Psychological well-being as a predictor of cyberbullying victimization in university students: a Bayesian approach

Introduction The present study examined the relationship between psychological well-being among university students and cyberbullying exposure. Methods The study included 262 students from Kuban State University as its sample. The Cyberbullying Scale (CBS) and the Depression, Anxiety, and Stress Scale (DASS-21) were used as data collection tools. We preferred Bayesian statistical methods for data analysis. Results The results of the study revealed that exposure to cyberbullying did not differ according to gender, age, and daily internet usage time. Researchers found that depression was the strongest predictor of exposure to cyberbullying, accounting for approximately 9% of the variance. Anxiety and stress variables did not significantly contribute to the explained variance in the model. Discussion The findings of the study emphasize the importance of developing protective interventions, especially for students with depressive symptoms. These results underline the significance of developing campaigns against cyberbullying and strengthening university psychological support systems. The findings also highlight the necessity for computer literacy programs and social support systems.