Network analysis of depressive and anxiety symptoms in adolescents during the later stage of the COVID-19 pandemic

Yi-lang Tang,Yu-Tao Xiang,Jingxia Lin,Huanzhong Liu,Hong Cai,Rui Liu,Todd Jackson,Xu Chen,Qinge Zhang,Zhaohui Su,Wei Bai,Teris Cheung,Han Qi

doi:10.1038/s41398-022-01838-9

Abstract

Network analysis is an effective approach for examining complex relationships between psychiatric symptoms. This study was designed to examine item-level relationships between depressive and anxiety symptoms using network analysis in an adolescent sample and identified the most central symptoms within the depressive-anxiety symptoms network model. Depressive and anxiety symptoms were assessed using the Patient Health Questionire-9 (PHQ-9) and Generalized Anxiety Disorder Screener (GAD-7), respectively. The structure of depressive and anxiety symptoms was characterized using “Strength” and “Bridge Strength” as centrality indices in the symptom network. Network stability was tested using a case-dropping bootstrap procedure. Finally, a Network Comparison Test (NCT) was conducted to examine whether network characteristics differed on the basis of gender, school grade and residence. Network analysis revealed that nodes PHQ2 (“Sad mood”), GAD6 (“Irritability”), GAD3 (“Worry too much”), and PHQ6 (“Guilty”) were central symptoms in the network model of adolescents. Additionally, bridge symptoms linking anxiety and depressive symptoms in this sample were nodes PHQ6 (“Guilty”), PHQ2 (“Sad mood”), and PHQ9 (“Suicide ideation”). Gender, school grade and residence did not significantly affect the network structure. Central symptoms (e.g., Sad mood, Irritability, Worry too much, and Guilty) and key bridge symptoms (e.g., Guilty, Sad mood, and Suicide ideation) in the depressive and anxiety symptoms network may be useful as potential targets for intervention among adolescents who are at risk for or suffer from depressive and anxiety symptoms.

Highlights

Adolescence is a crucial period in life, characterized by many unique changes and challenges
“Sad mood” (PHQ2) was one of the most central symptoms to emerge within the depression-anxiety network of Chinese adolescents
Similar findings have been reported in previous studies on depressive and anxiety symptom networks of adults with psychiatric disorders [24, 55], adults with depression [23, 56], a sample of US children and adolescents [25], and adolescents in Sub-Saharan Africa [27]

Summary

INTRODUCTION

Adolescence is a crucial period in life, characterized by many unique changes and challenges. A network analysis of the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study revealed the importance of “Sad mood” and “Anhedonia” in non-psychotic depressive disorder [23] In another network analysis study, “Sad mood” and “Worry” emerged as the most central symptoms in the depression-anxiety network among psychiatric patients [24, 25]. To identify relationships between nodes, the eLASSO combined logistic regression with model selection based on a Goodness-of-Fit measure. This algorithm could result in a sparse network model which is more interpretable than the original model. No network analysis studies have been published on comorbid depressive and anxiety symptoms in general samples of adolescents in China. Strength is the sum of the correlations of one node to all other

METHODS

RESULTS

Cai et al 4

DISCUSSION

CONFLICT OF INTEREST