Two Multiple Sclerosis Quality-of-Life Measures: Comparison in a National Sample
Bibliographic record
Abstract
BACKGROUND: Multiple sclerosis (MS) has a profound impact on patients' health-related quality of life (HRQoL). It is unclear how HRQoL can be best assessed for different purposes. This study aimed to compare two HRQoL questionnaires of differing lengths for feasibility of administration, patient perceptions and psychometric properties. METHODS: This was an open-label, 24-month study in 334 patients with relapsing MS treated with subcutaneous interferon β-1a. At baseline and months 6, 12, 18 and 24, patients completed the Multiple Sclerosis International Quality of Life (MusiQoL) and Multiple Sclerosis Quality of Life-54 (MSQOL-54) questionnaires and compared them using an evaluation questionnaire. HRQoL scores over time and psychometric properties (correlations with clinical disease measures, relative validity and responsiveness to change) of the questionnaires were assessed. RESULTS: A minority of patients had missing items on either HRQoL measure. Completion time was significantly shorter for MusiQoL versus MSQOL-54 (p<0.0001). Patients felt that MusiQoL was easier to use than MSQOL-54 but preferred MSQOL-54 in terms of thoroughness. Mean HRQoL scores increased significantly from baseline to 24 months; correlations of both measures were stronger with an anxiety and depression measure than with disability or recent relapse occurrence. Relative validity and responsiveness to change were similar for both instruments. CONCLUSION: The shorter MusiQoL is suitable for evaluating HRQoL in patients with MS and may be more practical to administer than the more thorough MSQOL-54.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".