Modeling the Social Environmental Influences and Mechanisms of Suicide

描述（由申请人提供）：自杀是一个主要的公共卫生问题，具有复杂的病因根源，由于生产力和医疗保健的损失而造成的巨大社会成本，以及对医疗和公共卫生干预措施的抵制。先前的研究暗示了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，研究既没有确定1)社会环境的哪些层面（如人际关系、家庭、社区、宏观环境）对处于生命历程不同阶段的男女自杀结果影响最大，也没有确定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（如酒精和药物使用、精神疾病、生活事件）相互作用。由于理论、方法和统计方面的障碍，传统上和独特地阻碍了跨学科视角的自杀研究的科学整合，研究往往沿着社会科学/公共卫生和临床/生物学的路线分岔。该项目提出了一种创新的解决方案，通过将大学和政府的社会，行为，统计和生物医学科学家组成的跨学科团队整合社会网络中的理论进展，通过连接来自新的联邦努力（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）的数据来克服数据障碍，并采用考虑数据复杂性的修正和分析技术（例如，合并的数据库、正确审查的数据、嵌套的数据级别）。具体而言，Aim I对网络情节模型III-R进行了调整，以发展个体、情境和多层次的假设，将社会环境水平与自杀联系起来。Aim II编制了一套开创性的数据集，将相对较新的联邦数据工作联系起来，并使用适当的统计更正和新颖的先进技术检验假设。Aim III评估新方法的优势和局限性，制定计划，通过与联邦机构和州死亡登记系统/官员合作，填补剩余的数据空白，并与生物医学伦理学家合作，确保在整个项目中保护人类受试者。该研究计划已经获得了美国疾病控制与预防中心和其他重要联邦机构的合作，消除了自杀研究中长期存在的数据和分析障碍，在理解多种社会背景的作用、连接远端和近端途径的有前途的理论机制（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。同时实现这三个目标，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。跨学科理论的精细化，数据汇编、校正和概念操作的创新，以及统计方法的严格结合，将提高针对自杀和其他健康结果的临床和社区干预的知识和科学基础。

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.