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Smartphone-based meditation training to reduce adolescent depression

Smartphone-based meditation training to reduce adolescent depression
基于智能手机的冥想训练可减少青少年抑郁
批准号:
10664427
负责人:
Matthew Hirshberg
金额:
$13.5万
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-07-07 至 2027-06-30

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中文摘要
翻译
项目摘要/摘要 尽管有强有力的证据表明(A)抑郁在青春期急剧上升,(B)心理健康在青春期 青春期预示着终生轨迹,(C)以冥想为基础的干预(Mbi)可减少抑郁 青少年人群的症状、获得和研究mbi的机会有限。移动医疗(MHealth) Mbi的交付提供了可获得性、可负担性和个性化的承诺。关于移动健康的研究 成人的MBIS表明,这些方案在减轻抑郁方面是可行的、可接受的、安全的和有效的 症状。加上对行为和心理生理学(即个人)的动态评估的进展 传感数据)通过可穿戴设备、mHealth和个人传感数据代表了 干预研究和精神卫生保健。尽管移动健康技术在当今世界无处不在 在青少年中,几乎没有关于青少年mHealth mbi的研究,也没有研究整合 使用个人传感数据的mHealth MBI交付。拟议的职业发展奖开始 通过培养候选人进行临床研究的技能来解决这一知识差距 青少年样本、个人感觉数据和先进的调解方法,以确定 变化。这项新的训练将被用于对150名患有重度抑郁的青少年样本的研究 症状,即有强有力的初步疗效证据的mHealth MBI的影响。参与者将是 随机分配给mHealth MBI或等待列表控制条件。目标1将评估可行性, 抑郁青少年接受为期8周的mHealth MBI的可接受性和安全性。目标2将初步评估 在减少抑郁症状方面的计划效果。目标3将描述心理特征(即,坚持不懈 思考、认知距离、孤独)、行为(即通过地理位置数据进行社会隔离),以及 心理生理(即,通过可穿戴设备的睡眠质量和心率指标)对抑郁的中介作用 症状采用先进的结构方程建模方法。这些方法将提供初步的 干预效果的证据,同时潜在地确定多个层面的变化机制 分析,为规划未来的大规模随机对照试验提供关键数据。所有的目标都将是 在临床研究基础方面的说明性、体验性和指导性培训 由美国国立卫生研究院资助的临床和翻译研究所(卢旺达问题国际法庭)和健康心理中心。目标3 将通过在个人感知数据和高级调解方法方面的新培训来促进,并由 在这些领域拥有丰富专业知识的导师团队。综合起来,本研究所的研究目标和培训目标 该项目旨在促进可获得、可接受、安全和有效的mHealth mbi的发展 治疗并最终预防青少年抑郁症。这一奖项将使候选人能够进行 未来的干预和机制研究旨在减轻青少年抑郁的负担。
英文摘要
Project Summary / Abstract Despite robust evidence that (a) depression rises precipitously during adolescence, (b) mental health during adolescence predicts lifelong trajectories, and (c) meditation-based interventions (MBIs) reduce depressive symptoms, access to and research on MBIs in adolescent populations is limited. Mobile health (mHealth) delivery of MBIs offers the promise of accessibility, affordability, and personalization. Research on mHealth MBIs in adults indicates these programs are feasible, acceptable, safe, and effective in reducing depressive symptoms. Coupled with advances in ambulatory assessment of behavior and psychophysiology (i.e., personal sensing data) through wearable devices, mHealth and personal sensing data represent a new frontier in intervention research and mental health care. Although mHealth technologies are ubiquitous for today’s adolescents, there is virtually no research on mHealth MBIs in adolescents and no research integrating mHealth MBI delivery with personal sensing data. The proposed Career Development Award begins to address this knowledge gap by developing the candidate’s skills to conduct research involving clinical adolescent samples, personal sensing data, and advanced mediation methods to identify mechanisms of change. This new training will be leveraged to study, in a sample of 150 adolescents with elevated depressive symptoms, the impact of a mHealth MBI that has strong preliminary evidence of efficacy. Participants will be randomly assigned to the mHealth MBI or to a wait-list control condition. Aim 1 will assess the feasibility, acceptability, and safety of the 8-week mHealth MBI in depressed adolescents. Aim 2 will preliminarily assess program efficacy in reducing depressive symptoms. Aim 3 will characterize psychological (i.e., perseverative thinking, cognitive distancing, loneliness), behavioral (i.e., social isolation via geolocation data), and psychophysiological (i.e., sleep quality and heart rate metrics via wearable) mediator effects on depressive symptoms using advanced structural equation modeling methods. These methods will provide preliminary evidence of intervention efficacy while potentially identifying mechanisms of change at multiple levels of analysis, providing critical data for planning future, large-scale randomized controlled trials. All aims will be supported by didactic, experiential, and mentored training in the fundamentals of clinical research through the NIH-funded Institute for Clinical and Translational Research (ICTR) and the Center for Healthy Minds. Aim 3 will be facilitated by new training in personal sensing data and advanced mediation methods, supported by a mentor team with extensive expertise in these domains. Combined, the research aims and training goals of this project seek to promote the development of accessible, acceptable, safe, and effective mHealth MBIs for the treatment and ultimately prevention of adolescent depression. This award will enable the candidate to conduct future intervention and mechanism research aimed at reducing the burden of depression in adolescents.
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