Mother: a maternal online technology for health care dataset

503 question and answer pairs on maternal health were collected through a survey of challenges facing pregnant mothers in a rural and semi-urban area of Uganda. The answers to the questions were provided and validated by professional medical personnel. The participants were purposively sampled, focusing on women in their 1st, 2nd and 3rd trimesters, with a 94% response rate. The dataset addresses common health concerns, symptoms, and conditions associated with pregnancy, particularly for women without immediate access to medical personnel. It targets maternal health outcomes such as pregnancy, morbidity, and mortality, specifically among women of reproductive age.

Authors

Institutions

Publication Details

Journal
BMC Research Notes
Published
2025-04-08
DOI
https://doi.org/10.1186/s13104-025-07230-2
Primary Topic
Global Maternal and Child Health
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Mother: a maternal online technology for health care dataset

Odongo Steven Eyobu, Tonny J. Oyana, Lukman Bukenya, Brian Angoda Nyanga et al.
BMC Research Notes
Global Maternal and Child Health
article

Mother: a maternal online technology for health care dataset

Odongo Steven Eyobu, Tonny J. Oyana, Lukman Bukenya, Brian Angoda Nyanga, Daniel Ongom
article en

Abstract

503 question and answer pairs on maternal health were collected through a survey of challenges facing pregnant mothers in a rural and semi-urban area of Uganda. The answers to the questions were provided and validated by professional medical personnel. The participants were purposively sampled, focusing on women in their 1st, 2nd and 3rd trimesters, with a 94% response rate. The dataset addresses common health concerns, symptoms, and conditions associated with pregnancy, particularly for women without immediate access to medical personnel. It targets maternal health outcomes such as pregnancy, morbidity, and mortality, specifically among women of reproductive age.

BMC Research NotesVol. 18(1)
Makerere University (UG)
European Commission
Good health and well-being
Openalex Percentile: Top 91%
Global Maternal and Child Health
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.