Online concussion resources for young children and caregivers: a systematic search
Bibliographic record
Abstract
INTRODUCTION: In Canada, concussions are common among children aged 3-12 years. Caregivers play a vital role in their child's post-concussion care, highlighting the need for resources tailored to children and caregivers. Although many online pediatric concussion resources exist, their suitability for younger children and caregivers remains unclear. OBJECTIVE: To identify and assess the quality, readability, usability, and suitability of online concussion resources for children aged 3-12 years and their caregivers. METHODS: A four-phased systematic search strategy was used and involved: 1) searching Canadian children's hospital websites, 2) applying pre-established inclusion/exclusion criteria, 3) evaluating content quality, and 4) evaluating resources for suitability, readability, and usability. RESULTS: = 1) focused on return to play beyond organized sport. CONCLUSIONS: The identified resources offer accurate concussion information for children and caregivers, but lack specificity for their intended audience and accessibility for nonreaders. Future resources should consider specifying the intended age group, improving accessibility for nonreaders, and including information about important activities for this age group such as returning to active play.
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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 | 0.010 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.019 | 0.022 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".