Optimizing prevention approaches for children reintegrating from orphanages in Azerbaijan

摘要 联合国估计，全球有200万至800万儿童生活在孤儿院和世界各国 前苏联(FSU)和东欧的机构托儿所儿童人数最多 全世界--多达130万儿童。由于苏联解体后的经济危机， 阿塞拜疆有大量的“社会孤儿”，他们是由贫困的父母留在国营的孩子 机构。孤儿院多年的剥夺、与父母的分离和虐待严重加剧了 收容机构儿童中出现心理健康问题的风险。然而，目前的去制度化和 家庭团聚倡议提供基本的病例管理服务，但不涉及精神健康问题 收容儿童的问题，没有注意到导致贫困的相关因素 首先是制度化。预防孤儿院6-12岁儿童的心理健康问题 与他们在阿塞拜疆的亲生家庭或大家庭团聚，拟议的研究将完善和测试三个 循证干预方法(A)加强家庭干预；b)心理健康筛查和 转介治疗；以及(C)以儿童储蓄账户的形式赋予经济权力)。基于 研究小组与当地社区合作委员会合作进行的形成性研究， 对干预内容进行了调整，以最大限度地适应阿塞拜疆的文化背景。在 拟议的研究中，调整后的干预措施将在一项试验中测试400名儿童-照顾者双方，使用 多阶段优化策略(MOST)，以比较不同的干预组件并确定最多 最佳组合。这项研究将检验每个干预成分对儿童心理健康的影响 结果(抑郁、焦虑症状；破坏性行为；创伤后症状；精神障碍 依恋)。如果有效，研究结果研究可能会改变大规模的非制度化倡议 由儿童基金会或其他组织在阿塞拜疆和FSU地区实施。这项研究针对的是顶级 NIMH中的两个挑战全球精神卫生目标B的重大挑战(高级预防和 实施早期干预)：1)制定适合当地情况的战略，以消除儿童期虐待 2)制定干预措施，以减少儿童社会经济地位低下带来的长期负面影响 关于心理健康的。此外，此R01应用程序的目标是加强本地研究专业知识 用于预防儿童心理健康的个人、家庭和结构性干预措施的测试和适应 有问题。通过培训和合作研究，该项目将在以下方面增强知识和技能：1) 儿童心理健康预防性干预的核心内容和变化机制 创伤、虐待和剥夺病史；2)采用多层次循证干预和 一个FSU国家新的社会文化背景下的衡量工具；3)方法和统计 评估包含多个组件的复杂干预措施的技术。

ABSTRACT The UN estimates that globally between 2 to 8 million children live in orphanages and the countries of the former Soviet Union (fSU) and Eastern Europe have the highest number of children in institutional care worldwide--up to 1.3 million children. Due to the economic crisis following the collapse of the Soviet Union, Azerbaijan hosts a large population of “social orphans,” children left by destitute parents in state-run institutions. Years of deprivation, separation from parents, and maltreatment in orphanages severely heighten the risk of mental health problems among institutionalized children. However, current deinstitutionalization and family reunification initiatives provide basic case management services, but do not address the mental health problems of institutionalized children and do not attend to the poverty-related factors that led to institutionalization in the first place. To prevent mental health problems among 6-12 children from orphanages reunited with their biological or extended families in Azerbaijan, the proposed study will refine and test three evidence-based intervention approaches (a) family strengthening intervention; b) mental health screening and referral for treatment; and c) economic empowerment in the form of Child Savings Accounts). Based on the formative research conducted by the study team in collaboration with a local Community Collaborative Board, the intervention components have been adapted to maximize fit to the cultural context of Azerbaijan. In the proposed study, the adapted interventions will be tested with 400 child-caregiver dyads in a trial using the Multiphase Optimization Strategy (MOST) to compare different intervention components and identify the most optimal combination. The study will test effects of each intervention component on children's mental health outcomes (symptoms of depression, anxiety; disruptive behaviors; post-traumatic symptoms; and disturbances of attachment). If efficacious, the study results study could transform large-scale deinstitutionalization initiatives implemented by UNICEF or other organizations in Azerbaijan and in the fSU region. The study addresses top two challenges within the NIMH Grand Challenges in Global Mental Health Goal B (Advance prevention and implementation of early interventions): 1) to develop locally appropriate strategies to eliminate childhood abuse and 2) to develop interventions to reduce the long-term negative impact of low childhood socioeconomic status on mental health. Additionally, the goal of this R01 application is to strengthen the local research expertise in testing and adaptation of individual, family, and structural interventions for preventing child mental health problems. Through training and collaborative research, the project will enhance knowledge and skills in: 1) core components and mechanisms of change in preventive mental health interventions for children with a history of trauma, abuse and deprivation; 2) adaptation of multilevel evidence-based interventions and measurement tools to a new socio-cultural context of a fSU country; 3) methodological and statistical techniques for evaluating complex interventions with multiple components.