Generic Health-Related Quality of Life Utility Measure for Preschool Children (Health Utilities Preschool): Design, Development, and Properties
Bibliographic record
Abstract
OBJECTIVES: Health Utilities Preschool (HuPS) was developed to fill the need for a generic preference-based measure (GPM) applicable in early childhood. A GPM has all the properties for higher-order summary measures, such as quality-adjusted life-years, required to inform important policy decisions regarding health and healthcare services. METHODS: Development was in accordance with published standards for a GPM, statistical procedures, and modeling. HuPS incorporates key components of 2 existing measurement systems: Health Status Classification System for Preschool Children and Health Utilities Index Mark 3 (HUI3). The study included a series of 4 measurement surveys: definitional, adaptational, quantificational, and evaluational health-related quality of life (HRQL). HuPS measurements were evaluated for reliability, validity, interpretability, and acceptability. RESULTS: Definitional measurements identified 8 Health Status Classification System for Preschool Children attributes in common with HUI3 (vision, hearing, speech, ambulation, dexterity, emotion, cognition, and pain and discomfort), making the HUI3 scoring equation commensurate with HuPS health states. Adaptational measurements informed the content of attribute-level descriptions (n = 35). Quantificational measurements determined level scoring coefficients. HRQL scoring inter-rater reliability (intraclass correlation coefficient = 0.79) was excellent. Continuity of HRQL scoring with HUI3 was reliable (intraclass correlation coefficient = 0.80, P < .001) and valid (mean absolute difference = 0.016, P = .396). CONCLUSIONS: HuPS is an acceptable, reliable, and valid GPM. HRQL scoring is continuous with HUI3. Continuity expands the applicability of GPM (HUI3) scoring to include subjects as young as 2 years of age. Widespread applications of HuPS would inform important health policy and management decisions as HUI3 does for older subjects.
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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 | 0.010 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".