An Empathy-Driven, Conversational Artificial Intelligence Agent (Wysa) for Digital Mental Well-Being: Real-World Data Evaluation Mixed-Methods Study.
An Empathy-Driven, Conversational Artificial Intelligence Agent (Wysa) for Digital Mental Well-Being: Real-World Data Evaluation Mixed-Methods Study.
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DOI：
10.2196/12106
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发表时间：
2018-11-23
影响因子：
5
通讯作者：
Subramanian V
中科院分区：
文献类型：
--
作者：
Inkster B;Sarda S;Subramanian V
世界卫生组织2017年的一份报告指出，重度抑郁症影响了近5%的人口。重度抑郁症与心理社会功能受损和生活质量下降有关。心理健康人员短缺、等待时间长、被认为是耻辱和政府开支较低等挑战构成了缓解心理健康问题的障碍。单独的面对面心理治疗只能提供时间点的支持，无法快速扩展以应对这一日益增长的全球公共卫生挑战。支持人工智能（AI）、富有同情心和证据驱动的会话式移动的应用程序技术可以通过提高采用率和实现覆盖率，在填补这一空白方面发挥积极作用。虽然这种技术可以帮助管理这些障碍，但他们永远不应该用医疗保健专业人员来代替更严重的心理健康问题。然而，应用程序技术可以作为补充或中间支持系统。移动的心理健康应用程序需要维护隐私，并促进短期和长期的积极成果。本研究旨在提供一个初步的真实世界数据评估的有效性和参与水平的人工智能，移情，基于文本的会话移动的心理健康应用程序，Wysa，对用户自我报告的抑郁症状。在这项研究中，观察了一组匿名的全球用户，他们自愿安装了Wysa应用程序，参与了基于文本的消息传递，并使用患者健康问卷9自我报告了抑郁症状。根据2个连续筛选时间点上和之间的应用程序使用程度，出现了2个不同的用户组（高用户和低用户）。该研究使用混合方法来评估这些用户的影响和参与程度。定量分析通过比较高用户和低用户之间抑郁症状的平均改善来衡量应用程序的影响。定性分析通过分析应用内用户反馈来衡量应用参与度和体验，并评估机器学习分类器在对话期间检测用户异议的性能。平均情绪改善（即，两组之间自我报告抑郁评分前后的差异）（即，高与低用户; n=108和n=21，分别）显示，高用户组有显着较高的平均改善，（平均5.84 [SD 6.66]）与低使用者组（平均3.52 [SD 6.15]）相比; Mann-Whitney P= 0.03，中等效应量为0.63。此外，67.7%的用户反馈认为应用程序体验是有益和令人鼓舞的。关于Wysa应用程序对自我报告有抑郁症状的用户的有效性和参与度的真实数据评估结果显示出希望。然而，需要进一步的工作，以验证这些初步调查结果在更大的样本和更长的时间。
A World Health Organization 2017 report stated that major depression affects almost 5% of the human population. Major depression is associated with impaired psychosocial functioning and reduced quality of life. Challenges such as shortage of mental health personnel, long waiting times, perceived stigma, and lower government spends pose barriers to the alleviation of mental health problems. Face-to-face psychotherapy alone provides only point-in-time support and cannot scale quickly enough to address this growing global public health challenge. Artificial intelligence (AI)-enabled, empathetic, and evidence-driven conversational mobile app technologies could play an active role in filling this gap by increasing adoption and enabling reach. Although such a technology can help manage these barriers, they should never replace time with a health care professional for more severe mental health problems. However, app technologies could act as a supplementary or intermediate support system. Mobile mental well-being apps need to uphold privacy and foster both short- and long-term positive outcomes. This study aimed to present a preliminary real-world data evaluation of the effectiveness and engagement levels of an AI-enabled, empathetic, text-based conversational mobile mental well-being app, Wysa, on users with self-reported symptoms of depression. In the study, a group of anonymous global users were observed who voluntarily installed the Wysa app, engaged in text-based messaging, and self-reported symptoms of depression using the Patient Health Questionnaire-9. On the basis of the extent of app usage on and between 2 consecutive screening time points, 2 distinct groups of users (high users and low users) emerged. The study used mixed-methods approach to evaluate the impact and engagement levels among these users. The quantitative analysis measured the app impact by comparing the average improvement in symptoms of depression between high and low users. The qualitative analysis measured the app engagement and experience by analyzing in-app user feedback and evaluated the performance of a machine learning classifier to detect user objections during conversations. The average mood improvement (ie, difference in pre- and post-self-reported depression scores) between the groups (ie, high vs low users; n=108 and n=21, respectively) revealed that the high users group had significantly higher average improvement (mean 5.84 [SD 6.66]) compared with the low users group (mean 3.52 [SD 6.15]); Mann-Whitney P=.03 and with a moderate effect size of 0.63. Moreover, 67.7% of user-provided feedback responses found the app experience helpful and encouraging. The real-world data evaluation findings on the effectiveness and engagement levels of Wysa app on users with self-reported symptoms of depression show promise. However, further work is required to validate these initial findings in much larger samples and across longer periods.
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影响因子：
3.7
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