Promoting advance care planning among community-based older adults: A randomized controlled trial
Bibliographic record
Abstract
OBJECTIVE: To test an intervention designed to motivate older adults in documenting their healthcare preferences in advance, and to guide proxies in making hypothetical decisions that match those of the older adult. METHODS: The trial involved 235 older adults, of which half were assisted in communicating their wishes to their proxy. Hypothetical vignettes were used at baseline and twice after the intervention to elicit older adults' preferences and assess their proxy's ability to predict them. RESULTS: By the end of the trial, 80% of older adults allocated to the experimental group had documented their wishes. Changes over time in mean accuracy scores did not differ between groups for any hypothetical situations, except when limiting the sample to dyads that were highly discordant at baseline. CONCLUSION: The intervention motivated a large proportion of older adults to express their preferences but had little effect on proxies' ability to predict them. PRACTICE IMPLICATIONS: Educational tools developed for this study will assist healthcare providers in helping older adults to record their wishes in advance. Clients must be informed of the challenge of making substitute decisions and of the need to discuss the amount of leeway the proxy should have in interpreting expressed wishes.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".