Namaste care delivered by caregivers of community‐dwelling older adults with moderate to advanced dementia: A mixed methods study protocol
Bibliographic record
Abstract
AIM: The aim of this study is to adapt and evaluate the feasibility, acceptability, and preliminary effectiveness of a multisensory, psychosocial intervention called Namaste Care delivered by family and friend caregivers of community-dwelling older adults with moderate to advanced dementia. DESIGN: A multiphase mixed methods design combining quantitative and qualitative methods will be used. METHODS: This study is composed of two phases. Phase 1 is guided by a qualitative description approach. Small group workshop sessions with 8-10 caregivers of community-dwelling older adults with moderate to advanced dementia will be conducted to adapt Namaste Care. In Phase 2, 10-20 caregivers will receive training and implement the adapted Namaste Care approach at home. A one group, before-after design will be used to evaluate feasibility, acceptability and preliminary effectiveness of the approach over 3 months. Feasibility will be assessed using quantitative measures and acceptability will be explored using qualitative methods. Outcomes to evaluate preliminary effectiveness include quality of life (QoL), positive perceptions of caregiving, self-efficacy, and caregiver burden. DISCUSSION: There are currently few skill-building interventions that can be delivered by caregivers of people with moderate to advanced dementia at home. Caregivers should be involved in developing programs to enhance program relevance. This research will be the first to explore the feasibility of implementing the Namaste Care approach at home by caregivers. IMPACT: Study results will provide important information about the feasibility and preliminary effects of an adapted form of Namaste Care. This program has the potential to improve the QoL of caregivers and may prevent hospitalization or long-term care placement of older persons with moderate to advanced dementia. The revised Namaste Care program supports building the skills of caregivers so that their needs and the needs of older persons with dementia living at home are being addressed.
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 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 | 0.046 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.026 | 0.005 |
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".