An Examination of Distress Intolerance in Undergraduate Students High in Symptoms of Generalized Anxiety Disorder
Bibliographic record
Abstract
People with generalized anxiety disorder (GAD) engage in maladaptive coping strategies to reduce or avoid distress. Evidence suggests that uncertainty and negative emotions are triggers for distress in people with GAD; however, there may also be other triggers. Recent conceptualizations have highlighted six types of experiences that people report having difficulty withstanding: uncertainty, negative emotions, ambiguity, frustration, physical discomfort, and the perceived consequences of anxious arousal. The present study examined the extent to which individuals high in symptoms of GAD are intolerant of these distress triggers, compared to individuals high in depressive symptoms, and individuals who are low in GAD and depressive symptoms. Undergraduate students (N = 217) completed self-report measures of GAD symptoms, depressive symptoms, and distress intolerance. Individuals high in GAD symptoms reported greater intolerance of all of the distress triggers compared to people low in symptoms of GAD and depression. Individuals high in GAD symptoms reported greater intolerance of physical discomfort compared to those high in depressive symptoms. Furthermore, intolerance of physical discomfort was the best unique correlate of GAD status, suggesting that it may be specific to GAD (versus depression). These findings support continued investigation of the transdiagnosticity and specificity of distress intolerance.
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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 | 0.004 |
| 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 | 0.001 | 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".