Japanese health utilities index mark 3 (HUI3): measurement properties in a community sample
Bibliographic record
Abstract
BACKGROUND: The McMaster Health Utilities Index Mark 3 (HUI3) is a generic multi-attribute, preference-based system for assessing health-related quality of life (HRQOL). This study describes the translation procedures and cultural adaptation of the Japanese HUI3 and its measurement properties in a community sample. METHODS: The Japanese HUI3 was developed through forward and back translations in cooperation with the developers of the HUI. Acceptability, comprehensibility of questionnaires, and test-retest reliability were assessed. In a community survey of a total of 3860 people (age: 41 ± 14.3, male/female: 2651/1209), the Canadian scoring function was used to calculate utility scores. Construct validity was assessed by examining the relationship between 20 personal characteristics and utility scores. RESULTS: Linear regression estimates demonstrated a significant negative relation between HUI3 utility score and low education, male gender, poor interpersonal relationships, older age, and a higher number of chronic diseases. Single-attribute utility scores were associated with chronic conditions in the manner expected. The community samples were relatively healthy. More than 90% of the respondents were distributed in levels 1 and 2 in all attributes except cognition. Interpretability of utility score was assessed by estimation of the relationship between visual analogue scale (VAS) and the self-rated health and utility score. Independence of attributes was assessed. For only 3 of the 28 possible cross-comparisons among the 8 attributes were correlations coefficients greater than 0.25. CONCLUSION: Translation and adaptation of the HUI3 questionnaire into Japanese was successful, but the sample size and selection bias limit the interpretation of our study conclusions.
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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 | 0.012 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 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".