为养老社区设计可访问的LLM聊天机器人，提升老人数字素养与信息获取能力。
Learning from Elders: Making an LLM-powered Chatbot for Retirement Communities more Accessible through User-centered Design
- 基于用户访谈与角色画像，聚焦易用性与双功能设计。
- 试点显示高满意度，经优化后支持字体调节与个性化回复。
- 适合关注老年数字包容与人机交互的研究者与实践者。
退休社区中老年人普遍存在低技术与电子健康素养问题，阻碍其使用数字工具。为此，我们采用以人为本的设计方法，为本地养老社区开发了一个基于大语言模型（LLM）的聊天机器人原型。通过访谈与角色构建，重点提升可访问性，并实现双重功能：简化内部信息查询，促进技术与电子健康素养。对居民的试点测试显示高满意度与易用性，但也暴露出改进空间。据此，我们利用GPT-3.5 Turbo和Streamlit进一步优化，通过定制提示工程实现简洁回应。系统集成可调字体大小、界面主题切换及个性化跟进功能。未来计划加入语音转文字功能，并开展纵向干预研究。结果表明，基于大语言模型的聊天机器人可通过可访问、个性化的互动，有效弥合养老社区中的数字素养鸿沟。
原文摘要 · Abstract (English)
Low technology and eHealth literacy among older adults in retirement communities hinder engagement with digital tools. To address this, we designed an LLM-powered chatbot prototype using a human-centered approach for a local retirement community. Through interviews and persona development, we prioritized accessibility and dual functionality: simplifying internal information retrieval and improving technology and eHealth literacy. A pilot trial with residents demonstrated high satisfaction and ease of use, but also identified areas for further improvement. Based on the feedback, we refined the chatbot using GPT-3.5 Turbo and Streamlit. The chatbot employs tailored prompt engineering to deliver concise responses. Accessible features like adjustable font size, interface theme and personalized follow-up responses were implemented. Future steps include enabling voice-to-text function and longitudinal intervention studies. Together, our results highlight the potential of LLM-driven chatbots to empower older adults through accessible, personalized interactions, bridging literacy gaps in retirement communities.
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