Wellness in children’s rehabilitation – what does it mean?
Bibliographic record
Abstract
PURPOSE: Rehabilitation research on wellness promotion for children and youth with disabilities is limited and tends to narrowly focus on physical aspects of health. An overarching sense of wellness includes multiple, overlapping dimensions (e.g., physical, social, emotional, occupational). This study's main objectives were to explore what wellness means for young people with disabilities, and what contributes to their sense of wellness. METHODS: = 10) on how wellness is understood and addressed at a Canadian children's rehabilitation hospital. Themes were identified through an inductive analysis of focus group transcripts and notes written by participants and research team members. RESULTS: Having a variety of relationships and social connections, meaningful activity opportunities, becoming as independent as possible, and having stable medical health contributed to wellness for young people with disabilities. CONCLUSIONS: Rehabilitation care can promote wellness by co-creating personalized care pathways across multiple wellness dimensions with young people with disabilities and their families, focusing on strengths rather than deficits, and improving access to a variety of activities and communities.IMPLICATIONS FOR REHABILITATIONRehabilitation professionals in children's rehabilitation have unique, ongoing opportunities to promote and support wellness with young people with disabilities and their families.Rehabilitation professionals can embed personalized, strengths-focused wellness pathways across multiple dimensions into the care of children with disabilities.Helping children and families address barriers to meaningful activities and promoting social connections can foster an overarching sense of wellness.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".