Measurement properties of the brief pain inventory- short form (BPI-SF) and the revised short mcgill pain questionnaire-version-2 (SF-MPQ-2) in pain-related musculoskeletal conditions: A systematic review protocol
Bibliographic record
Abstract
© 2020 BY THE ARCHIVES OF BONE AND JOINT SURGERY. Background: The Brief Pain Inventory-Short Form (BPI-SF) and Revised Short-Form McGill Pain Questionnaire Version-2 (SF-MPQ-2) are generic pain assessment tools used in research and practice for pain assessment in musculoskeletal (MSK) conditions. A comprehensive review that systematically analyses their measurement properties in MSK conditions has not been performed. This review protocol describes the steps that will be taken to locate, critically appraise, compare and summarize clinical measurement research on the BPI-SF and SF-MPQ-2 in pain-related MSK conditions. Methods: Medline, EMBASE, CINAHL and Scopus will be searched for publications that examine the measurement properties of the Brief Pain Inventory and Revised Short-Form McGill Pain Questionnaire Version-2. Two reviewers will independently screen citations (title, abstract and full text) and extract relevant data. The extensiveness, rigor, and quality of measurement property reports will be examined with a structured measurement studies appraisal tool, and with the updated COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) guidelines. Findings will be descriptively summarized, and when possible, a meta-analysis will be performed. Discussion: This review will summarize and compare the current level of evidence on the measurement properties of the BPI-SF and SF-MPQ-2 in a spectrum of musculoskeletal conditions. We expect clinicians/researchers dealing with MSK conditions to have synthesized evidence that informs their decision making and preferences. In addition, the review hopes to identify gaps and determine priorities for future research with or on the BPI-SF and SF-MPQ-2 in MSK conditions.
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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 | 0.073 | 0.106 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.017 | 0.016 |
| Bibliometrics | 0.015 | 0.012 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.034 | 0.004 |
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".