An evaluation of the responsiveness of a comprehensive set of outcome measures for children and adolescents with traumatic brain injuries
Bibliographic record
Abstract
The relative responsiveness of nine outcome measure scales was evaluated with 33 children and adolescents (aged 4-18 years) who had sustained traumatic brain injuries. Scales were selected to evaluate outcomes from each of the World Health Organization (WHO) International Classification of Functioning, Disability and Health domains. The outcome measures were administered to all participants during their inpatient rehabilitation stay and again at a follow-up clinic visit. No single outcome measure captured the diversity of improvement in this sample. The measures agreed that improvement had occurred, but did not agree about which children were improving. This result suggests that the scales were measuring different skills and outcomes. Three of the measures used in combination, either the Child Health Questionnaire or the Functional Independence Measure for Children, the American Speech-Language-Hearing Association National Outcome Measures System (Birth to Kindergarten NOMS/School-aged Health Care) and the Gross Motor Function Measure, are sufficient to detect change in each of the children where change occurred. The Pediatric Evaluation of Disability Inventory and the MultiAttribute Health Status Classification were the least responsive of the nine measures used.
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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 | 0.027 | 0.089 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".