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Record W4321461115 · doi:10.22605/rrh8142

Preliminary findings from the early phases of the Music and Movement for Health study: the feasibility of an arts-based health programme for older adults

2023· article· en· W4321461115 on OpenAlexaff
Amanda M. Clifford, Steven Byrne, Orfhlaith Ní Bhriain, Pui Sze Cheung, Ali Sheikhi, Catherine Woods, Desmond O’Neill, Rosemary Joan Gowran, Liam Glynn, Hilary Moss, Quinette Louw, Lehana Thebane, Susan Coote, Jon Salsberg

Bibliographic record

VenueRural and Remote Health · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsMcMaster University
Fundersnot available
KeywordsThe artsMovement (music)Music therapyPsychologyGerontologyMedicineVisual artsPsychiatryArt

Abstract

fetched live from OpenAlex

Introduction (including aim): There is a lack of community-based programmes for older adults in Ireland. Such activities are vital to enable older people to (re)connect after COVID-19 measures, which had a detrimental effect on physical function, mental health and socialisation. The aims of the preliminary phases of the Music and Movement for Health study were to refine stakeholder informed eligibility criteria, recruitment pathways and obtain preliminary measures for feasibility of the study design and programme, which incorporates research evidence, practice expertise and participant involvement. METHODS: Two Transparent Expert Consultations (TECs) (EHSREC No: 2021_09_12_EHS), and Patient and Public Involvement (PPI) meetings were conducted to refine eligibility criteria and recruitment pathways. Participants from three geographical regions in the mid-west of Ireland will be recruited and randomised by cluster to participate in either a 12-week Music and Movement for Health programme or control. We will assess the feasibility and success of these recruitment strategies by reporting recruitment rates, retention rates and participation in the programme. RESULTS: Both the TECs and PPIs provided stakeholder-informed specification on inclusion/ exclusion criteria and recruitment pathways. This feedback was vital in strengthening our community-based approach as well as effecting change at the local level. The success of these strategies from phase 1 (March-June) are pending. DISCUSSION: Through engaging with relevant stakeholders, this research aims to strengthen community systems by embedding feasible, enjoyable, sustainable and cost-effective programmes for older adults to support community connection and enhance health and wellbeing. This will, in turn, reduce demands on the healthcare system.Note: We would like to thank and acknowledge those who participated in the PPIs for their time and invaluable feedback.

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)0.097
metaresearch head score (Gemma)0.139
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 score0.097
Threshold uncertainty score0.515

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0970.139
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0040.003
Open science0.0020.005
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0090.002

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 head0.123
GPT teacher head0.369
Teacher spread0.246 · 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
Published2023
Admission routes1
Has abstractyes

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