Exploring Impacts of Integrating a Rehabilitation Dog into Physiotherapy from the Perspectives of Children with Cerebral Palsy and Their Caregivers
Bibliographic record
Abstract
BackgroundRehabilitation for children with cerebral palsy (CP) often includes physiotherapy to enhance community participation and quality of life. Animal-assisted services (AAS) are a novel approach in physiotherapy to increase motivation, enjoyment and wellbeing. Our team conducted a study integrating a rehabilitation dog (Loki) into animal-assisted physiotherapy (AA-PT) for children with CP. This study presents the experiences and perspectives of children with CP who worked with Loki.MethodsInterpretive Description approach with reflective thematic analysis was used. Semi-structured interviews were completed at two timepoints: T1) single timepoint walking with Loki; T2) after an 8-week AA-PT intervention with Loki (subset of participants). ResultsAmbulatory children with CP aged 7-16 years (n = 11 (T1); n = 4 (T2)) and their caregiver (n = 11 (T1); n = 4 (T2)) participated. Three themes describing the perceived impact of working with Loki were described: 1) Connection, Relationship and Bonding; 2) Being upheld: physical support and emotional safety; 3) Empowerment Through Participation and Confidence.ConclusionChildren with CP and their caregivers reported immense enjoyment and value in having Loki present as part of the physiotherapy intervention. Centered around an immediate bond formed with Loki, the emotional and physical support children experienced improved willingness to participate in the AA-PT and in community following interactions with Loki.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".