Expectations and Attributions in Social Anxiety Disorder: Diagnostic Distinctions and Relationship to General Anxiety and Depression
Bibliographic record
Abstract
Contemporary cognitive models suggest that social anxiety disorder arises from a number of cognitive factors, including tendencies to form pessimistic (rather than optimistic) attributions and expectations for socially-related events. These models also assume that the strengths of such attributions and expectations are more closely linked with social anxiety than with general anxiety or depression. To test these assumptions, a battery of self-report measures was completed by participants with a primary diagnosis of generalized social anxiety disorder (n = 75), panic disorder with agoraphobia (n = 44), or post-traumatic stress disorder (n = 59). To examine differences on these cognitive variables, group comparisons were performed controlling for general anxiety, depression and medication status. Social anxiety disorder, compared with panic disorder with agoraphobia and post-traumatic stress disorder, was characterized by lower expectations for positive social events and higher expectations for negative social events. There was no difference among the groups on expectations for non-social positive or negative events. Stable and global attributions for social negative events were more closely associated with social anxiety disorder than with panic disorder with agoraphobia and post-traumatic stress disorder. Correlational analyses also revealed specific relationships among social-cognitive measures and social anxiety, even after controlling for general anxiety and depression. The results are consistent with cognitive models of social anxiety disorder.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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".