Advance Directives in the Context of Uncertain Prognosis for Residents of Nursing Homes
Bibliographic record
Abstract
This report documents the findings of a mixed-methods study focused on the advanced directives of 182 residents of three LTC facilities in southern Ontario, Canada. Although almost all had a completed advance directive within 3 months of death, most did not have a palliative designation or directive until a few days before they died. Each facility’s written Progress Notes revealed staff members usually sought additional confirmation of care preferences from residents’ substitute decision-makers within a few days of the death. It was thus common for advance directives to change from a more interventionist approach to the least interventionist approach near death. This change indicates that the meaning and significance of advance care planning and resulting advance directives must be considered in light of the processes and temporal factors involved in their completion and use within this distinct population. The relational nature of advance care planning and concern about ageism as a factor for withholding or withdrawing life support for LTC residents are considered as possible explanatory factors. These findings and their implications are described in relation to end-of-life care policies and practices in LTC facilities.
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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 | 0.007 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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 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".