Mentalized affectivity: A new model and assessment of emotion regulation

David M. Greenberg, Jonela Kolasi, Camilla P. Hegsted, Yoni Berkowitz, Elliot L. Jurist

Research output: Contribution to journalArticlepeer-review

36 Scopus citations

Abstract

Here we introduce a new assessment of emotion regulation called the Mentalized Affectivity Scale (MAS). A large online adult sample (N = 2,840) completed the 60-item MAS along with a battery of psychological measures. Results revealed a robust three-component structure underlying mentalized affectivity, which we labeled: Identifying emotions (the ability to identify emotions and to reflect on the factors that influence them); Processing emotions (the ability to modulate and distinguish complex emotions); and Expressing emotions (the tendency to express emotions outwardly or inwardly). Hierarchical modeling suggested that Processing emotions delineates from Identifying them, and Expressing emotions delineates from Processing them. We then showed how these components are associated with personality traits, well-being, trauma, and 18 different psychological disorders (including mood, neurological, and personality disorders). Notably, those with anxiety, mood, and personality disorders showed a profile of high Identifying and low Processing compared to controls. Further, results showed how mentalized affectivity scores varied across psychological treatment modalities and years spent in therapy. Taken together, the model of mentalized affectivity advances prior theory and research on emotion regulation and the MAS is a useful and reliable instrument that can be used in both clinical and non-clinical settings in psychology, psychiatry, and neuroscience.

Original languageEnglish
Article numbere0185264
JournalPLoS ONE
Volume12
Issue number10
DOIs
StatePublished - Oct 2017
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2017 Greenberg et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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