Social problem-solving and social adjustment in paediatric traumatic brain injury
Bibliographic record
Abstract
OBJECTIVE: Little is known regarding the predictors of social deficits that occur following childhood traumatic brain injury (TBI). The current study sought to investigate social problem solving (SPS) and its relationship to social adjustment after TBI. METHODS: Participants included 8-13 year old children, 25 with severe TBI, 57 with complicated mild-to-moderate TBI and 61 with orthopaedic injuries (OI). Children responded to scenarios involving negative social situations by selecting from a fixed set of choices their causal attribution for the event, their emotional reaction to the event and how they would behave in response. Parent ratings of social behaviours and classmate friendship nominations and sociometric ratings were obtained for a sub-set of all participants. RESULTS: Children with severe TBI were less likely than children with OI to indicate they would attribute external blame or respond by avoiding the antagonist; they were more likely to indicate they would feel sad and request adult intervention. Although several SPS variables had indirect effects on the relationship between TBI and social adjustment, clinical significance was limited. CONCLUSIONS: The findings suggest that, while children with TBI display atypical SPS skills, SPS cannot be used in isolation to accurately predict social adjustment.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".