The Perceived Impact of COVID-19 on Functional Activities Among Canadian Education Workers: A Cross-Sectional Study
Bibliographic record
Abstract
Objective: This cross-sectional study examined the self-perceived impact of the COVID-19 pandemic on 2,378 education workers in Ontario, Canada, during the second wave. Methods: We examined six domains of functioning as per the short version of the World Health Organization Disability Assessment Schedule-2.0. Participants selected if their functioning had improved, remained unchanged or worsened during the pandemic for each item. Results: Educational workers described a general worsening of functional activities since the beginning of the pandemic. Moderate-to-extreme challenges were reported for all six functional domains. These challenges appeared to aggravate functional challenges for workers with disability, as indicated by pre-existing work accommodations. Older participants reported worse mobility than younger participants; however, they appeared to have better coping skills in learning new tasks and maintaining friendships. Women were more likely to report difficulties in maintaining household responsibilities. Conclusions: We consider the role of mental health challenges and pre-existing inequality as predictors of pandemic-related difficulties. Recommendations include more longitudinal research in this population and policymakers to incorporate a health promotion lens to support their education workers more proactively.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".