Evidence map›Paper›PMID 41050802›Full record

ArticleFrontiers in psychology2025

A network analysis of anxiety and depression symptoms among empty nesters in China.

Hong Luo, Tao Wang

Abstract read
In one paragraph

Article in Frontiers in psychology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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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

2 authors.

Hong LuoThe First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
Tao WangThe First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Mental health is closely linked to the development of various diseases and serves as a cornerstone of healthy aging. Empty nesters, who lack family support, are particularly vulnerable to mental health issues such as anxiety and depression. Network analysis offers a novel methodological approach to uncovering associations between mental disorders. This study aimed to construct a network model of anxiety and depression symptoms among Chinese empty nesters, identify central and bridge symptoms, and explore their interrelationships to inform targeted interventions. Methods: A total of 5,130 individuals aged 60 and above were selected from the China Longitudinal Healthy Longevity Survey (CLHLS 2017-2018). Depression and anxiety symptoms were assessed using the 10-item Center for Epidemiologic Studies Depression Scale (CESD-10) and the Generalized Anxiety Disorder Scale-7 (GAD-7). A symptom network was constructed using the Extended Bayesian Information Criterion (EBIC) model and the Graphical Gaussian Model (GGM) with the Least Absolute Shrinkage and Selection Operator (LASSO) regularization. Central symptoms and bridge symptoms were identified using Expected Influence (EI) and bridge Expected Influence (bEI). The stability and accuracy of the network were evaluated through non-parametric bootstrap methods. Additionally, the Network Comparison Test (NCT) was employed to examine potential gender differences in network structure. Results: Network analyses revealed that the central symptoms of anxiety-depression network were CESD-3 (I felt sadness), GAD-2 (Not being able to stop or control worrying) and GAD-4 (Trouble relaxing). CESD-1(I was bothered by things that do not usually bother me), GAD-1 (Feeling nervous, anxious, or on edge) and GAD-3 (Worrying too much about different things) are critical bridge symptoms linking depression and anxiety. Furthermore, this study found that the anxiety-depression network among empty nesters did not exhibit gender differences. Conclusion: This study identified CESD-3 (I felt sadness), GAD-2 (Not being able to stop or control worrying), and GAD-4 (Trouble relaxing) as central symptoms in the anxiety-depression network among empty nesters. These findings provide critical insights for developing precise interventions aimed at mitigating the progression of anxiety and depression, improving mental health in this population, and ultimately promoting healthy aging.

Indexed as

anxietyChinadepressionempty nesternetwork analysis

Identifiers

PMID41050802
PMCPMC12488660

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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.