Caring for older people living alone with dementia: Healthcare professionals’ experiences
Bibliographic record
Abstract
Older adults living alone with dementia are at greater risk of placement in long-term care homes compared with those living with others. Healthcare professionals have vital roles in supporting them to continue living in the community. Yet, little is known about how healthcare professionals fulfill these roles and what their experiences are like. The study purpose was to describe health care professionals' experiences of caring for older people with dementia living alone. Using a qualitative descriptive approach and qualitative content analysis method, 15 healthcare professionals were interviewed in Ontario, Canada. The overall theme of the findings, doing the best we can for them, involved discussing sensitive care issues with what professionals viewed as gentle realism. Walking the tightrope expressed tensions in meeting professional responsibilities. Constraints (my hands are tied) and boundaries (it's not my job, it's not my decision) described perceived limitations on professional roles. Effects of the emotional struggle involved in working with these older people were lessened by believing I did the right thing. The findings have implications for what we could do better for older people with dementia living alone, through integration of person-centered/relationship-centered principles in education programs, community agency policies, a national dementia care strategy, and culture change in community care.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| 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".