title: What are 'good' depression symptoms? Comparing the centrality of DSM and non-DSM symptoms of depression in a network analysis.
abstract: BACKGROUND
  The symptoms for Major Depression (MD) defined in the DSM-5 differ markedly from symptoms assessed in common rating scales, and the empirical question about core depression symptoms is unresolved. Here we conceptualize depression as a complex dynamic system of interacting symptoms to examine what symptoms are most central to driving depressive processes.
  
  
  METHODS
  We constructed a network of 28 depression symptoms assessed via the Inventory of Depressive Symptomatology (IDS-30) in 3,463 depressed outpatients from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study. We estimated the centrality of all IDS-30 symptoms, and compared the centrality of DSM and non-DSM symptoms; centrality reflects the connectedness of each symptom with all other symptoms.
  
  
  RESULTS
  A network with 28 intertwined symptoms emerged, and symptoms differed substantially in their centrality values. Both DSM symptoms (e.g., sad mood) and non-DSM symptoms (e.g., anxiety) were among the most central symptoms, and DSM criteria were not more central than non-DSM symptoms.
  
  
  CONCLUSIONS
  Many subjects enrolled in STAR*D reported comorbid medical and psychiatric conditions which may have affected symptom presentation.
  
  
  CONCLUSIONS
  The network perspective neither supports the standard psychometric notion that depression symptoms are equivalent indicators of MD, nor the common assumption that DSM symptoms of depression are of higher clinical relevance than non-DSM depression symptoms. The findings suggest the value of research focusing on especially central symptoms to increase the accuracy of predicting outcomes such as the course of illness, probability of relapse, and treatment response.
authors.affiliation: Faculty of Psychology and Educational Sciences, University of Leuven, Leuven, Belgium. Electronic address: Eiko.Fried@gmail.com.
authors.forename: Eiko I
authors.initials: EI
authors.lastname: Fried
authors.affiliation: Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands.
authors.forename: Sacha
authors.initials: S
authors.lastname: Epskamp
authors.affiliation: School of Life Sciences, Arizona State University, Tempe, USA.
authors.forename: Randolph M
authors.initials: RM
authors.lastname: Nesse
authors.affiliation: Faculty of Psychology and Educational Sciences, University of Leuven, Leuven, Belgium.
authors.forename: Francis
authors.initials: F
authors.lastname: Tuerlinckx
authors.affiliation: Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands.
authors.forename: Denny
authors.initials: D
authors.lastname: Borsboom
mesh_terms: D000328:Adult; D015897:Comorbidity; D003863:Depression / Q000175:diagnosis* / Q000523:psychology; D003865:Major Depressive Disorder / Q000175:diagnosis* / Q000523:psychology; D039721:Diagnostic and Statistical Manual of Mental Disorders; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D011594:Psychometrics; D063189:Symptom Assessment
keywords: Centrality; Depression symptoms; Major depression; Network analysis