Sensitivity to Pain Traumatization Scale: development, validation, and preliminary findings
Bibliographic record
Abstract
BACKGROUND: This article reports three studies describing the development and validation of the 12-item Sensitivity to Pain Traumatization Scale (SPTS-12). SPT refers to the anxiety-related cognitive, emotional, and behavioral reactions to pain that resemble the features of a traumatic stress reaction. METHODS: In Study 1, a preliminary set of 79 items was administered to 116 participants. The data were analyzed by using combined nonparametric and parametric item response theory resulting in a 12-item scale with a one-factor structure and good preliminary psychometric properties. Studies 2 and 3 assessed the factor structure and psychometric properties of the SPTS-12 in a community sample of 823 participants (268 with chronic pain and 555 pain-free) and a clinical sample of 345 patients (126 with chronic post-surgical pain, 92 with other nonsurgical chronic pain, and 127 with no chronic pain) at least 6 months after undergoing coronary artery bypass graft surgery, respectively. RESULTS: The final SPTS-12 derived from Study 1 comprised 12 items that discriminated between individuals with different levels of SPT, with the overall scale showing good to very good reliability and validity. The results from Studies 2 and 3 revealed a one-factor structure for chronic pain and pain-free samples, excellent reliability and concurrent validity, and moderate convergent and discriminant validity. CONCLUSION: The results of the three studies provide preliminary evidence for the validity and reliability of the SPTS-12.
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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 | 0.012 | 0.017 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".