抑郁和焦虑共病的网络分析：COVID-19大流行防控常态化阶段中国青少年全国性调查研究

A network analysis of the depression and anxiety comorbidity: a nationwide survey among Chinese adolescents during the normalization phase of COVID-19 pandemic prevention and control

抑郁和焦虑共病的网络分析：COVID-19大流行防控常态化阶段中国青少年全国性调查研究

Authors: Tingting Li, Dan Zhang, Tangjun Jiang, Wanyu Che, Yi Zhang, Yuhui Wan, Fangbiao Tao, Shuman Tao, Xiaoyan Wu

Journal: Bmc Psychiatry

PMID: 40598155

DOI: 10.1186/s12888-025-07036-3

Abstract

Objectives: This study employed network analysis to investigatethe comorbidity model between depression and anxiety among Chinese adolescentsduring the normalization phase of COVID-19 pandemic prevention and control.

Methods: From October to December 2021, a total of 22868 adolescents were selected from 27 schools in 8 cities of China by multistage cluster sampling. Depressive symptoms and anxiety symptomsof adolescents were evaluated by the Patient Health Questionnaire 9 (PHQ-9) and the Generalized Anxiety Disorder scale 7 (GAD-7), respectively. The network structure between depression and anxiety was explored using the Extended Bayesian Information Criterion (EBIC) and the graphical Least Absolute Shrinkage and Selection Operator (LASSO) method. The centrality of nodes, stability, accuracy, central symptoms, bridging symptoms, and network comparison were analyzed.

Results: In the present study, 7236 (31.6%) participants reported with depression-anxiety comorbidity. The obtained network model was highly stable. The edges between ‘Control worry’and ‘Too much worry’, between ‘Restless’and ‘Irritable’, and between ‘Anhedonia’and ‘Sad mood’were the three strongest positive edges in the anxiety and depression community. The edges between ‘Motor’and ‘Restless’, between ‘Guilt’and ‘Nervous’, and between ‘Suicide’and ‘Afraid’were the three strongest positive edges in the comorbidity community.‘Sad mood’ and ‘Too much worry’were the core symptoms within the ‘depression’network and ‘anxiety’network. ‘Nervous’, ‘Guilt’, and ‘Restless’were three crucial bridge symptoms linking the comorbidity of depression and anxiety networks. Furthermore, ‘Too much worry’(strength index = 1.087) has the highest strength value. ‘Nervous’(bridge strength index = 0.51, expected influence(1-step)= 0.51, expected influence(2-step)= 0.93) not only demonstrated the highest bridgestrength but also exhibited the highest bridge expected influence.At last, we found that there were no significant differences between genders.

Conclusions: In this study, ‘Nervous’, ‘Guilt’, and ‘Restless’were identified as three crucial bridge symptoms linking the comorbidity of depression and anxiety networks. Timely and multilevel interventionstargetingthese bridge symptoms may help alleviate the comorbidity of depression and anxiety in Chinese adolescents.

Keywords: Network analysis, Comorbidity, Depression, Anxiety

摘要

目的：本研究采用网络分析方法，探讨了中国青少年在COVID-19大流行防控常态化阶段抑郁与焦虑的共病模型。

方法：2021年10—12月，采用多阶段整群抽样方法，从中国8个城市的27所学校中选取了22 868名青少年作为研究对象。采用患者健康问卷—9项和广泛性焦虑障碍量表—7项分别评估青少年的抑郁症状和焦虑症状。使用扩展贝叶斯信息准则和图形最小绝对收缩和选择算子方法探索抑郁和焦虑之间的网络结构。分析节点的中心性、稳定性、准确性、核心症状、桥梁症状和网络比较。

结果：在本研究中，7236名(31.6%）参与者报告患有抑郁-焦虑合并症。所构建的网络模型具有高度稳定性。“控制担忧”和“过度担心”，“不安”和“易怒”，以及“快感缺乏”和“悲伤情绪”这三组之间的边缘是焦虑和抑郁社区中最强的三个正向边缘。“运动”和“不安”，“内疚”和“紧张”，以及“自杀”和“恐惧”这三组之间的边缘是合并症社区中最强的三个正向边缘。“悲伤情绪”和“过度担心”是“抑郁”网络和“焦虑”网络的核心症状。“紧张”、“内疚”和“不安”是连接抑郁和焦虑共病网络的三个关键桥梁症状。此外，“过度担心”(强度指数＝1.087）具有最高的强度值。“紧张”(桥梁强度指数＝0.51，预期影响(1步）＝0.51，预期影响(2步）＝0.93）不仅表现出最高的桥梁强度，还展现出最高的桥梁预期影响。最后，我们发现性别之间没有显著差异。

结论：在本研究中，“紧张”、“内疚”和“不安”被确定为连接抑郁和焦虑共病网络的三个关键桥梁症状。针对这些桥梁症状及时采取多层次干预可能有助于缓解中国青少年抑郁和焦虑的共病情况。

关键词：焦虑; 合并症; 抑郁; 网络分析