Individual Predictors of Posttraumatic Distress: A Structural Equation Model
Bibliographic record
Abstract
OBJECTIVE: Recent research has called into question the "dose-effect" model of understanding response to trauma and has turned attention to the contribution of personality and environmental factors. This research seeks to model the interrelation of relational capacity (a component of personality), perceptions of social support, and posttraumatic distress. METHOD: A group of firefighters (n = 164) completed questionnaires that addressed exposure to traumatic events, social support, current level of distress, and relational capacity. Structural equation modelling was used to develop a framework for understanding traumatic reactions. RESULTS: The overall fit of the hypothesized model was excellent. Relational capacity had a significant negative effect on support, indicating that perceived social support decreased as disturbances in relational capacity increased. Perceived social support had a significant negative effect on level of distress. CONCLUSION: While some emotional response to disturbing events may be normal, the severity of symptoms covaries with the ability of the individual to develop and sustain supportive relationships to buffer the impact of events.
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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 | 0.011 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".