Adapting the metaverse perception scale for Iranian nursing students: translation and psychometric assessment

The integration of metaverse technologies into healthcare education is expand ing globally. However, there is a lack of culturally validated instruments to assess students’ perceptions within the Iranian context. This study aimed to evaluate the psychometric properties of the Persian version of the Metaverse Perception Scale among Iranian nursing students. A cross-sectional psychometric study was con ducted with 436 nursing students. The translated scale underwent Exploratory Fac tor Analysis (EFA) and Confirmatory Factor Analysis (CFA). Internal consistency was assessed using Cronbach’s alpha. Convergent and discriminant validity were evaluated through Composite Reliability (CR), Average Variance Extracted (AVE), inter-construct correlations, √AVE, MSV and ASV. Factor analysis revealed a four factor structure—Education, Technology, Lifestyle, and Challenges—which ex plained 67.08% of the total variance. CFA results indicated that the refined 20-item version of the questionnaire had a good overall model fit (χ²/df=1.647; CFI=0.958; RMSEA=0.054). All CR values and AVE values were above 0.70 and 0.50, re spectively, supporting convergent validity. For all factors, √AVE values exceeded inter-construct correlations, and both MSV and ASV were lower than AVE, sup porting discriminant validity. The scale demonstrated strong internal consistency (Cronbach’s alpha=0.917−0.822). The Persian version of the Metaverse Perception Scale (P-MPS) is a valid and reliable scale for assessing nursing students’ percep tions of metaverse technologies in educational settings. This scale shows strong potential for application in both researc