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Sex Offender Management Assessment and Planning Initiative, Office of the Sex Offender Sentencing, Monitoring, Apprehending, Registering, and Tracking (SMART)
Sex Offender Management Assessment and Planning Initiative Office of the Sex Offender Sentencing, Monitoring, Apprehending, Registering, and Tracking (SMART)
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Chapter 6: Sex Offender Risk Assessment
by Kevin Baldwin, Ph.D.


Although the desire to predict the risk of future violence posed by individuals is likely centuries old, risk assessment efforts until recently have been relatively unsuccessful in terms of their predictive accuracy. Notwithstanding pseudoscientific methods such as phrenology (which claimed to gauge behavior propensities based on measurements of the skull), risk assessment for many decades has primarily involved individual mental health professionals applying their accumulated experience and clinical acumen to produce a clinical judgment of the degree of risk posed by a particular individual. Scientists have repeatedly questioned the validity of such unstructured clinical judgment as the basis for risk assessments (Grove, 2005; Grove & Meehl, 1996; Meehl, 1954), but it took the publication of John Monahan's Predicting Violent Behavior: An Assessment of Clinical Techniques in 1981 to usher in a truly scientific approach to violence risk assessment. In the three decades since the publication of Monahan's book, the relative accuracy of violence risk assessments has increased substantially.

The ability to accurately assess the likelihood of future violent acts—and future criminal behavior more generally—is important to clinicians, policymakers, and the public alike. In this context, risk assessment typically involves arriving at an estimate of the likelihood that an offender will recidivate (that is, revert to illegal behavior) after the individual experiences legal consequences or intervention for a prior criminal act. (For more information on "Adult Sex Offender Recidivism," see chapter 5 in the Adult section.)

Risk assessment serves many purposes throughout the offender adjudication process. It is often undertaken for dispositional purposes to help determine, for example, an appropriate sentence or custody level or the conditions of community supervision. In these situations decisions are often predicated, at least in part, on the assessed likelihood of recidivism, with resources being allocated accordingly to promote community safety (Kingston et al., 2008).

Research has suggested that offenders convicted of sexual offenses have received more attention from policymakers than any other category of offenders over the past 20 years (Ackerman et al., 2011; Levenson, 2009), and that there is consequently a need for methods and tools that can be used to accurately assess the risk to public safety that sexual offenders pose. Indeed, estimates of risk for sex offenders are used in various community corrections, institutional corrections, and civil commitment decision-making contexts. Thus, the scientific and theoretical underpinnings of risk assessment are a critical component of the successful management of adult sexual offenders (Tabachnick & Klein, 2011). (For more on "Sex Offender Management Strategies," see chapter 8 in the Adult section.)

In many respects, the effectiveness of sex offender management policies relies on the ability of criminal justice professionals to accurately differentiate sexual offenders according to their risk for recidivism (Hanson & Morton-Bourgon, 2005). Arguing from a policy standpoint, Tabachnick and Klein (2011) have stated that the results of actuarial risk assessments in particular should inform decision-making at all levels regarding the supervision of adult sexual offenders in order to prevent recidivism.

While much progress has been made regarding the ability of professionals in the field to accurately estimate the likelihood of future sexual reoffense, no one is presently able to estimate either the timing or the severity of such future criminal conduct (J. Levenson, personal communication, May 23, 2011). Therefore, it is critically important to establish a clear understanding of exactly what risk is being assessed and to frame expectations accordingly. Current methods at present allow, in most cases, only for an estimate of the likelihood of both future sexual and nonsexual offending over a specific timeframe. The accuracy of these estimates depends in part on the degree to which the individual offender being assessed matches a known group of sex offenders and the degree to which the factors included in the risk assessment accurately reflect the known universe of relevant risk factors.

Review of Research

Sex offender risk assessments are most often employed in applied forensic settings for purposes of decision-making (Doren, 2002). The typical venues for sex offender risk assessment include—

"The purposes of risk assessment span the spectrum of the adjudication process."

