Reproducibility: Reliability and Agreement Parameters of the Revised Short McGill Pain Questionnaire Version-2 for use in Patients with Musculoskeletal Shoulder Pain
Bibliographic record
Abstract
Background: The Revised Short-Form McGill Pain Questionnaire Version-2 (SF-MPQ-2) is a multidimensional outcome measure designed to evaluate neuropathic and nonneuropathic pain. A recent systematic review found insufficient psychometric data with respect to musculoskeletal health conditions.Aims: The aim of this study was to describe the reproducibility (reliability and agreement) and internal consistency of the SF-MPQ-2 for use among patients with musculoskeletal shoulder pain.Methods: Eligible patients with shoulder pain from musculoskeletal (MSK) sources completed the SF-MPQ-2 at baseline (n = 195), and a subset did so again after 3 to 7 days (n = 48) if their response to the global rating of change scale remained unchanged. Cronbach’s alpha (α) and intraclass correlation coefficient (ICC[2,1]) were calculated. Standard error of measurement (SEM), group and individual minimal detectable change (MDC90), and Bland-Altman plots were used to assess agreement.Results: Cronbach’s α ranged from 0.83 to 0.95, suggesting very satisfactory internal consistency across the SF-MPQ-2 domains. Excellent ICC(2,1) scores were found in support of the total (0.95) and continuous (0.92) subscales; the remaining subscales displayed good ICC(2,1) scores (0.78–0.88). Bland-Altman analysis revealed no systematic bias between the test and retest scores (mean difference = 0.13 to 0.19). Though the best agreement coefficients were seen on the total scale (SEM = 0.5; MDC90 = 1.2, MDC90group = 0.3), they were acceptable for the SF-MPQ-2 subscales (SEM: range, 0.7–1; MDC90: range, 1.7–2.3; MDC90group: range, 0.4–0.5).Conclusions: The SF-MPQ-2 provides good to excellent test–retest reliability for multidimensional pain assessment among patients with musculoskeletal shoulder pain conditions.
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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 | 0.014 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".