Validation of the effect of soundscape on the well‐being and behaviour of people with dementia: a randomized clinical trial
Bibliographic record
Abstract
Abstract Background Using the Soundscape approach to design an environment that improves people’s quality of life is crucial. This approach is more challenging for people with dementia. This project uses a personalized algorithm to play sounds at prescheduled moments throughout the night in patients’ rooms in a research hospital specializing in dementia care to evaluate the reduction in resistance to care and agitation. Method A single‐blind repeated measure randomized clinical trial is designed to estimate the overall or average effects of the customized soundscape on people with dementia. Twenty‐six participants were randomized into two groups of AcustiCare (n = 13) and Treatment as usual (n = 13) for six weeks for each study group. Result The primary outcomes of this study were the NPI‐total score and the PAS‐resisting care subscale. In a linear mixed effects model, there were improvements in the NPI‐total scores over time in both groups (‐5.9 +/‐1.3; ρ<0.001). With the PAS‐resisting care subscale, a significant group x time difference, with a greater reduction in PAS‐resisting care score in the AcustiCare group (‐0.81 +/‐ 0.4; ρ = 0.042). Conclusion People with dementia can benefit from augmented sonic environments since auditory stimulation can reduce agitation and anxiety and provide safety and familiarity. The outcome of a small sample size showed improvement in resistance to care and reduction in agitation; These results can also be used to calculate effect size and determine the sample size for a future RCT.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".