Piloting a choir program for nursing home residents with advanced dementia
Bibliographic record
Abstract
There is growing evidence that active music making can improve both cognitive and psychosocial functioning in people with mild to moderate dementia but limited research on interventions, specifically choral singing, with advanced dementia. The purpose of this study was to develop and implement a choir for individuals with advanced dementia living in a nursing home, and to assess possible benefits. We explored relationships between choir participation and cognitive functioning, loneliness, depression, and quality of life in residents with advanced dementia in a nursing home facility and participants’ individual perspectives of their experience with choir participation. Twelve residents participated in weekly choir rehearsals which culminated in a concert performance at the end of eight months. Baseline and post-intervention assessments of the Montreal Cognitive Assessment, UCLA Loneliness Scale, Geriatric Depression Scale, and Dementia Quality of Life Scale were administered. Choir members also participated in post-concert interviews. Thematic analyses of these interviews were conducted. Results showed overall decreases in loneliness, improvement in quality of life, and slowing of cognitive decline. Results did not show overall decreases in depression scores. Thematic analysis of interviews revealed six themes: Friendship, Enjoyment of Music in General, Enjoyment of Choir, Memories, Family, Religion/Spirituality, and Beauty.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".