Risk assessment for juvenile sex offenders

Risk Assessment

1. Int J Offender Ther Comp Criminol. Feb;57(2) doi: /​X Epub Dec 5. Since , the sex offender domain of the IPSA has been administered to two groups of juveniles. The parole population sample consists of Level 1 and. Recidivism (ERASOR) and the Juvenile Sexual Offense Recidivism Risk For more information, see the Sex Offender Management Assessment and Planning​.

Since , the sex offender domain of the IPSA has been administered to two groups of juveniles. The parole population sample consists of Level 1 and. 1. Int J Offender Ther Comp Criminol. Feb;57(2) doi: /​X Epub Dec 5. However, much of the literature on risk factors for juvenile sexual offending remains.

Since , the sex offender domain of the IPSA has been administered to two groups of juveniles. The parole population sample consists of Level 1 and. When assessing risk with sex offenders in general, and with juveniles in The original version of this risk assessment scale for juvenile sex offenders was. Approaches to Assessing Risk. Now that we have reviewed some of the potential risk factors for sexually abusive youth, let's talk about some of the processes by.






T he assessment of sexual recidivism risk for juveniles who commit sexual offenses serves several purposes. The overall purpose is to estimate the risk of future sexual offending so that the most effective steps can be taken to reduce, contain or eliminate that risk. Hence, risk assessment essentially serves as sex investigative tool that helps inform and guide various intervention, treatment and legal processes. A risk assessment can be administered at different points once a juvenile is identified by authorities as the perpetrator of a sexual offense.

An assessment can be administered during the intake screening process to inform and guide authorities as to the appropriate course of action.

In the event of a referral to the court, an assessment can be administered prior to or during adjudication or trial, when transfer to the adult criminal court occurs to provide the court, its officers and other professionals with risk information that can be used in legal proceedings, as well as in decision-making regarding supervision or treatment.

Of for, the point in the process at which an assessment is administered, as well as the purpose of the evaluation, may have significant impact on the risk evaluation. Within the context of treatment, risk assessment is typically used to set a baseline assignment of risk and to then periodically re-evaluate risk during treatment.

In addition, the risk assessment process can be used to determine the type and intensity of treatment needed assessment to help define targets for treatment and case management. Regardless of the purpose of risk assessment or the point at which it occurs, assessing risk involves risk predictions about the likelihood of future behavior, which is an inherently difficult task under any circumstances.

The process of risk assessment for juveniles who sexually offend is further complicated by the relatively low base rates of sexual recidivism found among juveniles. Juvenile risk assessment is complicated even further by the ongoing development and maturation of youth.

Accordingly, risk assessment models and tools must account for these developmental factors in order to accurately estimate risk. Hence, Stockdale, Olver and Wong note that adolescent risk assessment instruments must be capable of capturing changes in risk that result from developmental changes, with or without treatment.

Whereas the process of juvenile risk assessment was once largely driven by adult risk assessment research and instrumentation, the field of juvenile risk assessment has largely developed in its own right over the past 15 or so years, and continues to do so.

Like adult risk assessment, juvenile assessment assessmdnt traditionally offenders on the identification and assessment of factors within the individual juvenile increase and possibly predict risk for sexual recidivism. Risk assessment for sexual recidivism — both juveniles and adult — has also traditionally focused on static risk factors that reflect risk behaviors for experiences related to sexual offending. Ogfenders risk factors are those that have previously occurred and will remain unaltered over time.

Contemporary risk assessment, however, also includes a focus on dynamic risk factors. Dynamic risk factors are those associated with current behaviors, thoughts, feelings, attitudes, situations, interactions and relationships. So named because they are fluid and sometimes relational or situational, dynamic risk factors may thus change over time, particularly through offenders form of treatment.

Dynamic risk factors are sometimes referred to as criminogenic needs because they contribute directly or indirectly to criminal behavior.

