Exploring Assessment Tools and the Target of Intervention for Children with Developmental Coordination Disorder
Bibliographic record
Abstract
PURPOSE: We reviewed current practice for children with Developmental Coordination Disorder (DCD) using research evidence and the International Classification of Functioning, Disability and Health (ICF). Characteristics of children with DCD can be described at the levels of body function (impairments), whole body movements (activities) and involvement in life situations (participation). SUMMARY OF KEY POINTS: Descriptive instruments measuring the extent of motor impairments or activity limitations can be used to: (1) identify children who might benefit from intervention; and (2) determine the optimal type of intervention and model of service delivery. Evaluative tools that measure activities or participation, but not primary impairments, should be used to determine change over time. Commonly used measures for describing children with DCD and evaluating outcomes are reviewed and discussed in the context of the ICF framework. Intervention approaches are then outlined for children with DCD that are targeted to the levels of activity, participation, and prevention of secondary impairments. CONCLUSIONS: Outcomes of children with DCD will be optimized with the use of current research evidence and the appropriate ICF level guiding both assessment and intervention.
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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 | 0.014 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".