Intraindividual Dynamic Network Analysis – Implications for Clinical Assessment

Sarah Jo David, Andrew J. Marshall, Emma K. Evanovich, Gregory H. Mumma

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

A network analysis approach to psychopathology regards symptoms as mutually interacting components of a multifaceted system (Borsboom & Cramer, 2013). Although several studies using this approach have examined comorbidity between disorders using cross-sectional samples, a direct application of the network analysis approach to intraindividual dynamic relations between symptoms in a complex, comorbid case has not been reported. The current article describes an intraindividual dynamic network analysis (IDNA) approach to understanding the psychopathology of an individual using dynamic (over time) lead-lag interrelations between symptoms. Multivariate time series data were utilized to create and examine an intraindividual, lag-1 network of the partial, day-to-day relations of symptoms in an individual with comorbid mood and anxiety disorders. Characteristics of the network, including centrality indices, stability, dynamic processes between symptoms, and their implications for clinical assessment are described. Additional clinical implications and future directions for IDNA, including the potential incremental validity of this assessment approach for empirically-based idiographic assessment and personalized treatment planning, are discussed. This person-specific IDNA approach may be especially useful in complex and comorbid cases.

Original languageEnglish
Pages (from-to)235-248
Number of pages14
JournalJournal of Psychopathology and Behavioral Assessment
Volume40
Issue number2
DOIs
StatePublished - Jun 1 2018

Keywords

  • Comorbidity
  • Dynamic
  • Intraindividual
  • Network analysis
  • Personalized treatment planning

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