Multilevel analysis of American Indian mental health, illness, and service use

描述(由申请人提供)：美国印第安人(AI)人口的一部分最近才出现心理健康状况。然而，记录确诊疾病的流行率只是第一步：亚综合征或疾病的部分表现可能对疾病的进展、服务使用和预防具有重要影响。此外，与诊断无关的与精神疾病相关的痛苦或损害的测量已被证明涵盖了精神健康的不同方面，使其在制定DSM-V中的作用成为激烈辩论的话题。最后，人工智能群体中情绪问题的“文化习语”可能会提供一张精神疾病的文化地图，以补充和阐述通过其他措施捕捉到的精神疾病。要描述精神疾病的各个方面，同样重要的是了解它们产生的背景。文化信仰、家庭进程和社区条件--不包括个人的文化信仰、家庭进程和社区条件--有助于我们理解精神疾病和随后的服务使用，特别是在亲属关系和社区生活对日常生活不可或缺的人工智能人群中。然而，到目前为止，还没有关于家庭和社区影响的严格分析。 在其他人群中的创新研究已经证明了社区环境在精神疾病和服务使用中的重要性。这些努力主要集中在城市地区或全国人口众多的地区。最近，已有数据可用于在农村认可机构中进行多层次调查。来自美国印第安人服务利用、精神病学流行病学和风险/保护因素项目(AI-SUPERPFP)的数据是专门为调查这些人群中的精神疾病和服务而设计的，现在附加了地理编码的社区和地理空间信息，使这些数据成为解决与AI精神障碍和服务使用相关的复杂和多层次因素的理想数据。本提案是对《计划公告》(PA-07-103；农村精神卫生与药物滥用障碍研究)的回应。它将涉及以下目标：[1]确定精神疾病的人口统计学，包括两个人工智能部落内部和之间的精神障碍(完全和亚症状)、文化习语、痛苦和损害；[2)通过开发多水平模型，将精神疾病纳入社区和家庭背景；以及[3)扩展多水平模型，以确定服务使用的家庭、社区和地理空间背景，包括生物医学和传统模式。

DESCRIPTION (provided by applicant): A mental health profile has only recently emerged of portions of American Indian (AI) populations. Documenting the prevalence of diagnosed conditions, however, is only the first step: Subsyndromal or partial manifestations of disorder likely hold important implications for progression, service use, and prevention. Additionally, measures of distress or impairment associated with mental illness, independent of diagnosis, have been shown to capture different dimensions of mental health, making their role in the formulation of DSM-V a topic of heated debate. Finally, "cultural idioms" of emotional problems in AI populations are likely to provide a cultural map of mental illness to complement and elaborate mental illness captured by other measures. As important to delineating the dimensions of mental illness, is understanding the context in which they arise. Cultural beliefs, family processes, and community conditions -- net of those of the individual -- are instrumental in our understanding of mental illness and subsequent service use, particularly in AI populations where kinship and community life is integral to daily life. Yet, to date, rigorous analyses delineating family and community influences have been absent. Innovative research in other populations has demonstrated the importance of community context in mental illness and service use. These efforts have focused mainly on urban areas or large national populations. Recently, data have become available for a multilevel investigation among rural AIs. Data from the American Indian Service Utilization, Psychiatric Epidemiology, and Risk/Protective Factors Project (AI- SUPERPFP), specifically designed to investigate mental illness and services in these populations, and now appended with geocoded community and geospatial information, make these data ideal for addressing the complex and multilayered factors associated with AI psychiatric disorders and service use. This proposal responds to Program Announcement (PA-07-103; Research on Rural Mental Health and Drug Abuse Disorders). It will address the following aims: [1] Determine the demography of mental illness, including psychiatric disorders (full and subsyndromal), cultural idioms, distress, and impairment within and across two AI tribes; [2] place mental illness in community and family context through the development of multilevel models; and [3] extend the multilevel models to determine the family, community, and geospatial context of service use, including both biomedical and traditional modalities.