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网络分析中国抑郁障碍患者躯体症状。

Network analysis of somatic symptoms in Chinese patients with depressive disorder.

机构信息

Department of Nursing, Air Force Military Medical University, Xi'an, Shanxi, China.

School of Nursing, Fudan University, Shanghai, China.

出版信息

Front Public Health. 2023 Mar 13;11:1079873. doi: 10.3389/fpubh.2023.1079873. eCollection 2023.

DOI:10.3389/fpubh.2023.1079873
PMID:36992877
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10040552/
Abstract

INTRODUCTION

Network theory conceptualizes somatic symptoms as a network of individual symptoms that are interconnected and influenced by each other. In this conceptualization, the network's central symptoms have the strongest effect on other symptoms. Clinical symptoms of patients with depressive disorders are largely determined by their sociocultural context. To our knowledge, no previous study has investigated the network structure of somatic symptoms among Chinese patients with depressive disorders. The aim of this study was to characterize the somatic symptoms network structure in patients with depressive disorders in Shanghai, China.

METHOD

A total of 177 participants were recruited between October 2018 and June 2019. The Chinese version of the Patient Health Questionnaire-15 was used to assess somatic symptoms. In order to quantify the somatic symptom network structure, indicators of "closeness," "strength," and "betweenness" were employed as identifiers for network-central symptoms.

RESULT

The symptoms of "feeling your heart pound or race," "shortness of breath," and "back pain" had the highest centrality values, indicating that these symptoms were central to the somatic symptom networks. Feeling tired or mentally ill had the strongest positive correlation with insomnia or other sleep problems ( = 0.419), followed by chest pain and breathlessness ( = 0.334), back pain, and limb or joint pain ( = 0.318).

DISCUSSION

Psychological and neurobiological research that offers insights into somatic symptoms may focus on these central symptoms as targets for treatment and future research.

摘要

简介

网络理论将躯体症状概念化为个体症状相互关联和相互影响的网络。在这种概念化中,网络的中心症状对其他症状的影响最大。抑郁症患者的临床症状在很大程度上取决于他们的社会文化背景。据我们所知,以前没有研究调查过中国抑郁症患者躯体症状的网络结构。本研究旨在描述中国上海抑郁症患者的躯体症状网络结构。

方法

共招募了 177 名参与者,时间为 2018 年 10 月至 2019 年 6 月。使用中文版患者健康问卷-15 评估躯体症状。为了量化躯体症状网络结构,采用“接近度”、“强度”和“中介度”作为网络中心症状的标识符。

结果

“心跳或心悸”、“呼吸急促”和“背痛”这三种症状的中心性值最高,表明这些症状是躯体症状网络的中心。疲倦或精神疾病与失眠或其他睡眠问题的相关性最强(=0.419),其次是胸痛和呼吸急促(=0.334)、背痛、四肢或关节疼痛(=0.318)。

讨论

有助于深入了解躯体症状的心理和神经生物学研究可以将这些中心症状作为治疗和未来研究的目标。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ebb/10040552/c002b01a5a3d/fpubh-11-1079873-g0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ebb/10040552/817b6b7e57d9/fpubh-11-1079873-g0001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ebb/10040552/f8dc7cd3bd74/fpubh-11-1079873-g0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ebb/10040552/c002b01a5a3d/fpubh-11-1079873-g0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ebb/10040552/817b6b7e57d9/fpubh-11-1079873-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ebb/10040552/50a182ead724/fpubh-11-1079873-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ebb/10040552/8880ba51afd2/fpubh-11-1079873-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ebb/10040552/ad20278e0274/fpubh-11-1079873-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ebb/10040552/f8dc7cd3bd74/fpubh-11-1079873-g0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ebb/10040552/c002b01a5a3d/fpubh-11-1079873-g0006.jpg

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2
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Arch Psychiatr Nurs. 2022 Jun;38:6-13. doi: 10.1016/j.apnu.2022.01.004. Epub 2022 Jan 29.
3
Time for united action on depression: a Lancet-World Psychiatric Association Commission.
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BMC Cancer. 2025 May 14;25(1):872. doi: 10.1186/s12885-025-14256-z.
4
Understanding the complex network of anxiety, depression, sleep problems, and smartphone addiction among college art students using network analysis.运用网络分析方法了解高校艺术专业学生中焦虑、抑郁、睡眠问题和智能手机成瘾之间的复杂网络关系。
Front Psychiatry. 2025 Mar 4;16:1533757. doi: 10.3389/fpsyt.2025.1533757. eCollection 2025.
5
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7
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9
Measurement Properties of the Patient Health Questionnaire-15 and Somatic Symptom Scale-8: A Systematic Review and Meta-Analysis.患者健康问卷-15 和躯体症状量表-8 的测量特性:系统评价和荟萃分析。
JAMA Netw Open. 2024 Nov 4;7(11):e2446603. doi: 10.1001/jamanetworkopen.2024.46603.
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Lancet Psychiatry. 2022 Feb;9(2):137-150. doi: 10.1016/S2215-0366(21)00395-3. Epub 2022 Jan 10.
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9
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10
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