Peritraumatic distress across the lifespan: Clinical implications of age differences during the COVID‐19 pandemic
Bibliographic record
Abstract
Abstract The Peritraumatic Distress Inventory (PDI) is a well‐known self‐report questionnaire indexing the distress experienced during and shortly after a most stressful or traumatic event. Although sociodemographic factors contributing to peritraumatic distress have been previously investigated, no research has examined the nature and severity of peritraumatic distress reactions in a non‐clinical, community sample as a function of age. An international sample of 5621 adult participants were grouped according the World Health Organization's age stratification protocol. Mean scores and item endorsement on the PDI were compared across groups with respect to their worst experience of the COVID‐19 pandemic. A significant between‐group difference was found, F(55,615) = 30.74, p < 0.001, n2 = 0.027 whereby participants aged 18–39 years old reported the highest levels of peritraumatic distress. This group also endorsed a higher proportion of items on the PDI's two main factors (emotional distress and physical reactions), and were more likely to endorse feelings of helplessness, than older participants. It appears that severity of peritraumatic distress during the pandemic has affected younger people the most. Results are discussed in light of clinical implications.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".