Survey of educators regarding the return to learn after a sport-related concussion
Bibliographic record
Abstract
Objective To evaluate the impact of an educational intervention upon educators’ knowledge of sport-related concussion (SRC) management strategies and their understanding of academic accommodations as part of the return to learn (RTL) strategy after an SRC. Design A pre- and post-intervention study. Setting A sport-focused Ontario (Canada) secondary school. Participants 94 educational staff, including teachers, administrators and school psychologists. Interventions Three ten-minute didactic lectures were followed by ninety minute facilitated focus groups during an educators’ professional development workshop. Participants learned about the nature and management of SRC with an emphasis upon RTL. Participants also had to reflect on their own experiences with some of the 63 students who had RTL at that school, after an SRC during the prior 3.5 years. Outcome measures Participants answered pre and post intervention surveys directed toward knowledge of SRC management principles and acknowledgement of accommodations. Main results 81 of the 94 participants submitted two matched pre and post surveys. Educators indicated significantly increased understanding of SRC management and showed a significantly increased support of accommodations after the intervention (p<0.05). Conclusions Educators’ understanding of SRC management strategies is essential to facilitate a successful RTL. This study suggests that a brief educational intervention can improve the support of educators for academic accommodations as part of the RTL phase of SRC management. Competing interests None.
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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 | 0.003 | 0.014 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".