Transdiagnostic Reward System Dynamics and Social Disconnection in Suicide

项目摘要/摘要 这个重新提交的项目评估了正价系统(PVS)在人际关系过程中的作用 有自杀风险的跨诊断样本中的披露、寻求帮助和安全计划。人际关系 因素是当代从自杀意念向行为转变的模式的核心，以及社会因素 资源是有效的自杀安全规划的关键。然而，促进非正式求助的干预措施 到目前为止都是无效的，几乎一半的人在自杀之前不会向任何人透露自杀的想法 尝试。自杀中社会接近或回避行为潜在机制的基础研究 有助于为更有效的自杀预防干预确定新的目标。在这里，我们重点关注 调查奖励系统(即，评估、反应能力和/或学习)如何参与 危机前和危机期间的社会外展行为。在此计划中，我们将招募具有以下任一条件的参与者 情感性或精神病性障碍，以当前积极的自杀意念为分层。两者的有目的抽样 情感和精神病诊断能够将具有类似高自杀背景风险的群体包括在内， 然而，PVS和负价系统(NVS)的轮廓各不相同。我们将使用纵向脉冲串测量 设计将以实验室为基础的任务与生态瞬时评估和被动传感相结合。 参与者将被纵向跟踪12个月。在基于实验室的任务中，我们将管理我们的 经过验证的二元范式，可同时评估模拟社交网络中的PVS和NVS组件 从属关系和披露上下文，并支持面部情感编码和自然语言处理 演讲。在目标1中，我们将管理基于实验室的任务，并专注于评估PVS对自杀的影响- 相关的社会联系，包括标准安全计划的社会要素(例如，在危机中联系的人) 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，以及是否向谁披露了自杀意念。在目标3中，我们 将集成基于实验室和生态的即时评估数据流，以构建和测试集成的 自杀行为12个月以上的预测模型，评估情感或情感影响的稳定性 精神病综合症。我们将评估社会隶属动态是否调节了 PVS成分与自杀意念和行为。这项研究的预期产品包括 综合数据集，为转化性干预提供信息，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联系任务、使用移动设备 健康和计算方法来模拟求助的动态方面，以及重点比较 精神病和情感性综合症。该方案通过探测跨域连接来与RDoC保持一致 (PVS、NVS和社会进程)在跨诊断样本中，并对NIMH战略做出反应 计划(目标2.2，目标3.2)和NIMH对数字心理健康特别感兴趣的通知。

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.