Test–Retest Reliability and Construct Validity of the German Translation of the Gait Outcome Assessment List (GOAL) Questionnaire for Children with Ambulatory Cerebral Palsy
Bibliographic record
Abstract
Abstract The Gait Outcome Assessment List (GOAL) is a patient or caregiver-reported assessment of gait-related function across different domains of the International Classification of Functioning, Disability, and Health (ICF) developed for ambulant children with cerebral palsy (CP). So far, the questionnaire is only available in English. The aim of this study was to translate the GOAL into German and to evaluate its reliability and validity by studying the association between GOAL scores and gross motor function as categorized by the gross motor function classification system (GMFCS) in children with cerebral palsy (CP). The GOAL was administered to primary caregivers of n = 91 children and adolescents with CP (n = 32, GMFCS levels I; n = 27, GMFCS level II; and n = 32, GMFCS level III) and n = 15 patients were capable of independently completing the whole questionnaire (GMFCS level I). For assessing test–retest reliability, the questionnaire was completed for a second time 2 weeks after the first by the caregivers of n = 36 patients. Mean total GOAL scores decreased significantly with increasing GMFCS levels with scores of 71 (95% confidence interval [CI]: 66.90–74.77) for GMFCS level I, 56 (95% CI: 50.98–61.86) for GMFCS level II, and 45 (95% CI: 40.58–48.48) for GMFCS level III, respectively. In three out of seven domains, caregivers rated their children significantly lower than children rated themselves. The test–retest reliability was excellent as was internal consistency given the GOAL total score. The German GOAL may serve as a much needed patient-reported outcome measure of gait-related function in ambulant children and adolescents with CP.
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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 | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".