The general view of forensic research and several authors has led to the development of a more ...... Ottawa: Department of the Solicitor General of Canada. .... The assessment of sex offenders in Ireland and the Irish sex offender risk tool.
New directions in assessing risk for sexual offenders Leam A. Craig, Kevin D. Browne, Todd E. Hogue & Ian Stringer Abstract Risk assessment is the cornerstone of effective offender management. The identification of the risks posed by offenders and the factors associated with recidivism are crucial to the identification of appropriate and effective interventions designed to reduce the risk of recidivism. While it is generally accepted that the predictive accuracy of actuarial methods outperforms clinical judgement, critics of the actuarial approach argue that the limitations of actuarial risk assessments are such that experts have yet to reach consensus on the best risk factors for predictive accuracy and methods for combining these risk factors into an overall evaluation. This paper considers a number of important conceptual issues associated with the assessment of risk for sexual offenders and offers an alternative approach to risk appraisal. The Multiaxial Risk Appraisal (MARA) model encourages a more global approach to the assessment of risk and examines ‘nomothetic’ (actuarial scales and psychometric assessments of psychopathology and psychosexual characteristics) and ‘idiographic’ (empirically guided clinical assessment and dynamic changes in risk) approaches. One of the advantages of using the MARA model is that the resultant assessment considers the theoretical possibility that there are different aetiological pathways impacting on an offender’s risk of recidivism and allows for the inclusion of dynamic risk-related information.
Introduction As Hanson, Moreton and Harris (2003) argue, much is known about the static, historical factors associated with increased recidivism risk, however, less is known about the offender characteristics that need to change in order to reduce risk. There has been considerable research in recent years demonstrating that structured risk assessments are more accurate than unstructured clinical assessments (Beech, Fisher & Thornton, 2003). The predictive accuracy of clinical judgement and actuarial measures has been debated (Grubin, 1999) and it is widely accepted that actuarial risk measures outperform clinical judgement (Bonta, Law & Hanson, 1996; Hanson & Bussière, 1996; McNeil, Sandberg & Binder, 1998). Goggin (1994) found the mean correlation coefficient for prediction of recidivism using actuarial methods was 0.22 while for clinical methods it was 0.08. Similarly, Grove, Zald, Lebow, Snitz and Nelson (2000) found that mechanical-prediction techniques were about 10 per cent more accurate than clinical predictions, and depending on the specific analysis, mechanical prediction substantially outperformed clinical prediction in 33 per cent to 47 per cent of studies examined. In a study of 192 sexual offenders Hood, Shute, Feilzer and Wilcox (2002) examined the risk assessment procedures of Parole Boards in the UK between 1992
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and 1994 compared with Static-99 (Hanson & Thornton, 2000). Over a six-year follow-up they found that actuarial measures (ROC AUC = 0.77) were better at predicting sexual offence reconviction than compared to clinical judgement (ROC AUC = 0.32) (A. Wilcox, personal communication, 16 September 2002). In contrast clinical judgement has been criticised for overemphasizing the importance of violent offending (Quinsey & Maguire, 1986), and being influenced by biased terminology or descriptions of the offender (Hood, Shute, Feilzer & Wilcox, 2002), all adding to increase an offender’s subjective level of risk (Monohan. et al., 2001). Nevertheless, Rogers (2000) argues that actuarial methods stress risk factors at the cost of neglecting protective factors. Actuarial measures fail to consider mediating and moderating effects such as treatment intervention and are heavily influenced by rates of recidivism. Base rate estimates may produce erroneous results if applied imprudently to forensic samples without regard to their unstable prevalence rates or the farreaching effects of settings, referral questions and