Applying best treatments by using a regression equation to target violence-prone youth: a review^1,2

Abstract

In past research, the best treatments of anger management training, jobs, and mentors have been shown to divert 25% to 37% of at-risk youth from court. Within Midwestern urban high schools located in crime-ridden areas, youth were given these treatments after fi rst being identifi ed as at-risk using a predictive regression equation comprising carefully chosen and relevant demographics, behaviors, and test scores. This regression of data from the perpetrators of 500 shootings replicated previous results from 4 other samples ( N s = 71, 30, 26, and 127) of those who had used fi rearms in homicides with matched control groups. Youth (who were expelled, academically failing, maladaptive, low in SES, previously arrested, suspended, truant, or underachieving) included 250 students in 6 high schools during 2009; 1,700 pupils in 38 high schools during 2010; 1,700 more in 38 high schools during 2011; and 1,200 others in 32 high schools during 2012. After treatment, homicides decreased by 32%, shootings by 46%, and assaults by 77%. This saved approximately 104 lives and $492 million dollars, with a Return on Investment ( ROI) = 6.42.Every community struggles with how to deal with violence. Researchers and scientists have confl icting, confusing, and contradictory explanations of violence, how to fi nd it, prevent it, and what it costs. However, there are three promising approaches for predic-1