Literature DB >> 29952625

Don't blame the model: Reconsidering the network approach to psychopathology.

Laura F Bringmann1, Markus I Eronen2.   

Abstract

The network approach to psychopathology is becoming increasingly popular. The motivation for this approach is to provide a replacement for the problematic common cause perspective and the associated latent variable model, where symptoms are taken to be mere effects of a common cause (the disorder itself). The idea is that the latent variable model is plausible for medical diseases, but unrealistic for mental disorders, which should rather be conceptualized as networks of directly interacting symptoms. We argue that this rationale for the network approach is misguided. Latent variable (or common cause) models are not inherently problematic, and there is not even a clear boundary where network models end and latent variable (or common cause) models begin. We also argue that focusing on this contrast has led to an unrealistic view of testing and finding support for the network approach, as well as an oversimplified picture of the relationship between medical diseases and mental disorders. As an alternative, we point out more essential contrasts, such as the contrast between dynamic and static modeling approaches that can provide a better framework for conceptualizing mental disorders. Finally, we discuss several topics and open problems that need to be addressed in order to make the network approach more concrete and to move the field of psychological network research forward. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

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Mesh:

Year:  2018        PMID: 29952625     DOI: 10.1037/rev0000108

Source DB:  PubMed          Journal:  Psychol Rev        ISSN: 0033-295X            Impact factor:   8.934


  37 in total

1.  The network approach to psychopathology: a review of the literature 2008-2018 and an agenda for future research.

Authors:  Donald J Robinaugh; Ria H A Hoekstra; Emma R Toner; Denny Borsboom
Journal:  Psychol Med       Date:  2019-12-26       Impact factor: 7.723

2.  On the equivalency of factor and network loadings.

Authors:  Alexander P Christensen; Hudson Golino
Journal:  Behav Res Methods       Date:  2021-01-06

3.  Main Symptomatic Treatment Targets in Suspected and Early Psychosis: New Insights From Network Analysis.

Authors:  Natalia Jimeno; Javier Gomez-Pilar; Jesus Poza; Roberto Hornero; Kai Vogeley; Eva Meisenzahl; Theresa Haidl; Marlene Rosen; Joachim Klosterkötter; Frauke Schultze-Lutter
Journal:  Schizophr Bull       Date:  2020-07-08       Impact factor: 9.306

4.  Extending our understanding of the association between posttraumatic stress disorder and positive emotion dysregulation: A network analysis approach.

Authors:  Nicole H Weiss; Ateka A Contractor; Alexa M Raudales; Talya Greene; Nicole A Short
Journal:  J Anxiety Disord       Date:  2020-02-25

5.  Network Analysis of ADHD and ODD Symptoms: Novel Insights or Redundant Findings with the Latent Variable Model?

Authors:  Jonathan Preszler; G Leonard Burns
Journal:  J Abnorm Child Psychol       Date:  2019-10

Review 6.  Network Analysis as an Alternative Approach to Conceptualizing Eating Disorders: Implications for Research and Treatment.

Authors:  Cheri A Levinson; Irina A Vanzhula; Leigh C Brosof; Kelsie Forbush
Journal:  Curr Psychiatry Rep       Date:  2018-08-06       Impact factor: 5.285

7.  The replicability and generalizability of internalizing symptom networks across five samples.

Authors:  Carter J Funkhouser; Kelly A Correa; Stephanie M Gorka; Brady D Nelson; K Luan Phan; Stewart A Shankman
Journal:  J Abnorm Psychol       Date:  2019-12-12

8.  Digital phenotyping for psychiatry: Accommodating data and theory with network science methodologies.

Authors:  D M Lydon-Staley; I Barnett; T D Satterthwaite; D S Bassett
Journal:  Curr Opin Biomed Eng       Date:  2018-12-14

9.  Quantifying the Reliability and Replicability of Psychopathology Network Characteristics.

Authors:  Miriam K Forbes; Aidan G C Wright; Kristian E Markon; Robert F Krueger
Journal:  Multivariate Behav Res       Date:  2019-05-29       Impact factor: 5.923

10.  Network structures and temporal stability of self- and informant-rated affective symptoms in Alzheimer's disease.

Authors:  T T Saari; I Hallikainen; T Hintsa; A M Koivisto
Journal:  J Affect Disord       Date:  2020-07-19       Impact factor: 4.839

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