Understanding the uptake of HIV testing among women in Liberia: the role of female genital mutilation/cutting
Bibliographic record
Abstract
Past studies show that the processes of female genital mutilation/cutting (FGM/C) on women can increase their susceptibility to HIV infection. This is because genital tears or ruptures, scars and wounds from FGM/C may expose survivors to heightened risks of contracting sexually transmitted infections, including HIV, if they engage in unsafe sexual practices. Hence, there is the need to promote HIV screening and testing among this population. Yet, in Liberia, there is a dearth of studies exploring the uptake of HIV testing among women who have experienced FGM/C. To understand this relationship, we used the 2019–2020 Liberia Demographic and Health Survey (LDHS) and employed logistic regression analysis to answer the following questions: (1) Are FGM/C survivors less likely to have been tested for HIV compared to non-FGM/C women; and (2) How does this disparity in the uptake of HIV testing differ by women’s marital status? We found that survivors of FGM/C were less likely to have been tested for HIV than non-FGM/C women, even after accounting for theoretically relevant variables (OR = 0.83, p < 0.01). In response to our second question, we found that survivors of FGM/C who were formerly married were less likely to have been tested for HIV compared to their non-FGM/C counterparts (OR = 0.48, p < 0.01). These findings highlight the importance of trauma-informed HIV prevention strategies in Liberia, and the need for policymakers to take a holistic approach to addressing the challenges that FGM/C survivors, especially formerly married women, may face in accessing HIV prevention and testing services, and to work towards creating a more inclusive and supportive environment for all at-risk groups.
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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 | 0.010 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".