Factor structure and invariance of the pain catastrophizing scale in patients with chronic pain and their spouses.
Bibliographic record
Abstract
PURPOSE: This study was designed to investigate the equivalency and factor structure of the patients and significant others' version of pain catastrophizing scales in patients with chronic pain and their spouses who are not in pain. METHOD: Participants were 142 married couples in which 1 spouse reported chronic musculoskeletal pain. Confirmatory factor analyses were used to compare 4 models of pain catastrophizing, and to examine the invariance of the factor structure of the PCS-Patient version and the PCS-Significant other version in patients with chronic pain and their spouses. RESULTS: The results indicated that the 2-factor oblique model provided an adequate fit to the data of both patients with chronic pain and their spouses who are not in pain. Moreover, it was found that when gender was controlled, the hypothesized factor structures of the PCS-patient version and the PCS-Significant other version were invariant. Indeed, it was revealed that the PCS-Patient version and the PCS-Significant other version measure the same factors in couples in which 1 of them have a chronic pain condition. CONCLUSIONS: The findings of the current study showed that the 2-factor oblique model is the best fit in both samples (i.e., patients with chronic pain and their spouses). Therefore, it can be suggested that these versions can be used among patients and their spouses and the findings regarding them can be compared. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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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 | 0.004 | 0.018 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".