Reliability of the scat2/3 in college athletes
Bibliographic record
Abstract
Objective To evaluate psychometric properties of the Sport Concussion Assessment Tool (SCAT). Design Retrospective clinical study in which athletes completed the SCAT over 2 consecutive seasons. Athletic therapists administered the SCAT and a pre-season medical questionnaire. Setting University setting. Participants 165 college athletes who were enrolled at a university in Western Canada who played collision sports. Intervention the SCAT2 and subsequently the SCAT3 was administered to all participants at baseline. Main outcome measures Intraclass coefficients (ICC’s) and paired sample t-tests. Main results The intraclass reliability coefficients for demographic variables ranged from moderate to good (0.66 to 0.94). The reliability of the cognitive test results and balance error scoring system (BESS) was rated as good (0.83 and 0.88 respectively). Total symptom report and symptom severity report was moderate, with significant differences noted between males and females. History of concussion did not significantly impact reliability coefficients. Among the 22 athletes who suffered concussions during a competitive season, the reliability of the core components of the SCAT remained high. Conclusions The reliability of the SCAT2/3 is classified as good although symptom report is more variable Competing interests None. Keywords: concussion, sport concussion assessment tool, psychometric properties
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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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".