Ecosystemic Needs Assessment for Children with Developmental Coordination Disorder in Elementary School: Multiple Case Studies
Bibliographic record
Abstract
This study explored the needs of children with developmental coordination disorder (DCD) from an ecosystemic viewpoint as part of a theory-driven program evaluation process. A multiple case study needs assessment was conducted. Participants included ten children with DCD, their parents (n = 12), teachers (n = 9), and service providers (n = 6). Data collection involved semi-structured interviews, validated questionnaires, and a review of the children's records. The results support the relevance of using an ecosystemic model to assess the needs of children with DCD in their life and social contexts. More specifically, the results highlight the need to provide additional services at school, such as occupational therapy and special education, as well as information and training regarding DCD for parents and teachers. The results also point to the relevant variables to consider in an intervention program based on theory-driven evaluations. This study shows how employing an ecosystemic frame of reference provides a better understanding of the needs of children with DCD. Future research should document the ecosystemic profiles and evolution of the needs of children with DCD with a larger sample from diverse socioeconomic backgrounds using a longitudinal study design.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".