The Buddy Program: High school students inform the design of a school-based peer support program for concussion
Bibliographic record
Abstract
Prior research provides little guidance on how to support return to school post-concussion. Peer support may be one strategy to enable adolescents to return to school post-concussion. The purpose of this study was to explore what high school students preferred in a school-based peer support program post-concussion. We conducted a qualitative instrumental case study in one high school in Calgary, Canada. Seven semi-structured focus groups were conducted with 53 high school students (16 boys, 36 girls, 1 preferring not to disclose gender; median age = 16 years, range = 15-18 years). All adolescents were enrolled in a sport medicine course and had either a history of concussion (n = 20) or were interested in supporting peers who had sustained a concussion (n = 33). Focus group questions aimed to solicit which factors the adolescents believed should be considered in the development of a post-concussion peer support program. We analyzed the focus group transcriptions using content analysis. Adolescents preferred a one-on-one Buddy Program. A one-on-one environment would provide a trusting and confidential relationship between the student with a concussion and their buddy. Peer support could include social support, advocacy support for academic accommodations, tutoring support, and concussion education. In future, the Buddy Program should be piloted in high schools.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".