Response Inhibition After Traumatic Brain Injury (TBI) in Children: Impairment and Recovery
Bibliographic record
Abstract
Children who experience traumatic brain injury (TBI) often show cognitive impairments postinjury, some of which recover over time. We examined the recovery of motor response inhibition immediately following TBI and over 2 years. We assessed the role of injury severity, age at injury, and lesion characteristics on initial impairment and recovery while considering the role of pre-injury psychiatric disorder. Participants were 136 children with TBI aged 5-16 years. Latency of motor response inhibition was measured with the stop-signal task within 1 month of the injury and again at 3, 6, 12, and 24 months. The performance of the TBI participants at each measurement occasion was standardized with 117 children of similar age, but without injury. Residualized latency scores were calculated. Growth curve analyses showed an initial impairment in response inhibition and improvement over the 2 years following injury. Younger TBI patients were initially more impaired although they exhibited greater recovery of response inhibition than did older TBI patients. Longer duration of coma, but not reactivity of pupils or Glasgow Coma Scale score, predicted initial deficit. Lesion characteristics or pre-injury attention deficit hyperactivity disorder did not predict initial impairment or recovery. Replication with longitudinal testing of a comparison group of children sustaining extracranial injury is necessary to confirm our findings.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".