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

描述（由申请人提供）：最近才出现了部分美国印第安人（AI）人口的心理健康概况。然而，记录诊断疾病的患病率只是第一步：疾病的亚综合征或部分表现可能对病情进展、服务使用和预防具有重要意义。此外，与精神疾病相关的痛苦或损害的测量，独立于诊断，已被证明捕捉到精神健康的不同方面，使它们在制定DSM-V中的作用成为一个激烈辩论的话题。最后，人工智能人群中情感问题的“文化习语”可能会提供一幅精神疾病的文化地图，以补充和详细阐述其他测量方法捕捉到的精神疾病。对于描述精神疾病的维度同样重要的是理解它们产生的背景。文化信仰、家庭过程和社区条件（不包括个人情况）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与日常生活不可或缺的人工智能人群中。然而，迄今为止，还没有对家庭和社区的影响进行严格的分析。

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.