Cyberbully victimization and its association with residual depressive symptoms among clinically stable adolescents with psychiatric disorders during the COVID-19 pandemic: A perspective from network analysis

Frontiers in Psychology

article

Xiao-Meng Xie¹  Hong Cai²  Shu-Ying Li⁴  Zong-Lei Li⁵  Wu-Yang Zhang⁶  Yan-Jie Zhao¹  Yao Zhang⁴  Gabor S. Ungvari⁷  Yi-Lang Tang⁹  Fan He¹  Yu-Tao Xiang² 

[1] The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital and the Advanced Innovation Center for Human Brain Protection, School of Mental Health;Unit of Psychiatry, Department of Public Health and Medicinal Administration, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau;Centre for Cognitive and Brain Sciences, University of Macau;Department of Psychiatry, The First Affiliated Hospital of Zhengzhou University;Department of Psychiatry, Xiamen Xianyue Hospital;Department of Pediatric Development and Behavior, The Third Affiliated Hospital of Zhengzhou University;Section of Psychiatry, University of Notre Dame Australia;Division of Psychiatry, School of Medicine, University of Western Australia / Graylands Hospital;Department of Psychiatry and Behavioral Sciences, Emory University;Mental Health Service Line, Atlanta VA Medical Center

关键词: COVID-19;    cyberbullying;    Victimization;    Psychiatric disorder;    Adolescent patients;    Network analysis;   

DOI  :  10.3389/fpsyg.2022.1080192

学科分类：社会科学、人文和艺术（综合）

来源: Frontiers

【 摘 要 】

Objective: Cyberbullying is frequently reported by adolescents with psychiatric disorders. The COVID-19 pandemic has dramatically altered the lifestyle and daily routine of whole populations. The pattern of cyberbullying and its associated factors and relationships with different residual depressive symptoms in clinically stable adolescent psychiatric patients are unknown. This study examined the prevalence of cyberbullying and its relationships with different residual depressive symptoms in this patient population during the COVID-19 outbreak using network analysis (NA). Methods: This was a multicenter, cross-sectional study carried out. 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 depressive symptoms and internet addiction were evaluated e using standardized instruments. The severity of internet addiction and depressive symptoms were also measured using the Internet Addiction Test (IAT) and the Patient Health Questionnaire-9 (PHQ-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. Results: Altogether 1,265 patients completed the assessments. The overall prevalence of cyberbullying was 92.3% (95%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”. Conclusion: During 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 NA study should be targeted in interventions and preventive measures.

【 授权许可】

CC BY