  • Sentencing and criminal adjudications, during which the results of the assessment are used to ascertain appropriate levels and periods of confinement and/or community supervision.
  • Determinations of treatment needs, settings, and modalities.
  • Sex Offender Registration and Notification (SORN) proceedings, during which the results of the assessment are used to classify ("level") offenders based on their assessed risk.
  • Civil commitment proceedings, during which the results of the assessment are used to argue for and against indefinite confinement based on the assessed risk for sexual recidivism.

Figure 1. Sex Offender Management Practices Across the Criminal Justice Spectrum
Figure 1. Sex Offender Management Practices Across the Criminal Justice  Spectrum. Case Processing: Arrest and Investigation, Prosecution and Defense, Sentencing and Disposition. Corrections: Corrections Programming, Treatment. Reentry and Tracking: Supervision, Treatment, Registration, Community Notification. Community Support: Prevention and Education, Victim Services and Outreach, Community Involvement

Methods of assessing sex offender risk can generally be categorized as follows (Hanson, 1998):

  • Unguided (or unstructured) clinical judgment: The evaluator1 reviews case material and applies personal experience to arrive at a risk estimate, without relying on a specific list of risk factors or underlying theory to prioritize or weight any of the information used.
  • Guided (or structured) clinical judgment: The evaluator begins with a finite list of factors thought to be related to risk, drawn from personal experience and/or theory rather than from relevant empirical evidence.
  • Research-guided clinical judgment: The evaluator begins with a finite list of factors identified in the professional literature as being related to risk. While these factors are given priority in the risk assessment, they are combined with other factors and considerations using the clinician's judgment.
  • Pure actuarial approach: The evaluator employs an existing instrument composed of a finite, weighted set of factors (generally static, or relatively unchanging and historical in nature) identified in the literature as being associated with risk. The instrument is used to identify the presence or absence of each risk factor, and an estimate of risk is arrived at through a standard, prescribed means of combining the factors. This approach is the only risk assessment method that can be scored using a computerized algorithm or by minimally trained nonclinicians.
  • Adjusted actuarial approach: The evaluator begins with the administration of an existing actuarial instrument and then employs a finite list of considerations that can be used to raise or lower the assessed level of risk.

Comparisons of the above-described approaches to risk assessment have a long and at times contentious history (Grove, 2005; Grove & Meehl, 1996; Grove et al., 2000; Meehl, 1954). While the superiority of structured approaches to unstructured approaches appears to have been settled (Grove, 2005; Hanson & Morton-Bourgon, 2009; A. Phenix, personal communication, May 10, 2011), each of the structured approaches has its merits as well as its supporters and detractors (Doren, 2002; A. Phenix, personal communication, May 10, 2011). Nonetheless, recent research (Hanson & Morton-Bourgon, 2009) suggests that pure actuarial assessments should be favored over other approaches (Hanson, 2009).

"There are three generations of risk assessment methods: Unstructured professional opinion, actuarial methods using static predictors, and methods that include both static and dynamic factors."

Criminologist James Bonta (1996) has identified three generations of risk assessment methods: unstructured professional opinion (corresponding to Hanson's (1998) unstructured clinical judgment), actuarial methods using static predictors (corresponding to Hanson's actuarial approach), and methods that include both static and dynamic factors (referred to by Bonta as criminogenic needs). By including dynamic risk factors in the assessment process, third-generation risk assessments can be used to both guide and evaluate the impact of intervention efforts. The current thinking in the field confirms the promise of third-generation risk assessment methods, as research tells us more about the relationship between specific dynamic factors and risk for recidivism (Hanson, 2011; Mann, Hanson, & Thornton, 2010; A. Phenix, personal communication, May 10, 2011).

For accurate risk assessment to occur, the factors associated with the type of risk being assessed must be known. Knowledge about the risk factors associated with recidivism typically is generated through research in which the recidivism rate for offenders with a particular characteristic is compared to the recidivism rate for offenders without that characteristic, or for offenders possessing other characteristics (Hanson, 2000). To date, no single characteristic (that is, "risk factor") has been found in isolation to be a robust predictor of recidivism. As a result, the assessment of risk by necessity involves the combination of a number of risk factors in a meaningful manner.

