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坚持数字孕期护理——从SMART start可行性研究中汲取的经验教训。

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

作者信息

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

机构信息

Machine Learning and Data Analytics Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.

Ambient Assisted Living & Medical Assistance Systems, Department of Computer Science, University of Bayreuth, Bayreuth, Germany.

出版信息

NPJ Digit Med. 2025 Aug 30;8(1):561. doi: 10.1038/s41746-025-01966-8.

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.

摘要

世界卫生组织日益强调数字健康技术在支持产前护理方面的作用。尽管有这种潜力,但此类技术在现实世界中的应用仍然有限,即使在拥有成熟传统系统的高收入国家也是如此。我们开发了一个全面的数字孕期护理框架SMART Start,并在一项涉及德国528名孕妇的前瞻性研究中对其进行了评估。该研究已在德国临床试验注册中心(DRKS00036867)注册。参与者配备了移动应用程序和自我检查技术。移动应用程序具有研究功能、与怀孕相关的问卷、数字产妇记录以及支持怀孕的内容。自我检查技术包括用于在家测量常规产前护理参数(体重、血压、尿液分析)的标准护理套件,以及带有新型传感器的创新套件(智能手表、睡眠分析仪)。在此,我们分析了对数字孕期护理的依从性,并从临床和技术角度介绍了所吸取的经验教训。在所有参与者中,49%的人使用了至少一个数字套餐。在最初的14周内,每周体重跟踪的依从率高达67%。血压和尿液分析测量的依从性较低,分别在20%和28%时达到峰值,但随时间保持稳定。问卷完成率因问卷长度和复杂性而异。31%的用户在注册时退出。虽然总体保留时间在各参与者亚组之间没有显著差异(所有p>0.05),但依从性分析显示,在参与特定自我检查方案方面存在有意义的组间差异。这种差异强调,持续参与并不一定意味着始终如一地参与数字护理模式的所有组成部分。对研究计划的依从性表明,孕妇通常愿意并能够参与基于家庭的多模式自我监测;然而,未来的研究应解决适应性安排、以患者为中心的反馈、敏捷开发和跨学科合作的重要性。所提出的SMART Start框架提供了一条通往数据驱动、个性化孕期护理的途径,同时有可能减少对传统医疗基础设施的需求。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f233/12398578/0fd1ae30351c/41746_2025_1966_Fig1_HTML.jpg

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