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Yoonjeong Lee 1 Article
Psychosocial Well-Being of Clinical Nurses Performing Emotional Labor: A Path Analytic Model Approach
Yoonjeong Lee, Hyunli Kim
J Korean Acad Nurs 2019;49(3):307-316.   Published online January 15, 2019
DOI: https://doi.org/10.4040/jkan.2019.49.3.307
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Abstract Purpose

This study was conducted to investigate the influence of emotional expressivity, emotional intelligence, affectivity, job autonomy, social support, and emotional labor on clinical nurses’ individual well-being and to provide guidelines for interventions and strategies for its improvement.

Methods

The sample consisted of 207 nurses recruited from a general hospital in Korea. The participants completed a structured self-report questionnaire comprising measures of emotional expressivity, emotional intelligence, positive affectivity, negative affectivity, job autonomy, supervisor support, coworker support, deep acting, surface acting, emotional exhaustion, and job satisfaction. Data were analyzed using SPSS statistics 22.0 and AMOS 22.0.

Results

The final model was a good fit for the data based on the model fit indices. In the path analysis, surface acting, negative affectivity, supervisor support, and coworker support had statistically significant effects on emotional exhaustion, explaining 29.0% of the variance. Deep acting, emotional exhaustion, positive affectivity, and emotional intelligence had statistically significant effects on job satisfaction, explaining 43.0% of the variance.

Conclusion

Effective strategies to improve clinical nurses’ individual well-being should focus on surface acting, deep acting, affectivity, social support, and emotional intelligence. The results of this study can be utilized as base data to manage emotional labor and improve clinical nurses’ individual well-being.

Citations

Citations to this article as recorded by  
  • Validity and Reliability of the Korean version of the Wong and Law Emotional Intelligence Scale for Nurses
    Hye-Ja Park, Soyoung Yu
    Sage Open.2021;[Epub]     CrossRef
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  • 1 Web of Science
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