Karl Hanson and his colleagues (Hanson & Bussière, 1998; Hanson & Morton-Bourgon, 2005) have published the results of a series of meta-analyses2 that together have shed considerable light on the known universe of static risk factors associated with sexual recidivism. The strongest predictors of sexual recidivism are factors related to sexual criminality, such as a demonstrated sexual interest in children, a history of prior sexual offenses, the age of onset of sexual offending behavior, and having committed a variety of sexual offenses. Factors relating to a lifestyle of instability/criminality were also found to be associated with sexual offense recidivism (Hanson & Bussière, 1998; Hanson & Morton-Bourgon, 2005). Criminal lifestyle characteristics (e.g., substance abuse, history of rule violation) are also the factors most strongly related to violent and any recidivism among sex offenders, mentally disordered offenders, and offenders in general (Hanson & Morton-Bourgon, 2009). Over the past three decades, numerous studies have examined the factors that are related to sexual offense recidivism, and not a single study has found the specific type of crime an offender is convicted of to be predictive of the likelihood of recidivism (Freeman & Sandler, 2010).

Sex offender risk assessment, while similar in many ways to the assessment of other latent constructs (psychological concepts) within psychology and mental health, differs in at least one significant aspect. The construct being assessed—the commission of a new sexual offense—is unobservable and is likely never to be observed by the assessor. Sex offender risk assessment entails a process of estimating the likelihood of a future event based entirely on secondary, indicator variables (Hanson, 2009). While actuarial risk assessment tools must meet standard criteria for psychological measures (e.g., reliability and validity), the utility of these instruments depends considerably on the selection of relevant risk factors and the methods used to combine these factors to arrive at a meaningful overall assessment of risk (Hanson, 2009). It is important to keep in mind that for purposes of risk assessment, the utility of a risk factor depends on its empirical relationship to the outcome being predicted (Helmus et al., 2012). The consideration of base rates is also critical (Thornton, Hanson, & Helmus, 2011). The base rate is equal to the proportion of a group that shares a specific characteristic. For purposes of sex offender risk assessment, the relevant base rate is the proportion of convicted sex offenders who commit a subsequent sexual offense, either over a specified timeframe or over the course of their lifetime. The base rate is arrived at through reference to large meta-analyses of sex offender recidivism, such as Hanson and Bussière (1998) and Hanson and Morton-Bourgon (2005). These studies found the 5-year recidivism rate to be approximately 13 percent. It is important to remember, however, that this figure is an underestimate, given that not all recidivist behavior is detected.

The accurate assessment of risk involves gaining an understanding of all available, relevant factors associated with the known criterion or outcome behavior. While research findings are quite consistent regarding the historical, relatively unchangeable factors referred to as "static" risk factors (e.g., age at first offense, number of previous convictions), there is less agreement at present regarding more fluid, changeable risk factors referred to as "dynamic" risk factors (e.g., employment status, cooperation with supervision). The utility of a rather fixed set of static variables associated with sex offender risk has been established in numerous studies (Hanson & Bussière, 1998; Hanson & Morton Bourgon, 2005), and empirically identified static risk factors are a primary component of several valid and reliable instruments used in the field today (e.g., Static 99R, Static-2002R, MnSOST-R).

A number of instruments incorporating dynamic factors have appeared in recent years, such as the Stable-2007/Acute-2007 (Hanson et al., 2007) and the Forensic version of the Structured Risk Assessment (Thornton & Knight, 2009). Neither of these instruments, however, has the research backing of the more established instruments of static risk, such as the Static-99R and Static 2002R. A recent meta-analysis (Mann, Hanson, & Thornton, 2010) provides the most complete understanding to date of the relationship between a host of dynamic factors and sex offender recidivism.

