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Record W4408652550 · doi:10.1080/17533015.2025.2481275

Physiotherapists use dance in their clinical practice in creative and diverse ways

2025· article· en· W4408652550 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueArts & Health · 2025
Typearticle
Languageen
FieldPsychology
TopicDiversity and Impact of Dance
Canadian institutionsUniversity Health NetworkToronto Rehabilitation InstituteUniversity of Toronto
Fundersnot available
KeywordsDanceClinical PracticePsychologyEngineering ethicsMedical educationMedicineVisual artsEngineeringNursingArt

Abstract

fetched live from OpenAlex

Purpose To investigate how physiotherapists use dance in clinical practice.Methods This was a cross-sectional study of Canadian physiotherapists with a web-based questionnaire distributed via social media and professional and healthcare organizations. Responses were analyzed with descriptive statistics and descriptive content analysis.Results Of the 81 respondents included in the analysis, 36 (44%) had used dance in practice, while 45 (56%) had not. Respondents were more likely to have used dance in practice if they had formal dance experience (X2 (1, n = 81) = 3.73, p = .044). The rationale for implementing dance included improving physical, psychosocial, and cognitive outcomes. Common barriers were clinician inexperience and insufficient resources, while a common concern about using dance was that they may not be taken seriously.Conclusion Canadian physiotherapists used dance clinically in more diverse ways than reported in the scientific literature. Future work should evaluate these specific dance interventions and inform the development of clinical practice guidelines.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.317
Threshold uncertainty score0.774

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.110
GPT teacher head0.455
Teacher spread0.345 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it