To Plan or Not to Plan? Experiences and Challenges of Older Swiss Adults Facing End-of-Life Decisions
Bibliographic record
Abstract
End-of-life (EoL) planning and the drafting of advance care directives (ACD) are challenging for older adults. As part of a mixed study, the content of 18 semi-structured interviews with Swiss community-dwelling older adults was analyzed to investigate contextual and interactional aspects that might influence their choice to complete ACD. Results show that EoL planning vary greatly. Three types of planners were highlighted: the solo planners, the collaborative planners, and the delegators. Each represents a specific way of conceiving autonomy, the usefulness of ACD and of involving third parties in the decision-making process. Whereas for solo planners, ACD is a personal, rational affair, for collaborative planners and delegators, reflection and decisions on EoL issues are interactional and iterative processes. The results suggest that health and social care professionals would benefit from taking into consideration the various types of planning, in order to provide the best support to older adults for ACD completion.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| 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".