Barriers to obstetric fistula treatment in low‐income countries: a systematic review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To identify the barriers faced by women living with obstetric fistula in low-income countries that prevent them from seeking care, reaching medical centres and receiving appropriate care. METHODS: Bibliographic databases, grey literature, journals, and network and organisation websites were searched in English and French from June to July 2014 and again from August to November 2016 using key search terms and specific inclusion and exclusion criteria for discussion of barriers to fistula treatment. Experts provided recommendations for additional sources. RESULTS: Of 5829 articles screened, 139 were included in the review. Nine groups of barriers to treatment were identified: psychosocial, cultural, awareness, social, financial, transportation, facility shortages, quality of care and political leadership. Interventions to address barriers primarily focused on awareness, facility shortages, transportation, financial and social barriers. At present, outcome data, though promising, are sparse and the success of interventions in providing long-term alleviation of barriers is unclear. CONCLUSION: Results from the review indicate that there are many barriers to fistula treatment, which operate at the individual, community and national levels. The successful treatment of obstetric fistula may thus require targeting several barriers, including depression, stigma and shame, lack of community-based referral mechanisms, financial cost of the procedure, transportation difficulties, gender power imbalances, the availability of facilities that offer fistula repair, community reintegration and the competing priorities of political leadership.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it