What will happen to my mom? A grounded theory on nurses’ support of relatives’ end-of-life decision-making process for residents living with dementia in long-term care homes
Bibliographic record
Abstract
BACKGROUND: Relatives of an older person living in a long-term care home with advanced-stage dementia must often make important and difficult decisions, including ones that impact the resident's end-of-life. Healthcare professionals must support them in this decision-making process. The aim of this study was to propose a theory on nurses' support of relatives who make end-of-life decisions for a resident living with dementia in a long-term care home. METHOD: A constructivist grounded theory approach was used, with a theoretical sample of nine nurses and 10 relatives whom we met for face-to-face interviews. Three documents on end-of-life care, which were available in the study setting, were also included. The analysis was carried out using the method proposed by Charmaz. FINDINGS: The findings highlight the importance of building a strong and trusting relationship between nurses and relatives. Furthermore, exploring the refusal of palliative or end-of-life care, supporting relatives' need to witness firsthand the condition of the person living with dementia, and education at a "good" time are useful interventions that nurses can make to support relatives' decision-making. CONCLUSION: Better support of relatives in end-of-life decision-making improves the well-being of relatives and older people living with dementia alike.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".