Minimal important differences of measurement instruments used in rheumatoid arthritis: a scoping review
Bibliographic record
Abstract
BACKGROUND: Many outcomes relevant to rheumatoid arthritis are measured as continuous variables. Judging whether the results of those measurements are clinically significant requires determining the minimal important difference (MID) estimate. Therefore, valid MID estimate(s) are essential for the purposes of clinical decision-making and developing clinical recommendations. Our objective is to present the MID estimates for instruments used to measure outcomes in rheumatoid arthritis studies. METHODS: We conducted a scoping review. We included original research reports on MID of instruments used to measure outcomes in rheumatoid arthritis, using distribution- or anchor-based methods. We excluded conference abstracts. We searched MEDLINE (OVID) and EMBASE (OVID) databases on January 6, 2025 and scanned the reference lists of included studies and of identified relevant systematic reviews. Reviewers screened the titles and abstracts and full-texts, then abstracted data in duplicate and independently. They resolved disagreements by discussion or by consulting a third reviewer. We summarized the data narratively and in tabular formats. RESULTS: We identified 35 eligible studies reporting on a total of 144 MID estimates for 72 instruments used in rheumatoid arthritis. The most common constructs measured were physical function (26%), disease activity (18%), health status (17%) and fatigue (14%). The majority of measurement instruments were generic (60%). The most common instrument with MID estimates was the Health Assessment Questionnaire Disability Index (7%). The majority of MID estimates were calculated using anchor-based methods (72%). We did not critically appraise the included studies. CONCLUSIONS: We identified the MID estimates for a substantive number of measurement instruments used in rheumatoid arthritis. There was considerable variability in the findings for the same instrument within and across studies.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".