Quality of life in children with acquired brain injury: Parent perspectives 1–5 years after injury
Bibliographic record
Abstract
PRIMARY OBJECTIVE: To obtain parental ratings of children's quality of life, cognitive, emotional and behavioural functioning, as well as ratings of service provision, following traumatic brain injury (TBI). RESEARCH DESIGN: A retrospective, cross-sectional study. METHODS AND PROCEDURES: Parents of 47 children with mild or moderate-severe TBI completed standardized questionnaires evaluating quality of life (PedsQL 4.0) and cognitive, emotional and behavioural functioning (Strengths and Difficulties Questionnaire). Data collected was compared with published normative data for these scales. Views regarding parental experiences of care and their ratings of service provision were also obtained. RESULTS: Quality of life was significantly lower in 13-times as many children with TBI than expected from the normative population. Parents reported that more than 43% of children with TBI had cognitive, emotional and behavioural difficulties that impacted on their daily life. Whilst high levels of social deprivation were found, this did not fully explain the significantly raised levels of difficulties. Another factor associated with this poor outcome was the absence of systematic, routine follow-up or intervention. CONCLUSIONS: Parents frequently reported poor quality of life and cognitive, emotional and behavioural problems in their children following TBI. These preliminary findings indicate that children, after TBI, are at risk of developing persistent clinical problems and require follow-up beyond the acute period of their recovery.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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 | 0.000 |
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".