Intolerance of uncertainty, pain catastrophizing, and symptoms of depression: a comparison between adults with and without chronic pain
Bibliographic record
Abstract
Recent evidence suggests that individuals living with chronic pain demonstrate reduced tolerance of uncertainty compared to healthy individuals. Intolerance of uncertainty often lead to excessive worry, which may be related not only to the tendency to catastrophize pain, but also to increased distress. However, the specific nature of these relationships remains largely unexplored. The present study sought to investigate the associations between intolerance of uncertainty, pain catastrophizing, and symptoms of depression, while exploring how they differ between adults with and without chronic pain. Questionnaires were administered electronically to a community sample of 160 adults. All variables were significantly and positively correlated in the chronic pain group (n = 80), while only intolerance of uncertainty and symptoms of depression were positively and strongly correlated in the pain-free group (n = 80). Individuals in the chronic pain group reported higher levels of pain catastrophizing and symptoms of depression compared to the pain-free group, but both groups exhibited similar levels of intolerance of uncertainty. Intolerance of uncertainty and pain catastrophizing were significant predictors of the severity of depression in both groups, even after controlling for age and gender. However, intolerance of uncertainty was no longer statistically significant in the chronic pain group once pain catastrophizing was considered. These findings suggest that intolerance of uncertainty serves as a general vulnerability factor for psychological distress in adults, while pain catastrophizing acts as a specific vulnerability factor for individuals living with chronic pain. Enhancing knowledge about the role of cognitive factors in depression among individuals with chronic pain could help improve the management of this debilitating condition.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".