Sensitivity to Pain Traumatization: A Higher‐Order Factor Underlying Pain‐Related Anxiety, Pain Catastrophizing and Anxiety Sensitivity among Patients Scheduled for Major Surgery
Bibliographic record
Abstract
BACKGROUND: The present article addresses two related developments in the psychology of pain, and integrates them into a coherent framework to better understand the relationship between pain and trauma. The first is an emerging conceptualization regarding the nature of the hierarchical organization of major pain-related anxiety constructs. The second is the theoretical rationale and empirical evidence linking pain and symptoms of post-traumatic stress disorder. OBJECTIVES: To explore the underlying hierarchical factor structure of commonly used pain-related anxiety measures including the Pain Anxiety Symptoms Scale (PASS-20), the Pain Catastrophizing Scale (PCS), and the Anxiety Sensitivity Index (ASI); and to relate this structure to post-traumatic stress disorder in patients scheduled for major surgery. METHODS: Measures were completed by 444 patients scheduled to undergo major surgery. Exploratory factor analysis and subsequent higherorder analysis using the Schmid-Leiman transformation were conducted to investigate the underlying factor structure of the ASI, the PCS and the PASS-20. RESULTS: Twenty items from the ASI, the PASS-20 and the PCS loaded exclusively on one higher-order factor. The authors suggest the term 'sensitivity to pain traumatization' (SPT) for the underlying construct based in part on the strong, significant positive correlation between SPT scores and scores on the Post-traumatic Stress Disorder Checklist - Civilian Version. Finally, the total SPT score was significantly higher for patients with a history of pain than for those without a history of pain, both before surgery and one year after surgery. SPT describes the propensity to develop anxiety-related somatic, cognitive, emotional and behavioural responses to pain that resemble features of a traumatic stress reaction. Together, the results of the present study provide preliminary evidence for the construct validity of SPT.
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| 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".