MétaCan
Menu
← Back to cohort
Record W2987938829 · doi:10.1093/geroni/igz038.2784

IMPACT OF ADAPTED DANCE ON MOOD AND PHYSICAL FUNCTION AMONG ALZHEIMER’S DISEASE ASSISTED LIVING RESIDENTS

2019· article· en· W2987938829 on OpenAlexaboutno aff
Crystal G. Bennett

Bibliographic record

VenueInnovation in Aging · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsDanceDementiaMoodCaregiver burdenPhysical therapyIntervention (counseling)MedicineGerontologyPhysical medicine and rehabilitationDiseasePsychologyPsychiatry

Abstract

fetched live from OpenAlex

Abstract Neuropsychiatric secondary symptoms and altered physical function are prevalent among persons with Alzheimer’s Disease and related dementia disorders (ADRD) which increase healthcare costs and caregiver burden. Adapted dance is a promising intervention that may improve these symptoms and physical function. The purpose of this study is to test whether 12 weeks of adapted dance (60 min 2x/week) improves agitation, physical function, and reduces caregiver burden. An experimental crossover design will be used. ADRD residents with a Montreal Cognitive Assessment score between 6-26, Timed up and go of <20 seconds, Cohen-Mansfield Agitation Inventory Score (CMAI) of >15, and do not use oxygen or assistive device will be eligible to participate. Outcomes will be assessed at baseline and every 4 weeks during each study arm for 24 weeks. Measures include CMAI and the Neuropsychiatric Inventory-Clinician Scale for agitation; Short Physical Performance Battery for physical function; and Zarit Burden Interview for caregiver burden.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0010.000

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 head0.050
GPT teacher head0.317
Teacher spread0.267 · 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 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

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueInnovation in Aging→Same topicArt Therapy and Mental Health→French-language works237,207→