Dataset for "Development and Multidimensional IRT-Based Validation of the AI-Induced Occupational Anxiety Scale Among University Students"

This dataset accompanies the study entitled “Development and Multidimensional IRT-Based Validation of the AI-Induced Occupational Anxiety Scale Among University Students.” The study aimed to develop and validate the AI-Induced Occupational Anxiety Scale (AIOAS), a multidimensional instrument designed to assess university students’ occupational anxiety related to artificial intelligence-driven changes in the labor market. The uploaded dataset contains item-level responses to the initial 30-item trial form of the scale. The data are organized into two worksheets: “EFA,” including responses from 344 participants used for exploratory factor analysis, and “CFA_IRT,” including responses from 516 participants used for confirmatory factor analysis and multidimensional item response theory analyses. In total, the dataset includes anonymized responses from 860 university students. Items are coded as M1–M30, and responses are scored on a 5-point Likert-type scale ranging from 1 to 5. The dataset was used to examine the factor structure, reliability, discriminant validity, and item-level psychometric properties of the scale. Based on the analyses, the final AIOAS consisted of 22 items across four dimensions: Job Security Anxiety, Competition Anxiety, Occupational Uncertainty Anxiety, and Adaptation Anxiety. No personally identifying information is included in the dataset. The data are shared to support transparency, reproducibility, and further research on AI-induced occupational anxiety, psychometric scale development, multidimensional item response theory, human–AI interaction, and university students’ career-related concerns in the AI era.