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November 15, 2025Computers in Human Behavior ReportsOpen Access

Psychometric properties of the Persian version of the artificial intelligence self-efficacy scale (AISES) in medical sciences students

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Authors

NGNeda GilaniAPAhmad PourabbasGDGholamali Dehghani

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Overview

Cross-sectional study validates the Persian AI self-efficacy scale in medical students, highlighting reliability and validity metrics.

Key Points

  • This study aims to translate and validate the Persian version of the Artificial Intelligence Self-Efficacy Scale among medical sciences students in Iran.
  • Cross-sectional survey conducted with 501 medical students
  • Evaluated content, face, construct, and convergent validity
  • Applied Exploratory Factor Analysis and Confirmatory Factor Analysis
  • Tested reliability with Cronbach's alpha and Composite Reliability
  • Assessed item discrimination using Item Response Theory
  • Identified a four-factor structure explaining 77.27% of variance
  • Confirmed model fit with CFI = 0.944, RMSEA = 0.057
  • Achieved high item discrimination (α = 1.06–3.78)
  • All reliability coefficients exceeded 0.80
  • Validated convergent and discriminant metrics

Cite This Study

Gilani et al. (2025) studied this question.

synapsesocial.com/papers/69251994c0ce034ddc3536a2https://doi.org/10.1016/j.chbr.2025.100858
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  4. 4Turkish adaptation of the Artificial Intelligence Self-Efficacy Scale (AISES) and its role in prospective teachers’ intentions to use AI in classroom practices2026
  5. 5Cultural Adaptation and Validation of the Medical Artificial Intelligence Readiness Scale for Medical Student Questionnaire in Indian Undergraduate Medical Education: A Mixed-methods Study2025