Time-Specific Differences in Stated Preferences for Health in the United States
Bibliographic record
Abstract
BACKGROUND: Changes over time in health state values from a societal perspective may be an important reason to consider updating societal value sets for preference-based measures of health. OBJECTIVE: The aim was to examine whether stated health preferences are different between 2002 and 2017, controlling for demographic changes in the United States. METHODS: Data from 2002 and 2017 US EQ-5D-3L valuation studies were combined. The primary analysis compared valuations of better-than-dead (BTD) states only, as both studies used the same time trade-off (TTO) method for these states. For worse-than-dead (WTD) states, the 2017 study used the lead-time TTO and the 2002 study used the conventional TTO, which necessitated transformation. Regression models were fitted to BTD values to estimate time-specific differences, adjusting for respondent characteristics. Secondary analyses examined models that fitted WTD values (using linear and nonlinear transformations of the 2002 data) and all values. RESULTS: The adjusted BTD-only model showed mean values were higher for 2017 compared with 2002 (βY2017=0.05, P<0.001). WTD-only models showed negative changes over time but that were dependent on the transformation method (linear βY2017=-0.72; nonlinear βY2017=-0.35; both P<0.001). Using all values, 2017 mean valuations were lower using a linear transformation (βY2017=-0.11; P<0.001) but did not differ with the nonlinear transformation. CONCLUSIONS: Individuals in 2017 are generally less willing to trade quantity for quality of life compared with 2002. This study provides evidence of time-specific differences in a society's preferences, suggesting that the era in which values were elicited may be an important reason to consider updating societal value sets.
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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 | 0.014 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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 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".