Effectiveness of upgraded maternity waiting homes and local leader training in improving institutional births among women in the Jimma zone, Ethiopia: study protocol for a cluster-randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Ethiopia is one of the ten countries in the world that together account for almost 60% of all maternal deaths. Recent reductions in maternal mortality have been seen, yet just 26% of women who gave birth in Ethiopia in 2016 reported doing so at a health facility. Maternity waiting homes (MWHs) have been introduced to overcome geographical and financial barriers to institutional births but there is no conclusive evidence as to their effectiveness. We aim to evaluate the effects of upgraded MWHs and local leader training in increasing institutional births in the Jimma zone of Ethiopia. METHODS: A parallel, three-arm, stratified, cluster-randomized controlled trial design is being employed to evaluate intervention effects on institutional births, which is the primary outcome. Trial arms are: (1) upgraded MWH + religious/community leader training; (2) leader training alone; and (3) standard care. Twenty-four primary health care unit catchment areas (clusters) have been randomized and 3840 women of reproductive age who had a pregnancy outcome (livebirth, stillbirth or abortion) are being randomly recruited for each survey round. Outcome assessments will be made using repeat cross-sectional surveys at baseline and 24 months postintervention. An intention to treat approach will be used and the primary outcome analysed using generalized linear mixed models with a random effect for cluster and time. A cost-effectiveness analysis will also be conducted from a societal perspective. DISCUSSION: This is one of the first trials to evaluate the effectiveness of upgraded MWHs and will provide much needed evidence to policy makers about aspects of functionality and the community engagement required as they scale-up this programme in Ethiopia. TRIAL REGISTRATION: ClinicalTrial.gov, NCT03299491. Retrospectively registered on 3 October 2017.
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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 | 0.035 | 0.028 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.015 | 0.007 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.053 | 0.007 |
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".