In addition, both juvenile and adult risk assessment can also be used as a process by which to identify offfenders assess risk factors, as well as protective factors, or those elements, strengths, supports and circumstances that mitigate risk for sexual recidivism, increasingly considered in contemporary juvenile risk assessment. Given the importance of risk assessment in sex offender management and treatment, this chapter reviews the literature on the assessment of risk for sexual recidivism for juveniles who commit sexual offenses.

It summarizes what is scientifically known about risk assessment for juveniles who sexually assessment and presents key, up-to-date research findings on the defining features and predictive accuracy of commonly used assessment instruments.

When reading this chapter, it is important to keep the following in mind. First, while it is possible to describe the historical context and current state of juvenile risk assessment, there is ongoing controversy sex the field about the best model to employ in risk assessment and the capacity of various models and offenders to accurately predict risk for sexual recidivism. Both of these issues will be discussed in detail. Second, although research on female juveniles who commit sexual offenses and preadolescent children who engage in sexually ofgenders and sexually troubled behavior is emerging, the existing knowledge offenders concerning juvenile risk assessment is primarily based on studies of adolescent males who commit sexual offenses.

Little has changed in this regard, despite increased research on female juveniles, and no risk assessment instrument risk that is specifically designed offenders assess risk in the adolescent female population. The same continues to be true ofenders respect to both understanding and estimating risk in children with sexual behavior problems, and the research stream for this population has not picked up in asessment noticeable manner.

Accordingly, although much of the information for this review is pertinent to both males and females, and to adolescents and pre-adolescents, the reader ffor bear in juvenile that the research cited and discussed in this chapter is most directly relevant to male adolescents who commit sexual offenses.

Juvenile sexual offending takes place within an environment of developmental, social and contextual circumstances that differ for each young person, and we recognize the heterogeneity of each individual despite shared features and commonalities. Juvenile risk assessment, therefore, focuses not only on adolescents who commit sexual offenses, but also on the systems within which they live, learn and function and on which they depend for structure, guidance and nurturance.

In short, risk assessments of juveniles who sexually offend place behavior and risk factors in the context of the social environment, as well as assessment context of child and adolescent development. In fact, unlike adult odfenders assessment instruments, the most widely used juvenile risk assessment instruments set what are essentially time limits or expiration dates for any individual's assessed risk level or score, either requiring reassessment of risk within for specified time period such as every six months 2 or noting that the risk estimate is limited to offendsrs recidivism prior to age For instance, in their study of 1, juvenile offenders, van der Put and colleagues found that the assesssment of both static and dynamic risk factors on recidivism varied by the age of the adolescent.

Evaluation should include a wide range of individual, social, interactional and contextual factors. Currently, two general models are used in juvenile risk assessment: the actuarial model and the clinical model. In both models, the assessment process attempts to identify and evaluate the likely effects of risk factors believed to be associated with sexual recidivism. In the actuarial model — also known as statistical or mechanical risk — risk determination is based entirely on a statistical comparison between the personal characteristics and past behavior of the juvenile and those of known assesement.

The assessment of static risk factors is a distinguishing feature of the actuarial model, although clinical models exist as well. Clinical risk assessment is primarily based on observation and professional judgment, rather than statistical analysis, in which assessment evaluator attempts to develop an understanding of the juvvenile and the presence offfenders likely effect of defined risk factors. In contemporary applications of the clinical model, a structured risk assessment instrument is used to guide clinical judgment.

Unlike actuarial assessment, clinical risk assessment typically evaluates both static and risk risk factors and, increasingly, protective factors that may decrease the risk of sexual reoffense. Sex fact, Quinsey juveenile colleagues have argued for strict adherence to the actuarial model and the elimination of clinical judgment from the risk assessment process altogether.

These positions, however, are not universally agreed upon, and there is strong disagreement with the assertion that actuarial risk assessment has greater predictive power juvenile clinical assessment Boer et al.

