Adherence to digital pregnancy care – lessons learned from the SMART start feasibility study

The World Health Organization increasingly highlights the role of digital health technologies in supporting prenatal care. Despite this potential, the real-world implementation of such technologies remains limited, even in high-income countries with established analog systems. We developed a comprehensive digital pregnancy care framework, SMART Start and evaluated it in a prospective study involving 528 pregnant individuals in Germany. This study is registered at the German Clinical Trials Register (DRKS00036867). Participants were equipped with a mobile app and self-examination technologies. The mobile app featured study functionality, pregnancy-related questionnaires, digital maternity records, and pregnancy-supportive content. Self-examination technologies included a standard care kit for home measurements of routine prenatal care parameters (weight, blood pressure, urinalysis), and an innovative kit with novel sensors (smartwatch, sleep analyzer). Here, we analyzed the adherence to digital pregnancy care and present the lessons learned from a clinical and technical perspective. Among all participants, 49% engaged with at least one digital package. Weekly weight tracking reached adherence rates up to 67% in the first 14 weeks. Adherence to blood pressure and urinalysis measurements was lower, peaking at 20 and 28%, respectively, but remained stable over time. Questionnaire completion rates varied in dependence on their length and complexity. 31% of users disengaged at the time of registration. While overall retention time did not significantly differ across participant subgroups (all p > 0.05), adherence analyses revealed meaningful group-level differences in engagement with specific self-examination protocols. This discrepancy underscores that continued participation does not necessarily imply consistent engagement with all components of the digital care model. The adherence to the study schedule demonstrated that pregnant individuals are generally willing and capable of engaging in home-based, multimodal self-monitoring; however, the importance of adaptive scheduling, patient-centered feedback, agile development, and interdisciplinary collaboration should be addressed by future studies. The presented SMART Start framework offers a pathway towards data-driven, personalized pregnancy care while potentially reducing the demand for conventional healthcare infrastructure.

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Publication Details

Journal
npj Digital Medicine
Published
2025-08-30
DOI
https://doi.org/10.1038/s41746-025-01966-8
Citations
4
Primary Topic
Mobile Health and mHealth Applications
Type
article
Field-Weighted Citation Impact
11.26

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article

Adherence to digital pregnancy care – lessons learned from the SMART start feasibility study

Constanza Pontones, Patrick Ziegler, Hanna Huebner, Matthias Braun et al.
4 citations
npj Digital Medicine
Mobile Health and mHealth Applications
11.26
article

Adherence to digital pregnancy care – lessons learned from the SMART start feasibility study

Constanza Pontones, Patrick Ziegler, Hanna Huebner, Matthias Braun, Bjoern M. Eskofier, Michael Nissen, Katharina Jäger, Heike Leutheuser, Nina Danzberger, Hannah Bleher, Lothar Haeberle, Sabrina Uhrig, Kristina Kast, Chloë Goossens, Adriana Titzmann, Johannes Kornhuber, Matthias W. Beckmann, Peter A. Fasching, Oliver Schoeffski
article en
4 citations

Abstract

The World Health Organization increasingly highlights the role of digital health technologies in supporting prenatal care. Despite this potential, the real-world implementation of such technologies remains limited, even in high-income countries with established analog systems. We developed a comprehensive digital pregnancy care framework, SMART Start and evaluated it in a prospective study involving 528 pregnant individuals in Germany. This study is registered at the German Clinical Trials Register (DRKS00036867). Participants were equipped with a mobile app and self-examination technologies. The mobile app featured study functionality, pregnancy-related questionnaires, digital maternity records, and pregnancy-supportive content. Self-examination technologies included a standard care kit for home measurements of routine prenatal care parameters (weight, blood pressure, urinalysis), and an innovative kit with novel sensors (smartwatch, sleep analyzer). Here, we analyzed the adherence to digital pregnancy care and present the lessons learned from a clinical and technical perspective. Among all participants, 49% engaged with at least one digital package. Weekly weight tracking reached adherence rates up to 67% in the first 14 weeks. Adherence to blood pressure and urinalysis measurements was lower, peaking at 20 and 28%, respectively, but remained stable over time. Questionnaire completion rates varied in dependence on their length and complexity. 31% of users disengaged at the time of registration. While overall retention time did not significantly differ across participant subgroups (all p > 0.05), adherence analyses revealed meaningful group-level differences in engagement with specific self-examination protocols. This discrepancy underscores that continued participation does not necessarily imply consistent engagement with all components of the digital care model. The adherence to the study schedule demonstrated that pregnant individuals are generally willing and capable of engaging in home-based, multimodal self-monitoring; however, the importance of adaptive scheduling, patient-centered feedback, agile development, and interdisciplinary collaboration should be addressed by future studies. The presented SMART Start framework offers a pathway towards data-driven, personalized pregnancy care while potentially reducing the demand for conventional healthcare infrastructure.

npj Digital MedicineVol. 8(1)
University of Bonn (DE), Friedrich-Alexander-Universität Erlangen-Nürnberg (DE), Bayreuth Medical Center (DE), Helmholtz Zentrum München (DE), Universitätsklinikum Erlangen (DE), University of Bayreuth (DE)
Bundesministerium für Gesundheit
Openalex Percentile: Top 2%
Mobile Health and mHealth Applications
11.26
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