Beliefs About Automatic Mood Regulation: Engagement in Sad Experiences, Emotional Reactivity, and Task Performance

Automatic mood regulation is believed to be an adaptive and frequently used emotion regulation strategy. Automatic mood regulation is hypothesized to be particularly useful at times when cognitive resources are limited and might not support effortful mood regulation, which requires greater attention. We recently developed a self-report measure entitled the Beliefs About Automatic Mood Regulation Scale (BAMR), which focuses on personal beliefs that automatic mood regulation works for the respondent (Hutchison & Gunthert, 2013). The present study explores how the BAMR relates to affect and task performance in a laboratory experiment. After sadness was induced by showing a series of sad film clips, participants were randomly assigned to a version of an editing task designed to utilize low or high levels of self-regulation, which consumes cognitive resources. At several time points during the experiment, affect was assessed via self-report questionnaires and physiological measures of heart rate, blood pressure, and finger temperature. Results indicated that the BAMR, controlling for beliefs in effortful mood regulation, predicted better performance on the editing task, increased positive affect after the high-regulation version of the editing task, and a trend towards less fear after the editing task. Hypotheses that the BAMR would predict greater emotional engagement with sad material, increased serenity, and decreased negative affect, sadness, and fatigue after the editing task were not supported.