Trajectories of Executive Functions After Early Childhood Traumatic Brain Injury: Teacher Ratings in the Initial 81 Months Postinjury
Bibliographic record
Abstract
OBJECTIVE: To explore teacher-rated trajectories of executive functioning (EF) after early childhood traumatic brain injury (TBI) and to identify injury-related, academic, and family factors associated with growth trajectories using latent class growth analysis. PARTICIPANTS: A total of 121 children who sustained a TBI or orthopedic injury (OI) between the ages of 3 and 7 years were recruited from 3 tertiary care children's hospitals and a general hospital in Ohio, including 57 with moderate or severe TBI and 64 with OI. DESIGN: Assessments were completed at baseline (0-3 months postinjury) and an average of 6, 12, 18, and 81 months postinjury. Changes in teacher-rated EF were modeled across time and heterogeneity in recovery and moderating factors was examined. MEASURES: Study variables included participant demographics, teacher-rated EF (Behavior Rating Inventory of Executive Function), family functioning (McMaster Family Assessment Device), and parenting style (Parenting Practices Questionnaire). RESULTS: Analysis of teacher-rated EF yielded 2 trajectories: Normative (64.71%) and At-Risk (35.29%). Traumatic brain injury was a weak predictor of membership in the At-Risk trajectory ( P = .05). Membership in the At-Risk trajectory (compared with Normative category) was associated with a higher incidence of Individualized Education Programs, higher baseline EF concerns, increased endorsement of authoritarian parenting, lower socioeconomic status, and non-White race. CONCLUSION: Teacher-rated EF after pediatric TBI differs from OI. Increased EF concerns over time were associated with increased baseline EF and characteristics of the home and school environment. These findings extend previous research on recovery of EF to educational settings and outline potentially modifiable risk factors that can maximize success in the school settings for children who experience early-childhood traumatic injury.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".