Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Meta-Analysis
. 2016 Aug 15;18(8):e220.
doi: 10.2196/jmir.6153.

Efficacy of Internet-Based Self-Monitoring Interventions on Maternal and Neonatal Outcomes in Perinatal Diabetic Women: A Systematic Review and Meta-Analysis

Ying Lau  1 , Tha Pyai Htun, Suei Nee Wong, Wai San Wilson Tam, Piyanee Klainin-Yobas
Affiliations
Meta-Analysis

Efficacy of Internet-Based Self-Monitoring Interventions on Maternal and Neonatal Outcomes in Perinatal Diabetic Women: A Systematic Review and Meta-Analysis

Ying Lau et al. J Med Internet Res. .

Abstract

Background: Self-monitoring using the Internet offers new opportunities to engage perinatal diabetic women in self-management to reduce maternal and neonatal complications.

Objective: This review aims to synthesize the best available evidence to evaluate the efficacy of Internet-based self-monitoring interventions in improving maternal and neonatal outcomes among perinatal diabetic women.

Methods: The review was conducted using Cochrane Central Register of Controlled Trials, PubMed, EMBASE, Cumulative Index to Nursing and Allied Health Literature, PsyINFO, Scopus, and ProQuest Dissertations and Theses to search for English-language research studies without any year limitation. A risk of bias table was used to assess methodological quality. Meta-analysis was performed with RevMan software. Cochran Q and I(2) tests were used to assess heterogeneity. The overall effect was assessed using z tests at P<.05. Of the 438 studies identified through electronic searches and reference lists, nine experimental studies from 10 publications were selected.

Results: Half of the selected studies showed low risk of bias and comprised 852 perinatal diabetic women in six countries. The meta-analysis revealed that Internet-based self-monitoring interventions significantly decreased the level of maternal glycated hemoglobin A1c (z=2.23, P=.03) compared to usual care among perinatal diabetic women at postintervention. Moreover, Internet-based self-monitoring interventions significantly decreased the cesarean delivery rate (z=2.23, P=.03) compared to usual care among the mixed group at postintervention.

Conclusions: This review shows neonatal or other maternal outcomes are similar between Internet-based self-monitoring interventions and usual diabetes care among perinatal diabetic women. The long-term effects of the intervention must be confirmed in future studies using randomized controlled trials and follow-up data.

Keywords: Internet; interventions; meta-analysis; pregnancy in diabetics.

PubMed Disclaimer

Conflict of interest statement

Conflicts of Interest: None declared.

Figures

Figure 1
Figure 1
PRISMA flow diagram of article selection procedure.
Figure 2
Figure 2
Risk of bias summary.
Figure 3
Figure 3
Forest plot of mean difference (95% CI) in change of HbA1c (%) for the Internet-based self-monitoring intervention and control groups. IV: inverse variance.
Figure 4
Figure 4
Forest plot of risk ratio in change of cesarean delivery rate for the Internet-based self-monitoring intervention and control groups.
Figure 5
Figure 5
Forest plot of mean difference (95% CI) in change of neonatal body weight (grams) for the Internet-based self-monitoring intervention and control groups. IV: inverse variance.
Figure 6
Figure 6
Forest plot of risk ratio for change in neonatal hypoglycemia rate for the Internet-based self-monitoring intervention and control groups.
See this image and copyright information in PMC

References

    1. Son KH, Lim N, Lee J, Cho M, Park H. Comparison of maternal morbidity and medical costs during pregnancy and delivery between patients with gestational diabetes and patients with pre-existing diabetes. Diabet Med. 2015 Apr;32(4):477–486. doi: 10.1111/dme.12656. http://europepmc.org/abstract/MED/25472691 - DOI - PMC - PubMed
    1. Feig DS, Hwee J, Shah BR, Booth GL, Bierman AS, Lipscombe LL. Trends in incidence of diabetes in pregnancy and serious perinatal outcomes: a large, population-based study in Ontario, Canada, 1996-2010. Diabetes Care. 2014 Jun;37(6):1590–1596. doi: 10.2337/dc13-2717.dc13-2717 - DOI - PubMed
    1. Balkhi AM, Reid AM, Westen SC, Olsen B, Janicke DM, Geffken GR. Telehealth interventions to reduce management complications in type 1 diabetes: A review. World J Diabetes. 2015 Apr 15;6(3):371–379. doi: 10.4239/wjd.v6.i3.371. http://www.wjgnet.com/1948-9358/full/v6/i3/371.htm - DOI - PMC - PubMed
    1. Wei Q, Sun Z, Yang Y, Yu H, Ding H, Wang S. Effect of a CGMS and SMBG on maternal and neonatal outcomes in gestational diabetes mellitus: a randomized controlled trial. Sci Rep. 2016;6:19920. doi: 10.1038/srep19920. doi: 10.1038/srep19920.srep19920 - DOI - DOI - PMC - PubMed
    1. Ramadas A, Quek KF, Chan CK, Oldenburg B. Web-based interventions for the management of type 2 diabetes mellitus: a systematic review of recent evidence. Int J Med Inform. 2011 Jun;80(6):389–405. doi: 10.1016/j.ijmedinf.2011.02.002.S1386-5056(11)00047-5 - DOI - PubMed