Key features of palliative care service delivery to Indigenous peoples in Australia, New Zealand, Canada and the United States: a comprehensive review
Bibliographic record
Abstract
BACKGROUND: Indigenous peoples in developed countries have reduced life expectancies, particularly from chronic diseases. The lack of access to and take up of palliative care services of Indigenous peoples is an ongoing concern. OBJECTIVES: To examine and learn from published studies on provision of culturally safe palliative care service delivery to Indigenous people in Australia, New Zealand (NZ), Canada and the United States of America (USA); and to compare Indigenous peoples' preferences, needs, opportunities and barriers to palliative care. METHODS: A comprehensive search of multiple databases was undertaken. Articles were included if they were published in English from 2000 onwards and related to palliative care service delivery for Indigenous populations; papers could use quantitative or qualitative approaches. Common themes were identified using thematic synthesis. Studies were evaluated using Daly's hierarchy of evidence-for-practice in qualitative research. RESULTS: Of 522 articles screened, 39 were eligible for inclusion. Despite diversity in Indigenous peoples' experiences across countries, some commonalities were noted in the preferences for palliative care of Indigenous people: to die close to or at home; involvement of family; and the integration of cultural practices. Barriers identified included inaccessibility, affordability, lack of awareness of services, perceptions of palliative care, and inappropriate services. Identified models attempted to address these gaps by adopting the following strategies: community engagement and ownership; flexibility in approach; continuing education and training; a whole-of-service approach; and local partnerships among multiple agencies. Better engagement with Indigenous clients, an increase in number of palliative care patients, improved outcomes, and understanding about palliative care by patients and their families were identified as positive achievements. CONCLUSIONS: The results provide a comprehensive overview of identified effective practices with regards to palliative care delivered to Indigenous populations to guide future program developments in this field. Further research is required to explore the palliative care needs and experiences of Indigenous people living in urban areas.
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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 | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.019 | 0.026 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".