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Lee, Garam (2015)
Publisher: Occupational Safety and Health Research Institute
Journal: Safety and Health at Work
Languages: English
Types: Article
Subjects: Original Article, logistic regression analysis, job stress, RA1-1270, Public aspects of medicine, work conditions, Korean Working Conditions Survey, emotional labor

Classified by OpenAIRE into

mesheuropmc: reproductive and urinary physiology
Background: The present study aims to investigate job stressors and stress relievers for Korean emotional laborers, specifically focusing on the effects of work conditions and emotional labor properties. Emotional laborers are asked to hide or distort their real emotions in their interaction with clients. They are exposed to high levels of stress in the emotional labor process, which leads to serious mental health risks including burnout, depression, and even suicide impulse. Exploring job stressors and relieving factors would be the first step in seeking alternatives to protect emotional laborers from those mental health risks. Methods: Using the third wave data of Korean Working Conditions Survey, logistic regression analysis was conducted for two purposes: to examine the relations of emotional labor and stress, and to find out job stressors and relievers for emotional laborers. Results: The chances of stress arousal are 3.5 times higher for emotional laborers; emotional laborers experience double risk-burden for stress arousal. In addition to general job stressors, emotional laborers need to bear burdens related to emotional labor properties. The effect of social support at the workplace is not significant for stress relief, unlike common assumptions, whereas subjective satisfaction (wage satisfaction and work-life balance) is proven to have relieving effects on emotional laborers' job stress. Conclusion: From the results, the importance of a balanced understanding of emotional labor for establishing effective policies for emotional laborer protection is stressed.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

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