The Effortless Assessment of Risk States (EARS) Tool: An Interpersonal Approach to Mobile Sensing

JMIR Mental Health
Monika N LindNicholas B Allen

Abstract

To predict and prevent mental health crises, we must develop new approaches that can provide a dramatic advance in the effectiveness, timeliness, and scalability of our interventions. However, current methods of predicting mental health crises (eg, clinical monitoring, screening) usually fail on most, if not all, of these criteria. Luckily for us, 77% of Americans carry with them an unprecedented opportunity to detect risk states and provide precise life-saving interventions. Smartphones present an opportunity to empower individuals to leverage the data they generate through their normal phone use to predict and prevent mental health crises. To facilitate the collection of high-quality, passive mobile sensing data, we built the Effortless Assessment of Risk States (EARS) tool to enable the generation of predictive machine learning algorithms to solve previously intractable problems and identify risk states before they become crises. The EARS tool captures multiple indices of a person's social and affective behavior via their naturalistic use of a smartphone. Although other mobile data collection tools exist, the EARS tool places a unique emphasis on capturing the content as well as the form of social communication on the phone....Continue Reading

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Citations

Jan 18, 2020·Journal of Child Psychology and Psychiatry, and Allied Disciplines·Candice L Odgers, Michaeline R Jensen
Feb 6, 2020·Journal of Medical Internet Research·Nastasia GriffioenIsabela Granic
Sep 4, 2020·Expert Review of Neurotherapeutics·Patricia A RichardsonLaura E Simons

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Software Mentioned

RADAR
Beiwe
Purple
iOS
Robot
EARS
Apache
Funf
Google Fit
CNS

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