Using Meta-level Smartphone Data to Promote Early Intervention inSchizophrenia

Project Summary andquot Using Meta level Smartphone Data to Promote Early Intervention in Schizophrenia Schizophrenia is one of the most debilitating disorders in the world today It affects over million adult Americans each year NIMH director Dr Thomas Insel has declared The best chance for preventing serious functional disability among people with schizophrenia may be to intervene at the earliest stages of the disorder at the first episode of psychosis or even before symptoms appear However to act before symptoms appear requires improved predictive capacity NIMH Budget Creating tools to identify high risk `prodromalandapos individuals may be the single most important step towards developing effective interventions to reduce the duration of untreated psychosis DUP and thereby also reduce the morbidity and mortality associated with schizophrenia Recent studies have shown that over of individuals with schizophrenia are re hospitalized within the first months following their initial hospitalization Even after the first hospitalization preventing relapse and re hospitalization may lessen the long term severity of the illness In this SBIR Phase I study we propose to determine the feasibility of screening for prodromal individuals and individuals at high risk of relapse by applying interpretive algorithms to Passively Gathered Meta level Smartphone Data PGMSD We hypothesize that PGMSD can effectively assist in screening for prodromal individuals who are progressing toward psychosis as well as for remotely assessing individuals at risk for relapse during the critical month period following their first episode of psychosis FEP In Phase I we plan to recruit individuals who have been or are being evaluated at the Prodromal clinics at Columbia UCSD and UCLA where an estimated to of clients already own Smartphones Data gathered may include the frequency of telephone calls emails and texts to assess within person changes in social connectedness GPS accelerometer data to assess physical activity isolation and sleep patterns In the past several IRB approved studies have used smartphones for gathering similar data from patients Algorithms will be developed using several techniques including machine learning to convert the meta level data into measures of social functioning physical isolation physical activity and sleep wake reversals In addition to achieving technological success our goal in Phase I is to provide evidence of our ability to use PGMSD algorithms to differentiating group means of participants who are controls prodromal or experiencing their FEP SIPS or or or In Phase II we will further develop and validate these algorithms If successful the Phase II project will have a large and sustained impact as our algorithms will help identify at risk individuals who `areandapos or `are notandapos progressing toward conversion serve as an objective measure of treatment effectiveness give rise to clinical reports delivered to EHR systems that hold promise for preventing relapse during the critical months after initial diagnosis potentially reducing hospitalization and re hospitalization rates Project Narrative The proposed research protocol seeks to determine the feasibility of identifying individuals progressing toward a first psychotic episode or re hospitalization by applying interpretive algorithms developed in part using machine learning to Passively Gathered Meta level Smartphone Data PGMSD collected from the smartphones of participants ages If successful the PGMSD derived algorithms will assist in screening for prodromal individuals progressing toward psychosis as well as with remotely assessing individuals at risk for relapse during the critical month period following their first episode of psychosis FEP potentially decrease hospitalization and re hospitalization rates This passive data gathering approach will augment existing active data collection approaches aid clinicians in focusing on interpreting rather than gathering data from their clients and could modify clinical paradigms by shifting treatment from individuals suffering from Schizophrenia to individuals who are at risk of developing psychosis with the goal of achieving `secondaryandapos and eventually `primaryandapos prevention