Predictors of externalizing behavior outcomes following pediatric stroke
Bibliographic record
Abstract
Children who experience pediatric stroke are at higher risk for future behavioral problems in childhood. We examined the prevalence of parent reported externalizing behaviors and executive function problems in children following stroke and neurological predictors. This study included 210 children with pediatric ischemic stroke (mean age 9.18 years (SD = 3.95)). The parent form of the Behavioral Assessment System for Children-Second Edition (BASC-2) and Behavior Rating Inventory of Executive Function (BRIEF) were used to evaluate externalizing behavior and executive function. No externalizing behavior or executive function differences were found between perinatal (n = 94) or childhood (n = 116) stoke, except for the shift subscale which had higher T-scores among the perinatal group (M = 55.83) than childhood group (M = 50.40). When examined together, 10% of children had clinically elevated hyperactivity T-scores as opposed to the expected 2%. Parents endorsed higher ratings of concern on the behavior regulation and metacognition indices of the BRIEF. Externalizing behaviors were correlated moderately to strongly with executive functions (r = 0.42 to 0.74). When examining neurological and clinical predictors of externalizing behaviors, only female gender was predictive of increased hyperactivity (p = .004). However, there were no significant gender differences in diagnosis of attention deficit hyperactivity disorder (ADHD). In summary, in this cohort, children with perinatal and childhood stroke did not differ on parent reported externalizing behavior or executive function outcomes. However, compared to normative data, children with perinatal or childhood stroke are significantly more likely to experience clinically elevated levels of hyperactivity.
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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 | 0.000 | 0.002 |
| 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 | 0.001 |
| 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".