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

Author:

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.

Abstract

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

Publisher

Cambridge University Press (CUP)

Subject

Psychiatry and Mental health,Applied Psychology

Reference63 articles.

1. qgraph: Network Visualizations of Relationships in Psychometric Data

2. Association of symptom network structure with the course of longitudinal depression;van Borkulo;Journal of the American Medical Association (JAMA) Psychiatry,2015

3. Reconsidering anhedonia in depression: Lessons from translational neuroscience

4. The Impact of Individual Depressive Symptoms on Impairment of Psychosocial Functioning

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3