Factors Associated With Self-Reported Concussion History in Middle School Athletes
Bibliographic record
Abstract
OBJECTIVE: Identifying personal characteristics associated with sustaining a concussion is of great interest, yet only a few have examined this in children. The purpose of this study was to examine the association between sex, neurodevelopmental disorders, health history, and lifetime history of self-reported concussion in 12- and 13-year-old athletes. DESIGN: Cross-sectional study. SETTING: Middle schools. PARTICIPANTS: Participants were 1744 twelve- and thirteen-year-old student athletes who completed preseason Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT) testing, including a self-report questionnaire about previous concussions, developmental diagnoses, and previous medical treatment. INDEPENDENT VARIABLES: Age, sex, attention-deficit/hyperactivity disorder (ADHD), learning disabilities (LDs), and previous treatment for migraine. MAIN OUTCOME MEASURES: Self-reported history of concussion. RESULTS: A minority of athletes (13.7%) reported previous concussions (1 concussion, n = 181; 2 concussions, n = 41; and 3+ concussions, n = 17). A small proportion reported a history of ADHD (4.4%), LD (2.8%) or migraine treatment (4.0%). Higher rates of self-reported previous concussions were associated with male sex [16.9% vs 9.1%; χ(1) = 21.47, P < 0.001] and previous migraine treatment [31.9% vs 13.0%; χ(1) = 20.08, P < 0.001]. There were no differences in self-reported concussion history between 12- and 13-year olds (P = 0.18) and those with/without ADHD (P = 0.41) or LDs (P = 0.06). The overall logistic regression model was statistically significant [χ(5) = 42.01, P < 0.001] but explained only 4.3% of the variance. Previous treatment for migraine [P < 0.001, Exp(B) = 3.30] and male sex [P < 0.001, Exp(B) = 2.06] were independently associated with a self-reported concussion history, whereas age, LD, and ADHD were not (P's > 0.05). CONCLUSIONS: Male sex and previous migraine treatment were associated with higher rates of self-reported previous concussions in both independent and multivariate models in middle school athletes, whereas age, ADHD, and LDs were not.
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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 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".