Zeroing in on violent recidivism among released prisoners
Authors: Matt DeLisi
Journal: The Lancet Psychiatry (2016)

Substantial heterogeneity exists among the criminal-offender population,1Moffitt TE Adolescence-limited and life-course-persistent antisocial behavior: a developmental taxonomy.Psych Review. 1993; 100: 674-701Crossref PubMed Scopus (7257) Google Scholar, 2Vaughn MG DeLisi M Gunter T Fu Q Beaver KM Perron BE Howard MO The severe 5%: a latent class analysis of the externalizing behavior spectrum in the United States.J Crim Just. 2011; 39: 75-80Crossref PubMed Scopus (178) Google Scholar, 3Vaughn MG Salas-Wright CP DeLisi M Maynard BR Violence and externalizing behavior among youth in the United States: is there a severe 5%?.Youth Viol Juv Just. 2014; 12: 3-21Crossref Scopus (199) Google Scholar and with 30 million individuals released from prisons worldwide each year, the identification of those who are most likely to perpetrate future violence is essential. Fazel and colleagues' study4Fazel S Chang Z Fanshaw T et al.Prediction of violent reoffending on release from prison: derivation and external validation of a scalable tool.Lancet Psychiatry. 2016; (published April 13.)http://dx.doi.org/10.1016/S2215-0366(16)00103-6Google Scholar in The Lancet Psychiatry is an important advance for enabling such identifications. Using a total cohort of 47 326 prisoners released in Sweden between 2001 and 2009, they showed that 8883 (24%) of the ex-prisoners committed a new violent offence after their release from confinement during the mean follow-up of 3·2 years (SD 2·6), and that the estimated probabilities of violent reoffending at 1, 2, and 5 years after release were 11%, 18%, and 31%, respectively. More than 70% of the violent offences were assaults or robberies, 2% were sexual offences, and 1% were homicides. The investigators created a scale including the following risk factors to predict general reoffending and violent reoffending: male sex, younger age, non-immigrant status, shorter length of incarceration, most recent offence being violent, previous violent crime, never married, less education, being unemployed before prison, low income, living in an area of high neighbourhood deprivation, alcohol use disorder, drug use disorder, any mental disorder, and any severe mental disorder. Their model evinced good overall discrimination and calibration in both derivation and external validation samples. In terms of its sensitivity and specificity, their scale was as good or better than the nine most commonly used actuarial instruments for violence risk: for risk of violent reoffending at 1 year, sensitivity was 76% (95% CI 73–79) and specificity was 61% (60–62). At 2 years, sensitivity was 67% (95% CI 64–69) and specificity was 70% (69–72). The investigators further provide a web calculator version of the model (OxRec) that is free to use to facilitate risk assessment generally. Fazel and colleagues' study is an impressive piece of research and, perhaps more importantly, one that has obvious real-world application. Foremost, it provides a framework to assess prisoners who have mental health conditions that could be used to connect them with the appropriate psychiatric, substance use or abuse treatment, and social service agencies in the community. The findings from their study also show the challenges of predicting violence among the most severe offenders—limitations that are acknowledged by the investigators. Low positive predictive values are a problem with predicting any rare outcome. This is seen in any medical screening test where the prevalence of the disease is low, and the same applies in forensic psychiatry. For example, just 1% of the released cohort included homicide offenders, and 2% sexual offenders, therefore any methods that attempt to predict such rare outcomes before the event will be limited. In terms of further research into predicting the most severe outcomes, a clue can be derived from Fazel and colleagues' model. Two of the important items from their scale were that the most recent offence was violent, and previous violent crime. An adaptation of this scale could include the factor that the most recent offence was related to homicide (eg, murder or attempted murder), sex (eg, rape, sexual abuse, or child molestation), or both (eg, sexual homicide). Previous arrests for these types of offences could also be scored to create an enriched scale that could be used to predict homicide and sexual offences. In view of the striking costs associated with serious violence,5DeLisi M Rape, murder! It's just a shot away.J Crim Just. 2015; 43: 152-153Crossref Scopus (3) Google Scholar, 6Wickramasekera N Wright J Elsey H Murray J Tubeuf S Cost of crime: a systematic review.J Crim Just. 2015; 43: 218-228Crossref Scopus (77) Google Scholar, 7Post LA Mezey NJ Maxwell C Wibert WN The rape tax: tangible and intangible costs of sexual violence.J Interpersonal Viol. 2002; 17: 773-782Crossref Scopus (57) Google Scholar the identification of ways to predict such crimes is essential. Finally, the results from Fazel and colleagues' study4Fazel S Chang Z Fanshaw T et al.Prediction of violent reoffending on release from prison: derivation and external validation of a scalable tool.Lancet Psychiatry. 2016; (published April 13.)http://dx.doi.org/10.1016/S2215-0366(16)00103-6Google Scholar show that even with total population data, findings for the most violent offenders—those for whom severe violence, psychopathy, and sexual crimes figure prominently—are scarce.8Mokros A Osterheider M Hucker SJ Nitschke J Psychopathy and sexual sadism.Law Human Beh. 2011; 35: 188-199Crossref PubMed Scopus (59) Google Scholar, 9Nitschke J Blendl V Ottermann B Osterheider M Mokros A Severe sexual sadism—an underdiagnosed disorder? Evidence from a sample of forensic inpatients.J Forensic Sci. 2009; 54: 685-691Crossref Scopus (15) Google Scholar, 10DeLisi M Psychopathy as unified theory of crime. Palgrave Macmillan, New York2016Crossref Google Scholar I urge criminal justice practitioners and criminologists to carefully read this Article, capitalise on opportunities to apply the study methods to their own data, and tweak them to reach the most challenging offenders. I declare no competing interests. Prediction of violent reoffending on release from prison: derivation and external validation of a scalable toolWe have developed a prediction model in a Swedish prison population that can assist with decision making on release by identifying those who are at low risk of future violent offending, and those at high risk of violent reoffending who might benefit from drug and alcohol treatment. Further assessments in other populations and countries are needed. Full-Text PDF Open Access