Psychometric Properties of Chosen Scales Evaluating Disability in Low Back Pain—Narrative Review
Bibliographic record
Abstract
Low back pain (LBP) is one of the most common disabling conditions. This disability significantly reduces the quality of life of LBP patients. This article reviews the most common and well-known measures currently used to assess disability in LBP, such as the Oswestry Disability Index (ODI), the Roland-Morris Disability Questionnaire (RMDQ), the Quebec Back Pain Disability Scale (QBPDS), the Low Back Outcome Score (LBOS), and the Low Back Pain Rating Scale (LBPRS). To reliably evaluate questionnaires and other measurement methods, there are parameters known as psychometric properties, which consist primarily of the validity, reliability and sensitivity. These methods are based on a multi-item questionnaire assessing physical functioning that is completed independently by the patient. They can be used to assess the disability associated with many conditions. All are specific to LBP, and their psychometric properties have been tested on a relevant population of patients with the condition and published in peer-reviewed publications.
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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 | 0.015 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".