Baseline concussion symptom report in college athletes: comparison of scores on SCAT2 versus impact
Bibliographic record
Abstract
Objective To investigate differences between baseline self-report of concussion symptoms with two commonly used concussion assessment tools. Design Retrospective, cross-sectional. Setting University of Alberta. Subjects One hundred and ninety-four varsity athletes (117 males; 77 females). Intervention Prior to the competitive season, subjects completed baseline testing, including self-report of concussion symptoms, with the Subjective Concussion Assessment Tool (SCAT2) and the on-line computerised Immediate Post-Concussion Assessment of Cognition (ImPACT) test, under supervision of an athletic therapist. Testing was counterbalanced to control for serial position effect. Outcome Measures The 18 shared self-report concussion symptoms were compared, and a general linear model used to identify possible interactions between gender and group type (SCAT2 vs ImPACT). Finally correlations were calculated. Results There was an interaction between gender and group type for 1 symptom (trouble falling asleep). Surprisingly, pairwise comparisons identified differences (p≤ 0.05) on 10/18 paired symptoms, with correlations ranging from 0.08 to 0.58. Conclusions Subjects respond differently when self-reporting concussion symptoms, depending on type of instrument used, and mode of administration. Despite test items being similar in content, there are significant differences in symptom reports in the same subject between SCAT2 and ImPACT tests. Use of similar data collection methods for baseline testing, assessment post-injury and prior to return-to-play is indicated, to increase both the diagnostic and prognostic utility of such tests. This further emphasises current recommendations that these tests not be used in isolation to make therapeutic decisions regarding athletes with concussion; and underscores the importance of serial clinical evaluations by a suitably qualified physician. Competing interests None. All authors have signed the disclosure form.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.002 | 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".