17 Tailored exercise for survivors with brain tumours: A case series
Bibliographic record
Abstract
Purpose: Exercise has been shown to be beneficial for the physical and psychological health of cancer survivors, however, little research has been conducted on the effects of exercise in the brain tumour population. Survivors with brain tumours present with unique challenges in terms of mobility and function that may compromise their ability to safety take part in community-based exercise. Methods: Three survivors with primary brain tumours will be profiled in this case series presentation. Participants were screened using a cancer specific intake questionnaire and the Physical Activity Readiness Questionnaire, and triaged to supervised clinic-based or community-based exercise. All participants completed the 12-week intervention for the Alberta Cancer Exercise (ACE) study. Measurements were taken at baseline, and post-intervention including measures of body composition, aerobic fitness, musculoskeletal fitness, balance and flexibility. Self-reported measures included questionnaires to assess impact on physical functioning, symptoms and quality of life, and to evaluate satisfaction with programming. Results: One participant was referred to supervised clinic-based exercise programming due to a high risk of falls, and two participants were deemed safe and approved for community-based supported exercise programming at a preferred location closer to their home. Preliminary results suggest high program satisfaction, maintenance and/or benefit of physical fitness, balance, and symptom control. Conclusions: Further efforts are needed to better tailor programming to the needs of the survivor and consideration given to the advantages of the supervised clinic-based environment when compared to the survivor preference for a “closer to home” community-based setting.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".