Exploration of Potential Determinants of Implementation of a Clinical Practice Guide to Enhance Physical Activity Participation of Children With Developmental Coordination Disorder
Bibliographic record
Abstract
Purpose: This project explored the potential determinants (barriers and facilitators) of implementing a recently developed clinical practice guide (CPG) for the promotion and enhancement of the physical activity participation of children with developmental coordination disorder (DCD) prior to its release for clinical use. Method: The validated Clinician Guideline Determinants Questionnaire was used to explore the potential determinants reported by nine physiotherapists who provide services to children with DCD. Results: There was 100% agreement with the CPG content. All participants also agreed that following the CPG recommendations would improve care delivery and patient outcomes. Potential barriers of implementation were related to several factors, such as guideline factors (e.g., a lot of information, need for a visual summary), individual health professional factors (e.g., need for CPG training and experience), professional interactions (e.g., need to create community and school partnerships), and incentives and resources (e.g., need for dedicated time). Facilitators were having the above-mentioned needs met. Conclusions: Successful implementation of this CPG by paediatric physiotherapists may require: (1) that certain CPG and educational resources be put in place; (2) support to develop community and school partnerships, and (3) support from managers.
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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 | 0.017 | 0.085 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".