Further, For, Boer sex Eher and Rich have argued that actuarial assessment does not provide information about risk or possible risk management strategies that are highly personalized for the individual being assessed; hence, it fails to meet the practical offenders ethical issues and requirements sex to any individual case. Further, it is clear that the rosk and clinical assessment models both have strengths and weaknesses.

Campbell writes that neither actuarial nor clinical risk offenders instruments stand up to rigorous scientific scrutiny, noting that all assesmsent actuarial ris, clinical risk assessment instruments are insufficiently standardized, lack inter-rater reliability, 4 are absent of adequate operational manuals and generally fail to satisfy significant scientific standards. Similarly, Grisso and Hart and colleagues have argued that such instruments have for yet achieved the level of psychometric rigor needed to meet publication standards.

Sixteen years or so later, little has changed, despite assessment in both adult and juvenile risk assessment. First-generation methods primarily involved unstructured clinical judgment, whereas second-generation methods involved statistically derived and static actuarial assessments of risk.

Third-generation methods, which are increasingly common in sexual risk assessments of adult offenders, incorporate both the actuarial base of a static assessment and the dynamic factors of a clinical assessment.

Fourth-generation methods integrate an even wider range of dynamic factors, incorporating factors relevant to treatment interventions, case management and monitoring. Third- and fourth-generation methods not only recognize the utility of both static and dynamic risk factors, but also that "there is no reason to think that one type is sex to another when it comes to the predicting recidivism" Rsk,p. In fact, when dynamic measures are part of the assessment risi, the sex accuracy of risk assessment assessment exceed that which may be achievable with only static risk factors Allan et al.

McGrath and Thompson report that although static juvfnile dynamic risk factors both predicted sexual recidivism in juveniles who commit sexual offenses, a combination of static and dynamic factors resulted in a significant improvement in prediction. While the characterizations and propositions described above are largely drawn from the literature on risk assessment for juvenile sexual offenders, they are equally offenders in the context of risk assessment for juveniles who commit sexual offenses, in which, thus far, clinical risk assessment represents almost the entirety of juvenile sexual risk assessment instruments, with the exception of a single actuarial instrument.

Moreover, these ideas and principles are essential for understanding the groundwork upon which juvenile risk assessment is built. Epps describes the goal of juvenile risk assessment as synthesizing psychosocial, statistical, factual and environmental information in a manner that allows assessment decisions asswssment be made about matters of management, treatment and placement.

Within this context, Will describes three broad purposes for juvenile risk assessment: i the assessment of risk for re-offense, ii the development of a clinical formulation upon which treatment can be based and iii the assessment of the juvenile's motivation to accept and engage in treatment.

Notably, these three goals closely approximate the principles of for, need and responsivity that have been increasingly central in practice. Graham, Richardson and Bhate describe six overarching and interactive goals for juvenile risk assessment:. In short, the goals of a comprehensive risk assessment process extend beyond the assessment of risk alone.

To this end, Prentky, Righthand offenders Lamade juvenil juvenile risk assessment as informing the treatment planning process with respect to risk-relevant needs and interventions designed to ror prosocial rehabilitation.

Similarly, Viljoen, Brodersen, Shaffer and McMahon have stated the "goal of risk assessment is to identify youths' needs in order to assist in planning individualized risk management or risk reduction efforts" p.

An extensive literature has developed that juvenile identified and discussed risk factors for juvenile sexual offending. However, much of the literature juvenile risk factors for juvenile sexual offending remains theoretical and descriptive, rather than the result of reliably replicated statistical research. It also is characterized by a number of methodological problems and other limitations Spice et al.

Spice and colleagues noted that early studies on offenders sexual recidivism were often based on follow-up periods of less than three years, and that early, as well as more contemporary, studies often employed small sample sizes.

They also noted that risk factors examined vary widely from one study to another. Similarly, McCann and Lussier for that the risk factors examined in many studies were selected by researchers based on their own clinical experience, the literature on adult sexual recidivism and, until recently, a lack of theoretical understanding regarding sexual offending behavior assessment juveniles. Additionally, risk factors for juvenile sexual and nonsexual offending are significantly influenced by developmental processes in children and adolescents, and are not necessarily stable or uniform during adolescence Kim and Duwe, ; Quinsey et al.

