Race Not a Predictor of Future Violence, Monahan Says

The most telling risk factor in predicting whether a person will commit a violent crime in the future is whether the person has previous offenses, Professor John Monahan said.

Race should not be considered a risk factor in determining whether someone is likely to commit a violent crime in the future, Professor John Monahan said at a talk sponsored by the Center for the Study of Race and Law March 15. Monahan, a professor of psychology and psychiatric medicine who directs the MacArthur Foundation Research Network on Mandated Community Treatment at U.Va., is only the second non-lawyer on the Law School faculty.

"One way to look at risk factors for violence is to look at them in four categories. Look at what the individual is, what the individual has, what the individual has done, and what has been done to the individual," Monahan said. The most telling risk factor in predicting whether a person will commit a violent crime is whether the person has previous offenses, he said.

Age, gender, personality, mental disorders, personality disorders, substance abuse disorders, prior violence, a pathological family environment, and victimization are all factors that can predict future violent behavior, Monahan said. Scientific evidence suggests that race has such an insignificant correlation to the risk of future violence that it should not be considered, he added.

Monahan's interest in analyzing such risk factors was precipitated by a recent case in Texas where a young man was convicted of first-degree murder. During the sentencing phase of the trial, the prosecution brought in a psychologist who listed all the risk factors the man had that could predict he would commit a violent crime in the future. Among these factors were his age, gender, his prior offenses, and his Hispanic ethnicity. (The defense argued that he was not Hispanic, but Argentinean.) The defendant was ultimately sentenced to death. After multiple appeals, the state of Texas changed its position the night before the case was to be heard by the U.S. Supreme Court and determined that it was unfair to use race as a risk factor in the case.

"There were plenty of reasons to think this guy was going to be violent," Monahan said. Including race as a risk factor "really did make it unfair."

Criminal sentencing in many courts, including Virginia's, depends on the seriousness of the crime and the likelihood of the defendant being violent in the future. This same principle applies to the civil commitment of the mentally ill and of sexually violent predators, Monahan explained. To be institutionalized, an individual must be proven to have a mental disorder and likely to be violent to himself or herself or others. Similarly, sexually violent predators who are committed in mental institutions must have been convicted of certain sex crimes and determined to be likely to continue to commit those crimes.

Monahan examined which risk factors can legally be taken into account, which depends on the legal purpose of the prediction. In criminal sentencing, for example, the decision is supposed to reflect blame as opposed to the likelihood of the person committing a violent crime again. "The only factor that you can be morally accountable for is prior crime. To sentence third offenders longer than first offenders is fine. To take any of these other risk factors into account, I think is not fine."

In cases of civil commitment for mental illness, Monahan argued that the use of any scientifically proven risk factors can be taken into account, with the sole exception of race.

"I think that preventing violence is clearly an important government interest. Including gender is substantially related to that government interest. If you don't include gender as a variable on, for example, the sexually violent predator risk assessment, the game is over," he said. "Gender differences are genuine. They are not hypothesized, and while they may be archaic in the language given by the Supreme Court, they are not outdated." Statistics show that gender is a notable factor in violent crime rates. Men are significantly more likely than women to commit violent crimes-murder, rape, robbery, and assault.

Monahan identified two methods used to determine the probability of someone committing future violence. One is through a clinical interview with a psychologist or psychiatrist, where the individual is asked questions about his or her background and childhood and the clinician assesses whether the person is likely to be violent based on his answers. Most risk assessments currently take place through this technique.

However, seven empirical studies on clinical risk assessments have shown their inaccuracy. "I think the bottom line is, they are more accurate than chance, but they're not much more accurate than chance. This is very close to Ouija board kind of stuff," Monahan said. "It is just very, very difficult to know what risk factors to take into account as to whether someone is going to be violent in the future."

A much better way to predict violent behavior, Monahan said, is to use statistical or actuarial data.

"You don't have an interview with someone where you can ask whatever you want to ask about. Rather, you study what factors actually predict violent behavior, and then you ask people [about] those risk factors and you don't ask [about] other kinds of risk factors."

In the last 10 years, there have been myriad developments in statistical risk assessments. Monahan, in conjunction with the MacArthur Foundation, has recently released the first violence risk assessment software, called "Classification of Violence Risk." In seven minutes, through a series of questions, the program can predict the risk of a person's future violence. The scores are classified into five categories, from a low of 1-percent likelihood to a high of 76-percent likelihood. This method "is vastly more accurate than the clinical predictions" Monahan said.

Monahan used the software to conduct a study of a large group of people hospitalized with mental disorders. The test was highly predictive: three out of four of those put in the highest category committed a violent crime within four months after they were released from the hospital.