evaluation procedures (Rogers, 2000). Similarly, Litwack (2001) urges caution over the uncritical acceptance of actuarial risk assessment measures and offers a critique of the methodologies used in clinical versus actuarial studies. He argues that research to date has failed to demonstrate that actuarial methods of risk assessment are superior to clinical methods. Most clinical determinations of dangerousness are not ‘predictions’ of violence and it is very difficult to compare clinical and actuarial assessments of dangerousness. Litwack suggested that actuarial assessments should be re-evaluated using clinically relevant outcome criteria such as imminence, frequency and severity of offending. In response, Harris, Rice and Cormier (2002) compared the predictive accuracy of clinical judgement with that of the VRAG on a sample of forensic psychiatric patients using the area under the curve (AUC) of the Receiver Operating Characteristic (ROC) analysis. The ROC analysis are preferred indices of predictive accuracy and effect size (Harris, 2003) and plots the sensitivity or ‘hit rate’ (the percentage of re- offenders correctly identified as high-risk on assessment) against the specificity or ‘false alarm rate’ (the percentage of non-reoffenders correctly identified as low-risk). This method is not vulnerable to differences in the base rate of recidivism and can be interpreted as the probability that a randomly selected recidivist would have a more deviant score than a randomly selected non-recidivist. Harris et al. (2002) found that the VRAG performed significantly better at predicting violent recidivism over a six-month period (ROC AUC = 0.80) than did clinical judgement (ROC AUC = 0.70), regardless of length of opportunity or severity of outcome and identified fewer false alarms during a one-year follow-up. In spite of extensive research demonstrating the predictive accuracy of actuarial approaches over clinical judgement, the limitations of actuarial risk assessments are sufficient that experts have yet to reach consensus on the best methods for combining risk factors into an overall evaluation. This paper considers a number of important conceptual issues associated with the assessment and examines the nomothetic (actu-
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arial), idiographic (client centred) and psychometric methods of risk assessment and offers an alternative approach to risk appraisal.
Approaches to risk assessment Actuarial risk assessment procedures can offer probabilistic estimates that a specific behaviour may occur within a given time frame (Hanson, 1997; Hanson & Thornton, 2000). This approach standardises the assessment procedure, reduces clinical error (Quinsey, Harris, Rice & Cormier, 1998) and provides a defensible and transparent decision process. Although there are a number of criticisms of the actuarial approach, actuarial sexual violence risk assessments are promising as they have the potential to assist forensic practitioners in making informed and defensible decisions about a sex offender’s risk of future violence. However, sex offender risk assessment measures for sexual offenders have not lived up to their expectations in being able to make precise predictions about future sexual violence (Hart, Laws & Kropp, 2003). In fact, the rigid use of actuarial measures does not represent good practice. The general view of forensic research and several authors has led to the development of a more comprehensive view of risk assessment, employing the benefits of actuarial methods while recognising the importance of considering behaviour contextually. Heilbrun (1997) suggests that risk appraisal can be divided into two approaches. The ‘prediction model’ focuses on the probability of a specified event occurring within a given time period, and the ‘control model’ considers those factors that reduce the risk of an event occurring. Heilbrun argues that risk assessment can be enhanced in the prediction model by utilising static (i.e. historical, non-changeable risk factors: useful for evaluating long-term risk), or dynamic factors (i.e. enduring factors linked to the likelihood of offending that can nevertheless be changed following intervention). The control model would seek to identify dynamic factors to manage risk and reduce