Sensory sensitivity, intolerance of uncertainty and sex differences predicting anxiety in emerging adults
Bibliographic record
Abstract
As multiple vulnerability factors have been defined for anxiety disorders, it is important to investigate the interactions among these factors to understand why and how some individuals develop anxiety. Sensory Sensitivity (SS) and Intolerance of Uncertainty (IU) are independent vulnerability factors of anxiety, but their unique relationship in predicting anxiety has rarely been studied in non-clinical populations. The objective of this investigation was to examine the combined effects of SS and IU on self-reported anxiety in a sample of university students. In addition, with the frequently reported sex bias in anxiety literature, we expected that the combined effects of vulnerability factors would be different for females and males. A convenience sample of 313 university students, ages 17-26 years was recruited. The participants completed the Intolerance of Uncertainty Scale (IUS-12), the Adult/Adolescent Sensory Profile (AASP), and the Beck Anxiety Inventory (BAI). Results of moderated mediation analyses demonstrated a strong partial mediation between SS and anxiety through IU, providing evidence that IU, a cognitive bias against the unknown, was one mechanism that explained how SS was related to anxiety. Further, the effect of IU on anxiety was approximately twice as strong in females. Our results highlight the importance of studying the unique relationships among multiple vulnerability factors to better understand anxiety susceptibility in emerging adults.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".