Tech to Predict Schizophrenia

Schizophrenia, a psychiatric disorder affecting about 1 percent of the population, is a leading cause of functional disability in the U.S. Typically, the diagnosis hinges on the display of visible positive symptoms such as hallucinations and delusions.

Negative symptoms may appear years before positive symptoms emerge and these symptoms often bring young people who later develop schizophrenia into contact with the mental healthcare system. The symptoms can be characterized by reductions in emotion, lack of motivation to engage in goal directed activities, and decreased participation in social activities

The University of Georgia (UGA) https://www.uga.edu with Gregory P. Strauss PhD., Assistant Professor of Psychology and Neurosciences, plus other neuroscientists, are developing novel technology-based tools to realize symptoms earlier and improve risk prediction.

Funded with $3 million from the National Institute of Mental Health https://www.nimh.nih.gov, UGA along with Northwestern University, and Emory University are going to research and evaluate novel risk identification methods such as digital phenotyping.

The participants in the project will record videos on their cell phones throughout the day, where they will tell the neuroscientists what they are doing and how they feel. Then the researchers will use automated algorithms to process the participant’s emotion in the face and in the voice to quantify negative symptoms.

The videos will be used for lexical analysis to determine whether certain keywords related to positive emotions are present or how tangential or incoherent the speech may be. This will help identify other key symptoms such as speech disorganization or even suicidal thoughts.

However, the use of video has long been part of methods used in a laboratory setting, but often requires painstaking manual analysis. The research colleagues want to automate the entire process and then move the automated information to the real world where emotions naturally occur.

According to Dr. Strauss. “If a phone could help monitor their symptoms and prevent young people returning for frequent clinical reevaluations, then a new level in using technology for mental health care will be achieved.”

Dr. Strauss hopes that the findings on brain mechanisms will uncover new targets for treatment since there are currently no medications capable of effectively treating negative symptoms. He reports that this is one of biggest challenges in the field of psychiatry.

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