sexual or violent recidivism. Like Heilbrun (1997), Sreenivasan, Kirkish, Garrick, Weinberger and Phenix (2000) offer a critique of the actuarial movement and suggest an alternative approach to risk assessment. They argue that actuarial models are limited primarily to ‘static’ variables and do not target patient treatment potential or management and were derived for the purpose of making absolute predictions of the behaviour reoccurring in a specific time period. Sreenivasan et al argue that the predictive accuracy of a tool is directly impacted upon by the actual risk factors for an individual. They describe a two-pathway approach to risk appraisal distinguishing between the ‘idiographic’ and ‘nomothetic’. The idiographic approach relies upon person-specific factors of risk, while the nomothetic approach compares risk to large group norms. This essentially is the combination of actuarial methods and empirically guided clinical judgment. As with integrated empirically guided clinical judgement, psychometrically assessed sexual deviance is increasingly being considered in risk assessment research. Fisher, Beech and Browne (2000) found that high deviancy men had significantly
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higher levels of cognitive distortions, significantly poorer empathy for victims of sexual abuse and significantly higher levels of emotional fixation on children. High deviancy men had significantly more victims, were more likely to have previous convictions for a sexual offence, were more likely to have committed an extrafamilial offence, and more likely to have offended against boys than when compared to the low deviancy group (Beech, 1998). Indeed, considering risk factors such as psychometrically assessed deviancy (Beech, Friendship, Erikson & Hanson, 2002; Beech, Fisher & Beckett, 1999; Beech, Erikson, Friendship & Ditchfield, 2001), prooffending attitudes (Hudson, Wales, Bakker & Ward, 2002) and other dynamic measures (Dempster & Hart, 2002; Thornton, 2002) increases predictive accuracy when combined with static risk factors. Although Beech et al.’s (2002) sample was small (N=53) with low base rates of recidivism (N= 8, 4.2 per cent), the current trend in research (Hanson & Harris, 2000, 2001; Thornton, 2002) suggests that taking into account dynamic psychological problems (emotional identification with children and justifications for sexual offending), and deviance alongside static risk classification contributes to an offender’s risk of sexual recidivism.
Multiaxial Risk Appraisal Extending the work of Heilbrun (1997) and Sreenivasan et al. (2000), Craig (2004) argues for a more global approach to risk assessment, the ‘Multiaxial Risk Appraisal’ (MARA) model. Due to the differences in sexual offender subgroups (i.e. recidivism base rates, victim and offender characteristics, psychopathology and psychosexual traits) forensic practitioners and risk assessment may be better served by adopting a ‘multiple-pathway risk assessment’ approach (Figure 1). The MARA model encourages a more global approach to risk appraisal by considering ‘nomothetic’ (actuarial methods and psychometric assessments of psychopathology and psychosexual characteristics) and ‘idiographic (empirically guided clinical assessment and dynamic changes in risk) domains. One of the disadvantages of using a single [actuarial] risk appraisal approach is that the resultant assessment ignores the theoretical possibility that there are different aetiological pathways impacting on an offender’s risk of recidivism (Ward & Hudson, 1998) and fails to take into account newer research results (Doren, 2002). Roberts, Doren and Thornton (2002) investigated the inter-relationships between several actuarial risk measures (RRASOR, Hanson, 1997; Static-99, Hanson & Thornton, 2000; MnSOST, Epperson, Kaul & Hout, 1995; MnSOST-R, Epperson, Kaul, Hout, Hesselton, Alexander & Goldman, 2000; VRAG, Quinsey, Harris Rice & Corier, 1998) and the Psychopathy Checklist – Revised (PCL-R, Hare, 1991) and reported two distinct dimensions relating to ‘deviant sexual interests’ and ‘anti-social/violent personality characteristics’ arguing two underlying drives toward sexual recidivism: 1. Diagnosable and illegal sexual desires and, 2. A general propensity toward interpersonal violence.
