COVID-19: short- and long-term impacts on work and well-being
Bibliographic record
Abstract
The broad risks and drastic changes associated with the COVID-19 pandemic pose various psychosocial and physical challenges, which can affect the health and well-being of employees and the organizations they work for. This chapter builds on research undertaken in support of the Canadian military to provide timely insight into how people may react during and after the crisis, and how organizational leaders can support their personnel through it. We took a pragmatic approach in reviewing the scientific literature and available data that (in)directly relates to the COVID-19 pandemic, and we distilled the information to a manageable set of recommendations deemed relevant to the organizational context. Our review yielded considerations in several key areas, including (a) impacts of disasters, (b) impacts of COVID-19 on work life, and (c) on family life, (d) (non-)compliance with public health directives, (e) reintegration into the workplace, and (f) crisis communication and management. Although certain organizations (e.g., military/public safety), may be well-prepared to manage the effects of the crisis (e.g., with a workforce that is trained for and experienced in dealing with stressful and ambiguous situations), our review suggests that some workers, regardless of organizational affiliation, may be particularly susceptible to its negative effects based on their perceptions, demographic characteristics, personal or financial circumstances, family dynamics, pre-existing health conditions, and the nature of their work. In this chapter, we discuss the various risk factors and offer evidence-informed recommendations for how organizational leaders might mitigate the potential harmful and enduring effects of COVID-19 and future crises, and we offer a research agenda to address critical knowledge gaps
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".