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Record W4387009262 · doi:10.32920/24194751

Understanding Group Singing in Older Adults with Aphasia from a Biopsychosocial Perspective: A Pilot Study

2023· preprint· en· W4387009262 on OpenAlexaff
Alexander Pachete

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsToronto Metropolitan UniversityYork University
Fundersnot available
KeywordsBiopsychosocial modelLonelinessSocial connectednessPsychosocialSocial isolationPsychologySingingPerceptionClinical psychologyDevelopmental psychologyAphasiaSocial supportSocial psychologyPsychotherapistPsychiatry

Abstract

fetched live from OpenAlex

Social isolation and loneliness are barriers to social wellbeing for many older adults. These barriers may arise due to changes in lifestyle, social groups, and self-perception. Prior research has shown that group singing can improve social connectedness, but there has been limited consideration of older adults with communication disorders. The present pilot study investigated whether 13 weeks of group singing could improve the social connectedness and communicative function of 10 individuals with aphasia. Participants were assessed with regard to psychosocial wellbeing, self-perception of their disorder, and speech production. In addition, their cortisol levels and pain thresholds were analysed to investigate the potential sociobiological basis of psychosocial effects. Results showed positive increases in psychological wellbeing but no changes in social wellbeing. Physiological findings were inconclusive. Social wellbeing showed positive trends which may indicate that more choir sessions are needed to foster social connection.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · 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
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.195
GPT teacher head0.396
Teacher spread0.201 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

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