Assessment of a collaborative concussion management strategy in a school-based sport program
Bibliographic record
Abstract
OBJECTIVE: To analyze the implementation of a concussion management protocol in which a team physiotherapist is involved in the identification of concussions and return-to-play (RTP) decisions. DESIGN: A prospective injury surveillance cohort study in a school-based Canadian football program (4 teams; grades 8 to 12) over 4 years. For years 1 to 2, the team physician made all RTP decisions; over years 3 to 4, the team physiotherapist was allowed to make some RTP decisions using pre-established criteria defined in the protocol. SETTING: A high school in Québec, Que. PARTICIPANTS: Male student athletes between 11 and 17 years old. MAIN OUTCOME MEASURES: Same-season recurrence (SSR) of concussion symptoms following RTP. RESULTS: A total of 119 concussions were identified (55 during the first 2 years and 64 during the last 2 years) during 27,741 athlete-exposures in 672 athlete-years for an incidence rate of 4.3 per 1000 athlete-exposures. During years 1 to 3, no SSR was observed following RTP clearance. During year 4 there was 1 case of SSR that occurred 11 days after clearance. The overall SSR rate of concussion symptoms following RTP clearance was 0.8%. CONCLUSION: A very low rate of SSR was achieved whether the team physician made all RTP decisions or the team physiotherapist was allowed to make some of the RTP decisions through the terms of the protocol.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".