Abstract
With interpersonal violence, currently a leading cause of death (World Health Organization 2004) and recent reports suggesting that approximately 100,000 juveniles are arrested for violent crimes each year in the USA alone (Puzzanchera 2009; Puzzanchera et al. 2010), establishing valid and reliable methods of identifying children and adolescents who will commit violent acts is an important public health and safety issue. One method of identifying future offenders is through the use of risk assessment tools, instruments designed to predict the likelihood of antisocial behavior. Numerous juvenile and adult risk assessment tools, the manuals of which claim high rates of predictive validity and reliability, have been introduced in recent decades (Bonta 2002; Schwalbe 2007). The investigation of these measures’ psychometric properties has produced a sizeable literature which has often come to conflicting conclusions as to which tools produce the highest rates of predictive validity in different contexts (Singh and Fazel 2010).
Predicting the weather is easy compared with predicting violence
Monahan and Steadman (1996, p. 932)
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Notes
- 1.
 There also exist risk assessment tools which use a derivation of the low/moderate/high binning scheme. For example, tools such as the Youth Level of Service/Case Management Inventory (YLS/CMI; Hoge and Andrews 2002) classify individuals into one of four risk classifications: low, moderate, high, and very high risk.
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Singh, J.P. (2012). The History, Development, and Testing of Forensic Risk Assessment Tools. In: Grigorenko, E. (eds) Handbook of Juvenile Forensic Psychology and Psychiatry. Springer, Boston, MA. https://doi.org/10.1007/978-1-4614-0905-2_14
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