Mediators of psychosocial well-being for immigrant women living with breast cancer in Canada: a critical ethnography
Bibliographic record
Abstract
Abstract Background: Immigrant women living with breast cancer experience a lack of psychosocial and emotional support, which adds to the complexity of navigating and using health care services in Canada. Aim: To explore the mediators of psychosocial well-being for immigrant women living with breast cancer in Canada. Methods: A critical ethnography was used. The study identified 27 immigrants living with breast cancer, who had been born in a foreign country, migrated to Canada within the past 10 years, and lived in rural communities of British Columbia between August 2021 and March 2022. Institutional research ethics board approval and informed consent were obtained. Results: The findings indicated two significant themes: The immigrant women had limited knowledge, information, and communication and experienced physical, psychological, and emotional distress. Conclusion: There is a significant need for culturally responsive care services for immigrant women living with breast cancer in rural communities. Recommendations include the development of psychosocial oncology, such as integrated counseling and therapies, to reduce cancer-related post-traumatic stress and improve their psychosocial and emotional well-being. Interdisciplinary approaches to psychosocial oncology are particularly crucial for immigrants and rural communities, where women need access to cancer navigation and ongoing support for a better health-related quality of life.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.013 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".