Leveraging Digital Data to Examine Individual Trajectories of Severe Mental Illness

June 14, 2019

McLean Hospital researchers are set to commence work on a study that will leverage extensive digital data to evaluate, at the individual level, the biological, environmental, and social factors that trigger dangerous mental states, particularly mania and psychosis, in people with bipolar disorder and schizophrenia.

Supported by the National Institutes of Health, this new longitudinal study aims to develop an unprecedented bird’s-eye view of mental illness in individuals over time by continuously measuring a wide variety of factors that may be related to one another, such as sleep and energy or mood and motivation, and showing how those relationships evolve and impact a person’s mental condition.

According to the researchers, by developing predictors of mania and psychosis through the collection and analysis of smartphone, wearable, and audio/video data, and then testing these predictors in individuals with active psychotic disorders, it will be possible to identify the specific factors that promote or hinder healthy behaviors in early psychosis and bipolar disorder and lay the groundwork for tailored intervention strategies.

Justin T. Baker, MD, PhD, with graphs projected on and around him
Justin T. Baker, MD, PhD

“Each participant, in effect, will become their own experiment in this study,” said Justin T. Baker, MD, PhD, scientific director of the McLean Institute for Technology in Psychiatry and co-principal investigator of the study. “Our project will study 100 such individuals, with varying forms of bipolar spectrum and schizophrenia spectrum conditions, and collect 100 person-years of rich, clinical, multivariate data that comprehensively reflects their experiences living with a mental illness.”

Baker said that he and the study’s co-principal investigator, McLean Hospital President and Psychiatrist in Chief Scott L. Rauch, MD, believe that by using intensive, longitudinal, within-person protocols that leverage recent advances in mobile and wireless sensor technologies and big data analytic methods, “our study will advance our understanding of the underlying mechanisms of bipolar disorder and schizophrenia and help us predict the onset of manic or psychotic episode-related behaviors, person by person.”

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