Is there evidence of benefits associated with dancing in children and adults with cerebral palsy? A scoping review
Bibliographic record
Abstract
Purpose: Cerebral palsy is a neurological disorder not only affecting motor functions but also cognitive and psychosocial dimension. Multispecialty therapies are needed to address these dimensions. Dance practice provides multidimensional benefits for people with various neurological disorders and may present a real potential for people with cerebral palsy. A scoping review is conducted to evaluate the impact of dance in children and adults with cerebral palsy, based on the Human Development Model–Disability Creation Process 2 and its three key concepts: personal factors, environmental factors and life habits.Materials and methods: Studies were selected based on a systematic search of published literature in the following databases PubMed, Medline, EBM Reviews, EMBASE and CINAHL. Studies addressing any concepts on the impact of dance training on motor, cognitive and psychosocial dimensions in people with cerebral palsy were included.Results: Seven studies representing 45 children and 12 adults with cerebral palsy were selected. They had heterogeneous populations, protocols and outcomes measures, but overall covered the three main concepts of the model. Dance may have both motor and social benefits although the evidence remains weak.Conclusions: Dance appears to be a promising activity for people with cerebral palsy. Recommendations are proposed for future studies.Implications for rehabilitationCerebral palsy affects motor and cognitive functions and has social repercussions.Dance can be a promising activity for people with a cerebral palsy.Dance may have both motor and social benefits although the evidence remains weak.
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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 | 0.006 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".