Translation, cross-cultural adaptation and validation of the Quebec back pain disability scale to urdu language
Bibliographic record
Abstract
Background: Back pain is one of most prevalent health issues. The Quebec Back Pain Disability Scale (QBPDS) is a frequently used tool for back pain. Quebec Back Pain Disability Scale was translated into Urdu so that Urdu speaking population can appropriately report their back pain experience. Objectives: To translate and across cultural adapt QBPDS into Urdu (QBPDS-U) as well as to evaluate QBPDS-U’s psychometric properties in patients having non-specific low back pain (NLPB). Methods: The ethical approval obtained had reference number SN/73/19. The QBPDS was forward and backward translated and culturally modified into Urdu, according to Mapi Research Trust Guidelines. To assess the psychometric properties, there were 200 NLPB patients and 50 healthy individuals recruited for the study. The QBPDS-U, Oswestry Disability Index (ODI), visual analogue scale for pain (VASpain), and Visual Analogue Scale for disability (VASdisability) were used. Patients responded to all questionnaires, as well as the global rating of change scale (GROC), after three weeks of physical therapy. Reliability, factor analysis, validity, and responsiveness were examined. Results: The QBPDS-U showed high internal consistency (Cronbach’s alpha=0.96) and excellent test-retest reliability (intra-class correlation coefficient=0.93). Factor analysis of QBPDS-U retained single factor structure. The QBPDS-U correlated moderately with VASdisability and VASpain [(r=0.65), P<0.001], but strongly with ODI [(r=0.73), P<0.001]. Discriminative validity was confirmed by significant differences in QBPDS-U total scores between healthy individuals and patients (P<0.001). The responsiveness of the QBPDS-U was verified by a significant difference in change scores between the stable and better groups (P<0.001). Conclusion: The QBPDS-U is a valid, reliable, and responsive tool for measuring disability in NLBP patients who speak Urdu.
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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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".