Kahler Christopher W, Lechner William J, MacGlashan James, Wray Tyler B, Littman Michael L
Center for Alcohol and Addiction Studies, Department of Behavioral and Social Sciences, Brown University School of Public Health, Providence, RI, United States.
Brown University, Computer Science Department, Providence, RI, United States.
JMIR Ment Health. 2017 Jun 28;4(2):e25. doi: 10.2196/mental.7571.
Computer-delivered interventions have been shown to be effective in reducing alcohol consumption in heavy drinking college students. However, these computer-delivered interventions rely on mouse, keyboard, or touchscreen responses for interactions between the users and the computer-delivered intervention. The principles of motivational interviewing suggest that in-person interventions may be effective, in part, because they encourage individuals to think through and speak aloud their motivations for changing a health behavior, which current computer-delivered interventions do not allow.
The objective of this study was to take the initial steps toward development of a voice-based computer-delivered intervention that can ask open-ended questions and respond appropriately to users' verbal responses, more closely mirroring a human-delivered motivational intervention.
We developed (1) a voice-based computer-delivered intervention that was run by a human controller and that allowed participants to speak their responses to scripted prompts delivered by speech generation software and (2) a text-based computer-delivered intervention that relied on the mouse, keyboard, and computer screen for all interactions. We randomized 60 heavy drinking college students to interact with the voice-based computer-delivered intervention and 30 to interact with the text-based computer-delivered intervention and compared their ratings of the systems as well as their motivation to change drinking and their drinking behavior at 1-month follow-up.
Participants reported that the voice-based computer-delivered intervention engaged positively with them in the session and delivered content in a manner consistent with motivational interviewing principles. At 1-month follow-up, participants in the voice-based computer-delivered intervention condition reported significant decreases in quantity, frequency, and problems associated with drinking, and increased perceived importance of changing drinking behaviors. In comparison to the text-based computer-delivered intervention condition, those assigned to voice-based computer-delivered intervention reported significantly fewer alcohol-related problems at the 1-month follow-up (incident rate ratio 0.60, 95% CI 0.44-0.83, P=.002). The conditions did not differ significantly on perceived importance of changing drinking or on measures of drinking quantity and frequency of heavy drinking.
Results indicate that it is feasible to construct a series of open-ended questions and a bank of responses and follow-up prompts that can be used in a future fully automated voice-based computer-delivered intervention that may mirror more closely human-delivered motivational interventions to reduce drinking. Such efforts will require using advanced speech recognition capabilities and machine-learning approaches to train a program to mirror the decisions made by human controllers in the voice-based computer-delivered intervention used in this study. In addition, future studies should examine enhancements that can increase the perceived warmth and empathy of voice-based computer-delivered intervention, possibly through greater personalization, improvements in the speech generation software, and embodying the computer-delivered intervention in a physical form.
计算机辅助干预已被证明在减少重度饮酒大学生的酒精摄入量方面是有效的。然而,这些计算机辅助干预依赖鼠标、键盘或触摸屏响应来实现用户与计算机辅助干预之间的交互。动机性访谈的原则表明,面对面干预可能有效,部分原因是它鼓励个体深入思考并大声说出改变健康行为的动机,而当前的计算机辅助干预不具备这一点。
本研究的目的是朝着开发一种基于语音的计算机辅助干预迈出第一步,该干预可以提出开放式问题并对用户的口头回答做出适当回应,更紧密地模拟人工进行的动机性干预。
我们开发了(1)一种由人工控制器运行的基于语音的计算机辅助干预,它允许参与者对语音生成软件提供的预设提示说出自己的回答;以及(2)一种基于文本的计算机辅助干预,所有交互都依赖鼠标、键盘和计算机屏幕。我们将60名重度饮酒大学生随机分组,让其中一组与基于语音的计算机辅助干预进行交互,另一组30人与基于文本的计算机辅助干预进行交互,并比较他们对系统的评分,以及在1个月随访时他们改变饮酒行为的动机和饮酒行为。
参与者报告说,基于语音的计算机辅助干预在会话中与他们进行了积极互动,并以符合动机性访谈原则的方式提供内容。在1个月随访时,基于语音的计算机辅助干预组的参与者报告与饮酒相关的量、频率和问题显著减少,并且对改变饮酒行为的重要性的认知有所增加。与基于文本的计算机辅助干预组相比,被分配到基于语音的计算机辅助干预组的参与者在1个月随访时报告的与酒精相关的问题明显更少(发生率比为0.60,95%置信区间为0.44 - 0.83,P = 0.002)。两组在对改变饮酒的重要性认知、饮酒量以及重度饮酒频率的测量方面没有显著差异。
结果表明,构建一系列开放式问题、一组回答和后续提示是可行的,这些可用于未来完全自动化的基于语音的计算机辅助干预,该干预可能更紧密地模拟人工进行的动机性干预以减少饮酒。此类努力将需要利用先进的语音识别能力和机器学习方法来训练一个程序,以模拟本研究中基于语音的计算机辅助干预中人工控制器所做出的决策。此外,未来的研究应该考察如何增强基于语音的计算机辅助干预的感知温暖度和同理心,可能通过更大程度的个性化、语音生成软件的改进以及将计算机辅助干预以实体形式呈现来实现。