Daily dynamics of negative affect: indicators of rate of response to treatment and remission from depression?

Marieke A. Helmich*, M. Wichers, Frenk Peeters, Evelien Snippe

*Corresponding author for this work

Research output: Working paperPreprintAcademic

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Abstract

More instability (MSSD) and variability (SD) of negative affect (NA) have been related to current and future depressive symptoms. We investigated whether MSSD and SD of NA were predictive of the rate of symptom improvement during treatment and of reaching remission status. Forty-six individuals with major depressive disorder completed six days of ecological momentary assessments (10 beeps per day)before starting a combination of pharmacotherapy and supportive therapy. During and after treatment, the Hamilton Depression Rating Scale (HDRS) diagnostic interview was performed monthly for 18 months. Using multilevel modeling and logistic regression, a linear decrease in HDRS scores as well as reaching remission status (HDRS of ≤7 within or after five months) were predicted by the mean, SD and MSSD of NA in momentary assessments, and relevant baseline predictors. MeanNA, but not the SD orMSSDof NA, predicted rates of depressive symptom reduction over five months. The odds of remitting during treatment were not associated with any predictors. Our results suggest that pre-treatment assessments ofNA instability and variability may not give an indication of the treatment response over time. Clinically, the mean of NA may be more promising as a baseline indicator of response potential.
Original languageEnglish
PublisherPsyArXiv Preprints
Number of pages27
DOIs
Publication statusPublished - 1-Nov-2021

Keywords

  • major depressive disorder
  • depression
  • treatment response
  • remission
  • emotion
  • negative affect
  • affect dynamics
  • variability
  • instability
  • destabilization
  • antidepressant therapy
  • psychotherapy
  • multilevel model
  • rate of change
  • symptom improvement
  • Ecological momentary assessment
  • experience sampling method

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