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Technology-Assisted Assessment of Post-Hospital Adherence in Schizophrenia

精神分裂症出院后依从性的技术辅助评估

基本信息

批准号：
8703805
负责人：
BRANDON A GAUDIANO
金额：
$ 18.75万
依托单位：
BUTLER HOSPITAL (PROVIDENCE, RI)
依托单位国家：
美国
项目类别：
财政年份：
2013
资助国家：
美国
起止时间：
2013-07-19 至 2016-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8703805
关键词：
Acute Address Adherence Adjuvant Analgesic Adverse effects Affect Alcohol or Other Drugs use Antipsychotic Agents Appointment Attitude Behavior Behavior Therapy Behavioral Behavioral Sciences Characteristics Chronic Chronic Disease Clinical Continuity of Patient Care Cues Data Data Collection Development Devices Disease Electronics Environmental Risk Factor Event Feedback Future Goals Health Health behavior Healthcare Systems Hospitalization Hospitals Individual Inpatients Intervention Knowledge Lead Measures Medical Memory Mental disorders Modeling Oral Outcome Outpatients Patients Pharmaceutical Preparations Phase Population Procedures Protocols documentation Provider Psychotic Disorders Public Health Relapse Research Research Proposals Risk Schizoaffective Disorders Schizophrenia Self Management Social support Strategic Planning Suicide Symptoms Technology Testing Theoretical model Time base compliance behavior cost critical period disability environmental stressor experience follow-up handheld mobile device high risk improved indexing innovation insight medication compliance negative emotional state new technology novel pill premature primary outcome programs psychologic psychosocial public health relevance response severe mental illness social stigma stressor tool treatment adherence treatment program

项目摘要

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.

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，包括精神分裂症和情感障碍，是重要的公共卫生问题，因为它们通常是严重的，使人衰弱，并使患者处于自杀等负面后果的风险中。特别是精神疾病，与治疗、残疾和再入院相关的社会成本过高有关，这通常是治疗不依从的结果。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，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。住院病人出院后的一个月是一个特别关键的时期，在这个时期，病人不遵守出院计划和随后的不良结局的风险最高。本R21探索性/开发性研究申请的目标是建立可行且可接受的基于移动的器械的研究方案，以识别在未来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性、背景预测因素。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，在初步研究中已显示出了解慢性病患者健康行为和疾病管理的前景。EMA通过使用通过移动的电子设备（例如，智能手机），使数据较少受到回顾性偏差的影响（例如，记忆偏差）并且对波动的环境因素更敏感（例如，对线索的反应）。EMA将用于检查60例精神分裂症或情感障碍住院患者的依从性障碍，从出院时开始，持续出院后4周，以确定药物治疗和行为不依从出院后计划的预测因素（例如，预约出席）。我们将评估EMA程序在该人群中的可行性和可接受性。此外，为期四周的出院后EMA阶段将评估预测变量与未来药物治疗和行为依从性的相关性，并与随访期间（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。如果成功的话，我们相信目前的研究将有助于改善精神病和其他慢性疾病的自我管理。