micro-Stress EMA: A Passive Sensing Framework for Detecting in-the-wild Stress in Pregnant Mothers.


Journal

Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies
ISSN: 2474-9567
Titre abrégé: Proc ACM Interact Mob Wearable Ubiquitous Technol
Pays: United States
ID NLM: 101719413

Informations de publication

Date de publication:
Sep 2019
Historique:
entrez: 21 5 2020
pubmed: 21 5 2020
medline: 21 5 2020
Statut: ppublish

Résumé

High levels of stress during pregnancy increase the chances of having a premature or low-birthweight baby. Perceived self-reported stress does not often capture or align with the physiological and behavioral response. But what if there was a self-report measure that could better capture the physiological response? Current perceived stress self-report assessments require users to answer multi-item scales at different time points of the day. Reducing it to one question, using microinteraction-based ecological momentary assessment (micro-EMA, collecting a single

Identifiants

pubmed: 32432212
doi: 10.1145/3351249
pmc: PMC7236910
mid: NIHMS1575327
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : NIDDK NIH HHS
ID : K25 DK113242
Pays : United States

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Auteurs

Zachary D King (ZD)

Northwestern University, United States.

Judith Moskowitz (J)

Northwestern University, United States.

Begum Egilmez (B)

Northwestern University, United States.

Shibo Zhang (S)

Northwestern University, United States.

Lida Zhang (L)

Northwestern University, United States.

Michael Bass (M)

Northwestern University, United States.

John Rogers (J)

Northwestern University, United States.

Roozbeh Ghaffari (R)

Northwestern University, United States.

Laurie Wakschlag (L)

Northwestern University, United States.

Nabil Alshurafa (N)

Northwestern University, United States.

Classifications MeSH