An Animal-Assisted Physiotherapy Intervention with a Rehabilitation Dog for Walking and Balance Training: A Case Series of Children Living with Cerebral Palsy
Bibliographic record
Abstract
PurposePhysiotherapy (PT) is an essential part of care for improving function and increasing community participation in children with cerebral palsy (CP). Combining animal-assisted intervention (AAI) with PT (AA-PT) offers a unique approach, potentially boosting motivation and participation in ambulatory children with CP. This case series piloted AA-PT integrating a rehabilitation dog for children with CP, to enhance walking and balance training.MethodsFour ambulatory children with CP (7-16 y.o.a, GMFCS I-II, 3 girls, 1 boy) participated in an 8-week individualized AA-PT intervention. Assessments at baseline (0 weeks), pre-intervention (8 weeks), post-intervention (16 weeks), and follow-up (24 weeks) included Kids Mini BESTest, timed up and go (TUG), dual task cost (DTC), and spatiotemporal parameters. The AA-PT included weekly 60-min sessions integrating a rehabilitation dog in walking and balance training. Visual analog scales (VAS) assessed perceived comfort, safety, enjoyment, and confidence while walking with and without the rehabilitation dog.ResultsIndividual-responder analysis showed improvements in Kids Mini BESTest scores, reduced DTC, and increased walking speed for all. Children reported higher enjoyment, confidence, safety, and comfort when walking with the rehabilitation dog.ConclusionAA-PT integrating a rehabilitation dog may enhance balance, dual-task cost, walking speed, and confidence in ambulatory children with CP.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".