Differentiating the roles of intolerance of uncertainty and negative beliefs about worry across emotional disorders
Bibliographic record
Abstract
Background: Researchers have examined intolerance of uncertainty (IU) and negative beliefs about worry (NBW) in emotional disorders. However, the distinct relationships of IU and NBW remain unclear. We examined IU and NBW across emotional disorders, controlling for overlapping symptoms. We also explored prospective and inhibitory IU. Methods: A sample of 565 undergraduates completed measures of IU and NBW, as well as measures of generalized anxiety, depression, social anxiety, panic, post-traumatic stress, obsessive-compulsive, and illness anxiety disorder symptoms. Regression analyses were used to determine which factors were uniquely associated with symptoms of each disorder. Results: Both IU and NBW were associated with generalized anxiety and social anxiety disorder symptoms. IU was also associated with obsessive-compulsive disorder symptoms and negatively associated with panic disorder symptoms. NBW was also associated with depression. Neither IU now NBW were associated with post-traumatic stress or illness anxiety disorders. Prospective and inhibitory IU also had differential associations with the emotional disorders. Conclusions: Our results indicate that IU and NBW, while transdiagnostic, are differentially associated with emotional disorder symptoms. Our results also support the discriminant validity of prospective and inhibitory IU.
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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 | 0.003 | 0.012 |
| 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 | 0.000 | 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".