Modeling the Social Environmental Influences and Mechanisms of Suicide

描述(申请人提供)：自杀是一个主要的公共卫生问题，具有复杂的病因，由于生产力和医疗保健的丧失而造成的巨大社会成本，以及对医疗和公共卫生干预的抵制。以前的研究已经涉及到广泛的风险和保护因素，并记录了对社会环境的强烈影响。然而，研究既没有1)确定哪些水平的社会环境(例如，人际关系、家庭、邻里关系、宏观环境)对生命过程不同阶段的女性和男性的自杀结果影响最大，也没有2)社会环境背景如何相互作用和/或与个人行为、认知和生物因素(例如，酒精和药物使用、精神疾病、生活事件)相互作用。研究往往沿着社会科学/公共卫生和临床/生物学的路线分叉，这是因为传统上和独特的理论、方法和统计学障碍阻碍了自杀研究跨学科视角的科学整合。该项目为这一僵局提出了一种创新的解决方案，将大学和政府中的社会、行为、统计和生物医学科学家组成的跨学科团队聚集在一起，整合社交网络中的理论进步，通过链接来自新的联邦努力的数据(例如，CDC的国家暴力数据报告系统、人口普查局的美国社区研究)来克服数据障碍，并采用考虑到数据复杂性的校正和分析技术(例如，合并的数据库、正确审查的数据、嵌套的数据级别)。具体地说，Aim I对网络剧集模式III-R进行了调整，以开发将社会环境水平与自杀联系起来的个人、背景和多层次的假设。AIM II汇编了一个开创性的数据集，将相对较新的联邦数据工作联系起来，并使用适当的统计校正和新颖的先进技术测试假设。AIM III评估了新方法的优点和局限性，制定了通过与联邦机构和州死亡登记系统/官员合作来填补剩余数据空白的计划，并与生物医学伦理学家合作，确保在整个项目中保护人类主体。随着疾病预防控制中心和其他主要联邦机构的合作，这项研究计划消除了自杀研究中长期存在的数据和分析障碍，导致在理解多种社会背景的作用、连接远端和近端通路的有前景的理论机制(社会网络)以及社会和生物/个人因素的相互作用方面取得了重大进展。同时在这三个目标上工作，可以立即在数据丰富方面取得进展，以测试假设，并同时关注规划未来的联邦数据收集。跨学科理论的完善，数据汇编、更正和概念操作的创新，以及统计方法的严格结合，将改善针对自杀和其他健康结果的临床和社区干预措施的知识和科学基础。

DESCRIPTION (provided by applicant): Suicide stands as a major public health problem with complex etiological roots, tremendous societal cost through lost productivity and medical care, and resistance to medical and public health interventions. Previous research has implicated a wide range of risk and protective factors, with strong effects documented for the social environment. However, research has neither 1) identified which levels of the social environment (e.g., interpersonal relationships, families, neighborhoods, macro-environments) are most influential in suicide outcomes for women and men at different stages of the life course nor 2) how social environmental contexts interact with each other and/or with individual behavioral, cognitive, and biological factors (e.g., alcohol and drug use, mental illness, life events). Research tends to be bifurcated along social science/public health and clinical/biological lines due to theoretical, methodological and statistical barriers that have traditionally and uniquely prevented scientific integration of suicide research across disciplinary perspectives. This project proposes an innovative solution to this stalemate by bringing together a trans-disciplinary team of social, behavioral, statistical and biomedical scientists in universities and in government to integrate theoretical advances in social networks, overcome data barriers by linking data from new federal efforts (e.g., CDC's National Violence Data Reporting System, Census Bureau's American Community Study), and employ corrections and analytic techniques that take into account data complexity (e.g., merged data bases, right censored data, nested data levels). Specifically, Aim I tailors the Network Episode Model III-R to develop individual, contextual and multi-level hypotheses linking social environmental levels and suicide. Aim II compiles a pioneering data set linking relatively new federal data efforts and testing hypotheses using appropriate statistical corrections and novel advanced techniques. Aim III assesses strengths and limits of the new approach, develops plans to fill remaining data gaps by working with federal agencies and state death registration systems/officials, and works with biomedical ethicists to ensure human subject protections across the entire project. With cooperation already secured from the CDC and other key federal agencies, this research plan eliminates longstanding data and analytic barriers in suicide research, leading to significant advancements in understanding the role of multiple social contexts, a promising theoretical mechanism (social network) linking distal and proximal pathways, and interaction of social and biological/individual factors. Working simultaneously on the three aims allows immediate advancement in data enrichment for testing hypotheses and concurrent attention to planning future federal data collections. The refinement of trans- disciplinary theory, innovation in data compilation, correction and concept operationalization, and the rigorous combination of statistical methods will improve knowledge and scientific foundations for clinical and community-based interventions targeted to suicide and other health outcomes.