Evidence map›Paper›PMID 38062456›Full record

ArticleReproductive health2023

Effectiveness of a breastfeeding promotion intervention model based on Society ecosystems Theory for maternal women: a study protocol of randomized controlled trial.

Yan-Qiong Ouyang, Jie Zhou, Jin-Yi Guo, Shi-Yun Wang, Xin Wang, Yi-Bei Zhou-Chen, Sharon R Redding, Hui-Jun Chen

Open access · goldAbstract readClinical Trial Protocol
In one paragraph

Article in Reproductive health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 18% of its field
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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Review
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

8 authors at 3 institutions in 2 countries.

Yan-Qiong OuyangSchool of Nursing, Wuhan University, 115 Donghu Road, Wuchang District, Wuhan, 430071, China.
Jie ZhouSchool of Nursing, Wuhan University, 115 Donghu Road, Wuchang District, Wuhan, 430071, China. zhoujie.2017@whu.edu.cn.
Jin-Yi GuoSchool of Nursing, Wuhan University, 115 Donghu Road, Wuchang District, Wuhan, 430071, China.
Shi-Yun WangSchool of Nursing, Wuhan University, 115 Donghu Road, Wuchang District, Wuhan, 430071, China.
Xin WangSchool of Nursing, Wuhan University, 115 Donghu Road, Wuchang District, Wuhan, 430071, China.
Yi-Bei Zhou-ChenSchool of Nursing, Wuhan University, 115 Donghu Road, Wuchang District, Wuhan, 430071, China.
Sharon R ReddingProject HOPE, Washington, DC, USA.
Hui-Jun ChenDepartment of Gynaecology and Obstetrics, Zhongnan Hospital of Wuhan University, 169 Donghu Road, Wuchang District, Wuhan, 430071, China. karrel@sina.com.
Wuhan Donghu University · CNWuhan University · CNProject HOPE · US

Funding

Humanities and Social Science Fund of Ministry of Education of China 22YJAZH085
6 · The paper itself

Abstract

backgroundBreastfeeding is recognized internationally as the most scientific and effective way to feed infants and young children. According to the World Health Organization in 2022, the exclusive breastfeeding rate within 6 months is 34.1% in China, which is still far from the goal of "more than 60% exclusive breastfeeding rate of infants within 6 months" by 2030 required by China's State Council. It is necessary to promote breastfeeding and provide maternal breastfeeding guidance to increase exclusive breastfeeding. Factors influencing breastfeeding can be explained by the society ecosystems theory, distributed in macro, mezzo and micro systems. The interventions focused on breastfeeding promotion are mainly carried out in the health systems and services, home and family environment, community environment, work environment, policy environment or a combination of these facilities. But there is sparse research on integrating resources in the macro, mezzo and micro systems of maternal breastfeeding processes to promote breastfeeding behavior. A randomized controlled trial will test the effect of a breastfeeding promotion intervention model based on the society ecosystems theory versus usual prenatal and postnatal care on maternal and infant health and the exclusive breastfeeding rate at 6 months. METHODS/

designThe study is a single-blind, parallel design, randomized controlled trial with an intervention group (n = 109) and a control group (n = 109) that compares the effect of a breastfeeding promotion intervention model based on the society ecosystems theory with usual prenatal and postnatal care. The intervention covers macro- (policy, culture), mezzo- (family-hospital-community) and micro- (biological, psychological and social) systems of the maternal breastfeeding process. Infant feeding patterns, neonatal morbidity and physical and mental health of antenatal and postpartum women will be collected at baseline (28 to 35 weeks of gestation), 1-, 4-, and 6-month postpartum. DISCUSSION: This is a multifaceted, multifactorial, and multi-environmental breastfeeding promotion strategy to help mothers and their families learn breastfeeding knowledge and skills. The study provides a new modality for adding breastfeeding interventions to prenatal and postnatal care for healthcare providers in the hospital and the community.

trial registrationChinese Clinical Trial Registry at www.chictr.org.cn , ChiCTR2300075795.

Indexed as

Breast FeedingHealth PromotionChildChild, PreschoolEcosystemFemaleHumansInfantInfant, NewbornMothersPregnancyRandomized Controlled Trials as TopicSingle-Blind MethodBreastfeedingNursingProtocolRandomized controlled trialSociety ecosystems theory

Identifiers

PMID38062456
PMCPMC10704786
OpenAlexW4389429869

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.