基于网络的自主引导式干预措施:关于用户需求及具身对话代理满足这些需求潜力的范围综述。
Self-Guided Web-Based Interventions: Scoping Review on User Needs and the Potential of Embodied Conversational Agents to Address Them.
作者信息
Scholten Mark R, Kelders Saskia M, Van Gemert-Pijnen Julia Ewc
机构信息
Centre for eHealth & Wellbeing Research, Department of Psychology, Health and Technology, University of Twente, Enschede, Netherlands.
Optentia Research Focus Area, North-West University, Vanderbijlpark, South Africa.
出版信息
J Med Internet Res. 2017 Nov 16;19(11):e383. doi: 10.2196/jmir.7351.
BACKGROUND
Web-based mental health interventions have evolved from innovative prototypes to evidence-based and clinically applied solutions for mental diseases such as depression and anxiety. Open-access, self-guided types of these solutions hold the promise of reaching and treating a large population at a reasonable cost. However, a considerable factor that currently hinders the effectiveness of these self-guided Web-based interventions is the high level of nonadherence. The absence of a human caregiver apparently has a negative effect on user adherence. It is unknown to what extent this human support can be handed over to the technology of the intervention to mitigate this negative effect.
OBJECTIVE
The first objective of this paper was to explore what is known in literature about what support a user needs to stay motivated and engaged in an electronic health (eHealth) intervention that requires repeated use. The second objective was to explore the current potential of embodied conversational agents (ECAs) to provide this support.
METHODS
This study reviews and interprets the available literature on (1) support within eHealth interventions that require repeated use and (2) the potential of ECAs by means of a scoping review. The rationale for choosing a scoping review is that the subject is broad, diverse, and largely unexplored. Themes for (1) and (2) were proposed based on grounded theory and mapped on each other to find relationships.
RESULTS
The results of the first part of this study suggest the presence of user needs that largely remain implicit and unaddressed. These support needs can be categorized as task-related support and emotion-related support. The results of the second part of this study suggest that ECAs are capable of engaging and motivating users of information technology applications in the domains of learning and behavioral change. Longitudinal studies must be conducted to determine under what circumstances ECAs can create and maintain a productive user relationship. Mapping the user needs on the ECAs' capabilities suggests that different kinds of ECAs may provide different solutions for improving the adherence levels.
CONCLUSIONS
Autonomous ECAs that do not respond to a user's expressed emotion in real time but take on empathic roles may be sufficient to motivate users to some extent. It is unclear whether those types of ECAs are competent enough and create sufficient believability among users to address the user's deeper needs for support and empathy. Responsive ECAs may offer a better solution. However, at present, most of these ECAs have difficulties to assess a user's emotional state in real time during an open dialogue. By conducting future research with relationship theory-based ECAs, the added value of ECAs toward user needs can be better understood.
背景
基于网络的心理健康干预已从创新原型发展成为针对抑郁症和焦虑症等精神疾病的循证且临床应用的解决方案。这些开放获取、自我引导型的解决方案有望以合理成本覆盖并治疗大量人群。然而,目前阻碍这些自我引导型基于网络的干预效果的一个重要因素是高不依从率。缺少人工护理者显然对用户的依从性有负面影响。尚不清楚这种人工支持能在多大程度上转交给干预技术以减轻这种负面影响。
目的
本文的首要目标是探究文献中关于用户在需要反复使用的电子健康(eHealth)干预中保持动力和参与度所需支持的内容。第二个目标是探究具身对话代理(ECA)提供这种支持的当前潜力。
方法
本研究通过范围综述对关于(1)需要反复使用的eHealth干预中的支持以及(2)ECA的潜力的现有文献进行回顾和解读。选择范围综述的理由是该主题广泛、多样且在很大程度上未被探索。基于扎根理论提出(1)和(2)的主题,并相互映射以寻找关系。
结果
本研究第一部分的结果表明存在很大程度上仍未明确且未得到解决的用户需求。这些支持需求可分为与任务相关的支持和与情感相关的支持。本研究第二部分的结果表明,ECA能够在学习和行为改变领域吸引并激励信息技术应用的用户。必须进行纵向研究以确定ECA在何种情况下能够建立并维持富有成效的用户关系。将用户需求映射到ECA的能力上表明,不同类型的ECA可能为提高依从性水平提供不同的解决方案。
结论
不实时响应用户表达的情感但扮演共情角色的自主ECA在一定程度上可能足以激励用户。尚不清楚这些类型的ECA是否足够胜任并在用户中建立足够的可信度以满足用户对支持和共情的更深层次需求。响应型ECA可能提供更好的解决方案。然而,目前,这些ECA中的大多数在开放对话期间难以实时评估用户的情绪状态。通过对基于关系理论的ECA进行未来研究,可以更好地理解ECA对用户需求的附加价值。