RESPONSIVENESS OF ARABIC INSTRUMENTS FOR PAIN AND DISABILITY IN PATIENTS WITH LOW BACK PAIN
Bibliographic record
Abstract
Background: Fear-Avoidance Beliefs Questionnaire (FABQ), Quebec Back Pain Disability Scale (QDS), and Roland-Morris Disability Questionnaire (RMDQ) is widely used in patients with low back pain (LBP) to assess the level of disability. Nonetheless, there are limited data about the responsiveness properties of the Arabic versions of these scales. This study was conducted to assess the responsiveness of the Arabic versions of the FABQ, QDS, and RMDQ compared to that of the Visual Analog Scale (VAS).Methods: A sample of 68 patients with LBP completed FABQ, QDS, RMDQ, and VAS at baseline and after 14 days.Responsiveness was evaluated by calculating the standard error of measurement (SEM), the minimal detectable difference at 95% confidence level (MDD95%), standardized response mean (SRM), Cohen’s effect size (ES), Guyatt’s responsiveness index (GRI), area under the curve (AUC), and minimal clinically significant difference (MCID).Results: The SEM, MDD 95%, SRM, ES, GRI, AUC, and MCID for FABQ, QDS, RMDQ, and VAS were 2.54, 2.83, 0.77, and 0.82; 7.05, 7.85, 2.14, and 2.28; 0.67, 0.96, 0.74, and 1.04; 0.39, 0.39, 0.36, and 0.79; 0.76, 1.34, 1.26, and 1.66; 0.49, 0.63, 0.57, and 0.70; and 3.5, 4.5, 2.5, and 1.5; respectively.Conclusion: Although the responsiveness of the Arabic versions of FABQ, QDS, and RMDQ was below the recommended standards and less than the responsiveness calculated for the VAS, it was comparable with previously published versions in other languages. Additional studies are necessary to examine the three scales' responsiveness with a more extended follow-up period.
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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 | 0.013 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".