International clinimetric evaluation of the MG‐QOL15, resulting in slight revision and subsequent validation of the MG‐QOL15r
Bibliographic record
Abstract
INTRODUCTION: The MG-QOL15 is a validated, health-related quality of life (HRQOL) measure for myasthenia gravis (MG). Widespread use of the scale gave us the opportunity to further analyze its clinimetric properties. METHODS: We first performed Rasch analysis on >1,300 15-item Myasthenia Gravis Quality of Life scale (MG-QOL15) completed surveys. Results were discussed during a conference call with specialists and biostatisticians. We decided to revise 3 items and prospectively evaluate the revised scale (MG-QOL15r) using either 3, 4, or 5 responses. Rasch analysis was then performed on >1,300 MG-QOL15r scales. RESULTS: The MGQOL15r performed slightly better than the MG-QOL15. The 3-response option MG-QOL15r demonstrated better clinimetric properties than the 4- or 5-option scales. Relative distributions of item and person location estimates showed good coverage of disease severity. CONCLUSIONS: The MG-QOL15r is now the preferred HRQOL instrument for MG because of improved clinimetrics and ease of use. This revision does not negate previous studies or interpretations of results using the MG-QOL15. Muscle Nerve 54: 1015-1022, 2016.
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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 | 0.039 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".