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个人的范围。对于每一起自杀死亡，估计 135 人遭受自杀损失的潜在创伤。研究表明，接触自杀 损失可能会导致精神和身体健康困扰，那些经历不良后果的人称为 “自杀者的幸存者。”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），在不考虑合并症的情况下检查有限数量的结果， 并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纵向流行病学研究 自杀幸存者阻碍了我们了解自杀对健康的全面影响以及自杀的全部范围的能力 自杀公共卫生危机。该项目的总体目标是使用丹麦国家登记数据来记录 暴露于该环境的人群的心理和身体健康结果以及合并症 30 年期间的自杀损失。丹麦拥有全民医疗保健体系，并得到政府支持 全国电子健康和社会登记处，以及跨登记处链接记录的能力 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第一学位 1994 年至 2024 年间遭受自杀损失的亲属和同居者，以及两个比较队列 (1) 遭受事故损失，以及 (2) 来自一般人群（目标 1）。该队列将包括所有可用的 30 年随访期间的社会人口统计和电子病历数据。这些数据将 用于对自杀损失进行流行病学结果分析（目标 2）。我们将识别所有心理和 身体健康 ICD 编码的针对自杀损失的诊断结果（与事故损失和自杀损失相比） 普通人群），并研究结果如何随失去亲人后的时间、关系类型和性别而变化。这 该方法将为自杀领域内的预防和干预提供新的、更精确的目标 事后预防。该队列还将用于确定最显着的诊断合并症模式， 跟踪自杀损失（目标 3）。无监督机器学习将识别自杀损失的潜在亚组 具有常见的精神和身体健康共病模式的幸存者，其目标是 为跨诊断预防/治疗提供信息并产生机制假设。这项研究是一项 有效的方法为自杀损失的流行病学奠定基础。我们的结果将为临床医生和 政策制定者拥有设计和研究特定疾病和跨诊断所需的信息 预防和治疗目前尚未探索和未充分探索的自杀对失去幸存者的影响的干预措施。 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，结果 可以在其他人群（例如较小的美国样本）中复制，以进一步将我们的发现结合起来。