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Record W4411930679 · doi:10.2196/69452

Dance as an Adjunct Therapy for Neurological Rehabilitation – Creative Enrichment for Recovery (DAN-CER): Program Design and Protocol for a Mixed Methods Pilot to Assess Feasibility and Acceptability

2025· article· en· W4411930679 on OpenAlexvenueno aff
Danielle Pretty, Michael Francis Norwood, Tamara Ownsworth, Kelly Dungey, Susan Jones, Zara Gomes, Kelly Clanchy, Elizabeth Kendall

Bibliographic record

VenueJMIR Research Protocols · 2025
Typearticle
Languageen
FieldPsychology
TopicDiversity and Impact of Dance
Canadian institutionsnot available
Fundersnot available
KeywordsAdjunctPreprintProtocol (science)RehabilitationMedicineDancePhysical therapyPsychologyMedical educationComputer scienceAlternative medicineWorld Wide WebVisual artsArt

Abstract

fetched live from OpenAlex

BACKGROUND: Dance is a novel recreational activity that may improve psychosocial outcomes in inpatient neurological rehabilitation; however, adapted dance programs in neurological rehabilitation settings are still emerging. OBJECTIVE: This paper describes the co-design process undertaken to develop an adapted dance program for use in neurological rehabilitation. It also presents a study protocol aimed at evaluating the program's feasibility, acceptability, and preliminary efficacy in a subacute hospital setting. METHODS: A 3-phase co-design approach was used to develop the Dance as an Adjunct Therapy for Neurological Rehabilitation - Creative Enrichment for Recovery (DAN-CER) program and protocol, including knowledge seeking, seeking expert input, and refining. Information sources included a literature review, stakeholder meetings, workshops, and focus groups with clinicians and patients. This study has approval from two ethics committees (HREC/2023/QGC/99631 and GU 2023/813). RESULTS: We undertook 4 workshops with Queensland Ballet, and 2 focus groups were undertaken with staff and neuroscience ward patients. The resultant program was mapped to the Template for Intervention Description and Replication (TIDieR) checklist. A mixed methods design was selected to evaluate the program. Primary outcomes are the feasibility and acceptability of the adapted dance program with data on accrual and attendance collected weekly. Semistructured interviews with patients and staff were conducted postintervention. The secondary outcome is the efficacy of DAN-CER for improving well-being and affect, with impact on fatigue monitored. Adapted dance classes and data collection assessments began in late October 2024, and data collection was completed in late February 2025. At the time of manuscript submission, 14 participants had been recruited. Interviews have been transcribed, and preliminary coding is underway; findings are expected to be submitted for publication in December 2025. CONCLUSIONS: The rigor of the multiphase co-design process enabled the development of an adapted dance intervention capable of accommodating the physical, cognitive, and communication challenges of neurorehabilitation ward patients. The proposed mixed methods protocol will enable multidimensional evaluation of the adapted dance program. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/69452.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.049
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.049
Threshold uncertainty score0.262

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0490.031
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0030.002
Science and technology studies0.0050.003
Scholarly communication0.0030.002
Open science0.0040.004
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0300.007

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 head0.514
GPT teacher head0.663
Teacher spread0.149 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreProtocol

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

Citations0
Published2025
Admission routes1
Has abstractyes

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