Evidence for the Network Theory of Mental Disorders in People at Ultra High Risk of and Diagnosed With Schizophrenia
Date
Authors
Buchwald, K
Vignes, M
Sandham, M
Narayanan, A
Williams, M
Siegert, R
Supervisor
Item type
Journal Article
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Publisher
University of California Press
Abstract
The network theory of mental disorders proposes that symptoms cause the expression of other symptoms. Research on the network theory is increasing, but empirical support is lacking. We aim to assess the viability of an integrated latent variable model and network model of psychopathology. We sourced 795 ultra-high-risk participants from the North American Prodromal Longitudinal Three Study and 1,446 participants with schizophrenia from the Clinical Antipsychotic Trials of Intervention Effectiveness study. We reconstructed a Bayesian network on the Scale of Psychosis Risk Symptoms and Positive and Negative Syndrome Scale on five training samples and then estimated the parameters on five test samples from each study, respectively. We compared the three models (Network model, latent variable model, and integrated model) on the five test samples from each assessment (30 models). The integrated model had a significantly superior fit than the LVM and had a better fit than the network model in all test samples. This novel finding provides partial support that items may interact and that networks with latent variables may be used to model the structure of an assessment if there is a poor fit to the latent variable model structure.Description
Keywords
52 Psychology, 5201 Applied and Developmental Psychology, Serious Mental Illness, Schizophrenia, Mental Illness, Brain Disorders, Clinical Research, Mental Health, 4.2 Evaluation of markers and technologies, Mental health, 3 Good Health and Well Being, 52 Psychology, symptom networks, latent variable model, structural equation model, Bayesian networks, schizophrenia
Source
Collabra Psychology, ISSN: 2474-7394 (Print); 2474-7394 (Online), University of California Press, 12(1). doi: 10.1525/collabra.158304
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This is an open access article distributed under the terms of the Creative Commons Attribution License (4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.