Assessment of Pain Intensity in Clinical Trials: Individual Ratings vs Composite Scores
Bibliographic record
Abstract
OBJECTIVES: To evaluate the reliability of findings suggesting that composite scores made up of just two ratings of recalled pain may be adequately reliable and valid for assessing outcome in pain clinical trials. DESIGN: Secondary analyses of data from a study where the responsivity of the outcome measures was a critical concern; that is, a study with few subjects testing the effects of a treatment that had only modest effects. Ten adults with spinal cord injury rated four domains of pain intensity (current pain and 24-hour recalled worst, least, and average pain) on four occasions before and after 12 sessions of neurofeedback treatment. We evaluated the reliability and validity of four single ratings and 16 different composite scores. RESULTS: None of the single-item scales performed adequately. However, composite scores made up of two items or more yielded consistent effect size estimates. CONCLUSIONS: The findings provide additional evidence that two-item composite scores may be adequate for assessing the primary outcome of pain intensity in chronic pain clinical trials. Additional research is needed to further establish the generalizability of these findings.
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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 | 0.294 | 0.505 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| 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; 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".