GRIEF AND BEREAVEMENT SUPPORT FOR STAFF IN LONG-TERM CARE HOMES: IDENTIFYING BARRIERS AND FACILITATORS
Bibliographic record
Abstract
Abstract Admissions of older adults to long-term care are occurring at more advanced ages with more complex care needs, resulting in shorter lengths of stay before death and an increased demand for a palliative approach to care. However, long-term care staff often lack access to sustainable educational, organizational, and interpersonal support in end-of-life care, and must learn on the job while facing death in the workplace. To address this gap, we conducted a scoping review of literature on grief and bereavement support for long-term care staff. Following PRISMA-Scoping Review guidelines and the six-step framework by Levac and colleagues, social sciences databases were searched and data were analyzed through narrative synthesis and the creation of infographics. Fifty-eight studies met inclusion criteria. Strategies, interventions, and rituals were organized into five domains:1) Cultural Attitudes Toward Death and Unmet Need for Support; 2) Organizational Policy and Practice; 3) Formal Peer-support; 4) Informal Peer-support; and 5) Individual Beliefs and Self-Care Practices influenced by temporal aspects. Identifying barriers and facilitators of grief support for long-term care staff, and hospice and palliative care specialists’ practices, can offer more holistic and effective approaches to long-term care staff wellness to combat burnout and staff turnover. Grief rituals present scalable, holistic approaches fostering long-term care staff wellness that could be explored in future research to collaboratively build long-term care staff capacity for person-centered end-of-life care.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".