Social Processing Deficits in Remitted Adolescent Depression

青少年抑郁症缓解后的社会处理缺陷

• 批准号: 10292961
• 负责人: RANDY PATRICK AUERBACH
• 金额: $ 73.33万
• 依托单位: NEW YORK STATE PSYCHIATRIC INSTITUTE DBA RESEARCH FOUNDATION FOR MENTAL HYGIENE, INC
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-12-01 至 2024-10-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10292961
• 关键词: Adolescence; Adolescent; Adopted; Attention; Behavior; Cellular Phone; Code; Communication; Data; Depressed mood; Emotional; Evaluation; Event-Related Potentials; Exhibits; Face; Face Processing; Facial Expression; Feedback; Frequencies; Gestures; Hand; Individual; Individual Differences; Intervention; Laboratories; Maintenance; Major Depressive Disorder; Measures; Mental Depression; National Institute of Mental Health; Process; Process Measure; Public Health; Recurrence; Relapse; Research; Research Domain Criteria; Risk; Risk Behaviors; Role; Social Network; Social Processes; Stressful Event; Structure; Suicide; Symptoms; Testing; Text Messaging; Time; Youth; aged; child depression; depressive symptoms; digital; digital communication; disability; follow-up; indexing; information processing; innovation; lens; negative affect; neurophysiology; outcome prediction; peer; recurrent depression; relapse prediction; relapse risk; showing emotion; smartphone Application; social; social communication; social media; stem; supervised learning; visual tracking

Major depressive disorder (MDD) is a leading cause of disability worldwide and has a peak onset during adolescence. While interventions are moderately effective for many adolescents, 40 to 70% will relapse within 5 years. Further, MDD relapse predicts academic difficulties, risky behaviors, and suicide. Thus, identifying mechanisms of MDD relapse is critical to clarify intervention targets for this significant public health problem. During adolescence, social processes and dynamics (especially with peers) are particularly significant, although it is unclear which social processes are most critical to MDD relapse. The present study focuses on the role of social communication, a set of mechanisms involving the receiving and delivery of socially relevant information. Social communication is especially significant to adolescents, as maladaptive social communication can negatively impact the establishment and maintenance of relationships, thus increasing risk for MDD relapse. For the proposed study, we will employ an NIMH’s Research Domain Criteria (RDoC) lens and use multiple measures (behavior, event-related potentials [ERPs], eye tracking) to compare adolescents (aged 14-17 years) with remitted depression (remMDD; N=200) to healthy controls (HC; N=100) on deficits in several aspects of social communication, including: (i) processing of nonverbal social information, (ii) processing of socioemotional feedback, and (iii) digital communication. First, Aim 1 will test whether remMDD adolescents abnormally process two types of nonverbal social information—facial expressions (as indexed by reduced accuracy and abnormal ERPs [i.e., the N170]) and hand gesturing behaviors (assessed via eye-tracking). Second, Aim 2 will test whether remMDD adolescents abnormally process socioemotional feedback (being accepted versus rejected by same-aged peers), a well-established trigger of adolescent MDD. Specifically, Aim 2 will test whether remMDD adolescents exhibit a reduced Late Positive Potential [LPP]), an ERP indexing emotional encoding, following positive social feedback from faux peers during a peer evaluation task. Third, using an innovative smartphone app, Aim 3 will collect multiple indicators of digital communication regarding the structure of adolescents’ digital social network (i.e., size of the network; frequency of communication) and sentiment of the communication with their digital social network (i.e., coding sentiment from their texts, social media posts); allowing us to test whether remMDD adolescents exhibit abnormal digital communication. Last, we will follow adolescents for 1-year to determine whether processing of nonverbal information, social feedback, and digital communication predict the escalation of depression symptoms and MDD relapse. Further, supervised machine learning will explore which social communication deficit(s) predict symptoms or MDD relapse, and whether these social processes predict outcomes independent of (or interaction with) other established predictors of relapse (e.g., stressful life events). In summary, the project has the promise to identify social process that contribute to recurrent depression, which, ultimately, will lead to innovative treatment approaches.

重度抑郁症 (MDD) 是全球范围内导致残疾的主要原因，并且在 虽然干预措施对许多青少年有一定效果，但 40% 至 70% 的人会在 5 年内复发。 此外，MDD 复发预示着学业困难、危险行为和自杀。 MDD 复发机制对于明确这一重大公共卫生问题的干预目标至关重要。 在青春期，社会过程和动态（尤其是与同龄人）尤其重要， 尽管尚不清楚哪些社会过程对 MDD 复发最关键，但本研究重点关注 MDD 复发。 社会沟通的作用，一套涉及接收和传递社会相关信息的机制 社会沟通对于青少年尤其重要，因为适应不良的社会沟通。 会对人际关系的建立和维持产生负面影响，从而增加重度抑郁症复发的风险。 对于拟议的研究，我们将采用 NIMH 的研究领域标准 (RDoC) 镜头并使用多个 比较青少年（14-17 岁）的措施（行为、事件相关电位 [ERP]、眼动追踪） 缓解性抑郁症（remMDD；N=200）与健康对照（HC；N=100）在多个方面的缺陷 社交沟通，包括：（i）非语言社交信息的处理，（ii） 首先，目标 1 将测试青少年是否患有 remMDD。 异常处理两种类型的非语言社会信息——面部表情（按减少的索引 准确性和异常 ERP [即 N170]）和手势行为（通过眼动追踪评估）。 其次，目标 2 将测试 remMDD 青少年是否异常处理社会情绪反馈（即 具体来说，目标 2 将测试 remMDD 青少年是否表现出降低的晚期阳性电位 [LPP]），这是一种 ERP 索引 情感编码，在同伴评估任务中遵循假同伴的积极社会反馈。 Aim 3 将使用创新的智能手机应用程序收集有关数字通信的多项指标 青少年数字社交网络的结构（即网络规模；交流频率）以及 与他们的数字社交网络沟通的情绪（即，从他们的文本、社交网络中编码情绪 媒体帖子）；让我们能够测试 remMDD 青少年是否表现出异常的数字交流。 我们将跟踪青少年一年，以确定是否处理非语言信息、社会反馈、 数字通信可以预测抑郁症状的升级和重度抑郁症的复发。 机器学习将探索哪些社交沟通缺陷可以预测症状或 MDD 复发，以及 这些社会过程预测的结果是否独立于其他既定的（或与之相互作用） 复发的预测因素（例如，压力性生活事件）总而言之，该项目有望识别社会因素。 导致抑郁症复发的过程，最终将导致创新的治疗方法。