Technology-Assisted Assessment of Post-Hospital Adherence in Schizophrenia

描述(由申请人提供)：技术辅助评估精神分裂症患者住院后的依从性慢性精神疾病，包括精神分裂症和分裂情感障碍，是重大的公共卫生问题，因为它们通常是严重的，使人虚弱，并使患者面临自杀等负面后果的风险。尤其是，精神障碍与与治疗、残疾和再入院相关的高得不成比例的社会成本有关，这些成本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有效，但患者对药物的依从性经常较差，患者提前终止行为治疗计划的风险很高，使他们面临复发和住院的风险。住院出院后的一个月是一个特别关键的时期，在这段时期内，患者不遵守出院计划和随后的不良结局的风险最高。R21探索性/发展研究应用程序的目标是建立一种可行和可接受的基于移动设备的研究方案，以确定在未来的技术辅助自我管理干预中可能可修改的治疗依从性的生态有效的上下文预测因素。为了解决目前知识上的差距，我们将使用生态瞬时评估(EMA)，这是一种动态评估程序，已在初步研究中显示出在理解慢性病患者的健康行为和疾病管理方面的前景。EMA通过使用通过移动电子设备(例如智能手机)进行的简单测量来实时评估自然环境中的变量，从而使数据不那么容易受到回溯性偏差(例如记忆偏差)的影响，并且对波动的环境因素(例如对线索的反应)更加敏感。EMA将用于检查60名精神分裂症或分裂情感障碍住院患者从出院开始到出院后持续4周的依从性障碍，以确定药物和行为不遵守出院后计划(例如，预约出院)的预测因素。我们将评估EMA程序在这一人群中的可行性和可接受性。此外，出院后四周的EMA阶段将评估预测变量与未来用药和行为依从性的关系，并与随访(1、3和6个月)收集的行为和回顾数据进行比较，以确定递增有效性。如果成功，我们相信，目前的研究将导致应用于改善精神病和其他慢性病的自我管理。

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.