Cybervictimization among Iranian university students

Abstract Background Cybervictimization represents a critical public health concern with substantial psychosocial ramifications. However, empirical investigations examining its socio-demographic determinants among emerging adults in higher education contexts remain limited, particularly within Non-Western settings. This study examined the continuous severity and socio-demographic correlates of cybervictimization among Iranian university students, while rigorously validating the psychometric properties and gender invariance of the measurement scale. Methods A cross-sectional survey was conducted among 828 enrolled university students aged 17–25 years (Mean age = 21.05, SD = 1.82; 67.6% female) across three major public universities in Iran. Cybervictimization was assessed using the 12-item Cyber-Bullying/Victimization Experiences Questionnaire (CBVEQ). Confirmatory Factor Analysis (CFA) using the Weighted Least Squares Means and Variance adjusted (WLSMV) estimator was performed to evaluate construct validity, followed by multi-group CFA to assess gender measurement invariance. Socio-demographic predictors of continuous victimization scores were identified via multivariable linear regression analysis. Results The unidimensional CFA model demonstrated excellent fit to the empirical data (χ 2 (54) = 304.904, CFI = 0.995, TLI = 0.994, RMSEA = 0.075, SRMR = 0.060). Standardized factor loadings across all items were strong (0.64–0.88). Sequential multi-group CFAs supported full scalar measurement invariance across gender (ΔCFI = + 0.001, ΔRMSEA = -0.003). CBVEQ total scores exhibited a strongly floor-concentrated and right-skewed distribution (Mean = 16.45, SD = 6.84, skewness = 2.359, kurtosis = 5.877). In the multivariable linear regression model (F(6, 821) = 7.932, p < 0.001, R 2 = 0.055), male gender (β = 0.193, p < 0.001) and higher parental education (β = 0.105, p = 0.003) emerged as statistically significant independent predictors of elevated victimization severity. Conversely, higher subjective economic status (β = -0.095, p = 0.038) was significantly associated with reduced victimization severity. Age, employment status, and family income adequacy were not significantly associated with cybervictimization. Conclusion Cybervictimization severity among university students is significantly associated with gendered interaction dynamics and socio- economic status rather than chronological age. The confirmed full scalar measurement invariance supports the psychometric suitability and gender measurement invariance of the CBVEQ for gender comparative research. Interventions targeting digital safety in higher education should account for gender-specific risk profiles and social stratification factors.