Testing the Valuation of the EQ-5D-Y-5L in Adults and Adolescents: Results From a 5-Country Study and Implications for the Descriptive System
Bibliographic record
Abstract
OBJECTIVES: The EQ-5D-Y-5L (Y-5L) is a new health-related quality-of-life instrument for children and adolescents. Value sets for the Y-5L are planned. This article aimed to test the ability of adult and adolescent respondents to differentiate the ordinal levels of the Y-5L in valuation tasks and to explore the characteristics of stated preferences for the Y-5L between adults and adolescents. METHODS: We collected latent-scale discrete choice experiment data via an online survey of adults (≥18 years) and adolescents (12-17 years) in Australia, Canada, China, The Netherlands, and Spain. A D-Efficient design consisting of 192 choice pairs was grouped into 16 blocks of 12 choice tasks per respondent. We used mixed-logit models to analyze the data and incremental dummies to represent movements from a less-severe level to its consecutive more-severe level. RESULTS: We did not observe preference inversions in adults or adolescents (ie, no statistically significant positive coefficients on the incremental dummies). Adults showed similar preferences for the Y-5L in terms of dimension importance: Pain/Discomfort was considered the most important dimension in all countries except for China; Looking After Myself and Usual Activity were the least important dimensions. In contrast, Mobility was considered the most important dimensions by adolescents in Canada, Spain, and China. CONCLUSIONS: Adults could differentiate between the Y-5L level labels in valuation tasks, whereas more randomness was observed in adolescents' choices. Observed differences between adult and adolescent stated preferences for the Y-5L raise questions about how these preferences should be reflected in cost-effectiveness analysis.
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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 | 0.021 | 0.008 |
| 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 | 0.000 |
| 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".