普适人机交互中的协商策略：一种新型故事板量表与实地研究
Negotiation Strategies in Ubiquitous Human-Computer Interaction: A Novel Storyboards Scale & Field Study
AI总结：
本研究结合休闲约束协商模型与跨理论模型，提出并验证故事板量表StoryWear，用于评估STTs中十一类运动参与协商策略的有效性并给出实施指南。
摘要：
在当今互联社会中，可穿戴设备和移动健身应用等自我追踪技术（STTs）使人们能够通过普适的身体活动监测来改善健康与福祉，并带来若干个人和社会收益。尽管此类技术的硬件不断进步，但用户参与度低和有效性下降等局限，要求更具依据且有理论基础的人机交互设计。为应对这些挑战，我们基于此前尚未被探索的休闲约束协商模型和跨理论模型，系统地定义并评估STTs功能的有效性；这些功能承认用户的情境约束，并建立由人协商的STTs叙事。具体而言，我们提出并验证了一个以人为中心的量表StoryWear，它通过包容性的故事板形式，捕捉并探究人们用来克服运动参与约束的十一维协商策略。基于初步研究，StoryWear表现出高可靠性，适合未来在普适计算中的工作。结果表明，协商策略在感知有效性上存在差异，并且对现有STTs用户具有更高吸引力，其中自我激励、承诺以及理解不运动的负面影响位居前列。最后，我们给出了面向真实世界实施的可操作指南，并对个性化训练的未来进行了评论。
英文摘要：
In today's connected society, self-tracking technologies (STTs), such as wearables and mobile fitness apps, empower humans to improve their health and well-being through ubiquitous physical activity monitoring, with several personal and societal benefits. Despite the advances in such technologies' hardware, low user engagement and decreased effectiveness limitations demand more informed and theoretically-founded Human-Computer Interaction designs. To address these challenges, we build upon the previously unexplored Leisure Constraints Negotiation Model and the Transtheoretical Model to systematically define and assess the effectiveness of STTs' features that acknowledge users' contextual constraints and establish human-negotiated STTs narratives. Specifically, we introduce and validate a human-centric scale, StoryWear, which exploits and explores eleven dimensions of negotiation strategies that humans utilize to overcome constraints regarding exercise participation, captured through an inclusive storyboards format. Based on our preliminary studies, StoryWear shows high reliability, rendering it suitable for future work in ubiquitous computing. Our results indicate that negotiation strategies vary in perceived effectiveness and have higher appeal for existing STTs' users, with self-motivation, commitment, and understanding of the negative impact of non-exercise placed at the top. Finally, we give actionable guidelines for real-world implementation and a commentary on the future of personalized training.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
