An Investigation of the Effects of Worry and Anger on Threatening Interpretations and Hostile Attributions of Ambiguous Situations
Bibliographic record
Abstract
Individuals with generalized anxiety disorder (GAD) frequently report elevated anger. Information processing biases may underlie this finding. We examined the effects of worry (n = 51) and anger rumination (n = 50) inductions, relative to relaxation (n = 49), on information processing biases associated with GAD and trait anger using an experimental design. We also examined whether participants who met diagnostic criteria for GAD via self-report (n = 41) exhibited greater negative information processing styles than less anxious individuals (n = 109) following the mood inductions. Participants completed tasks assessing threatening interpretations of ambiguous situations and hostile and benign attributions of ambiguous intent. There were no differences in information processing across the three conditions. However, GAD analogues demonstrated greater threatening interpretations and hostile attributions than their less anxious counterparts, regardless of experimental condition. This suggests that GAD symptoms relate to both threatening interpretation and hostile attribution biases.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".