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Figure 1: Multiaxial Risk Appraisal (MARA)
NOMOTHETIC (acturial measure)
DIMENSION
IDIOGRAPHIC (client centred)
RISK ASSESSMENT
RISK SCALES
PSYCHOPATHOLOGY
Multiple Measures ● RRASOR/Static-99 ● RM2000 Sex/Violence ● SACJ-Min
Psychometric Measures ● Personality traits ● Psychosexual characteristics
Risk Prediction: Consider ● Probabilistic Estimate ● Time Contingent ● Sub-group Base Rates
Traits: Stable Dynamic Factors ● Abnormality/Disorder ● Sexual Deviance
EMPIRICALLY GUIDED CLINICAL ASSESSMENT
Guided Clinical Assessment ● Developmental influences ● Criminogenic Factors/Need FUNCTIONAL ANALYSIS Offence Related Factors ● Acute Dynamic Factors ● Facilitators/Inhibitors of Risk ● Context/Dispositional Factors
Estimate Likelihood of Recidivism ● Frequency ● Imminence ● Severity
Management of Risk ● Review Acceptability of Risk ● Identify Intervention Strategies ● Review Supervision and Monitoring
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RRASOR tended to correlate with sexual deviance dimensions, whereas other actuarial instruments tended to correlate with the general violence dimension. Additional support for a difference between RRASOR and Static-99 was reported by Doren (2001) and Quackenbush (2000). These results are consistent with those reported by Craig, Browne, Beech and Stringer (2003a). Similarly, Ward and Hudson (1998) propose a multiple pathway model for the sexual offence process that incorporates self-regulation research and refers to ways in which offenders control and direct their own actions. The self-regulation model was based on the accounts of incarcerated child molesters and argues that it is possible to identify clear patterns in the behaviour of sexual offenders and to classify offenders according to one of four different routes to offending. They defined these routes to offending based on the offender’s goal toward deviant sex (i.e. approach or avoidance), and by the selection of strategies designed to achieve that goal (i.e. active or passive). The ‘multiple pathway model of sexual offence processes’ offers support to the notion of multiple pathways to risk assessment. Logically, if there are several routes to sexual reoffending, it is unlikely that any one method of risk appraisal will accurately predict recidivism. Rather, a multi-pathway approach to risk assessment is more likely to provide a global assessment of risk. Such a model should include recognition of the predictive accuracy of actuarial tools, inclusion of the role of personality and additional factors, as well as including idiographic tailoring which recognises the unique needs of the specific individuals.
Nomothetic approach The advantage of the MARA approach to risk appraisal over other approaches is that it investigates risk of recidivism from different trajectories. The ‘nomothetic’ approach recognises the utility of actuarial methods in providing estimates of risk within specified time periods. The question here is how many and which actuarial risk measures to use? The use of a single measure has positive and negative attributes attached. While the use of a single measure promotes consistency in risk appraisal, there are drawbacks relating to the applicability of that measure to the individual. When choosing an actuarial measure, the effect of base rates and cohort characteristics need to be considered and, as far as is possible, closely matched to the offender being assessed. Beyond the general guideline to use actuarial risk instruments that are based on sound research evidence, a number of other recommendations can be derived from the research. Firstly, practitioners should ensure that the assessment instruments they use actually have evidence supportive of their use and that they have been designed for use with the relevant subgroup of offenders. Many offender assessment instruments in use today were developed for other populations and they generalise poorly to offender groups. Bartosh, Garby, Lewis and Gray (2003) investigated the predictive utility of the Static-99, RRASOR, MnSOST-R and SORAG in predicting sexual recidivism. The effectiveness of each instrument varied depending on the offender type.
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Static-99 and SORAG both significantly predicted sexual, violent, and any recidivism for extrafamilial child molesters, and all four tests were predictive of violent or any recidivism in this subgroup. For incest offenders, all four tests were at least moderately predictive of sexual recidivism, whereas the Static-99 and the SORAG were highly predictive of violent or any recidivism. None of the four tests established consistent predictive validity across recidivism categories in regard to rapists or handsoff offenders, however, the Static-99 and the SORAG were significant in terms of sexual recidivism. Similarly, Craig, Browne and Stringer (in press) considered empirically the application of sex offender risk assessment measures on offenders with adult or child victims on six risk assessment measures (Static-99 SACJ-Min, RRASOR, Risk Matrix 2000-Sexual/Violent and SVR-20). Levels of risk of the 139 sexual offenders with child and adult victims ranged from seven per cent low risk to 62 per cent high risk, and nought per cent low risk to 93 per cent high risk respectively. Offenders with adult victims obtained significantly higher