Correspondence of classifications between parents of children with cerebral palsy aged 2 to 6 years and therapists using the Gross Motor Function Classification System
Bibliographic record
Abstract
AIM: The aim of this study was to determine the agreement and reliability of parent report using a lay version of the Gross Motor Function Classification System (GMFCS) among children with cerebral palsy in the two youngest age bands. METHOD: Data were obtained from the Canadian section of the Movement and Participation in Life Activities of Young Children study database. One hundred and thirty-two parents of two groups of children participated: children aged 2 to 4 years (35 males, 26 females; mean age 3y 2mo; SD 5mo) and children aged 4 to 6 years (39 males, 32 females; mean age 4y 11mo; SD 6mo) at the final data collection point. Therapists classified motor function using the GMFCS and parents used the GMFCS Family Report Questionnaire, with parents and therapists being masked to the others' responses. Agreement between respondents was determined using precise agreement and Cohen's unweighted kappa statistic. Reliability between respondents was determined using the intraclass correlation coefficient (ICC). RESULTS: Overall, precise agreement was 77%, chance-corrected agreement was κ = 0.70 (95% confidence interval [CI] 0.61-0.79), and reliability was ICC = 0.95 (95% CI 0.93-0.96). INTERPRETATION: These values indicate substantial agreement and reliability between parents of children aged 2 to 6 years and therapists. Some parents had a tendency to rate their children as more functionally limited than did therapists, leading us to question whose the true criterion standard' rating should be.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".