A Conceptual Model of Family Surrogate End-of-Life Decision-Making Process in the Nursing Home Setting: Goals of Care as Guiding Stars
Bibliographic record
Abstract
An increasing proportion of dying is occurring in America's nursing homes (NH). Family members are involved in (and affected by) medical decision-making on behalf of NH residents approaching the end of life, especially when the resident is cognitively impaired. This article proposes an empirically derived conceptual model of the key factors NH family surrogate decision-makers consider when establishing or changing goals of care and the iterative process as applied to the NH setting. This model also establishes the importance of family social role expectations toward their loved one as well as the concept, "stance toward dying," as key in establishing or changing the main goal of care. NH staff and physicians can use the model as a framework for providing information and support to family members. Research is needed to better understand how to prepare staff and settings to support family surrogate decision-makers, in particular around setting goals of care. The model can be generalized beyond nursing homes.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.012 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".