Cultural Adaptation and Validation of the Medical Artificial Intelligence Readiness Scale for Medical Student Questionnaire in Indian Undergraduate Medical Education: A Mixed-methods Study

Abstract

Abstract Background: The Medical Artificial Intelligence Readiness Scale for Medical Students (MAIRS-MSs), originally developed and validated in Turkey, is a pioneering tool designed to quantify artificial intelligence (AI) readiness. However, its use in different educational and cultural contexts necessitates rigorous revalidation. This study aimed to undertake the psychometric re-evaluation and contextual adaptation of the MAIRS-MS instrument within an Indian undergraduate medical education framework. Methodology: This research employed a mixed-methods approach and was carried out at a medical college in central India, including 482 undergraduate medical students across different academic years. The 22-item MAIRS-MS questionnaire, which assesses four domains (Cognition, Ability, Vision, and Ethics), was administered. Internal consistency was measured using Cronbach’s alpha, and construct validity was analysed through Pearson’s correlation. In addition, qualitative insights were gathered via Focus Group Discussions (FGDs) and were analyzed thematically. Results: The MAIRS-MS instrument exhibited high internal reliability: Cognition (α = 0.865), Ability (α = 0.879), Vision (α = 0.763), Ethics (α = 0.812), and overall scale (α = 0.923). All items demonstrated statistically significant item-total correlations ( P < 0.01), affirming strong construct validity. FGDs highlighted both enthusiasm for AI and notable gaps in ethical and legal understanding, with unanimous support for its curricular integration. Conclusion: The MAIRS-MS scale demonstrates robust psychometric properties within the Indian context and is a valid instrument for evaluating AI readiness in medical students. These findings support the structured incorporation of AI education into the undergraduate medical curriculum.

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