Combining mobile-health (mHealth) and artificial intelligence (AI) methods to avoid suicide attempts: the Smartcrises study protocol
Combining mobile-health (mHealth) and artificial intelligence (AI) methods to avoid suicide attempts: the Smartcrises study protocol
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DOI：
10.1186/s12888-019-2260-y
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发表时间：
2019-09-07
期刊：
影响因子：
4.4
通讯作者：
Baca-Garcia, Enrique
中科院分区：
文献类型：
--
作者：
Berrouiguet, Sofian;Barrigon, Maria Luisa;Baca-Garcia, Enrique
临床目的的数字足迹筛选依赖于可穿戴技术收集数据和提取相关信息以供患者管理的能力。人工智能（AI）技术允许处理实时观测信息并不断从数据中学习以建立理解。我们设计了一个系统，能够基于智能手机的原生传感器和先进的机器学习和信号处理技术，从数字足迹中获得临床感知，以识别自杀风险。Smartcrisis研究是一项跨国比较研究。这项研究的目的是确定自杀风险与睡眠质量变化和食欲紊乱之间的关系。来自希门尼斯·迪亚兹医院精神科（西班牙马德里）和尼姆大学医院（法国）的门诊患者将被建议参加这项研究。两个智能手机应用程序和一个可穿戴臂带将用于捕获数据。在干预组中，智能手机应用程序（MEmind）将允许捕获与睡眠、食欲和自杀念头相关的生态瞬间评估（EMA）数据。讨论可能会提出一些关于数据安全的担忧。我们的系统符合患者数据的最高安全级别。还必须考虑与EMA方法相关的几个重要伦理考虑因素。EMA方法需要代表参与者承担不可忽略的时间承诺。EMA依赖于每天或有时更频繁的智能手机通知。此外，以持续的方式记录参与者的日常经历是EMA的一个组成部分。这种方法可能比要求参与者完成回顾性问卷要重要得多，但在症状监测方面也更准确。总体而言，我们认为Smartcrises可以参与从传统的风险因素识别到针对每个患者特征量身定制的个性化预防策略的范式转变。
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 Fundacion Jimenez Diaz 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.