Technology-Assisted Assessment of Post-Hospital Adherence in Schizophrenia

描述（由申请人提供）：精神分裂症住院后依从性的技术辅助评估慢性精神疾病，包括精神分裂症和分裂情感性障碍，是重要的公共卫生问题，因为它们通常很严重，使人虚弱，并使患者面临自杀等负面结果的风险。特别是精神障碍，与治疗、残疾和再入院相关的社会成本过高，这往往是治疗不坚持的结果。药物和疾病自我管理干预已被证明在治疗精神障碍方面是有效的，但患者对药物的依从性往往很差，并且患者处于过早终止行为治疗计划的高风险中，使他们面临复发和住院的风险。住院患者出院后的一个月是一个特别关键的时期，在这个时期，患者不遵守出院计划和随后预后不良的风险最高。本R21探索性/发展性研究应用程序的目标是建立一个可行且可接受的基于移动设备的研究方案，以确定生态有效的治疗依从性的上下文预测因子，这些预测因子将在未来的技术辅助自我管理干预中有可能被修改。为了解决目前的知识差距，我们将使用生态瞬时评估（EMA），这是一种动态评估程序，在了解慢性疾病患者的健康行为和疾病管理的初步研究中显示出希望。EMA通过使用移动电子设备（例如，智能手机）进行的简短测量，实时评估自然环境中的变量，使数据较少受到回顾性偏差（例如，记忆偏差）的影响，并对波动的环境因素（例如，对线索的反应性）更加敏感。EMA将用于检查60名精神分裂症或分裂情感性障碍住院患者的依从性障碍，从出院开始并在出院后持续4周，以确定药物和行为不遵守出院后计划的预测因素（例如，预约出勤）。我们将评估EMA程序在该人群中的可行性和可接受性。此外，出院后4周的EMA阶段将评估预测变量与未来用药和行为依从性的关联，并与随访（1个月、3个月和6个月）收集的行为和回顾性数据进行比较，以确定增量有效性。如果成功，我们相信，目前的研究将导致应用于改善自我管理的精神病和其他慢性疾病。

DESCRIPTION (provided by applicant): Technology-Assisted Assessment of Post-Hospital Adherence in Schizophrenia Chronic mental illnesses, including schizophrenia and schizoaffective disorder, are significant public health concerns because they often are severe, debilitating, and put patients at risk for negative outcomes such as suicide. Psychotic disorders, in particular, are associated with disproportionately high societal costs related to treatment, disability, and readmission, which are often the result of treatment no adherence. Medications and illness self-management interventions have been shown to be effective in the treatment of psychotic disorders, but patients' adherence to medications frequently is poor and patients are at high risk for premature termination from behavioral treatment programs, putting them at risk for relapse and hospitalization. The month after inpatient hospitalization discharge is a particularly critical period in which patients are at highest risk for no adherence to discharge plans and subsequent poor outcomes. The goal of this R21 Exploratory/Developmental Research application is to establish a feasible and acceptable mobile device-based research protocol to identify ecologically-valid, contextual predictors of treatment adherence that will be potentially modifiable in a future technology-assisted self- management intervention. To address the current gap in knowledge, we will use Ecological Momentary Assessment (EMA), which is a dynamic assessment procedure that has shown promise in preliminary research for understanding health behaviors and illness management in patients with chronic illnesses. EMA assesses variables in natural settings in real-time through the use of brief measures conducted via mobile electronic devices (e.g., smartphones), making data less subject to retrospective biases (e.g., memory bias) and more sensitive to fluctuating environmental factors (e.g., reactivity to cues). EMA will be used to examine adherence barriers in 60 hospitalized patients with schizophrenia or schizoaffective disorder beginning at discharge and continuing 4-weeks post-discharge to identify predictors of medication and behavioral no adherence to post-discharge plans (e.g., appointment attendance). We will assess the feasibility and acceptability of the EMA procedures in this population. In addition, the four-week post- discharge EMA phase will assess the association of the predictor variables with future medication and behavioral adherence and be compared to behavioral and retrospective data collected over follow-up (one, three, and six months) to determine incremental validity. If successful, we believe that the current study will lead to applications for improving self-management in psychosis and other chronic illnesses as well.