Psychometric Evaluation of the Dutch Version of the Assessment of Preschool Children's Participation (APCP): Construct Validity and Test–Retest Reliability
Bibliographic record
Abstract
The aim of this study is to examine construct validity, internal consistency, and test-retest reliability of the Dutch translation of the Assessment of Preschool Children's Participation (APCP) a participation measure for children aged 2 to 5 years and 11 months with and without physical disabilities. Parents of 126 preschool children participated. Sixty-seven of the children had no physical disabilities (mean age three years two months, SD 1.2) and 59 children had physical disabilities (mean age two years nine months, SD 1.8). Validity was tested using three hypotheses regarding having a physical disability, gender and age differences. Most, but not all hypotheses were confirmed. Children with a physical disability participated in fewer activities and with lower intensity than children without physical disabilities (p < .001). Boys and girls participated in an equally wide variety of activities and with similar intensity except for skill development. Four- to five-year-old children in general participated in more activities than two- to three-year-old children and had a higher intensity score (p < .001). For activity types, age differences were found for skill development (p < .001) and social activities (p < .001). Internal consistency was sufficient for four out of 10 activity types. Intra Class Correlations for test-retest reliability ranged from 63 to .91. Our findings indicate that the Dutch APCP shows sufficient psychometric properties for some but not all aspects of the measure.
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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 | 0.011 | 0.024 |
| 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".