体验采样法的时间网络将睡眠障碍确定为广泛性焦虑障碍的核心症状。

Temporal network of experience sampling methodology identifies sleep disturbance as a central symptom in generalized anxiety disorder.

机构信息

Mental Health Education Center, Chengdu University, 610106, Chengdu, China.

University of Amsterdam, 1018WB, Amsterdam, the Netherlands.

出版信息

BMC Psychiatry. 2024 Mar 29;24(1):241. doi: 10.1186/s12888-024-05698-z.

Abstract

BACKGROUND

A temporal network of generalized anxiety disorder (GAD) symptoms could provide valuable understanding of the occurrence and maintenance of GAD. We aim to obtain an exploratory conceptualization of temporal GAD network and identify the central symptom.

METHODS

A sample of participants (n = 115) with elevated GAD-7 scores (Generalized Anxiety Disorder 7-Item Questionnaire [GAD-7] ≥ 10) participated in an online daily diary study in which they reported their GAD symptoms based on DSM-5 diagnostic criteria (eight symptoms in total) for 50 consecutive days. We used a multilevel VAR model to obtain the temporal network.

RESULTS

In temporal network, a lot of lagged relationships exist among GAD symptoms and these lagged relationships are all positive. All symptoms have autocorrelations and there are also some interesting feedback loops in temporal network. Sleep disturbance has the highest Out-strength centrality.

CONCLUSIONS

This study indicates how GAD symptoms interact with each other and strengthen themselves over time, and particularly highlights the relationships between sleep disturbance and other GAD symptoms. Sleep disturbance may play an important role in the dynamic development and maintenance process of GAD. The present study may develop the knowledge of the theoretical model, diagnosis, prevention and intervention of GAD from a temporal symptoms network perspective.

摘要

背景

广泛性焦虑障碍(GAD)症状的时间网络可以为理解 GAD 的发生和维持提供有价值的信息。我们旨在对时间性 GAD 网络进行探索性概念化,并确定核心症状。

方法

一个具有较高 GAD-7 评分(GAD-7 [Generalized Anxiety Disorder 7-Item Questionnaire]≥10)的参与者样本(n=115)参加了一项在线日常日记研究,他们根据 DSM-5 诊断标准(总共 8 个症状)在 50 天内报告他们的 GAD 症状。我们使用多层 VAR 模型获得时间网络。

结果

在时间网络中,GAD 症状之间存在大量滞后关系,且这些滞后关系均为正相关。所有症状均具有自相关性,时间网络中也存在一些有趣的反馈回路。睡眠障碍的出度中心性最高。

结论

本研究表明 GAD 症状如何随时间相互作用并自我加强,特别是突出了睡眠障碍与其他 GAD 症状之间的关系。睡眠障碍可能在 GAD 的动态发展和维持过程中发挥重要作用。本研究可能从时间性症状网络的角度发展 GAD 的理论模型、诊断、预防和干预方面的知识。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4416/10981297/ebb2108f9870/12888_2024_5698_Figa_HTML.jpg

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