The Emotion Regulation Questionnaire (ERQ) evaluates emotion regulation strategies, particularly expressive suppression and cognitive reappraisal. However, the ERQ does not discern between regulating positive and negative emotions. Recent insights suggest that suppression and reappraisal can impact mental health differently when targeting specific emotional valence (positive vs negative). We developed and validated the Emotion Regulation Questionnaire - Positive/Negative (ERQ-PN), designed to measure positive and negative forms of suppression and reappraisal strategies. We recruited 963 participants (female = 478) through Prolific.com and administered the ERQ-PN. Participants had an average age of 45 years and were predominantly White (74%) and heterosexual (84%). Model fit was estimated using the comparative fit index and the root-mean-square error of approximation. We also used the Bayesian information criterion to compare the fit of different models.  Overall, participants used reappraisal more often to decrease negative emotions (vs. increasing positive) and leaned toward using suppression more for negative emotions (vs. positive). Structural validity was assessed through confirmatory factor analyses. These analyses revealed that the four-factor model (Model 2) delineating four latent variables (positive reappraisal, negative reappraisal, positive suppression, and negative suppression) had a good fit (RMSEA = 0.07, CFI = 0. 97, TLI = 0.96, χ2(98) = 531.28, p < 0.001). An incremental validity assessment revealed that positive and negative reappraisal correlated as expected with related mental health constructs, with notable differences among suppression subtypes. The ERQ-PN represents a valid measure of emotion regulation that accounts for both positive and negative emotions.

The authors have declared that no competing interests exist.

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The study was approved by the Indiana University Bloomington Institutional Review Board (IRB), approval number #17145. Informed consent was obtained online through Qualtrics.

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Data can be found on the Open Science Foundation (OSF) website: https://osf.io/ezngp/.