Application of a mobile health platform for assessing cognition and psychiatric symptoms in Veterans

自杀对退伍军人来说是一个致命的问题。预测和预防自杀的一个主要挑战是， 自杀行为随着时间的推移而波动，就像之前的认知，情感和身体状态一样。 移动的医疗技术的最新进展有望深入测量自杀的风险因素， 是接近的、随时间变化的，并且在使用智能手机的日常生活中自然发生。认知因素-包括 认知控制和社会认知-在自杀风险中发挥作用;然而，迄今为止，移动的健康工具还没有 被用来客观地衡量退伍军人的认知表现波动。为了弥补这一差距，我们 我建议使用我们以前开发的移动的健康工具来测量认知控制和社会认知 在自杀风险较高的退伍军人的日常生活中。利用我们提供移动的医疗服务的经验 在自杀风险的个人评估，我们将研究认知之间的动态关系， 表现和自杀，以及其他与自杀风险相关的背景变量。一种跨诊断 当前有自杀意念的退伍军人样本将完成同步移动的认知测试（MCT）， 生态瞬时评估（EMA），为期两周的密集评估。我们的目标是找出 认知测试表现和与自杀风险密切相关的结构（限制性应对）之间的关联 能力，消极的人际关系信念，思维）。我们还试图研究如何建立关系， 密集的移动的健康纵向数据集与现实世界的自杀结果有关，我们将从 电子病历和远程保健评估。我们将使用数据集来识别退伍军人的亚型 基于他们的自杀意念的时间模式，并检查亚型和现实世界之间的关联， 自杀的结果。最后，我们将探讨特定上下文变量的作用（例如，睡眠）的自杀风险。 该项目的可验证数据将包括一个密集的纵向数据集，该数据集克服了 传统的静态实验室评估。该数据集可用于评估额外的实时 自杀相关近端危险因素的纵向研究和干预性研究 自杀的基础

Suicide is a lethal problem for Veterans. A major challenge in predicting and preventing suicide is that ideation and suicide behaviors fluctuate over time, as do the cognitive, emotional, and physical states that precede them. Recent advances in mobile health technology hold promise for intensively measuring risk factors for suicide that are proximal, time-varying, and occur naturalistically in daily life using smartphones. Cognitive factors - including cognitive control and social cognition - play a role in suicide risk; to date, however, mobile health tools have not been adopted to objectively measure cognitive performance fluctuations in Veterans. To address this gap, we propose to use our previously developed mobile health tool for measuring cognitive control and social cognition in the daily lives of Veterans with elevated suicide risk. Drawing on our experience delivering mobile health assessments in individuals at-risk for suicide, we will examine the dynamic relationships between cognitive performance and suicide, as well as other contextual variables associated with suicide risk. A transdiagnostic sample of Veterans with current suicidal ideation will complete concurrent mobile cognitive tests (MCTs) and ecological momentary assessments (EMA) within a two-week intensive assessment. Our aims are to identify associations between cognitive test performance and constructs closely linked to suicide risk (restricted coping ability, negative interpersonal beliefs, ideation). We also seek to examine how relationships established in the intensive mobile health longitudinal dataset relate to real-world suicide outcomes which we will derive from the electronic medical record and telehealth assessments. We will use the dataset to identify subtypes of Veterans based on their temporal pattern of suicidal ideation and examine associations between subtypes and real-world suicide outcomes. Finally, we will explore the role of specific context variables (e.g., sleep) in suicide risk. Deliverables from this project will include an intensive longitudinal dataset that overcomes limitations of traditional static laboratory-based assessments. This dataset can be leveraged to assess additional real-time proximal risk factors associated with suicide in longitudinal studies and interventional research on the cognitive underpinnings of suicide.