SCAT2 and SCAT3 scores at baseline and after sports-related mild brain injury/concussion: qualitative synthesis with weighted means
Bibliographic record
Abstract
OBJECTIVE: Identify all Sport Concussion Assessment Tool (SCAT2/3) studies, compare baseline and postconcussion results. DESIGN: Systematic review (qualitative synthesis, weighted means). DATA SOURCES: 18 databases, 9 grey literature resources searched for SCAT2/3 data; 9150 articles identified, titles/abstracts assessed/data-entry independently by two reviewers. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Any studies reporting partial/complete SCAT2/3 data. RESULTS: 21 studies with data (partial/complete data 16 SCAT2 (4087 athletes); 5 SCAT3 (891). Newcastle-Ottawa risk-of-bias scale: studies with maximum possible score of 4, 85% scored 3 or 4; studies with maximum possible score of 6, 75% scored 5 or 6. SCAT2 high schoolers: weighted mean score for symptoms 18.46 (22=no symptoms), Balance Error Scoring System (BESS) 26.14, Standardised Assessment of Concussion (SAC) 26.00 and SCAT2 total 88.63. Collegiate/adults weighted means: symptoms 20.09, BESS 25.54, SAC 27.51 and total SCAT2 91.20. Between-study and within-study variability similar to those of the high schoolers. Limited variability between genders. Only 2 studies report baseline and postconcussion scores and 9 partial scores, but data are too limited to provide weighted average scores. CONCLUSIONS: Group mean baseline SCAT scores for high school and collegiate athletes are similar, with minimal gender differences; baseline symptoms show more variability than other components. There are minimal data for elementary students and professionals, no data for adult non-collegiate athletes. Two studies provide preconcussion and postconcussion scores. No data on minimal significant clinical differences to guide players/coaches in withdrawing from a game in progress and deciding when recovery is complete and play can be resumed. The SCAT needs supplementing with clinical and neuropsychological return-to-play assessments.
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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 | 0.081 | 0.215 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.017 |
| Bibliometrics | 0.034 | 0.030 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".