Digital phenotyping is defined as the “moment-by-moment quantification of the individual-level human phenotype in situ using data from personal digital devices”. In other words, it is a method of data collection that uses technology, such as a smartphone, to collect data from a participant. Active and passive data can be collected as a person goes about their daily life. Active data is data actively input by the user, such as ratings of how happy or sad they feel at this moment, whereas passive data is data that is collected in the background, without any input from the user, such as GPS or step counters.
The PATH lab’s research in this area aims to help us learn how we can use smartphones to better understand the well-being of people with and without type 2 diabetes. To learn more about this area of research, click here.
McInerney, A., Schmitz, N., Matthews, M., & Deschenes, S. S. (2021). Exploring behavioural predictors of psychological distress among adults with and without diabetes using digital phenotyping. European Health Psychology Society.