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Enregistrement W6928626664 · doi:10.3886/e123302v1-145202

Increasing Women's Access to Skilled Pregnancy Care in Rural Nigeria

2024· dataset· en· W6928626664 sur OpenAlexaffabout

Notice bibliographique

RevueICPSR Data Holdings · 2024
Typedataset
Langueen
Domaine
Thématique
Établissements canadiensUniversity of Ottawa
Organismes subventionnairesnon disponible
Mots-clésPsychological interventionGovernment (linguistics)PregnancyRural healthHealth careRural areaDeveloping countryPublic healthChristian ministry

Résumé

récupéré en direct d'OpenAlex

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>

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,003
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Communication savante, Science ouverte, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesMéta-épidémiologie (sens strict), Science ouverte, Charge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Jeu de données · Signal consensuel: Jeu de données
Score de désaccord entre enseignants0,059
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,003
Méta-épidémiologie (sens strict)0,0010,002
Méta-épidémiologie (sens large)0,0020,000
Bibliométrie0,0020,003
Études des sciences et des technologies0,0000,000
Communication savante0,0030,003
Science ouverte0,0120,017
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0010,038

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,030
Tête enseignante GPT0,340
Écart entre enseignants0,310 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeSans objet
Domainenon disponible
GenreJeu de données

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2024
Routes d'admission2
Résumé présentoui

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