Social and Behavioral Outcomes following Childhood Traumatic Brain Injury: What Predicts Outcome at 12 Months Post-Insult?
Bibliographic record
Abstract
This study sought to investigate social and behavioral outcomes 12 months following childhood traumatic brain injury (TBI) and to identify predictors of these outcomes. The study also compared rates of impairment in social and behavioral outcomes at 12 months post-injury between children with TBI and a typically developing (TD) control group. The study comprised 114 children ages 5.5 to 16.0 years, 79 with mild, moderate, or severe TBI and 35 TD children, group-matched for age, sex and socio-economic status. Children with TBI were recruited via consecutive hospital admissions and TD children from the community. Social and behavioral outcomes were measured via parent-rated questionnaires. Analysis of covariance models identified a significant mean difference between the mild and moderate groups for social problems only, but the moderate and severe TBI groups showed a higher rate of impairment, particularly in externalizing problems. Pre-injury function, injury severity, parent mental health, and child self-esteem all contributed significantly to predicting social and behavioral outcomes. Both injury and non-injury factors should be considered when identifying children at risk for long-term difficulties in social and behavioral domains.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".