Moving Guidelines into Action: A Report from Cancer Care Ontario’s Event Let’s Get Moving: Exercise and Rehabilitation for Cancer Patients
Bibliographic record
Abstract
The need for an improved understanding of the rehabilitation services landscape in Ontario and for promotion of Cancer Care Ontario’s newly developed Exercise for People with Cancer guideline brought Cancer Care Ontario’s Psychosocial Oncology and Survivorship Programs together to host a knowledge translation and exchange event. The primary objectives of the event were to understand recommendations from Cancer Care Ontario’s new exercise guideline, to discuss key considerations and determine strategies for the implementation of the guideline recommendations, and to explore the current state and future directions of cancer rehabilitation in Ontario. The event was attended by 124 stakeholders, including clinicians, allied health care professionals, administrators, patients, community partners, and academics representing each of the 13 regional cancer programs in Ontario. Attendees participated in two small-group activities that focused on determining the best approach for implementing the guideline recommendations into practice and discussing current barriers and the future state of cancer rehabilitation in Ontario. The activities allowed for networking and collaboration between attendees. The event provided an opportunity for the Psychosocial Oncology and Survivorship Programs to learn about the types of goals and plans that could be feasible in implementing the guideline in each region, and about ways to prioritize gaps in access to rehabilitation services and the types of implementation strategies that might be used to address the gaps. Overall, attendees were highly satisfied with the event, and the findings are being used to help inform research and practice activities with respect to guideline implementation and rehabilitation practice.
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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 | 0.008 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 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".