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dc.creatorMittal, Vijay A.
dc.creatorEllman, Lauren M.
dc.creatorStrauss, Gregory P.
dc.creatorWalker, Elaine F.
dc.creatorCorlett, Philip R.
dc.creatorSchiffman, Jason
dc.creatorWoods, Scott W.
dc.creatorPowers, Albert R.
dc.creatorSilverstein, Steven M.
dc.creatorWaltz, James A.
dc.creatorZinbarg, Richard
dc.creatorChen, Shuo
dc.creatorWilliams, Trevor
dc.creatorKenney, Joshua
dc.creatorGold, James M.
dc.identifier.citationMittal VA, Ellman LM, Strauss GP, Walker EF, Corlett PR, Schiffman J, et al. Computerized Assessment of Psychosis Risk. J Psychiatry Brain Sci. 2021;6:e210011.
dc.description.abstractEarly detection and intervention with young people at clinical high risk (CHR) for psychosis is critical for prevention efforts focused on altering the trajectory of psychosis. Early CHR research largely focused on validating clinical interviews for detecting at-risk individuals; however, this approach has limitations related to: (1) specificity (i.e., only 20% of CHR individuals convert to psychosis) and (2) the expertise and training needed to administer these interviews is limited. The purpose of our study is to develop the computerized assessment of psychosis risk (CAPR) battery, consisting of behavioral tasks that require minimal training to administer, can be administered online, and are tied to the neurobiological systems and computational mechanisms implicated in psychosis. The aims of our study are as follows: (1A) to develop a psychosis-risk calculator through the application of machine learning (ML) methods to the measures from the CAPR battery, (1B) evaluate group differences on the risk calculator score and test the hypothesis that the risk calculator score of the CHR group will differ from help-seeking and healthy controls, (1C) evaluate how baseline CAPR battery performance relates to symptomatic outcome two years later (i.e., conversion and symptomatic worsening). These aims will be explored in 500 CHR participants, 500 help-seeking individuals, and 500 healthy controls across the study sites. This project will provide a next-generation CHR battery, tied to illness mechanisms and powered by cutting-edge computational methods that can be used to facilitate the earliest possible detection of psychosis risk.
dc.format.extent40 pages
dc.relation.ispartofCOVID-19 Research
dc.relation.haspartJournal of Psychiatry and Brain Science, Vol. 6
dc.rightsAttribution CC BY
dc.subjectClinical high-risk
dc.subjectRisk screening|Behavioral tasks
dc.subjectComputational psychiatry
dc.subjectPrecision medicine
dc.subjectComputerized assessment
dc.subjectRisk calculator
dc.titleComputerized Assessment of Psychosis Risk
dc.type.genreJournal article
dc.ada.noteFor Americans with Disabilities Act (ADA) accommodation, including help with reading this content, please contact
dc.description.schoolcollegeTemple University. College of Liberal Arts
dc.temple.creatorEllman, Lauren M.

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