A qualitative analysis of decision-making among women with sexual violence-related pregnancies in conflict-affected eastern Democratic Republic of the Congo
Bibliographic record
Abstract
BACKGROUND: Sexual violence is prevalent in conflict-affected settings and may result in sexual violence-related pregnancies (SVRPs). There are limited data on how women with SVRPs make decisions about pregnancy continuation or termination, especially in contexts with limited or restricted access to comprehensive reproductive health services. METHODS: A qualitative study was conducted in Bukavu, Democratic Republic of the Congo (DRC) as part of a larger mixed methods study in 2012. Utilizing respondent-driven sampling (RDS), adult women who self-reported sexual violence and a resultant SVRP were enrolled into two study subgroups: 1) women currently raising a child from an SVRP (parenting group) and 2) women who terminated an SVRP (termination group). Trained female research assistants conducted semi-structured interviews with a subset of women in a private setting and responses were manually recorded. Interview notes were translated and uploaded to a qualitative software program, coded, and thematic content analysis was conducted. RESULTS: A total of 55 women were interviewed: 38 in the parenting group and 17 in the termination group. There were a myriad of expressed attitudes, beliefs, and emotional responses toward SVRPs and the termination of SVRPs with three predominant influences on decision-making, including: 1) the biologic, ethnic, and social identities of the fetus and/or future child; 2) social reactions, including fear of social stigmatization and/or rejection; and 3) the power of religious beliefs and moral considerations on women's autonomy in the decision-making process. CONCLUSION: Findings from women who continued and women who terminated SVRPs reveal the complexities of decision-making related to SVRPs, including the emotional reasoning and responses, and the social, moral, and religious dimensions of the decision-making processes. It is important to consider these multi-faceted influences on decision-making for women with SVRPs in conflict-affected settings in order to improve provision of health services and to offer useful insights for subsequent programmatic and policy decisions.
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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 | 0.011 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".