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Record W3115673715 · doi:10.1093/geroni/igaa057.3034

Raising Our Voices: The Impact of a Dementia Choir on Well-Being and Quality of Life

2020· article· en· W3115673715 on OpenAlexaff
Debra Sheets, Stuart MacDonald, André Smıth

Bibliographic record

VenueInnovation in Aging · 2020
Typearticle
Languageen
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsChoirDementiaPsychologySocial isolationFriendshipQuality of life (healthcare)Stigma (botany)GerontologyMedical educationDevelopmental psychologyMedicineSocial psychologyPedagogyPsychiatryPsychotherapist

Abstract

fetched live from OpenAlex

Abstract Stigma represents one of the biggest barriers to living well with dementia following diagnosis. Social isolation is common as roles, friendships and opportunities to participate in the broader community disappear. An intergenerational dementia choir is a joyful activity that offers opportunities for learning, friendships and purposeful engagement towards common goals (e.g., regular social engagement, public concerts at season’s end). Data collection involved surveys and interviews with 32 dyads comprised of persons with dementia (PwD) and caregivers, as well as focus groups with 29 high school students. Results illustrate the development of a choir community across weeks of participation with far reaching benefits. Both caregivers and PwD experienced reductions in health risks and improvements in quality of life. Students’ understanding of dementia became more positive over time and new friendships developed. The discussion focuses on the need for meaningful and inclusive community activities for PwD and their caregivers.

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)0.003
metaresearch head score (Gemma)0.006
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 score0.004
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0030.002
Scholarly communication0.0030.001
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.143
GPT teacher head0.443
Teacher spread0.301 · 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
Published2020
Admission routes1
Has abstractyes

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