Towards a paradigm shift in pediatric rehabilitation: accelerating the uptake of evidence on participation into routine clinical practice
Bibliographic record
Abstract
PURPOSE: Evidence for the importance of focusing on participation to promote health and wellbeing in childhood-onset disability exists, but practice is slow to change. This paper provides a knowledge translation roadmap to accelerate uptake of participation evidence into day-to-day practice. MATERIALS AND METHODS: A structured roadmap to guide knowledge translation initiatives for implementing participation-based practices in co-creation with service users was developed based on elements from: the Five-factorframework for predicting implementation outcomes, the Cultural Cone framework, and the Knowledge-to-Action model. RESULTS: Guiding principles paired with examples of multi-component knowledge implementation strategies to facilitate readiness for change by stakeholders at the micro (e.g., client/family, service providers), meso (e.g., administrators within organisations such as rehabilitation centres, hospitals, schools) and macro (e.g., local and governmental policy, regulatory bodies) levels are introduced. Solution-based strategies are provided to facilitate "readiness to change" for each stakeholder group. The strategies are examples for successful implementation of evidence-based interventions/approaches that can be contextualized across settings. CONCLUSIONS: The knowledge translation roadmap can assist children and families, service providers, administrators, and policymakers to bridge existing knowledge-to-practice gaps surrounding participation. Partnering and collaborating through a "family-clinician-manager-community leader-policymaker" synergy is key for achieving strategic practice change focussed on participation.Implications for RehabilitationSound evidence surrounding the topic of participation, including effective assessments and interventions, is available and ready for use.Shifting towards participation-focused practices for children and youth with disabilities requires a systemic multi-level KT approach.Our Participation-KT roadmap, comprised of a framework and a list of principles and strategies for implementation, can be used to guide all stakeholders to foster a shift in practice.Forming partnerships and working collaboratively with all stakeholders is key for successful implementation.
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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 | 0.390 | 0.327 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.005 | 0.015 |
| Scholarly communication | 0.019 | 0.027 |
| Open science | 0.009 | 0.028 |
| Research integrity | 0.012 | 0.015 |
| Insufficient payload (model declined to judge) | 0.009 | 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".