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ObjectiveThis study examined the prevalence of cyberbullying and its relationship with residual depressive symptoms in this patient population during the COVID-19 outbreak using network analysis.MethodsThis was a multicenter, cross-sectional study. Adolescent patients attending maintenance treatment at outpatient departments of three major psychiatric hospitals were included. Experience of cyberbullying was measured with a standard question, while the severity of Internet addiction and depressive symptoms were measured using the Internet Addiction Test and the Patient Health Questionnaire-9, respectively. The network structure of depression and cyberbully were characterized and indices of “Expected Influence” was used to identify symptoms central to the network. To identify particular symptoms that were directly associated with cyberbully, the flow function was used.ResultsAltogether 1,265 patients completed the assessments. The overall prevalence of cyberbullying was 92.3% (95% confidence interval (CI): 90.8–93.7%). Multiple logistic regression analysis revealed that male gender (p = 0.04, OR = 1.72, 95%CI: 1.04–2.85) was significantly associated with higher risk of cyberbullying, while a relapse of illness during the COVID-19 pandemic was significantly associated with a lower risk of cyberbullying (p = 0.03, OR = 0.50, 95%CI: 0.27–0.93). In the network of depression and cyberbully, “Sad mood,” “Anhedonia” and “Energy” were the most central (influential) symptoms. Furthermore, “Suicidal ideation” had the strongest negative association with cyberbully followed by “Guilt”.ConclusionDuring the COVID-19 pandemic, the experience of cyberbullying was highly prevalent among clinically stable adolescent psychiatric patients, particularly male patients. This finding should raise awareness of this issue emphasizing the need for regular screening and interventions for adolescent patients. Central symptoms (e.g., “Sad mood,” “Anhedonia” and “Energy”) identified in this study should be targeted in interventions and preventive measures. |
