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孕产妇健康数字健康平台:设计、招募策略及从PowerMom观察性队列研究中获得的经验教训

Digital Health Platform for Maternal Health: Design, Recruitment Strategies, and Lessons Learned From the PowerMom Observational Cohort Study.

作者信息

Ajayi Toluwalase, Kueper Jacqueline, Ariniello Lauren, Ho Diana, Delgado Felipe, Beal Matthew, Waalen Jill, Baca Motes Katie, Ramos Edward

机构信息

Jacobs Center for Health Innovation, Department of Medicine and Pediatrics, University of California, San Diego, La Jolla, CA, United States.

Digital Trial Center, Scripps Research Translational Institute, La Jolla, CA, United States.

出版信息

JMIR Form Res. 2025 Apr 7;9:e70149. doi: 10.2196/70149.

Abstract

BACKGROUND

Maternal health research faces challenges in participant recruitment, retention, and data collection, particularly among underrepresented populations. Digital health platforms like PowerMom (Scripps Research) offer scalable solutions, enabling decentralized, real-world data collection. Using innovative recruitment and multimodal techniques, PowerMom engages diverse cohorts to gather longitudinal and episodic data during pregnancy and post partum.

OBJECTIVE

This study aimed to evaluate the design, implementation, and outcomes of the PowerMom research platform, with a focus on participant recruitment, engagement, and data collection across diverse populations. Secondary objectives included identifying challenges encountered during implementation and deriving lessons to inform future digital maternal health studies.

METHODS

Participants were recruited via digital advertisements, pregnancy apps, and the PowerMom Consortium of more than 15 local and national organizations. Data collection included self-reported surveys, wearable devices, and electronic health records. Anomaly detection measures were implemented to address fraudulent enrollment activity. Recruitment trends and descriptive statistics from survey data were analyzed to summarize participant characteristics, assess engagement metrics, and quantify missing data to identify gaps.

RESULTS

Overall, 5617 participants were enrolled from 2021 to 2024, with 69.8% (n=3922) providing demographic data. Of these, 48.5% (2723/5617) were younger than 35 years, 14% (788/5617) identified as Hispanic or Latina, and 13.7% (770/5617) identified as Black or African American. Geographic representation spanned all 50 US states, Puerto Rico, and Guam, with 58.3% (3276/5617) residing in areas with moderate access to maternity care and 16.4% (919/5617) in highly disadvantaged neighborhoods based on the Area Deprivation Index. Enrollment rates increased substantially over the study period, from 55 participants in late 2021 to 3310 in 2024, averaging 99.4 enrollments per week in 2024. Participants completed a total of 17,123 surveys, with 71.8% (4033/5617) completing the Intake Survey and 12.4% (697/5617) completing the Postpartum Survey. Wearable device data were shared by 1168 participants, providing more than 378,000 daily biometric measurements, including activity levels, sleep, and heart rate. Additionally, 96 participants connected their electronic health records, contributing 276 data points such as diagnoses, medications, and laboratory results. Among pregnancy-related characteristics, 28.1% (1578/5617) enrolled during the first trimester, while 15.1% (849/5617) reported information about the completion of their pregnancies during the study period. Among the 913 participants who shared delivery information, 56.1% (n=512) had spontaneous vaginal deliveries and 17.9% (n=163) underwent unplanned cesarean sections.

CONCLUSIONS

The PowerMom platform demonstrates the feasibility of using digital tools to recruit and engage diverse populations in maternal health research. Its ability to integrate multimodal data sources showcases its potential to provide comprehensive maternal-fetal health insights. Challenges with data completeness and survey attrition underscore the need for sustained participant engagement strategies. These findings offer valuable lessons for scaling digital health platforms and addressing disparities in maternal health research.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03085875; https://clinicaltrials.gov/study/NCT03085875.

摘要

背景

孕产妇健康研究在参与者招募、留存和数据收集方面面临挑战,在代表性不足的人群中尤为如此。像PowerMom(斯克里普斯研究所)这样的数字健康平台提供了可扩展的解决方案,能够实现分散式的真实世界数据收集。通过创新的招募和多模式技术,PowerMom吸引了不同的队列,以收集孕期和产后的纵向和偶发性数据。

目的

本研究旨在评估PowerMom研究平台的设计、实施和结果,重点关注不同人群中的参与者招募、参与度和数据收集。次要目标包括确定实施过程中遇到的挑战,并总结经验教训,为未来的数字孕产妇健康研究提供参考。

方法

通过数字广告、孕期应用程序以及由15个以上地方和国家组织组成的PowerMom联盟招募参与者。数据收集包括自我报告的调查、可穿戴设备和电子健康记录。实施了异常检测措施以应对欺诈性注册活动。分析调查数据的招募趋势和描述性统计数据,以总结参与者特征、评估参与度指标并量化缺失数据以识别差距。

结果

总体而言,2021年至2024年期间共招募了5617名参与者,其中69.8%(n = 3922)提供了人口统计学数据。在这些参与者中,48.5%(2723/5617)年龄小于35岁,14%(788/5617)为西班牙裔或拉丁裔,13.7%(770/5617)为黑人或非裔美国人。地理分布涵盖美国所有50个州、波多黎各和关岛,根据地区贫困指数,58.3%(3276/5617)居住在获得孕产妇保健服务便利程度中等的地区,16.4%(919/5617)居住在高度贫困社区。在研究期间,招募率大幅上升,从2021年末的55名参与者增加到2024年的3310名,2024年平均每周招募99.4名。参与者共完成了17123份调查,其中71.8%(4033/5617)完成了初始调查,12.4%(697/5617)完成了产后调查。1168名参与者分享了可穿戴设备数据,提供了超过378000条每日生物特征测量数据,包括活动水平、睡眠和心率。此外,96名参与者连接了他们的电子健康记录,提供了276个数据点,如诊断、药物治疗和实验室检查结果。在与怀孕相关的特征中,28.1%(1578/5617)在孕早期登记,而15.1%(849/5617)在研究期间报告了其怀孕结束的信息。在分享分娩信息的913名参与者中,56.1%(n = 512)为自然阴道分娩,17.9%(n = 163)接受了非计划剖宫产。

结论

PowerMom平台证明了使用数字工具在孕产妇健康研究中招募和吸引不同人群的可行性。其整合多模式数据源的能力展示了其提供全面母婴健康见解的潜力。数据完整性和调查损耗方面的挑战凸显了持续的参与者参与策略的必要性。这些发现为扩大数字健康平台规模和解决孕产妇健康研究中的差距提供了宝贵的经验教训。

试验注册

ClinicalTrials.gov NCT03085875;https://clinicaltrials.gov/study/NCT03085875

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