Interventions to improve cancer survivorship among Indigenous Peoples and communities: a systematic review with a narrative synthesis
Bibliographic record
Abstract
PURPOSE: The purpose of this systematic review is to synthesize the evidence on the types of interventions that have been utilized by Indigenous Peoples living with cancer, and report on their relevance to Indigenous communities and how they align with holistic wellness. METHODS: A systematic review with narrative synthesis was conducted. RESULTS: The search yielded 7995 unique records; 27 studies evaluating 20 interventions were included. The majority of studies were conducted in USA, with five in Australia and one in Peru. Study designs were cross-sectional (n=13); qualitative (n=5); mixed methods (n=4); experimental (n=3); and quasi-experimental (n=2). Relevance to participating Indigenous communities was rated moderate to low. Interventions were diverse in aims, ingredients, and outcomes. Aims involved (1) supporting the healthcare journey, (2) increasing knowledge, (3) providing psychosocial support, and (4) promoting dialogue about cancer. The main ingredients of the interventions were community meetings, patient navigation, arts, and printed/online/audio materials. Participants were predominately female. Eighty-nine percent of studies showed positive influences on the outcomes evaluated. No studies addressed all four dimensions of holistic wellness (physical, mental, social, and spiritual) that are central to Indigenous health in many communities. CONCLUSION: Studies we found represented a small number of Indigenous Nations and Peoples and did not meet relevance standards in their reporting of engagement with Indigenous communities. To improve the cancer survivorship journey, we need interventions that are relevant, culturally safe and effective, and honoring the diverse conceptualizations of health and wellness among Indigenous Peoples around the world.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 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) | 0.001 | 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".