Publication: Combining mobile-health (mHealth) and artificial intelligence (AI) methods to avoid suicide attempts: The Smartcrises study protocol
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2019-09-07
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BioMed Central (BMC)
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Abstract
Background: The screening of digital footprint for clinical purposes relies on the capacity of wearable technologies
to collect data and extract relevant information’s for patient management. Artificial intelligence (AI) techniques
allow processing of real-time observational information and continuously learning from data to build
understanding. We designed a system able to get clinical sense from digital footprints based on the smartphone’s
native sensors and advanced machine learning and signal processing techniques in order to identify suicide risk.
Method/design: The Smartcrisis study is a cross-national comparative study. The study goal is to determine the
relationship between suicide risk and changes in sleep quality and disturbed appetite. Outpatients from the
Hospital Fundación Jiménez Díaz Psychiatry Department (Madrid, Spain) and the University Hospital of Nimes
(France) will be proposed to participate to the study. Two smartphone applications and a wearable armband will
be used to capture the data. In the intervention group, a smartphone application (MEmind) will allow for the
ecological momentary assessment (EMA) data capture related with sleep, appetite and suicide ideations.
Discussion: Some concerns regarding data security might be raised. Our system complies with the highest level of
security regarding patients’ data. Several important ethical considerations related to EMA method must also be
considered. EMA methods entails a non-negligible time commitment on behalf of the participants. EMA rely on
daily, or sometimes more frequent, Smartphone notifications. Furthermore, recording participants’ daily experiences
in a continuous manner is an integral part of EMA. This approach may be significantly more than asking a
participant to complete a retrospective questionnaire but also more accurate in terms of symptoms monitoring.
Overall, we believe that Smartcrises could participate to a paradigm shift from the traditional identification of risks
factors to personalized prevention strategies tailored to characteristics for each patient.
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Keywords
Data mining, Sensors, Smartphone, Suicide, Wearables
Bibliographic citation
BMC Psychiatry, (209), 19(1), 277.