Ethical AI Dilemma Anxiety refers to the psychological distress experienced by university students when confronting moral uncertainties surrounding the use of artificial intelligence in academic contexts. Despite growing recognition of this phenomenon, validated instruments for its measurement remain absent from the literature. This study reports the development and psychometric validation of the Ethical AI Dilemma Anxiety Scale (EAIDAS), a novel instrument designed to measure anxiety arising from ethical uncertainties surrounding AI use in academic contexts. Following expert content validation using Lawshe’s Content Validity Ratio, the 24-item scale was administered to two independent samples of Egyptian university students ( N = 665 for exploratory analysis; N = 865 for confirmatory analysis). Exploratory factor analysis with parallel analysis identified a three-dimensional structure comprising Academic Integrity Anxiety, Professional Future Anxiety, and Societal Impact Anxiety, collectively explaining 43% of total variance. Confirmatory factor analysis demonstrated excellent model fit (CFI = 0.961, RMSEA = 0.043) for both first-order and second-order factor structures. The scale exhibited strong internal consistency ( α = 0.886–0.920) and adequate test–retest reliability over 3 weeks. Convergent and discriminant validity were established through composite reliability, average variance extracted, the Fornell-Larcker criterion, and the heterotrait-monotrait ratio. EAIDAS provides researchers, educators, and policymakers with a valid and reliable tool for assessing students’ ethical anxiety related to AI integration, enabling evidence-based interventions and institutional policy development.
Helali et al. (Wed,) studied this question.