Supporting The Knowledge Translation Of Exercise Recommendations For People With Bone Metastases Using An Experience-based Co-design Approach
Bibliographic record
Abstract
People with bone metastases have historically been advised to limit exercise due to risk of adverse events, such as fracture. In 2022, the International Bone Metastases Exercise Working Group published evidence-informed recommendations stating regular exercise may improve physical function and quality of life in people with bone metastases, and the risk of skeletal events weighed against potential health benefits. However, published guidelines alone often fail to change clinical practice. PURPOSE: To collaborate with knowledge users (KU) to co-design knowledge translation (KT) products and a dissemination plan to support the uptake of the exercise recommendations for people with bone metastases. METHODS: An experienced-based co-design approach was used, collaborating with three KU groups: 1) patient/family partners; 2) oncology healthcare providers (physicians, nurses, allied health); and 3) community-based exercise professionals (physiotherapists, exercise physiologists). Through facilitated meetings, KT product ideas were generated, prioritized, and co-created and a dissemination strategy was discussed. RESULTS: Twenty-nine KUs participated in four engagement sessions (n = 10 patient/family partners, n = 9 healthcare providers, and n = 10 exercise professionals). The KT products prioritized for development were: 1) a patient education handout; 2) patient education videos; 3) a clinical communication tool; and 4) professional development materials for exercise professionals and healthcare providers. The dissemination plan will involve partnerships with target organizations (e.g., Canadian Cancer Society). CONCLUSIONS: Collaborating with KUs through experience-based co-design has enabled the development of KT products likely to be more useful and acceptable to the intended audience than those designed by researchers alone. Our KT products can support people with bone metastases to engage in exercise safely and increase the satisfaction of oncology healthcare providers and exercise professionals in what information and resources they can offer patients. With our product launch, we will evaluate the reach, use, and partnership indicators of the KT products and dissemination plan. Canadian Cancer Society and Michael Smith Health Research BC
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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 | 0.103 | 0.121 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".