The Small World of Psychopathology

Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands.
PLoS ONE (Impact Factor: 3.23). 11/2011; 6(11):e27407. DOI: 10.1371/journal.pone.0027407
Source: PubMed


Mental disorders are highly comorbid: people having one disorder are likely to have another as well. We explain empirical comorbidity patterns based on a network model of psychiatric symptoms, derived from an analysis of symptom overlap in the Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV).
We show that a) half of the symptoms in the DSM-IV network are connected, b) the architecture of these connections conforms to a small world structure, featuring a high degree of clustering but a short average path length, and c) distances between disorders in this structure predict empirical comorbidity rates. Network simulations of Major Depressive Episode and Generalized Anxiety Disorder show that the model faithfully reproduces empirical population statistics for these disorders.
In the network model, mental disorders are inherently complex. This explains the limited successes of genetic, neuroscientific, and etiological approaches to unravel their causes. We outline a psychosystems approach to investigate the structure and dynamics of mental disorders.

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Available from: Angelique Cramer
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    • "Occasioned by patterns of extensive diagnostic co-occurrence, there has been substantial interest in mapping the fundamental nature of psychopathology using quantitative modeling techniques (e.g., Krueger, 1999; Krueger and Markon, 2006; Cramer et al., 2010; Borsboom et al., 2011; Kotov et al., 2011; Wigman et al., 2015). Prime examples of these efforts include the empirically identified Internalizing (e.g., unipolar mood disorders, anxiety disorders) and Externalizing (e.g., substance use, antisocial behavior) spectra (e.g., Achenbach, 1966; Krueger, 1999; Wright et al., 2013). "
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