Functional Connectivity with Regions Related to Emotional Regulation is Altered in Emotional Laborers

서지정보

ㆍ발행기관 : 한국감성과학회 ㆍ수록지정보 : 감성과학 / 25권 / 4호
ㆍ저자명 : Seokyeong Min, Tae Hun Cho, Soo Hyun Park, Sanghoon Han

목차

Abstract
1. INTRODUCTION
2. METHODS
2.1. Participants
2.2. Clinical assessment
2.3. Image acquisition
2.4. Data preprocessing and head motion correction
2.5. Functional connectivity multivariatepattern analysis (fcMVPA)
2.6. Node and edge definition
2.7. Connectivity-based multivariate patternanalysis
2.8. Age control
2.9. Permutation testing
2.10. Edge feature characteristics
3. RESULTS
3.1. Demographic and clinical assessmentresults
3.2. Discriminating between EL and CTRL groupsusing functional connectivity patterns
3.3. Investigation of potential confounds
3.4. Relating classifier evidence with behavioralmeasures
3.5. Edge feature characteristics
4. DISCUSSION
5. CONCLUSION
REFERENCES

영어 초록

Emotional labor, characterized by a dysfunctional type of emotional regulation called surface acting, has detrimental psychological consequences on employees, including depression and social anxiety. Because such disorders exhibit psychological characteristics manifested through brain activation, previous studies have succeeded in distinguishing individuals with depression and social anxiety from healthy controls using their functional connectivity characteristics. However, it has not been established whether the functional connectivity characteristics associated with emotional labor are distinguishable. Thus, we obtained resting-state fMRI data from participants in the emotion labor (EL) group and control (CTRL) group, and we subjected their whole-brain functional connectivity matrices to a linear support vector machine classifier. Our analysis revealed that the EL and CTRL groups could be successfully distinguished on the basis of individuals' connectivity patterns, and confidence in the classification was correlated with the scores on the depression and social anxiety scales. These results are expected to provide insight on the neurobiological characteristics of emotional labor and enable the sorting of employees undergoing adverse emotional labor utilizing neurobiological observations.

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