mean scores using the RM2000/S and SACJ-Min than did sex offenders with child victims who obtained significantly higher scores on the RRASOR. Offenders with adult victims were more likely to be considered medium-high to high risk using Static-99 and SACJ-Min respectively, whereas offenders with child victims were more likely to obtain scores in the low to medium-low risk categories using the RM2000/S. It is important to recognise that actuarial risk measures only provide probabilistic estimates of risk or likelihood that certain behaviour (as applied to a specific group of offenders used in the construction of the risk measure) will occur in a specified time period. Given that base rates differ between offender subgroups, the use of actuarial measures on offenders with characteristics that differ to the cohort sample should be used with caution. Indeed, any comparisons between an individual’s level of risk and ‘base rate’ data should be ignored unless all relevant characteristics between the offender and the sample base rate are shared (Cohen, 1981). In interpreting actuarial scores, Doren (2002) suggests that practitioners should beware of the potential variability due to the sampling process and report confidence intervals and error rates. Similarly, the potential multidimensionality of sex offender recidivism is not addressed through the use of any single measure. Accurate multiple-instrument interpretation requires prior knowledge of the degree to which different scales assess each of the multiple aetiological dimensions (Doren, 2002). RRASOR tends to correlate with sexual deviance dimensions, whereas the other actuarial instruments (in particular Risk Matrix 2000-Violent) correlate with the general violence dimension (Craig, Beech & Browne, 2003; Doren & Roberts, 1998; Roberts et al., 2002). Haynes, Yates, Nicholaichuck, Gu and Bolton (2000) reported that the incorporation of physiological sexual deviance (measured using the penile plethysmograph: PPG) added nothing to the statistical accuracy of the RRASOR in predicting sexual recidivism. Although PPG measured deviancy was the highest single correlate with sexual recidivism (Hanson & Bussière, 1998; Nunes, Firestone, Bradford, Greenberg & Broom,
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2002), Haynes et al.’s results suggest that the RRASOR statistically already addresses the issue of deviance. While the RRASOR may be more useful in assessing the sexual deviance risk dimension, the Risk-Matrix 2000-Violence or Static-99 may be better suited to evaluating risk along the violent/anti-social dimension. In examining the predictive validity of several risk measures, Roberts et al. (2002) found that the sum of the six non-RRASOR items on Static-99 were strongly correlated with the PCL-R and VRAG. It was reported that the six non-RRASOR items were sufficient to make the overall Static-99 scale function differently from the RRASOR items it contains. In support of this Doren (2001) found that the RRASOR and Static-99 were effectively independent of one another specifically when assessing high risk, with their relative overall predictive accuracy being statistically equal.
Psychopathology Psychometric measures are commonly used for assessment in the correctional setting examining personality traits (Blackburn, 1982; Borum & Grisso, 1995; Quinnella & Bow, 2001), affective states (Hanson & Harris, 2000, 2001) and sexual deviance (Beech et al., 1999, 2002; Nichols & Molinder, 1984; Thornton, 2002). Unlike actuarial risk measures which tap into aspects of antisocial behaviour and offer a probabilistic estimate of risk, psychometric measures provide a more objective appraisal of an individual’s psychological traits and characteristics. Recently, psychological traits have been emphasised as an important component to risk assessment of sex offenders (Beech & Ward, in press). Personality inventories are routinely used in psychiatric and correctional settings. Indeed, the Hare Psychopathy Checklist – Revised (PCL-R: Hare, 1991), which is a structured clinical assessment, has seen extensive research into its risk prediction qualities (Buffington-Vollum et al., 2002; Hanson & Harris, 1998; Seto & Barbaree, 1999; Hare et al., 2000; Langstrom & Grann, 2000, 2002; McGuire, 2000; Serin, Mailoux & Malcolm, 2001; Worling, 2001; Quinsey, Harris, Rice & Cormier, 1998). While the utility of personality inventories such as the Millon Inventories (Millon, 1983, 1987, 1994; Millon et al., 1997) and the MMPI have been investigated in correctional settings, few have been used as risk predictors. Craig, Browne, Beech and Stringer (2003b) administered the Special Hospitals Assessment of Personality and Socialisation (SHAPS; Blackburn, 1982) to 121 sexual and violent offenders. Reconviction data was obtained after an average follow-up period of 105 months. Although none of the SHAPS scales consistently predicted sexual reconviction, the Impulsivity scale significantly predicted violent (r=0.18, ROC AUC=0.65; r=0.26, RIC AUC=0.71) and general reconviction (r=0.27, ROC AUC=0.70; r=0.27, ROC AUC=0.71) over five and 10-year periods respectively. These results support the use of personality inventories as a tool to appraise risk of criminal recidivism. In its construction the Impulsivity scale correlated with interview ratings of Psychopathy, which has also been found to be a strong predictor of violent recidivism.
