ABSTRACT
This chapter summarizes the findings of a study by Fox, Heide, Khachatryan, Michel, and Cochran (2021) that developed the first statistically derived classification of male juvenile homicide offenders (JHOs) in the United States based on heterogeneous offense, offender, and victim characteristics. This study contributed to the discipline in two notable ways. First, it used a data set of over 44,000 cases of juvenile homicide across the United States spanning more than 40 years (1970s–2010s), thereby overcoming many limitations of prior research that used small and nonrepresentative convenience samples. Second, it employed a sophisticated analytic classification technique known as latent class analysis (LCA) to objectively identify latent subtypes of JHOs based upon crime, victim, and offender features. The LCA revealed that six distinct subgroups of male JHOs exist within the data, each with its own unique characteristics. The main takeaway from this study is that “one-size-fits-all” crime prevention models are unlikely to be effective; more tailored approaches to intervention, prevention, and treatment in response to each unique JHO subtype’s offense and offender features would be beneficial. We therefore conclude by discussing ways in which knowledge of different types of male JHOs may aid law enforcement in solving murders, practitioners in designing effective intervention and treatment programs, and policymakers in developing successful crime prevention strategies.
