Development of the Applied Coaching Tool for Pediatric Rehabilitation Therapists: A Practice Support Tool for Therapists Coaching Parents of Young Children
Bibliographic record
Abstract
AIM: Describes the development and implementation of the Applied Coaching Tool (ACT), and training protocol, to build coaching competency in therapists supporting parents of young children. METHODS: The ACT was developed using literature review, draft tool creation, expert review and refinement. A training protocol for therapists to learn how to coach was developed using principles of adult learning, coaching and instructional design to increase learner competence and confidence. RESULTS: The ACT framework includes five coaching events to support therapists to implement coaching practices including self-directed goals, learner-focused interventions with meaningful reflection, practice and feedback. Within the ACT, behaviors associated with coaching events were defined as overt therapist actions and elaborations - examples of interactional behaviors. The training plan for therapists consisted of a workshop, intentional practice with coaching feedback over a period of five months, and assessment of competence. Pilot implementation demonstrated evidence of acceptability, appropriateness, adoption and fidelity of the ACT. CONCLUSION: Use of the ACT, and the training plan, provides practical clinical behaviors for therapists to coach families to be active participants in rehabilitation which may contribute to improvements in self-efficacy and motivation in therapy. Furthermore, it provides a reliable standard amongst therapists coaching in pediatric rehabilitation.
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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 | 0.021 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".