Trends in concussions at Ontario schools prior to and subsequent to the introduction of a concussion policy - an analysis of the Canadian hospitals injury reporting and prevention program from 2009 to 2016
Bibliographic record
Abstract
BACKGROUND: Concussion is a preventable injury that can have long-term health consequences for children and youth. In Ontario, the Policy/Program Memorandum # 158 (PPM) was introduced by the Ministry of Education of Ontario in March 2014. The PPM's main purpose is to require each school board in the province to create and implement a concussion policy. The purpose of this paper is to examine trends in school-based concussions prior to and subsequent to the introduction of the PPM. METHODS: This report examined emergency department (ED) visits in 5 Ontario hospitals that are part of the Canadian Hospitals Injury Reporting and Prevention Program (CHIRPP), and compared trends over time in diagnosed concussions, and suspected concussions identified as "other head injury" in children and youth aged 4-18. RESULTS: From 2009 to 2016 study years, there were 21,094 suspected concussions, including 8934 diagnosed concussions in youth aged 4-18. The average number of diagnosed concussions in the 5 years before the PPM was 89 concussions/month, compared to approximately 117 concussions per month after; a 30% increase in the monthly rate of concussions presenting to the ED. The total number of concussion or head injury-related ED visits remained relatively unchanged but the proportion of diagnosed concussions rose from 31% in 2009 to 53% in 2016. The proportion of diagnosed concussions in females also increased from 38% in 2013 to 46% in 2016. The percent of all diagnosed concussions occurring at schools increased throughout the study reaching almost 50% in 2016 with most injuries taking place at the playground (24%), gymnasium (22%) or sports field (20%). CONCLUSIONS: The introduction of the PPM may have contributed to a general increase in concussion awareness and an improvement in concussion identification at the school level in children and youth aged 4-18.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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".