New research suggests that speech patterns may reveal a person’s risk for psychosis-related disorders. The discovery could lead to earlier diagnosis.

Identifying which at-risk young people will develop psychotic disorders can be a frustrating guessing game for mental health experts.

But new technology that can analyze speech patterns is raising hopes that, in the future, identifying those at risk for psychosis will be as easy as having a conversation.

A small study out this week found that a computer algorithm could identify who would develop psychosis with an accuracy of up to 83 percent.

Psychosis is a frightening condition that’s “characterized as disruptions to a person’s thoughts and perceptions that make it difficult for them to recognize what is real and what isn’t,” according to the National Alliance on Mental Illness.

Psychosis can be caused by a host of mental health conditions such as schizophrenia, which is a psychotic disorder, as well as depression and bipolar disorder.

While there are known risk factors, such as having a family member with a psychotic disorder, mental health experts haven’t been able to determine who among those at risk will actually develop psychosis.

In recent years, researchers have turned to computer algorithms to help them parse the language of at-risk individuals to see if there are clues in their speech.

This week, researchers reported in a small study that speech patterns may help reveal who is likely to develop psychosis.

Researchers from Icahn School of Medicine at Mount Sinai, the New York State Psychiatric Institute, the University of California Los Angeles (UCLA), and other institutions used a computer algorithm to examine the speech patterns of 93 at-risk young people in New York and California.

Their results were published this week in World Psychiatry.

The computer analyzed transcripts of interviews with the subjects that had been conducted years earlier.

Words were coded so that the algorithm could determine which words were out of place. As a result, the program could figure out when a person likely went off topic during the interview.

Researchers said the algorithm could identify which patients went on to develop psychosis with 83 percent accuracy. The team then used the program on a second group of study patients and found it had a 79 percent accuracy rate.

The program could also differentiate between healthy people and those with recent psychosis onset with 72 percent accuracy.