Speaker
Description
Trait Emotional Intelligence (Trait EI) is conceptualized as a multidimensional and hierarchical construct. However, traditional psychometric models have struggled to fully capture its theoretical complexity. This study proposes a cross-cultural validation of the Trait Emotional Intelligence Questionnaire Full-Form (TEIQue-FF) across British and Italian samples, adopting a bifactor Exploratory Structural Equation Modeling (B-ESEM) framework with oblique rotation. We argue that B-ESEM better reflects the Trait EI conceptualization by simultaneously modeling a latent global factor and allowing correlation among specific domains—features not accommodated by traditional higher-order models. The four first-order factors are treated as correlated dimensions, while Self-Motivation and Adaptability facets load directly onto the global factor, a structure naturally accommodated by bifactor models without imposing constraints typical of higher-order models. The study design includes testing the B-ESEM structure separately in each national sample, followed by Multigroup ESEM to assess measurement invariance across countries. Data will be collected online via Prolific to ensure sample comparability and data quality. This project addresses a significant gap, as no study to date has examined the B-ESEM structure or tested the cross-cultural invariance of the TEIQue-FF, although similar analyses have been conducted on the short form. By aligning the measurement model more closely with the original theoretical conceptualization, this study aims to enhance the psychometric robustness and cross-cultural generalizability of the TEIQue-FF. Expected findings will have implications for the future operationalization and international application of Trait EI assessment tools. Preliminary findings and methodological considerations will be presented and critically discussed at the Conference.
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