"Whenever I remember I shed tears and can't speak": A thematic qualitative analysis of trauma experiences and resiliency amongst displaced women fleeing the Sudan war.
Bibliographic record
Abstract
Background The ongoing war in Sudan has resulted in the world's largest humanitarian crisis to date, and the widespread violence and displacement has resulted in poor mental health outcomes. This study explores the mental health impact of violence and displacement on women and girls fleeing the conflict in Sudan to South Sudan. Methods A cross sectional, mixed methods study was conducted in South Sudanese settlement sites in July 2024. The study gathered data on women's and girls experiences of migration across the border from Sudan to South Sudan at Aweil North, using a sensemaking approach which captured micronarratives from participants aged 13+. Qualitative data were screened manually for inclusion, and narratives related to mental health and resilience were analyzed thematically. Results 327 narratives were included in the study. Main themes included experiences of psychological trauma, impact of trauma, life at settlement centres and resilience. Our study found high levels of traumatic experiences amongst study participants, including sexual violence, death or killing of a family member, torture, and abduction, with a wide range of mental health impacts. The lack of support and services at settlement centres appeared to compound these concerns. Despite adversity many participants demonstrated resilience, indicating the potential for post-traumatic growth. Conclusions Our study found strong evidence of the mental health impact of the ongoing war and insufficient aid in South Sudanese settlement centres amongst women and girls. As resilient behaviours were found amongst study participants, interventions which harness resiliency may help foster post-traumatic growth in this population. Finally, as both mental health research and humanitarian response in this area are often overlooked, there is a clear need for coordinated advocacy efforts to increase mental health support and services in response to this ongoing conflict.
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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 | 0.011 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.008 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".