发表机构
School of Information Sciences, University of Illinois, Urbana-Champaign; Northeastern University（伊利诺伊大学厄巴纳-香槟分校信息科学学院; 东北大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究通过三阶段LLM流水线生成个性化且幽默程度不同的同伴健康故事，实验发现个性化提升老年人感知相关性与同理心，且幽默偏好低者获益更明显。
AI 中文摘要
同伴故事已被证明能提升老年人在健康行为改变中的自我效能感。尽管有效，但由于难以匹配异质性老年群体中多样化的健康关切和应对风格，同伴故事在大规模健康促进中的部署面临困难。大型语言模型（LLMs）已被证明能生成真实的叙事，然而个性化与叙事情感风格（如幽默）如何共同影响老年人的反应仍属未知。我们开发了一个理论驱动的系统，通过基于自我效能机制的三阶段LLM流水线，生成在个性化和幽默程度上有所变化的第人称同伴健康叙事。我们邀请了三十一位老年人参与一项受试者内实验室研究。结果表明，个性化提升了同伴故事的感知相关性和关联性，尤其是对于幽默偏好较低的老年人。这些发现将情感风格上的个体差异定位为设计LLM辅助健康传播中个性化的第二个维度。
英文摘要
Peer stories have been shown to boost self-efficacy in older adults' health behavior change. Despite their effectiveness, peer stories are difficult to deploy in health promotion at scale given the difficulty of matching the diverse health concerns and coping styles of heterogeneous older populations. Large language models (LLMs) have been shown to generate authentic narratives, yet how personalization and narrative affective style, such as humor, jointly shape older adults' responses remains unknown. We developed a theory-driven system that generates first-person peer health narratives varying in personalization and humor through a three-stage LLM pipeline grounded in self-efficacy mechanisms. Thirty-one older adults were invited to participate in a within-subjects lab study. Results showed that personalization increased perceived relatability and relevance of peer stories, especially for older adults with lower humor preference. These findings position individual differences in affective styles as a second dimension in designing personalization for LLM-assisted health communication.
