Datasheet2_Understanding the impact of an AI-enabled conversational agent mobile app on users’ mental health and wellbeing with a self-reported maternal event: a mixed method real-world data mHealth study.docx

BackgroundMaternal mental health care is variable and with limited accessibility. Artificial intelligence (AI) conversational agents (CAs) could potentially play an important role in supporting maternal mental health and wellbeing. Our study examined data from real-world users who self-reported a maternal event while engaging with a digital mental health and wellbeing AI-enabled CA app (Wysa) for emotional support. The study evaluated app effectiveness by comparing changes in self-reported depressive symptoms between a higher engaged group of users and a lower engaged group of users and derived qualitative insights into the behaviors exhibited among higher engaged maternal event users based on their conversations with the AI CA.MethodsReal-world anonymised data from users who reported going through a maternal event during their conversation with the app was analyzed. For the first objective, users who completed two PHQ-9 self-reported assessments (n = 51) were grouped as either higher engaged users (n = 28) or lower engaged users (n = 23) based on their number of active session-days with the CA between two screenings. A non-parametric Mann–Whitney test (M–W) and non-parametric Common Language effect size was used to evaluate group differences in self-reported depressive symptoms. For the second objective, a Braun and Clarke thematic analysis was used to identify engagement behavior with the CA for the top quartile of higher engaged users (n = 10 of 51). Feedback on the app and demographic information was also explored.ResultsResults revealed a significant reduction in self-reported depressive symptoms among the higher engaged user group compared to lower engaged user group (M–W p = .004) with a high effect size (CL = 0.736). Furthermore, the top themes that emerged from the qualitative analysis revealed users expressed concerns, hopes, need for support, reframing their thoughts and expressing their victories and gratitude.ConclusionThese findings provide preliminary evidence of the effectiveness and engagement and comfort of using this AI-based emotionally intelligent mobile app to support mental health and wellbeing across a range of maternal events and experiences.

背景：母体心理健康护理存在差异，且可及性有限。人工智能（AI）对话代理（CAs）可能在支持母体心理健康及福祉方面发挥重要作用。本研究考察了在与数字心理健康及福祉AI赋能的对话应用（Wysa）互动过程中，自我报告母体事件的现实世界用户的数据。研究通过比较高参与度用户组与低参与度用户组在自我报告抑郁症状变化方面的差异，评估了应用的有效性，并基于与AI对话代理的对话，从高参与度母体事件用户的言行中提炼出定性洞见。方法：分析了报告在与应用对话过程中经历母体事件的用户的匿名真实世界数据。为实现第一个目标，完成了两次PHQ-9自我报告评估（n=51）的用户根据其与对话代理在两次筛查之间的活跃会话天数被分为高参与度用户组（n=28）或低参与度用户组（n=23）。使用非参数Mann-Whitney检验（M-W）和非参数共同语言效应量来评估两组在自我报告抑郁症状方面的差异。为实现第二个目标，对高参与度用户组前四分之一（n=51中的10人）与对话代理的互动行为进行了Braun和Clarke主题分析。同时，还探讨了应用反馈和人口统计学信息。结果：结果显示，与低参与度用户组相比，高参与度用户组的自我报告抑郁症状显著减少（M-W p=0.004），且效应量较大（CL=0.736）。此外，定性分析中浮现出的主要主题揭示了用户表达了担忧、希望、对支持的需求，以及对思维的重构以及表达胜利和感激之情。结论：这些发现为使用基于AI的情感智能移动应用支持母体事件和经历的广泛心理健康及福祉的有效性、参与度和舒适度提供了初步证据。