Given these problems, it is not surprising that findings regarding risk factors vary considerably and are inconsistent across different studies Spice et al. Despite the problems outlined above, the empirical research indicates that it is the presence and interaction of multiple risk factors, rather than the presence offenders any single risk factor alone, that juvenile most important in understanding risk.

Thus, all risk assessment sex — risk of whether they are used with adults or juveniles, or whether they are actuarial or clinical — include multiple risk factor items, and all risk assessment processes are concerned not only with the presence of different risk factors, but also with the interactive and amplifying effects of multiple risk factors.

The problem for the low base rate for juvenile sexual recidivism complicates the process of determining which individual risk factors are likely to juvenile most important in juvenile risk assessment. In fact, many of the risk factors included in juvenile risk assessment instruments used today have face validity an intuitive and perhaps common sense appeal that appears to reflect aspects of riskbut very little proven predictive validity.

In any case, as Prentky et juvenile. That is, establishing causality requires empirical evidence that the presence or absence of the risk factor results in changes in the base rate of offending behavior Prentky et al. This is, at best, a difficult task.

Risk remaining 14 factors they describe as either third-tier "possible" risk factors based on general clinical support asseessment fourth-tier "unlikely" risk factors that either sex empirical support or are contradicted by empirically derived evidence. Although evidence supporting some elements of their typology is found in later studies, it is also true that later studies have found evidence for factors not supported in their four-tier typology, as well producing some evidence for still more risk factors.

Indeed, the literature is mixed and inconsistent. Leroux et al. Similarly, Miner and colleagues identified social isolation as a risk factor, or predictor, for adolescents who sexually abuse children but not peers or adultsas well as the adolescent's experience of masculine inadequacy.

In their juvenile of data from the National Longitudinal Study of Adolescent Health, Casey, Beadnell and Lindhorst also found childhood sexual victimization to be a significant predictor of later sexually coercive behavior, as was a history of adolescent delinquency.

Similarly, Leroux et al. These included a history for prior nonsexual offenses, the use of threats or weapons, having a male victim and having a child victim. In addition, McCann asswssment Lussier found that older age upon intake for treatment was associated with increased likelihood of reoffending.

Nevertheless, they noted that even the risk factors found to be the best predictors of assessment recidivism in their study had a relatively small effect size and were based on findings derived from analyses involving small sample sizes. In an earlier meta-analysis, Heilbrun, Lee and Cottle 7 concluded that younger age at first offense, prior noncontact sexual offenses and having an acquaintance victim rather than a ogfenders victim were associated with sexual recidivism.

However, in their study of juveniles who commit sexual offenses, Spice and colleagues found that only opportunity to reoffend was significantly associated with sexual recidivism, although a number of risk and protective factors were linked to nonsexual recidivism.

As the findings presented above demonstrate, research on the risk factors for sexual recidivism has produced inconsistent and sometimes contradictory results. Indeed, as Spice and colleagues observe, it is clear that the risk literature regarding risk factors for sexual recidivism among sexually abusive youth is disconnected and varied, with little to unify it. Whether the disparate findings are an artifact of sex methodological variations found across studies, a reflection of real-world risk factor dynamics or some combination of the two remains unknown at this time.

Spice and colleagues and Offenderw and Lussier have voiced concerns about the idiosyncratic nature of individual studies as well as the lack of consistency across studies in terms of research designs, samples, hypotheses and statistical procedures. However, Rich argues that risk factors for sexual recidivism may operate differently in different people, and at different points in child and adolescent development.

In discussing their findings, Worling, Bookalam and Litteljohn , p. The fact that more contemporaneous ratings were … more predictive of subsequent sexual offending suggests that it is important for clinicians to reassess adolescents and that clinical and forensic decisions are likely to be more accurate if they are based on more recent risk assessments.

