Transdiagnostic Reward System Dynamics and Social Disconnection in Suicide

跨诊断奖励系统动态和自杀中的社会脱节

• 批准号: 10655760
• 负责人: Colin A. Depp
• 金额: $ 77.37万
• 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: 2023-05-18 至 2028-02-29
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10655760
• 关键词: Accounting; Acute; Affect; Affective; Basic Science; Behavior; Buffers; Chronic; Code; Computing Methodologies; Data; Data Collection; Data Set; Diagnosis; Diagnostic; Disclosure; Ecological momentary assessment; Elements; Emotions; Face; Feeling suicidal; Impairment; Individual; Intervention; Learning; Link; Longitudinal Studies; Measurement; Measures; Mediating; Modeling; Mood Disorders; Motivation; National Institute of Mental Health; Natural Language Processing; Negative Valence; Participant; Patient Recruitments; Persons; Play; Populations at Risk; Positive Valence; Prevention; Prevention strategy; Process; Psychopathology; Psychotic Disorders; Research; Research Domain Criteria; Resources; Rewards; Role; Safety; Sampling; Social Behavior; Social Network; Social Processes; Social outcome; Specific qualifier value; Strategic Planning; Suicide; Suicide prevention; Syndrome; System; Testing; Time; Translating; Withdrawal; Work; affective psychoses; approach behavior; avoidance behavior; data integration; data streams; design; digital; digital mental health; dynamic system; experience; help-seeking behavior; ideation; improved; innovation; interest; longitudinal design; mHealth; motivational processes; novel; outreach; predictive modeling; preventive intervention; psychotic; recruit; response; smartphone based assessment; social; social relationships; speech processing; suicidal behavior; suicidal risk; suicide attempter; suicide rate; tool

PROJECT SUMMARY/ABSTRACT This resubmitted project evaluates the role of the positive valence system (PVS) in the interpersonal processes of disclosure, help-seeking, and safety planning in a transdiagnostic sample at risk for suicide. Interpersonal factors are central to contemporary models of the transition from suicide ideation to behavior, and social resources are key to effective suicide safety planning. Yet, interventions to promote informal help-seeking have been ineffective to date, and almost half of people do not disclose suicidal thoughts to anyone prior to attempt. Basic research on the mechanisms underlying social approach or avoidance behaviors in suicide could help identify new targets for more effective suicide prevention interventions. Here, we focus on investigating how the reward system (i.e., valuation, responsiveness and/or learning) is involved in engaging in social outreach behaviors before and during crises. In this proposal, we will recruit participants with either affective or psychotic disorders, stratified by current active suicidal ideation. Purposive sampling of both affective and psychotic diagnoses enables inclusion of a group with a similar high background risk of suicide, yet varying PVS and negative valence system (NVS) profiles. We will use a measurement burst longitudinal design which integrates lab-based tasks with bouts of ecological momentary assessment and passive sensing. Participants will be followed longitudinally for 12 months. Among lab-based tasks, we will administer our validated dyadic paradigm that simultaneously evaluates PVS and NVS components in a simulated social affiliation and disclosure context, and enables facial emotion coding and natural language processing of speech. In Aim 1, we will administer lab-based tasks and focus on evaluating the impact of PVS on suicide- related social affiliation, including social elements of the standard safety plan (e.g., people to contact in crisis) and help seeking opportunity within each individual’s social network. In Aim 2, we will use mobile assessments to model short-term dynamics of suicidal ideation and whether and to whom ideation is disclosed. In Aim 3, we will integrate lab-based and ecological momentary assessment data streams to build and test integrated predictive models of suicidal behavior over 12 months, evaluating stability of effects across affective or psychotic syndromes. We will evaluate whether social affiliation dynamics mediate the relationship between PVS components and suicidal ideation and behavior. The intended products of this research include an integrated dataset informative for translational interventions to improve long-term and acute suicide prevention. Innovative aspects of the proposed study include the lab-based dyadic social affiliation task, use of mobile health and computational methods to model dynamic aspects of help seeking, and the focal comparison of psychotic and affective syndromes. This proposal aligns with RDoC by probing connections across domains (PVS, NVS and Social Processes) in a transdiagnostic sample, and is also responsive to the NIMH Strategic Plan (Aim 2.2, Aim 3.2) and the NIMH Notice of Special Interest in Digital Mental Health.

项目概要/摘要 这个重新提交的项目评估了正价系统（PVS）在人际过程中的作用 具有自杀风险的跨诊断样本中的披露、寻求帮助和安全计划。 因素是当代从自杀意念到行为转变模型的核心，社会因素 然而，资源是有效的自杀安全规划的关键，而促进非正式寻求帮助的干预措施则至关重要。 迄今为止效果不佳，几乎一半的人在此之前不会向任何人透露自杀的想法 尝试对自杀的社会方法或回避行为的机制进行基础研究。 可以帮助确定更有效的自杀预防干预措施的新目标。 研究奖励系统（即评估、响应能力和/或学习）如何参与参与 危机前和危机期间的社会外展行为 在本提案中，我们将招募具有以下任一行为的参与者。 情感或精神障碍，根据当前的主动自杀意念进行分层。 情感和精神病诊断可以纳入具有类似高自杀背景风险的群体， 但不同的 PVS 和负价系统 (NVS) 配置文件我们将使用测量纵向爆发。 设计将基于实验室的任务与生态瞬时评估和被动传感相结合。 我们将对参与者进行为期 12 个月的纵向跟踪。 经过验证的二元范式，可同时评估模拟社交中的 PVS 和 NVS 组件 隶属关系和披露上下文，并实现面部情感编码和自然语言处理 在目标 1 中，我们将执行基于实验室的任务，并重点评估 PVS 对自杀的影响。 相关的社会关系，包括标准安全计划的社会要素（例如，危机中的联系人） 并帮助在每个人的社交网络中寻找机会 在目标 2 中，我们将使用移动评估。 模拟自杀意念的短期动态以及是否以及向谁披露自杀意念。 将整合基于实验室和生态的瞬时评估数据流来构建和测试集成的 12 个月内自杀行为的预测模型，评估情感或情感影响的稳定性 我们将评估社会归属动态是否介导两者之间的关系。 PVS 成分与自杀意念和行为。本研究的预期产品包括 综合数据集为转化干预措施提供信息，以改善长期和急性自杀预防。 拟议研究的创新方面包括基于实验室的二元社会归属任务、移动设备的使用 健康和计算方法来模拟寻求帮助的动态方面，以及重点比较 该提案通过探索跨领域的联系与 RDoC 保持一致。 （PVS、NVS 和社会过程）在跨诊断样本中，并且还响应 NIMH 战略 计划（目标 2.2、目标 3.2）和 NIMH 对数字心理健康特别关注的通知。