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Record W4392091396 · doi:10.1017/s0714980824000084

Bringing Dance to Older Adults: Program Experts’ Perspectives on the Role of Community Dance Classes to Support Older Adults

2024· article· en· W4392091396 on OpenAlexafffund
Vanessa Paglione, Lindsay Morrison, Meghan H. McDonough, Andrea Downie, Sarah Kenny

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2024
Typearticle
Languageen
FieldPsychology
TopicDiversity and Impact of Dance
Canadian institutionsUniversity of Calgary
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsDanceInclusion (mineral)Dance educationPsychologyLiteracySociologyGerontologyPublic relationsPedagogySocial psychologyVisual artsMedicinePolitical scienceArt

Abstract

fetched live from OpenAlex

BACKGROUND: Dancing offers several health and wellness benefits for older adults: it may promote physical literacy (PL) and positively influence the aging process. Yet, limited research considers the perspectives of those with experience working with older adults and in community dance programming. OBJECTIVE: The purpose of this study was to understand program experts' perspectives on how older adult community dance can promote PL and contribute to age-friendly cities and community initiatives. METHODS AND FINDINGS: Four themes were identified from semi-structured interviews with five program experts: (1) expert instructors tailor classes to participants' needs and interests; (2) the heart of what draws us to dancing: authentic experience and social connection; (3) elitist, ableist, and gendered assumptions of dance prevent social inclusion of older adults in dancing spaces; and (4) collaboration across sectors is needed to offer accessible, sustainable, and valued dance programming. DISCUSSION: Recommendations for developing and implementing older adult community dance programming are described.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.433
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.013
GPT teacher head0.263
Teacher spread0.250 · 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.

Study designQualitative
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

Citations5
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal on Aging / La Revue canadienne du vieillissementSame topicDiversity and Impact of DanceFrench-language works237,207