title: Network analysis of substance abuse and dependence symptoms.
abstract: BACKGROUND
  The DSM uses one set of abuse and dependence criteria to assess multiple substance use disorders (SUDs). Most SUD research aggregates across these symptoms to study the behavior of SUD as a static construct. We use an alternative approach that conceptualizes symptoms as directly interacting variables in psychopathological networks. We apply network models to symptom-level data to investigate the unique roles of individual symptoms and their interactions in SUD.
  
  
  METHODS
  We analyzed 11 DSM III-R/IV abuse and dependence criteria in a sample of 2405 adult twins who reported use of at least one illicit substance six or more times from the Virginia Adult Twin Study of Psychiatric and Substance Use Disorders (VATSPSUD). We estimated a symptom network for each substance class as well as a global network collapsed across all substance classes. We examined similarities and differences across the 6 networks in terms of symptom-to-symptom connections and symptom centrality.
  
  
  RESULTS
  The global network model revealed several interesting symptom connections, such as a strong predictive relation between tolerance and more-than-planned substance use. The most central symptom was using a drug more than planned. In addition, several interesting differences across substances emerged, both in the strength of symptom connections as well as the centrality of symptoms to each network.
  
  
  CONCLUSIONS
  When analyzed as networks, abuse and dependence symptoms do not function equivalently across illicit substance classes. These findings suggest the value of analyzing individual symptoms and their associations to gain new insight into the mechanisms of SUD.
authors.affiliation: Department of Psychology, University of Amsterdam, The Netherlands. Electronic address: MRhemtulla@uva.nl.
authors.forename: Mijke
authors.initials: M
authors.lastname: Rhemtulla
authors.affiliation: Faculty of Psychology and Educational Sciences, University of Leuven, Belgium.
authors.forename: Eiko I
authors.initials: EI
authors.lastname: Fried
authors.affiliation: Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA; Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA.
authors.forename: Steven H
authors.initials: SH
authors.lastname: Aggen
authors.affiliation: Faculty of Psychology and Educational Sciences, University of Leuven, Belgium.
authors.forename: Francis
authors.initials: F
authors.lastname: Tuerlinckx
authors.affiliation: Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA; Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA; Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA.
authors.forename: Kenneth S
authors.initials: KS
authors.lastname: Kendler
authors.affiliation: Department of Psychology, University of Amsterdam, The Netherlands.
authors.forename: Denny
authors.initials: D
authors.lastname: Borsboom
mesh_terms: D000328:Adult; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D008960:Models, Psychological; D019966:Substance-Related Disorders / Q000175:diagnosis* / Q000523:psychology*; D014427:Twins / Q000523:psychology; D014768:Virginia; D055815:Young Adult
keywords: Network analysis; Substance abuse; Substance use disorders; Symptom interactions