Workers’ perspectives on the effects of telework during the COVID-19 pandemic on their well-being: A qualitative study in Canada
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic caused an unprecedented health emergency across the world. Public health measures aimed at slowing the spread of the virus impose measures concerning physical distancing that citizens must observe. Thousands of workers quickly found themselves having to telework, with no preparation by their organizations. The literature reports the positive effects of teleworking on certain indicators of well-being, as well as best teleworking practices in a normal context. The urgent and unplanned nature of the switch to teleworking in a crisis may have changed the relationship between teleworking and well-being. OBJECTIVE: This study aimed to explore workers' perspectives on teleworking in the context of the COVID-19 pandemic, regarding its effects on their well-being. METHODS: Following a descriptive interpretive research design, we collected qualitative data from 15 teleworkers via focus groups and individual interviews. Two researchers used a thematic analysis strategy to analyze the data. RESULTS: Data analysis led to identifying 16 factors that participants cited as influencing the well-being of teleworkers. These form eight categories: delays related to uncertainty, manager practices, organizational practices, social interactions, job characteristics, teleworking space, personal realities and personal practices. The results show the influence of interactions between work demands, control and social support on the well-being of workers. CONCLUSION: Because of its many advantages, organizations and their workers will increasingly engage in telework. The influences of telework on people's well-being call for implementing concrete "best practices" that are applicable and that consider workers' perspectives.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".