title: The small world of psychopathology.
abstract: BACKGROUND
  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).
  
  
  RESULTS
  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.
  
  
  CONCLUSIONS
  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.
authors: Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands. d.borsboom@uva.nl
authors: Denny
authors: D
authors: Borsboom
authors: Angélique O J
authors: AO
authors: Cramer
authors: Verena D
authors: VD
authors: Schmittmann
authors: Sacha
authors: S
authors: Epskamp
authors: Lourens J
authors: LJ
authors: Waldorp
mesh_terms: D003198:Computer Simulation; D039721:Diagnostic and Statistical Manual of Mental Disorders; D006801:Humans; D007255:Information Services; D001523:Mental Disorders / Q000175:diagnosis* / Q000523:psychology*; D011569:Psychiatric Status Rating Scales; D011599:Psychopathology