Wearables, Apps and Sensors for Data Collection 3 |
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| Coordinator 1 | Dr Heidi Guyer (RTI International) |
| Coordinator 2 | Professor Florian Keusch (University of Mannheim School of Social Sciences ) |
The recent and ongoing proliferation and development of mobile technology allows researchers to collect objective health and behavioral data at increased intervals, in real time, and may also reduce participant burden. Wearable health devices can measure activity, heart rate, temperature, sleep behaviors and more; apps can be used to track behaviors- such as spending, transportation use or health measures- as well as for ecological momentary assessment; smartphone sensors have been used to capture sound and movement, among others. The COVID-19 pandemic brought about additional uses of apps and sensors to measure population trends on a large range of topics including mobility, access, symptoms, infection, and contagion. Large national studies such as the UK Biobank study and the U.S. based NIH All of Us research program have demonstrated the scalability of integrating wearables in population-based data collection. Other studies, smaller in scope or sample, have developed innovative approaches of integrating apps and sensors in data collection.
However, researchers using these new technologies to collect data face many decisions about which devices to use, how to distribute them, how to process the data, etc. These decisions impact other components of the research design including selection bias and data quality. In this session, we invite presentations demonstrating novel uses of wearables, apps, and sensors for data collection as well as potential barriers or challenges. Presentations may be related to measurement, consent, data storage, data analysis and data collection.