“My job is to get pregnant women to the hospital”: a qualitative study of the role of traditional birth attendants in the distribution of misoprostol to prevent post-partum haemorrhage in two provinces in Mozambique
Bibliographic record
Abstract
BACKGROUND: Post-partum haemorrhage is the leading cause of maternal deaths in Mozambique. In 2015, the Mozambican Ministry of Health launched the National Strategy for the Prevention of Post-Partum Haemorrhage at the Community Level. The strategy included the distribution of misoprostol to women in advance at antenatal care and via Traditional Birth Attendants who directly administer the medication. The study explores the role of Traditional Birth Attendants in the misoprostol program and the views of women who used misoprostol to prevent post-partum haemorrhage. METHODS: This descriptive study collected data through in-depth interviews and focus group discussions. Traditional Birth Attendants between the ages of 30-70 and women of reproductive age participated in the study. Data was collected between June-October 2017 in Inhambane and Nampula Provinces. Line by line thematic analysis was used to interpret the data using Nvivo (v.11). RESULTS: The majority of TBAs in the study were satisfied with their role in the misoprostol program and were motivated to work with the formal health system to encourage women to access facility based births. Women who used misoprostol were also satisfied with the medication and encouraged family and friends to access it when needed. Women in the community and Traditional Birth Attendants requested assistance with transportation to reach the health facility to avoid home births. CONCLUSIONS: This study contributes to the evidence base that Traditional Birth Attendants are an appropriate channel for the distribution of misoprostol for the prevention of post-partum haemorrhage at the community level. More support and resources are needed to ensure Traditional Birth Attendants can assist women to have safe births when they are unable to reach the health facility. A consistent supply of misoprostol is needed to ensure women at the community level receive this life saving medication.
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.009 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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".