The Gait Outcomes Assessment List (GOAL): validation of a new assessment of gait function for children with cerebral palsy
Bibliographic record
Abstract
AIM: We investigated the validity of the Gait Outcomes Assessment List (GOAL), as an assessment of gait function in children with cerebral palsy (CP). METHOD: We studied a prospective cohort of 105 children with CP (Gross Motor Function Classification System [GMFCS] levels I-III; 65 males, 40 females; mean [SD] age 11y 11mo [3y 5mo], range 6-20y), who attended gait assessment over a 10-month period. Parents completed the GOAL, Functional Mobility Scale (FMS), and Functional Assessment Questionnaire (FAQ) during their child's gait evaluation. Ninety children completed instrumented gait analysis (IGA). Total GOAL and domain scores, Gait Profile Score (GPS), and Gait Variable Scores were calculated. RESULTS: =42.4, p<0.001]). Moderate correlations were found between total GOAL and FMS (5m and 50m r=0.59; 500m r=0.66) and FAQ walking (r=0.77) and activities list (r=0.75, p<0.01). There was a moderate negative correlation between total GOAL and GPS (r=-0.59) and gait appearance domain and GPS (r=-0.52, p<0.01). INTERPRETATION: The GOAL is a valid assessment of gait function in ambulant children with CP. It has the potential to improve understanding of the child's and parents' priorities and thus, in conjunction with IGA, provide a more balanced assessment across the domains of the World Health Organization's International Classification of Functioning, Disability and Health. WHAT THIS PAPER ADDS: The Gait Outcomes Assessment List (GOAL) can discriminate between Gross Motor Function Classification System levels. The GOAL correlates with standard functional assessments and gait analysis. Used with gait analysis, the GOAL provides comprehensive assessment across all International Classification of Functioning, Disability and Health domains.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".