Student Competition (Clinical/Best Practice Implementation) ID 1984705
Bibliographic record
Abstract
Background The foremost reported unmet health need for Canadians with chronic neurological conditions is linked to physical maintenance. One way to address this issue is through activity programing offered through public institutions, where rehabilitation can be integrated into secondary health care settings. Parkwood Institute in London, Ontario has developed several programs, including virtual exercise classes, day programs, and a community fitness center. People who have participated in these initiatives can provide insights that could be used to create more robust person-centered rehabilitation physical activity programing. Objectives To explore the lived experiences of individuals participating in activity programs offered through Parkwood Institute to develop recommendations for future program development. Methods Using purposive sampling of individuals with a chronic neurological health condition who have participated in a physical activity program offered through Parkwood, we will use a grounded theory methodology to explore individual perspectives. Data will be collected using semi-structured interviews to gather critical perspectives and data will be analyzed using constant comparative analysis. Data collection and analysis will be an iterative process, meaning codes and categories will be developed from initial interviews, with subsequent data being continuously compared to identify similarities and differences. Results The findings of this research will, once completed, describe the impact of various physical activity programs, including benefits, challenges, and recommendations for future development. Conclusions The theoretical interpretations of the findings will be presented as a list of recommendations for activity programs offered through rehabilitation centers to assist researchers, clinicians, and policy makers in decision-making.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.519 | 0.216 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".