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27 Crim. Behav. & Mental Health 1 (2017)

handle is hein.journals/cbmh27 and id is 1 raw text is: Criminal Behaviour and Mental Health 27: 1-7 (2017) Published online in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/cbm.2031 Managing uncertainty in the clinical prediction of risk of harm: Bringing a Bayesian approach to forensic mental health CONOR DUGGAN' AND ROLAND JONES2, 11nstitute of Mental Health, University of Nottingham, Nottingham, UK; 2Partnerships in Care, Llanarth Court, UK ABSTRACT Predicting the likelihood of harm posed by mentally disordered offenders remains controversial. It is proposed that a Bayesian approach may help quantify the uncertainty surrounding such prediction. An example of this approach quantifying the risk of breast cancer in the event of a positive mammogram is provided. One of the taxing problems facing forensic mental health clinicians is providing accurate information to colleagues and to the courts on the risk of future violence by people with a mental disorder. There has been extensive debate about the value of applying actuarial data to an individual case. In brief, Hart et al. (2007), then Cooke and Michie (2010) calculated the confidence and prediction intervals respectively for actuarial estimates when applied to an individual and concluded that resultant risk estimates were mathematically meaningless, as they spanned nearly the entire range from 0 to 1. The assumptions attached to their approaches were criticised by Mossman and Selike (2007), Harris et al. (2007), Hanson and Howard (2010) and, perhaps most cogently, by Imrey and David (2015). Scurich and John (2012) also joined this debate but, in addition, proposed an alternative solution - based on a Bayesian approach. Although a few authors have used this approach (Salo et al., 2012; Costantinou et al., 2015, 2016), here, we provide a simple introduction to the application of Bayesian calculations to risk assessment in the hope that it will encourage their more widespread use by clinicians. Thomas Bayes was an 18th century parish minister in Tunbridge Wells who was interested in conditional probability - that is the probability of an event given that Copyright t 2017 John Wiley & Sons, Ltd. 27: 1-7 (2017) DOI: 10.1002/cbm

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