Evidence map›Paper›PMID 40969708›Full record

ArticleFrontiers in psychiatry2025

Network analysis of depressive symptoms in Chinese outpatients with somatic symptom disorder.

Yihui Li, Junning Fang, Yunhui Zhong, Yibo Li, Yuanping Liao, Hong Tang

Abstract read
In one paragraph

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

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2citing papers in PubMed
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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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5 · Who and what money

Authors and funding

6 authors.

Yihui LiDepartment of Psychology, Gannan Medical University, Ganzhou, Ganzhou, Jiangxi, China.
Junning FangDepartment of Psychology, Gannan Medical University, Ganzhou, Ganzhou, Jiangxi, China.
Yunhui ZhongThe Third People's Hospital of Ganzhou, Ganzhou, Jiangxi, China.
Yibo LiDepartment of Psychiatry and Psychology, College of Basic Medical Sciences, Tianjin Medical University, Tianjin, China.
Yuanping LiaoThe Third People's Hospital of Ganzhou, Ganzhou, Jiangxi, China.
Hong TangDepartment of Psychology, Gannan Medical University, Ganzhou, Ganzhou, Jiangxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Somatic symptom disorder and depression in clinical practice are strongly correlated. In this study, network analysis was used to assess the depressive symptoms of patients with somatic symptom disorder to identify the most core and influential symptoms. The aim of this study was to provide new perspectives for the treatment and rehabilitation of patients with somatic symptom disorder. Methods: A total of 899 individuals were enrolled from Gannan Medical University's First Affiliated Hospital, Ganzhou People's Hospital, and Third People's Hospital of Ganzhou. A version of the Patient Health Questionnaire-9 was administered to assess symptoms of depression. We described the network structure of depressive symptoms, utilizing indicators of "strength," "betweenness," and "closeness" to identify the key symptoms within the network. A bootstrap approach with case-dropping was used to test the network's stability. Results: Concentration (PHQ7), Motor (PHQ8), and Anhedonia (PHQ1) symptoms had the highest centrality values, the strength values are 1.67, 1.62, and 1.58 respectively. The edge connecting sad mood (PHQ2) and energy (PHQ4) were the most influential in the model, with an edge weight of 0.69, the highest among all edges. Conclusions: This network analysis study identifies distinct depressive symptomatology within the Chinese SSD patient population. Core symptoms anhedonia, cognition, and motivation primarily drive depressive symptoms, underscoring the need for clinical focus on these manifestations to prevent exacerbation. Tailored interventions targeting these core symptoms, including the integration of pleasant experiences, dopamine-based medications, attention bias modification training, and behavioral activation therapy, should be considered in treatment strategies.

Indexed as

Chinese outpatientsdepressive symptomsnetwork accuracy and stabilitynetwork analysissomatic symptom disorder

Identifiers

PMID40969708
PMCPMC12440883

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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.