Traditional and Complementary Medicine Use Among Indigenous Cancer Patients in Australia, Canada, New Zealand, and the United States: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Cancer 'patients' are increasingly using traditional indigenous and complementary medicines (T&CM) alongside conventional medical treatments to both cure and cope with their cancer diagnoses. To date T&CM use among Indigenous cancer patients from Australia, Canada, New Zealand, and the United States has not been systematically reviewed. METHODS: We systematically searched bibliographic databases to identify original research published between January 2000 and October 2017 regarding T&CM use by Indigenous cancer patients in Australia, Canada, New Zealand, and the United States. Data from records meeting eligibility criteria were extracted and appraised for quality by 2 independent reviewers. RESULTS: Twenty-one journal articles from 18 studies across all 4 countries met our inclusion criteria. T&CM use ranged from 19% to 57.7% (differing across countries). T&CM was mostly used concurrently with conventional cancer treatments to meet their spiritual, emotional, social, and cultural needs; however, bush, traditional, and herbal medicines were used in a minority of cases as an alternative. CONCLUSIONS: Our findings highlight the importance of T&CM use to Indigenous cancer patients across these 4 countries; we identified multiple perceived spiritual, emotional and cultural benefits to its use. The patient's perception of their health professional's attitudes toward T&CM in some cases hindered or encouraged the patient's disclosure. Additional research is required to further explore the use and disclosure of T&CM among Indigenous cancer patients to help inform and ensure effective, safe, coordinated care for Indigenous cancer patients that relies on shared open decision making and communication across patients, communities, and providers.
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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 | 0.007 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.012 | 0.018 |
| Science and technology studies | 0.001 | 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".