Social skill and social withdrawal outcomes in children following pediatric stroke
Bibliographic record
Abstract
Pediatric stroke can result in long-term impairments across attention, functional communication and motor domains. The current paper utilized parent reports of the Behavioral Assessment System for Children 2nd Edition and the Pediatric Stroke Outcome Measure to examine children’s social skills and withdrawal behavior within a pediatric stroke population. Using the Canadian Pediatric Stroke Registry at The Hospital for Sick Children, data were analyzed for 312 children with ischemic stroke. Children with ischemic stroke demonstrated elevated parent-reported social skills problems (observed = 20.51%, expected = 14.00%) and clinically elevated social withdrawal (observed = 11.21%, expected = 2.00%). Attentional problems significantly contributed to reduced social skills, F (3,164) = 30.68, p < 0.01, while attentional problems and neurological impairments accounted for increased withdrawal behavior, F (2, 164) = 7.47, p < 0.01. The presence of a motor impairment was associated with higher social withdrawal compared to individuals with no motor impairment diagnosis, t(307.73) = 2.25, p < .025, d = 0.25, 95% CI [0.42, 6.21]. The current study demonstrates that children with stroke who experience motor impairments, attentional problems, reduced functional communication skills, and neurological impairments can experience deficits in their social skills and withdrawal behavior.
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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 | 0.003 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".