發表評論-心理與性-萬維博客-萬維讀者網（電腦版）

【摘要】背景：心理健康聊天機器人正越來越多地被用於解決全球心理健康治療缺口，它們提供可擴展、便捷且匿名的支持。雖然先前的研究表明用戶可能會與這些聊天機器人建立關係，但這種關係體驗背後的機制和個體差異仍未得到充分探索。隨着數字治療聯盟 (DTA) 概念的興起，深入了解主觀關係建立過程對於設計更有效的數字心理健康干預措施至關重要。目的：本研究旨在探究人們如何主觀地感知和發展與心理健康聊天機器人的關係。我們試圖識別促進或阻礙這種聯繫形成的關鍵體驗維度和互動動態，從而促進 DTA 概念的不斷發展。方法：我們進行了一項為期4周的短期縱向日記研究，研究對象為 26 名成年參與者，他們與兩個廣泛使用的心理健康聊天機器人（Woebot 和 Wysa）進行了互動。數據收集方式為每周調查、對話截圖和半結構化訪談。採用反思性主題分析來識別反覆出現的主題，並解讀影響參與者與聊天機器人關係體驗的情感、溝通和情境因素。結果：共有18名參與者報告與至少一個聊天機器人建立了某種或輕度聯繫。訪談敘述揭示了三種關係類別：聯繫（明確的情感聯繫）、輕度聯繫（暫時或部分聯繫）和無聯繫（缺乏聯繫）。心理健康狀況較低和較高的參與者（基於世界衛生組織五大幸福感指數評分）都報告建立了這種關係，這表明建立聯繫的能力並不嚴格取決於心理健康狀況。主題分析確定了六個關鍵主題，解釋了人們為何會或不會建立聯繫：在對話中主導或被主導的願望、偏好的自我表達方式與接受的輸入之間的一致性、對聊天機器人關懷和培養的期望、對聊天機器人建議和提議活動的有效性的感知、對口語化交流的欣賞以及對私密和非評判性對話的重視。結論：我們的研究結果為人們如何解讀和參與心理健康聊天機器人的關係過程提供了實證洞察，從而推進了數字治療聯盟（DTA）的理論基礎。我們的分析並非偏向單一的設計風格，而是強調了偏好與聊天機器人的交互風格和對話角色之間的協調的重要性。參與者最初對同理心和信任的期望也影響了關係的發展。基於這些見解，我們認為，聊天機器人可以通過將情感支持與相關指導相結合、允許靈活的輸入方式以及通過情境感知響應保持連續性來更好地支持早期治療關係。這些特性可以增強其治療價值並促進更牢固的關係。

【關鍵詞】心理健康聊天機器人；數字治療聯盟；縱向研究；日記研究；用戶體驗；人機關係；幸福感；對話代理。

[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.

論文原文：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.

https://doi.org/10.2196/76642

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