Combining mobile-health (mHealth) and artificial intelligence (AI) methods to avoid suicide attempts: the Smartcrises study protocol
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...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2019-09-01
|
| Series: | BMC Psychiatry |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s12888-019-2260-y |
| _version_ | 1818483455562874880 |
|---|---|
| author | Sofian Berrouiguet María Luisa Barrigón Jorge Lopez Castroman Philippe Courtet Antonio Artés-Rodríguez Enrique Baca-García |
| author_facet | Sofian Berrouiguet María Luisa Barrigón Jorge Lopez Castroman Philippe Courtet Antonio Artés-Rodríguez Enrique Baca-García |
| author_sort | Sofian Berrouiguet |
| collection | DOAJ |
| description | 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. Trial registration number NCT03720730. Retrospectively registered. |
| first_indexed | 2024-12-10T15:42:12Z |
| format | Article |
| id | doaj.art-857b808905c04a6bb28fc1369b520978 |
| institution | Directory Open Access Journal |
| issn | 1471-244X |
| language | English |
| last_indexed | 2024-12-10T15:42:12Z |
| publishDate | 2019-09-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Psychiatry |
| spelling | doaj.art-857b808905c04a6bb28fc1369b5209782022-12-22T01:43:05ZengBMCBMC Psychiatry1471-244X2019-09-011911910.1186/s12888-019-2260-yCombining mobile-health (mHealth) and artificial intelligence (AI) methods to avoid suicide attempts: the Smartcrises study protocolSofian Berrouiguet0María Luisa Barrigón1Jorge Lopez Castroman2Philippe Courtet3Antonio Artés-Rodríguez4Enrique Baca-García5Department of Psychiatry and Emergency, Brest Medical University HospitalInserm U1061, La Colombières Hospital, University of MontpellierDepartment of Psychiatry, Autónoma UniversityInserm U1061, CAC University Hospital of NîmesDepartment of Psychiatry, Autónoma UniversityDepartment of Psychiatry, Autónoma UniversityAbstract 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.http://link.springer.com/article/10.1186/s12888-019-2260-ySuicideData miningSensorsSmartphoneWearables |
| spellingShingle | Sofian Berrouiguet María Luisa Barrigón Jorge Lopez Castroman Philippe Courtet Antonio Artés-Rodríguez Enrique Baca-García Combining mobile-health (mHealth) and artificial intelligence (AI) methods to avoid suicide attempts: the Smartcrises study protocol BMC Psychiatry Suicide Data mining Sensors Smartphone Wearables |
| title | Combining mobile-health (mHealth) and artificial intelligence (AI) methods to avoid suicide attempts: the Smartcrises study protocol |
| title_full | Combining mobile-health (mHealth) and artificial intelligence (AI) methods to avoid suicide attempts: the Smartcrises study protocol |
| title_fullStr | Combining mobile-health (mHealth) and artificial intelligence (AI) methods to avoid suicide attempts: the Smartcrises study protocol |
| title_full_unstemmed | Combining mobile-health (mHealth) and artificial intelligence (AI) methods to avoid suicide attempts: the Smartcrises study protocol |
| title_short | Combining mobile-health (mHealth) and artificial intelligence (AI) methods to avoid suicide attempts: the Smartcrises study protocol |
| title_sort | combining mobile health mhealth and artificial intelligence ai methods to avoid suicide attempts the smartcrises study protocol |
| topic | Suicide Data mining Sensors Smartphone Wearables |
| url | http://link.springer.com/article/10.1186/s12888-019-2260-y |
| work_keys_str_mv | AT sofianberrouiguet combiningmobilehealthmhealthandartificialintelligenceaimethodstoavoidsuicideattemptsthesmartcrisesstudyprotocol AT marialuisabarrigon combiningmobilehealthmhealthandartificialintelligenceaimethodstoavoidsuicideattemptsthesmartcrisesstudyprotocol AT jorgelopezcastroman combiningmobilehealthmhealthandartificialintelligenceaimethodstoavoidsuicideattemptsthesmartcrisesstudyprotocol AT philippecourtet combiningmobilehealthmhealthandartificialintelligenceaimethodstoavoidsuicideattemptsthesmartcrisesstudyprotocol AT antonioartesrodriguez combiningmobilehealthmhealthandartificialintelligenceaimethodstoavoidsuicideattemptsthesmartcrisesstudyprotocol AT enriquebacagarcia combiningmobilehealthmhealthandartificialintelligenceaimethodstoavoidsuicideattemptsthesmartcrisesstudyprotocol |