Further evidence that psychopathology networks have limited replicability and utility: Response to Borsboom et al. (2017) and Steinley et al. (2017)

Miriam K. Forbes, Aidan G.C. Wright, Kristian E. Markon, Robert Krueger

Research output: Contribution to journalLetterpeer-review

71 Scopus citations

Abstract

In our target article, we tested the replicability of 4 popular psychopathology network estimation methods that aim to reveal causal relationships among symptoms of mental illness. We started with the focal data set from the 2 foundational psychopathology network papers (i.e., the National Comorbidity Survey-Replication) and identified the National Survey of Mental Health and Wellbeing as a close methodological match for comparison. We compared the psychopathology networks estimated in each data set-as well as in 10 sets of random split-halves within each data set-with the goal of quantifying the replicability of the network parameters as they are interpreted in the extant psychopathology network literature. We concluded that current psychopathology network methods have limited replicability both within and between samples and thus have limited utility. Here we respond to the 2 commentaries on our target article, concluding that the findings of Steinley, Hoffman, Brusco, and Sher (2017)-along with other recent developments in the literature-provide further conclusive evidence that psychopathology networks have poor replicability and utility.

Original languageEnglish (US)
Pages (from-to)1011-1016
Number of pages6
JournalJournal of abnormal psychology
Volume126
Issue number7
DOIs
StatePublished - Oct 2017

Bibliographical note

Publisher Copyright:
© 2017 American Psychological Association.

Keywords

  • Network analysis
  • Psychopathology networks
  • Replication crisis

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