"The use of third-generation risk assessment instruments that incorporate both static and dynamic risk factors is becoming more prevalent. These instruments have the potential added benefit of providing targets for treatment."

The use of third-generation risk assessment instruments that incorporate both static and dynamic risk factors is becoming more prevalent (Hanson & Morton-Bourgon, 2009; A. Phenix, personal communication, May 10, 2011). These instruments have the potential added benefit of providing targets for intervention. An example of a third-generation instrument is the Level of Service/Case Management Inventory (Andrews, Bonta, & Wormith, 2004), which provides a general assessment of risks and needs for criminal-justice-involved persons. The Violence Risk Scale: Sexual Offender Version (VRS:SO) is a recently developed instrument specifically designed to assess risks and needs among sex offenders. This measure contains 7 static factors and 17 dynamic factors; the dynamic, treatment-change factors are based on the Transtheoretical Model of Change (Beggs & Grace, 2010). (For more on treatment, see chapter 7, "The Effectiveness of Treatment for Adult Sex Offenders," in the Adult section.)

A variety of sex offender risk assessment tools possess acceptable, empirically supported psychometric properties (Doren, 2002, 2006; Hanson, 2009; A. Phenix, personal communication, May 10, 2011). While a complete review and analysis of these instruments is beyond the scope of this chapter, a meta-analysis conducted by Hanson and Morton-Bourgon (2009) provides important insights concerning the relative accuracy of different approaches. Their analysis consisted of 536 findings drawn from 118 distinct samples with a total sample of 45,398 sex offenders in 16 different countries. The followup periods ranged from 6 months to 23 years; the average followup period was 5 years and 10 months (standard deviation = 46.6 months). The following types of risk assessment approaches were included in the analysis: empirical actuarial, mechanical (using factors chosen primarily on the basis of theory or literature reviews), adjusted actuarial, structured professional judgment, and unstructured professional judgment.

Hanson and Morton-Bourgon (2009) concluded that empirically derived actuarial approaches were more accurate than unstructured professional judgment in assessing risk of all outcomes (sexual, violent, and any recidivism). The accuracy of structured professional judgment methods fell in between these two methods. For the prediction of sexual recidivism, actuarial instruments designed for assessing the risk of sexual recidivism had the greatest predictive accuracy, followed by mechanical approaches designed for assessing the risk of sexual recidivism and actuarial instruments designed for assessing the risk of general recidivism. Unstructured professional judgment and actuarial instruments for assessing violent recidivism risk were less accurate in assessing the likelihood of sexual recidivism. The predictive accuracy of structured professional judgment fell in between that of actuarial instruments and unstructured professional judgment approaches. In addition, structured professional judgment exhibited a large degree of variability in the few studies that examined this method (Hanson & Morton-Bourgon, 2009).

Hanson and Morton-Bourgon (2009) also found that for assessing the likelihood of sexual recidivism, the best-supported instruments were the—

  • Static-99 (Hanson & Thornton, 2000).
  • Static-2002 (Hanson, Helmus, & Thornton, 2010).
  • MnSOST-R (Epperson et al., 2000).
  • Risk Matrix-2000 Sex (Kingston et al., 2008).
  • SVR-20, specifically using the mechanical approach of adding up the item scores (Boer et al., 1997).

For assessing the likelihood of violent (including sexual) recidivism, the best-supported instruments were the—

  • Violence Risk Appraisal Guide (VRAG) (Webster et al., 1994).
  • Sex Offender Risk Appraisal Guide (SORAG) (Quinsey et al., 2006).
  • Risk Matrix-2000 Combined (Thornton, 2007).
  • Statistic Index of Recidivism (SIR) (Nafekh & Motiuk, 2002).
  • Level of Service Inventory-Revised (LSI-R) and its variants (Andrews, Bonta, & Wormith, 2004, 2006).

