“We’ve All Lost So Much”: The Long-Term Care Home Experiences of Essential Family Caregivers During COVID-19
Bibliographic record
Abstract
BACKGROUND: During the coronavirus (COVID-19) pandemic, long-term care homes (LTCHs) imposed visitor restrictions that prevented essential family caregivers (EFCs) from entering the homes. Under these policies, EFCs had to engage in virtual, window, and outdoor visits, prior to the re-initiation of indoor visits. OBJECTIVE: To understand EFCs' visitation experiences with LTCH residents during COVID-19. METHODS: Seven virtual focus groups with EFCs were conducted and analysed using a thematic approach. FINDINGS: Six themes were identified: (a) inconsistent and poor communication; (b) lack of staffing and resources; (c) increasing discord between EFCs and staff during COVID-19; (d) shock related to reunification; (e) lack of a person-centred or family-centred approach; and, (f) EFC and resident relationships as collateral damage. DISCUSSION: Our findings reflect how EFCs' visitation experiences were affected by factors at the individual, LTCH, and health-system levels. Future sectoral responses and visitation guidelines should recognize EFCs as an integral part of the care team.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.008 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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".