Physical Rehabilitation Practices for Children and Adolescents with Cancer in Canada
Bibliographic record
Abstract
Purpose: Children and adolescents with cancer who undergo cancer treatment are at high risk of developing adverse effects, many of which may be amenable to physical rehabilitation. We aimed to identify the current clinical physical rehabilitation practice patterns, services, and programmes available for children and adolescents with cancer in Canada. Method: A cross-sectional survey in English and French was conducted. Participants were health care professionals (HCPs) who provided physical rehabilitation services to children and adolescents with cancer in Canada. The survey included questions on the HCPs’ practice patterns and the programmes and services they provided. Results: A total of 35 HCPs responded: 27 physical therapists (77%), 6 occupational therapists (17%), 1 exercise professional (3%), and 1 speech-language pathologist (3%). Overall, they reported activity limitations, alterations in motor performance, muscle weakness, peripheral neuropathy, and fatigue as the top priorities for rehabilitation services. HCPs believed that interventions were valuable in reducing the burden of cancer effects; however, issues such as space, resources, and lack of clinical practice guidelines were viewed as barriers to providing services. Conclusions: Paediatric oncology rehabilitation services exist in some regions in Canada. HCPs strongly support the need to develop clinical practice guidelines for paediatric oncology rehabilitation.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".