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

基于应用程序的青少年正念训练变化的机制和预测因素

• 批准号: 10651776
• 负责人: Christian Anthony Webb
• 金额: $ 62.76万
• 依托单位: MCLEAN HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-06-15 至 2026-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10651776
• 关键词: Accounting; Address; Adolescent; Adverse effects; Adverse event; Affective; Age; Algorithms; American; Anxiety; Attention; Brain; Cellular Phone; Characteristics; Clinical; Clinical Trials; Cognitive; Communication; Control Groups; Coupled; Development; Diagnostic; Ecological momentary assessment; Elasticity; Emotions; Goals; Grain; Individual; Intervention; Link; Machine Learning; Measures; Mediating; Mental Depression; Mindfulness Training; Modeling; National Center for Complementary and Integrative Health; Neurobiology; Online Systems; Outcome; Panic; Patient Self-Report; Pattern; Persons; Predictive Value; Prevalence; Probability; Prognosis; Protocols documentation; Randomized; Recommendation; Research; Research Activity; Rest; Risk Factors; Risk-Benefit Assessment; Sensitivity and Specificity; Strategic Planning; Surveys; Symptoms; Teenagers; Testing; Thinking; Work; Youth; active control; adverse outcome; algorithm development; anxiety symptoms; attentional control; cognitive task; coping; cost; cost effective; depressive symptoms; efficacy evaluation; experience; functional MRI scan; improved; kernel methods; machine learning algorithm; machine learning model; mindfulness; mindfulness meditation; neural; neuromechanism; outcome prediction; personalized medicine; personalized predictions; post intervention; predicting response; programs; psychosocial; rumination; skills; smartphone application

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.

项目概要/摘要 近年来，基于正念的智能手机应用程序迅速流行，是其中最受欢迎的应用程序之一。 这些平台中最受欢迎的——拥有超过 4200 万用户。最近的调查显示，11% 的美国青少年使用该平台。 使用正念应用程序作为应对焦虑或抑郁症状的手段，这些症状会增加 越来越多的研究表明，沉思是一种在青少年时期发生的现象。 至关重要的是，涉及青少年抑郁和焦虑发展的跨诊断危险因素。 正念冥想在针对沉思并最终改善 正念应用程序为治疗抑郁和焦虑症状提供了一种方便且经济有效的方法。 接受正念训练，同时对年轻人进行互动和参与，尽管它们越来越受欢迎。 在青少年中，对这些应用程序进行的研究少之又少，有两个关键问题尚未解决。 解决了这些问题，这些问题与 NCCIH 战略计划高度一致：(1) 潜在的神经和机制是什么？ 解释这些应用程序有益效果的认知机制，以及 (2) 基于应用程序的对象 为了解决这些差距，青少年（13-18 岁）将被随机分配到一个小组。 应用程序提供的正念课程与主动控制条件的比较，并将在干预前和干预后完成 静息态功能磁共振成像 (fMRI) 扫描可探测静态和动态功能 大脑网络内部和之间的连接与正念训练和沉思密切相关 （即默认模式网络和显着网络）此外，认知任务将在课前和课后进行管理。 干预后评估可能通过正念训练增强的注意力控制能力。 正念技能和沉思的变化将通过基于智能手机的生态瞬时评估 首先，我们将测试 (1) 大脑功能是否发生变化。 连通性、(2) 注意力控制和 (3) 获得和使用正念技能在群体之间进行调解 （即应用程序与控件）减少沉思的差异 其次，我们将测试机器是否存在差异。 结合基线临床、人口统计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应用程序的正念训练中受益。 机器学习允许开发预测个人水平结果的算法，以及 众多预测变量的整合，而不是依赖单个变量，这些变量单独来看可能会产生有限的影响 最终，这种算法可以为个人风险效益评估提供信息。 可以用来客观地传达经历积极结果与消极结果的概率 用户在使用正念应用程序之前，总体而言，结果预计会推进（1）我们的工作。 了解基于应用程序的正念产生有益影响的根本机制 培训和（2）我们预测哪些青少年适合这些日益流行的应用程序的能力。