Some risk assessment experts have suggested that the accuracy of purely actuarial approaches can be increased if certain dynamic risk factors (e.g., active substance abuse, demonstrated pro-offending attitudes) are included in the assessment instrument or otherwise considered as part of the assessment process. Discussions of the relative merits of this approach can be found in Wollert and colleagues, 2010; Hanson and Morton-Bourgon, 2009; Doren, 2002; and McGrath, Cumming, and Lasher, 2012. One dynamic risk factor that has received considerable attention in this context is the offender's age at the time of assessment. The inverse relationship between age and criminal offending—as age increases, offending decreases—is one of the more robust findings within criminology. This relationship has been found to hold across time and geographic locations, for different types of crimes and offenders, and in both community and incarcerated offender populations (Hirschi & Gottfredson, 1983). Age as an adjusting factor in risk assessment has received considerable attention not only because of the strength and consistency of its relationship to offending, but also because some actuarial instruments (e.g., Static-99 and Static-2002) have been found to underestimate the likelihood of recidivism for younger offenders and to overestimate it for older offenders (Helmus et al., 2012; Wollert et al., 2010). As a result of these findings, the Static-99 and Static-2002 have been revised to better account for the impact of the offender's age at the time of assessment, resulting in the Static-99R and Static-2002R. (Both of these revised instruments do not need to be adjusted for age.) Using age-adjusted risk tables is especially important when assessing older offenders.

Another set of factors often considered as potential adjustments to actuarial measures are those referred to as "criminogenic needs" (Bonta, 1996) or psychologically meaningful risk factors (Mann, Hanson, & Thornton, 2010). These are dynamic (that is, changeable) risk factors that can serve as targets for intervention efforts. For a risk factor to be considered psychologically meaningful, there must be a plausible rationale that the factor is a cause of sexual offending and there must be strong empirical evidence that the factor predicts sexual recidivism. This latter requirement is best demonstrated through research associating variation between groups in the predictor (proposed predicting factor) with variation between groups in the rate of failure (Hanson, 2009).

While it stands to reason that clinicians would want to consider dynamic factors when assessing risk, doing so via an adjustment of actuarial instruments may not be the most effective way. Although few studies have examined the effects of making actuarial risk assessment clinical adjustments, those that have done so found that overrides—a consideration of factors outside the actuarial scheme (i.e., the evaluator judges whether the predicted recidivism rate is a fair evaluation of the offender's risk)—decrease predictive accuracy (Hanson, 2009; Hanson & Morton-Bourgon, 2009). These studies (Gore, 2007; Hanson, 2007; Vrana, Sroga, & Guzzo, 2008) have all been prospective in nature, and they involved actuarial instruments currently used with sex offenders.

"Empirical research has yet to identify a single "best" risk assessment instrument."

It is important to note that empirical research undertaken to date has yet to identify a single "best" assessment instrument. With this and the limitations of using only one risk assessment instrument (particularly in especially high-stakes situations such as civil commitment evaluations) in mind, clinicians have considered the potential benefits of using more than one instrument during the assessment process (Doren, 2002; Hanson, 2009, 2011). In fact, in a study of evaluators who conduct civil commitment evaluations, Jackson and Hess (2007) reported that 79.5 percent of the evaluators use more than one actuarial instrument in their sex offender civil commitment evaluations.

Two primary rationales support the notion that using more than one instrument provides potential benefits. First, classical test theory suggests that increasing the number of items in an assessment increases reliability and coverage. Second, if there are multiple driving forces behind sexual offending behavior, and individual risk assessment instruments tap these underlying dimensions or pathways to sexual offense recidivism differentially, then the use of multiple instruments would have a distinct advantage over the use of a single instrument alone. As Doren (2002, p. 138) points out, "The evidence for multiple underlying dimensions potentially driving sexual offending represents the main relative weakness to using only the 'best' single risk assessment instrument in a sex offender civil commitment evaluation." 

