Decisions on cancer care by Indigenous peoples in Alberta and Saskatchewan: a narrative analysis
Bibliographic record
Abstract
INTRODUCTION: The prevalence of cancer is increasing among Indigenous peoples in Canada. To enhance quality of life of those Indigenous people affected by cancer, their decision-making experiences must be understood. This article presents the findings of a qualitative study exploring the treatment decision-making practices among Indigenous peoples with cancer in rural and remote Alberta and Saskatchewan, Canada. METHODS: This study employed a qualitative narrative-based approach using the Indigenous research method of storytelling. Seventeen Indigenous participants (14 women, three men) with various forms of cancer were interviewed. Open-ended questions were used that were designed to understand participants' decision-making processing regarding their cancer treatment. RESULTS: Keeping with Indigenous methodology, the interview transcripts were analysed by a narrative method, with the intent that the data would be presented in story format. Eight vignettes relating to decision making were created: being strong for family; family support; strength and independence; denial and not wanting to know; fear-based decision making; finding the blessing; the spiritual journey; and traditional medicine and doctors. Participants were involved in validating the analysis to ensure that data were accurately interpreted. CONCLUSION: The vignettes demonstrate the similarities and differences among Indigenous people with cancer from other countries. A primary feature is that family members play a central role in participants' cancer treatment decisions. While some participants embraced and relied upon traditional medicines, others were supported by the providers of Western health care. A healthcare system that provides access to both traditional and Western medicine can be essential to culturally safe, high-quality cancer care for Indigenous peoples.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 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".