Is Post-Event Processing a Social Anxiety Specific or Transdiagnostic Cognitive Process in the Anxiety Spectrum?
Bibliographic record
Abstract
BACKGROUND: Research on post-event processing (PEP), where individuals conduct a post-mortem evaluation of a social situation, has focused primarily on its relationship with social anxiety. AIMS: The current study examined: 1) levels of PEP for a standardized event in different anxiety disorders; 2) the relationship between peak anxiety levels during this event and subsequent PEP; and 3) the relationship between PEP and disorder-specific symptom severity. METHOD: Participants with primary DSM-IV diagnoses of social anxiety disorder (SAD), obsessive compulsive disorder (OCD), panic disorder with/without agoraphobia (PD/A), or generalized anxiety disorder (GAD) completed diagnosis specific symptom measures before attending group cognitive behavioural therapy (CBT) specific to their diagnosis. Participants rated their peak anxiety level during the first group therapy session, and one week later rated PEP in the context of CBT. RESULTS: The results indicated that all anxiety disorder groups showed heightened and equivalent PEP ratings. Peak state anxiety during the first CBT session predicted subsequent level of PEP, irrespective of diagnostic group. PEP ratings were found to be associated with disorder-specific symptom severity in SAD, GAD, and PD/A, but not in OCD. CONCLUSIONS: PEP may be a transdiagnostic process with relevance to a broad range of anxiety disorders, not just SAD.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".