Indeed, the empirical evidence suggests that multiple dimensions or pathways underlie sexual offending, with a number of scholars describing a convergence between two of these dimensions: sexual criminality and general criminality. Doren (2002) describes the high sexual criminality/low general criminality pathway as typical of the generally law-abiding pedophile, and the low sexual criminality/high general criminality pathway as typical of an antisocial individual for whom sexual violence is simply one of many manifestations of a criminal behavioral pattern. Evidence for these two pathways also has been found in meta-analytic studies of the factors associated with sex offender recidivism (Hanson & Bussière, 1998; Hanson & Morton-Bourgon, 2005). Hence, an evaluation of both dimensions/pathways as part of the risk assessment process seems beneficial and advisable, whether it is done using a single instrument that assesses both dimensions or multiple instruments that tap each dimension separately. (For more about pathways, see chapter 3, "Sex Offender Typologies," in the Adult section.)

These two underlying dimensions of sexual offending were discussed in a recent study of the incremental validity of a number of actuarial instruments (Babchishin, Hanson, & Helmus, 2011). As part of that study, the Rapid Risk Assessment for Sex Offense Recidivism (RRASOR) instrument was found to tap sexual criminality, while the Static-99 was found to assess risk along the general criminality pathway. Further, Babchishin, Hanson, and Helmus (2011) found that the RRASOR (which taps the sexual criminality dimension) and the Static-99R and Static-2002R (both of which tap the general criminality dimension) all added incremental validity to one another, in spite of substantial intercorrelations and substantial item overlap across the three instruments. 

There are other compelling reasons to use more than one instrument during the risk assessment process, even when the instruments tap the same dimension or the same theoretical domain. Including a larger number of items that assess the same construct and having similar predictive accuracy increases reliability and adds to the overall predictive accuracy of the procedure. When using scales that assess the same domain of risk factors, averaging the scores is recommended. If the scales do not assess the same factors, evaluators will need to apply a scoring model that identifies the latent constructs assessed by the scales and that is based on empirical evidence concerning the manner in which the separate constructs should be weighted and combined. If such an empirically supported model is not possible, it is recommended that evaluators use the single instrument in which they have the most confidence (Babchishin, Hanson, & Helmus, 2011).

Another issue of critical importance in sex offender risk assessment is the communication of risk assessment findings (Babchishin & Hanson, 2009; Doren, 2002; Hanson, 2009). Currently, nominal descriptors of risk (low, moderate, and high) are used most commonly (Babchishin & Hanson, 2009). While qualitative descriptions in general and these particular nominal descriptors are usually preferred over numerical formats for communicating risk, the use of qualitative labels alone has certain limitations. Perhaps the most significant limitation is that clinicians (as well as decision-makers) can have very different interpretations of what these nominal categories represent. The context in which risk assessment findings are communicated can also influence interpretation.

One way to mitigate the problems associated with the exclusive use of nominal categories is to also provide numerical indicators of risk, such as a recidivism rate probability, a percentile rank, or a risk ratio. There are various numerical formats commonly used to convey absolute risk, such as frequencies (e.g., the likelihood of recidivism is 1 out of 10) and percentages (e.g., the likelihood of recidivism is 10 percent), both of which are usually accompanied by a specific timeframe (e.g., within the next 5 years). Relative risk estimates, such as percentile ranks (e.g., the individual's risk for reoffense is equal to or greater than 90 percent of offenders) and risk ratios (the individual is four times more likely to sexually recidivate compared to the average offender), are useful as well.

While numerical estimates provide more information and are potentially less ambiguous than qualitative descriptors alone, they too have limitations. For example, even though the assessed risk is the same, risk frequencies reported with larger denominators (e.g., 10 out of 10,000 compared to 1 out of 1,000) tend to result in higher perceived risk. Interpreting numerical risk estimates properly can also be a challenge when base rates for the behavior in question are unknown or are not taken into consideration. Simply put, people tend to overestimate the likelihood of low-probability events and underestimate the likelihood of high-probability events. For instance, people are more likely to fear flying than driving, even though the likelihood of dying in a car crash is many times that of dying in a plane crash.

