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Cited by 304

The DOI matches its Crossref record; 92 of the 92 references it cites were found in a registry or an index.

Emotional Labor and Burnout: A Review of the Literature

Open access
Jeung, Da-Yee, Kim, Changsoo, Chang, Sei-Jin·2018·Yonsei Medical Journal

Abstract

This literature review was conducted to investigate the association between emotional labor and burnout and to explore the role of personality in this relationship. The results of this review indicate that emotional labor is a job stressor that leads to burnout. Further examination of personality traits, such as self-efficacy and type A behavior pattern, is needed to understand the relationships between emotional labor and health outcomes, such as burnout, psychological distress, and depression. The results also emphasized the importance of stress management programs to reduce the adverse outcomes of emotional labor, as well as coping repertories to strengthen the personal potential suitable to organizational goals. Moreover, enhancing employees' capacities and competence and encouraging a positive personality through behavior modification are also necessary.

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Crossref · 10.3349/ymj.2018.59.2.187

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Metadata

Authors
Jeung, D.-Y., Kim, C., & Chang, S.-J.
Venue
Yonsei Medical Journal
Publisher
XMLink
Published
2018
Volume
59
Issue
2
Pages
187
ISSN
  • 0513-5796 (ISSN-L)
  • 1976-2437
OpenAlex
W2786979395
Cited by
304
References
92
FWCI
39.87
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Emotional Labor and Burnout: A Review of the Literature. https://app.cochat.ai/papers/10.3349/ymj.2018.59.2.187
The paper
Jeung, D.-Y., Kim, C., & Chang, S.-J. (2018). Emotional Labor and Burnout: A Review of the Literature. Yonsei Medical Journal. https://doi.org/10.3349/ymj.2018.59.2.187

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.