心理健康聊天机器人与数字治疗联盟：日记研究与主题分析
心理健康聊天机器人与数字治疗联盟：日记研究与主题分析
The Digital Therapeutic Alliance with Mental Health Chatbots: Diary Study and Thematic Analysis
——《JMIR心理健康》第12卷第76642号文，2025年10月——
【摘要】背景：心理健康聊天机器人正越来越多地被用于解决全球心理健康治疗缺口，它们提供可扩展、便捷且匿名的支持。虽然先前的研究表明用户可能会与这些聊天机器人建立关系，但这种关系体验背后的机制和个体差异仍未得到充分探索。随着数字治疗联盟 (DTA) 概念的兴起，深入了解主观关系建立过程对于设计更有效的数字心理健康干预措施至关重要。目的：本研究旨在探究人们如何主观地感知和发展与心理健康聊天机器人的关系。我们试图识别促进或阻碍这种联系形成的关键体验维度和互动动态，从而促进 DTA 概念的不断发展。方法：我们进行了一项为期4周的短期纵向日记研究，研究对象为 26 名成年参与者，他们与两个广泛使用的心理健康聊天机器人（Woebot 和 Wysa）进行了互动。数据收集方式为每周调查、对话截图和半结构化访谈。采用反思性主题分析来识别反复出现的主题，并解读影响参与者与聊天机器人关系体验的情感、沟通和情境因素。结果：共有18名参与者报告与至少一个聊天机器人建立了某种或轻度联系。访谈叙述揭示了三种关系类别：联系（明确的情感联系）、轻度联系（暂时或部分联系）和无联系（缺乏联系）。心理健康状况较低和较高的参与者（基于世界卫生组织五大幸福感指数评分）都报告建立了这种关系，这表明建立联系的能力并不严格取决于心理健康状况。主题分析确定了六个关键主题，解释了人们为何会或不会建立联系：在对话中主导或被主导的愿望、偏好的自我表达方式与接受的输入之间的一致性、对聊天机器人关怀和培养的期望、对聊天机器人建议和提议活动的有效性的感知、对口语化交流的欣赏以及对私密和非评判性对话的重视。结论：我们的研究结果为人们如何解读和参与心理健康聊天机器人的关系过程提供了实证洞察，从而推进了数字治疗联盟（DTA）的理论基础。我们的分析并非偏向单一的设计风格，而是强调了偏好与聊天机器人的交互风格和对话角色之间的协调的重要性。参与者最初对同理心和信任的期望也影响了关系的发展。基于这些见解，我们认为，聊天机器人可以通过将情感支持与相关指导相结合、允许灵活的输入方式以及通过情境感知响应保持连续性来更好地支持早期治疗关系。这些特性可以增强其治疗价值并促进更牢固的关系。
【关键词】心理健康聊天机器人；数字治疗联盟；纵向研究；日记研究；用户体验；人机关系；幸福感；对话代理。
[Abstract] Background: Mental health chatbots are increasingly used to address the global mental health treatment gap by offering scalable, accessible, and anonymous support. While prior research suggests that users may develop relationships with these chatbots, the mechanisms and individual differences underlying such relational experiences remain underexplored. As the concept of the digital therapeutic alliance (DTA) gains traction, a deeper understanding of subjective relationship-building processes is essential to inform the design of more effective digital mental health interventions. Objective: This study aimed to investigate how people subjectively perceive and develop relationships with mental health chatbots over time. We sought to identify key experiential dimensions and interactional dynamics that facilitate or hinder the formation of such bonds, contributing to the evolving conceptualization of the DTA. Methods: We conducted a 4-week short-term longitudinal diary study with 26 adult participants who interacted with two widely available mental health chatbots (Woebot and Wysa). Data were collected through weekly surveys, conversation screenshots, and semistructured interviews. A reflexive thematic analysis was used to identify recurring themes and interpret the emotional, communicative, and contextual factors shaping participants’ relational experiences with the chatbots. Results: A total of 18 participants reported forming a bond or light bond with at least one chatbot. Interview narratives revealed three relational categories: Bond (clear emotional connection), Light Bond (tentative or partial connection), and No Bond (absence of connection). Both participants with lower and higher psychological well-being (based on the World Health Organization—Five Well-Being Index scores) reported forming such relationships, suggesting that bonding capacity is not strictly dependent on mental health status. Thematic analysis identified six key themes that explain why people did or did not form bonds: the desire to lead or be led in conversation, alignment between preferred style of self-expression and accepted inputs, expectations for caring and nurturing from the chatbot, perceived effectiveness of the chatbot’s advice and proposed activities, appreciation for colloquial communication, and valuing a private and nonjudgmental conversation. Conclusions: Our findings provide empirical insight into how people interpret and engage in relational processes with mental health chatbots, advancing the theoretical foundation of the DTA. Rather than favoring one design style, our analysis highlights the importance of alignment between preferences and the chatbot’s interaction style and conversational role. Participants’ initial expectations around empathy and trust also shaped how relationships developed. Drawing on these insights, we suggest that chatbots may better support early therapeutic relationships by blending emotional support with relevant guidance, allowing flexible input methods, and maintaining continuity through context-aware responses. These features may enhance their therapeutic value and foster stronger relationships.
[Key words] mental health chatbot; digital therapeutic alliance; longitudinal study; diary study; user experience; human-chatbot relationship; well-being; conversational agent.
论文原文：Zian Xu, Yi-Chieh Lee, Karolina Stasiak, Jim Warren, Danielle Lottridge (2025). The Digital Therapeutic Alliance with Mental Health Chatbots: Diary Study and Thematic Analysis. JMIR Ment Health, Volume 12: e76642, October 10, 2025.
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