Factors associated with mathematical capacity in children with Developmental Coordination Disorder
Bibliographic record
Abstract
BACKGROUND: Developmental Coordination Disorder (DCD) is a condition characterized by difficulties in motor planning and coordination and affects 5 to 6% of all school-aged children. Children with DCD frequently present with difficulties with academic activities such as handwriting. However, no study to date has comprehensively described mathematical capacity and its potential associated factors in this high-risk group. AIMS: We aimed to describe the frequency and nature of mathematical difficulties of school-aged children with DCD and to evaluate potential factors associated with mathematical performance. METHODS: A total of 55 elementary school-aged children with DCD underwent comprehensive standardized assessments of mathematical, visuoperceptual (VP), attentional, visual-motor integration (VMI), and motor skills. The contribution of each factor to mathematical capacity was established using hierarchical multivariate linear regression models. RESULTS: Children with DCD (9.1 ± 1.5 years, 44 males) had lower overall mathematical capacity compared to normative data (-0.59 SD) on the KeyMath 3rd edition, with poorer performance in basic concepts and problem-solving. Thirty-eight percent of the sample performed below the 15th percentile in overall mathematical skills. VP skills were the most important factors associated with most mathematical domains. Thirty-four percent of the variance of overall mathematical capacity was explained by VP skills, inattention, VMI and motor impairments while controlling for household income (F [5,49]=5.029, p < .0001). CONCLUSION: Children with DCD present with mathematical difficulties in basic concepts and problem-solving, which are partially explained by VP skills. Our findings stress the important of systematically assessing mathematical difficulties children with DCD to ensure they receive the necessary support that leads to academic success.
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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 | 0.000 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".