Extending the network perspective on comorbidity

Haig, Brian D.; Vertue, Frances M.

doi:10.1017/s0140525x10000762

Cited by 6 publications

(7 citation statements)

References 71 publications

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“…Network models are based on the premise that symptom inter-relationships reflect direct causal influences between symptoms, rather than underlying latent factors, as in the factor analysis framework. The exact relationship between factor and network models remains unclear, however (Molenaar, 2010; Ross, 2010), and various authors disagreed with the network proponents’ critique of the latent variable approach (Belzung et al 2010; Danks et al 2010; Haig & Vertue, 2010; Humphry & McGrane, 2010; Markus, 2010). Most importantly, no empirical comparison of these two approaches has yet been reported (Krueger et al 2010).…”

Section: Discussionmentioning

confidence: 99%

New insights into the correlation structure of DSM-IV depression symptoms in the general population v. subsamples of depressed individuals

Foster

Mohler‐Kuo

2017

Epidemiol Psychiatr Sci

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First, caution is warranted when considering studies assessing dimensions of depression because general population-based studies and studies of depressed individuals generate different data that can lead to different conclusions. This problem likely generalises to other models based on the symptoms' inter-relationships such as network models. Second, whereas the overall severity aligns individuals on a continuum of disorder intensity that allows non-affected individuals to be distinguished from affected individuals, the clinical evaluation and treatment of depressed individuals should focus directly on each individual's symptom profile.

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Section: Discussionmentioning

confidence: 99%

New insights into the correlation structure of DSM-IV depression symptoms in the general population v. subsamples of depressed individuals

Foster

Mohler‐Kuo

2017

Epidemiol Psychiatr Sci

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“…As we will explain, common cause models are in fact more complex and flexible than has been assumed in the psychological network literature: even if symptoms of a disorder have a common cause, this does not imply that the symptoms do not directly interact with each other (Danks et al, 2010;Haig & Vertue, 2010;Haslam, 2010;Humphry & McGrane, 2010).…”

Section: Don't Blame the Modelmentioning

confidence: 99%

“…In this paper, we will refer to this perspective as the network approach, which has become the standard expression in the literature (e.g., Borsboom, 2017b;Fried & Cramer, 2017). 1 When the network approach was introduced, several researchers cast doubt on the necessity to counterpose latent variable (or common cause) models and network models (see, e.g., Ashton & Lee, 2012;Danks, Fancsali, Glymour, & Scheines, 2010;Haig & Vertue, 2010;Humphry & McGrane, 2010;Krueger, DeYoung, & Markon, 2010;Markus, 2010;McFarland & Malta, 2010;Molenaar, 2010). This critique, however, has not changed the basic rationale for the network approach, which even in recent articles is still based on the contrast between latent variable and network models (e.g., Hofmann, Curtiss, & McNally, 2016;McNally, 2016;Nuijten et al, 2016;Robinaugh et al, 2014;van der Maas, Kan, Marsman, & Stevenson, 2017).…”

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confidence: 99%

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

Bringmann¹,

Eronen²

2018

Psychological Review

212

163

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Citation for published version (APA): Bringmann, L. F., & Eronen, M. I. (2018). Don't blame the model: Reconsidering the network approach to psychopathology. Psychological Review, 125(4), 606-615. https://doi.org/10.1037/rev0000108 Copyright Other than for strictly personal use, it is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license (like Creative Commons).Take-down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. 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.

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“…This approach is presented by its proponents as a radically new way of conceptualizing psychopathology; as a model of mental disorder that rejects the search for underlying cause/s of psychopathology, i.e., the essentialist or latent variable model (Borsboom et al, 2018). However, there is considerable debate over whether this is the case, or whether SNWM is simply a new and promising measurement tool (Bringmann & Eronen, 2018;Epskamp et al, 2017;Haig & Vertue, 2010;Humphry & McGrane, 2010;Molenaar, 2010;T. Ward & Fischer, 2019).…”

Section: Fuzzy Kindsmentioning

confidence: 99%

“…There is considerable debate over whether SNWM is really a new way of thinking about mental disorder, or simply a new and promising measurement tool (Bringmann & Eronen, 2018;Epskamp et al, 2017;Haig & Vertue, 2010;Humphry & McGrane, 2010;Molenaar, 2010). Following Ward and Fischer (2019), I consider SNWMs to be best thought of as phenomenal models 92 .…”

Section: Symptom Network Modeling [Snwm] Based Approachesmentioning

confidence: 99%

What is Mental Disorder? Developing an Embodied, Embedded, and Enactive Psychopathology

Nielsen¹

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<p>What we take mental disorder to be has implications for how researchers classify, explain, and treat mental disorders. It also shapes how the public treat those who are experiencing mental disorder. This is the often-underemphasized task of conceptualization, which sits at the foundation of psychopathology research. In this thesis I consider the nature of mental disorder through the lens of a growing perspective known as embodied enactivism. Embodied enactivism is a philosophical position on human functioning that holds the mind to be: embodied (non-cartesian, and constituted by both brain and body), embedded (richly influenced by the physical and social environment across development), and enactive (meaning and experience arise through the precarious organisms’ interactions with the world). After overviewing a selection of current conceptual positions – present either as independent conceptual frameworks or within our classification systems – I move to presenting my own conceptual framework of mental disorder grounded in an embodied, embedded, and enactive view. Some implications of this framework for the task of classification are explored, and a meta-methodological framework for developing explanations of psychopathology is developed. It is shown that the concept of mental disorder developed: moves beyond the internalist bias of many current concepts, recognizes the normative nature of disorder, encourages consideration of cultural and individual variance, does not unduly prioritize brain-level explanations of human behaviour, and can sit comfortably within a wholly natural world view.</p>

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Extending the network perspective on comorbidity

Cited by 6 publications

References 71 publications

New insights into the correlation structure of DSM-IV depression symptoms in the general population v. subsamples of depressed individuals

New insights into the correlation structure of DSM-IV depression symptoms in the general population v. subsamples of depressed individuals

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

What is Mental Disorder? Developing an Embodied, Embedded, and Enactive Psychopathology

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