Patient-Reported Questionnaires in Multiple Sclerosis Rehabilitation: Responsiveness and Minimal Important Difference of the French Version of the Multiple Sclerosis Questionnaire for Physiotherapists
Bibliographic record
Abstract
Purpose: The aim of this study was to evaluate the responsiveness and minimal important difference (MID) of the French version of the Multiple Sclerosis Questionnaire for Physiotherapists (MSQPT). Method: A distribution-based approach was used. Patients (32) were recruited from inpatient and outpatient settings; they completed both the MSQPT and the Hamburg Quality of Life Questionnaire in Multiple Sclerosis (HAQUAMS) at baseline and again at 6 months or discharge. Responsiveness was evaluated using effect size (ES), standardized response mean (SRM), and modified SRM (MSRM), and the relative efficiency between the MSQPT and HAQUAMS was calculated. Distribution-based MID estimates were calculated for 0.33 SD, standard error of measurement, and minimal detectable change. Results: The main ES ranged from 0.41 (low) to 1.23 (high). The SRM (−0.89 to 2.69) was generally higher than the ES. The main MSRMs were acceptably low (−0.03 to 0.19). Although the MSQPT seemed more efficient than the HAQUAMS in detecting improved activity and participation, it was less efficient at identifying their deterioration. In a comparison of responsiveness and MID between the German and French versions of the MSQPT, the differences between estimates were small. Conclusions: The available evidence indicates that the French MSQPT is a responsive questionnaire with MIDs that are similar to those of the original German version.
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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 | 0.031 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".