Connecting People with Cancer to Physical Activity and Exercise Programs: A Pathway to Create Accessibility and Engagement
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Recent guidelines concerning exercise for people with cancer provide evidence-based direction for exercise assessment and prescription for clinicians and their patients. Although the guidelines promote exercise integration into clinical care for people with cancer, they do not support strategies for bridging the guidelines with related resources or programs. Exercise program accessibility remains a challenge in implementing the guidelines, but that challenge might be mitigated with conceptual frameworks ("pathways") that connect patients with exercise-related resources. In the present paper, we describe a pathway model and related resources that were developed by an expert panel of practitioners and researchers in the field of exercise and rehabilitation in oncology and that support the transition from health care practitioner to exercise programs or services for people with cancer. The model acknowledges the nuanced distinctions between research and exercise programming, as well as physical activity promotion, that, depending on the available programming in the local community or region, might influence practitioner use. Furthermore, the pathway identifies and provides examples of processes for referral, screening, medical clearance, and programming for people after a cancer diagnosis. The pathway supports the implementation of exercise guidelines and should serve as a model of enhanced care delivery to increase the health and well-being of people with cancer.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it