Developing an empirical classification of violent offences for use in the prediction of recidivism in England and Wales
| DOI | https://doi.org/10.1108/17596591111154176 |
| Published date | 15 July 2011 |
| Pages | 141-154 |
| Date | 15 July 2011 |
| Author | Philip Howard,Louise Dixon |
| Subject Matter | Health & social care,Sociology |
Developing an empirical classification
of violent offences for use in the prediction
of recidivism in England and Wales
Philip Howard and Louise Dixon
Abstract
Purpose – The classification of criminal acts as violent or nonviolent should be a keystone of actuarial
predictors of violent recidivism, as it affects their outcome measure and scoring of criminal history,thus
influencing many decisions about sentencing, release and treatment allocation. Examination of existing
actuarial and clinical violence risk assessment tools and research studies reveals considerable variation
in the classifications used. This paper aims to use large samples to develop an alternative, empirically
grounded classification that can be used to improve actuarial predictive scores within the offender
assessment system (OASys), the tool used by the National Offender Management Service of England
and Wales to assess static and dynamic risk.
Design/methodology/approach – Two analytical steps are implemented. First, to identify offences that
frequently involve violent acts, 230,334 OASys cases are analyzed for indicators of violent content.
Second, the ability of dynamic and static risk factors to predict reoffending for various offence types is
investigated, analyzing 26,619 OASys cases that have official recidivism data.
Findings – The resulting empirical classification of violent offences adds public order, criminal damage,
threats/harassment, robbery/aggravated burglary and weapon possession offences to the central
group of homicide and assault offences. The need to assess risk of sexual recidivism separately is
discussed.
Originality/value – This study has successfully produced an offence classification for use in a new
predictor of violent recidivism. The use of empirical methods to select these offenceshelps to maximise
predictive validity.
Keywords Risk management, Risk assessment, Recidivism prediction, Violent crime, Classification,
Offender profiles
Paper type Research paper
Introduction
The prediction of violent recidivism has been one of the key concerns of forensic psychology
research over recent decades. Several well-regarded risk assessment instruments now exist
and have been compared in validation studies, which in turn have been combined in
meta-analyses (Campbell et al., 2007; Hanson and Morton-Bourgon, 2009; Yang et al.,
2010). Empirical research around the selection and combination of risk factors in violence
risk predictors must be considered well advanced – yet the question of which criminal acts
should comprise the ‘‘violent recidivism’’ outcome has traditionally been neglected.
This study investigates this issue empirically,as the first step in the production of the OASys
Violence Predictor (OVP). OVP is a new predictor of violent recidivism for use in the National
Offender Management Service (NOMS), the adult correctional system of England and
Wales. This study first sets out the context of risk assessment in NOMS, and why the
introduction of a new predictor is necessary. It explains why defining ‘‘violent recidivism’’
precisely matters. It then analyses large samples of existing risk assessments to classify a
set of criminal offences as OVP’s violent recidivism outcome. This classificationensures that
OVP focuses upon a set of criminal acts, which all involve violent behaviour and together
DOI10.1108/17596591111154176 VOL.3 NO. 3 2011, pp.141-154, QEmeraldGroup PublishingLimited, ISSN1759-6599
j
JOURNAL OF AGGRESSION, CONFLICT AND PEACE RESEARCH
j
PAGE 141
Philip Howard is a Senior
Research Officer, National
Offender Management
Service, Ministry of Justice
& School of Psychology,
University of Birmingham,
Birmingham, UK.
Louise Dixon is a Senior
Lecturer, School of
Psychology, University of
Birmingham,
Birmingham, UK.
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