The current status of static and dynamic factors in sexual offender risk assessment
| Published date | 28 September 2012 |
| DOI | https://doi.org/10.1108/17596591211270671 |
| Pages | 169-185 |
| Date | 28 September 2012 |
| Author | Anthony R. Beech,Leam A. Craig |
| Subject Matter | Health & social care,Sociology |
Invited paper
The current status of static and dynamic
factors in sexual offender risk assessment
Anthony R. Beech and Leam A. Craig
Abstract
Purpose – The aim of this paper is to provide up-to-date discussion of the types of factors used to
assess sexual offenders risk.
Design/methodology/approach – The current status of the factors used to assess risk in sexual
offenders is examined.
Findings – Risk factors broadly fall into two categories: static factors (i.e. generally unchangeable
information such as previous offence history) from which a number of actuarial scales have been
developed; and dynamic factors (i.e. psychological dispositions) that are typically identified in
treatment. It is suggested that these risk factors are artefacts of the same behavioural and psychological
vulnerabilities at different stages of assessment, with static factors acting as markers for underlying
dispositions, while dynamic factors are the underlying dispositions.
Practical implications – The paper discusses in some detail the status of age as a risk factor, where
even though it is typically considered a static risk factor in a number of actuarial scales (allowance
typically being made if individuals are over/under 25), there is a dynamic element (i.e. change with age
or the passage of time) to this aspect of assessment.
Originality/value – This paper may be useful to practitioners working in the field, in terms of providing a
useful heuristic framework for risk conceptualisation.
Keywords Sexual offenders, Assessment, Static risk, Dynamic risk, Risk analysis, Criminals,
Risk assessment
Paper type Conceptual paper
Introduction
The assessment of risk in sexual offenders has been dominated by the use of actuarial risk
assessment instruments (ARAIs) to such an extent that their use has been written into
legislation when considering the sentencing or release of sexual offenders in Canada, the
USA, and the UK (Craig and Beech, 2010). A static risk factor is something that is useful for
evaluating long-term risk, but because it is historical in nature it cannot be used to
assess changes in levels of risk over time. For example, static risk factors contained in
the STATIC-99 (Hanson and Thornton, 2000) actuarial risk scale include: sexual deviance
measured by whether the offender has offended against males, ever been married and has
committed a non-contact sexual offence; range of potential victims measured by whether
the offender offended against unrelated or stranger victims; persistent sexual offending
measured by number of previous sexual convictions; and anti-sociality (as measured by
current or previous non-sexual violence or four or more previous criminal convictions), and
under 25 years of age. In their meta-analysis of 82 recidivism studies (29,450 sexual
offenders), Hanson and Morton-Bourgon (2005) identified risk factors of antisocial lifestyle
and sexual deviance as relatively static factors associated with sexual recidivism.
DOI10.1108/17596591211270671 VOL. 4 NO. 4 2012,pp. 169-185, QEmeraldGroup PublishingLimited,ISSN 1759-6599
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JOURNAL OF AGGRESSION, CONFLICT AND PEACE RESEARCH
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PAGE 169
Anthony R. Beech is
based at the
University of Birmingham,
Birmingham, UK.
Leam A. Craig is based at
the Forensic Psychology
Practice Ltd and the
University of Birmingham,
Birmingham, UK.
In contrast, dynamic factors are enduring factors linked to the likelihood of offending that can
nevertheless be changed following intervention. Dynamic factors can be subdivided into
stable and acute factors. Stable dynamic risk factors are those which are relatively persistent
characteristics of the offender which are subject to change such as levels of responsibility,
cognitive distortions, and sexual arousal. Acute dynamic factors are rapidly changing factors
such as substance misuse, isolation, and negative emotional states, the presence of which
increase risk (Hanson and Harris, 1998). Hanson and Morton-Bourgon (2005) identified a
number of promising dynamic risk factors as areas for intervention, including: sexual deviancy
(any deviant sexual interest, sexual preoccupations), antisocial personality (antisocial
personality disorder and psychopathy as measured by Psychopathic Checklist-Revised:
PCL-R; Hare, 2003), and antisocial traits (general self-regulation problems, employment
instability, and hostility).
In assessing sexual recidivism risk, researchers, and practitioners treat static and dynamic
risk factors separately assuming an orthogonal relationship between the two concepts.
Orthogonal data are usually considered to be mutually exclusive, the features of which can
be used without thinking about how that usage will affect other features. This assumes
independence between two data sets or concepts of risk assessment. Where a relationship is
said to exist, the data cannot be assumed to be orthogonal but dependent in some way. This
makes an important difference to our statistical modelling because, in orthogonal designs, the
variation that is attributable to a given factor is constant, and does not depend upon the order
in which factors are removed from the model. In analysing data, we must be careful therefore
to judge the significance of factors in non-orthogonal studies, when they are removed from the
maximal model (i.e. from the model including all the other factors and interactions with which
they might confound). If the explanatory variables are correlated with each other, then the
significance attached to the given explanatory variable will depend upon whether one has
deleted it from the maximal model or added it to the null model (Crawley, 2007). In relation to
sexual offender risk assessment, if static and dynamic factors can be shown to be dependent
factors, then orthogonal assumptions are questioned. There is a growing body of research
drawing parallels between static and dynamic factors suggesting that the two concepts are
functionally linked. The aim of this paper is to highlight commonalities between static and
dynamic factors with a view to redefining the concepts of risk assessment.
Static risk factors
ARAIsareoftenmadeupofstatic(historical)riskitems.Probablythemostwell-knownARAIs
include: Risk Matrix 2000/Sexual (RM2000/S; Thornton et al., 2003), extensively used in theUK;
theRapid Risk Assessmentof Sexual OffenceRecidivism(RRASOR; Hanson,1997), STATIC-99
(Hanson and Thornton, 2000); STATIC-2002( Hansona nd Thornton, 2003; Phenix et al., 2008);
and the Sex Offender Risk Appraisal Guide (SORAG; Quinsey et al., 2006). Actuarial in struments
share a number of characteristics. Each includes ‘‘predictor’’ items that we reselecte dbecause
they were found to be highly correlated with sexual recidivism. A sum of the risk items produces
an overall risk score, which translates into a risk category (e.g. low, medium, high, or very high).
Although some items may be weighted more heavily than others (such as age risk item),
individuals who are positive for many items usually obtain scores placing them in a high risk
groupwhile individuals whoare positive foronly a few obtain low riskscores. In most cases,the
scale developers have compiled experience tables (Ohlin, 1951) from retrospective (often meta-
analytical) studies of released sex offenders that show the percentage of offenders in each risk
category who have recidivated. Hence, a value might be extracted of 45 percent for an individual
of high risk over a ten-year period, which means that 45 out of 100 such individuals are predicted
to recidivate within this time period; or conversely one of the 55 out of 100 who do not.
Validation studies have consistently demonstrated predictive accuracy for these measures
across samples and countries including: Australia (Allan et al., 2006); Belgium (Ducro and
Pham, 2006); Brazil (Baltieri and de Andrade, 2008); Canada (Kingston et al., 2008); Denmark
(Bengtson, 2008); Germany (Stadtland et al., 2006); New Zealand (Skelton et al., 2006); and
the UK (Craig et al., 2006). Such is the dominance of the use of ARAIs that Cortoni et al. (2010)
note that the use of the actuarial approach has permeated the entire criminal justice system in
the USA, Canada, and the UK.
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