Bibliographic record
Abstract
PURPOSE: The purpose of this research is to understand the important components of client-centred rehabilitation from the perspective of adult clients with long-term physical disabilities. METHOD: Focus groups were conducted with adult clients who had completed at least one course of rehabilitation in the publicly-funded rehabilitation system in Ontario. Data were analysed using an iterative inductive approach. RESULTS: The major theme underlying all of the participants' comments was the need for better transitions between rehabilitation programs and the community. Participants felt ill-prepared for community living and the emotional challenges of living with a long-term condition and, once discharged from rehabilitation, felt isolated and had difficulty finding out about and accessing community services. CONCLUSIONS: The findings demonstrate that client-centred rehabilitation encompasses much more than goal-setting and decision-making between individual clients and professionals. It refers to a philosophy or approach to the delivery of rehabilitation services that reflects the needs of individuals and groups of clients. This entails a shift from an acute-illness, curative model to one that acknowledges the long-term nature of the career of chronic illness or disability. Definitions of evidence that is deemed credible need to be broadened beyond expert, 'scientific' evidence to include multiple dimensions of evidence including the expertise of the client.
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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 | 0.014 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.009 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".