Impact of COVID-19 on care homes: A qualitative study of experiences of black carers in UK
Bibliographic record
Abstract
Abstract COVID-19 has drastically impacted care home residents, families, and staff. However, little is known about the impact of this pandemic on carers from the ethnically minoritised background. The present research explored the experiences of UK’s black carers during COVID-19. A semi-structured interview-based qualitative study was conducted involving black carers from Berkshire, Hampshire, and Oxfordshire. Interviews were conducted online through Microsoft Teams, and a thematic analysis was performed on verbatim transcribed interviews. The present study included 15 participants from three UK counties which have a large number of care homes. The analysis of interviews resulted in the development of seven themes: 1) reactions to COVID, 2) infection control in the work environment, 3) workplace discrimination, 4) impact of COVID on well-being, 5) coping mechanisms and impact of deaths, 6) reflection on challenges, and 7) recommendations to care home managers. In conclusion, the black carers reported a substantial impact on their mental and physical health. They recognized the need for timely information, sufficient and fair availability of PPEs, more support, better communication, and equitable work distribution to maintain their mental and physical health.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.009 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".