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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

3Citations signalées, ce qui n’est pas une note de qualité
4Institutions déclarées
2Pays d’affiliation déclarés

Rattachement africain : cn, us. Niveau de preuve : code pays fourni par la source.

Le résumé fourni par la source

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.

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Le contrôle bibliographique ouvert

DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref
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
Date Crossref
01/07/2025
Éditeur
Springer Science and Business Media LLC
Type
journal-article

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Les sujets associés

Mental Health Research TopicsCOVID-19 and Mental HealthHealth, Environment, Cognitive Aging

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