Expanding the Concept of End‐of‐life Care in Long‐term Care: A Scoping Review Exploring the Role of Healthcare Assistants
Bibliographic record
Abstract
BACKGROUND: The context of care provided in long-term care homes is changing, as an increasing number of older adults are entering long-term care with advance stages of illness and higher care needs. Long-term care homes are quickly becoming the place of death for an increasing number of older adults, despite recent literature identifying inadequate and suboptimal levels of end-of-life care. Within long-term care, healthcare assistants represent 60%-70% of the unregulated workforce and provide 70%-90% of the direct care to residents. Research indicates that a high level of uncertainty exists surrounding the role of healthcare assistants in end-of-life care, with numerous studies reporting the role of healthcare assistants to be 'unclear' with varying levels of responsibilities and autonomy. OBJECTIVE: The purpose of this scoping review was to explore healthcare assistants' experiences and perspectives of their role in end-of-life care in long-term care. METHODS: We applied Arksey and O'Malley's methodological framework, with recommendations from Levac and colleagues' guiding principles. Electronic databases and the grey literature were searched for relevant articles. Search concepts included end-of-life care and healthcare assistants. Articles were included in this review if they explored healthcare assistants' experiences or perspectives of providing end-of-life care in long-term care. The peaceful end of life theory by Ruland and Moore (1998) was used to organise data extraction and analysis. RESULTS: A total of n = 15 articles met the inclusion criteria. The most predominant role-required behaviours reported by healthcare assistants were as follows: psychosocial support to significant others, knows the resident's care wishes and physical care with respect and dignity. The most predominant extra-role behaviours reported by healthcare assistants were as follows: becoming emotionally involved, acting as extended family and ensuring residents do not die alone. CONCLUSIONS: Findings from this review expanded the concept of end-of-life care by illustrating the role-required and extra-role behaviours healthcare assistants perform when providing end-of-life care in long-term care. IMPLICATIONS FOR PRACTICE: Findings from this scoping review highlight the numerous behaviours healthcare assistants perform outside their role description in order to provide end-of-life care to dying residents in long-term care. These findings could inform policymakers and managers of long-term care homes.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".