Evaluators can also make mistakes when communicating the results of risk assessments. Doren (2002) has identified three common errors in communicating results when using a single instrument: incorrectly describing the risk percentage associated with a particular score, neglecting to address sampling error or failing to provide confidence interval estimates, and ignoring or incorrectly stating the qualifiers as to what has been assessed.

Consumers of risk assessment information typically desire more than a simple nominal or numeric indicator of risk. Frequently, decision-makers want the risk assessment process to provide them with information on the likelihood of recidivism, the potential consequences associated with recidivism, and what might be done to mitigate the assessed risk (Hanson, 2009). Doren's (2002) recommendations for communicating the results of sex offender risk assessment, especially in cases involving civil commitment, include the following:

  • Nominal risk categories should be accompanied by numerical risk estimates. When used in tandem, nominal and numerical means of conveying risk are more accurate and informative than either one is in isolation.
  • Nominal categories should be explicitly defined so as to limit the degree to which readers define for themselves the meaning of the specific nominal descriptors. Two examples would be stating that "low risk" means that the risk of sexual recidivism is similar to what would be expected from a group of non-sex offenders, and "high risk" means that an offender is more likely than not to sexually recidivate over the course of his lifetime.

Significant growth has occurred in recent years in both the development of sex-offender-specific risk assessment instruments and their use in the field. While significant advances have been made regarding the reliability and predictive validity of instruments, a number of limitations remain. As noted above, there is currently no single "best" risk assessment for all offenders in all situations. In fact, there are certain populations for whom there is no validated risk assessment instrument (e.g., child pornography offenders and female offenders). (For more on child pornography offenders, see chapter 4, "Internet-Facilitated Sexual Offending," in the Adult section.) In addition, while development and testing of third-generation instruments continues, some experts are skeptical that a single actuarial scale containing all relevant risk factors could ever be developed (Hanson, 2000). Therefore, contemporary risk assessment involves a bit of paradox: even though research on risk assessment has largely eliminated subjective judgment from within the risk assessment process itself, clinical judgment on the part of the evaluator is still needed to make valid, research-informed decisions about the appropriate risk assessment instrument(s) to apply in any particular setting. To that end, Hanson (2009) has provided the following set of qualities to guide the future of sex offender risk assessment:

  • Assess risk factors whose nature, origins, and effects can be understood.
  • Enable reliable and valid assessment of clinically useful causal factors.
  • Provide precise estimates of recidivism risk.
  • Allow all relevant factors to be considered.
  • Inform the development of treatment targets and risk management strategies.
  • Allow the assessment of both long- and short-term changes in risk.
  • Incorporate protective factors as well as risk factors.
  • Facilitate the engagement of the patient/offender in the assessment process.
  • Use risk assessment methods that are easy to implement in a broad range of settings.


Significant advancements in the science and practice of sex offender risk assessment have occurred over the past two decades. A number of reliable, valid approaches for assessing sex offender risk are now available. Rigorous scientific research has demonstrated that respectable levels of predictive accuracy have been obtained with purely actuarial risk assessment approaches, approaches using structured professional judgment, and the mechanical combination of items from structured risk schemes. While research evidence to date has not indicated which of these approaches are best suited to specific testing circumstances and contexts (Hanson, 2009), recent meta-analyses (Hanson & Morton-Bourgon, 2009) suggest that purely actuarial assessment approaches should be favored over other approaches for the assessment of risk for sexual reoffense (Hanson, 2009). Ultimately, however, decisions about the best approach or instrument to use should be made in the context of the assessment setting, the characteristics of the individual being assessed, and the specific purpose of the risk assessment.

"Training and monitoring of evaluators is needed to ensure that risk assessment procedures and instruments are used appropriately and with integrity."

Many of the purely actuarial tools in wide use today can be completed quickly and easily by a variety of trained personnel (Klima & Lieb, 2008). The advent of automated actuarial tools conceptually allows even clerical workers to compute risk scores using these instruments. It is nonetheless important to provide ongoing training and monitoring of evaluators to ensure that risk assessment procedures and instruments are always used appropriately and with integrity. The need for training and technical assistance in the context of risk assessment was identified by the 2012 SOMAPI forum participants.

