Towards clinically actionable digital phenotyping targets in schizophrenia.

ABSTRACT: Digital phenotyping has potential to quantify the lived experience of mental illness and generate real-time, actionable results related to recovery, such as the case of social rhythms in individuals with bipolar disorder. However, passive data features for social rhythm clinical targets in individuals with schizophrenia have yet to be studied. In this paper, we explore the relationship between active and passive data by focusing on temporal stability and variance at an individual level as well as large-scale associations on a population level to gain clinically actionable information regarding social rhythms. From individual data clustering, we found a 19% cluster overlap between specific active and passive data features for participants with schizophrenia. In the same clinical population, two passive data features in particular associated with social rhythms, "Circadian Routine" and "Weekend Day Routine," and were negatively associated with symptoms of anxiety, depression, psychosis, and poor sleep (Spearman ? ranged from -0.23 to -0.30, p?

SUBMITTER: Henson P 

PROVIDER: S-EPMC7200667 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature