A Systematic Literature Review of Important and Meaningful Differences in the EQ-5D Index and Visual Analog Scale Scores
Bibliographic record
Abstract
OBJECTIVES: We aimed to provide a comprehensive summary, synthesis, and appraisal of minimally important difference (MID) estimates for EQ-5D instruments. METHODS: We conducted a systematic search using relevant terms related to "minimally/clinically, meaningful/ important difference/change" and "EQ-5D" in 6 major databases, including MEDLINE, Embase, PsycINFO, CINAHL, Scopus, and Cochrane Library (up to January 2023). We included studies that provided at least 1 original MID estimate for the EQ-5D. RESULTS: A total of 90 studies reporting 840 MID estimates were included. MID estimates for the EQ-5D-3L index score ranged from 0.075 to 0.8 using distribution-based approaches (239 estimates; 20 studies), from 0.003 to 0.72 using anchor-based approaches (189 estimates; 43 studies), and from 0.038 to 0.082 using instrument-defined approaches (4 estimates; 1 study). For the EQ-5D-5L, MID estimates ranged from 0.023 to 0.115 using distribution-based approaches (17 estimates; 12 studies), from 0.01 to 0.41 using anchor-based approaches (97 estimates; 15 studies), and from 0.037 to 0.101 using instrument-defined approaches (62 estimates; 8 studies). For the EQ visual analog scale, MID estimates ranged from 0.96 to 16.6 using distribution-based approaches (87 estimates; 14 studies) and from 0.42 to 51.0 using anchor-based approaches (84 estimates; 24 studies). MID estimates varied by underlying clinical conditions, baseline scores, and direction of change. CONCLUSIONS: A wide range of MID estimates for EQ-5D instruments were identified, highlighting the variability of MID across populations, estimation methods, direction of change, baseline scores, and EQ-5D versions. These factors should be carefully considered when selecting an appropriate MID for interpreting EQ-5D scores.
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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 | 0.042 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 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".