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An Approach-Avoidance, Computational Framework for Predicting Behavioral Therapy Outcome in Anxiety and Depression

An Approach-Avoidance, Computational Framework for Predicting Behavioral Therapy Outcome in Anxiety and Depression
预测焦虑和抑郁行为治疗结果的避免接近计算框架
批准号:
10651737
负责人:
ROBIN L AUPPERLE
金额:
$53.01万
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
未结题
起止时间:
2020-07-01 至 2025-06-30

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中文摘要
翻译
项目总结 抑郁症和焦虑症高度并存,排在导致多年生活的十大原因之列。 残疾。目前的黄金标准疗法是有效的,但效果并不像我们希望的那样好, 超过50%的人正在经历长期的改善。两种治疗抑郁症的金标准行为干预 焦虑包括行为激活,专注于增强接近有意义和 加强活动,以暴露为基础的治疗,重点是减少回避和挑战负面影响 通过暴露在令人焦虑的线索或情况下而产生的期望。虽然这些干预措施已经 不同的治疗方法与回避治疗靶点,目前几乎没有知识来指导临床 决策,即告知在经常患有焦虑的情况下应提供哪些策略 和抑郁症状。接近-回避决策范式侧重于评估神经和 面对潜在奖励和威胁时的行为反应,利用尽管是 对焦虑和抑郁以及行为激活和基于暴露的治疗都很重要。 在这项研究中,我们将招募同时报告焦虑和抑郁症状的个体,并 将他们随机分为在小组环境中提供的三种不同心理治疗干预措施之一,包括 (1)行为激活;(2)暴露疗法;(3)支持性疗法 心理治疗。参与者将完成临床、自我报告、行为和功能磁共振成像 治疗前后进行功能磁共振(FMRI)评估。临床症状也将在三个月和六个月内进行评估 在治疗完成后。我们将使用计算方法来模拟不同的因素, 在接近-回避决策过程中影响一个人的行为,包括避免威胁的动力与 对待奖励和信心,而不是一个人决策中的不确定性。 该项目将实现以下目标(1)确定大脑和行为的变化 接近-回避冲突中的反应与心理健康症状的变化有关,不同的 治疗方法,(2)确定基线大脑和行为反应的程度 方法-回避冲突预测对不同治疗方法的反应,高于和超过 人口统计学和基线症状严重程度的影响。 结果将增强我们对不同心理治疗方法(行为疗法)的理解 激活,基于暴露的治疗)可能会影响大脑的反应和决策,当面对潜在的 奖励与威胁、接近与回避的驱动力。此外,结果将具有重要的 关于更个性化的心理治疗方法的潜力的影响,增强 了解哪些类型的治疗策略可能对哪些个人最有益。
英文摘要
PROJECT SUMMARY Depression and anxiety disorders are highly comorbid and rank in the top ten causes of years lived with disability. Current gold-standard treatments are effective but do not work as well as we would like, with less than 50% experiencing long-lasting improvements. Two gold-standard behavioral interventions for depression and anxiety include behavioral activation, focused on enhancing approach behavior towards meaningful and reinforcing activities, and exposure-based therapy, focused on decreasing avoidance and challenging negative expectations through exposure to anxiety-provoking cues or situations. While these interventions have divergent approach versus avoidance treatment targets, there is currently little knowledge to guide clinical decision-making, i.e., to inform which strategies should be provided in the frequent case of comorbid anxiety and depression symptoms. Approach-avoidance decision-making paradigms focus on assessing neural and behavioral responses when faced with potential rewards and threats, tapping into processes though to be important for both anxiety and depression as well as behavioral activation and exposure-based therapy. For this study, we will recruit individuals reporting both anxiety and depression symptoms and randomize them to one of three different psychotherapeutic interventions delivered in a group setting, including (1) behavioral activation, (2) exposure-based therapy, and a non-specific therapy approach (3) supportive therapy. Participants will complete clinical, self-report, behavioral, and functional magnetic resonance imaging (fMRI) assessments before and after therapy. Clinical symptoms will also be assessed three and six months following therapy completion. We will use a computational approach to model the different factors that may influence one’s behavior during approach-avoidance decision-making, including drives to avoid threat versus approach reward and confidence versus uncertainty in one’s decisions. This project will accomplish the following aims (1) Determine how changes in brain and behavior responses during approach-avoidance conflict relate to changes in mental health symptoms with the different therapy approaches, (2) Determine the degree to which baseline brain and behavior responses during approach-avoidance conflict predict response to the different therapy approaches, above and beyond the influence of demographics and baseline symptom severity. Results will have enhance our understanding of how different psychotherapy approaches (behavioral activation, exposure-based therapy) may impact brain responses and decisions when faces with potential reward versus threat and approach versus avoidance drives. In addition, results will have important implications concerning the potential for a more personalized approach to psychotherapy, enhancing knowledge of which types of therapy strategies may be most beneficial for which individuals.
期刊论文(20)
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科研奖励(0)
会议论文
DOI: 10.1016/j.neuroimage.2020.117077
发表时间: 2020-10-15
期刊: NeuroImage
影响因子: 5.7
作者: [McDermott TJ, Kirlic N, Akeman E, Touthang J, Cosgrove KT, DeVille DC, Clausen AN, White EJ, Kuplicki R, Aupperle RL]
通讯作者: Aupperle RL
DOI: 10.1093/scan/nsac045
发表时间: 2023-02-23
期刊: SOCIAL COGNITIVE AND AFFECTIVE NEUROSCIENCE
影响因子: 4.2
作者: [White, Evan J., Demuth, Mara J., Nacke, Mariah, Kirlic, Namik, Kuplicki, Rayus, Spechler, Philip A., McDermott, Timothy J., DeVille, Danielle C., Stewart, Jennifer L., Lowe, John, Paulus, Martin P., Aupperle, Robin L.]
通讯作者: Aupperle, Robin L.
DOI: 10.1016/j.bbi.2021.05.023
发表时间: 2021-08
期刊: Brain, behavior, and immunity
影响因子: --
作者: [Cosgrove KT, Kuplicki R, Savitz J, Burrows K, Simmons WK, Khalsa SS, Teague TK, Aupperle RL, Paulus MP]
通讯作者: Paulus MP
DOI: 10.1038/s41598-021-91308-x
发表时间: 2021-06-03
期刊: Scientific reports
影响因子: 4.6
作者: [Smith R, Kirlic N, Stewart JL, Touthang J, Kuplicki R, McDermott TJ, Taylor S, Khalsa SS, Paulus MP, Aupperle RL]
通讯作者: Aupperle RL
共 17 条
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    An Approach-Avoidance, Computational Framework for Predicting Behavioral Therapy Outcome in Anxiety and Depression
    海外基金