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. 2023 Apr 4:12:e45178.
doi: 10.2196/45178.

Effectiveness of the Internet of Things for Improving Working-Aged Women's Health in High-Income Countries: Protocol for a Systematic Review and Network Meta-analysis

Noyuri Yamaji  1 , Aya Nitamizu  1 , Etsuko Nishimura  1 , Daichi Suzuki  2 , Kiriko Sasayama  3 , Md Obaidur Rahman  4   5 , Eiko Saito  6 , Daisuke Yoneoka  4   7 , Erika Ota  1   7
Affiliations

Effectiveness of the Internet of Things for Improving Working-Aged Women's Health in High-Income Countries: Protocol for a Systematic Review and Network Meta-analysis

Noyuri Yamaji et al. JMIR Res Protoc. .

Abstract

Background: Women often experience many unique health issues and conditions throughout their working lives. The Internet of Things (IoT) is a system of interrelated digital devices that can enable data exchanges over a network without human-to-human or human-to-computer interaction. The usage of applications and IoT in improving women's health has recently increased worldwide. However, there has been no consensus on the effectiveness of IoT in improving women's health outcomes.

Objective: This systematic review and network meta-analysis (NMA) aims to assess and synthesize the role of apps and the IoT in improving women's health and to identify the ranking of interventions for ensuring better results for each stated outcome.

Methods: Our systematic review and NMA will be conducted in accordance with the guidelines of the Cochrane Handbook. We will comprehensively search the following electronic databases: PubMed (including MEDLINE), Cochrane Central Register of Controlled Trials, Embase, Cumulative Index to Nursing and Allied Health Literature (ie, CINAHL), PsycINFO, ClinicalTrials.gov, and the World Health Organization International Clinical Trials Registry, along with other resources to identify relevant randomized controlled trials that have assessed the effects of various apps and the IoT with regard to improving working-aged women's health in high-income countries. We will segment and analyze the results of the included studies based on age categories (women undergoing a preconception period, those undergoing gestational and postpartum periods, and menopausal and pre- and postmenopausal women) and the medical history (women who have a specific medical condition-eg, cancer or diabetes-and women who do not have them) separately. Two independent reviewers will perform the study selection, data extraction, and quality assessment. Our primary outcomes include health status, well-being, and quality of life. We will perform pairwise meta-analysis and NMA to estimate the direct, indirect, and relative effects of apps and the IoT on women's health outcomes. We will also assess the hierarchy of interventions, statistical inconsistencies, and certainties of evidence for each outcome.

Results: We plan to conduct the search in January 2023 and are currently discussing search strategies with the literature search specialists. The final report is planned for submission to a peer-reviewed journal in September 2023.

Conclusions: To the best of our knowledge, this review will be the first to identify the ranking of IoT intervention for ensuring working-aged women's health outcomes. These findings may be of great use to researchers, policy makers, and others with an interest in the field.

Trial registration: International Prospective Register of Systematic Reviews (PROSPERO) CRD42022384620; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=384620.

International registered report identifier (irrid): PRR1-10.2196/45178.

Keywords: Internet of Things; IoT; application; apps; digital health; health app; high income; mHealth; meta analyses; meta analysis; mobile health; network meta-analysis; review method; systematic review; women’s health.

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Conflict of interest statement

Conflicts of Interest: There are no conflicts of interest to declare. This work is supported by the Japan Agency for Medical Research and Development (22rea522103h0001).

Figures

Figure 1
Figure 1
Preferred Reporting Items for Systematic Reviews and Meta-Analyses flow diagram.
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