Multiple Past Concussions in High School Athletes with ADHD (P7.170)
Bibliographic record
Abstract
OBJECTIVE: To examine cognitive functioning and symptom reporting associated with multiple concussions in male high school athletes with Attention Deficit Hyperactivity Disorder (ADHD). BACKGROUND: ADHD and history of multiple concussions are important risk factors or modifiers to consider in concussion assessment and management. Current evidence suggests that individuals with ADHD have a higher lifetime prevalence of concussions. To date, however, there are no published studies examining the association between multiple prior concussions, cognition, and symptom reporting in student athletes with ADHD. DESIGN/METHODS: High school boys with ADHD (N=1,261) completed ImPACT® baseline testing prior to participating in sports. Cognitive test performance and symptom reporting was compared between athletes with ADHD who reported a history of 0, 1, 2, or 3 or more concussions. No athlete reported experiencing a concussion in the past 6 months. RESULTS: The majority (76.0[percnt]; n=958) of the ADHD sample reported a history of no previous concussions, 15.2[percnt] (n=192) reported a history of 1 concussion, 4.8[percnt] (n=61) reported a history of 2 concussions, and 4.0[percnt] (n=50) reported a history of 3 or more concussions. ImPACT® cognitive composite scores (i.e., verbal memory, visual memory, visual motor, and reaction time) were relatively consistent across these subgroups; those with prior injuries did not perform more poorly than those with no prior injuries. However, athletes with a history of 3 or more prior concussions reported significantly more symptoms at baseline. CONCLUSIONS: To our knowledge, this is the first large-scale study examining cognitive performance and symptom reporting associated with concussion history in high school athletes with ADHD. Consistent with previous findings in young athletes with multiple concussions, athletes with ADHD and a history of multiple concussions reported greater symptoms than those with no concussion history.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".