Provoost Simon, Lau Ho Ming, Ruwaard Jeroen, Riper Heleen
Department of Clinical, Neuro & Developmental Psychology, Section Clinical Psychology, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.
EMGO Institute for Health and Care Research, VU University Medical Centre, Amsterdam, Netherlands.
J Med Internet Res. 2017 May 9;19(5):e151. doi: 10.2196/jmir.6553.
Embodied conversational agents (ECAs) are computer-generated characters that simulate key properties of human face-to-face conversation, such as verbal and nonverbal behavior. In Internet-based eHealth interventions, ECAs may be used for the delivery of automated human support factors.
We aim to provide an overview of the technological and clinical possibilities, as well as the evidence base for ECA applications in clinical psychology, to inform health professionals about the activity in this field of research.
Given the large variety of applied methodologies, types of applications, and scientific disciplines involved in ECA research, we conducted a systematic scoping review. Scoping reviews aim to map key concepts and types of evidence underlying an area of research, and answer less-specific questions than traditional systematic reviews. Systematic searches for ECA applications in the treatment of mood, anxiety, psychotic, autism spectrum, and substance use disorders were conducted in databases in the fields of psychology and computer science, as well as in interdisciplinary databases. Studies were included if they conveyed primary research findings on an ECA application that targeted one of the disorders. We mapped each study's background information, how the different disorders were addressed, how ECAs and users could interact with one another, methodological aspects, and the study's aims and outcomes.
This study included N=54 publications (N=49 studies). More than half of the studies (n=26) focused on autism treatment, and ECAs were used most often for social skills training (n=23). Applications ranged from simple reinforcement of social behaviors through emotional expressions to sophisticated multimodal conversational systems. Most applications (n=43) were still in the development and piloting phase, that is, not yet ready for routine practice evaluation or application. Few studies conducted controlled research into clinical effects of ECAs, such as a reduction in symptom severity.
ECAs for mental disorders are emerging. State-of-the-art techniques, involving, for example, communication through natural language or nonverbal behavior, are increasingly being considered and adopted for psychotherapeutic interventions in ECA research with promising results. However, evidence on their clinical application remains scarce. At present, their value to clinical practice lies mostly in the experimental determination of critical human support factors. In the context of using ECAs as an adjunct to existing interventions with the aim of supporting users, important questions remain with regard to the personalization of ECAs' interaction with users, and the optimal timing and manner of providing support. To increase the evidence base with regard to Internet interventions, we propose an additional focus on low-tech ECA solutions that can be rapidly developed, tested, and applied in routine practice.
具身对话代理（ECA）是计算机生成的角色，可模拟人类面对面交流的关键属性，如言语和非言语行为。在基于互联网的电子健康干预中，ECA可用于提供自动化的人际支持因素。
我们旨在概述ECA在临床心理学中的技术和临床可能性以及应用的证据基础，以便让健康专业人员了解该研究领域的进展。
鉴于ECA研究涉及多种应用方法、应用类型和科学学科，我们进行了一项系统的范围综述。范围综述旨在梳理某一研究领域的关键概念和证据类型，并回答比传统系统综述更宽泛的问题。我们在心理学和计算机科学领域的数据库以及跨学科数据库中系统检索了ECA在治疗情绪、焦虑、精神病、自闭症谱系障碍和物质使用障碍方面的应用。如果研究传达了针对上述某种障碍的ECA应用的初步研究结果，则将其纳入。我们梳理了每项研究的背景信息、针对不同障碍的处理方式、ECA与用户的交互方式、方法学方面以及研究目的和结果。
本研究纳入了N = 54篇出版物（N = 49项研究）。超过一半的研究（n = 26）聚焦于自闭症治疗，ECA最常用于社交技能训练（n = 23）。应用范围从通过情感表达简单强化社交行为到复杂的多模态对话系统。大多数应用（n = 43）仍处于开发和试点阶段，即尚未准备好进行常规实践评估或应用。很少有研究对ECA的临床效果进行对照研究，如症状严重程度的降低。
用于精神障碍的ECA正在兴起。在ECA研究的心理治疗干预中，越来越多地考虑并采用诸如通过自然语言或非言语行为进行交流等先进技术，并取得了有前景的结果。然而，关于其临床应用的证据仍然稀缺。目前，它们对临床实践的价值主要在于对关键人际支持因素的实验性确定。在将ECA用作现有干预措施的辅助手段以支持用户的背景下，关于ECA与用户交互的个性化以及提供支持的最佳时机和方式等重要问题仍然存在。为了增加关于互联网干预的证据基础，我们建议额外关注可快速开发、测试并应用于常规实践的低技术ECA解决方案。
