Leveraging Implementation Science and Design Methods to Sustain Community-Based Mental Health Services for Refugees

全世界难民人数史无前例地增加，约有26人 截至2019年底，有100万男子、妇女和儿童被迫流离失所。超过一半的人 世界上的难民生活在人口稠密的城市地区或中低收入国家的难民营中。一台较小的 1%的难民永久安置在高收入国家。在这些背景下，难民人数上升了 常见精神障碍的比率。战争和强迫移民也造成了社会系统的破坏。 家庭分离、紧张和冲突以及社交网络的丧失等人际关系。有一个 关于难民心理健康和心理社会需求的模型的新证据基础，但存在重大差距 存在关于如何使循证干预(EBI)适应难民人口并使其持续存在的问题 社区设置。为了解决这些差距，我的职业目标是建立一个独立的研究项目 重点是为全世界的难民社区实施以社区为基础的精神卫生服务 位移连续体。在与社区合作伙伴的协作下，我的目标是研究整合 将EBIS纳入非传统服务环境，使难民能够获得预防和护理干预措施， 促进积极的心理健康结果。我的研究试图解决的一个中心问题是如何最好地 调动社会和家庭资源，提高应对能力和福祉。这些研究的优先顺序是由 我15年多的临床实践经验，在美国和美国处理受战争影响的人群 在全球范围内，芝加哥大学的博士培训和早期研究经验。此K01应用程序是 构建我的优势并在关键领域发展新的知识和技能，以实现 我的长期目标。我的培训目标集中在1)实施科学方法，以适应、扩大和 在社区环境中维持EBIS；2)以人为中心的设计在社区难民中的应用 精神卫生服务；3)社区试验设计和分析。在成功人士的支持下 多学科导师团队，我将把这些技能应用到一个研究项目中，该项目专注于实施 同伴主导的多家庭小组(MFG)预防干预称为两个社区的咖啡馆 促进接纳难民家庭，满足难民家庭的多层次需求。使用飞行员 随机化类型1混合实施-有效性设计，研究目的包括：1)适应 叙利亚难民家庭的多家庭咖啡馆模式和社区同行提供者的送货方式 使用Adapt-ITT框架和以人为本的设计方法的组织；2)试行Adapted 评估实施科学领域的CAFE模型；以及3)探索心理健康的变化 成果、家庭和社区支持以及变革机制。利用新的知识和 从K01获得的技能和试点研究数据，我将准备R01提案以进一步测试该模型 落实和成效。

There has been an unprecedented increase in the number of refugees worldwide, with approximately 26 million men, women and children forcibly displaced from their homes at the end of 2019. More than half of the world’s refugees live in dense urban areas or refugee camps in low- and middle-income countries. A smaller percentage are permanently resettled in high-income countries. Across these contexts, refugees have elevated rates of common mental disorders. War and forced migration also contribute to systematic disruptions in social relationships including family separation, tension and conflict, and losses of social networks. There is an emerging evidence base of models regarding refugees’ mental health and psychosocial needs, but major gaps exist regarding how to adapt evidence-based interventions (EBIs) to refugee populations and sustain them in community settings. To address these gaps, my career goal is to establish an independent research program focused on the implementation of community-based mental health services for refugee communities across the displacement continuum. In collaboration with community partners, I aim to examine methods for integrating EBIs into non-traditional service settings to enable refugees’ access to prevention and care interventions that promote positive mental health outcomes. A central concern my research seeks to address is how to best mobilize social and family resources to enhance coping and wellbeing. These research priorities are shaped by my more than fifteen years of clinical practice experience working with war-affected populations in the U.S and globally, doctoral training at the University of Chicago and early research experiences. This K01 application is structured to build upon my strengths and develop new knowledge and skills in key areas needed to achieve my long-term goals. My training aims focus on 1) implementation science methods to adapt, scale up and sustain EBIs in community settings; 2) the application of human-centered design to community-based refugee mental health services; and 3) community-based trial design and analysis. With support from an accomplished multidisciplinary team of mentors, I will apply these skills to a research project that focuses on implementing a peer-led multiple family group (MFG) prevention intervention called CAFES in two community-based organizations in Chicago to promote uptake and meet the multi-level needs of refugee families. Using a pilot randomized type 1 hybrid implementation-effectiveness design, the research aims include: 1) Adapting the multiple family CAFES model for Syrian refugee families and delivery by peer providers in community-based organizations using the ADAPT-ITT framework and human-centered design methods; 2) Piloting the adapted CAFES model to assess implementation science domains; and 3) Exploring changes in mental health outcomes and family and community support and mechanisms of change. Drawing on the new knowledge and skills and pilot study data obtained from this K01, I will prepare an R01 proposal to further test the model implementation and effectiveness.