Concussion related deficits in the general population predict impairments in varsity footballers
Bibliographic record
Abstract
ObjectiveWe investigated the long-term cognitive effects of concussion in 19,261 members of the general population and a cohort of varsity American football players with a history of frequent head impacts, using tests that are known to be sensitive to small changes in performance. MethodsWe asked 19,261 participants to complete a demographic questionnaire and 12 cognitive tests measuring aspects of executive function, including inhibitory control. We compared the performance of those reporting a history of concussion (post-concussion) to those reporting no history of concussion (non-concussed) on the cognitive battery and four non-cognitive variables. We used the results of this population-level study to predict the profile of cognitive performance in varsity American football players, who completed the same cognitive tasks. ResultsPost-concussion and non-concussed participants did not differ on 11 of the 12 cognitive tasks employed. However, on a test of inhibitory control based on the classic Stroop paradigm, post-concussion participants showed accuracy-related impairments specific to the incongruent conditions of the task. Post-concussion participants reported higher levels of anxiety, depression, and trouble concentrating. An entirely independent sample of 74 varsity American football players demonstrated the same pattern of impairment: compared to healthy controls, they scored significantly lower on the test of inhibitory control but were indistinguishable from controls on the 11 other tasks.InterpretationSelf-reported concussion is not associated with long-term general effects on cognitive function. Nevertheless, those who report at least one concussion and those who expose themselves to long-term frequent sport-related head impacts, do have a modest, but statistically robust, deficit of inhibitory control.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".