Adaptation and Validation of the Social Media Cyberbullying Victimization Scale Among Chinese College Students: Cross-Sectional Study.

Background: Cyberbullying victimization is a significant risk factor for poor psychological well-being among college students. Existing tools fail to capture the distinct dimensions of victimization in social media contexts. Objective: This study aimed to adapt and validate a Social Media Cyberbullying Victimization Scale (SMCVS) and examine its associations with psychological outcomes among Chinese college students. Methods: In Shanghai, China, 1766 students from multiple universities completed questionnaires including demographic information, the SMCVS, the Patient Health Questionnaire-9, and the Generalized Anxiety Disorder-7 scale. The psychometric evaluation of the SMCVS included content validity, construct validity, criterion validity, internal consistency reliability, split-half reliability, and test-retest reliability. Receiver operating characteristic analyses were used to evaluate predictive ability for depression and anxiety. Results: Content validity was satisfactory, and 13 items were retained, with item-level content validity index values ranging from 0.833 to 1 and a scale-level content validity index of 0.949. Exploratory factor analysis identified 2 dimensions-"information harassment" and "reputation and privacy violation"-explaining 82.2% of the total variance. Confirmatory factor analysis supported this structure (goodness-of-fit index=0.943, comparative fit index [CFI]=0.982, normed fit index=0.978, and root mean square error of approximation [RMSEA]=0.075). Multigroup confirmatory factor analysis supported configural and metric invariance across both gender and academic major (ΔCFI≤0.01, ΔRMSEA≤0.015); scalar invariance was achieved for gender but not for academic major. Both dimensions showed significant correlations with depression (r=0.433-0.457) and anxiety (r=0.356-0.372). Cronbach α, Spearman-Brown coefficient, and test-retest reliability coefficient were 0.959, 0.973, and 0.860, respectively. The SMCVS demonstrated moderate discriminative accuracy for depression (area under the curve [AUC]=0.738; optimal cutoff=19.5) and anxiety (AUC=0.739; optimal cutoff=22.5). Conclusions: The SMCVS demonstrates sound psychometric properties and may be useful for assessing social media cyberbullying victimization among Chinese college students. Its validated 2D structure clarifies distinct patterns of victimization and their psychological correlates, offering implications for targeted prevention and intervention.