Comparison of the standard gamble, rating scale, AQLQ and SF-36 for measuring quality of life in asthma
Bibliographic record
Abstract
With interest in health economics growing, there is a demand for valid methods for measuring health-related quality of life (HRQL) in asthma using utilities. The aims of this study were to develop disease-specific versions of the standard gamble and rating scale, to compare their measurement properties with those of the Asthma Quality of Life Questionnaire (AQLQ) and the Medical Outcomes Survey Short-Form 36 (SF-36), as well as to determine their validity for assessing asthma-specific quality of life. Forty adults with symptomatic asthma participated in a 9-week observational study. Participants completed the standard gamble, rating scale, AQLQ, SF-36 and other measures of clinical asthma status at baseline and after 1, 5 and 9 weeks. In patients whose asthma was stable between assessments, reliability was good for the rating scale (intraclass correlation coefficient (ICC)=0.89) and the AQLQ (ICC=0.95) but more modest for the SF-36 mental score (ICC=0.68), SF-36 physical score (ICC=0.65) and standard gamble (ICC=0.59). The responsiveness index was highest in the AQLQ (1.35), followed by the rating scale (0.74), the physical score of the SF-36 (0.61) and the standard gamble (0.31). Construct validity (correlation with other indices of health status) was strongest for the AQLQ and the rating scale. In conclusion, both the disease-specific rating scale and the Asthma Quality of Life Questionnaire have strong measurement properties for measuring asthma-specific quality of life; the Short-Form 36 health survey physical summary score has more modest properties. Although the disease-specific standard gamble has acceptable discriminative properties, its evaluative properties are too inadequate for it to be used in cost/utility analyses. Poor correlation between the standard gamble and the rating scale indicates that utilities cannot be derived from rating scale data.
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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 | 0.055 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".