The validity of a general factor of emotional intelligence in the South African context

Emotional intelligence (EI) plays an important role in the prediction of important work-related outcomes, such as work performance. Southern African scholars frequently deploy total scores of EI without considering its hierarchical structure. This study investigated the presence of a general factor,...

Full description

Bibliographic Details
Main Authors: Xander van Lill, Anneke Stols, Pakeezah Rajab, Jani Wiggett
Format: Article
Language:English
Published: AOSIS 2023-03-01
Series:African Journal of Psychological Assessment
Subjects:
Online Access:https://ajopa.org/index.php/ajopa/article/view/123
Description
Summary:Emotional intelligence (EI) plays an important role in the prediction of important work-related outcomes, such as work performance. Southern African scholars frequently deploy total scores of EI without considering its hierarchical structure. This study investigated the presence of a general factor, as manifested among the subscales of the EQ-i 2.0, using an archival dataset of 16 581 employees in Southern Africa. Orthogonal first-order, single-factor, higher-order, oblique lower-order and bifactor models were specified to investigate the hierarchical structure of EI. The evidence supports the notion that a total score could be calculated for EI based on the EQ-i 2.0. A total EI score also appears to be predictive of employees’ individual work performance, as measured by their managers. It might, therefore, be practically meaningful for practitioners to calculate or use a total score when making selection decisions about employees based on the EQ-i. 2.0. Contribution: The findings of the present study offer insights into the theoretical and empirical structure of EI based on statistical techniques that have not been used on the construct in the Southern African context. Concurrent validity evidence further provides additional support that an overall quantitative score, based on the EQ-i. 2.0, has utility in hiring practices, where the aim is to predict future work performance.
ISSN:2707-1618
2617-2798