Determinants of supportive care experiences for women living with breast cancer in rural communities of British Columbia.
Bibliographic record
Abstract
Background: Enabling women with breast cancer to actively participate in their care requires a better understanding of the interplay between contextual factors and mediators. This research explored the determinants of supportive care experiences for women living with breast cancer in rural communities of British Columbia. Methods: The study used a quantitative, descriptive, cross-sectional design. A survey regarding demographic, health, decision support, and breast cancer supportive care experiences was administered to 100 participants. Results: = 23%. Conclusion: The findings emphasize the growing need for psychosocial and emotional supportive care for cancer survivors. The results highlight the potential benefits of informed decision-support tools to fortify supportive care, emphasizing the need to facilitate better supportive care services for women battling breast cancer. Recommendation: Supportive care plays a crucial role in guiding individuals' experiences with cancer through the healthcare system. Increasing supportive care centres, especially in rural areas, could improve patient-reported outcomes, and experiences, and ensure timely access to care.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".