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


Journal

NPJ digital medicine
ISSN: 2398-6352
Titre abrégé: NPJ Digit Med
Pays: England
ID NLM: 101731738

Informations de publication

Date de publication:
30 Mar 2022
Historique:
received: 13 07 2021
accepted: 23 02 2022
entrez: 31 3 2022
pubmed: 1 4 2022
medline: 1 4 2022
Statut: epublish

Résumé

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.

Identifiants

pubmed: 35354895
doi: 10.1038/s41746-022-00579-9
pii: 10.1038/s41746-022-00579-9
pmc: PMC8967890
doi:

Types de publication

Journal Article Review

Langues

eng

Pagination

40

Informations de copyright

© 2022. The Author(s).

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Auteurs

S M Goodday (SM)

4YouandMe, Seattle, WA, USA. sarah@4youandme.org.
Department of Psychiatry, University of Oxford, Oxford, UK. sarah@4youandme.org.

E Karlin (E)

4YouandMe, Seattle, WA, USA.

A Brooks (A)

4YouandMe, Seattle, WA, USA.

C Chapman (C)

4YouandMe, Seattle, WA, USA.

D R Karlin (DR)

4YouandMe, Seattle, WA, USA.
MindMed, Inc., New York, NY, USA.
Tufts University School of Medicine, Boston, MA, USA.

L Foschini (L)

Evidation Health Inc., Santa Mateo, CA, USA.

E Kipping (E)

Evidation Health Inc., Santa Mateo, CA, USA.

M Wildman (M)

Evidation Health Inc., Santa Mateo, CA, USA.

M Francis (M)

Sema4, Stamford, CT, USA.

H Greenman (H)

Sema4, Stamford, CT, USA.

Li Li (L)

Sema4, Stamford, CT, USA.

E Schadt (E)

Sema4, Stamford, CT, USA.

M Ghassemi (M)

Institute for Medical Engineering and Science, MIT, Cambridge, MA, USA.
Department of Electrical Engineering and Computer Science, MIT, Cambridge, MA, USA.
Vector Institute, CIFAR AI Chair, Toronto, Canada.

A Goldenberg (A)

Vector Institute, CIFAR AI Chair, Toronto, Canada.
SickKids Research Institute, Department of Computer Science, University of Toronto, Toronto, Canada.

F Cormack (F)

Cambridge Cognition, Cambridge, GB, USA.
Department of Psychiatry, University of Cambridge, Cambridge, GB, USA.

N Taptiklis (N)

Cambridge Cognition, Cambridge, GB, USA.

C Centen (C)

Bodyport Inc., San Francisco, CA, USA.

S Smith (S)

Bodyport Inc., San Francisco, CA, USA.

S Friend (S)

4YouandMe, Seattle, WA, USA.
Department of Psychiatry, University of Oxford, Oxford, UK.

Classifications MeSH