The Study of Psychopathology from the Network Analysis Perspective: A Systematic Review.


Journal

Psychotherapy and psychosomatics
ISSN: 1423-0348
Titre abrégé: Psychother Psychosom
Pays: Switzerland
ID NLM: 0024046

Informations de publication

Date de publication:
2019
Historique:
received: 22 11 2018
accepted: 29 01 2019
pubmed: 20 3 2019
medline: 14 6 2019
entrez: 20 3 2019
Statut: ppublish

Résumé

Network analysis (NA) is an analytical tool that allows one to explore the map of connections and eventual dynamic influences among symptoms and other elements of mental disorders. In recent years, the use of NA in psychopathology has rapidly grown, which calls for a systematic and critical analysis of its clinical utility. Following PRISMA guidelines, a systematic review of published empirical studies applying NA in psychopathology, between 2010 and 2017, was conducted. We included the literature published in PubMed and PsycINFO using as keywords any combination of "network analysis" with the terms "anxiety," "affective disorders," "depression," "schizophrenia," "psychosis," "personality disorders," "substance abuse" and "psychopathology." The review showed that NA has been applied in a plethora of mental disorders in adults (i.e., 13 studies on anxiety disorders; 19 on mood disorders; 7 on psychosis; 1 on substance abuse; 1 on borderline personality disorder; 18 on the association of symptoms between disorders), and 6 on childhood and adolescence. A critical examination of the results of each study suggests that NA helps to identify, in an innovative way, important aspects of psychopathology like the centrality of the symptoms in a given disorder as well as the mutual dynamics among symptoms. Yet, despite these promising results, the clinical utility of NA is still uncertain as there are important limitations on the analytic procedures (e.g., reliability of indices), the type of data included (e.g., typically restricted to secondary analysis of already published data), and ultimately, the psychometric and clinical validity of the results.

Sections du résumé

BACKGROUND
Network analysis (NA) is an analytical tool that allows one to explore the map of connections and eventual dynamic influences among symptoms and other elements of mental disorders. In recent years, the use of NA in psychopathology has rapidly grown, which calls for a systematic and critical analysis of its clinical utility.
METHODS
Following PRISMA guidelines, a systematic review of published empirical studies applying NA in psychopathology, between 2010 and 2017, was conducted. We included the literature published in PubMed and PsycINFO using as keywords any combination of "network analysis" with the terms "anxiety," "affective disorders," "depression," "schizophrenia," "psychosis," "personality disorders," "substance abuse" and "psychopathology."
RESULTS
The review showed that NA has been applied in a plethora of mental disorders in adults (i.e., 13 studies on anxiety disorders; 19 on mood disorders; 7 on psychosis; 1 on substance abuse; 1 on borderline personality disorder; 18 on the association of symptoms between disorders), and 6 on childhood and adolescence.
CONCLUSIONS
A critical examination of the results of each study suggests that NA helps to identify, in an innovative way, important aspects of psychopathology like the centrality of the symptoms in a given disorder as well as the mutual dynamics among symptoms. Yet, despite these promising results, the clinical utility of NA is still uncertain as there are important limitations on the analytic procedures (e.g., reliability of indices), the type of data included (e.g., typically restricted to secondary analysis of already published data), and ultimately, the psychometric and clinical validity of the results.

Identifiants

pubmed: 30889609
pii: 000497425
doi: 10.1159/000497425
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't Systematic Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

71-83

Informations de copyright

© 2019 S. Karger AG, Basel.

Auteurs

Alba Contreras (A)

Department of Clinical Psychology, School of Psychology, Complutense University, Madrid, Spain.

Ines Nieto (I)

Department of Clinical Psychology, School of Psychology, Complutense University, Madrid, Spain.

Carmen Valiente (C)

Department of Clinical Psychology, School of Psychology, Complutense University, Madrid, Spain, mcvalien@ucm.es.

Regina Espinosa (R)

Department of Psychology, School of Education and Health, Camilo José Cela University, Madrid, Spain.

Carmelo Vazquez (C)

Department of Clinical Psychology, School of Psychology, Complutense University, Madrid, Spain.

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Classifications MeSH