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

美洲印第安人心理健康、疾病和服务使用的多层次分析

• 批准号: 7640929
• 负责人: CAROL E KAUFMAN
• 金额: $ 46.57万
• 依托单位: UNIVERSITY OF COLORADO DENVER
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-20 至 2011-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7640929
• 关键词: Address; American; American Indian and Alaska Native; American Indians; Anthropology; Attention; Belief; Censuses; Collection; Communities; Complement; Complex; Cultural Diversity; DSM-V; Data; Demography; Development; Diagnosis; Dimensions; Disease; Distress; Drug Formulations; Drug abuse; Emotional; Employee Strikes; Epidemiology; Family; Family Process; Family history of; Feedback; Heating; Impairment; Indian reservation; Individual; Investigation; Life; Location; Manuscripts; Maps; Measures; Mental Health; Mental disorders; Minority; Modality; Modeling; NIH Program Announcements; Population; Post-Traumatic Stress Disorders; Prevalence; Prevention; Provider; Psychiatry; Psychology; Research; Research Personnel; Respondent; Risk; Role; Rural; Rural Population; Sampling; Services; Tribes; Work; alcohol use disorder; community living; design; innovation; member; multidisciplinary; multilevel analysis; programs; service utilization; tribal leader; urban area

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.

描述（由申请人提供）：精神健康状况只是最近才出现的部分美洲印第安人（AI）人口。然而，记录确诊疾病的患病率只是第一步：亚综合征或部分症状可能对疾病的进展、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，已被证明可以捕获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，人工智能人群中情绪问题的“文化习惯用语”可能会提供一个精神疾病的文化地图，以补充和阐述其他措施所捕获的精神疾病。同样重要的是，要描绘精神疾病的维度，是了解他们出现的背景。文化信仰、家庭过程和社区条件--不包括个人的因素--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是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。 在其他人群中进行的创新研究表明，社区环境在精神疾病和服务使用中的重要性。这些努力主要侧重于城市地区或人口众多的国家。最近，数据已成为多层次的调查农村的AI。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，专门用于调查这些人群的精神疾病和服务，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精神疾病和服务使用相关的复杂和多层次因素的理想选择。本提案是对方案公告（PA-07-103;农村心理健康和药物滥用障碍研究）的回应。它将致力于以下目标：[1]确定精神疾病的人口统计学，包括精神障碍（完全和亚综合征），文化习惯用语，痛苦，以及两个AI部落内部和之间的障碍; [2]通过多层次模型的发展，将精神疾病置于社区和家庭背景中;和[3]扩展多层次模型，以确定服务使用的家庭，社区和地理空间环境，包括生物医学和传统模式。