Safe Birth and Cultural Safety in southern Mexico: study protocol for a randomised controlled trial
Bibliographic record
Abstract
BACKGROUND: Indigenous women in the southern Mexican state of Guerrero face poor maternal health outcomes. Living as they do at the very periphery of the Western health system, they often receive low-quality care from health services that lack human and financial resources. Traditional health systems remain active in indigenous communities where traditional midwives accompany women through motherhood. Several interventions have explored training birth attendants in Western birthing skills, but little research has focussed on supporting traditional midwives by recognising their knowledge. This trial supports traditional midwifery in four indigenous groups and measures its impact on maternal health outcomes. METHODS: The study includes four indigenous populations in the State of Guerrero (Nahua, Na savi/Mixteco, Me'phaa/Tlapaneco and Nancue ñomndaa/Amuzgo), covering approximately 8000 households. A parallel-group cluster-randomised controlled trial will compare communities receiving usual care with communities where traditional midwives received support in addition to the usual care. The intervention was defined in collaboration with participants in a 2012 pilot study. Supported midwives will receive a small stipend, a scholarship to train one apprentice, and support from an intercultural broker to deal with Western health personnel; additionally, the health staff in the intervention municipalities will participate in workshops to improve understanding and attitudes towards authentic traditional midwives. A baseline and a final survey will measure changes in birth and pregnancy complications (primary outcomes), and changes in gender violence, access to healthcare, and engagement with traditional cultural activities (secondary outcomes). The project has ethical approval from the participating communities and the Universidad Autónoma de Guerrero. DISCUSSION: Indigenous women at the periphery of Western health services do not benefit fully from the attenuated services which erode their own healthcare traditions. Western health service providers in indigenous communities often ignore traditional knowledge and resources, inadvertently or in ignorance, disrespecting indigenous cultures. Improved understanding between midwives and the official healthcare system can contribute to more appropriate referral of high-risk cases, improving the use of scarce resources while lowering costs of healthcare for indigenous families. TRIAL REGISTRATION: ISRCTN12397283 . Retrospectively registered on 6 December 2016.
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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 | 0.017 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".