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The Association Between the Use of Antenatal Care Smartphone Apps in Pregnant Women and Antenatal Depression: Cross-Sectional Study

Authors :
Mo, Yushi
Gong, Wenjie
Wang, Joyce
Sheng, Xiaoqi
Xu, Dong R
Source :
JMIR mHealth and uHealth, Vol 6, Iss 11, p e11508 (2018)
Publication Year :
2018
Publisher :
JMIR Publications, 2018.

Abstract

BackgroundAntenatal care smartphone apps are increasingly used by pregnant women, but studies on their use and impact are scarce. ObjectiveThis study investigates the use of antenatal care apps in pregnant women and explores the association between the use of these apps and antenatal depression. MethodsThis study used a convenient sample of pregnant women recruited from Hunan Provincial Maternal and Child Health Hospital in November 2015. The participants were surveyed for their demographic characteristics, use of antenatal care apps, and antenatal depression. Factors that influenced antenatal pregnancy were analyzed using logistic regression. ResultsOf the 1304 pregnant women, 71.31% (930/1304) used antenatal care apps. Higher usage of apps was associated with urban residency, nonmigrant status, first pregnancy, planned pregnancy, having no previous children, and opportunity to communicate with peer pregnant women. The cutoff score of the Edinburgh Postnatal Depression Scale was 10, and 46.11% (601/1304) of the pregnant women had depression. Logistic regression showed that depression was associated with the availability of disease-screening functions in the apps (odds ratio (OR) 1.78, 95% CI 1.03-3.06) and spending 30 minutes or more using the app (OR 2.05, 95% CI 1.19-3.52). Using apps with social media features was a protective factor for antenatal depression (OR 0.33, 95% CI 0.12-0.89). ConclusionsThe prevalence of the use of prenatal care apps in pregnant women is high. The functions and time spent on these apps are associated with the incidence of antenatal depression.

Details

Language :
English
ISSN :
22915222
Volume :
6
Issue :
11
Database :
Directory of Open Access Journals
Journal :
JMIR mHealth and uHealth
Publication Type :
Academic Journal
Accession number :
edsdoj.1a783e17368d4794acf0c7ae2329f8a2
Document Type :
article
Full Text :
https://doi.org/10.2196/11508