A Digital Companion, the Emma App, for Ecological Momentary Assessment and Prevention of Suicide: Quantitative Case Series Study.

Margot Morgiève; Catherine Genty; Jérôme Azé; Jonathan Dubois; Marion Leboyer; Guillaume Vaiva; Sofian Berrouiguet; Philippe Courtet

doi:10.2196/15741

Journal articles

A Digital Companion, the Emma App, for Ecological Momentary Assessment and Prevention of Suicide: Quantitative Case Series Study.

Margot Morgiève ¹ Catherine Genty ¹ Jérôme Azé ² Jonathan Dubois ¹ Marion Leboyer ³ Guillaume Vaiva ⁴ Sofian Berrouiguet ⁵ Philippe Courtet ^{1, 2}

1 CHU - Hôpital Lapeyronie [Montpellier]

2 ADVANSE - ADVanced Analytics for data SciencE

LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier

3 Hôpital Albert Chenevier

4 CHRU Lille - Centre Hospitalier Régional Universitaire [Lille]

5 SPURBO - Soins Primaires, Santé Publique, Registre des cancers de Bretagne Occidentale

Abstract : Many suicide risk factors have been identified, but traditional clinical methods do not allow for the accurate prediction of suicide behaviors. To face this challenge, emma, an app for ecological momentary assessment (EMA), ecological momentary intervention (EMI), and prediction of suicide risk in high-risk patients, was developed.

Keywords : case reports ecological momentary assessment ecological momentary intervention mHealth mobile health prediction prevention suicide

Document type :

Journal articles

Domain :

Computer Science [cs] / Machine Learning [cs.LG]

Complete list of metadata

https://hal-lirmm.ccsd.cnrs.fr/lirmm-03022244
Contributor : Jérôme Azé <>
Submitted on : Tuesday, November 24, 2020 - 4:54:18 PM
Last modification on : Thursday, November 26, 2020 - 3:21:49 AM
Long-term archiving on: : Thursday, February 25, 2021 - 8:50:23 PM

A Digital Companion, the Emma App, for Ecological Momentary Assessment and Prevention of Suicide: Quantitative Case Series Study.

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A Digital Companion, the Emma App, for Ecological Momentary Assessment and Prevention of Suicide: Quantitative Case Series Study.

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