The Intolerance of Uncertainty Index: Replication and extension with an English sample.
Bibliographic record
Abstract
Intolerance of uncertainty (IU) is related to anxiety, depression, worry, and anxiety sensitivity. Precedent IU measures were criticized for psychometric instability and redundancy; alternative measures include the novel 45-item measure (Intolerance of Uncertainty Index; IUI). The IUI was developed in French with 2 parts, assessing general unacceptability of uncertainty (15 items, Part A) and manifestations of uncertainty approximating more common anxiety disorder symptoms (30 items, Part B). The psychometric stability of the back-translated English items of the IUI as well as the incremental variance of Parts A and B remain to be assessed. The current study involved 2 samples of English-speaking community participants (n = 437 and n = 309; 73% women and 27% men) who completed the IUI and several related measures. Exploratory and confirmatory factor analyses suggested a refinement of IUI items as well as a unitary structure for Part A and a 3-factor structure for Part B. Regression results suggested Parts A and B each provide incremental validity in measures of worry, generalized anxiety disorder symptoms, negative problem orientation, and depression. Comprehensive results, implications, and future research directions are discussed.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".