Attention Deficit Hyperactivity Disorder Symptoms and Response Inhibition After Closed Head Injury in Children: Do Preinjury Behavior and Injury Severity Predict Outcome?
Bibliographic record
Abstract
We examined the effect of closed head injury (CHI) on the development of symptoms of secondary attention deficit hyperactivity disorder (SADHD), emotional disturbance, and impaired response inhibition. We also investigated the relation of developmental and recovery variables to SADHD symptoms and inhibition. Participants were 200 children aged 5-17 years, 137 children who had CHI, and 63 children with no history of CHI served as controls. We assessed preinjury behavior problems, head injury variables (severity, age at time of injury, time since injury), postinjury SADHD, and anxiety symptoms at least 2 years following the head injury. Response inhibition was measured with the stop-signal task. CHI predicted the development of SADHD symptoms and anxiety with more severe injury predicting more severe outcomes. Only the combination of severe CHI and a high level of SADHD symptoms predicted poor response inhibition. Postinjury anxiety was not associated with poor inhibition. The consequences of CHI did not vary with age at injury or time since injury, but poorer outcome was predicted by preinjury behavior problems. CHI in children leads to SADHD symptoms and anxiety even after taking preinjury disturbance into account. Poor response inhibition is a consequence of CHI but only when the CHI is severe and the child manifests high levels of SADHD symptoms.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".