Body awareness and chronic low back pain: validity and reliability study of Turkish version of body awareness rating scale
Bibliographic record
Abstract
Background/aim: Previous studies reported that patients with chronic low back pain (CLBP) had trouble describing senses or body functions. A questionnaire, the body awareness rating questionnaire (BARQ), was recently developed for assessing body awareness. The aim of the study was to develop a Turkish version of the BARQ and investigate the validity and reliability in patients with CLBP. Materials and methods: BARQ translated to Turkish with forward-backward method. Ninety-nine patients with CLBP and 101 healthy controls (HC) completed the BARQ-T. Fifty-one of patients with CLBP and HC repeated BARQ-T 3 days later. In addition to BARQ-T, Oswestry disability index (ODI), pain severity, short form 36 (SF-36) and Toronto alexithymia scale (TAS) were administered. Results: The current study found good-excellent Cronbach’s alpha values for patients with CLBP (α: between 0.883–0.967) and acceptable-good Cronbach’s alpha values for HC (α: between 0.649–0.825) in factors of BARQ-T. ICC values for test-retest validity were found to be good-excellent for patients with CLBP in all factors. BARQ-T was positively correlated with SF-36 and negatively correlated with ODI and TAS (P < 0.05). Conclusion: The study confirmed that the BARQ-T has acceptable validation and reliability in terms of pain perception and pain assessment in the Turkish CLBP community.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".