Supporting Women after Obstetric Fistula Surgery to Enhance Their Social Participation and Inclusion
Bibliographic record
Abstract
Obstetric fistula is a childbirth complication causing abnormal openings between the urinary, bowel, and genital tracts, leading to involuntary leakage and potential long-term disability. Even after surgical repair, women continue to face psychological and social challenges that affect their social inclusion and participation. This study explored family and service provider perspectives on current support systems and identified gaps affecting women's inclusion and participation post-fistula surgery. Building on a prior study of women who underwent obstetric fistula surgical repair, we qualitatively examined available formal and informal post-surgical supports in Ethiopia. We conducted 20 interviews with family members and service providers and analyzed them using Charmaz's grounded theory inductive analysis approach. We identified four themes that indicated the available formal support in fistula care, the impact of formal support on women's social participation and inclusion, the gaps in formal support systems, and post-surgery informal supports and their challenges. Both groups believed support needs for women after surgery remain unmet, highlighting the need to strengthen holistic support services to improve women's social inclusion and participation. This study contributes to limited research on formal and informal support for women, emphasizing the need for enhanced economic, psychological, and sexual health-related support post-obstetric fistula surgery.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 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 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".