The significant other version of the Pain Catastrophizing Scale (PCS-S): Preliminary validation
Bibliographic record
Abstract
Researchers have hypothesized that pain catastrophizing has a social function. Although work has focused on the catastrophizing of individuals with chronic pain (ICPs), little is known about the pain catastrophizing of their significant others. The purpose of this study was to test the validity of a revised version of the original PCS [Sullivan MJL, Bishop S, Pivik J. The pain catastrophizing scale: development and validation. Psychol Assess 1995; 7: 432-524.] in which individuals were instructed to report on their own catastrophizing about their significant other's pain. In Study 1, a confirmatory factor analysis was conducted to determine the factor structure of the PCS-Significant Other (PCS-S) in a diverse sample of university undergraduates (n=264). An oblique second-order 3-factor model with two cross-loadings provided the best fit and this model was invariant across gender and racial groups. This factor structure was cross-validated in Study 2 with a second sample of university undergraduates (n=213). Results indicated that the 3-factor structure with two cross-loadings was a viable model of significant others' pain catastrophizing across gender and racial groups. In Study 3, this factor structure was replicated and the content validity of the PCS-S was examined in a sample of adult ICPs and their spouses (n=111). Spouse catastrophizing was related to ICP pain severity and interference as well as both spouses' depressive symptoms. In addition, ICPs were at a greater risk for psychological distress when both spouses had higher levels of catastrophizing. The PCS-S has the potential to be a useful and valid measure of pain catastrophizing in the significant others of ICPs.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".