Embracing the Emotion in Emotional Intelligence Measurement: Insights from Emotion Theory and Research

Abstract

Emotional intelligence (EI) has gained significant popularity as a scientific construct over the past three decades, yet its conceptualization and measurement still face limitations. Applied EI research often overlooks its components, treating it as a global characteristic, and there are few widely used performance-based tests for assessing ability EI. The present paper proposes avenues for advancing ability EI measurement by connecting the main EI components to models and theories from the emotion science literature and related fields. For emotion understanding and emotion recognition, we discuss the implications of basic emotion theory, dimensional models, and appraisal models of emotion for creating stimuli, scenarios, and response options. For the regulation and management of one’s own and others’ emotions, we discuss how the process model of emotion regulation and its extensions to interpersonal processes can inform the creation of situational judgment items. In addition, we emphasize the importance of incorporating context, cross-cultural variability, and attentional and motivational factors into future models and measures of ability EI. We hope this article will foster exchange among scholars in the fields of ability EI, basic emotion science, social cognition, and emotion regulation, leading to an enhanced understanding of the individual differences in successful emotional functioning and communication.

Designing and evaluating tasks to measure individual differences in experimental psychology: a tutorial

“…Closely related to working memory are executive functions, the functions needed to initiate and perform tasks, while ignoring distractors. Here too, consistent individual differences have been observed and linked to theories about the nature of the functions (Friedman & Miyake, 2017 ; Miyake et al, 2000 ), and again research has been devoted to finding tasks that optimally measured the various functions (Karr et al, 2018 ; Rey-Mermet et al, 2018 ).…”

“…While such diversity need not be a bad thing for research, it is important to know how well the different scales converge, especially if they are used for clinical diagnosis and have real-life implications. Similarly, we may wonder to what extent different measures of working memory or executive function converge on the traits they claim to measure (Miyake et al, 2000 ; Muffato et al, 2023 ; Rey-Mermet et al, 2018 ; Snyder et al, 2021 ).…”

Studying individual differences in experimental psychology: A tutorial

“…Content can be based on developers' intuitions or previous research. Mortillaro and Schlegel (2023) point out that building content on an existing theory is a particularly good idea. They discussed the development of tests to measure emotion understanding.…”

Exploring Actual and Presumed Links between Accurately Inferring Contents of Other People’s Minds and Prosocial Outcomes

“…The overlapping elements of thought-feeling accuracy and accuracy at decoding nonverbal and affective cues have earned both forms of accuracy a place in the discussion of "emotional intelligence". Furthermore, and of relevance for this Special Issue (see Mortillaro and Schlegel 2023), both forms of accuracy are measures of ability rather than personality traits. Emotion decoding accuracy has also been linked-although not consistently in empirical results-to prosocial behavior and (often self-reported) measures of empathy-related constructs (see Hodges and Wise 2016;Mayukha et al 2020;Olderbak and Wilhelm 2017;Schlegel 2020).…”

“…However, thought-feeling accuracy and emotion decoding accuracy also differ; among other things, the latter is generally measured using static stimuli (e.g., a photo of a facial expression), often made from actors posing emotional expressions outside of natural social interactions (e.g., Gur et al 2002;Nowicki and Duke 1994;Schlegel et al 2014) or posing for other purposes (e.g., for advertisements, such as the Reading the Mind in Eyes Task (RMET) 1 , (Baron-Cohen et al 2001); but there are some exceptions, e.g., (Costanzo and Archer 1989)). Additional coverage of some measures of emotion recognition and nonverbal decoding, along with their applications to emotional intelligence, appears elsewhere (e.g., Buck et al 2017) and in this issue (e.g., Mortillaro and Schlegel 2023).…”