Factor structure and internal consistency of a Swedish version of the Pain Catastrophizing Scale
Bibliographic record
Abstract
BACKGROUND: Pain catastrophizing is highly relevant to assess in the context of long-standing pain. The Pain Catastrophizing Scale (PCS) is a well-established questionnaire used to measure catastrophizing in individuals with long-standing pain. So far, no Swedish translation has been evaluated in regard to validity and reliability. The aims of this study were to translate the PCS questionnaire from English to Swedish, and to investigate its construct validity (face, content, and structural validity) and reliability (internal consistency). METHODS: We translated the original English version of the PCS to Swedish and collected item responses from 194 persons suffering from primarily long-standing musculoskeletal pain. We used confirmatory factor analysis to evaluate structural validity, and tested the model fit of a one-factor model, an oblique two-factor model, and an oblique three-factor model. We evaluated the measure's reliability in regard to internal consistency calculated with Cronbach's alpha. RESULTS: A three-factor model comprising a four-item rumination factor, a three-item magnification factor, and a six-item helplessness factor provided the best fit to the data. Internal consistency was adequate and Cronbach's α was 0.92 for the entire scale, 0.84 for the rumination subscale; 0.69 for the magnification subscale, and 0.89 for the helplessness subscale. CONCLUSIONS: The results indicated adequacy of a three-factor solution and the questionnaire's internal consistency, and provide initial support for the structural validity and internal consistency of a Swedish version of the PCS. Future studies should replicate the study in larger samples and extend the current evaluation in regard to validity and reliability.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".