The Short‐Form McGill Pain Questionnaire as an outcome measure: Test–retest reliability and responsiveness to change
Bibliographic record
Abstract
Abilities of the Short-Form McGill Pain Questionnaire to assess change have scarcely been addressed in previous studies. The aim of the present study was to examine test-retest reliability, sensitivity to change and responsiveness to clinically important change using a Norwegian version (NSF-MPQ) in different groups of patients. ICC(1,1) values for test-retest reliability (relative reliability) assessed 1-3 days apart for total, sensory and affective scores were, respectively, 0.75, 0.76 and 0.62 in patients with musculoskeletal pain (n=58), and 0.93, 0.95 and 0.79 in patients with rheumatic pain (n=25). Variability in total scores (absolute reliability) was less in patients with rheumatic pain (within-subject standard deviation, S(w)=2.70) than in patients with musculoskeletal pain (S(w)=4.28). Sensitivity to change by standardized response mean (SRM) was mostly large (>0.80) for three patient groups reporting improvement after treatment. More sensitivity to change was demonstrated by the total and sensory scores than by the affective score, and sensitivity of the total score was similarly good to capture improvement as the Visual Analogue Scale (VAS). Indication was provided that mean improvement of groups in NSF-MPQ total scores should be >5 on the 0-45 scale to demonstrate a clinically important change. Responsiveness to clinically important change by receiver operating characteristic curve analysis was modest, as area under the curve indicating ability to discriminate improved and not improved patients with musculoskeletal pain, was only 0.61. The study indicates mostly satisfactory test-retest reliability and responsiveness values of the NSF-MPQ, but shows that the measurement properties vary between groups of patients with pain.
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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 | 0.034 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.001 | 0.001 |
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".