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While both the PCL-R (Barbaree et al., 2001; Brown & Forth, 1997; Firestone et al., 1998; Gretton et al., in press; Sjöstedt & Långström, 2002) and the SHAPS significantly predict violent recidivism in sexual offenders, both are poor at predicting sexual recidivism. Cohen et al. (2002) examined impulsivity-aggressive traits in paedophiles and found no evidence of selective impulsive-aggressive traits. However, given that the sample size was small (N=20 paedophiles and N=24 controls) it is difficult to generalise these results. Impulsive behaviour is so common among offenders that some theorists have proposed that ‘low self-control’ is the essential element of all criminal behaviour (Gottfredson & Hirshi, 1990). Scales used to predict criminal recidivism, such as the PCL-R, or Level of Service Inventory – Revised (LSI-R, Andrews & Bonta, 1995), typically contain numerous items related to impulsivity and lifestyle instability. In general, factors related to general criminality also predict sexual offence recidivism among sex offender samples (Hanson & Bussière, 1998). Indeed, in developing the Sex Offender Need Assessment Rating (SONAR) Hanson and Harris (2001) reported a relatively strong effect for general self-regulation deficits. This is consistent with Quinsey, Coleman, Jones and Altrows (1997) who reported that ‘dynamic antisociality’ predicted re-offending among mentally disordered offenders supervised in the community. The Multiphasic Sex Inventory (MSI; Nichols & Molinder, 1984) is a psychometric measure widely used to assess psychosexual characteristics of sexual offenders. Amongst other scales, the MSI examines sexual obsession, deviant sexual interests, paraphilias, and the use of cognitive distortions, victim empathy, and levels of responsibility expressed by the offender. It is well established in the literature that factors such as psychometrically assessed sexual deviance is associated with sexual recidivism (Beech et al., 1999; Finkelhor, 1984; Hudson, Wales, Bakker & Ward, 2002; Marshall, Anderson & Fernandez, 1999; Salter, 1988). Rather than using the MSI as a sole indicator of treatment effect, Craig, Browne, Beech and Stringer (2003b) examined its predictive validity in a sample of 119 sexual offenders followed-up over a 10-year period. MSI scales sexual obsession (r=0.32, ROC AUC=0.85), paraphilia (atypical sexual outlet) (r=0.19, ROC AUC=0.74), and Factor 1: Sexual Deviance (r=0.20, ROC AUC=0.74) significantly predicted sexual reconviction over a two year follow-up period. The idea that psychometrically assessed sexual deviance is predictive of sexual recidivism is broadly supported by Hudson, Wales, Bakker and Ward (2002) who reported that offenders who score high on the Rape Myths Acceptance Scale were at greater risk of sex recidivism. Beech et al. (2001) examined dynamic factors (psychometrically determined measures of sexual deviancy and treatment effect) in 53 child molesters referred to community treatment programmes. After a six-year follow-up, reconviction data were analysed and it was found that psychological deviance and Static-99 both predicted recidivism and did so independently of each other. These dynamically assessed measures showed incremental predictive accuracy beyond that reported by the actuarial risk measure. It is argued that risk assess-
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ments with child molesters should consider the offenders attitudes and social functioning along with criminal histories. Details of personality traits and psychosexual characteristics not only provide the forensic practitioner with information on treatment need, but can also inform the assessment of risk of recidivism.
