The Cognitive Strategies Behind Multimodal Health Sensemaking: A Menstrual Health Tracking Case Study

The proliferation of commodity devices for gathering health data has led to multimodal health trackers that provide increasingly holistic views of people's well-being. As these trackers become more complex, it becomes harder for users to interpret how different signals interrelate in order to derive actionable insights and make informed health decisions. Addressing this challenge first requires understanding the cognitive and behavioral processes through which users interpret and make sense of multimodal data. In this paper, we use menstrual health tracking as a case study for investigating how individuals interpret multimodal health data. We conducted a 100-day longitudinal study with 20 participants who used a variety of health trackers to monitor signals relevant to menstrual health (e.g., hormones, sleep, mood). Through surveys and interviews, we identified that participants aligned their health goals with each device's perceived scope and approached multimodal data with hypotheses that involved pairs of signals. Our findings shed light on how a person's confidence in the sensemaking processes shapes their engagement with multimodality, leading to design recommendations that scaffold trust between users and their devices while encouraging exploration and staying true to users' evolving health goals.