AI 中文总结
该研究针对心脏病预防数据共享的粒度同意机制，通过两阶段设计与心脏病患者实验，发现低/高粒度同意界面定量差异不显著，定性揭示控制权-负担悖论，为相关设计提供启示。
AI 中文摘要
动态同意机制可赋予终端用户更强的控制权，但目前鲜有研究关注患有慢性病的老年人如何在健康数据生命周期的粒度同意机制中权衡控制权与负担。本研究采用两阶段设计流程评估该权衡关系：首先通过专家研讨会（n=5）明确粒度动态同意原型的设计需求；随后开展混合方法研究，以心脏病患者（n=7）为对象，对比动态同意机制中单步与多步粒度的差异。定量结果显示，低粒度与高粒度同意界面在可用性、工作负荷、感知信息控制权或数据共享意愿上无显著差异；但定性研究发现存在控制权-负担悖论，且参与者对粒度的参与度依赖于信任，他们还希望AI介导的数据处理具备更高的透明度与控制权。本研究为健康数据生命周期中粒度同意机制的设计提供了启示。
英文摘要
Dynamic consent can promise end users with greater control, but little is known about how older adults with chronic conditions navigate the tradeoff between control and burden in granular consent mechanisms in health data life-cycles. Using a two-stage design process we evaluated this tradeoff. An expert workshop (n=5) informed the design requirements for granular dynamic consent prototype. We evaluated single step vs multi-step granularity in dynamic consent using prototypes with cardiac patients (n=7) using a mixed-methods study. Quantitative measures showed no significant differences between low- and high-granularity consent screens in usability, workload, perceived information control or willingness to share data. However, qualitative findings revealed a control-burden paradox and trust-dependent engagement with granularity. Participants sought greater transparency and control over AI-mediated data processing. We contribute implications for designing granular consent in health data life-cycles.
CommentsAccepted as MuC'26 Work in Progress (WIP) submission
DOI：10.18420/muc2026-mci-wip-337
