Working in a pandemic: Exploring the impact of COVID-19 health anxiety on work, family, and health outcomes.
Bibliographic record
Abstract
The COVID-19 pandemic has unhinged the lives of employees across the globe, yet there is little understanding of how COVID-19 health anxiety (CovH anxiety)-that is, feelings of fear and apprehension about having or contracting COVID-19-impacts critical work, home, and health outcomes. In the current study, we integrate transactional stress theory (Lazarus & Folkman, 1984) with self-determination theory (Deci & Ryan, 2000) to advance and test a model predicting that CovH anxiety prompts individuals to suppress emotions, which has detrimental implications for their psychological need fulfillment. In turn, lack of psychological need fulfillment hinders employees' abilities to work effectively, engage with their family, and experience heightened well-being. Our model further predicts that handwashing frequency-a form of problem-focused coping-will mitigate the effects of CovH anxiety. We test our propositions using a longitudinal design that followed 503 employees across the first four weeks that stay-at-home and social distancing orders were enacted. Consistent with predictions, CovH anxiety was found to impair critical work (goal progress), home (family engagement) and health (somatic complaints) outcomes due to increased emotion suppression and lack of psychological need fulfillment. Further, individuals who frequently engage in handwashing behavior were buffered from the negative impact of CovH anxiety. Combined, our work integrates and extends existing theory and has a number of important practical implications. Our research represents a first step to understanding the work-, home-, and health-related implications of this unprecedented situation, highlighting the detrimental impact of the anxiety stemming from the COVID-19 pandemic. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".