Feasibility of Mobile Technology-Based Assessments of Community Reintegration in Homeless Veterans

退伍军人无家可归是一个全国性的危机，洛杉矶有最高的无家可归的退伍军人人口在 我们尽管在为退伍军人提供住房方面取得了令人印象深刻的进展，特别是通过HUD-VASH 然而，一个根本问题仍然存在：永久性住房是必要的第一步，但不是一个 为成功融入社会创造了充分条件。重新融入社区，定义为全面 参与工作、社交、独立生活和娱乐活动，并不是一次就自动产生的。 提供了外壳。尽管提供了住房，但累犯率（返回无家可归）仍然很高。此外，本发明还 对非VA样本的少数相关研究表明，在提供支持性住房后， (e.g.,职业和社会功能仍然很差）。HUD-VASH临床医生描述了类似的不良结局 在退伍军人，但几乎没有任何数据的类型，严重程度和原因的问题，在社区 重新融入最近安置的退伍军人（Rhev）。这些信息对于开发恢复至关重要- 可以在这个复杂的，快速增长的退伍军人群体中实施的集中治疗。 2015年，我们的团队建立了VA研究增强奖计划（REAP）， 洛杉矶无家可归退伍军人的社区融合。REAP致力于了解 重新融合问题的范围，确定其决定因素，并制定新的干预措施。我们有 在我们与RHV及其治疗提供者的工作中，确定了两个主要挑战。1.不足 措施：现有的社区融合措施缺乏必要的敏感性，无法确定 RHV所面临的挑战，而且还没有对RHV实际支出的细粒度评估 他们的时间2.参与率低：让生殖器病毒参与治疗和研究极为困难 需要反复去退伍军人管理局因此，我们的研究评估只提供了一个 整合的横截面快照，未能捕捉到他们生活中的动态波动。此外，委员会认为， 不利用现有的治疗服务会导致累犯和不良后果。因此我们 我认为有必要超越传统的评估和治疗方式来解决这些问题 挑战新的移动的技术似乎非常适合这一目的。 本提案的目的是评估通过移动的提供的数字表型分析（DP）的可行性 利用智能手机技术评估患有严重精神疾病的RHV的社区融合情况。我们 将使用主动（社会接触的生态瞬时评估[EMA]）和被动（全球 定位系统测量社区的流动性）DP指数。活跃的EMA指数涉及提示 参与者在一周内每天多次完成简短的调查， 生态有效的信息比传统的横截面措施。被动索引自动 使用标准的手机传感器在后台收集。DP指数从未在这方面进行过研究。 人口为了评估在这一具有挑战性的人群中的可行性，我们提出了一个为期2年的混合定量/ 质的研究方法分为两个阶段。第1阶段（目标1，第1 - 3个月）由重点小组组成， 利益相关者调整现有的EMA社区整合调查（最初为SMI开发）， RHV，并了解RHV对通过智能手机被动收集数据的看法。阶段2（目标2，月 4 - 24）包括HUD-VASH中27例发生SMI的RHV，他们将完成（a）基线临床评估， 社区融合，（B）为期7天（每天5次调查）的发展计划期，以评估可行性，（c）发展计划后的定量/ 可接受性的定性评价。该提案旨在为使用移动的 这些技术有可能用于生殖健康病毒的创新评估和治疗。

Veteran homelessness is a national crisis and Los Angeles has the highest homeless Veteran population in the US. Despite impressive progress in providing housing for Veterans, particularly through the HUD-VASH program, a fundamental problem remains: Permanent housing is a necessary first step, but not a sufficient condition, for successful community reintegration. Community reintegration, defined as full engagement in work, social, independent living, and recreational activities, does not arise automatically once housing is provided. Despite the provision of housing, recidivism (return to homelessness) is high. Further, the few relevant studies of non-VA samples demonstrate a failure to thrive after supported housing is provided (e.g., vocational and social functioning remain poor). HUD-VASH clinicians describe similarly poor outcomes in Veterans, but there are hardly any data on the types, severity, and causes of problems in community reintegration in recently-housed Veterans (RHVs). This information is essential for developing recovery- focused treatments that can be implemented in this complex, rapidly growing Veteran population. In 2015, our team established the VA Research Enhancement Award Program (REAP) on Enhancing Community Integration for Homeless Veterans in Los Angeles. The REAP is devoted to understanding the scope of reintegration problems, identifying their determinants, and developing novel interventions. We have identified two major challenges in our work with RHVs and their treatment providers. 1. Inadequacy of measures: Existing measures of community integration lack the sensitivity needed to identify the specific challenges faced by RHVs, and there have been no fine-grained assessments of how RHVs actually spend their time. 2. Poor rates of participation: It is extremely difficult to engage RHVs in treatment and research that require repeated visits to the VA campus. Consequently, our research assessments provide only single cross-sectional snapshots of integration that fail to capture the dynamic fluctuations in their lives. Furthermore, failure to engage in available treatment services contributes to recidivism and poor outcomes. We therefore believe it is necessary to look beyond traditional assessment and treatment modalities to address these challenges. New mobile technologies appear ideally suited this purpose. The goal of this proposal is to evaluate the feasibility of Digital Phenotyping (DP) delivered via mobile smartphone technology to assess community integration in RHVs with Serious Mental Illnesses (SMIs). We will use both active (Ecological Momentary Assessment [EMA] of social contact) and passive (Global Positioning System measures of mobility in the community) DP indices. Active EMA indices involve cueing participants to complete brief surveys multiple times per day over a week to obtain more fine-grained, ecologically valid information than traditional cross-sectional measures. Passive indices are automatically collected in the background using standard phone sensors. DP indices have never been examined in this population. To evaluate feasibility in this challenging population, we propose a 2-year mixed quantitative/ qualitative methods study with two phases. Phase 1 (Aim 1, Months 1-3) consists of focus groups with key stakeholders to adapt an existing EMA community integration survey (originally developed for SMI) for use in RHVs and to understand RHVs' views about passive data collection via smartphone. Phase 2 (Aim 2, Months 4-24) includes 27 RHVs with SMIs in HUD-VASH who will complete (a) baseline clinical assessments of community integration, (b) a 7-day (5 surveys/day) DP period to evaluate feasibility, (c) post-DP quantitative/ qualitative evaluations of acceptability. The proposal aims to break new ground in the use of mobile technologies, which have the potential for innovative assessment and treatment delivery applications for RHVs.