices.
๐ Results
The study revealed that the overall AI readiness score among students was 70.59 ยฑ 19.24. Notably, the vision category scored the highest, while the ability category lagged behind. The analysis indicated that while there was a trend of higher readiness in female students, the difference was not statistically significant. Additionally, older students tended to demonstrate greater AI readiness, suggesting that experience may play a role in preparedness.
๐ Impact and Implications
The findings of this study underscore the urgent need for medical education institutions to enhance their AI training offerings. By establishing dedicated AI training centers and integrating AI-focused courses into the curriculum, universities can better prepare students for the evolving demands of the healthcare sector. This proactive approach will not only improve individual readiness but also contribute to the overall advancement of healthcare practices through technology.
๐ฎ Conclusion
The study highlights the critical importance of preparing medical students for the integration of AI technologies in healthcare. With an overall readiness score of 70.59, there is room for improvement. By investing in AI education and training, medical schools can ensure that future healthcare professionals are equipped with the knowledge and skills necessary to leverage AI effectively, ultimately enhancing patient care and outcomes.
๐ฌ Your comments
What are your thoughts on the readiness of medical students to work with AI technologies? How can educational institutions better prepare future doctors for this challenge? ๐ฌ Share your insights in the comments below or connect with us on social media:
Factors affecting medical artificial intelligence (AI) readiness among medical students: taking stock and looking forward.
Abstract
BACKGROUND: Measuring artificial intelligence (AI) readiness among medical students is essential to assess how prepared future doctors are to work with AI technology. Therefore, this study aimed to examine the factors influencing AI readiness among medical students at Kermanshah University of Medical Sciences, both by evaluating the current situation and considering future developments.
METHODS: This was a cross-sectional descriptive-analytical study. The statistical population consisted of 800 first- to fifth-year medical students selected through convenient sampling at Kermanshah University of Medical Sciences from November to March 2023. The data collection tools were demographic checklists and Persian version questionnaire of the medical artificial intelligence readiness scale for medical students (MAIRS-MS). The data were analyzed at a significance level of Pโ<โ0.05 using independent t-test, and analysis of variance (ANOVA) tests through SPSS-24 software.
RESULTS: Most of the students were male (56.13%). The overall score for medical AI readiness was 70.59โยฑโ19.24 out of a maximum possible score of 110. Students had the highest mean score of 9.73โยฑโ2.96 out of 15 in vision and the lowest mean score of 25.74โยฑโ7.52 out of 40 in ability. The overall mean of AI readiness (71.84โยฑโ18.27) was higher in females than males (69.62โยฑโ19.93), but this difference was not significant (pโ=โ0.106). Furthermore, the mean total score of AI readiness increased with the increasing age of the students.
CONCLUSION: Our findings underscore the need to prepare students to work with AI technologies and to provide them with the essential knowledge and skills across different areas of AI. Accordingly, the Kermanshah University of Medical Sciences student's education unit should set up more AI training centers to provide and introduce basic artificial intelligence courses. Moreover, universities should identify the needs of students based on scientific evidence, and the medical education system should design AI training programs in its educational framework in the same direction.
Author: [‘Ziapour A’, ‘Darabi F’, ‘Janjani P’, ‘Amani MA’, ‘Yฤฑldฤฑrฤฑm M’, ‘Motevaseli S’]
Journal: BMC Med Educ
Citation: Ziapour A, et al. Factors affecting medical artificial intelligence (AI) readiness among medical students: taking stock and looking forward. Factors affecting medical artificial intelligence (AI) readiness among medical students: taking stock and looking forward. 2025; 25:264. doi: 10.1186/s12909-025-06852-1