Gender differences in adolescent cyber delinquency patterns using multi-group latent transfer analysis

This study utilized MGLTA to derive longitudinal trajectories of adolescent cyber delinquency and analyzed the effects of gender and covariates on these trajectories. For this purpose, 1,954 students (1,050 male; 904 female) from 8th to 10th grade were sampled using KCYPS 2018 data. The four latent cyber delinquency statuses identified in this study were non-delinquents (71.6%), posting bad words (18.03%), moderate delinquents (9.39%), and serious delinquents (0.98%). The percentage of students who did cyber delinquency was about 28%. In terms of gender, males outnumbered females by 1.7-3.0 times, and the stability of cyber delinquency was significantly higher in males. As important factors predicting the gender development pattern of adolescent cyber delinquency identified in this study, for males, depression and phone dependence were risk factors, and self-esteem was a protective factor. On the other hand, for females, phone dependence was a risk factor, and attachment relationships were identified as protective factors. These results suggest the importance of targeted interventions differentiated by gender rather than a one-size-fits-all approach to adolescent cyber delinquency.