Understanding Indigenous peoples experiences to inform recommendations for improving cultural safety and care in radiation therapy centres in Alberta, Canada
Bibliographic record
Abstract
INTRODUCTION: Rates of common cancers are continuously increasing among Indigenous peoples and are above the incidence rates of non-Indigenous Canadians. When considering the intersecting social determinants of health such as culture, geography, funding, and access to basic health services, these all contribute to the unique cancer burden faced by Indigenous people. Indigenous patients sometimes feel alienated by the word "cancer", intimidated in the oncology setting and often avoid or delay seeking care, bypass screening and preventative care, and cease prescribed treatment before it is finished. Providing culturally competent, safe care to improve Indigenous health outcomes have been suggested and prioritized in health care systems across Canada. METHODS: Using an Indigenous methodology, sharing circles were held in Northern Alberta, Canada. Five Indigenous survivors of cancer and two Indigenous caregivers shared their experiences with oncology treatment in the radiation therapy centre. Results were transcribed verbatim and thematic analysis was conducted. RESULTS: This resulted in four main themes (1) historical and cultural understandings (2) reduce systemic harm by having dedicated Indigenous staff, cultural competency, and Indigenous specific supports (3) meaningful time commitment and relationship building (4) importance of kinship and Indigenous-centred, family-and-patient-centred care. These themes fed into the development of nine recommendations for policy and decision makers to improve cultural safety in the Alberta radiation therapy centres. CONCLUSION: Support for Indigenous patients and caregivers is essential to improve care in the radiation therapy centres. The findings from this work will support recommendations for health decision and policy makers within radiation therapy centres, which may be transferable to other centres within oncology and 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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.028 | 0.011 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| 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".