Login / Signup

Effort beats effectiveness in emotion regulation choice: Differences between suppression and distancing in subjective and physiological measures.

Christoph ScheffelSven-Thomas GraupnerAnne GärtnerJosephine ZernaAlexander StrobelDenise Dörfel
Published in: Psychophysiology (2021)
Emotion regulation (ER) can be implemented by different strategies which differ in their capacity to alter emotional responding. What all strategies have in common is that cognitive control must be exercised in order to implement them. The aim of the present preregistered study was to investigate whether the two ER strategies, expressive suppression and distancing, require different amounts of cognitive effort and whether effort is associated with personality traits. Effort was assessed subjectively via ratings and objectively via pupillometry and heart period. In two studies, N = 110 and N = 52 healthy adults conducted an ER paradigm. Participants used suppression and distancing during inspection of positive and negative pictures. They also had the choice to reapply either of the strategies at the end of the paradigm. Although distancing was more effective in downregulation of subjective arousal (Study 1: p < .001, η p 2  = .20; Study 2: p < .001, η p 2  = .207), about two thirds reapplied suppression, because it was perceived as less effortful. Effort was rated significantly lower for suppression compared to distancing (Study 1: p = .042, η p 2  = .04; Study 2: p = .002, η p 2  = .13). However, differences in effort were not reflected in pupillary data or heart period. Broad and narrow personality traits were neither associated with the preferred strategy nor with subjective or physiological effort measures. Findings suggest that people tend to use the ER strategy that is perceived as less effortful, even though it might not be the most effective strategy.
Keyphrases
  • systematic review
  • randomized controlled trial
  • machine learning
  • social support
  • signaling pathway
  • mental health
  • cell proliferation
  • artificial intelligence
  • sleep quality
  • deep learning