Mechanisms and Predictors of Change in App-Based Mindfulness Training for Adolescents

项目摘要/摘要 近年来，基于正念的智能手机应用程序越来越受欢迎。Headspace-在最大的 这些平台中最受欢迎的-拥有超过4200万用户。最近的调查表明，11%的美国青少年 使用正念应用程序作为应对焦虑或抑郁症状的一种手段，这些症状会增加 基本上是在青春期。越来越多的研究表明，沉思是一种 跨诊断危险因素参与青年抑郁症和焦虑症的发展。关键是， 正念冥想在针对冥想和最终改善方面显示出了巨大的前景。 抑郁和焦虑症状。正念应用程序提供了一种方便且经济高效的方式 获得正念训练，同时对年轻人来说是互动和参与的。尽管他们越来越受欢迎 在青少年中，对这些应用程序的研究令人惊讶地少之又少。有两个关键问题尚未解决 这些问题与NCCIH战略计划密切相关：(1)什么是潜在的神经和 解释这些应用程序的有益影响的认知机制，以及(2)基于应用程序的对象 正念是非常合适的。为了解决这些差距，青少年(13-18岁)将被随机分配到 APP提供的正念课程与主动控制条件的对比，并将完成干预前和干预后 静息状态功能磁共振成像(FMRI)扫描以探测静态和动态功能 大脑内部和大脑之间的网络连接与正念训练和沉思密切相关 (即，默认模式网络和显著网络)。此外，认知任务将在考试前和考试前进行 干预后评估通过正念训练可能增强的注意力控制能力。最后， 正念技能和沉思的变化将通过基于智能手机的生态瞬间进行评估 由PI的实验室开发的评估(EMA)协议。首先，我们将测试(1)大脑功能的变化 连通性、(2)注意力控制和(3)正念技能的获得和使用在组间起中介作用 (例如，应用程序与对照)减少沉思的差异。第二，我们将测试一台机器是否 结合基线临床、人口学和心理社会特征的学习模型可用于 确定哪些青少年预计将从基于APP的正念训练中受益。的最新进展 机器学习允许开发在个人层面预测结果的算法，以及 整合众多的预测因素，而不是依赖单一的变量，这些变量可能会孤立地限制 临床--有用的预测价值。最终，这样的算法可能会为个人的风险收益评估提供信息 它可以用来客观地传达经历正面和负面结果的概率 用户在使用正念应用程序之前。总体而言，结果有望推动(1)我们的 了解基于APP的正念有益效果的潜在机制 培训和(2)我们预测哪些青少年适合使用这些日益流行的应用程序的能力。

Project Summary/Abstract Mindfulness-based smartphone apps have surged in popularity in recent years. Headspace – among the most popular of these platforms – has over 42 million users. Recent surveys indicate that 11% of U.S. adolescents have used mindfulness apps as a means of coping with anxiety or depressive symptoms, which increase substantially during the adolescent years. A growing body of research implicates rumination as being a transdiagnostic risk factor involved in the development of depression and anxiety in youth. Critically, mindfulness meditation has shown significant promise in targeting rumination, and ultimately improving depressive and anxiety symptoms. Mindfulness apps offer a convenient and cost-effective means for accessing mindfulness training, while being interactive and engaging for youth. Despite their growing popularity among teens, strikingly little research has been conducted on these apps. Two critical questions have yet to be addressed, which are strongly aligned with the NCCIH Strategic Plan: (1) what are the underlying neural and cognitive mechanisms that account for the beneficial effects of these apps and (2) for whom is app-based mindfulness well-suited. To address these gaps, adolescents (ages 13-18) will be randomly assigned to an app-delivered mindfulness course vs. an active control condition and will complete pre- and post-intervention resting state functional magnetic resonance imaging (fMRI) scans to probe static and dynamic functional connectivity within – and between – brain networks strongly implicated in mindfulness training and rumination (i.e., Default Mode Network and Salience Network). In addition, cognitive tasks will be administered at pre- and post-intervention to assess attentional control abilities putatively enhanced by mindfulness training. Finally, mindfulness skills and changes in rumination will be assessed via a smartphone-based ecological momentary assessment (EMA) protocol developed in the PI’s lab. First, we will test whether changes in (1) brain functional connectivity, (2) attentional control and (3) acquisition and use of mindfulness skills mediate between-group (i.e., app vs. control) differences in the reduction of rumination. Second, we will test whether a machine learning model incorporating baseline clinical, demographic, and psychosocial characteristics can be used to identify which adolescents are predicted to benefit from app-based mindfulness training. Recent advances in machine learning allow for the development of algorithms predicting outcome at the individual level, as well as the integration of numerous predictors rather than relying on single variables that may, in isolation, have limited clinically-useful predictive value. Ultimately, such an algorithm may inform individual risk-benefit assessments that could be used to objectively communicate the probability of experiencing positive vs. adverse outcomes to users prior to engaging with a mindfulness app. Collectively, results are expected to advance (1) our understanding of the underlying mechanisms that account for the beneficial effects of app-based mindfulness training and (2) our ability to predict which adolescents are well-suited to these increasingly popular apps.