Development of an online exercise and education program for adults post-distal radius fracture
Bibliographic record
Abstract
BACKGROUND: Using an evidence-based, patient-engaged, multidisciplinary team approach, we created the Hands Up Program. The Hands Up Program is an exercise and education intervention for people 6-10 weeks after a distal radius fracture (DRF) to support their DRF rehabilitation and reduce the risk of future osteoporotic fractures. PURPOSE: The purpose of this article is to describe the staged and iterative process used to develop the Hands Up Program STUDY DESIGN: A co-design process. METHODS: The Hands Up Program was designed through extensive literature searches, primary data collection and with the ongoing feedback from a multidisciplinary team and patient partners. This web-based program received ongoing feedback during the design and creation phases. The participants also provided feedback after the pilot study was implemented. RESULTS: The Hands Up Program is a 6-week online whole-body exercise and education program. Participants are asked to engage in the program twice per week for 6 weeks and to track their engagement in the program. The program was primarily offered online, but the content was supplemented with hardcopy materials provided in a workbook to the participants at their first study visit. This multimodal format allows for increased accessibility of information for patients. This program is completed at participant's home on their own time. CONCLUSIONS: The Hands Up Program was rigorously developed to address the needs of individuals aged 50-65 after a DRF, suggesting a future risk of osteoporotic fractures. Future iterations of the program should consider equity and scalability.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".