Measurement Properties of the Quebec Back Pain Disability Scale in Patients With Nonspecific Low Back Pain: Systematic Review.
Bibliographic record
Abstract
BACKGROUND:\nThe Quebec Back Pain Disability Scale (QBPDS) has been translated into different languages, and several studies on its measurement properties have been done.\nPURPOSE:\nThe purpose of this review was to critically appraise and compare the measurement properties, when possible, of all language versions of the QBPDS by systematically reviewing the methodological quality and results of the available studies.\nMETHOD:\nBibliographic databases (PubMed, Embase, CINAHL, and PsycINFO) were searched for articles with the key words "Quebec," "back," "pain," and "disability" in combination with a methodological search filter for finding studies on measurement properties concerning the development or evaluation of the measurement properties of the QBPDS in patients with nonspecific low back pain. Assessment of the methodological quality was carried out by the reviewers using the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) checklist for both the original language version of the QBPDS in English and French and all translated versions. The results of the measurement properties were rated based on criteria proposed by Terwee et al.\nRESULTS:\nThe search strategy resulted in identification of 1,436 publications, and 27 articles were included in the systematic review. There was limited-to-moderate evidence of good reliability, validity, and responsiveness of the QBPDS for the different language versions, but for no language version was evidence available for all measurement properties.\nCONCLUSION:\nFor research and clinical practice, caution is advised when using the QBPDS to measure disability in patients with nonspecific low back pain. Strong evidence is lacking on all measurement properties for each language version of the QBPDS.
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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 | 0.024 | 0.109 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.013 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".