Treatment Related Exercise and Supportive Care Needs of People Living with and Beyond Breast Cancer
Bibliographic record
Abstract
People living with and beyond breast cancer (LWBBC) experience different side effects relative to the type of medical treatments they received which may influence their needs for additional supportive care. Investigating people LWBBC's needs according to treatment regimen may guide decision making about supportive care priorities. The study's objectives were to identify individuals LWBBC's needs for supportive care and to determine exercise program participation facilitators according to treatment type. A survey assessing the needs for supportive care and exercise facilitators was distributed on the Facebook pages of five non-profit Canadian cancer organizations for three months. Needs and facilitators were assessed according to the combination of treatment type received including chemotherapy, radiotherapy or a combination of both. A convenience sample of 214 women LWBBC (mean age 50 ± 11 years) responded to the survey. Most (84%) participants reported searching for supportive care, especially exercise or psychological support for pain/fatigue management and improvement of psychological well-being. Higer proportions of women receiving chemotherapy (86-95%) were searching for supportive care compared to women not receiving chemotherapy (70%). Psychological support was the most searched supportive care among women receiving both chemotherapy and radiotherapy, while exercise program was most sought out by women receiving only one of these two treatment types. Low cost (47%) and accessibility to a supervised program (46%) were the most important exercise program facilitators for participants during treatment. Needs of women LWBBC seemed to diverge according to received treatment and should be considered when tailoring supportive care for these individuals.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".