Psychometric Properties of the Canadian Little Developmental Coordination Disorder Questionnaire for Preschool Children
Bibliographic record
Abstract
AIMS: Test the psychometric properties and cut-off scores for the Canadian Little Developmental Coordination Disorder Questionnaire (Little DCDQ), which screens for coordination difficulties in children aged 3 to 4 years. METHODS: Parents of children with typical development (n = 108) and children at risk for motor problems (n = 245) completed the questionnaire. A subgroup (n = 119) of children was tested with the Movement Assessment Battery for Children-2 (MABC-2) and the Beery-Buktenica Developmental Test of visual-motor integration (VMI) to determine motor impairment (MI). RESULTS: Test-retest reliability (r = 0.956, p < .001) and internal consistency (Cronbach's alpha = 0.94) were high. Construct validity was supported by a factor analysis and significant difference in scores of children who were typically developing and were at risk. Concurrent validity was evaluated for the children who received standardized motor testing, with significant difference between children with and without MI. Discriminant function analysis showed that all 15 items were able to distinguish the two groups. The questionnaire correlated well with the MABC-2 and VMI. Validity as a screening tool was assessed using logistic regression modeling (X(2)(5) = 25.87, p < .001) and receiver operating curves, establishing optimal cut-off values with adequate sensitivity. CONCLUSIONS: The Little DCDQ is a reliable, valid instrument for early identification of children with motor difficulties.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".