BRAIN. Broad Research in Artificial Intelligence and Neuroscience

Volume: 17 | Issue: 1 | Paper number: 30.

Neuropsychological Dynamics of Emotional Intelligence: Trait Emotional Intelligence and Life Satisfaction in Higher Education

Published March 19, 2026
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Stephen Paul A. - Karunya Institute of Technology and Sciences, Karunya Nagar, Coimbatore (IN), K. Martina Rani - Karunya Institute of Technology and Sciences, Karunya Nagar, Coimbatore (IN), S. Samkutty Samueal - Karunya Institute of Technology and Sciences, Coimbatore (IN), A. Danam Tressa - St.Joseph's Degree & PG College, Hyderabad, Telangana (IN), P. Srilatha - Government Junior College, Borabanda, Jubilee Hills, Hyderabad, Telangana (IN), B. Giri Babu - Karunya Institute of Technology and Sciences, Coimbatore (IN),

Abstract

Trait Emotional Intelligence (TEI) is a set of personality-related, emotion-self-perception measures which outline the way people understand and manage emotions in their daily lives. In the framework of the recent interdisciplinary research, the study fills in the gaps in the methodology and cultural context by questioning the predictive value of TEI dimensions for life satisfaction (LS) in the context of Indian higher education students who face distinct academic and social stressors. The multivariate model (AIC = 154.73; R²=.241) using both logistic regression and structural equation modelling identified well-being (OR = 2.31, p = .012) and self-control (OR = 1.89, p = .028) as the only statistically salient predictors using an empirical sample of 118 students (aged 18-25) assessed with the TEIQue-SF and a global LS measure. These results highlight the utmost significance of dispositional optimism and emotional regulation in promoting psychological well-being and contentment with life. The bivariate correlation analysis showed that well-being (r=0.69), sociability (r=0.35), self-control (r=0.25), and emotionality (r=0.23) were all significantly related to LS. The difference between the small bivariate correlation of self-control and the strong, independent predictive value of self-control in the multivariate model is an important methodological improvement, which demonstrates the need to control the interrelated affective constructs. Lastly, the research gap addressed in this study lies in placing the predictive results within a neuropsychological paradigm, conceptually connecting the well-being factor to dopaminergic reward circuitry and self-control to fronto-amygdaloid connectivity.

Academic discipline and sub-disciplines: Neuroscience; Psychology; Cognitive Sciences

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DOI: http://dx.doi.org/10.70594/brain/17.1/30

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