Evaluating score distributions in the revised Dutch version of the Childhood Health Assessment Questionnaire
Bibliographic record
Abstract
OBJECTIVES: Evaluating the original, and the revised version of the Dutch Childhood Health Assessment Questionnaire (CHAQ). To explore the effect of different score calculation methods and eight more challenging items as proposed by Lam et al. (2004) on the score distribution in a population of patients with Juvenile Idiopathic Arthritis (JIA). METHODS: Two convenience samples of 59 and 31 children with JIA were studied. Box-and-whisker plots and the Kolmogorov-Smirnov (K-S) one-sample test of normality were used, to explore the score distributions. RESULTS: The results of this study confirm a ceiling effect when using the original CHAQ-30 with either score calculation method. The original CHAQ with the added eight more challenging items and the "mean" score calculation method, as well as the revised CHAQ showed less ceiling effect. CONCLUSION: The original CHAQ-38 with the "mean" score calculation method as well as the revised CHAQ are a possible alternative for future studies. However, there is a need for further prospective studies to improve the CHAQ and to support our findings.
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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 | 0.013 | 0.032 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".