Note: Results shown in area under the curve values. Rates for nonviolent crimes are not reported in this chapter.

Indeed, the study conducted by Worling — the instrument's primary author — and his colleagues shows variability in results depending on what is measured, when it is measured and how it is measured.

Area under the curve values range from 0. Although Worling et al. Moreover, for the purposes of research, Worling and colleagues, like researchers in some other studies, scored the ERASOR in ways that most field evaluators would not. In addition to a clinical rating low, moderate or high based on the final judgment of the evaluator which is the way in which ERASOR is designed to be scored by evaluators in the field , Worling et al.

As noted, based on the design of and instructions for the instrument, it is only the clinical rating score that is most likely to be used in the field. While some studies other than that conducted by Worling and his colleagues have found moderate to high levels of sexual recidivism predictive accuracy associated with the ERASOR clinical rating score, others have not produced similar results. For example, Chu and colleagues reported an area under the curve value of 0.

However, Viljoen and colleagues examined the predictive validity of ERASOR as part of a larger study of risk assessment instruments and reported a value of only 0. In their study, Rajlic and Gretton reported that ERASOR was moderately predictive of sexual recidivism, with an overall area under the curve value of 0. When used to evaluate risk for sexual recidivism among juveniles who had previously committed only sexual offenses, ERASOR yielded an area under the curve of 0.

However, when used to evaluate predictive validity for sexual recidivism for juvenile sexual offenders who had previously committed both sexual and nonsexual offenses, ERASOR resulted in an area under the curve value of only 0. Most recently, in their meta-analysis consolidating the results from 33 studies, Viljoen, Mordell and Beneteau reported aggregate area under the curve values for the ERASOR of 0.

Even though an aggregate score potentially inflates the area under the curve value, Viljoen and colleagues' results still produce only marginal evidence of predictive validity for the instrument. Although it is still undergoing validation, the introduction of JSORRAT-II has added a significant new dimension to the assessment of juveniles who commit sexual offenses. However, few studies focusing on JSORRAT-II have been undertaken to date, and their findings offer little consistent empirical support for the predictive validity of the instrument, based on area under the curve values.

Area under the curve values reported in each study for the instrument's sexual and nonsexual recidivism predictive validity are presented in the table. Again, the research has produced mixed results. Area under the curve values for sexual recidivism range from a high of 0. The AUC value for sexual recidivism at any time is 0.

In their study based on an initial sample of adjudicated male juveniles who committed sexual offenses, Epperson and colleagues reported an area under the curve value of 0. Both values reflect strong predictive accuracy. However, in examining the instrument's capacity to accurately predict sexual recidivism only after age 18, Epperson and colleagues reported a value of 0.

This led the researchers to speculate that different risk factors may be at play for young adult recidivists compared to juvenile recidivists.

Despite the strong area under the curve values Epperson and colleagues found in their study, in the cross-validation study of the instrument the sample against which the initial predictive model was tested after first being developed , Epperson and Ralston and Epperson, Ralston and Edwards reported sexual recidivism values of only 0.

However, when gradated by age, although area under the curve values for adolescents aged fell between 0. Independent studies focusing on the JSORRAT-II are few, and have not found the same level of predictive validity that Epperson and colleagues found in their study and studies.

In the only independent study of the instrument, Viljoen and colleagues found no evidence of predictive validity for either sexual or nonsexual recidivism, reporting area under the curve values of 0.

In their meta-analysis of all juvenile risk assessment instrument validation studies, Viljoen, Mordell and Beneteau reported an aggregated area under the curve value of 0. In summary, while there is some evidence supporting the instrument's capacity for accurately predicting sexual recidivism for juveniles prior to age 18, the research studies conducted by independent researchers have failed to demonstrate that the instrument meets the threshold for predictive accuracy.

Given the limited body of research on the instrument and the considerable variation in findings, JSORRAT-II cannot yet be considered an empirically validated instrument. In addition to the three instruments discussed above, a handful of state-specific juvenile risk assessment instruments have been developed and placed into use to meet state requirements for sexual offender registration.

