Concussion Public Policy for Elementary and High Schools in Ontario: Assessment of Content, Implementation, and Impact of PPM158
Bibliographic record
Abstract
Background and Objective: Concussions are a rising public health problem and have particular impact on the well-being of children and youth aged eighteen and under, having increased in rate 4.4-fold from 2003 to 2013 in Ontario.1 Concussion public policies have been developed across the United States and in Ontario, Canada, to address this issue, and further knowledge about them would help inform evidence-based policies. The objectives of the three studies in this thesis are to 1) develop consensus-based concussion public policy recommendations, 2) identify barriers to and facilitators of Policy/Program Memorandum 158 (PPM158) implementation, and 3) assess whether there has been a change in the rate of concussion-related visits associated with the establishment of PPM158.Methods: To address the first objective, we employed a modified Delphi method with a multi-disciplinary expert group. To address the second objective, we developed a survey and analyzed data with both quantitative and qualitative methods. To address the third objective, we used segmented regression in an interrupted time series design. We hypothesized that PPM158 was associated with a rise in concussion-related visit rates. Results: The results of the first study yielded 30 concussion public policy recommendations categorized into 6 categories: 1) Concussion Education, 2) Return-to-Learn, 3) Removal and Return-to-Play, 4) Communication, 5) Prevention of Concussion, and 6) General. The findings of the second study included specific barriers to PPM158 implementation in Ontario, such as poor parent/guardian concussion education and low access to physician/nurse practitioner notes for return-to-activity. Facilitators of PPM158 implementation included consistency in implementation and use of resources such as relationships with healthcare professionals. The findings of the third study were an immediate increase in concussion-related visits after the effective date of PPM158 in 2015, followed by a decrease in the trend of concussion-related visits by Ontarians aged 4-18. The high-income group and the oldest age-group (13-18) both had differentially greater response to implementation of PPM158.Conclusions: Together, these three studies make novel contributions to the concussion public policy content, implementation, and impact literature. These findings provide the context and recommendations for changes to improve existing concussion public policies and directions for future research.
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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 | 0.015 | 0.047 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".