Attitude, Readiness, and Predictors of AI Adoption among Undergraduate Medical Students

Manisha Sarkar; Sonali Sain; Prianka Mukhopadhyay; Aditya Prasad Sarkar

doi:10.55489/njcm.160920255559

Authors

Manisha Sarkar Department of Community Medicine, Bankura Sammilani Medical College, Bankura, West Bengal, India
Sonali Sain Department of Community Medicine, Bankura Sammilani Medical College, Bankura, West Bengal, India https://orcid.org/0000-0002-7563-8856
Prianka Mukhopadhyay Department of Community Medicine, Bankura Sammilani Medical College, Bankura, West Bengal, India https://orcid.org/0000-0003-1991-1819
Aditya Prasad Sarkar Department of Community Medicine, Bankura Sammilani Medical College, Bankura, West Bengal, India https://orcid.org/0000-0002-8754-083X

DOI:

https://doi.org/10.55489/njcm.160920255559

Keywords:

Algorithms, Deep Learning, Education Medical, Generative Artificial Intelligence, Supervised Machine learning, Unsupervised Machine learning

Abstract

Background: Artificial Intelligence (AI) is revolutionizing health care. Aim of study was to assess the attitude and readiness towards AI and their predictors among undergraduate medical students.

Methods: A cross-sectional study was conducted among 362 medical students at a West Bengal institute from November 2024 to April 2025, excluding the 3rd Prof Part II MBBS 2020 batch. Sit et al.’s attitude towards AI and Karaca et al.’s Medical artificial intelligence readiness scale for medical students (MAIRS-MS) tools were used. Multiple linear regression using stepwise method was used to determine the predictors.

Results: Only 19.9% students received teaching/training in AI. Mean score of ‘attitude’ and ‘readiness’ towards AI were 35.9±7.3 and 70.0±16.8 respectively. Nearly 43% understood AI limitations (43.7%) and could ethically use AI technology (43.1%). Familiarity with AI terminologies (ß=0.314, p<0.001) and AI training (ß=5.930, p<0.001) positively predicted attitude towards AI. Year of study (2^nd prof- ß=4.24, p=0.018; 3^rd Prof Part I- ß=8.63, p<0.001), training in AI (ß=7.48, p<0.001) and attitude towards AI (ß=1.37, p<0.001) positively predicted readiness towards AI

Conclusions: Teaching/training medical students in AI favors their attitude towards AI, both of which further impacts readiness towards AI thus promoting integration of AI in medical curricula.

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