The 3 Wishes Program Improves Families’ Experience of Emotional and Spiritual Support at the End of Life
Bibliographic record
Abstract
BACKGROUND: The end-of-life (EOL) experience in the intensive care unit (ICU) is emotionally challenging, and there are opportunities for improvement. The 3 Wishes Program (3WP) promotes the dignity of dying patients and their families by eliciting and implementing wishes at the EOL. AIM: To assess whether the 3WP is associated with improved ratings of EOL care. PROGRAM DESCRIPTION: In the 3WP, clinicians elicit and fulfill simple wishes for dying patients and their families. SETTING: 2-hospital academic healthcare system. PARTICIPANTS: Dying patients in the ICU and their families. PROGRAM EVALUATION: A modified Bereaved Family Survey (BFS), a validated tool for measuring EOL care quality, was completed by families of ICU decedents approximately 3 months after death. We compared patients whose care involved the 3WP to those who did not using three BFS-derived measures: Respectful Care and Communication (5 questions), Emotional and Spiritual Support (3 questions), and the BFS-Performance Measure (BFS-PM, a single-item global measure of care). RESULTS: Of 314 completed surveys, 117 were for patients whose care included the 3WP. Bereaved families of 3WP patients rated the Emotional and Spiritual Support factor significantly higher (7.5 vs. 6.0, p = 0.003, adjusted p = 0.001) than those who did not receive the 3WP. The Respectful Care and Communication factor and BFS-PM were no different between groups. DISCUSSION: The 3WP is a low-cost intervention that may be a feasible strategy for improving the EOL experience.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".