Don't Get Too Excited: Assessing Individual Differences in the Down-Regulation of Positive Emotions

ABSTRACT

A voluminous literature has documented the importance of emotion regulation for health and well-being. The studies in this literature, however, have generally focused on the down-regulation of negative affect. Few studies have examined the down-regulation of positive affect. In Study 1, we constructed a scale, the revised Regulatory Emotional Self-Efficacy Scale (r–RESE), which assesses both the down- and up-regulation of positive affect, in addition to the traditional down-regulation of negative affect. In Study 2, we conducted an extensive validation of the r–RESE scale, using a multimethod approach with informant ratings, to illustrate that the down-regulation of positive affect represents a process independent of each of the other forms of emotion regulation. In Study 3, we provided evidence that the ability to down-regulate positive emotions provides added predictive utility when predicting indexes of impulsivity and adjustment. Across the studies, we illustrate the potential importance of the down-regulation of positive emotions as a topic of study for the field of emotion regulation.

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Don’t Get Too Excited: Assessing Individual Differences in the Down-Regulation of Positive Emotions

Acknowledgments

We would like to thank and acknowledge the members of the Plaks lab for their assistance in the initial development of the scale and Quyet Dinh for organizing the data. We would also like to thank the members of Dr. Impett's Relationship and Well-Being Lab for their helpful comments on the earlier version of the manuscript.

Funding

This research project was supported by a standard research grant awarded to Jason Plaks and Jordan B. Peterson by the Canadian Social Sciences and Humanities Research Council.

Notes

¹ We initially fit a correlated trait–correlated method (CTCM) model but the model did not converge. Thus, as suggested by Lance et al. (2002), once the CTCM model failed, the CU model was chosen.

² Whereas the BIC value was slightly lower than 10, model fit worsened on all other fit indexes.

³ D-POS was uniquely predictive of the avoidance subscale of the attachment scale, but in the opposite direction from what we expected, where higher D-POS was significantly related to greater avoidance, b = .08, t(436) = 2.35, p = .02.

⁴ D-ANG also uniquely predicted the number of days in the opposite direction (IRR = 1.51, 95% CI [1.02, 2.22], p = .04).

⁵ We could not conduct a formal test to compare the strength of all the correlations as there would be too many tests to be conducted (4 RESE components and 6 outcome measures = 45 comparisons).