Development and validation of the trait and state versions of the Post-Event Processing Inventory
Bibliographic record
Abstract
BACKGROUND: Post-event processing (PEP) refers to negative and prolonged rumination following anxiety-provoking social situations. Although there are scales to assess PEP, they are situation-specific, some targeting only public-speaking situations. Furthermore, there are no trait measures to assess the tendency to engage in PEP. OBJECTIVES: The purpose of this research was to create a new measure of PEP, the Post-Event Processing Inventory (PEPI), which can be employed following all types of social situations and includes both trait and state forms. DESIGN AND METHOD: Over two studies (study 1, N = 220; study 2, N = 199), we explored and confirmed the factor structure of the scale with student samples. RESULTS: For each form of the scale, we found and confirmed that a higher-order, general PEP factor could be inferred from three sub-domains (intensity, frequency, and self-judgment). We also found preliminary evidence for the convergent, concurrent, discriminant/divergent, incremental, and predictive validity for each version of the scale. Both forms of the scale demonstrated excellent internal consistency and the trait form had excellent two-week test-retest reliability. CONCLUSION: Given the utility and versatility of the scale, the PEPI may provide a useful alternative to existing measures of PEP and rumination.
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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 | 0.000 |
| 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".