Study of a PST-trained voice-enabled artificial intelligence counselor for adults with emotional distress (SPEAC-2): Design and methods

IF 2 3区 医学 Q3 MEDICINE, RESEARCH & EXPERIMENTAL
Corina R. Ronneberg , Nan Lv , Olusola A. Ajilore , Thomas Kannampallil , Joshua Smyth , Vikas Kumar , Amruta Barve , Claudia Garcia , Sushanth Dosala , Nancy Wittels , Lan Xiao , Gbenga Aborisade , Aifeng Zhang , Zhengxin Tang , Jillian Johnson , Jun Ma
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引用次数: 0

Abstract

Background

Novel and scalable psychotherapies are urgently needed to address the depression and anxiety epidemic. Leveraging artificial intelligence (AI), a voice-based virtual coach named Lumen was developed to deliver problem solving treatment (PST). The first pilot trial showed promising changes in cognitive control measured by functional neuroimaging and improvements in depression and anxiety symptoms.

Methods

To further validate Lumen in a 3-arm randomized clinical trial, 200 participants with mild-to-moderate depression and/or anxiety will be randomly assigned in a 2:1:1 ratio to receive Lumen-coached PST, human-coached PST as active treatment comparison, or a waitlist control condition where participants can receive Lumen after the trial period. Participants will be assessed at baseline and 18 weeks. The primary aim is to confirm neural target engagement by testing whether compared with waitlist controls, Lumen participants will show significantly greater improvements from baseline to 18 weeks in the a priori neural target for cognitive control, right dorsal lateral prefrontal cortex engaged by the go/nogo task (primary superiority hypothesis). A secondary hypothesis will test whether compared with human-coached PST participants, Lumen participants will show equivalent improvements (i.e., noninferiority) in the same neural target from baseline to 18 weeks. The second aim is to examine (1) treatment effects on depression and anxiety symptoms, psychosocial functioning, and quality of life outcomes, and (2) relationships of neural target engagement to these patient-reported outcomes.

Conclusions

This study offers potential to improve the reach and impact of psychotherapy, mitigating access, cost, and stigma barriers for people with depression and/or anxiety.

Clinicaltrials.gov #: NCT05603923

针对有情绪困扰的成年人的 PST 培训语音人工智能顾问研究(SPEAC-2):设计与方法。
背景:为解决抑郁症和焦虑症的流行问题,迫切需要新颖且可扩展的心理疗法。利用人工智能(AI),我们开发了一种名为 "Lumen "的语音虚拟教练,用于提供问题解决治疗(PST)。首次试点试验显示,通过功能神经影像学测量,认知控制发生了可喜的变化,抑郁和焦虑症状也有所改善:为了在三臂随机临床试验中进一步验证 Lumen,200 名患有轻度至中度抑郁症和/或焦虑症的参与者将按 2:1:1 的比例被随机分配到接受 Lumen 指导的 PST、作为积极治疗对比的人类指导的 PST 或等待对照条件(参与者可在试验期结束后接受 Lumen 治疗)。参与者将在基线和 18 周时接受评估。主要目的是通过测试与候补对照组相比,Lumen 参与者从基线到 18 周是否会在认知控制的先验神经目标(go/nogo 任务所涉及的右背外侧前额叶皮层)上表现出显著的改善,从而确认神经目标的参与情况(主要优越性假设)。次要假设将检验与接受人类教练指导的 PST 参与者相比,Lumen 参与者从基线到 18 周是否会在相同的神经目标上表现出同等的改善(即非劣势)。第二个目的是检查(1)对抑郁和焦虑症状、社会心理功能和生活质量结果的治疗效果,以及(2)神经目标参与与这些患者报告结果之间的关系:这项研究有望提高心理治疗的覆盖面和影响力,减轻抑郁症和/或焦虑症患者在获得治疗、费用和耻辱感方面的障碍。
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来源期刊
CiteScore
3.70
自引率
4.50%
发文量
281
审稿时长
44 days
期刊介绍: Contemporary Clinical Trials is an international peer reviewed journal that publishes manuscripts pertaining to all aspects of clinical trials, including, but not limited to, design, conduct, analysis, regulation and ethics. Manuscripts submitted should appeal to a readership drawn from disciplines including medicine, biostatistics, epidemiology, computer science, management science, behavioural science, pharmaceutical science, and bioethics. Full-length papers and short communications not exceeding 1,500 words, as well as systemic reviews of clinical trials and methodologies will be published. Perspectives/commentaries on current issues and the impact of clinical trials on the practice of medicine and health policy are also welcome.
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