Evidence map›Paper›PMID 34387125›Full record

ArticleWomen's health (London, England)

Maternal knowledge-seeking behavior among pregnant women in Tanzania.

Elsie Somi Kaaya, Jesuk Ko, Edith Luhanga

Abstract read
In one paragraph

Article in Women's health (London, England). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Elsie Somi KaayaSchool of Computational and Communication Science and Engineering, The Nelson Mandela African Institution of Science and Technology, Arusha, Tanzania.ORCID 0000-0002-2420-6316
Jesuk KoDepartment of Industrial Engineering, Universidad Mayor de San Andrés (UMSA), La Paz, Bolivia.ORCID 0000-0002-0577-8589
Edith LuhangaSchool of Computational and Communication Science and Engineering, The Nelson Mandela African Institution of Science and Technology, Arusha, Tanzania.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMaternal mortality continues to be a global challenge with about 830 women dying of childbirth and pregnancy complications every day. Tanzania has a maternal mortality rate of 524 deaths per 100,000 live births.

objectiveKnowing symptoms associated with antenatal risks among pregnant women may result in seeking care earlier or self-advocating for more immediate treatment in health facilities. This article sought to identify knowledge-seeking behaviors of pregnant women in Northern Tanzania, to determine the challenges met and how these should be addressed to enhance knowledge on pregnancy risks and when to seek care.

methodsInterview questions and questionnaires were the main data collection tools. Six gynecologists and four midwives were interviewed, while 168 pregnant women and 14 recent mothers participated in the questionnaires.

resultsWith the rise in mobile technology and Internet penetration in Tanzania, more women are seeking information through online sources. However, for women to trust these sources, medical experts have to be involved in developing the systems.

conclusionThrough expert systems diagnosis of pregnancy complications and recommendations from experts can be made available to pregnant women in Tanzania. In addition, self-care education during pregnancy will save women money and reduce hospital loads in Tanzania.

Indexed as

Maternal MortalityPregnant PeopleDelivery, ObstetricFemaleHumansPregnancyPrenatal CareSurveys and QuestionnairesTanzaniaantenatal careexpert systemsknowledge-seeking behaviormaternal mortalitypregnancyself-care

Identifiers

PMID34387125
PMCPMC8369856

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.