Identifying the longitudinal outcomes of suicide loss in a population-based cohort

确定基于人群的队列中自杀损失的纵向结果

• 批准号: 10716673
• 负责人: Jaimie L. Gradus
• 金额: $ 73.83万
• 依托单位: BOSTON UNIVERSITY MEDICAL CAMPUS
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-06 至 2027-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10716673
• 关键词: Accidents; Address; Adverse event; Big Data; Caring; Cessation of life; Child; Computerized Medical Record; Data; Data Sources; Denmark; Diagnostic; Disease; Distress; Epidemiology; Event; Exposure to; Family; First Degree Relative; Foundations; Friends; Funding; Future; General Population; Goals; Government; Health; Healthcare; Healthcare Systems; Individual; Insurance; International Classification of Disease Codes; Intervention; Knowledge; Link; Literature; Medical; Mental Health; Methods; National Institute of Mental Health; Outcome; Pattern; Persons; Policy Maker; Population; Prevention; Psychiatric epidemiology; Public Health; Publishing; Records; Registries; Reporting; Research; Resources; Sample Size; Sampling; Selection Bias; Source; Spouses; Subgroup; Suicide; Suicide prevention; Survivors; Time; Trauma; United States; United States Department of Veterans Affairs; Work; adverse outcome; cohort; comorbidity; comparison group; cost efficient; data registry; design; eHealth; emotional distress; epidemiology study; experience; follow-up; high risk; improved; longitudinal design; novel; physical conditioning; population based; prevent; secondary analysis; sex; social; sociodemographics; suicidal individual; suicidal morbidity; therapy design; traumatic stress; unsupervised learning

PROJECT ABSTRACT The impact of suicide reaches well-beyond individual suicide decedents. For each suicide death, an estimated 135 people are exposed to the potential trauma of suicide loss. Research indicates that exposure to suicide loss can result in mental and physical health distress, with those experiencing adverse outcomes called “suicide loss survivors.” At the same time, the literature is severely limited by a lack of appropriate comparison groups (e.g., accident death loss), examining a limited number of outcomes without considering comorbidity, and focusing on one type of familial relation (e.g., spouses) while ignoring non-familial loss survivors (e.g., cohabitants). Consequently, the lack of high-quality population-level longitudinal epidemiologic studies of suicide loss survivors hinders our ability to understand the full health effects of suicide and the full extent of the suicide public health crisis. The overall goal of this project is to use Danish national registry data to document the mental and physical health outcomes and comorbidities among the population of individuals exposed to suicide loss over a 30-year period. Denmark has a universal healthcare system, with government supported nationwide electronic health and social registries, and the ability to link records across registries and individuals using unique personal/family identifiers and address information. Our project will leverage the registries to directly address gaps in the suicide loss literature. We will develop a cohort of all first-degree relatives and cohabitants exposed to suicide loss between 1994 and 2024, as well as two comparison cohorts (1) exposed to accident loss, and (2) from the general population (Aim 1). The cohorts will include all available socio-demographic and electronic medical record data over the 30-year follow-up period. These data will be used to conduct an epidemiologic outcome-wide analysis of suicide loss (Aim 2). We will identify all mental and physical health ICD-coded diagnostic outcomes that are specific to suicide loss (compared to accident loss and the general population), and examine how outcomes vary by time since loss, relationship type, and sex. This approach will inform novel and more precise targets for prevention and intervention within the field of suicide postvention. The cohort also will be used to identify the most salient patterns of diagnostic comorbidity that follow suicide loss (Aim 3). Unsupervised machine learning will identify latent subgroups of suicide loss survivors characterized by common patterns of mental and physical health comorbidity, with the goal of informing transdiagnostic prevention/treatment and generating mechanistic hypotheses. This study is an efficient way to lay a foundation for the epidemiology of suicide loss. Our results will provide clinicians and policymakers with the information needed to design and study both disorder-specific and transdiagnostic interventions to prevent and treat currently unexplored and underexplored effects of suicide on loss survivors. The cohort also can serve as an enduring resource for future research on suicide loss. Going forward, results can be replicated across other populations (e.g., smaller US samples) to further contextualize our findings.

项目摘要 自杀的影响远远超出了自杀死者的个人。对于每一个自杀死亡， 135人面临自杀损失的潜在创伤。研究表明，接触自杀 损失可能导致精神和身体健康困扰，那些经历不良后果的人被称为 “自杀损失幸存者”与此同时，由于缺乏适当的比较，文献受到严重限制 组（例如，事故死亡损失），检查有限数量的结果而不考虑合并症， 并且关注一种类型的家庭关系（例如，配偶）而忽略非家庭损失幸存者（例如， 同居者）。因此，缺乏高质量的人群水平的纵向流行病学研究， 自杀损失幸存者阻碍了我们理解自杀对健康的全面影响以及自杀对健康的全面影响的能力。 自杀公共卫生危机该项目的总体目标是利用丹麦国家登记册数据记录 暴露于以下物质的人群中的精神和身体健康结果以及合并症： 30年来的自杀损失。丹麦有一个全民医疗保健系统，政府支持 全国性的电子健康和社会登记册，以及将登记册之间的记录联系起来的能力， 使用唯一的个人/家庭标识符和地址信息的个人。我们的项目将利用 登记处直接解决自杀损失文献中的空白。我们将培养一批所有的第一学位 1994年至2024年期间暴露于自杀损失的亲属和同居者，以及两个比较队列 (1)暴露于事故损失，和（2）从一般人群（目标1）。队列将包括所有可用的 30年随访期间的社会人口统计学和电子病历数据。这些数据将 用于进行自杀损失的流行病学结果分析（目的2）。我们将识别所有精神和 身体健康ICD编码的诊断结果，特定于自杀损失（与事故损失相比， 一般人群），并研究结果如何随时间变化，因为损失，关系类型，和性别。这 该方法将为自杀领域的预防和干预提供新的和更精确的目标 预防后该队列还将用于确定诊断合并症的最显著模式， 自杀损失（目标3）。无监督机器学习将识别自杀损失的潜在亚组 幸存者的特点是共同的模式，精神和身体健康的comormacy，目标是 为跨诊断预防/治疗提供信息，并产生机制假设。本研究是一项 为自杀损失的流行病学研究奠定基础。我们的研究结果将为临床医生和 政策制定者掌握设计和研究疾病特异性和转诊断所需的信息 干预措施，以预防和治疗目前尚未探索和探索不足的自杀对损失幸存者的影响。 该队列还可以作为未来自杀损失研究的持久资源。展望未来，成果 可以在其他群体中复制（例如，更小的美国样本），以进一步将我们的发现置于背景中。