Digital phenotyping for psychiatry: accommodating data and theory with network science methodologies

Abstract

Digital phenotyping is the moment-by-moment quantification of our interactions with digital devices. With appropriate tools, digital phenotyping data afford unprecedented insight into our transactions with the world and hold promise for developing novel signatures of psychopathology that will aid in diagnosis, prognosis, and treatment selection of psychiatric disorders. In this review, we highlight empirical work merging digital phenotyping data, and particularly experience-sampling data collected via smartphone, with network theories of psychopathology and network science methodologies. The intensive, longitudinal, and multivariate data collected through digital phenotyping designs provide the necessary foundation for the application of network science methodologies to parsimoniously test network theories of psychopathology emphasizing causal interactions among psychiatric symptoms, as well as other phenotypes, across time.

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