REIMAGINING POLICY AND MODELS OF SERVICE DELIVERY TO ENHANCE ACCESS AND ENGAGEMENT IN PUBLICLY FUNDED PEDIATRIC REHABILTATION SERVICES
Bibliographic record
Abstract
Family-centred pediatric rehabilitation services have widely accepted benefits related to a child’s functioning and participation. However, some families experience barriers to accessing and engaging with these services. Families have identified that organizational policies and models of service delivery can impact their experiences with pediatric rehabilitation services. There is a paucity of research focusing on how policies and service delivery models impact access and engagement in Ontario’s publicly-funded pediatric rehabilitation services. Furthermore, there is a gap in the evidence related to recommendations for potential modifications to these structures to enhance access and engagement in these services. The first objective of this thesis is to critically examine policy in publicly-funded pediatric rehabilitation services to understand its impact on access to services. The second objective is to use co-design methodology to improve models of service delivery, with a focus on telerehabilitation, to improve access and engagement in pediatric rehabilitation services. These objectives are achieved through the research outputs of this thesis including recommendations supporting the development of inclusive discharge policies (Chapter 2) and co-created solutions aimed at enhancing experiences with pediatric telerehabilitation (Chapters 3 and 4). Findings from the critical discourse analysis of discharge policies in Chapter 2 emphasized the importance of taking an ethical and family-centred approach to policy development that authentically includes and amplifies family voices. Chapters 3 and 4 used co-design methodology engaging caregivers, clinicians and pediatric rehabilitation service managers to develop solutions focused on improving the 3C’s of communication, consistency and connection to enhance access and engagement with pediatric telerehabilitation services. The findings of this thesis call policy-makers and pediatric rehabilitation service organizations to extend the provision of family-centred service beyond the point of care to include authentic engagement of families in the development of policies and service delivery models.
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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 | 0.105 | 0.099 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.010 | 0.013 |
| Scholarly communication | 0.020 | 0.011 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".