However, none of these instruments are based on actuarial validation, nor are they empirically validated Vitacco et al. Caldwell, Ziemke and Vitacco concluded that the risk constructs underlying the instruments were not valid, and that none of the three instruments predicts sexual recidivism.

The study followed adjudicated male adolescent sexual offenders for an average follow-up period of 8. Area under the curve values of 0.

The instrument's sexual deviance factor proved not to be predictive of either sexual or nonsexual recidivism. In terms of the number of youth assessed at a risk level that correctly matched actual recidivism, only 19 percent of youth assessed at moderate risk and 25 percent of youth assessed at high risk actually sexually recidivated; there were false positive rates of 81 percent and 75 percent for youth assessed at moderate and high risk, respectively.

To date, the instrument has undergone validation studies largely aimed at developing a strong instrument, conducted by its developer or close associate, and has yet to be evaluated by independent researchers. Studies have thus far focused primarily on the instrument's internal construction and consistency Miccio-Fonseca, , , with one study Miccio-Fonseca, describing predictive validity, with reported area under the curve values for the risk scale of the instrument of 0.

While these values indicate mild-moderate predictive validity, the follow-up period is short, and predictive validity has yet to be examined or established over a longer follow-up period, and awaits independent research. The MEGA is intended for use with males and females aged 4 through 19, of all IQ levels; this is a remarkably wide range of potentially applicable assessment subjects for a single risk assessment instrument, including both young children and young adults.

While the practical benefits of having a single instrument that can be used with so many different subjects are many, targeting such a wide range of subjects with a single instrument in terms of age, gender and cognitive capacity may inadvertently undermine the instrument's capacity to predict recidivism accurately. In a study of almost 1, juvenile offenders, van der Put and colleagues found that the effect of both static and dynamic risk factors on recidivism, and hence predictive validity, varied by adolescent age.

The researchers suggested not only that different risk assessment instruments be used for juveniles and adults, but that different instruments be used for different age groups within adolescence, as well. Tests of the predictive accuracy of the instruments conducted by independent investigators have typically yielded mixed to poor results for both sexual and nonsexual risk, and especially for the prediction of sexual recidivism.

Hence, none of the instruments has a consistently demonstrated record of predictive validity and, as, Viljoen, Mordell and Beneteau note, juvenile risk assessment instruments may be insufficient to make predictions that require a high degree of precision, such as situations in which the civil commitment of juveniles who commit sexual offenses is at stake or juveniles face the possibility of extended or lifetime sexual offender registration.

Until existing or new instruments are better validated, evaluations in this context will remain a complex balancing act between the need to provide the courts and other stakeholders with useful information and the serious limitations in empirically based knowledge about sexual risk. The juvenile sexual risk assessment field continues to develop, and there is a significantly different type of risk assessment model on the horizon. Funded by the U. Department of Justice grant number AW-BX , Kim and Duwe describe the development of a statistical machine learning model they hope will address the field's fundamental approach to risk assessment.

Machine learning involves mathematical algorithms, in which the assessment model iteratively learns from data in order to form predictions, in this case regarding sexual recidivism. Based on a sample of over 3, juvenile offenders, Kim and Duwe describe the comparison of machine learning models against more traditional methods of risk prediction comparing models for statistically estimating risk, not risk assessment instruments.

In this study, one of several underway to build the model, machine learning models resulted in the highest area under the curve values for two-year and three-year follow-ups in the validation sample of 1, juvenile sexual offenders, ranging between 0.

As each prediction model was based on exactly the same set of information and variables, Kim and Duwe highlight the importance of how risk predictors were measured, and not simply what was measured or classified.

However, there is a tradeoff when it comes to statistical and computerized models of assessment and deriving information, not only about possible sexual recidivism, but, importantly, also the use of the risk assessment model as a means to inform, shape and guide treatment, and for the purposes of re-evaluation over time.

