UNDERSTANDING ACTIVITY ENGAGEMENT EXPERIENCE AMONG RESIDENTS WITH DEMENTIA IN LONG-TERM CARE HOMES
Bibliographic record
Abstract
Abstract Recreational and meaningful activities in long-term care homes are crucial in promoting well-being among residents with dementia. While existing research primarily focuses on planned activities facilitated by staff, little attention has been given to self-directed activities initiated by residents themselves, reflecting their intrinsic motivation, lifestyle, and lifelong interests such as walking, gardening, meal preparation and other household activities. In this study, activity is defined as personally meaningful behavior, including both programmed and self-directed activities, and supported by social and/or physical environmental stimuli. Utilizing critical ethnography in a long-term care home in Canada, our research aims to: 1) gather descriptive data on the types, diversity and process of residents’ activity engagement, and 2) examine the care home setting in its natural context to uncover the social practices, built environmental features and underlying organizational discourses that influence activity engagement. Observations will focus on residents’ engagement in various activities and their interactions with staff and the physical environment. Interviews will be conducted with activity staff and non-activity staff (e.g., care aides, nurses) to explore their perspectives on activity engagement, person-centered approach, and their respective roles in promoting engagement. This study offers insights into residents’ experiences with both structured and self-directed activities, and the influence of the care home’s social and physical environments on engagement. The study addresses the knowledge gap in meaningful engagement through self-directed activities and the role of social and physical environments. Fieldwork will be completed in summer and preliminary findings based on interviews and initial observations will be presented.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".