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深入了解孕期变化(BUMP):一项针对从孕前到产后女性的数字可行性研究方案

Better Understanding of the Metamorphosis of Pregnancy (BUMP): protocol for a digital feasibility study in women from preconception to postpartum.

作者信息

Goodday S M, Karlin E, Brooks A, Chapman C, Karlin D R, Foschini L, Kipping E, Wildman M, Francis M, Greenman H, Li Li, Schadt E, Ghassemi M, Goldenberg A, Cormack F, Taptiklis N, Centen C, Smith S, Friend S

机构信息

4YouandMe, Seattle, WA, USA.

Department of Psychiatry, University of Oxford, Oxford, UK.

出版信息

NPJ Digit Med. 2022 Mar 30;5(1):40. doi: 10.1038/s41746-022-00579-9.

Abstract

The Better Understanding the Metamorphosis of Pregnancy (BUMP) study is a longitudinal feasibility study aimed to gain a deeper understanding of the pre-pregnancy and pregnancy symptom experience using digital tools. The present paper describes the protocol for the BUMP study. Over 1000 participants are being recruited through a patient provider-platform and through other channels in the United States (US). Participants in a preconception cohort (BUMP-C) are followed for 6 months, or until conception, while participants in a pregnancy cohort (BUMP) are followed into their fourth trimester. Participants are provided with a smart ring, a smartwatch (BUMP only), and a smart scale (BUMP only) alongside cohort-specific study apps. Participant centric engagement strategies are used that aim to co-design the digital approach with participants while providing knowledge and support. The BUMP study is intended to lay the foundational work for a larger study to determine whether participant co-designed digital tools can be used to detect, track and return multimodal symptoms during the perinatal window to inform individual level symptom trajectories.

摘要

更好地理解孕期变化(BUMP)研究是一项纵向可行性研究,旨在通过数字工具更深入地了解孕前和孕期症状体验。本文描述了BUMP研究的方案。目前正在通过患者提供者平台和美国的其他渠道招募1000多名参与者。对孕前队列(BUMP-C)的参与者进行为期6个月的跟踪,或直至怀孕,而对孕期队列(BUMP)的参与者则跟踪至孕晚期。除了特定队列的研究应用程序外,还为参与者提供智能戒指、智能手表(仅适用于BUMP)和智能体重秤(仅适用于BUMP)。采用以参与者为中心的参与策略,旨在与参与者共同设计数字方法,同时提供知识和支持。BUMP研究旨在为一项更大规模的研究奠定基础工作,以确定参与者共同设计的数字工具是否可用于在围产期窗口检测、跟踪和反馈多模式症状,从而了解个体水平的症状轨迹。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8bc3/8967890/dcea81d497b9/41746_2022_579_Fig1_HTML.jpg

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