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Record W2166722178 · doi:10.1017/s071498081400018x

The Effect of a Community-Engaged Arts Program on Older Adults’ Well-being

2014· article· fr· W2166722178 on OpenAlexaff
Alison Phinney, Elaine Moody, Jeff Small

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2014
Typearticle
Languagefr
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsThe artsSense of communityPsychologyCoping (psychology)Presentation (obstetrics)Social psychologyGerontologyMedical educationClinical psychologyMedicineVisual arts

Abstract

fetched live from OpenAlex

RÉSUMÉ Cette étude utilisant des méthodes mixtes a évalué l'effet d'un programme d'arts communautaires engagés sur le bien-être physique, émotionnel et social des personnes âgées. Ateliers hebdomadaires ont été offerts pendant une période de trois ans dans des centres communautaires où les artistes ont collaboré avec quatre groupes de personnes âgées pour produire une œuvre d'art collective ou la performance d'une présentation publique. Les participants ont rempli questionnaires avant et après et des entretiens de groupe ont été menées à la fin du programme. Des analyses t-test appariés ont indiqué que les personnes âgées ont connu une amélioration perçue dans leur état de santé générale, l’expérience de la douleur, et le sens de la communauté. Une analyse descriptive et intérpretative des entretiens de groupe a révélé six thèmes qui ont éclairé la compréhension: (1) fournissant de la structure et de la discipline; (2) facilitant l’adaptation; (3) nécessitant un travail acharné et des efforts; (4) faisant ressortir son côté artistique; (5) la promotion de la participation sociale; et (6) apportant une contribution. Ces résultats concordent avec les recherches antérieures et contribuent à une meilleure compréhension de la façon dont les arts communautaires engagés peuvent favoriser le bien-être des personnes âgées.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.012
GPT teacher head0.233
Teacher spread0.221 · 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

Citations39
Published2014
Admission routes1
Has abstractyes

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