Acute posttraumatic stress symptoms and depression after exposure to the 2005 Saskatchewan Centennial Air Show disaster: Prevalence and predictors
Bibliographic record
Abstract
OBJECTIVES: The purpose of this study was to determine the prevalence of acute distress-that is, clinically significant posttraumatic stress symptoms (PTSS) and depression-and to identify predictors of each in a sample of people who witnessed a fatal aircraft collision at the 2005 Saskatchewan Centennial Air Show. DESIGN: Air Show attendees (N = 157) were recruited by advertisements in the local media and completed an Internet-administered battery of questionnaires. RESULTS: Based on previously established cut-offs, 22 percent respondents had clinically significant PTSS and 24 percent had clinically significant depressive symptoms. Clinically significant symptoms were associated with posttrauma impairment in social and occupational functioning. Acute distress was associated with several variables, including aspects of Air Show trauma exposure, severity of prior trauma exposure, low posttrauma social support (ie, negative responses by others), indices of poor coping (eg, intolerance of uncertainty, rumination about the trauma), and elevated scores on anxiety sensitivity, the personality trait of absorption, and dissociative tendencies. CONCLUSIONS: Results suggest that clinically significant acute distress is common in the aftermath of witnessed trauma. The statistical predictors (correlates) of acute distress were generally consistent with the results of studies of other forms of trauma. People with elevated scores on theoretical vulnerability factors (eg, elevated anxiety sensitivity) were particularly likely to develop acute distress.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".