Head Impact Burden and Change in Neurocognitive Function During a Season of Youth Football
Bibliographic record
Abstract
OBJECTIVE: To determine the association of repetitive subconcussive head impacts with functional outcomes in primary and high school tackle football players. SETTING: Youth football fields and an outpatient sports neurology clinic. PARTICIPANTS: A total of 112 primary school (n = 55, age 9-12 years) and high school (n = 57, age 15-18 years) football players. DESIGN: A prospective cohort study. MAIN MEASURES: Helmet-based sensors were used to record head impacts during practices and games during the 2016 football season. Impact g-forces were summed to yield a measure of cumulative impact. History of self-reported premorbid medical diagnoses was obtained preseason. Players completed assessments of a variety of outcomes both pre- and postseason: neuropsychological test performance, symptoms, vestibular and ocular-motor screening, balance, parent-completed attention-deficit hyperactivity disorder (ADHD) symptoms, and self-reported behavioral adjustment. RESULTS: Average cumulative impact was 3700 (standard deviation = 2700) g-forces for the season and did not differ between age groups (P = .594). Cumulative impact did not predict pre- to postseason change scores on any outcome measures (all P > .05). Instead, younger age group and reported history of premorbid ADHD predicted change scores on several cognitive testing measures and parent-reported ADHD symptoms, while reported history of premorbid anxiety and depression predicted change scores on symptom reporting. CONCLUSIONS: In youth tackle football, subconcussive head impacts sustained over the course of a single season may not be associated with neurocognitive functional outcomes. The absence of a significant association may reflect the relatively short follow-up interval, and signals the need for studies across multiple seasons.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".