Exploring the factors influencing meaningful engagement of persons living with advanced dementia through the Namaste Care Program: a qualitative descriptive study
Bibliographic record
Abstract
Background: Meaningful engagement has been described as active participation based on a person's interests, preferences, personhood, or perceived value. It has many benefits for persons living with dementia in long-term care (LTC) homes, including improvement in physical and cognitive function, and mental health. People with advanced dementia continue to need and benefit from inclusion and social contact in LTC, yet there is not a well-developed understanding of how to support this. A tailored intervention called Namaste Care has been shown to be an effective approach to meaningfully engage residents in LTC, decrease behavioral symptoms, and improve their comfort and quality of life. There is a need to consider how best to deliver this intervention. Objective: The aim of this study was to describe environmental, social, and sensory factors influencing meaningful engagement of persons with advanced dementia during Namaste Care implementation in LTC. Methods: In this qualitative descriptive study, focus groups and interviews were conducted with families, volunteers, staff, and managers at two LTC homes. Directed content analysis was conducted. The Comprehensive Process Model of Engagement was used as a coding framework. Results: With respect to environmental attributes, participants emphasized that a designated quiet space and a small group format were helpful for engagement. In terms of social attributes, participants emphasized Namaste Care staff capacity to deliver individualized care. Regarding sensorial factors, familiarity with the activities delivered in the program was emphasized. Conclusion: Findings reveal the need to offer small group programs that include adapted recreational and stimulating activities, such as Namaste Care, for residents at the end of life in LTC. Such programs facilitate meaningful engagement for persons with dementia as they focus on individual preferences, comfort, and inclusion while recognizing changing needs and abilities of residents.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".