Evidence map›Paper›PMID 38864987›Full record

ReviewMaternal and child health journal2024

Maternal Health Literacy in Pregnant Women: A Concept Analysis.

Anggie Pradana Putri, Yu Ying Lu

Abstract readReview
PubMed Publisher
In one paragraph

Review in Maternal and child health journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
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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

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

2 authors.

Anggie Pradana PutriSchool of Nursing, Mamba'ul 'Ulum Health College of Surakarta, Global Lubna Jaya Co, Ring Road Utara KM 0.3 Mojosongo, Jebres, Founder, Sukoharjo, Surakarta, Indonesia.
Yu Ying LuDepartment of Nursing, National Taipei University of Nursing and Health Sciences, No.365, Ming-De Road, Peitou District, Taipei City, 11219, Taiwan. yuyin@ntunhs.edu.tw.ORCID http://orcid.org/0000-0001-5223-6187

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesMaternal health literacy (MHL) plays a vital role in pregnancy outcomes, healthcare researchers should further analyze, refine, and develop this concept. This study aims to clarify the definition of MHL in pregnant women through a analysis of the concept.

methodsWalker and Avant's concept analysis approach was used to analyze the concept of MHL. A search of the literature was completed using the databases PubMed, CINAHL, Web of Science (WOS), and the Science and Technology Index (SINTA) for years 2001-2021; literature search included grey literature, publications from the government and academic institutions, and available both in English and Indonesia. A total of 12 articles were reviewed.

resultsMHL is a multifaceted and comprehensive concept. This study presents a working definition of MHL during pregnancy as the skills enabling women to access, comprehend, evaluate, and apply health information related to pregnancy, which are necessary for making decisions for improving and maintaining both maternal and fetal health. Guided by Walker and Avant's method, the major attributes and outcomes are determined in this study.

conclusionHealthcare professionals can utilize this analysis to familiarize their institutions with the MHL concept, emphasize its importance, and apply it to practice. This contributes to enhancing the body of knowledge on MHL and potentially improving maternal health outcomes.

Indexed as

Health LiteracyPregnant PeopleAdultConcept FormationFemaleHealth Knowledge, Attitudes, PracticeHumansIndonesiaMaternal HealthPregnancyContent analysisMaternal health literayPreganat women

Identifiers

What OpenQuestion holds

Textmetadata
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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.