Format

Send to

Choose Destination
Psychol Med. 2016 Dec;46(16):3359-3369. Epub 2016 Sep 14.

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

Author information

1
McLean Hospital/Harvard Medical School,Belmont, MA,USA.
2
University of Amsterdam,Haarlem,The Netherlands.
3
Department of Psychology,Emory University,Atlanta, GA,USA.
4
Department of Psychology,Southern Illinois University,Carbondale, IL,USA.

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.

KEYWORDS:

Anxiety; causal systems; co-morbidity; depression; network analysis

PMID:
27623748
PMCID:
PMC5430082
DOI:
10.1017/S0033291716002300
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Cambridge University Press Icon for PubMed Central
Loading ...
Support Center