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Testing the ELSA Birth App During Pregnancy and Labor for Primiparous Women: Randomized Controlled Trial
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Health Sciences (from 2013). Region Värmland, Karlstad, Sweden.ORCID iD: 0000-0001-7729-7912
Uppsala University, Sweden; Akademiska University Hospital, Sweden.ORCID iD: 0000-0003-0766-9957
Oslo University Hospital, Norway; University of South-Eastern Norway, Norway.ORCID iD: 0000-0003-3897-7055
University of South-Eastern Norway, Norway.ORCID iD: 0000-0001-5257-7993
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2025 (English)In: Journal of Medical Internet Research, E-ISSN 1438-8871, Vol. 27, article id e72807Article in journal (Refereed) Published
Abstract [en]

Background: Early labor is often managed at home without professional support. The Birth App (Birth by Heart) is an app designed to support women during early labor. A pilot study revealed that women found the app’s exercises simple, understandable, and practical. The app was perceived as useful and appreciated by women, although areas for improvement were identified, primarily related to technical issues. After the development and test period, the updated app was tested in a randomized controlled trial.

Objective: This study aims to investigate whether women using the Birth App during pregnancy and childbirth experience less distress during early labor compared to those receiving standard antenatal care.

Methods: We used online recruiting in a nonblinded 3-part blended care model with 1:1:1 randomization: group 1 (Birth App intervention); group 2 (Birth App Plus, combining the app with in-person additional midwifery contacts); and group 3 (control group receiving standard antenatal care). Pregnant nulliparous women were invited via social media. Eligibility criteria were nulliparity, planning a vaginal birth, from gestational week 25+0 to 35+6 weeks, proficiency in understanding Swedish, and having access to a smartphone or tablet. Data were analyzed with descriptive statistics, chi-square tests, and ANOVA.

Results: A total of 391 women completed the baseline questionnaire and were included in the study (group 1, n=118; group 2, n=114; group 3, n=118). Of these, 335 women responded to the questionnaire 1 month postpartum, yielding a response rate of 85.6%. Most participants experienced a spontaneous onset of labor (group 1: 67/103, 65%; group 2: 81/114, 71%; and group 3: control group, 86/118, 73%), with no statistically significant differences between groups. During early labor, women in group 1 remained at home for a mean of 16.76 (SD 20.45) hours, group 2 for a mean of 14.47 (SD 16.82) hours, and the control group for a mean of 12.90 (SD 15.99) hours (P=.32). For the primary and secondary outcomes, only women with spontaneous onset of labor (n=234) were included in the analysis. The primary outcome, emotional distress, showed similar mean values across all groups. No statistically significant differences were identified in the secondary outcomes: childbirth experience, pain relief, and support from the partner. However, for the secondary outcome fear of future birth, a pairwise testing from baseline to follow-up revealed a statistically significant mean difference for the intervention groups (group 1: mean 13.53, 95% CI 5.12‐21.92, P=.002; group 2: mean 14.59, 95% CI 7.75‐21.42, P<.001) with a medium effect size (Cohen d=.40 vs d=.47). For group 3, the mean was 6.78 (95% CI −.95 to 14.53; P=.08).

Conclusions: The Birth App, in conjunction with additional midwifery support, can be a valuable tool for pregnant women and their partners during pregnancy and childbirth. The observed reduction in fear of forthcoming childbirth associated with the Birth App warrants further investigation.

Place, publisher, year, edition, pages
JMIR Publications, 2025. Vol. 27, article id e72807
Keywords [en]
fear of childbirth, mobile app, early labor, emotional distress, midwifery support, antenatal education, mHealth, childbirth experience, randomized controlled trial, mobile health
National Category
Gynaecology, Obstetrics and Reproductive Medicine Computer Sciences
Research subject
Nursing Science; Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-107366DOI: 10.2196/72807ISI: 001609266000001PubMedID: 41100814Scopus ID: 2-s2.0-105018967571OAI: oai:DiVA.org:kau-107366DiVA, id: diva2:2008672
Projects
DHINO - Digital hälsoinnovationDWA - DigitalWell Arena
Funder
Region Värmland, RUN/ 230445Knowledge FoundationEuropean Regional Development Fund (ERDF), 20365177Vinnova, 2018-03025Region Värmland, LIVFOU-969649Region Värmland, LIVFOU981145
Note

There is a correction to this article published under the DOI of 10.2196/86193. 

Available from: 2025-10-23 Created: 2025-10-23 Last updated: 2025-12-03Bibliographically approved

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Ängeby, KarinIwaya, Leonardo HNordin, Anna

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Ängeby, KarinJohansson, MargaretaBørøsund, ElinVarsi, CecilieIwaya, Leonardo HNordin, Anna
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