Harmonizing Pain Outcome Measures: Results of the Pre-OMERACT Meeting on Partnerships for Consensus on Patient-important Pain Outcome Domains Between the Cochrane Musculoskeletal Group and OMERACT
Bibliographic record
Abstract
OBJECTIVE: A variety of authorities in pain measurement and outcome methodology met prior to the Outcome Measures in Rheumatology (OMERACT) 12 meeting in May 2014 to develop partnerships for consensus on pain outcomes. METHODS: Following overview presentations, discussion centered on pain-specific and global constructs in the domain of chronic pain. Practical issues for clinical trial implementation were also discussed. Breakout sessions were completed regarding additional details of domain constructs. A nominal group process involving all workshop participants confirmed that chronic pain outcome measures encompass a broad range of constructs and that existing scales may be inadequate for assessment in clinical trials. RESULTS: Participants endorsed that both pain intensity and pain interference are important constructs to be measured in clinical trials of chronic pain as it pertains to rheumatologic diagnoses. CONCLUSION: Further work is needed on inclusion of the patient perspective in the development of pain domains as well as Cochrane Collaboration summary of findings tables.
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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 | 0.623 | 0.601 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.009 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.010 | 0.027 |
| Research integrity | 0.008 | 0.012 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".