Academic Challenges in Developmental Coordination Disorder: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
AIMS: Developmental Coordination Disorder (DCD) is a chronic condition affecting motor coordination in daily activities. While motor difficulties are well documented in this population, it is unclear how frequent and to what extent academic activities are affected. This systematic review aims to comprehensively summarize the knowledge regarding the prevalence and extent of academic difficulties in reading, writing and mathematics in school-aged children with DCD. METHODS: Two independent reviewers analyzed original studies on academic difficulties in school-aged children with DCD. A binary random-effects model was used to calculate the pooled prevalence by academic difficulty. A random-effects model using standardized mean differences (g statistic) was calculated to estimate the extent of the academic difficulties. RESULTS: Twenty-four studies were included. A pooled prevalence of 84% of handwriting difficulties and 89.5% of mathematical difficulties was reported. No pooled prevalence of difficulties could be calculated for the other academic outcomes. Children with DCD present with poorer performance in handwriting legibility (g = -1.312) and speed (g = -0.931), writing (g = -0.859), mathematics (g = -1.199) and reading (g = -1.193). CONCLUSIONS: This review highlights the high frequency and severity of academic difficulties in children with DCD, specifically in mathematics, which stresses the importance of evaluating academic performance to target interventions to support optimal functioning in daily life.
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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 | 0.012 | 0.039 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.023 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".