Evidence map›Paper›PMID 40598155›Full record

ArticleBMC psychiatry2025

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.

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

Abstract read
In one paragraph

Article in BMC psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Tingting Li *Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei, 230032, Anhui, China.
Dan Zhang *Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei, 230032, Anhui, China.
Tangjun JiangDepartment of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei, 230032, Anhui, China.
Wanyu CheDepartment of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei, 230032, Anhui, China.
Yi ZhangDepartment of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei, 230032, Anhui, China.
Yuhui WanDepartment of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei, 230032, Anhui, China.
Fangbiao TaoDepartment of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei, 230032, Anhui, China.
Shuman TaoMOE Key Laboratory of Population Health Across Life Cycle, No 81 Meishan Road, Hefei, 230032, Anhui, China. shumantao@126.com.
Xiaoyan WuDepartment of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei, 230032, Anhui, China. xywuahmu@126.com.

Funding

National Natural Science Foundation of China 82173542, 82373592
6 · The paper itself

Abstract

objectivesThis 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.

methodsFrom 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.

resultsIn 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.

conclusionsIn 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.

Indexed as

AnxietyAnxiety DisordersCOVID-19DepressionAdolescentChinaComorbidityEast Asian PeopleFemaleHumansMaleSurveys and QuestionnairesAnxietyComorbidityDepressionNetwork analysis

Identifiers

PMID40598155
PMCPMC12211814

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LicenceCC BY-NC-ND
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.