The network structure of psychopathology in a community sample of preadolescents

Lynn Boschloo, Robert A Schoevers, Claudia D van Borkulo, Denny Borsboom, Albertine J Oldehinkel

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Psychopathology is often classified according to diagnostic categories or scale scores. These ignore potentially important information about associations between specific symptoms and, consequently, lead to heterogeneous constructs that may mask relevant individual differences. Network analyses focus on these specific symptom associations, providing the opportunity to explore the complex structure of psychopathology in more detail. We examined the empirical network structure of 95 emotional and behavioral problems of the Youth Self-Report (YSR) to explore how well this structure reflected the predefined YSR domains. The study was conducted in a large community sample (N = 2,175) of preadolescents (mean age = 11.1, SD = 0.6 years), and the network structure was determined by means of the recently developed network analysis technique, eLasso. Although problems within the same domain, in general, showed more and stronger connections than problems belonging to different domains, some problems showed substantially more or stronger associations than others; consequently, problems cannot be considered interchangeable indicators of their domain. Furthermore, no sharp boundaries were found between the domains as specific symptom pairs of different domains showed strong connections. Taken together, our findings indicate that network models provide a promising addition to the more traditional way of distinguishing diagnoses or scale scores. (PsycINFO Database Record

Original languageEnglish
Pages (from-to)599-606
Number of pages8
JournalJournal of Abnormal Psychology
Volume125
Issue number4
DOIs
Publication statusPublished - May 2016

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Psychopathology
Self Report
Masks
Individuality
Problem Behavior

Keywords

  • Affective Symptoms/complications
  • Antisocial Personality Disorder/complications
  • Child
  • Female
  • Humans
  • Male
  • Models, Psychological
  • Psychiatric Status Rating Scales
  • Self Report
  • Sensitivity and Specificity
  • Social Behavior Disorders/complications

Cite this

Boschloo, Lynn ; Schoevers, Robert A ; van Borkulo, Claudia D ; Borsboom, Denny ; Oldehinkel, Albertine J. / The network structure of psychopathology in a community sample of preadolescents. In: Journal of Abnormal Psychology. 2016 ; Vol. 125, No. 4. pp. 599-606.
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Boschloo, L, Schoevers, RA, van Borkulo, CD, Borsboom, D & Oldehinkel, AJ 2016, 'The network structure of psychopathology in a community sample of preadolescents' Journal of Abnormal Psychology, vol. 125, no. 4, pp. 599-606. https://doi.org/10.1037/abn0000150

The network structure of psychopathology in a community sample of preadolescents. / Boschloo, Lynn; Schoevers, Robert A; van Borkulo, Claudia D; Borsboom, Denny; Oldehinkel, Albertine J.

In: Journal of Abnormal Psychology, Vol. 125, No. 4, 05.2016, p. 599-606.

Research output: Contribution to JournalArticleAcademicpeer-review

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N2 - Psychopathology is often classified according to diagnostic categories or scale scores. These ignore potentially important information about associations between specific symptoms and, consequently, lead to heterogeneous constructs that may mask relevant individual differences. Network analyses focus on these specific symptom associations, providing the opportunity to explore the complex structure of psychopathology in more detail. We examined the empirical network structure of 95 emotional and behavioral problems of the Youth Self-Report (YSR) to explore how well this structure reflected the predefined YSR domains. The study was conducted in a large community sample (N = 2,175) of preadolescents (mean age = 11.1, SD = 0.6 years), and the network structure was determined by means of the recently developed network analysis technique, eLasso. Although problems within the same domain, in general, showed more and stronger connections than problems belonging to different domains, some problems showed substantially more or stronger associations than others; consequently, problems cannot be considered interchangeable indicators of their domain. Furthermore, no sharp boundaries were found between the domains as specific symptom pairs of different domains showed strong connections. Taken together, our findings indicate that network models provide a promising addition to the more traditional way of distinguishing diagnoses or scale scores. (PsycINFO Database Record

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KW - Models, Psychological

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KW - Self Report

KW - Sensitivity and Specificity

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