Comparative responsiveness of the health utilities index and the RAND-12 for multiple sclerosis
Bibliographic record
Abstract
BACKGROUND: Outcome measures need to be valid and have good test-retest reliability and responsiveness. We compared the responsiveness of the RAND-12 and the Health Utilities Index-mark III (HUI3) in persons with multiple sclerosis (MS). METHODS: In Spring 2018 and 2019, North American Research Committee on Multiple Sclerosis (NARCOMS) registry participants completed the HUI3, the RAND-12, and reported disability (Patient Determined Disease Steps (PDDS)) and employment status (full-time, part-time, and no). We used changes in PDDS and employment status as anchors. We assessed responsiveness using effect size, standardized response mean, and the responsiveness index. We used relative efficiency (RE) to compare the responsiveness of the health-related quality of life (HRQOL) scores, adjusting for sociodemographic factors. RESULTS: We included 4769 participants in the analysis. They had a mean (standard deviation (SD)) age of 60.9 (10.1) years, and 3826 participants (80.2%) were women. RE was highest for the HUI3 for changes in in disability status (HUI3: 1.0, Physical Component Score-12 (PCS-12): 0.80, and Mental Component Score-12 (MCS-12): 0.41) and for changes in employment status (HUI3: 1.0, PCS-12: 0.70, and MCS-12: 0.17). CONCLUSION: The HUI3 was more responsive to changes in disability and employment status than the PCS-12 or MCS-12. Given the HUI3's other strong psychometric properties, it may be the preferred generic measure of HRQOL in MS.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".