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Record W2766002835 · doi:10.1177/2333721417734672

Pilot of a Tailored Dance Intervention to Support Function in People With Cognitive Impairment Residing in Long-Term Care: A Brief Report

2017· article· en· W2766002835 on OpenAlexafffundabout
Hannah M. O’Rourke, Souraya Sidani, Charlene H. Chu, Mary Fox, Katherine S. McGilton, Jhonna Collins

Bibliographic record

VenueGerontology and Geriatric Medicine · 2017
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsToronto Rehabilitation InstituteYork UniversityUniversity of TorontoToronto Metropolitan University
FundersInstitute of Aging
KeywordsDanceIntervention (counseling)Term (time)GerontologyCognitive impairmentCognitionPsychologyLong-term careMedicinePhysical medicine and rehabilitationPsychiatryArtVisual arts

Abstract

fetched live from OpenAlex

Older adults who live in long-term care settings are at risk for functional decline, which may be mitigated by regular exercise. Using a single-group repeated measures design, this pilot study explored the feasibility, acceptability, and preliminary effects of a Waltz-based dance intervention delivered to 13 Canadian, English-speaking, long-term care residents with mild to moderate cognitive impairment. The findings supported intervention feasibility, based on a high completion rate (93%), level of attendance ( M = 7.15 of 10 sessions) and level of engagement during dance sessions ( M = 1.75 to 1.97 out of 2.00). On average, residents perceived dance sessions positively, and staff and family participants ( N = 26) rated them as somewhat acceptable overall ( M = 2.37, 0 to 4 scale). Additional research is needed to assess intervention efficacy in a larger sample.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.013
Threshold uncertainty score0.466

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.022
GPT teacher head0.325
Teacher spread0.303 · 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

Citations11
Published2017
Admission routes3
Has abstractyes

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