Feasibility, acceptability, and preliminary effectiveness of the adapted Namaste Care program delivered by caregivers of community-dwelling older persons with moderate to advanced dementia: a mixed methods feasibility study
Bibliographic record
Abstract
BACKGROUND: Caregivers have considerable responsibilities in supporting persons in advanced stages of dementia, however they receive little education. Namaste Care is a multisensory program originally designed to be delivered by healthcare providers in long-term care homes for persons with advanced dementia. The program has not yet been adapted and evaluated for use by caregivers of persons with moderate to advanced dementia living at home. The purpose of this feasibility study is to determine the feasibility, acceptability and preliminary effectiveness of the adapted Namaste Care program for use by caregivers of community-dwelling older persons with moderate to advanced dementia. METHODS: This feasibility study, with a one-group before-after design and interviews, was part of a larger study using a multiphase mixed methods design. A total of 12 caregivers delivered the program over three months. Caregivers completed questionnaires on caregiver quality of life, perceptions of caregiving, self-efficacy, and burden at baseline and 3-month follow-up. Caregivers participated in interviews at the 3-month follow-up to explore acceptability and perceived benefit. Descriptive statistics and paired t-tests were used to analyze quantitative data. A secondary analysis used multiple imputation to explore the impact of missing data. Experiential thematic analysis was used in analyzing qualitative data. RESULTS: The adapted Namaste Care program was judged to be feasible, given that all caregivers used it at least twice a week over the 3-month period. The retention rate of caregivers was 83% (10 of 12). Caregivers perceived that the program was practical, enhanced the wellbeing of persons with dementia, and brought them closer in their relationships with persons with dementia. There were no statistically significant changes for quality of life, perceptions of caregiving, self-efficacy, or burden outcomes. Multiple imputation results revealed promising findings for an improvement in caregiver wellbeing related to quality of life. CONCLUSIONS: The adapted Namaste Care program for use by caregivers of community-dwelling older persons with moderate to advanced dementia was feasible and acceptable. The program has the potential to enhance the quality of life and other outcomes of caregivers, however there is a need to conduct a larger trial that is adequately powered to detect these effects.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".