Identifying the Characteristics of Technology-Based Educational Interventions and Their Impact on Mothers' Breastfeeding Self-Efficacy

This review aims to identify the features of technology-based educational interventions and their effects on breastfeeding self-efficacy among mothers. Peer-reviewed articles published in Persian and English between 2015 and 2024 were collected. Various types of studies, including clinical trials, descriptive studies, mixed-methods research, and quasi-experimental studies (with or without blinding), were included. Databases such as Google Scholar, ScienceDirect, PubMed, Scopus, and domestic (Iranian) databases were searched using keywords like "breastfeeding," "educational technology," and "nursing mother." Out of 2,233 initially retrieved articles, 20 met the inclusion criteria, involving a total of 2,719 participants. Key variables examined included the type of technology used, delivery methods, and measured outcomes. The primary outcome assessed was mothers' breastfeeding self-efficacy, with major variables being intervention duration and breastfeeding self-efficacy. The findings indicate that interventions combining education with ongoing maternal support are the most effective technology-based approaches. While such interventions were widely implemented through mobile applications, maternal support was more prominent in interventions delivered via social networks and telephone follow-ups.

Institutions

Publication Details

Journal
The Journal of Telemedicine
Published
2025-06-30
DOI
https://doi.org/10.32592/tjt.2025.2.2.7
Primary Topic
Breastfeeding Practices and Influences
Type
article
Field-Weighted Citation Impact
0.00

Funders

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

Identifying the Characteristics of Technology-Based Educational Interventions and Their Impact on Mothers' Breastfeeding Self-Efficacy

The Journal of Telemedicine
Breastfeeding Practices and Influences
article

Identifying the Characteristics of Technology-Based Educational Interventions and Their Impact on Mothers' Breastfeeding Self-Efficacy

article en

Abstract

This review aims to identify the features of technology-based educational interventions and their effects on breastfeeding self-efficacy among mothers. Peer-reviewed articles published in Persian and English between 2015 and 2024 were collected. Various types of studies, including clinical trials, descriptive studies, mixed-methods research, and quasi-experimental studies (with or without blinding), were included. Databases such as Google Scholar, ScienceDirect, PubMed, Scopus, and domestic (Iranian) databases were searched using keywords like "breastfeeding," "educational technology," and "nursing mother." Out of 2,233 initially retrieved articles, 20 met the inclusion criteria, involving a total of 2,719 participants. Key variables examined included the type of technology used, delivery methods, and measured outcomes. The primary outcome assessed was mothers' breastfeeding self-efficacy, with major variables being intervention duration and breastfeeding self-efficacy. The findings indicate that interventions combining education with ongoing maternal support are the most effective technology-based approaches. While such interventions were widely implemented through mobile applications, maternal support was more prominent in interventions delivered via social networks and telephone follow-ups.

The Journal of Telemedicine
Isfahan University of Medical Sciences (IR), Ahvaz Jundishapur University of Medical Sciences (IR), Health Information Management (BE)
Ahvaz Jundishapur University of Medical Sciences
Openalex Percentile: Top 76%
Breastfeeding Practices and Influences
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.