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

Authors :
Massachusetts Institute of Technology. Institute for Medical Engineering & Science
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Goodday, SM
Karlin, E
Brooks, A
Chapman, C
Karlin, DR
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
Massachusetts Institute of Technology. Institute for Medical Engineering & Science
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Goodday, SM
Karlin, E
Brooks, A
Chapman, C
Karlin, DR
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
Source :
Nature
Publication Year :
2022

Abstract

<jats:title>Abstract</jats:title><jats:p>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.</jats:p>

Details

Database :
OAIster
Journal :
Nature
Notes :
application/pdf, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1342474887
Document Type :
Electronic Resource