Bibliographic record
Abstract
Betrayal trauma, or trauma perpetrated by someone with whom a victim is close, is strongly associated with a range of negative psychological and physical health outcomes. However, few studies have examined associations between different forms of trauma and emotional and physical symptoms. The present study compared betrayal trauma to other forms of trauma as predictors of young adults' psychological and physical symptoms, and explored potential mediators. A total of 185 university undergraduate students completed the Brief Betrayal Trauma Survey, the Trauma Symptom Checklist, the Toronto Alexithymia Scale, and the Pennebaker Inventory of Limbic Languidness. For each set of symptoms, simultaneous multiple regressions assessed the relative contributions of low versus high betrayal trauma to psychological and physical health reports. Structural equation models examined traumatic stress symptoms and alexithymia as mediators of the relationship between betrayal trauma and physical health symptoms. A total of 151 participants (82%) reported exposure to at least 1 of 11 forms of trauma queried (M = 2.08, SD = 1.94); 96 participants (51.9%) reported at least 1 betrayal trauma. Traumas characterized by high betrayal predicted alexithymia, anxiety, depression, dissociation, physical health complaints, and the number of days students reported being sick during the past month, whereas other traumas did not. Structural equation modeling revealed that traumatic stress symptoms and alexithymia mediated the association between betrayal trauma and physical health complaints. These results indicate that betrayal trauma is associated with young adults' physical and mental health difficulties to a greater extent than are other forms of trauma. Results may inform assessment, intervention, and prevention efforts.
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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 | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".