Economic, social and mental health impacts of an economic intervention for female sexual violence survivors in Eastern Democratic Republic of Congo
Bibliographic record
Abstract
Background. Conflict-affected communities face poverty and mental health problems, with sexual violence survivors at high risk for both given their trauma history and potential for exclusion from economic opportunity. To address these problems, we conducted a randomized controlled trial of a group-based economic intervention, Village Savings and Loans Associations (VSLA), for female sexual violence survivors in the Democratic Republic of Congo. Methods. In March 2011, 66 VSLA groups, with 301 study participants, were randomized to the VSLA program or a wait-control condition. Data were collected prior to randomization, at 2-months post-program in June 2012, and 8-months later for VSLA participants only. Outcome data included measures of economic and social functioning and mental health severity. VSLA program effect was derived by comparing intervention and control participants' mean changes from baseline to 2-month follow-up. Results. At follow-up, VSLA study women reported significantly greater per capita food consumption and significantly greater reductions in stigma experiences compared with controls. No other study outcomes were statistically different. At 8-month follow-up, VSLA participants reported a continued increase in per capita food consumption, an increase in economic hours worked in the prior 7 days, and an increase in access to social resources. Conclusions. While female sexual violence survivors with elevated mental symptoms were successfully integrated into a community-based economic program, the immediate program impact was only seen for food consumption and experience of stigma. Impacts on mental health severity were not realized, suggesting that targeted mental health interventions may be needed to improve psychological well-being.
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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 | 0.002 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".