Evaluating the Factor Structure and Criterion Validity of the Canadian Little DCDQ: Associations Between Motor Competence, Executive Functions, Early Numeracy Skills, and ADHD in Early Childhood
Bibliographic record
Abstract
The Canadian Little Developmental Coordination Disorder Questionnaire (Little DCDQ-CA) is a parent-report screening instrument that identifies 3- to 4-year-old children who may be at risk for Developmental Coordination Disorder (DCD). We tested the factor structure and criterion validity of the Little DCDQ-CA in a sample of preschool-aged children in the United States ( N = 233). Factor analysis indicated that the DCDQ-CA was best represented by one factor. Using cutoff scores that were proposed by the developer, 45% of the sample was identified as at-risk for DCD. Although a much larger percentage of children was identified as at-risk than would be expected based on the prevalence of formal DCD diagnoses in the population, the Little DCDQ-CA demonstrated good criterion validity. Specifically, compared with their peers, children who exceeded the at-risk criterion demonstrated worse motor competence, executive functioning skills, and early numeracy skills and were rated as having greater ADHD behaviors by their teachers, all consistent with expectations for children who are at risk for DCD. Results are discussed as they relate to future use of the Little DCDQ-CA.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".