A Data-Driven Typology of Emotion Regulation Profiles

Abstract

Typologies serve to organize knowledge and advance theory for many scientific disciplines, including more recently in the social and behavioral sciences. To date, however, no typology exists to categorize an individual’s use of emotion regulation strategies. This is surprising given that emotion regulation skills are used daily and that deficits in this area are robustly linked with mental health symptoms. Here we attempted to identify and validate a working typology of emotion regulation across six samples (collectively comprised of 1492 participants from multiple populations) by using a combination of computational techniques, psychometric models, and growth curve modeling. We uncovered evidence for three types of regulators: a type (Lo) that infrequently uses emotion regulation strategies, a type (Hi) that uses them frequently but indiscriminately, and a third type (Mix) that selectively uses some (cognitive reappraisal and situation selection), but not other (expressive suppression), emotion regulation strategies frequently. Results showed that membership in the Hi and Mix types is associated with better mental health, with the Mix type being the most adaptive of the three. These differences were stable over time and across different samples. These results carry important implications for both our basic understanding of emotion regulation behavior and for informing future interventions aimed at improving mental health.