A Quantitative Study Exploring How Depression Symptom Severity Moderates the Relationship Between Emotional Suppression and Workplace Performance in a Sample of American Office Worker

Major depressive disorder (MDD) is a heterogeneous disorder consisting of several subtypes, and both subthreshold depression and acute phase depression are associated with functional, occupational, and social impairments, even after remission. Studies suggest that depression symptom severity negatively affects a person’s health, work performance, and social functioning due to a person’s limited cognitive resources. In Western cultures, employers expect employees who have depression to use emotional regulation in the workplace, but these employees find that this uses cognitive resources to the extent that they are unable to do their work optimally and also fulfill their social functions in the workplace. This study explored whether depression symptom severity (DSS) moderated the relationship between emotional suppression and work performance in a sample of American office workers. In this study, the predictor variables were emotional suppression, measured by the Emotional Regulation Questionnaire (ERQ), and DSS, measured by the Center for Epidemiologic Studies Depression Scale (CES-D), and the outcome variable was workplace performance, measured by the Need Satisfaction at Work, Job Strain, and Performance Diary (NJP). Consistent with the literature, the hypothesis was that DSS would moderate the relationship between ERQ and NJP. No relationship between ERQ and NJP was found so a moderation analysis was inappropriate. Future researchers should explore how depression symptom severity influences the relationship between emotional suppression and workplace performance to minimize the impact of lost work productivity and improve the well-being of the American workforce.

Publication Details

Journal
Scholars Crossing (Liberty University)
Published
2024-12-11
Primary Topic
Machine Learning in Bioinformatics
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article

A Quantitative Study Exploring How Depression Symptom Severity Moderates the Relationship Between Emotional Suppression and Workplace Performance in a Sample of American Office Worker

Scholars Crossing (Liberty University)
Machine Learning in Bioinformatics
article

A Quantitative Study Exploring How Depression Symptom Severity Moderates the Relationship Between Emotional Suppression and Workplace Performance in a Sample of American Office Worker

article en

Abstract

Major depressive disorder (MDD) is a heterogeneous disorder consisting of several subtypes, and both subthreshold depression and acute phase depression are associated with functional, occupational, and social impairments, even after remission. Studies suggest that depression symptom severity negatively affects a person’s health, work performance, and social functioning due to a person’s limited cognitive resources. In Western cultures, employers expect employees who have depression to use emotional regulation in the workplace, but these employees find that this uses cognitive resources to the extent that they are unable to do their work optimally and also fulfill their social functions in the workplace. This study explored whether depression symptom severity (DSS) moderated the relationship between emotional suppression and work performance in a sample of American office workers. In this study, the predictor variables were emotional suppression, measured by the Emotional Regulation Questionnaire (ERQ), and DSS, measured by the Center for Epidemiologic Studies Depression Scale (CES-D), and the outcome variable was workplace performance, measured by the Need Satisfaction at Work, Job Strain, and Performance Diary (NJP). Consistent with the literature, the hypothesis was that DSS would moderate the relationship between ERQ and NJP. No relationship between ERQ and NJP was found so a moderation analysis was inappropriate. Future researchers should explore how depression symptom severity influences the relationship between emotional suppression and workplace performance to minimize the impact of lost work productivity and improve the well-being of the American workforce.

Scholars Crossing (Liberty University)
Decent work and economic growth
Openalex Percentile: Top 49%
Machine Learning in Bioinformatics
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