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Record W4402490178 · doi:10.1080/01942638.2024.2400623

Co-Construction of a Dance Class Adapted for Adolescents with Cerebral Palsy

2024· article· en· W4402490178 on OpenAlexaff
Frédérique Poncet, Claire Cherriere, Lucie Beaudry, Sylvie Fortin, Martin Lemay

Bibliographic record

VenuePhysical & Occupational Therapy In Pediatrics · 2024
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsUniversité du Québec à MontréalCentre Hospitalier Universitaire Sainte-JustineCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalCentre de réadaptation Lethbridge-Layton-MackayCentre for Interdisciplinary Research in Rehabilitation
Fundersnot available
KeywordsCerebral palsyDanceConstruct (python library)Class (philosophy)Physical medicine and rehabilitationPsychologyPhysical therapyMedicineComputer scienceArtArtificial intelligenceVisual arts

Abstract

fetched live from OpenAlex

AIM: To co-construct a dance class adapted for adolescents with cerebral palsy (CP). METHOD: A three phase co-construction process with study collaborators was used to (1) define the objectives and the obstacles and opportunities related to offering a dance class in the community through three focus groups with adolescents, their parents and study partners; (2) co-create the dance class based on the results of step 1, the expertise of the research team and the logic model of the dance class; and (3) test the dance class to evaluate its effects in relation to the defined objectives. RESULTS: Three objectives were identified: to have fun, promote movement, and social interaction. A weekly dance class (60 min./10 wk) was continuously tested on the adolescents and adapted by the dance facilitators. CONCLUSION: To improve practices and support the implementation of dance classes for young people with CP, eight recommendations are proposed relating to the creation of adapted classes and the evaluation of their desired effects.

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.

How this classification was reachedexpand

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)0.000
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 score0.031
Threshold uncertainty score0.442

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.028
GPT teacher head0.327
Teacher spread0.299 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2024
Admission routes1
Has abstractyes

Explore more

Same venuePhysical & Occupational Therapy In PediatricsSame topicCerebral Palsy and Movement DisordersFrench-language works237,207