The development and preliminary validation of a brief measure of chronic pain impact for use in the general population
Bibliographic record
Abstract
From a biopsychosocial perspective, assessing chronic pain's psychological impact should involve at minimum the measurement of pain severity, functional interference, and pain-related emotional burden. This article details the development of a brief instrument, the 15-item Profile of Chronic Pain: Screen (PCP:S), designed to address these three key elements in a national (US) sample of over 2400 individuals recruited via random digit dialing. Retest reliability, internal consistency, and preliminary validity were excellent. The scales also demonstrated minimal social desirability response bias. A series of confirmatory factor analyses on several distinct samples revealed a stable, 3-factor solution reflecting pain severity, interference, and emotional burden. Finally, national norms were developed by gender and three age groups. In view of its strong psychometric properties, the PCP:S has the potential to serve as a brief, cost-effective assessment tool for identifying individuals whose chronic pain merits more detailed psychosocial evaluation.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".