Our study aims to investigate how the fear of COVID-19 affects job satisfaction and mental well-being. Additionally, we will explore the moderating role of on-the-job embeddedness in these relationships.
The study surveyed 358 Indian-origin IT professionals through Amazon Mechanical Turk. It used confirmatory factor analysis to analyze the measurement model and hierarchical linear regression in SPSS 21 software to examine the structural relationships between variables. A robustness check was conducted using the MODLR macro in SPSS to identify any spurious moderation.
The results reveal a curvilinear (or U-shaped) relationship between COVID-19 fear, job satisfaction and mental well-being. Further, on-the-job embeddedness linearly moderates the relationship between COVID-19 fear and job satisfaction and COVID-19 fear and mental well-being.
The research design is cross-sectional, so results reported about causal relationships are considered cautiously. The relationships involving the variables and their direction are because of the theory’s assumptions rather than the test of causal relationships between variables.
This is the first study to show that the relationship between COVID-19 fear and job satisfaction and COVID-19 fear and mental well-being is curvilinear (or U-shaped). Further, we are again the first to show that on-the-job embeddedness positively moderates the two relationships: COVID-19 fear – job satisfaction and COVID-19 fear – mental well-being. This is one of the few studies that employed MODLR macro to check for spurious moderation.
