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December 8, 2025National Journal of Clinical AnatomyOpen Access

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

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Authors

DDDiwakar DhurandharMDMithilesh M DhamandeTCTripti Chandrakar

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Overview

Mixed-methods study evaluates artificial intelligence readiness in medical students, suggesting need for curricular integration.

Key Points

  • To revalidate the Medical Artificial Intelligence Readiness Scale for use in Indian undergraduate medical education.
  • Mixed-methods study conducted at a medical college in central India
  • Administered a 22-item questionnaire assessing Cognition, Ability, Vision, and Ethics to 482 students
  • Measured internal consistency using Cronbach’s alpha and analyzed construct validity with Pearson’s correlation
  • Gathered qualitative data via Focus Group Discussions and analyzed thematically.
  • MAIRS-MS showed high internal reliability across all domains: Cognition (α = 0.865), Ability (α = 0.879), Vision (α = 0.763), Ethics (α = 0.812), overall scale (α = 0.923)
  • All items had statistically significant item-total correlations (P < 0.01), indicating strong construct validity
  • FGDs revealed enthusiasm for AI but identified gaps in ethical understanding, with support for integrating AI into the curriculum.

Cite This Study

Dhurandhar et al. (2025) studied this question.

synapsesocial.com/papers/693624a44fa91c937236c2efhttps://doi.org/10.4103/njca.njca_75_25
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