“Whatever happens, happens” challenges of end-of-life communication from the perspective of older adults and family caregivers: a Qualitative study
Bibliographic record
Abstract
BACKGROUND: Effective communication is integral to the delivery of goal-concordant care for older adults and their family caregivers, and yet, it is uncommon in people with serious illness. This study explores the challenges of integrating end-of-life communication into heart failure management from the perspectives of older adults and family caregivers. METHODS: In a qualitative study of older adults with heart failure and their family caregivers, fourteen semi-structured interviews were conducted with 19 participants in Ontario, Canada. The interviews were transcribed verbatim and thematic analysis was applied to analyze the data. RESULTS: Four themes were identified in the context of participants' understanding of illness: 1) trivializing illness-related challenges, 2) positivity in late life, 3) discomfort in having end-of-life conversations, and 4) reluctant to engage despite need. These challenges often intertwine with one another. Most participants had not engaged in end-of-life discussions with their clinicians or family members. CONCLUSION: The findings provide insights that can inform approaches to integrate end-of-life communication for older adults with serious illness and caregivers. The identified challenges highlight a need for end-of-life communication to occur earlier in illness to be able to support individuals throughout the period of decline. In addition, end-of-life communication should be introduced iteratively for those who may not be ready to engage. Alternative approaches to communication are needed to elicit the challenges that patients and caregivers experience throughout the progression of illness to improve care for people nearing the end of life.
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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 | 0.018 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.007 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".