The Concept of a Toolbox of Outcome Measures for Children With Cerebral Palsy
Bibliographic record
Abstract
Accurate and well-targeted measurement of a child's abilities and participation in daily activities pre- and post-intervention is essential to understanding the effects of therapies provided by pediatric practitioners. There is growing interest in identification of outcome core sets for specified client groups. This article elaborates on the concepts to consider when selecting and interpreting measures from an outcomes toolbox for children with cerebral palsy. Principles discussed include use of self-report measures to open a dialogue with the child/parent; a holistic assessment approach to identify a child's challenges, strengths, and contextual factors that can influence functioning; links between measurement and heightened engagement of the child/family in the rehabilitation process and goals; and the need to plan the evaluation and dialogue aspects of the assessment process. If clinicians across the international rehabilitation community draw from the same toolbox, the end result could be a cohesive approach and common language to outcome measurement.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".