Increasing Women's Access to Skilled Pregnancy Care in Rural Nigeria
Bibliographic record
Abstract
Nigeria is estimated to account for 19% of all estimated global maternal deaths with approximately 58,000 in 2015. The high number is partly due to the inadequate access of women to evidence-based skilled pregnancy care. The Federal Ministry of Health (FMoH) and all major health policy agencies in Nigeria have recognized the need for increased access to skilled obstetric care, especially in rural areas, as critical to reducing the high rate of maternal mortality. However, despite the fact that policymakers recognize that primary health care should play a key role in improving rural women's access to skilled pregnancy care, Primary Health Centres (PHCs) are often poorly utilized throughout the country. This project is a 5-year (2015-2020) implementation research conducted by the Women's Health and Action Research Centre (WHARC), Benin City, Nigeria in collaboration with the University of Ottawa (UOttawa), Canada and with funding from the International Development Research Centre (IDRC), Global Affairs Canada (GAC) and the Canadian Institute for Health Research (CIHR) under the Innovating for Maternal and Child Health in Africa (IMCHA) Initiative. The project's specific objectives are: 1) to identify the demand and supply factors responsible for the use and non-use of PHCs for pregnancy care in Esan South East and Etsako East LGAs of Edo State, Nigeria; 2) based on Objective 1, to derive and implement a set of multi-faceted community-led interventions to increase women's access to skilled pregnancy care offered in PHCs in Esan South East and Etsako East Local Government Areas (LGA); and 3) to evaluate the effectiveness of the interventions using both indicators of access to services, as well as maternal and fetal/newborn health outcomes in the intervention communities. The study was conducted in Esan South East and Etsako East Local Government Areas (LGAs) in Edo State in southern Nigeria. Both LGAs are located in the rural and riverine areas of the state, adjacent to River Niger, with Estako East in the northern part of the Edo State part of the river, while Esan South East is in the southern part. Edo State is one of Nigeria’s thirty-six states. Each state consists of LGAs, and LGAs consist of political/health Wards. The study was originally designed to be a randomized control trial (Yaya et al., 2018) but was changed to a quasi-experiment separate sample pretest and posttest design. The change was necessitated by the difficulty in achieving reliable randomization in the study communities. The study was conducted in three phases. At phase one, a baseline was conducted using a mixed-method approach to address objective 1. Based on the results of the baseline research, a set of intervention activities were designed and implemented simultaneously in phase 2 for two years. Phase three was the endline research which addressed the study objective 3. Ethical approval for the study was obtained from the National Health Research Ethics Committee (NHREC) of Nigeria – protocol number NHREC/01/01/2007 – 10/04/2017; and written informed consent was obtained from individual respondent/participant, except in the community conversations where the consent was verbal. The data we are sharing contain baseline and endline data. collected through a mixed-method approach to address the study objectives. The baseline data were collected between July 29 to August 16, 2017, using a mixed-method that comprises a household survey, exit interview, PHC site assessment survey, community conversation, focus group discussion, and key informant interview. The endline data were collected between June 24 and July 6, 2020, using a household survey. All the data collection instruments were pretested and the data were collected by trained data collectors. <br><br><br><br><br>
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".