Quantifying cognitive function in concussed athletes before and after acute exercise using a choice reaction time task
Bibliographic record
Abstract
Following a concussion, cognitive deficits have been shown to last longer than symptom resolution. Currently clinicians rely heavily on symptom emergence following the fundamental exercises of the return to play (RTP) protocol, which may leave athletes at risk of returning to play too early if cognitive deficits have not been detected. The purpose of this study was to assess the effects of exercise on choice reaction time (CRT) both at rest and following an acute exercise in 3 populations: non-concussed (NC), recently concussed (RC), and post-concussion syndrome (PCS) individuals. A CRT task in the form of an iPad application measured each individual’s decision-making capabilities at four blocks: (1) 10 minutes prior to exercise, (2) Immediately prior to exercise, (3) immediately post exercise, and (4) 5 minutes post exercise. Participants were also fitted with an eye-tracking system during CRT task performance at rest in order to assess higher levels of cognitive processing. Results demonstrated a facilitative effect of learning and exercise arousal on CRT task performance in both NC and PCS but not in RC. Average RT in RC was not significantly different from NC while average RT in PCS was found to be significantly higher than NC. Gaze behaviour was significantly worse in PCS compared to NC while RC and NC were not significantly different. The absence of symptoms does not inherently mean that cognitive performance under acute physical stress has completely recovered in recently concussed individuals. On the other hand, PCS individuals continue to experience concussion-related symptoms, but appear to display partially recovered cognitive performance. Findings from the current study encourage the use of cognitive assessments following acute exercise during the RTP protocol in order to detect possibly lingering cognitive deficits.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".