Reliability and Validity of the Turkish Short-Form McGill Pain Questionnaire-2 (TR-SF-MPQ-2) in patients with chronic low back pain
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to assess validity and reliability of the Turkish version of the expanded and revised version of the Short-Form McGill Pain Questionnaire (TR-SF-MPQ-2) in patients with chronic low back pain (CLBP) and to investigate the relationship between TR-SF-MPQ-2 and etiology, pain scales, and disability index. PATIENTS AND METHODS: Between October 2014 and December 2014, a total of 194 patients with CLBP (66 males, 128 females; mean age 50±14.3 years; range, 35 to 65 years) attending to our outpatient clinic were included. To assess reliability, Cronbach alpha (α) and intraclass correlation coefficient (ICC) were estimated for participants who completed the questionnaire in the morning and afternoon. The validity of the questionnaire was evaluated by analyzing the confirmatory factor analysis. The Visual Analog Scale and Oswestry Disability Index were also used to test concurrent validity of the questionnaire. RESULTS: For total score, Cronbach α was 0.912 and ICC was 0.973, ranging from 0.72 to 0.84 for Cronbach α and from 0.960 to 0.989 for ICC in subgroups. The confirmatory factor analysis showed a good model fit for each subgroup (χ2/Df <3, GFI >0.95, CFI >0.90, NFI >0.90, and RMSEA <0.10). The correlation coefficient between the mean VAS and the mean total score was 0.648. CONCLUSION: Our study results indicate that the Turkish version of the SF-MPQ-2 is a reliable and valid tool to assess pain in the Turkish patients with CLBP.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".