Idiographic approach While actuarial risk assessment measures outperform clinical judgement and offer standardised, defensible decisions, they are fundamentally limited in their utility due to the over-reliance on static risk factors. Although static risk factors are useful for evaluating long-term risk, they say nothing about dynamic changes which may positively or negatively impact on levels of risk. Similarly, subtle changes in employment status, relationships, substance misuse, affective states or parole conditions may also been missed by psychometric measures designed to measure personality traits or sexual interests. While the use of psychometric measures adds to the risk appraisal along with actuarial risk assessments, the nomothetic and psychometric approaches alone are unable to comment on the dispositional and contextual factors. The motivation and criminogenic factors related to offending are not easily accessible from either actuarial or psychometric approaches, which say little of the reasons behind offending. Without an understanding of the processes of offending, it is not possible to determine factors that will facilitate or inhibit offending and in what circumstances an offender’s risk of sexual recidivism increases or decreases. An increasing number of studies in the literature offer support for an understanding of the dynamic factors related to sex offence recidivism (Allam, 2000; Beech, Erikson, Friendship & Ditchfield, 2001; Craig, Browne, Stringer & Beech, in press-b; Hanson & Harris, 1997; Haynes, Yates, Nicholaichuk, Gu & Bolton, 2000; Hudson, Wales, Bakker & Ward, 2002; McGrath, Cumming, Livingston & Hoke, 2003, Quinsey, Coleman, Jones & Altrows, 1997; Thornton, 2002; Wong et al., 2000), yet few have empirically investigated the utility of clinically adjusted actuarial estimates of risk (Hanson, 2003). McGrath et al. (2003) examined the recidivism rates of 195 adult male sex offenders who were referred to a prison-based cognitive-behavioural treatment program. Of this sample, 56 participants completed treatment, 49 entered but did not complete treatment, and 90 refused treatment services. Over a mean follow-up period of almost six years, the sexual re-offence rate for the completed-treatment group was 5.4 per cent versus 30.6 per cent for the some-treatment and 30.0 per cent for the no-treatment groups. Lower sexual recidivism rates were also found among those participants who received aftercare treatment and correctional supervision services in the community. Clinically adjusted assessment of dynamic change showed a significant relationship with sexual recidivism beyond that considered by the actuarial measures. Thornton and Beech (2002) examined the extent to which psychological deviance (using the Structured Risk Assessment system, Thornton, 2002; and psychometric
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indicators, Beech et al., 2002) predicts sexual recidivism compared with Static-99. The two systems of deviance assessment were standardized from which the Number of Dysfunctional Domains could be calculated. They compared the accuracy of the deviancy assessments and Static-99 on two samples of sex offenders and found that as a predictor of sexual recidivism the Number of Dysfunctional Domains obtained moderate accuracy (ROC AUC ranging from 0.83 to 0.85) compared with Static-99 (ROC AUC ranging from 0.91 to 0.75). In both samples the Number of Dysfunctional Domains made a statistically significant independent contribution to prediction over and above Static-99 risk category. Analysis of the combined samples confirmed that Static-99 and the Number of Dysfunctional Domains allowed better prediction than either factor alone. More recently Craissati (2003) examined reconviction data on 310 sexual offenders over a four-year period using actuarial measures combined with Sexual Risk Behaviour (SRB) factors. These included any offence with a sexual element, the targeting of victims and any behaviour associated with the index offence. For the rapists sample the ROC AUC increased from 0.71 to 0.85 when considering Static-99 (with risk factors, physical abuse during childhood, and a history of two or more childhood disturbances), and Static-99 plus SRB factors. For the child molesters the ROC AUC decreased from 0.78 to 0.68 when considering Static-99 (with risk factor – victim of childhood sexual abuse), and Static-99 with SRB factors. In Craig, Beech and Browne’s (2003) evaluation of the predictive accuracy of actuarial sex offender risk assessment measures an item analysis revealed four risk factors positively correlated with sex and violent reconviction that were not considered by the risk scales; history of foster care, history of substance abuse, history of employment problems/instability, and history of school maladjustment. Factoring the four risk items increased the strength of correlation between the Risk Matrix-2000/Violent (RMV) and sexual/violent, general and any reconviction of the three follow-up periods, peaking at r=0.52 (p
