“I Want to Do Something” – Exploring What Makes Activities Meaningful for Community-Dwelling People Living With Dementia: A Focused Ethnographic Study
Bibliographic record
Abstract
Supporting ageing in place, quality of life, and activity engagement are public health priorities for people with dementia. The importance of maintaining opportunities for meaningful activities has been widely acknowledged for those with dementia in long-term care, but little is known about what makes activities meaningful for, and how they are experienced by, people with different types of dementia in their own homes. This study used focussed ethnographic methods to explore the motivations and meanings of everyday activity engagement within the homes of 10 people with memory-led Alzheimer's disease and 10 people with posterior cortical atrophy. While participants' interactions with their everyday environments were challenged by their diagnoses, they were all finding ways to continue meaning-making via various activities. The main findings are encapsulated in three themes: (1) The fun and the function of activities; (2) Reciprocities of care, and (3) The constitution and continuity of (a changing) self. Ongoing engagement with both fun and functional activities offered participants living with different dementias opportunities to connect with others, to offer care and support (as well as receive it), and to maintain a sense of self and identity. Implications are discussed regarding the development and delivery of tailored interventions and support to enable continued engagement in meaningful activities for people with different types of dementia living in the community.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.010 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".