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Using technology to predict schizophrenia

Alan Flurry

Schizophrenia, a psychiatric disorder that affects about 1% of the population, is a leading cause of functional disability in the United States. Typically diagnosis has hinged on the display of visible “positive symptoms” such as hallucinations and delusions, but one key to earlier identification and treatment is a recognition of negative symptoms, and University of Georgia neuroscientists are developing novel technology-based tools to catch such symptoms and improve risk prediction.

Negative symptoms typically appear years before positive symptoms emerge and are often what first bring young people who later develop schizophrenia into contact with the mental health care system. These symptoms are characterized by reductions in emotion, motivation and expressive communication, and they include such behavior as avolition, or a lack of motivation to engage in goal-directed activities, and asociality, or decreased participation in social activity, among others.

“Historically, efforts at early identification and prevention of schizophrenia have focused on positive symptoms. These symptoms are often disruptive and require urgent clinical attention when they emerge,” said Gregory Strauss, assistant professor of psychology and neuroscience in the UGA Franklin College of Arts and Sciences. “However, it is the negative symptoms of the disorder that may be even more important to focus on for early identification and prevention.”

Funded with $3 million from the National Institute of Mental Health, Strauss is principal investigator on a project that will collect data at UGA, Northwestern University and Emory University to evaluate novel risk identification methods such as digital phenotyping. The project capitalizes on a ubiquitous 21st century technology.

Great work by Strauss and his team to shift the focus to the early appearance of these negative symptoms. Digital phenotyping tools will be critical in developing this new risk monitoring system that could be more effective for more people suffering from the debilitating condition.

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