Evidence map›Paper›PMID 39845668›Full record

ArticleFrontiers in public health2024

Impact of peer interaction on maternal health service utilization in rural northwest China.

Liuchun Xiang, Dan Li, Junhao Wu, Jun Chen, Jie Yang, Haisong Nie

Abstract read
In one paragraph

Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Liuchun XiangCenter for Experimental Economics in Education, Faculty of Education, Shaanxi Normal University, Xi'an, China.
Dan LiUnited Graduate School of Agricultural Science, Tokyo University of Agriculture and Technology, Tokyo, Japan.
Junhao WuCenter for Experimental Economics in Education, Faculty of Education, Shaanxi Normal University, Xi'an, China.
Jun ChenCenter for Experimental Economics in Education, Faculty of Education, Shaanxi Normal University, Xi'an, China.
Jie YangCenter for Experimental Economics in Education, Faculty of Education, Shaanxi Normal University, Xi'an, China.
Haisong NieInstitute of Agriculture, Tokyo University of Agriculture and Technology, Tokyo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Effective use of health services by pregnant and postpartum woman (PPWs) is crucial to maternal and child health. Most maternal deaths are attributed to inadequate maternal health services, especially in rural areas. As a vulnerable group, rural PPWs can effectively prevent and reduce maternal and infant health risk factors through whole-process health management and ensure the health and safety of mothers and infants. Therefore, improving the utilization rate of rural maternal health services is a key issue that needs to be addressed urgently. This study aimed to explore the influence of peer interaction on the utilization of maternal health services in rural areas and the mediating effect of maternal health service knowledge. Methods: Based on cross-sectional data of 821 PPWs in rural northwest China. This study used propensity score matching (PSM) to analyze the effects of peer interaction (PI) on maternal health service utilization, including maternal system management rate (Y1), prenatal screening rate (Y2), and postpartum visit rate (Y3). In addition, the mediating role of maternal health service knowledge between peer interaction and health service utilization was empirically tested. Results: The findings highlight the important role of peer interaction in improving the utilization rate of maternal health services in rural northwest China. The study found that peer interaction significantly improved the maternal system management rate, prenatal screening rate, and postpartum visit rate. At the same time, peer interaction enhances knowledge of maternal health services, which plays a key role in improving maternal health behaviors. Conclusion: Through experience sharing and knowledge exchange among peers, understanding of health services can be enhanced, and positive health behaviors can be promoted. Policymakers and healthcare providers should integrate peer support programs into existing maternal health initiatives and fully use social media and community resources to create interactive platforms for maternal and infant knowledge that combine online and offline. By actively promoting peer interaction and experience sharing, these initiatives can maximize the positive role of peer support, increase the utilization rate of health services, and effectively ensure their safety.

Indexed as

Maternal Health ServicesPatient Acceptance of Health CarePeer GroupRural PopulationAdultChinaCross-Sectional StudiesFemaleHumansPregnancymaternal health servicepeer interactionpregnant and postpartum womenpropensity score matchingrural area

Identifiers

PMID39845668
PMCPMC11751063

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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.