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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Sep 18, 2024
Open Peer Review Period: Sep 17, 2024 - Nov 12, 2024
Date Accepted: Feb 10, 2025
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Association of Digital Health Interventions With Maternal and Neonatal Outcomes: Systematic Review and Meta-Analysis

Wang J, Tang N, Jin C, Yang J, Zheng X, Jiang Q, Li S, Xiao N, Zhou X

Association of Digital Health Interventions With Maternal and Neonatal Outcomes: Systematic Review and Meta-Analysis

J Med Internet Res 2025;27:e66580

DOI: 10.2196/66580

PMID: 40085842

PMCID: 11953608

Association of digital health-based interventions with maternal and neonatal outcomes: A systematic review and meta-analysis.

  • Jianing Wang; 
  • Nu Tang; 
  • Congcong Jin; 
  • Jianxue Yang; 
  • Xiangpeng Zheng; 
  • Qiujing Jiang; 
  • Shengping Li; 
  • Nian Xiao; 
  • Xiaojun Zhou

ABSTRACT

Background:

Maternal and child health underpins the overall health of the population, and substantial evidence indicates that gestational weight gain is intrinsically connected to maternal and neonatal outcomes. The rapid growth and increasing use of digital health interventions, including telemedicine, telehealth, and mHealth, are considered accessible, applicable, and cost-effective. However, previous research into the effectiveness of technology-mediated interventions for promoting health outcomes has been inconclusive.

Objective:

This study investigated the effect of digital health interventions among pregnant women and newborns.

Methods:

Two independent researchers performed electronic literature searches in the PubMed, EMBASE, Web of Science, and Cochrane Library databases to identify eligible studies published from their inception until February 2024; an updated search was conducted in August 2024. The studies included randomized controlled trials (RCTs) related to maternal and neonatal clinical outcomes. The Revised Cochrane risk-of-bias tool for randomized trials (RoB2) was used to examine the risk of publication bias. Stata 15.1 was used to analyze the data.

Results:

We incorporated 42 pertinent randomized controlled trials involving 148,866 participants. In comparison to the routine care group, gestational weight gain is markedly reduced in the intervention group. (SMD = -0.145, 95% CI: -0.274 to -0.017, P = .027). A significant reduction was observed in the proportion of women with excessive weight gain (OR = 0.793, 95% CI: 0.693 to 0.907, P = .001), along with an increase in the proportion of women with adequate weight gain (OR = 1.334, 95% CI: 1.103 to 1.638, P = .003). Although no significant difference was reported for the proportion of individuals below standardized weight gain, there is a significant reduction in the risk of miscarriage (OR = 0.663, 95% CI: 0.462 to 0.951,P = .026), preterm birth(OR = 0.8, 95% CI: 0.746 to 0.858, P < .001) as well as complex neonatal outcomes(OR = 0.925, 95% CI: 0.866 to 0.988, P = .02). Other maternal and fetal outcomes were not significantly different between both groups.

Conclusions:

The findings corroborate our hypothesis that digitally facilitated healthcare can enhance certain facets of maternal and neonatal outcomes, particularly by mitigating excessive weight and maintaining individuals within a reasonable weight gain range. Therefore, encouraging women to join the digital health team sounds feasible and helpful. Clinical Trial: PROSPERO (CRD42024564331)


 Citation

Please cite as:

Wang J, Tang N, Jin C, Yang J, Zheng X, Jiang Q, Li S, Xiao N, Zhou X

Association of Digital Health Interventions With Maternal and Neonatal Outcomes: Systematic Review and Meta-Analysis

J Med Internet Res 2025;27:e66580

DOI: 10.2196/66580

PMID: 40085842

PMCID: 11953608

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