Understanding performance deficits in developmental coordination disorder: a meta‐analysis of recent research
Bibliographic record
Abstract
AIM: Developmental coordination disorder (DCD) is a significant disorder of childhood, characterized by core difficulties in learning fine and/or gross motor skills, and the attendant psychosocial problems. The aim of the meta-analysis presented here (the first on DCD since 1998) was to summarize trends in the literature over the past 14 years and to identify and describe the main motor control and cognitive deficits that best discriminate children with DCD from those without. METHOD: A systematic review of the literature published between January 1997 and August 2011 was conducted. All available journal papers reporting a comparison between a group of children with DCD and a group of typically developing children on behavioural measures were included. RESULTS: One hundred and twenty-nine studies yielded 1785 effect sizes based on a total of 2797 children with DCD and 3407 typically developing children. Across all outcome measures, a moderate to large effect size was found, suggesting a generalized performance deficit in children with DCD. The pattern of deficits suggested several areas of pronounced difficulty, including internal (forward) modelling, rhythmic coordination, executive function, gait and postural control, catching and interceptive action, and aspects of sensoriperceptual function. INTERPRETATION: The results suggest that the predictive control of action may be a fundamental disruption in DCD, along with the ability to develop stable coordination patterns. Implications for theory development and intervention are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.013 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.019 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".