Characterizing the Public's Preferential Attitudes Toward End‐of‐Life Care Options: A Role for the Threshold Technique?
Bibliographic record
Abstract
OBJECTIVES: To assess the Threshold Technique's (TT) feasibility in community-wide surveys of U.S. Medicare beneficiaries' preferences for end-of-life (EOL) care options. STUDY SETTING: Study participants were community-dwelling Medicare beneficiaries in four different regions in the United States. STUDY DESIGN: During personal interviews, participants considered four EOL scenarios, each presenting a choice between a less intense and more intense care option. DATA COLLECTION: Participants selected their initially favored option. Depending on that choice, in the subsequent TT the length of life offered by the more intense option was systematically increased or decreased until the participant "switched" to his or her initially rejected option. PRINCIPAL FINDINGS: Participants were able to select an initially favored option (in 3 of the 4 scenarios; this was the less intense option). The majority of participants were able to engage with the subsequent TT. In all scenarios, regardless of the increase/decrease in the length of life offered by the more intense option, the majority of participants were unwilling to "switch" to their initially rejected option. CONCLUSIONS: In surveys of populations' preferential attitudes toward EOL care options, the TT was a feasible elicitation method, engaging most participants and measuring the strength of their attitudes. Further methodological work is merited, involving (1) populations with various participant characteristics, and (2) different attributes in the TT task itself.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".