Strategies to support engagement and continuity of activity during mealtimes for families living with dementia; a qualitative study
Bibliographic record
Abstract
BACKGROUND: Mealtimes are an essential part of living and quality of life for everyone, including persons living with dementia. A longitudinal qualitative study provided understanding of the meaning of mealtimes for persons with dementia and their family care partners. Strategies were specifically described by families to support meaningful mealtimes. The purpose of this manuscript is to describe the strategies devised and used by these families living with dementia. METHODS: A longitudinal qualitative study was undertaken to explore the meaning and experience of mealtimes for families living with dementia over a three-year period. 27 families [older person with dementia and at least one family care partner] were originally recruited from the community of South-Western Ontario. Individual and dyad interviews were conducted each year. Digitally recorded transcripts were analyzed using grounded theory methodology. Strategies were identified and categorized. RESULTS: Strategies to support quality mealtimes were devised by families as they adapted to their evolving lives. General strategies such as living in the moment, as well as strategies specific to maintaining social engagement and continuity of mealtime activities were reported. CONCLUSIONS: In addition to nutritional benefit, family mealtimes provide important opportunities for persons with dementia and their family care partners to socially engage and continue meaningful roles. Strategies identified by participants provide a basis for further education and support to families living with dementia.
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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 | 0.014 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.008 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".