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Psychometric evaluation of Persian version of medical artificial intelligence readiness scale for medical students

2023·16 Zitationen·BMC Medical EducationOpen Access
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16

Zitationen

3

Autoren

2023

Jahr

Abstract

BACKGROUND: Artificial intelligence's advancement in medicine and its worldwide implementation will be one of the main elements of medical education in the coming years. This study aimed to translate and psychometric evaluation of the Persian version of the medical artificial intelligence readiness scale for medical students. METHODS: The questionnaire was translated according to a backward-forward translation procedure. Reliability was assessed by calculating Cronbach's alpha coefficient. Confirmatory Factor Analysis was conducted on 302 medical students. Content validity was evaluated using the Content Validity Index and Content Validity Ratio. RESULTS: The Cronbach's alpha coefficient for the whole scale was found to be 0.94. The Content Validity Index was 0.92 and the Content Validity Ratio was 0.75. Confirmatory factor analysis revealed a fair fit for four factors: cognition, ability, vision, and ethics. CONCLUSION: The Persian version of the medical artificial intelligence readiness scale for medical students consisting of four factors including cognition, ability, vision, and ethics appears to be an almost valid and reliable instrument for the evaluation of medical artificial intelligence readiness.

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Artificial Intelligence in Healthcare and EducationHealth Education and ValidationAI in Service Interactions
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