Multiple Past Concussions in High School Football Players
Bibliographic record
Abstract
BACKGROUND: There is increasing concern about the possible long-term effects of multiple concussions, particularly on the developing adolescent brain. Whether the effect of multiple concussions is detectable in high school football players has not been well studied, although the public health implications are great in this population. PURPOSE: To determine if there are measureable differences in cognitive functioning or symptom reporting in high school football players with a history of multiple concussions. STUDY DESIGN: Cross-sectional study; Level of evidence, 3. METHODS: Participants included 5232 male adolescent football players (mean [±SD] age, 15.5 ± 1.2 years) who completed baseline testing between 2009 and 2014. On the basis of injury history, athletes were grouped into 0 (n = 4183), 1 (n = 733), 2 (n = 216), 3 (n = 67), or ≥4 (n = 33) prior concussions. Cognitive functioning was measured by the Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT) battery, and symptom ratings were obtained from the Post-Concussion Symptom Scale. RESULTS: There were no statistically significant differences between groups (based on the number of reported concussions) regarding cognitive functioning. Athletes with ≥3 prior concussions reported more symptoms than did athletes with 0 or 1 prior injury. In multivariate analyses, concussion history was independently related to symptom reporting but less so than developmental problems (eg, attention or learning problems) or other health problems (eg, past treatment for psychiatric problems, headaches, or migraines). CONCLUSION: In the largest study to date, high school football players with multiple past concussions performed the same on cognitive testing as those with no prior concussions. Concussion history was one of several factors that were independently related to symptom reporting.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".