Elder‐Clowning in Long‐Term Dementia Care: Results of a Pilot Study
Bibliographic record
Abstract
OBJECTIVES: To assess the effects of elder-clowning on moderate to severe behavioral and psychological symptoms of dementia (BPSD) in nursing home residents with dementia, primarily of the Alzheimer's type. DESIGN: Before-and-after study. SETTING: Nursing home. PARTICIPANTS: Nursing home residents with moderate to severe BPSD, as defined according to a Neuropsychiatric Inventory-Nursing Home version (NPI-NH) score of 10 or greater (N = 23), and their care aides. INTERVENTION: A pair of elder-clowns visited all residents twice weekly (~10 minutes per visit) for 12 weeks. They used improvisation, humor, empathy, and expressive modalities such as song, musical instruments, and dance to individualize resident engagement. MEASUREMENTS: Primary outcomes were BPSD measured using the the NPI-NH, quality of life measured using Dementia Care Mapping (DCM), and nursing burden of care measured using the Modified Nursing Care Assessment Scale (M-NCAS). Secondary outcomes were occupational disruptiveness measured using the NPI-NH, agitation measured using the Cohen Mansfield Agitation Inventory (CMAI), and psychiatric medication use. RESULTS: Over 12 weeks, NPI-NH scores declined significantly (t22 = -2.68, P = .01), and DCM quality-of-life scores improved significantly (F1,50 = 23.09, P < .001). CMAI agitation scores decreased nominally, but the difference was not statistically significant (t22 = -1.86, P = .07). Occupational disruptiveness score significantly improved (t22 = -2.58, P = .02), but there was no appreciable change in M-NCAS scores of staff burden of care. CONCLUSION: Results suggest that elder-clowning reduced moderate to severe BPSD of nursing home residents with dementia, primarily of the Alzheimer's type. Elder-clowning is a promising intervention that may improve Alzheimer's disease care for nursing home residents.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".