Early Identification and Risk Management of Children with Developmental Coordination Disorder
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to determine the motor control issues, motor learning differences, and secondary impairments of children with developmental coordination disorder (DCD) and to explore physical therapists' contribution to their early management. SUMMARY OF KEY POINTS: DCD is a condition involving limitations in gross motor, postural, and/or fine motor performance that is not attributable to other neurological disorders. Manifestation is varied across children and depends, in part, on their level of anticipatory motor control, response to specific task demands, and ability to attend to feedback to obtain flexible, adaptive movement solutions. Children with DCD rely primarily on vision for feedback, frequently use "fixing" strategies, and exhibit limited motor repertoires. As a result of their movement problems, they tend to avoid physical activity and are prone to secondary impairments, including decreased strength and power. CLINICAL IMPLICATIONS AND RECOMMENDATIONS: Physical therapists can 1) use their keen observational skills to identify children with DCD earlier in life and 2) use their knowledge of the secondary impairments and movement difficulties to work with families to engage children in continuous movement activities to maintain strength and power and thus obtain the physical, social, and psychosocial benefits of physical activity.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".