Social Cognitive Mechanisms Underlying Disclosure and Help Seeking Behavior in Late-Life Suicide

项目摘要/摘要 本提案响应RFA-MH-22-135。在自杀未遂前不披露自杀意念是正常的 在以后的生活中更常见。同样，我们的初步数据显示，社交联系的包容性较低 在高危老年人的自杀安全计划中。不幸的是，增加非正式帮助的干预措施 到目前为止，寻找的方法都是无效的。因此，在人际关系过程中存在主要障碍，如 对于晚年自杀预防至关重要，需要新的目标来增加求助行为。这个 这个纵向观察项目的目的是了解为什么老年人不披露自杀 在自杀危机中思考或向他人寻求帮助。我们关注社会认知能力和偏见， 它们会影响个人对他人的看法(或误解)，并且以前曾与 孤独、自杀念头和行为。这项研究的前提是社会认知障碍 影响与从属关系和社会结构有关的正负配价系统 在自杀中寻求帮助。为了促进这项研究，我们团队开发并验证了一个二元社会 客观量化RDoC支持中涉及的正价和负价系统的从属任务 寻找。这项任务能够跨多个分析单元评估价态系统，包括行为、 自我报告、面部表情和自然语言处理。对这些内在过程的测量将是 通过结构性社会网络评估，与外部求助机会的量化相结合。一个 我们建议的社交网络分析的翻译方面是通过 自杀安全规划的社会因素。在一项纵向研究中，我们将招募不同年龄段的样本 来自各种紧急、初级和精神卫生保健环境的成年人。招聘将按以下顺序进行分层 由当前积极的自杀意念、无意念或未遂病史的抑郁症状定义的群体， 和健康的比较者。在研究的目标1中，我们将比较积极组和积极组的社会认知 来自我们的社会隶属关系任务的负价位指标，以及包括过去在内的社会网络结构 当前有自杀意念的小组中的求助和披露。在目标2中，我们将管理移动电话 情绪再认任务和社会隶属关系在通过生态途径预测自杀实时披露中的作用 超过30天的瞬时评估。然后，我们将评估社会认知和从属关系标志 通过收集一年多的纵向数据预测求助和自杀意念的轨迹。 探索性分析将利用通过应用时间序列网络分析和自然 语言处理以模拟隐藏在保密基础上的过程。我们的长期目标是将这一点 研究新的个性化干预措施，以改善嵌入当前 和新的老年人自杀预防方法。这一提议直接回应了NIMH战略 计划、目标2.2和3.2，以及NIMH在数字心理健康方面的优先领域。

PROJECT SUMMARY/ABSTRACT This proposal responds to RFA-MH-22-135. Non-disclosure of suicide ideation prior to attempt is normative and even more common in later life. Similarly, our preliminary data indicates lower inclusion of social contacts in suicide safety plans among at-risk older adults. Unfortunately, interventions to increase informal help seeking are ineffective to date. Therefore, major roadblocks exist in the interpersonal processes seen as essential to late-life suicide prevention, and new targets are needed for increasing help-seeking behavior. The purpose of this longitudinal observational project is to understand why older adults do not disclose suicide ideation or seek help from others amidst suicide crises. We focus on social cognitive abilities and biases, which influence how individuals perceive (or misperceive) others and have previously been associated with loneliness, suicidal ideation and behavior. The premise of this research is that social cognitive impairments impact the positive and negative valence systems involved in affiliation and the social structures that determine help seeking in suicide. Facilitating this research, our group has developed and validated a dyadic social affiliation task that objectively quantifies RDoC positive and negative valence systems involved in support seeking. This task enables evaluation of valence systems across multiple units of analysis, including behavior, self-report, facial affect and natural language processing. Measurement of these intrinsic processes will be integrated with quantification of extrinsic help-seeking opportunity, via structural social network assessment. A translational aspect of our proposed social network analyses is to augment network measurement with the social elements of suicide safety planning. In a longitudinal study, we will recruit a sample of diverse older adults from a variety of urgent, primary, and mental health care settings. Recruitment will be stratified by groups defined by current active suicide ideation, depressive symptoms without ideation or attempt histories, and healthy comparators. In Aim 1 of the study, we will compare groups on social cognition, positive and negative valence indicators from our social affiliation task, along with social network structure, including past help seeking and disclosure in the subgroup with current suicide ideation. In Aim 2, we will administer mobile emotion recognition tasks and social affiliation in predicting in real-time suicide disclosure through ecological momentary assessment over 30 days. We will then evaluate whether social cognition and affiliation markers predict trajectories of help seeking and suicide ideation through longitudinal data gathered over one year. Exploratory analyses will leverage the data derived by applying time series network analyses and natural language processing to model processes underlying non-disclosure. Our long-term goal is to translate this research to novel personalized interventions that improve interpersonal processes embedded in both current and novel suicide prevention approaches for older adults. This proposal responds directly to NIMH Strategic Plan, Aim 2.2 and 3.2, and the NIMH’s Priority Area in Digital Mental Health.