Facilitators and barriers to centre- and home-based exercise training in breast cancer patients - a swiss tertiary centre experience
Bibliographic record
Abstract
Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Swiss Cancer Research Background Exercise is an effective therapy for cancer patients to reduce fatigue and to improve health-related quality of life and physical function. Yet, cancer patients often do not meet physical activity guidelines. Purpose To understand why recommendations are not met, we aimed at identifying facilitators and barriers to supervised, centre-based exercise within a cardio-oncologic rehabilitation (CORE) programme and to unsupervised, home-based exercise as well as strategies used to manage these barriers. Methods Breast cancer patients who had completed a CORE programme at a Swiss tertiary centre were recruited. Semi-structured interviews were conducted with subsequent thematic analysis. Results Of 37 eligible breast cancer patients, 19 patients (mean age 48.9±9.7 years) participated to our invitation. Facilitators for centre-based exercise were social support, committedness and provision of structured exercise. Barriers towards centre-based exercise included physical and environmental barriers, while psychological barriers were reported predominantly for home-based exercise. Strategies to manage barriers included the adaptation of training circumstances, behaviour change strategies and strategies to deal with side effects. Conclusions Our results support the importance of providing CORE programmes and suggest that a special focus should be directed at the transition from supervised to self-organized exercise in order to enhance long-term exercise participation.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".