Background: There is increasing evidence that psychological constructs, such as emotional intelligence and emotional labor, play an important role in various organizational outcomes in service sector. Recently, in the "emotionally charged" healthcare field, emotional intelligence and emotional labor have both emerged as research tools, rather than just as theoretical concepts, influencing various organizational parameters including job satisfaction. The present study aimed at investigating the relationships, direct and/or indirect, between emotional intelligence, the surface acting component of emotional labor, and job satisfaction in medical staff working in tertiary healthcare.
Methods: Data were collected from 130 physicians in Greece, who completed a series of self-report questionnaires including: a) the Wong Law Emotional Intelligence Scale, which assessed the four dimensions of emotional intelligence, i.e. Self-Emotion Appraisal, Others' Emotion Appraisal, Use of Emotion, and Regulation of Emotion, b) the General Index of Job Satisfaction, and c) the Dutch Questionnaire on Emotional Labor (surface acting component).
Results: Emotional intelligence (Use of Emotion dimension) was significantly and positively correlated with job satisfaction (r=.42, p<.001), whereas a significant negative correlation between surface acting and job satisfaction was observed (r=-.39, p<.001). Furthermore, Self-Emotion Appraisal was negatively correlated with surface acting (r=-.20, p<.01). Self-Emotion Appraisal was found to influence job satisfaction both directly and indirectly through surface acting, while this indirect effect was moderated by gender. Apart from its mediating role, surface acting was also a moderator of the emotional intelligence-job satisfaction relationship. Hierarchical multiple regression analysis revealed that surface acting could predict job satisfaction over and above emotional intelligence dimensions.
Conclusions: The results of the present study may contribute to the better understanding of emotion-related parameters that affect the work process with a view to increasing the quality of service in the health sector.
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http://dx.doi.org/10.1186/1472-6963-12-463 | DOI Listing |
BMC Med Res Methodol
January 2025
Department of Women's and Children's Health - Obstetric & Reproductive Health Research, Uppsala University, Uppsala, 751 85, Sweden.
Background: Peripartum depression is a common but potentially debilitating pregnancy complication. Mobile applications can be used to collect data throughout the pregnancy and postpartum period to improve understanding of early risk indicators.
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BMC Med Ethics
January 2025
School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
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Appl Psychol Health Well Being
February 2025
College of Business, James Madison University, Harrisonburg, Virginia, USA.
As organizations are increasingly turning to voluntary wellness programs to improve employee well-being, the majority of studies in literature have focused on corporate-level benefits of wellness programs, such as productivity. However, there is a scarcity of studies that examine the intrinsic motivators that influence employee participation in such programs. In this study, we use a unique secondary dataset from a voluntary corporate wellness program and propose a novel theoretical framework based on motivational and behavioral theories to examine and understand the participants' behavior.
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College of Automotive Engineering, Jilin University, Changchun 130025, China.
The cockpit is evolving from passive, reactive interaction toward proactive, cognitive interaction, making precise predictions of driver intent a key factor in enhancing proactive interaction experiences. This paper introduces Cockpit-Llama, a novel language model specifically designed for predicting driver behavior intent. Cockpit-Llama predicts driver intent based on the relationship between current driver actions, historical interactions, and the states of the driver and cockpit environment, thereby supporting further proactive interaction decisions.
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