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测试计算机化认知训练对年轻抑郁症患者的作用机制:一项双盲、随机、对照治疗试验方案

Testing the Mechanism of Action of Computerized Cognitive Training in Young Adults with Depression: Protocol for a Blinded, Randomized, Controlled Treatment Trial.

作者信息

Rushia Sara N, Schiff Sophie, Egglefield Dakota A, Motter Jeffrey N, Grinberg Alice, Saldana Daniel G, Shehab Al Amira Safa, Fan Jin, Sneed Joel R

机构信息

Department of Psychology, The Graduate Center, City University of New York, New York, NY 10016, USA.

Department of Psychology, Queens College, City University of New York, Flushing, NY 11367, USA.

出版信息

J Psychiatr Brain Sci. 2020;5. doi: 10.20900/jpbs.20200014. Epub 2020 Jun 19.

Abstract

BACKGROUND

Depression is associated with a broad range of cognitive deficits, including processing speed (PS) and executive functioning (EF). Cognitive symptoms commonly persist with the resolution of affective symptoms and increase risk of relapse and recurrence. The cognitive control network is comprised of brain areas implicated in EF and mood regulatory functions. Prior research has demonstrated the effectiveness of computerized cognitive training (CCT) focused on PS and EF in mitigating both cognitive and affective symptoms of depression.

METHODS

Ninety participants aged 18-29 with a current diagnosis of major depressive disorder or persistent depressive disorder, or a Hamilton Depression Rating Scale score ≥12, will be randomized to either PS/EF CCT, verbal CCT, or waitlist control. Participants in the active groups will complete 15 min of training 5 days/week for 8 weeks. Clinical and neuropsychological assessments will be completed at baseline, week 4, week 8, and 3-month follow-up. Structural and functional magnetic resonance imaging (fMRI) will be completed at baseline and week 8. We will compare changes in mood, cognition, daily functioning, and fMRI data. We will explore cognitive control network functioning using resting-state and task-based fMRI.

RESULTS

Recruitment began in October 2019; we expect to finish recruitment by April 2022 and subsequently begin data analysis.

CONCLUSIONS

This study is innovative in that it will include both active and waitlist control conditions and will explore changes in neural activation. Identifying the neural networks associated with improvements following CCT will allow for the development of more precise and effective interventions.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03869463; https://clinicaltrials.gov/ct2/show/NCT03869463.

摘要

背景

抑郁症与广泛的认知缺陷有关,包括处理速度(PS)和执行功能(EF)。认知症状通常会随着情感症状的缓解而持续存在,并增加复发和再发的风险。认知控制网络由与执行功能和情绪调节功能相关的脑区组成。先前的研究表明,专注于处理速度和执行功能的计算机化认知训练(CCT)在减轻抑郁症的认知和情感症状方面是有效的。

方法

90名年龄在18 - 29岁之间、目前诊断为重度抑郁症或持续性抑郁症、或汉密尔顿抑郁量表评分≥12的参与者将被随机分为处理速度/执行功能计算机化认知训练组、言语计算机化认知训练组或等待列表对照组。活跃组的参与者将每周5天、每天完成15分钟的训练,持续8周。临床和神经心理学评估将在基线、第4周、第8周和3个月随访时完成。结构和功能磁共振成像(fMRI)将在基线和第8周时完成。我们将比较情绪、认知、日常功能和fMRI数据的变化。我们将使用静息态和基于任务的fMRI来探索认知控制网络的功能。

结果

招募工作于2019年10月开始;我们预计到2022年4月完成招募,随后开始数据分析。

结论

本研究的创新之处在于它将包括活跃组和等待列表对照组,并将探索神经激活的变化。确定与计算机化认知训练后改善相关的神经网络将有助于开发更精确、有效的干预措施。

试验注册

ClinicalTrials.gov NCT03869463;https://clinicaltrials.gov/ct2/show/NCT03869463

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