Changes in Health and Well-Being of Care Aides in Nursing Homes From a Pre-Pandemic Baseline in February 2020 to December 2021
Bibliographic record
Abstract
Nursing homes were profoundly affected by the COVID-19 pandemic, influencing work outcomes of care aides who provide the most direct care. We compared care aides' quality of work life by conducting a repeated cross-sectional analysis of data collected in February 2020 and December 2021 from a stratified random sample of urban nursing homes in two Canadian provinces. We used two-level random-intercept repeated-measures regression models, adjusting for demographics and nursing home characteristics. 2348 and 1116 care aides completed the survey in February 2020 and December 2021, respectively. The 2021 sample had higher odds of reporting worked short-staffed daily to weekly in the previous month than the 2020 sample. The 2021 sample also had a small but significant drop in professional efficacy and mental health. Despite the worsening changes, our findings suggest that this workforce may have withstood the pandemic better than might be expected.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".