Dynamic Network Analysis of Social Cognition and Suicide in Psychosis

精神病社会认知与自杀的动态网络分析

• 批准号: 10677212
• 负责人: Emma Parrish
• 金额: $ 4.03万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-04-28 至 2025-04-27
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10677212
• 关键词: Affect; Age; Behavior; Bipolar Disorder; Cellular Phone; Clinical Trials; Cognitive; Complex; Computational Technique; Computing Methodologies; Cross-Sectional Studies; Data; Data Science; Ecological momentary assessment; Emotions; Exclusion; Face; Feedback; Feeling; Feeling suicidal; Frequencies; Funding Mechanisms; Future; General Population; Goals; Individual; Intervention; Link; Major Depressive Disorder; Measures; Mediating; Methods; Modeling; Motivation; National Institute of Mental Health; National Research Service Awards; Participant; Pathway Analysis; Perception; Persons; Population; Psychoses; Psychotic Disorders; Research; Research Personnel; Role; Sampling; Schizoaffective Disorders; Schizophrenia; Series; Social Behavior; Social Perception; Suicide; Suicide attempt; Suicide prevention; Symptoms; Time; Training; Withdrawal; Work; biobehavior; cognitive ability; cognitive testing; density; digital health; effective intervention; follow-up; ideation; novel; parent project; preventive intervention; protective factors; psychologic; psychotic; psychotic symptoms; response; secondary analysis; severe mental illness; social; social cognition; social determinants; social influence; social relationships; suicidal; suicidal behavior; suicidal risk; theories; tool; training opportunity

PROJECT SUMMARY/ABSTRACT People with serious mental illness (SMI; i.e., schizophrenia, schizoaffective disorder, bipolar disorder, and major depressive disorder with psychotic features) are at an increased risk of suicidal ideation and behavior as compared to the general population. Despite this, there is still relatively little understanding of the mechanisms that contribute to suicidal ideation in SMI, and people with SMI are excluded in almost 80% of biobehavioral clinical trials. Recent research indicates that aberrant social cognitive emotion processing, in particular over- attribution of threat, is common in psychosis and is associated with suicide ideation and behavior. Our prior work indicates that perceived burdensomeness and thwarted belongingness can be measured validly with ecological momentary assessment (EMA) in SMI and relate to suicidal ideation in this population. However, the relationships social cognitive abilities and biases, which can be objectively measured, have not been explored in a dynamic fashion. Social cognitive interventions are effective in psychosis but to date have not been evaluated as a component of suicide prevention. This project will evaluate real-time dynamic and longitudinal linkages between social cognitive abilities and biases measured by a validated mobile social cognitive testing tool, in a large sample of people SMI stratified by suicide ideation. Furthermore, the candidate will apply a novel computational technique, network analysis adapted for EMA data, to understand time-varying factors affecting these modifiable constructs related to suicide in psychosis. Network analyses augment traditional within-person analyses with EMA data to evaluate complex time interdependencies among variables, including density and time-lagged relationships. This project will utilize existing EMA, mobile cognitive, and longitudinal in-lab data collected from an NIMH supported study that includes 304 people with SMI. This proposed F31 project aims to understand the individual time-varying relationships between over-attribution of threat, social variables, perceived burdensomeness, and thwarted belongingness using traditional mixed-effects models, and utilize network analyses to evaluate the interdependencies among these constructs and symptoms between people with and without suicidal ideation. Then, this project aims to examine how these baseline associations and networks predict ideation trajectories and suicidal behavior at 12-month follow-up. In conjunction, the training opportunities afforded by the F31 funding mechanism will facilitate the applicant’s long-term goal of becoming an independent investigator in the psychological and social cognitive contributors to suicide in psychotic disorders, capable of applying sophisticated computational approaches to inform new translational interventions including those delivered in real time through digital health. This proposal is consistent with NIMH strategy aim 2.2.A. by evaluating novel objective mechanisms that could lead to novel suicide intervention approaches for SMI.

项目总结/摘要 患有严重精神疾病的人（SMI;即，精神分裂症，情感障碍，双相情感障碍，和 具有精神病特征的重度抑郁症）有自杀意念和行为的风险增加， 与一般人群相比。尽管如此，对这些机制的了解仍然相对较少 导致SMI中的自杀意念，而SMI患者在近80%的生物行为研究中被排除在外。 临床试验最近的研究表明，异常的社会认知情绪加工，特别是过度- 归因于威胁，是常见的精神病，并与自杀意念和行为。我们事先 工作表明，感知负担和挫折感可以有效地测量与 SMI的生态瞬时评估（EMA），并与该人群的自杀意念有关。但 社会认知能力和偏见之间的关系，可以客观地衡量，还没有被探讨 in a dynamic动态fashion时尚.社会认知干预对精神病是有效的，但迄今为止还没有 作为预防自杀的一部分。该项目将评估实时动态和纵向 社会认知能力和偏见之间的联系，通过有效的移动的社会认知测试测量 工具，在一个大样本的人SMI分层自杀意念。此外，候选人将申请 一种新的计算技术，适用于EMA数据的网络分析，以了解时变因素 影响了这些与精神病自杀相关的可变结构。网络分析增强了传统 使用EMA数据进行人员内分析，以评估变量之间复杂的时间相关性，包括 密度和时滞关系。该项目将利用现有的EMA、移动的认知和纵向 从NIMH支持的研究中收集的实验室数据，包括304名患有SMI的人。这款F31 该项目旨在了解个人的时间变化之间的关系过度归因的威胁，社会 变量，感知负担，并使用传统的混合效应模型， 并利用网络分析来评估这些结构和症状之间的相互依赖性 有自杀意念和没有自杀意念的人之间的差异。然后，本项目旨在研究这些基线 协会和网络预测12个月随访时的意念轨迹和自杀行为。在 结合，F31资助机制提供的培训机会将有助于申请人 长期目标是成为心理和社会认知贡献者的独立调查员 精神疾病中的自杀，能够应用复杂的计算方法来告知新的 转化干预措施，包括通过数字健康在真实的时间内提供的干预措施。这项建议是 符合NIMH战略目标2.2.A。通过评估新的客观机制， 自杀干预方法。