Combining mobile-health (mHealth) and artificial intelligence (AI) methods to avoid suicide attempts: the Smartcrises study protocol
Open accessAbstract
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. TRIAL REGISTRATION NUMBER: NCT03720730. Retrospectively registered.
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- Authors
- Berrouiguet, S., Barrigón, M. L., Castroman, J. L., Courtet, P., Artés-Rodríguez, A., & Baca-García, E.
- Affiliations
- Université de Bretagne Occidentale (FR)
- Inserm (FR)
- Corresponding author
- Berrouiguet, Sofian
- Venue
- BMC Psychiatry
- Published
- 2019-09-07
- Volume
- 19
- Issue
- 1
- Pages
- 277-277
- ISSN
- 1471-244X (ISSN-L)
- PMC
- PMC6731613
- OpenAlex
- W2971631057
- Cited by
- 84
- References
- 44
- Citations by year
- 2026: 7 · 2025: 14 · 2024: 15 · 2023: 8 · 2022: 9 · 2021: 16 · 2020: 14 · 2019: 1
- FWCI
- 11.29
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- BMC Psychiatry (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (publishedVersion)
- HAL (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- e-Archivo (Carlos III University of Madrid) (submittedVersion, cc-by-nc-nd)
- Hispana (submittedVersion)
- Biblos-e Archivo (Universidad Autónoma de Madrid) (submittedVersion, public-domain)
- Funders
- American Foundation for Suicide Prevention ((LSRG-1-005-16))
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Social Sciences › Psychology › Clinical Psychology › Suicide and Self-Harm Studies
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Keywords
- suicide risk, suicide prevention, digital footprint, smartphone sensors, wearable armband, ecological momentary assessment, sleep quality, appetite, suicidal ideation, machine learning, personalized prevention
- MeSH terms
- Smartphone, Ecological Momentary Assessment, Wearable Electronic Devices, Adult, Appetite, Artificial Intelligence, Female, France, Humans, Male, Surveys and Questionnaires, Research Design, Spain, Suicide, Attempted, Randomized Controlled Trials as Topic, Telemedicine, Polysomnography
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