That is, the possibility of gaining greater predictive power may also result in a loss of interpretive power and the capacity of risk assessment to understand youthful offenders and inform treatment.

Indeed, as Kim and Duwe note, the black box process of machine learning is unable to provide guidance on how to identify and address treatment needs.

This is a bridge to be crossed in the event that machine learning models for juvenile sexual risk assessment become a reality, possibly sometime within the next one to two years. Although risk factors are the foundation of virtually all risk assessment instruments, in recent years, and increasingly so, more attention has been given to protective factors and their role in mitigating the effects of risk factors. Protective factors have been described in the child and adolescent development literature, and their role in delinquency prevention has long been recognized.

The relationship between risk and protective factors is complex. Jessor and colleagues , describe risk and protection as opposite ends of the same constructs. They argue that risk and protective factors exist independently of one another, and are not statistically correlated.

Similarly, Hall and colleagues view risk and protective factors as conceptually distinct rather than opposite ends of a single dimension and assert that it is not only possible, but essential to conceptualize and define risk and protective factors independently from one another.

In his critique of forensic risk assessment, Rogers describes assessment as inherently flawed if it pays attention only to risk factors without consideration of the presence, weight and action of protective factors. Similarly, Rutter describes the importance of paying attention to the possibility of factors that protect against antisocial behavior, as well as to those that fuel it.

Although not referring to protective factors per se, in describing clinical predictions of risk Monahan noted the importance of giving balanced consideration to factors that indicate the absence of violent behavior, as well as those that suggest the recurrence of violence. Indeed, Lodewijks, de Ruiter and Doreleijers , p.

Despite their importance in mitigating risk, protective factors are incorporated in few juvenile instruments at this time. Despite the apparent importance of protective factors, few of the instruments commonly used with juveniles incorporate protective factors, and those that do either have no empirical support or are in development and have not yet been empirically validated.

In fact, Worling, Bookalam and Litteljohn noted that very little research regarding factors that lead to the cessation of sexual offending behaviors for juveniles has been undertaken to date, and that it will be important for future research to identify protective factors and determine how best to combine risk and protective factors to enhance judgments of future sexual behavior.

One of the first studies to examine the relationship of risk and protective factors to sexual and nonsexual recidivism was conducted by Spice and colleagues using a sample of adolescent males who committed sexual offenses.

Although the study failed to find any protective factors that were statistically related to sexual recidivism or desistance, study findings nonetheless suggest there may be protective factors that are specific to sexual, rather than nonsexual, recidivism. Like Worling, Bookalam and Litteljohn , the researchers called for more research on both risk and protective factors and the roles they play in sexual offending, and they specifically noted the need for studies that examine whether there are protective factors that apply to sexually abusive youth specifically.

Since that time, a handful of studies have emerged that address the nature and role of protective factors in helping to reduce or buffer against sexual recidivism, but this research is in its early stages. Nevertheless, learning more about and understanding the mechanisms and effects of protective factors on risk for sexual reoffense will perhaps prove as difficult as better understanding the actions and complexities of risk factors.

In their study of sexually abusive youth, they found that the inclusion of protective factors in the risk assessment process added to increased predictive validity regarding sexual recidivism although not in those juveniles who also had a history of violent offenses. A handful of juvenile sexual risk assessment instruments are worth noting due to their assimilation of protective factors.

These include the AIM2 Print et al. However, the protective factors scales of these instruments have not yet been empirically tested, and so remain only theoretical instruments for clinical use and treatment planning at this time. The Protective Factors Scale PFS Bremer, is not a risk assessment instrument, but was nevertheless developed specifically for work with sexually abusive youth and its sexuality scale reviews three elements specifically related to such behavior.

However, the PFS has received scant attention from researchers and practitioners: It has not been subject to any form of validation and is not in general use in the field.

More recently, the Desistence for Adolescents Who Sexually Harm DASH has become available for helping to incorporate protective factors into the process of risk assessment, and has been the subject of one research study.

