Musculoskeletal Pain Evaluation: McGill Pain Questionnaire Versus Multidimensional Pain Evaluation Scale
Bibliographic record
Abstract
Abstract The first and most important step in pain management is to correctly assess it. Short-form McGill Pain Questionnaire-2(SF-MPQ-2) and Multidimensional Pain Evaluation Scale (MPES) are valid and reliable tools used in clinical practice and research. Our aim was to evaluate the efficacy of pharmacological and non-pharmacological treatments applied for pain relief. 27 patients were included in the study, of which 12 were outpatients and 15 were inpatients. Statistical and clinical significant differences were obtained only for the inpatient group on the MPES (p=0.00, difference between means=3.07) and for 3 out of 4 domains of the SF-MPQ-2 (p=0.01, 0.01 and 0.00 and the difference between means=2.60, 2.00 and 2.20 for continuous pain, neuropathic pain and affective descriptors, respectively). Outcomes of pain management are better for inpatients due to a combination of analgesic drugs with physical medicine and rehabilitation procedures and a strict monitoring during their hospitalization.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.007 | 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".