Responsiveness of visual analogue and McGill pain scale measures
Bibliographic record
Abstract
OBJECTIVE: To compare the responsiveness of the McGill Pain Questionnaire with the Visual Analogue Scale (VAS). DESIGN: A repeated measures 2-group design was used, with subjects divided into "improved" and "non-improved" groups. The external criterion to identify improved and non-improved patients was a 7-point global perceived effect scale. SUBJECTS: Seventy-five patients with low back pain who had participated in a randomized controlled trial of postsurgical rehabilitation were included in the study. INTERVENTIONS: All patients completed both a VAS and McGill pain scale to describe their pain over the last 24 hours and a separate VAS to describe their current pain. MAIN OUTCOME MEASURES: Responsiveness was evaluated by using receiver-operating characteristic curves, with the analysis repeated for a range of cut-off points on the global perceived effect scale. Secondary analyses of responsiveness were provided by the t value for independent change scores and Spearman's rank correlation coefficient (rho). RESULTS: The study confirmed the results of earlier studies in finding that the VAS was less responsive to clinical change when used to rate current pain in comparison with pain over the last 24 hours. The study found that the VAS was more responsive than the McGill Pain Questionnaire when both instruments were used to rate pain over the last 24 hours. CONCLUSION: The results of this study suggest that the VAS may be a better tool than the McGill Pain Questionnaire for measuring pain in clinical trials and clinical practice.
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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 | 0.027 | 0.145 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".