A health policy perspective: Evaluating the delivery of boxing programs for PD in canada
Bibliographic record
Abstract
Boxing is one of the most 'media-popular' promoted exercise interventions for individuals with Parkinson's disease (PD). However, there are only two scientific studies attempting to validate its effectiveness. Neither study was able to confirm PD-specific symptoms improvement, yet this disproportionate focus on boxing in the media has accelerated the existence of numerous programs internationally. The questionable delivery, along with the minimal scientific evidence raises concerns regarding the effectiveness, safety (qualifications of instructors/assessment tools) and the costs of these programs. Thus, our study evaluated the delivery of boxing programs in Canada using data gathered from telephone-interviews. Boxing programs were searched for using Google (the most popular search engine) and telephone-interviews were conducted guided by a questionnaire developed by the principal investigator. Programs (n=46) were identified and divided into Rock Steady Boxing (RSB) (affiliates share similarities in delivery of exercise) and private boxing programs. Data was analyzed using SPSS, Chi-square tests and descriptive statistics were conducted. Most boxing programs state boxing reduces PD progression, even though not all facilities effectively monitor disease progression. Further, only 4% of RSB and 24% of private boxing program instructors had a background (education/volunteer experience) in Parkinson's prior to running a boxing program for those with PD. However, individuals are charged a participation fee. Based on the findings, this paper made policy recommendations to promote improved delivery of boxing programs for PD in Canada, and has led to the development of my Master's thesis which will be described (an boxing RCT) at the conclusion of this presentation.Acknowledgments: Movement Disorders Research and Rehabilitation Centre and Wilfrid Laurier University
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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 | 0.012 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".