One of the primary challenges for the field in the future will be to identify more comprehensively the risk factors (both static and dynamic) that are related to sexual offending. Identifying these factors and incorporating them into the risk assessment process will help clinicians and decision-makers better match risk levels to treatment and management efforts, thereby fulfilling the promise of third-generation risk assessment instruments (Bonta, 1996). The need for tailored rather than uniform interventions, and the need to match sex offender treatment and management efforts to the risk levels and criminogenic needs of sex offenders, were acknowledged by the expertsboth researchers and practitionerswho participated in the SOMAPI forum. 

Given the lack of a single best risk assessment instrument, evaluators will continue to have to rely on their professional judgment to select and employ the best risk assessment approach for the circumstances and setting. Incorporating dynamic risk factors at this point in time requires a structured approach and subsequent clinical adjustment, as there are no universally agreed-upon weights for the relevant dynamic risk factors (A. Phenix, personal communication, May 10, 2011). Additional research concerning the use of dynamic risk factors is clearly needed, along with research on how best to use knowledge about the offender's strengths and assets (protective factors) as the factors that lead to desistence from crime (Griffin et al., 2008; K. Hanson, personal communication, April 8 and June 7, 2011; Maruna & LeBel, 2003).

Research on the best ways to revise assigned risk based on post-index behavior or qualities also is needed. In effect, this entails identifying treatment targets and assessing the impact of treatment on risk and other factors, such as institutional misconduct or the amount of time that has elapsed without a new conviction (K. Hanson, personal communication, April 8 and June 7, 2011). The ability to detect meaningful changes in risk, especially for high-risk offenders, is particularly important (Hanson, 2011; Olver et al., 2007). The VRS:SO is a promising development in this area (Beggs & Grace, 2010; Thornton, Hanson, & Helmus, 2011). Other instruments to consider for gauging changes in risk over time include the STABLE-2007 and the SRA—Forensic Version (Thornton & Knight, 2009). As noted previously, the Static-99 and Static-2002 have recently been revised to incorporate the impact of aging on risk, resulting in the inclusion of new age weights and the publication of the Static-99R and Static-2002R (Helmus et al., 2012). 

There also is a need to devise more effective and intuitive means of communicating risk assessment findings. Communication of risk should be tailored to the purpose and setting of the assessment, and both qualitative descriptors and numerical estimates that consumers of risk assessment information can use to guide sex offender management decision-making should be provided. Furnishing decision-makers with both an accurate, contextual understanding of risk, and also with recommendations for mitigating and managing risk, is likely to be most beneficial.

"Based on current knowledge, using science-based, actuarial methods to assess sex offender risk is advisable."

In conclusion, based on current knowledge, using science-based, actuarial methods to assess sex offender risk is highly advisable (Doren, 2002; Hanson & Morton-Bourgon, 2009; Tabachnik & Klein, 2011). As Hanson and Morton-Bourgon (2009, p. 10) aptly state, "Given its genesis in data, the empirical actuarial approach will ultimately provide the best estimates of absolute risk." In fact, such instruments should not be ignored in assessing the risk for sex offender reoffense unless there is clear and justifiable reason to do so, such as in cases for which no applicable risk instrument exists (Hanson & Morton-Bourgon, 2009).

For assessing the likelihood of sexual recidivism, the best-supported instruments are the Static-99, Static-2002, MnSOST-R, Risk Matrix-2000 Sex, and adding the item scores from the SVR-20 (Hanson & Morton-Bourgon, 2009). For assessing the likelihood of violent (including sexual) recidivism, the best supported instruments are the VRAG, the SORAG, the Risk Matrix-2000 Combined, the SIR, and the LSI-R and its variants (Hanson & Morton-Bourgon, 2009).


1 The terms "evaluator" and "evaluation" used throughout this chapter refer to the individual performing the risk assessment and the overall risk assessment process, respectively.

2 A meta-analysis combines the results of many evaluations into one large study with many subjects.


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