Embodied Conversational Agents in Clinical Psychology: A Scoping Review.
Embodied Conversational Agents in Clinical Psychology: A Scoping Review.
复制标题
DOI：
10.2196/jmir.6553
复制
发表时间：
2017-05-09
影响因子：
7.4
通讯作者：
Riper H
中科院分区：
文献类型：
--
作者：
Provoost S;Lau HM;Ruwaard J;Riper H
具体对话代理（eca）是计算机生成的角色，模拟人类面对面对话的关键属性，如语言和非语言行为。在基于互联网的电子卫生干预措施中，eca可用于提供自动化的人为支持因素。我们的目标是概述ECA在临床心理学中的应用的技术和临床可能性以及证据基础，以便向卫生专业人员介绍这一研究领域的活动。考虑到ECA研究中涉及的各种应用方法、应用类型和科学学科，我们进行了系统的范围审查。范围审查的目的是绘制一个研究领域的关键概念和证据类型，并回答比传统的系统审查不太具体的问题。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，系统地搜索了ECA在治疗情绪、焦虑、精神病、自闭症谱系和物质使用障碍方面的应用。如果研究传达了针对其中一种疾病的ECA申请的初步研究结果，则纳入研究。我们绘制了每项研究的背景信息，不同的疾病是如何处理的，eca和使用者如何相互作用，方法方面，以及研究的目标和结果。本研究纳入N=54篇出版物（N=49篇研究）。超过一半的研究（n=26）集中在自闭症治疗上，eca最常用于社交技能训练（n=23）。应用范围从简单的通过情感表达加强社会行为到复杂的多模态会话系统。大多数应用程序（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，例如减轻症状严重程度。针对精神障碍的eca正在出现。在非洲经委会的研究中，正在越来越多地考虑和采用最先进的技术，例如通过自然语言或非语言行为进行交流，并取得了有希望的结果。然而，关于其临床应用的证据仍然很少。目前，它们对临床实践的价值主要在于关键人的支持因素的实验确定。在使用eca作为现有干预措施的辅助手段以支持用户的背景下，关于eca与用户互动的个性化以及提供支持的最佳时机和方式的重要问题仍然存在。为了增加有关互联网干预的证据基础，我们建议额外关注可快速开发、测试和应用于日常实践的低技术ECA解决方案。
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.