Separate personality traits from states to predict depression

Lee Anna Clark, Jeffrey Vittengl, Dolores Kraft, Robin B. Jarrett

Research output: Contribution to journalArticle

86 Scopus citations

Abstract

Results have been inconsistent regarding the ability of personality measures to predict future depression severity levels, leading some researchers to question the validity of personality assessment, especially when patients are acutely depressed. Using a combination of regression and factor analytic techniques, we separated the variance of personality measures into stable trait and variable state-affect components. Findings supported the hypotheses that depression severity measured at different time points would correlate with both stable trait and concurrent state-affect components in personality measures, whereas change in depression severity would correlate with state changes but not with stable trait scores. Thus, personality assessments tap both state affect and trait variance, with the state-affect variance masking the trait variance when patients are depressed.

Original languageEnglish (US)
Pages (from-to)152-172
Number of pages21
JournalJournal of Personality Disorders
Volume17
Issue number2
DOIs
StatePublished - Apr 1 2003

ASJC Scopus subject areas

  • Clinical Psychology
  • Psychiatry and Mental health

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