Networks of major depressive disorder: A systematic review.

Depression Heterogeneity Network analysis Systematic review

Journal

Clinical psychology review
ISSN: 1873-7811
Titre abrégé: Clin Psychol Rev
Pays: United States
ID NLM: 8111117

Informations de publication

Date de publication:
04 2021
Historique:
received: 16 07 2020
revised: 06 01 2021
accepted: 23 02 2021
pubmed: 16 3 2021
medline: 26 10 2021
entrez: 15 3 2021
Statut: ppublish

Résumé

There has been a marked increase of network studies of Major Depressive Disorder (MDD). Despite rapidly growing contributions, their findings have yet to be systematically aggregated and examined. We therefore conducted a systematic review of depression network studies using PRISMA guidelines. A total of 254 clinical and population studies were collected from ISI's Web of Science and PsycINFO, between January 2010 to May 2020. A total of 23 between-subject studies were included for review, resulting in 58 cross-sectional networks. To determine their most critical symptoms and their connections, we analyzed strength centrality rankings, and aggregated the most robust symptoms connections into a summary network. Results indicated substantial variability between study samples, depression measures, and network features. Fatigue and Depressed Mood were the most central symptoms, while Weight changes tended to have the weakest centrality. Depressed Mood and Fatigue formed two separated symptoms communities characterized by recurrent connections, with Mood-Anhedonia as the most frequent edge of MDD. Network analysis informed our understanding of MDD, suggesting the critical role of Fatigue and Depressed Mood. The study's findings are discussed in their clinical and methodological implications, including future directions for network studies of MDD.

Identifiants

pubmed: 33721606
pii: S0272-7358(21)00043-X
doi: 10.1016/j.cpr.2021.102000
pii:
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Review Systematic Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

102000

Subventions

Organisme : NIMH NIH HHS
ID : R01 MH091034
Pays : United States

Informations de copyright

Copyright © 2021 Elsevier Ltd. All rights reserved.

Auteurs

Matteo Malgaroli (M)

Department of Psychiatry, NYU Grossman School of Medicine, New York, NY, United States of America. Electronic address: matteo.malgaroli@nyulangone.org.

Adam Calderon (A)

Department of Clinical Psychology, Teachers College, Columbia University, New York, NY, United States of America.

George A Bonanno (GA)

Department of Clinical Psychology, Teachers College, Columbia University, New York, NY, United States of America.

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Classifications MeSH