In order to gain a greater understanding of how several factors that can affect health interact with each other, researchers must use a combination of measurement methods in tandem. In order to study the effectiveness of using a blend of sensing technology like smartphone apps and wearable technology, self-reported surveys, and readily available group-level information (grades, attendance), our team developed a study to understand more about the social lives, sleep habits, physical activity levels, and academic performance of 1000 UT undergraduate students. How does sleep quality affect physical activity? Or vice versa? Do people report greater feelings of loneliness when they are alone or in a crowded room? Do grades suffer when meals are skipped? While the broader Whole Communities–Whole Health study will focus on young families instead of young adults, the process of data collection with the students allows the team to learn how best to assist future participants with technology set-up and overcome new challenges related to handling large amounts of real-time data. In addition, the team can learn new methods for collecting relevant information, analyzing it, and returning it to participants in a useful way.
David Schnyer (Principal Investigator – Department of Psychology), Kerry Kinney (CAE Engineering), Zoltan Nagy (CAE Engineering), Edison Tomaz (Electrical and Computer Engineering), Cameron Craddock (Dell Medical School), Darla Castelli (College of Education)