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Trait emotional intelligence as predictor of psychological health in undergraduate medical students: A hierarchical multiple regression approach
Indian J Physiol Pharmacol ; 2023 Mar; 67(1): 21-28
Article | IMSEAR | ID: sea-223973
Objectives: Trait emotional intelligence (TEI) is a key personality construct by which an individual recognizes, understands, expresses and regulates emotions in self and others to adapt to environments or achieve one’s goals. TEI skills are modifiable and have a potential to significantly influence psychological health (PH) of a person. The aims of current work were to evaluate relationship between TEI and PH of medical students and to explore the incremental validity of TEI to predict psychological distress beyond sociodemographic and educational factors in them. Materials and Methods: One hundred and thirty-two medical students (mean age 18.02 years) participated in this cross-sectional study. TEI and PH were assessed using TEI questionnaire short form (TEIQue-sf) and depression, anxiety and stress scale (DASS-21), respectively. Hierarchical multiple regression analysis was carried out to determine if scores on TEIQue-sf added significantly to the prediction of psychological symptoms in medical students. Results: There was a significant negative association (r = ?0.57, P < 0.001) between TEIQue-sf and DASS-21 scores. Hierarchical regression analyses revealed that after controlling for sociodemographic and educational variables, TEIQue-sf scores explained a statistically significant increment of variance (P < 0.001) in DASS-21 scores. TEI emerged as best predictor of psychological distress of medical students followed by educational factors. However, sociodemographic profile as an attribute failed to demonstrate significant capacity to predict PH of our participants. Conclusion: Our results indicate that TEI is a robust and unique predictor of better PH and plays a positive role in promoting psychological well-being
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Texto completo: 1 Índice: IMSEAR Revista: Indian J. physiol. pharmacol Ano de publicação: 2023 Tipo de documento: Article
Texto completo: 1 Índice: IMSEAR Revista: Indian J. physiol. pharmacol Ano de publicação: 2023 Tipo de documento: Article