Emotion Recognition from Realistic Dynamic Emotional Expressions Cohere with Established Emotion Recognition Tests: A Proof-of-Concept Validation of the Emotional Accuracy Test.

Abstract

Individual differences in understanding other people’s emotions have typically been studied with recognition tests using prototypical emotional expressions. These tests have been criticized for the use of posed, prototypical displays, raising the question of whether such tests tell us anything about the ability to understand spontaneous, non-prototypical emotional expressions. Here, we employ the Emotional Accuracy Test (EAT), which uses natural emotional expressions and defines the recognition as the match between the emotion ratings of a target and a perceiver. In two preregistered studies (Ntotal = 231), we compared the performance on the EAT with two well-established tests of emotion recognition ability: the Geneva Emotion Recognition Test (GERT) and the Reading the Mind in the Eyes Test (RMET). We found significant overlap (r > 0.20) between individuals’ performance in recognizing spontaneous emotions in naturalistic settings (EAT) and posed (or enacted) non-verbal measures of emotion recognition (GERT, RMET), even when controlling for individual differences in verbal IQ. On average, however, participants reported enjoying the EAT more than the other tasks. Thus, the current research provides a proof-of-concept validation of the EAT as a useful measure for testing the understanding of others’ emotions, a crucial feature of emotional intelligence. Further, our findings indicate that emotion recognition tests using prototypical expressions are valid proxies for measuring the understanding of others’ emotions in more realistic everyday contexts.