Context Changes Choices: A Prospective Study of the Effects of Hospitalization on Life-Sustaining Treatment Preferences
Bibliographic record
Abstract
OBJECTIVE: Policy and law encouraging individuals to document their wishes for life-sustaining medical treatment in advance of serious illness assumes that these wishes are unaffected by changes in health condition. To test this assumption, the authors examine the life-sustaining treatment preferences of a sample of elderly adults prior to, soon after, and several months after a hospitalization experience. SUBJECTS AND METHODS: As part of the Advance Directives, Values Assessment, and Communication Enhancement (ADVANCE) project, 401 individuals older than age 65 participated in 3 annual interviews. A subsample of 88 individuals who were hospitalized for greater than 48 hours during the course of the study participated in an additional "recovery" interview conducted soon after their release from the hospital (M = 14 days postdischarge). At each interview, subjects indicated their desire to receive 4 life-sustaining medical treatments in 4 serious illness scenarios. RESULTS: Treatment preferences showed a significant "hospitalization dip," with subjects reporting less desire to receive life-sustaining treatment at the recovery interview than they did at the annual interview conducted prior to hospitalization, but with desire returning to near prehospitalization levels at the annual interview conducted several months after hospitalization. This dip was more pronounced in preferences for cardiopulmonary resuscitation and artificial nutrition and hydration than in preferences for less invasive treatments. CONCLUSIONS: Preferences for life-sustaining treatment are dependent on the context in which they are made, and thus individuals may express different treatment preferences when they are healthy than when they are ill. These results challenge a key psychological assumption underlying the use of instructional advance directives in end-of-life decision making.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".