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

退伍军人无家可归是一场全国性危机，洛杉矶无家可归的退伍军人人数是全美最多的 美国。尽管在为退伍军人提供住房方面取得了令人瞩目的进展，特别是通过 HUD-VASH 计划中，一个根本问题仍然存在：永久住房是必要的第一步，但不是最终目标 成功重返社会的充分条件。重新融入社区，定义为完全融入 参与工作、社交、独立生活和娱乐活动，并不是一旦发生就自动产生的 提供住房。尽管提供了住房，累犯率（再次无家可归）仍然很高。此外， 对非 VA 样本的少数相关研究表明，在提供支持性住房后，他们未能蓬勃发展 （例如，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果 退伍军人中，但几乎没有任何有关社区问题的类型、严重程度和原因的数据 最近安置的退伍军人 (RHV) 重返社会。这些信息对于发展康复至关重要 - 可以在这个复杂、快速增长的退伍军人群体中实施集中治疗。 2015 年，我们的团队设立了 VA 研究增强奖励计划 (REAP) 洛杉矶无家可归退伍军人的社区融合。 REAP 致力于了解 重新融入社会问题的范围，确定其决定因素，并制定新的干预措施。我们有 确定了我们与 RHV 及其治疗提供者合作时面临的两大挑战。 1. 不足之处 措施：现有的社区融合措施缺乏识别具体群体所需的敏感性 RHV 面临的挑战，并且没有对 RHV 的实际支出进行细粒度的评估 他们的时间。 2. 参与率低：让 RHV 参与治疗和研究极其困难 需要多次访问 VA 校园。因此，我们的研究评估仅提供单一的 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， 未能获得现有的治疗服务会导致累犯和不良后果。我们因此 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。新的移动技术似乎非常适合此目的。 该提案的目标是评估通过移动设备提供的数字表型分析 (DP) 的可行性 智能手机技术可评估患有严重精神疾病 (SMI) 的 RHV 中的社区融合。我们 将使用主动（社会接触的生态瞬时评估 [EMA]）和被动（全球 社区移动性的定位系统测量）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，以获得更细粒度的、 比传统的横截面测量更具有生态有效性的信息。被动索引自动 使用标准手机传感器在后台收集。 DP 指数在此期间从未被检验过 人口。为了评估这一具有挑战性的人群的可行性，我们提出了一个为期 2 年的混合定量/ 定性方法研究分两个阶段。第 1 阶段（目标 1，第 1-3 个月）由焦点小组组成，重点关注 利益相关者调整现有的 EMA 社区整合调查（最初为 SMI 开发）以用于 RHV 并了解 RHV 对于通过智能手机被动收集数据的看法。第 2 阶段（目标 2，几个月 4-24) 包括 27 名在 HUD-VASH 中具有 SMI 的 RHV，他们将完成 (a) 基线临床评估 社区融合，(b) 7 天（5 次调查/天）的 DP 期来评估可行性，(c) DP 后定量/ 可接受性的定性评估。该提案旨在为移动设备的使用开辟新天地 技术，这些技术具有对 RHV 进行创新评估和治疗提供应用的潜力。

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.