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.

IF 3.4 2区 医学 Q2 PSYCHIATRY
Tingting Li, Dan Zhang, Tangjun Jiang, Wanyu Che, Yi Zhang, Yuhui Wan, Fangbiao Tao, Shuman Tao, Xiaoyan Wu
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引用次数: 0

Abstract

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

Methods: From October to December 2021, a total of 22 868 adolescents were selected from 27 schools in 8 cities of China by multistage cluster sampling. Depressive symptoms and anxiety symptoms of 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, 7 236 (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 bridge strength 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 interventions targeting these bridge symptoms may help alleviate the comorbidity of depression and anxiety in Chinese adolescents.

Clinical trial number: Not applicable.

新冠肺炎疫情防控常态化阶段全国青少年抑郁焦虑共病网络分析
目的:本研究采用网络分析探讨新冠肺炎疫情防控常态化阶段中国青少年抑郁与焦虑的共病模型。方法:采用多阶段整群抽样的方法,于2021年10月至12月在中国8个城市的27所学校抽取22 868名青少年。采用患者健康问卷9 (PHQ-9)和广泛性焦虑障碍量表7 (GAD-7)对青少年抑郁症状和焦虑症状进行评估。采用扩展贝叶斯信息准则(EBIC)和图形最小绝对收缩和选择算子(LASSO)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、中心症状、桥接症状和网络比较。结果:在本研究中,有7236名(31.6%)参与者报告有抑郁-焦虑合并症。得到的网络模型具有很高的稳定性。在焦虑和抑郁群体中,“控制焦虑”和“过度担忧”之间、“不安”和“易怒”之间、“快感缺乏”和“悲伤情绪”之间的边缘是三个最强的正面边缘。“运动”和“不安”之间的界限,“内疚”和“紧张”之间的界限,“自杀”和“害怕”之间的界限是共病群体中三个最强的正面界限。“悲伤情绪”和“过度担忧”是“抑郁”网络和“焦虑”网络中的核心症状。“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。其中,“Too much worry”(强度指标= 1.087)的强度值最高。“神经级”(桥梁强度指数为0.51,期望影响(1步)= 0.51,期望影响(2步)= 0.93)不仅表现出最高的桥梁强度,而且表现出最高的桥梁期望影响。最后,我们发现性别之间没有显著差异。结论:在这项研究中,“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。针对这些桥状症状的及时和多层次的干预可能有助于减轻中国青少年抑郁和焦虑的共病。临床试验号:不适用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
BMC Psychiatry
BMC Psychiatry 医学-精神病学
CiteScore
5.90
自引率
4.50%
发文量
716
审稿时长
3-6 weeks
期刊介绍: BMC Psychiatry is an open access, peer-reviewed journal that considers articles on all aspects of the prevention, diagnosis and management of psychiatric disorders, as well as related molecular genetics, pathophysiology, and epidemiology.
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