Development and initial validation of the Children Participation Questionnaire (CPQ)
Bibliographic record
Abstract
PURPOSE: To develop and test the psychometric properties of a parent-reported questionnaire measuring participation of preschool children (Children Participation Questionnaire; CPQ) aged 4-6 years in their everyday activities. METHODS: Reliability was tested by Cronbach's alpha and by test-retest. Construct validity was computed by known group differences analysis. Convergent and divergent validities were calculated by correlation with the Vineland Adaptive Behaviour Scale (VABS). Two hundred thirty-one children with mild to moderate developmental disabilities (mean age 5.16 +/- 0.66 years old) were compared to 249 children without disability (mean age 5.13 +/- 0.72 years old). RESULTS: The CPQ has good internal reliability. Cronbach's alpha for the participation measures ranged between 0.79 and 0.90, indicating good homogeneity. The temporal stability of the CPQ was supported with intra-class correlations ranging from 0.71 to 1.00. Significant differences were found between children with and without disabilities in all the CPQ measures. The CPQ could also differentiate between age groups and groups of varying socio-economic status. Convergent and divergent validity were supported. CONCLUSIONS: The CPQ has demonstrated good psychometric properties and can be used as a reliable and valid measure to assess children's participation at the age of 4-6 years.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".