Positive Beliefs about Post-Event Processing in Social Anxiety Disorder
Bibliographic record
Abstract
Abstract Background : Post-event processing (PEP) is an important maintenance factor of social anxiety disorder (SAD). This study examined psychometric properties of the Positive Beliefs about Post-Event Processing Questionnaire (PB-PEPQ; Fisak & Hammond, 2013), which measures metacognitive beliefs about PEP. Method : Participants receiving treatment for SAD ( n = 71) and other anxiety and related disorders ( n = 266) completed self-report questionnaires at several timepoints. Results : Confirmatory factor analysis did not support the PB-PEPQ's proposed unidimensional model. Subsequent exploratory factor analysis yielded a three-factor structure consisting of engaging in PEP to (1) review negative events (Negative scale), (2) review positive events (Positive scale), and (3) better understand one's social anxiety (Understand scale). Within the SAD subsample, PB-PEPQ scales demonstrated good internal consistency (α = 0.83–0.85) and test–retest reliability ( r = 0.65–0.78). Convergent and criterion validity of the PB-PEPQ Negative scale were supported. PB-PEPQ scale scores were significantly higher within the SAD group, as compared with the other groups (generalised anxiety disorder, panic disorder and agoraphobia, posttraumatic stress disorder, and obsessive-compulsive disorder), supporting the scales’ discriminative validity. Conclusion : Findings support the reliability and validity of the PB-PEPQ in a clinical sample and reveal the measure's multifactorial structure.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".