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精神病样本中抑郁与焦虑症状关系的网络分析

Network analysis of depression and anxiety symptom relationships in a psychiatric sample.

作者信息

Beard C, Millner A J, Forgeard M J C, Fried E I, Hsu K J, Treadway M T, Leonard C V, Kertz S J, Björgvinsson T

机构信息

McLean Hospital/Harvard Medical School,Belmont, MA,USA.

University of Amsterdam,Haarlem,The Netherlands.

出版信息

Psychol Med. 2016 Dec;46(16):3359-3369. doi: 10.1017/S0033291716002300. Epub 2016 Sep 14.

DOI:10.1017/S0033291716002300
PMID:27623748
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5430082/
Abstract

BACKGROUND

Researchers have studied psychological disorders extensively from a common cause perspective, in which symptoms are treated as independent indicators of an underlying disease. In contrast, the causal systems perspective seeks to understand the importance of individual symptoms and symptom-to-symptom relationships. In the current study, we used network analysis to examine the relationships between and among depression and anxiety symptoms from the causal systems perspective.

METHOD

We utilized data from a large psychiatric sample at admission and discharge from a partial hospital program (N = 1029, mean treatment duration = 8 days). We investigated features of the depression/anxiety network including topology, network centrality, stability of the network at admission and discharge, as well as change in the network over the course of treatment.

RESULTS

Individual symptoms of depression and anxiety were more related to other symptoms within each disorder than to symptoms between disorders. Sad mood and worry were among the most central symptoms in the network. The network structure was stable both at admission and between admission and discharge, although the overall strength of symptom relationships increased as symptom severity decreased over the course of treatment.

CONCLUSIONS

Examining depression and anxiety symptoms as dynamic systems may provide novel insights into the maintenance of these mental health problems.

摘要

背景

研究人员从共同病因的角度对心理障碍进行了广泛研究,在这种视角下,症状被视为潜在疾病的独立指标。相比之下,因果系统视角试图理解个体症状以及症状与症状之间关系的重要性。在当前研究中,我们从因果系统视角使用网络分析来检验抑郁症状和焦虑症状之间的关系。

方法

我们利用了来自一个大型精神病样本的数据,该样本来自一个部分住院项目的入院和出院时的数据(N = 1029,平均治疗时长 = 8天)。我们研究了抑郁/焦虑网络的特征,包括拓扑结构、网络中心性、入院和出院时网络的稳定性,以及治疗过程中网络的变化。

结果

抑郁和焦虑的个体症状在每种障碍内与其他症状的关联比在不同障碍的症状之间的关联更强。悲伤情绪和担忧是网络中最核心的症状。网络结构在入院时以及入院和出院之间都是稳定的,尽管随着治疗过程中症状严重程度的降低,症状关系的总体强度增加了。

结论

将抑郁和焦虑症状视为动态系统来研究,可能会为这些心理健康问题的维持提供新的见解。

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