Sexual victimization, PTSD, depression, and social support among women survivors of the 2010 earthquake in Haiti: a moderated moderation model
Bibliographic record
Abstract
BACKGROUND: In 2010, an important earthquake devastated Haiti and caused thousands of deaths. In a social context where women are particularly vulnerable, this cross-sectional study examined the associations between sexual assaults experienced by women before the earthquake, the earthquake exposure, the traumatic consequences, and their satisfaction of social support received. METHODS: A total of 660 women aged 18 to 86 completed questionnaires assessing exposure to the earthquake, sexual assault victimization, peritraumatic distress, Posttraumatic stress disorder (PTSD), depression, and social support. A moderated moderation model was computed to examine associations between exposure to the earthquake, sexual assault, social support, and traumatic consequences. RESULTS: Results showed that 31.06% of women were victims of sexual assault before the earthquake. They presented higher prevalence of peritraumatic distress, PTSD, and depression symptoms, compared to non-victims. The moderated-moderation model showed that sexual assault and exposure to the earthquake were positively associated with traumatic consequences (respectively, B = 0.560, p < 0.001; B = 0.196, p < 0.001), while social support was negatively associated with them (B = -0.095, p < 0.05). Results showed a triple interaction: women victim of sexual assault who were satisfied with received social support are less likely to develop traumatic consequences after being exposed to the earthquake(B = -0.141, p < 0.01). CONCLUSIONS: By demonstrating the role of sexual assault in the development of mental health problems after the Haitian earthquake, this study shows the importance for clinicians to investigate interpersonal trauma experienced before or following natural disasters among survivors. Results also indicate the key role of family and communities to help survivors build resilience and coping strategies with their social support.
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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 | 0.001 | 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) | 0.003 | 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".