APOS: Acute risk factors for post-discharge suicidal behaviour

APOS：出院后自杀行为的急性危险因素

• 批准号: 460438176
• 负责人: Professor Dr. Thomas Forkmann
• 金额: --
• 依托单位: Abteilung für Medizinische Psychologie und Medizinische Soziologie
• 依托单位国家: 德国
• 项目类别: Research Grants
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/460438176?language=en
• 关键词: APOS; Acute; risk; factors; post

Background:The risk for non-lethal and lethal suicide attempts is substantially increased after discharge from inpatient treatment due to acute suicidality. Yet, empirical evidence regarding proximal risk factors predicting suicidal ideation or behavior in the short-term is limited. Such evidence is needed to develop clinical monitoring concepts or interventions. The Interpersonal Theory of Suicide (IPTS, Joiner 2005), the Integrated Motivational-Volitional Model of Suicidal Behavior (IMV model, O’Connor 2011), and the Narrative-Crisis Model of Suicide (NCM, Galynker 2017) postulate several variables that might serve as proximal risk factors (e.g., perceived burdensomeness, entrapment, hyperarousal). Central assumptions of these theories have been supported by empirical studies. However, prospective and fine-grained studies in high-risk samples accounting for the temporal dynamics and the interactions of these variables and analyzing the predictive power with regards to suicidal ideation and behavior directly after discharge are lacking to date.Aim:The present study aims at empirically validating assumptions of the IPTS, the IMV-model, and the NCM. To this end, it will be investigated whether central concepts of these theories are predictors of suicidal ideation in real-time and suicidal behavior during a 6-months follow-up after discharge from inpatient psychiatric treatment (accounting for distal risk factors such as sex, previous suicide attempts, heart-rate variability). Individual trajectories of suicidal ideation will be further examined (digital phenotyping) and their predictive validity will be investigated. In addition, the specific role of heart-rate variability and heart-rate in real-time will be analyzed.Methods:In Essen and Leipzig, N=344 inpatients receiving treatment after acute suicidality or suicide attempt will be recruited over 18 months. After an extensive baseline assessment (central constructs of suicide theories, heart-rate variability, and control variables) and briefing, all participating patients will get a smartphone. Psychometrically reliable and valid items covering suicidal ideation and other variables of interest will be rated four times a day by the patients starting 1–3 days before discharge and 21 days following discharge, and two times a week for another 26 weeks in real-time. Additionally, the heart-rate will be assessed using a wearable. After six months, all participants will undergo a telephone follow-up on the occurrence of suicide ideation and attempts. Data will be analyzed using cox regression, multi-level models and latent profile analysis.RelevanceThis is the first study that investigates the prediction of suicidal ideation and behavior by variables of the IPTS, the IMV-model and the NCM applying a prospective and fine-grained study design in a high-risk population. We expect results derived from the project to improve the prediction of suicidal ideation and attempts.

背景：急性自杀倾向导致住院治疗出院后非致命性和致命性自杀企图的风险显著增加。然而，在短期内预测自杀意念或行为的近端风险因素的经验证据是有限的。制定临床监测概念或干预措施需要这些证据。人际自杀理论（IPTS, Joiner 2005）、自杀行为的综合动机-意志模型（IMV模型，O 'Connor 2011）和自杀的叙事-危机模型（NCM, Galynker 2017）假设了几个可能作为近端风险因素的变量（例如，感知负担、陷阱、过度觉醒）。这些理论的中心假设得到了实证研究的支持。然而，在高风险样本中进行的前瞻性和细粒度的研究，考虑了这些变量的时间动态和相互作用，并分析了出院后直接自杀意念和行为的预测能力，迄今为止还缺乏。目的：本研究旨在实证验证IPTS、imv模型和NCM的假设。为此，研究人员将调查这些理论的核心概念是否能预测实时自杀意念和住院精神病治疗出院后6个月的自杀行为（考虑到远端危险因素，如性别、以前的自杀企图、心率变异性）。自杀意念的个体轨迹将被进一步研究（数字表型），其预测有效性将被调查。此外，还将分析心率变异性和实时心率的具体作用。方法：在埃森和莱比锡，在18个月内招募N=344名急性自杀或企图自杀后接受治疗的住院患者。经过广泛的基线评估（自杀理论的核心结构、心率变异性和控制变量）和简报，所有参与的患者将获得一部智能手机。从出院前1-3天开始和出院后21天开始，患者每天进行四次心理测量学上可靠和有效的项目评估，包括自杀意念和其他感兴趣的变量，每周两次，持续26周。此外，心率将通过可穿戴设备进行评估。六个月后，所有参与者将接受电话随访，了解自杀意念和企图的发生情况。数据将使用cox回归、多级模型和潜在剖面分析进行分析。这是第一个在高风险人群中应用前瞻性和细粒度研究设计，通过IPTS、imv模型和NCM的变量来调查自杀意念和行为的预测的研究。我们期望从该项目中得出的结果能够改善对自杀意念和企图的预测。