Foreign Domestic Workers (FDWs) play a central role in home-based eldercare yet often experience substantial emotional caregiving burden shaped by linguistic barriers, social isolation, and limited access to support. While caregiving burden has been extensively studied among familial caregivers, little is known about how FDWs engage with emotional support technologies. We present an exploratory qualitative study of how FDWs in Singapore interact with a Large Language Model (LLM)-driven chatbot as an everyday, non-clinical form of emotional support. Through interviews and guided chatbot interactions, we conducted an inductive thematic analysis of participants' experiences. We identify three design-relevant themes: chatbots were experienced as psychologically safe and emotionally validating; they supported linguistic accessibility by accommodating imperfect and fragmented language; and they were appropriated as multifunctional resources for reassurance, guidance, and companionship. We discuss implications for designing LLM-driven emotional support tools that foreground psychological safety, accessibility, and flexible appropriation.

翻译：外籍家庭帮工（FDWs）在居家养老中扮演核心角色，但因语言障碍、社会孤立及缺乏支持渠道，常承受巨大的情感照护负担。尽管照护负担在家庭照护者中已被广泛研究，但关于外籍家庭帮工如何参与情感支持技术的研究尚属空白。我们开展了一项探索性定性研究，考察新加坡外籍家庭帮工如何与基于大语言模型（LLM）的聊天机器人互动，将其作为日常非临床形式的情感支持工具。通过访谈和引导式聊天机器人互动，我们对参与者的体验进行了归纳主题分析。我们识别出三个与设计相关的主题：聊天机器人被体验为心理安全且具有情感验证作用；它们通过适应不完美和碎片化的语言来支持语言可及性；它们被用作多功能资源，提供 reassurance（安心）、指导和陪伴。我们讨论了设计以大语言模型为驱动的情感支持工具的启示，这些工具应优先考虑心理安全、可及性和灵活的任务适应性。