Development of a Forced-Choice Measure of Typical-Performance Emotional Intelligence. (February 2015)

• Record Type: Journal Article
• Authors: Anguiano-Carrasco, Cristina; MacCann, Carolyn; Geiger, Mattis; Seybert, Jacob M.; Roberts, Richard D.
• Other Names: Keefer Kateryna guest-editor.
• Is Part Of: Journal of psychoeducational assessment. Volume 33:Number 1(2015)
• Page Start: 83
• Page End: 97
• Publication Date: 2015-02
• Subjects: item response theory (IRT) -- emotional intelligence -- forced-choice assessment -- Thurstone's law of comparative judgment; Ability -- Testing -- Periodicals; Educational tests and measurements -- Periodicals; 371.713
• DOI: 10.1177/0734282914550387
• Languages: English
• ISSNs: 0734-2829

Abstract

Self-report ratings of emotional intelligence (EI) can be faked in high-stakes situations. Although forced-choice administration can prevent response distortion, it produces ipsative scores when scored conventionally. This study ( n = 486) develops an 18-item EI rating scale assessing emotion perception, understanding, and management. We compare validity evidence for: (a) a single-stimulus rating scale; and (b) a forced-choice assessment scored with conventional methods versus item response theory (IRT) methods. The single-stimulus items showed acceptable fit to a three-factor solution, and the forced-choice items showed acceptable fit to the IRT solution. Correlations with criterion variables (ability and self-reported EI, Big Five personality, loneliness, life satisfaction, and GPA) were obtained for 283 participants. Correlations were in the expected direction for the single-stimulus and the IRT-based forced-choice scores. In contrast, the conventionally scored forced-choice test showed the expected correlations for emotion management, but not for emotion perception nor understanding. Results suggest that IRT-based methods for scoring forced-choice assessments produce equivalent validity to single-stimulus rating scales. As such, IRT-based scores on forced-choice assessments may allow EI tests to be used for high-stakes applications, where faking is a concern.