A fully automated conversational agent for promoting mental well-being: A pilot RCT using mixed methods.
A fully automated conversational agent for promoting mental well-being: A pilot RCT using mixed methods.
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DOI：
10.1016/j.invent.2017.10.002
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发表时间：
2017-12
期刊：
影响因子：
--
通讯作者：
Andersson G
中科院分区：
文献类型：
--
作者：
Ly KH;Ly AM;Andersson G
全自动自助干预措施可以作为大量人的高成本效益的心理健康促进工具。然而，这些干预措施的特点往往是依从性差。解决这个问题的一种方法是通过会话代理来模仿治疗支持。本研究的目的是评估智能手机应用程序的有效性和依从性，通过自动聊天机器人（Shim）为非临床人群提供积极心理学和CBT干预措施中使用的策略-以及探索参与者与此聊天机器人互动的观点和体验。共有28名参与者被随机分配到聊天机器人干预组（n = 14）或等待列表对照组（n = 14）。研究结果显示，与等待名单对照组相比，坚持干预的参与者（n = 13）显示出组和时间对心理健康（FS）和感知压力（PSS-10）的显着交互作用，效果大小（Cohen d范围为0.14-1.06）从小到大。此外，参与者在为期2周的干预期间表现出很高的参与度，整个期间平均打开应用程序的比例为17.71次。与其他声称具有高度吸引力的全自动干预研究（如Woebot和Panoply应用程序）相比，这一比例更高。据我们所知，定性数据揭示了以前没有发现的子主题，例如聊天机器人的调节格式。本研究的结果，特别是良好的依从率，验证了将来使用更大的样本量和活性对照组复制本研究的有用性。这一点很重要，因为寻找全自动、高度参与和有效的数字自助干预措施来促进心理健康对公共卫生至关重要。据我们所知，这是第一个通过对话代理促进非临床人群心理健康的RCT。完成者分析显示，与对照组相比，幸福感和感知压力有显着的相互作用。参与者表现出很高的参与度，在干预期间平均打开应用程序的比率为17.71次。定性数据为聊天机器人添加了特定的重要知识，包括与用户建立关系的能力。结果验证了在未来的全面RCT中复制这种小规模试点研究的有用性。
Fully automated self-help interventions can serve as highly cost-effective mental health promotion tools for massive amounts of people. However, these interventions are often characterised by poor adherence. One way to address this problem is to mimic therapy support by a conversational agent. The objectives of this study were to assess the effectiveness and adherence of a smartphone app, delivering strategies used in positive psychology and CBT interventions via an automated chatbot (Shim) for a non-clinical population — as well as to explore participants' views and experiences of interacting with this chatbot. A total of 28 participants were randomized to either receive the chatbot intervention (n = 14) or to a wait-list control group (n = 14). Findings revealed that participants who adhered to the intervention (n = 13) showed significant interaction effects of group and time on psychological well-being (FS) and perceived stress (PSS-10) compared to the wait-list control group, with small to large between effect sizes (Cohen's d range 0.14–1.06). Also, the participants showed high engagement during the 2-week long intervention, with an average open app ratio of 17.71 times for the whole period. This is higher compared to other studies on fully automated interventions claiming to be highly engaging, such as Woebot and the Panoply app. The qualitative data revealed sub-themes which, to our knowledge, have not been found previously, such as the moderating format of the chatbot. The results of this study, in particular the good adherence rate, validated the usefulness of replicating this study in the future with a larger sample size and an active control group. This is important, as the search for fully automated, yet highly engaging and effective digital self-help interventions for promoting mental health is crucial for the public health. To our knowledge, this is the first RCT for promoting mental health in a non-clinical population via a conversational agent. Completer analysis showed significant interaction effects on well-being and perceived stress compared to a control group. Participants showed high engagement, with an average open app ratio of 17.71 times during the intervention. Qualitative data add important knowledge specific for a Chatbot, including the ability to build a relationship with its user. The results validated the usefulness of replicating this small-scale pilot study in a future full-scale RCT.
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