Can the Health Utilities Index Measure Change?
Bibliographic record
Abstract
BACKGROUND: The Health Utilities Index (HUI) is a multidimensional, preference-weighted measure of health status. It comprises eight health attributes, aggregated into a single utility score. OBJECTIVES: The purpose of the study was to investigate the ability of the HUI to detect changes in health status in a general population cohort. RESEARCH DESIGN: Health status changes were analyzed in the full cohort and in persons who were diagnosed with chronic conditions, hospitalized, or became restricted in daily activities. SUBJECTS: To assess responsiveness, longitudinal data was used from the National Population Health Survey conducted in Canada in 1994 - 1995 and 1996 - 1997. We used cross-sectional data from the 1996 sample to classify chronic conditions into mild, moderate, and severe. MEASURES: Two measures of responsiveness were calculated: Standardized Response Mean (SRM) and Sensitivity Coefficient (SC). The HUI was compared with a global health index-the Self-Rated Health (SRH) scale. RESULTS: HUI scores improved between the two NPHS cycles in all age-sex groups, except men 65 years of age and older. Among the respondents who remained free of chronic conditions, improvements were seen primarily in the cognitive and emotional domains. The HUI deteriorated among persons who were diagnosed between the two cycles with a severe chronic condition, were hospitalized, or became restricted in activity, but not in those diagnosed with a moderate condition. The SRMs were generally smaller for the HUI compared with the SRH. CONCLUSIONS: The HUI responds to changes in health status associated with serious chronic illnesses. However, changes in the HUI do not always coincide with changes in self-reported health. Properties of the HUI scales require further study.
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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 | 0.021 | 0.128 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".