A Cohort Study of the Temporal Stability of ImPACT Scores Among NCAA Division I Collegiate Athletes: Clinical Implications of Test–Retest Reliability for Enhancing Student Athlete Safety
Bibliographic record
Abstract
OBJECTIVE: In this study we examined the temporal stability of the Immediate Post-Concussion Assessment and Cognitive Test (ImPACT) within NCAA Division I athletes across various timepoints using an exhaustive series of statistical models. METHODS: Within a cohort design, 48 athletes completed repeated baseline ImPACT assessments at various timepoints. Intraclass correlation coefficients (ICC) were calculated using a two-way mixed effects model with absolute agreement. RESULTS: Four ImPACT composite scores (Verbal Memory, Visual Memory, Visual Motor Speed, and Reaction Time) demonstrated moderate reliability (ICC = 0.51-0.66) across the span of a typical Division I athlete's career, which is below previous reliability recommendations (0.90) for measures used in individual decision-making. No evidence of fixed bias was detected within Verbal Memory, Visual Motor Speed, or Reaction Time composite scores, and minimal detectable change values exceeded the limits of agreement. CONCLUSIONS: The demonstrated temporal stability of the ImPACT falls below the published recommendations, and as such, fails to provide robust support for the NCAA's recommendation to obtain a single preparticipation cognitive baseline for use in sports-related concussion management throughout an athlete's career. Clinical interpretation guidelines are provided for clinicians who utilize baseline ImPACT scores for later performance comparisons.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 0.000 |
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".