A Comparison of Five Multi Attribute Utility Instruments
Bibliographic record
Abstract
This paper presents the results of the validation study carried out to evaluate the Assessment of Quality of Life (AQoL) Instrument for the measurement of health related quality of life and utility. It involves, inter alia, the largest comparison of utility instruments that has been carried out to date. The five instruments included in the study are the AQoL, the Canadian HUI III, the Finnish 15D, the EuroQoL (EQ5D) and the SF36 with UK utility weights as quantified by Brazier (1998). The paper compares: (i) the absolute utility score obtained by different sub-populations; (ii) instrument sensitivity; (iii) the incremental differences in utility between different health states; (iv) the structural properties of descriptive systems; and (v) a limited comparison with a Time Trade-Off (TTO) assessment of own health by individuals. Using these criteria the AQoL performs very well. Its predicted utilities are very similar to those obtained from the HUI. There is evidence that the AQoL has greater sensitivity to health states than other instruments and its psychometric properties, as usually judged, are excellent. Despite this, it is concluded that, at present, no single MAU system can claim to be the gold standard and that researchers should select an instrument that is sensitive to the health states which they are investigating and that caution should be exercised in treating any of the instrument results as representing a utility score which truly represents a trade-off between life and health related quality of life.
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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 | 0.055 | 0.143 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".