Effect of the Contents in Advance Directives on Individuals’ Decision-Making
Bibliographic record
Abstract
Completing an advance directive offers individuals the opportunity to make informed choices about end-of-life care. However, these decisions could be influenced in different ways depending on how the information is presented. We randomly presented 185 participants with four distinct types of advance directive: neutrally framed (as reference), negatively framed, religiously framed, and a combination. Participants were asked which interventions they would like to receive at the end of life. Between 60% and 70% of participants responded "accept the special interventions" on the reference form. However, the majority (70%-90%) chose "refuse the interventions" on the negative form. With respect to the religious form, 70% to 80% chose "not decided yet." Participants who refused special life-sustaining treatments were older, female, and with better prior knowledge about advance directives. Our findings imply that the specific content of advance directives could affect decision-making with regard to various interventions for end-of-life care.
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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 | 0.072 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".