Computerized Assessment of Psychosis Risk

Area of Science:

• Neuroscience
• Psychiatry
• Computational Psychology

Background:

• Early detection of psychosis in clinical high-risk (CHR) youth is crucial for intervention.
• Traditional clinical interviews for CHR detection have limitations in specificity and required expertise.
• Limited specificity means only 20% of CHR individuals develop psychosis, necessitating improved diagnostic tools.

Purpose of the Study:

• To develop the Computerized Assessment of Psychosis Risk (CAPR) battery, featuring behavioral tasks for early psychosis detection.
• To create a psychosis-risk calculator using machine learning (ML) applied to CAPR data.
• To evaluate the CAPR battery's ability to differentiate CHR individuals from controls and predict future outcomes.

Main Methods:

• Development of the CAPR battery with online, minimally trained behavioral tasks linked to psychosis neurobiology.
• Application of ML methods to CAPR data for creating a psychosis-risk calculator.
• Evaluation of the risk calculator across 500 CHR participants, 500 help-seeking individuals, and 500 healthy controls, assessing 2-year symptomatic outcomes.

Main Results:

• The study aims to develop and validate a novel psychosis-risk calculator based on the CAPR battery.
• Expected results include demonstrating significant differences in risk calculator scores between CHR individuals and control groups.
• Anticipated findings involve correlating baseline CAPR performance with two-year symptomatic outcomes, including psychosis conversion.

Conclusions:

• The CAPR battery and associated risk calculator represent a next-generation tool for early psychosis detection.
• This approach leverages computational methods and neurobiological insights for improved diagnostic accuracy.
• The project aims to facilitate earlier identification of psychosis risk, enabling timely intervention.