Measurement Properties of the Brief Pain Inventory-Short Form (BPI-SF) and Revised Short McGill Pain Questionnaire Version-2 (SF-MPQ-2) in Pain-related Musculoskeletal Conditions
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to systematically locate, critically appraise, and summarize clinical measurement research addressing the use of Brief Pain Inventory-Short Form (BPI-SF) and Revised Short McGill Pain Questionnaire Version-2 (SF-MPQ-2) in pain-related musculoskeletal (MSK) conditions. MATERIALS AND METHODS: We systematically searched 4 databases (Medline, CINAHL, EMBASE, and SCOPUS) and screened articles to identify those reporting the psychometric properties (eg, validity, reliability) and interpretability (eg, minimal clinically important difference) of BPI-SF and SF-MPQ-2 as evaluated in pain-related MSK conditions. Independently, 2 reviewers extracted data and assessed the quality of evidence with a structured quality appraisal tool and the updated COSMIN guidelines. RESULTS: In all, 26 articles were included (BPI-SF, n=17; SF-MPQ-2, n=9). Both tools lack reporting on their cross-cultural validities and measurement error indices (eg, standard error of measurement). High-quality studies suggest the tools are internally consistent (α=0.83 to 0.96), and they associate modestly with similar outcomes (r=0.3 to 0.69). Strong evidence suggests the BPI-SF conforms to its 2-dimensional structure in MSK studies; the SF-MPQ-2 4-factor structure was not clearly established. Seven reports of high-to-moderate quality evidence were supportive of the BPI-SF known-group validity (n=2) and responsiveness (n=5). One report of high quality established the SF-MPQ-2 responsiveness. DISCUSSION: Evidence of high-to-moderate quality supports the internal consistency, criterion-convergent validity, structural validity, and responsiveness of the BPI-SF and SF-MPQ-2 and establishes their use as generic multidimensional pain outcomes in MSK populations. However, more studies of high quality are still needed on their retest reliability, known-group validity, cross-cultural validity, interpretability properties, and measurement error indices in different MSK populations.
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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 | 0.160 | 0.485 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.018 | 0.017 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".