26 (17B) Test-retest reliability of the SCAT6® cognitive and tandem gait components among professional hockey players
Bibliographic record
Abstract
Purpose To examine the test-retest reliability and reliable change of the Sports Concussion Assessment Tool-6 (SCAT6®) cognitive and tandem gait components in a large sample of multi-cultural professional ice hockey players.Methods National Hockey League (NHL) and American Hockey League (AHL) players undergoing medical evaluations prior to the 2023/2024 (time 1) and 2024/2025 (time 2) seasons completed the NHL Modified SCAT (n=1388), which includes an expanded digits backward and tandem gait with an option to wear skates. Data were extracted from an existing clinical database of players. Test-retest reliability was examined with Pearson correlations and reliable change metrics (RCI) were developed. Regression-based norms were created for the Total Cognitive Score.Results Players were assessed on average 353.69±46.01 days following their baseline. A regression-based reliable change model incorporating baseline scores and word list form explained 40% of the variance in time two SCAT6® Total Cognitive performance ( r=.64). Test-retest reliabilities and practice-corrected .90 RCIs denoting decline included: English-language preference concentration (r=.56; reliable decline=-2), tandem gait fastest time with skates (r=.69; reliable decline=+3.60), tandem gait average time with skates (r=.72; reliable decline=+3.53), tandem gait fastest time without skates (r=.51; reliable decline=+4.20), and tandem gait average time without skates (r=.44; reliable decline=+4.68).Conclusions These findings highlight the importance of considering practice effects when determining reliable change from baseline on the new SCAT6® components in professional hockey players. These findings also provide initial evidence that test-retest reliability of new SCAT6® components is improved compared to prior research and earlier iterations of the SCAT®.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".