Modeling the Social Environmental Influences and Mechanisms of Suicide

社会环境影响和自杀机制建模

• 批准号: 8692021
• 负责人: Bernice A. Pescosolido
• 金额: $ 65.23万
• 依托单位: TRUSTEES OF INDIANA UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2016-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8692021
• 关键词: Accounting; Address; Age; Aggressive behavior; Alcohol consumption; American; Anxiety; Attention; Authorization documentation; Behavioral; Biological; Biological Factors; Caring; Cause of Death; Censuses; Centers for Disease Control and Prevention (U.S.); Cessation of life; Clinical; Cognitive; Collection; Communities; Community Surveys; Complex; Confidentiality; Coroners and Medical Examiners; County; Coupled; Data; Data Collection; Data Reporting; Data Security; Data Set; Databases; Distal; Drug usage; Ensure; Environment; Environmental Impact; Ethicists; Etiology; Event; Family Relationship; Feeling suicidal; Foundations; Functional disorder; Future; Genetic; Government; Health; Heritability; Impulsivity; Individual; Influentials; Injury; Institutional Review Boards; Intervention; Knowledge; Lead; Life; Life Cycle Stages; Link; Logistics; Measures; Medical; Mental Depression; Mental Health; Mental disorders; Modeling; Neighborhoods; Outcome; Pathway interactions; Pattern; Plant Roots; Preventive Intervention; Procedures; Productivity; Public Health; Religion; Reporting; Research; Research Design; Resistance; Risk; Role; Science; Secure; Services; Shame; Social Environment; Social Network; Social Sciences; Societies; Solid; Solutions; Staging; Statistical Methods; Stream; Substance abuse problem; Suicide; Suicide attempt; System; Techniques; Testing; Time; Translating; Universities; Violence; Visit; Woman; Work; accomplished suicide; base; biomedical scientist; cost; design; experience; human subject protection; hypothalamic pituitary axis; improved; innovation; member; men; noradrenergic; novel; novel strategies; pediatric trauma; prevent; psychologic; reducing suicide; social; social model; stem; suicidal behavior; theories

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.

描述（由申请人提供）：自杀是一个重大的公共卫生问题，其病因学根源复杂，由于生产力和医疗保健的损失以及对医疗和公共卫生干预措施的抵制而造成巨大的社会成本。先前的研究涉及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) 确定哪些层面的社会环境（例如，人际关系、家庭、社区、宏观环境）对生命历程不同阶段的女性和男性自杀结果影响最大，也没有 2) 社会环境背景如何相互影响和/或与个人行为、认知和生物因素（例如，酒精和毒品使用、精神疾病、生活事件）相互作用。由于理论、方法论和统计上的障碍，研究往往沿着社会科学/公共卫生和临床/生物学路线分叉，这些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。该项目提出了解决这一僵局的创新解决方案，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聚集在一起，整合社交网络中的理论进展，通过链接新的联邦工作（例如疾病预防控制中心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，并采用考虑到数据复杂性的修正和分析技术 （例如，合并数据库、右删失数据、嵌套数据级别）。具体来说，目标 I 定制了网络情节模型 III-R，以开发将社会环境水平与自杀联系起来的个人、情境和多层次假设。 Aim II 编制了一个开创性的数据集，将相对较新的联邦数据工作与使用适当的统计校正和新颖的先进技术测试假设联系起来。目标 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/官员合作来填补剩余的数据空白，并与生物医学伦理学家合作，确保整个项目中的人类受试者受到保护。在疾病预防控制中心和其他主要联邦机构的合作下，该研究计划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、连接远端和近端路径的有前途的理论机制（社交网络）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。同时致力于这三个目标可以立即推进数据丰富，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、校正和概念操作方面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。

项目成果

Examining Multi-Level Correlates of Suicide by Merging NVDRS and ACS Data.

通过合并 NVDRS 和 ACS 数据检查自杀的多层次相关性。

• 发表时间: 2017
• 期刊: U.S. Census Bureau Center for Economic Studies research paper series
• 作者: Boulifard,DavidA;Pescosolido,BerniceA
• 通讯作者: Pescosolido,BerniceA

Cross-level sociodemographic homogeneity alters individual risk for completed suicide.

• DOI: 10.1073/pnas.2006333117
• 发表时间: 2020-10-20
• 期刊: Proceedings of the National Academy of Sciences of the United States of America
• 影响因子: 11.1
• 作者: Pescosolido BA;Lee B;Kafadar K
• 通讯作者: Kafadar K