Differential item functioning of the Arm function in Multiple Sclerosis Questionnaire (AMSQ) by language, a study in six countries
Bibliographic record
Abstract
Background: The Arm function in Multiple Sclerosis Questionnaire (AMSQ) has been developed as a self-reported measure of arm and hand functioning for patients with multiple sclerosis (MS). The AMSQ was originally developed in Dutch and to date translated into five languages (i.e. English, German, Spanish, French, and Italian). Objective: The aim of this study was to evaluate differential item functioning (DIF) of the AMSQ in these languages. Methods: We performed DIF analyses, using “language” as the polytomous group variable. To detect DIF, logistic regression and item response theory principles were applied. Multiple logistic regression models were evaluated. We used a pseudo R 2 value of 0.02 or more as the DIF threshold. Results: A total of 1733 male and female patients with all subtypes of MS were included. The DIF analysis for the whole dataset showed no uniform or non-uniform DIF on any of the 31 items. All R 2 values were below 0.02. Conclusion: The AMSQ is validated in six languages. All items have the same meaning to MS patients in Dutch, English, German, Spanish, French, and Italian. This validation study enables use of the AMSQ in international studies, for monitoring treatment response and disease progression.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".