Neural sensitivity to social evaluation and daily online and in-person social experience with peers: Predicting fluctuations in suicidality, self-harm, and depressive symptoms in adolescent girls

项目摘要/摘要 青春期女孩的自杀率、自伤率和抑郁率高得惊人，并且急剧上升。 然而，在过去的十年中，还不清楚哪些女孩患这些严重问题的风险最高，以及她们 可能会升级。一些人认为，社交媒体(SM)使用量的戏剧性增长可能起到了一定作用，但更重要的是 需要严格的数据来评估在青春期女孩中使用SM的积极和消极影响。敏感度 对社会评价，如拒绝或排斥，是自我伤害的潜在交叉诊断风险因素 思想和行为(SITB；包括自杀意念和行为以及非自杀的自我伤害)和非自杀 抑郁症状(DEPsx)。这项研究考察了社交威胁和奖励同伴互动是如何-- 在线或面对面体验-有助于SITB、DEPsx和幸福感的实时波动。第一 目的是使用生态瞬间评估(EMA)来确定青春期女孩的日常主观体验是如何的。 在线和面对面的社交威胁和回报预测个人内部的近期变化和长期变化 人与人之间在SITB和DEPsx方面的差异，以及幸福感。样本将包括177名青少年 女孩(13-17岁)，75%的样本有高自杀风险(例如，在过去6周内有活跃的意念，在- 过去一年中的诱惑，或者过去一年中≥五次非自杀性自残)，至少有一半的高危标准- 受试者也报告DEPsx升高。女孩们将完成三次为期10天的EMA课程，并将提供 访问被动获得的关于短信使用和数字社交互动(即文本、视频聊天)的数据。多层次 建模分析将用于确定SITB、DEPsx和积极影响的短期变化的预测因素 (PA)，以及在6个月和12个月的后续行动中评估的长期结果。第二个目标是确定哪些是 女孩暴露在短期沉淀物中时，患DEPsx和/或SITB的风险最高，关注差异 在包括杏仁核的情感显著网络(ASN)内对社会评价的大脑激活中， 前岛、背侧和膝下扣带回皮质，以及伏隔核。在不同的基础上- 对语境理论的敏感性研究表明，ASN对社会评价的高度激活 一个易感因素，可能会放大日常社会经验对 SITB和DEPsx。女孩将完成神经成像任务，评估大脑对社会评估的反应 虚拟同行。假设人与人之间的社交威胁体验增加，同龄人的社交威胁体验比率更高 (在线和面对面)将与患有高度ASN的女孩的SITB和DEPsx联系最密切 对社会评价的激活，以及个人内部增加和更高的同伴社会奖励实验比率- ENS还将与PA/幸福更紧密地联系在一起，并更好地预防SITB和DEPsx ASN活跃度高的女孩对社会评价。最后，将使用机器学习来确定 SM的哪些客观特征与主观体验和情绪健康实时使用Track，并以 找出短期和长期情绪健康的最强预测值。

PROJECT SUMMARY/ABSTRACT Rates of suicide, self-harm, and depression are alarmingly high among adolescent girls, with a dramatic spike over the last decade, yet it is not clear which girls are at highest risk for these serious problems and when they might escalate. Some have argued that the dramatic rise in social media (SM) use may play a role, but more rigorous data are needed to evaluate the positive and negative effects of SM use in adolescent girls. Sensitivity to social evaluation, such as rejection or exclusion, is a potential cross-diagnostic risk factor for self-injurious thoughts and behaviors (SITB; including suicidal ideation and behavior and nonsuicidal self-injury) and de- pressive symptoms (DEPsx). This study examines how socially threatening and rewarding peer interactions— experienced online or in-person—contribute to real-time fluctuations in SITB, DEPsx, and well-being. The first aim is to use ecological momentary assessment (EMA) to identify how adolescent girls’ daily subjective experi- ence of online and in-person social threat and reward predict proximal within-person changes and longer-term between-person differences in SITB and DEPsx, along with wellbeing. The sample will include 177 adolescent girls (ages 13-17), with 75% of the sample at high-risk for suicide (e.g. active ideation within past 6 weeks, at- tempt in past year, or ≥ five episodes of nonsuicidal self-injury in past year), with at least half of high-risk par- ticipants also reporting elevated DEPsx. Girls will complete three 10-day bursts of EMA and will also provide access to passively obtained data on SM use and digital social interactions (i.e. text, video-chat). Multilevel modeling analyses will be used to identify predictors of near-term changes in SITB, DEPsx, and positive affect (PA), as well as long-term outcomes assessed at 6- and 12-month follow-up. A second aim is to identify which girls are at highest risk for DEPsx and/or SITB when exposed to near-term precipitants, focusing on differences in brain activation to social evaluation within an affective salience network (ASN) that includes the amygdala, anterior insula, dorsal and subgenual anterior cingulate cortex, and nucleus accumbens. Building on the differ- ential susceptibility to context theory, the study proposes that heightened ASN activation to social evaluation is a susceptibility factor that could amplify both the positive and negative effects of daily social experience on SITB and DEPsx. Girls will complete neuroimaging tasks that assess brain response to social evaluation from virtual peers. It is hypothesized that within-person increases and higher rates of peer social threat experiences (online and in-person) will be most strongly associated with SITB and DEPsx for girls with heightened ASN activation to social evaluation, and that within-person increases and higher rates of peer social reward experi- ences will also be more strongly associated with PA/wellbeing and more protective against SITB and DEPsx for girls with heightened ASN activation to social evaluation. Finally, machine learning will be used to determine which objective features of SM use track in real-time with subjective experience and emotional health, and to identify the strongest set of predictors of short-term and long-term emotional health.