Evidence map›Paper›PMID 40211370›Full record

ArticlePilot and feasibility studies2025

Development and testing of mobile phone text messages for improving maternal and newborn care practice in Jimma Zone, Ethiopia: a user-centered design approach.

Hordofa Gutema Abdissa, Gebeyehu Bulcha Duguma, Josef Noll, Demisew Amenu Sori, Zewdie Birhanu Koricha

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Article in Pilot and feasibility studies, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Hordofa Gutema AbdissaDepartment of Health, Behavior and Society, Faculty of Public Health, Institutes of Health, Jimma University, Jimma, Ethiopia. pthordeg@gmail.com.ORCID http://orcid.org/0000-0001-5282-1271
Gebeyehu Bulcha DugumaDepartment of Health, Behavior and Society, Faculty of Public Health, Institutes of Health, Jimma University, Jimma, Ethiopia.
Josef NollDepartment of Technology Systems, University of Oslo, Oslo, Norway.
Demisew Amenu SoriDepartment of Obstetrics and Gynecology, Faculty of Medicine, Institutes of Health, Jimma University, Jimma, Ethiopia.
Zewdie Birhanu KorichaDepartment of Health, Behavior and Society, Faculty of Public Health, Institutes of Health, Jimma University, Jimma, Ethiopia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMobile phone-based messaging for maternal education has indicated promising outcomes in promoting maternal and newborn care practices. However, most mobile phone-based messaging interventions are not tested before their implementation, and the evidence on the message content development process and methods is limited and underreported. The aim of this study was to develop and test text messages for interventions designed to improve maternal services utilization and newborn care practices.

methodsThe development process has 4 phases: engaging pregnant mothers and experts in selected districts of the Jimma Zone, Ethiopia. During phase 1, the draft messages were developed based on the message framing concept, and the number of messages was reduced after review. In phase 2, 12 mothers participated in card sorting and the messages were refined. In phase 3, 8 experts evaluated the messages using 10 items with a 5-point Likert scale. In phase 4, a pilot study (n = 30) was conducted to evaluate the messages and their delivery when they were sent to individuals' mobile telephones. In this phase, a system usability scale was also used to assess the usability of the planned intervention.

resultsAn initial bank of 120 messages was developed, 42 of which were discarded during the development process. Of these, 32 were discarded by the research team at phase 1, and 10 were discarded during the card sorting at phase 2. Based on the experts' evaluations, 14 messages were reworded and refined in phase 3. During the pilot testing phase, the majority (80%) of the participants mentioned that the time they had been receiving the message was early, and 66.7% of the participants preferred the time to receive text messages about health. The mean SUS score was 72.26, which is acceptable for the usability of the mobile phone-based messaging intervention.

conclusionA final bank of 78 (39 for each framing type) messages was obtained after refinement according to feedback from participants. The SUS showed an acceptable score for the planned intervention. This message development process confirms that the messages are acceptable, and important for improving maternal and newborn health care practices.

trial registrationPACTR202201753436676.

Indexed as

Development processMaternal healthNewborn careText messageUser-centered design

Identifiers

PMID40211370
PMCPMC11983728

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LicenceCC BY-NC-ND
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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.