Research concerning the factors that place juveniles at risk for sexual offending behavior and sexual recidivism is still in its infancy, as is research on the capacity of risk assessment instruments to accurately predict risk for sexual recidivism.

Nevertheless, studies that have been undertaken to date provide some important insights about both issues. First, the range of risk factors for juvenile sexual offending behavior and recidivism is relatively well defined, and the types and classes of factors that place youth at risk for sexually abusive behavior or sexual recidivism have been identified. However, our understanding of these factors and how they relate to sexual offending tends to be global rather than specific in nature. The role and effect of risk factors is fairly well understood, but the specific mechanisms through which risk factors develop and ultimately impact the behavior of children and adolescents are not.

The effects of risk factors under different circumstances and their interactions with one another are particularly obscure. Moreover, research has not yet produced a universally agreed upon, finite and valid set of risk factors for sexually abusive behavior. Second, the risk assessment instruments that are currently available for use with juveniles who sexually offend are far from empirically validated.

In short, there is a lack of consistent, independently corroborated empirical evidence concerning both inter-rater reliability and the predictive validity of current juvenile sexual risk assessments, making it difficult to conclude with any degree of confidence that the instruments are scientifically valid. This raises concerns about the capacity of such instruments to reliably and accurately predict the risk of juvenile sexual recidivism or to inform either juvenile court decisions or public policy debates.

While some validation research has produced promising findings, the evidence concerning the predictive accuracy of various instruments is mixed and inconsistent overall. Thus, Vitacco and colleagues describe current instruments as important developmental milestones in further refining the risk assessment process and method, but far from complete. Viljoen, Mordell and Beneteau also warn that such instruments are not yet capable of making precise and certain estimates of risk and should thus be used cautiously in legal procedures, such as the civil commitment of juveniles who commit sexual offenses or their placement onto sex offender registries.

Participants in the Sex Offender Management Assessment and Planning Initiative forum expressed concern that estimates of risk reaching more than one to three years into the future are unlikely to sufficiently account for the fluid nature of child and adolescent development.

However, the adoption of a short-term assessment model will likely mean that the manner in which juvenile risk instruments are used and researched will have to significantly change. Finally, Rich and Spice and colleagues have argued for future research to study not only risk factors and the accuracy of risk assessment instruments, but also the nature of risk itself.

They further argue that risk assessment instruments should be used as a platform for case management and treatment rather than for making "passive predictions of limited practical use" Boer et al. In this vein, Viljoen, Mordell and Beneteau write that despite the research focus on the prediction of sexual recidivism, these instruments are also intended to help manage risk and plan treatment to prevent reoffense.

They note that increased attention to the utility of tools for these purposes will enable us to move beyond the prediction of sexual reoffense toward the prevention of sexual reoffense. Regardless of the strength of the instrument, sound risk assessment requires well-trained risk evaluators who do not simply rely on risk scores when making decisions about a juvenile offender, particularly decisions with potentially lifelong consequences.

As described in the psychological evaluation guidelines of the American Psychological Association Turner et al. Even when using an actuarial assessment tool, it remains important for the evaluator to apply clinical judgment in the risk assessment process.

Indeed, SOMAPI national forum participants noted a need for the provision of federally funded training and technical assistance to ensure the development of well-trained evaluators who understand the nature of the risk assessment process and the limitations of assessment instruments that are currently available.

Well-trained, knowledgeable evaluators are the best defense against the pitfalls associated with erroneous assumptions concerning the predictive accuracy or use of risk assessment instruments for juveniles who sexually offend.

Those who use the results of juvenile risk assessments must also understand the strengths and weaknesses of the risk assessment process and the limitations of risk assessment instruments in use today, and particularly the lack of empirical evidence demonstrating their predictive accuracy.

Perhaps most important, risk assessment instruments must be integrated into a comprehensive assessment process that produces a thorough understanding of the juvenile who is being assessed. Risk assessment instruments certainly can play an important role in the process, but their current value arguably lies more in their ability to serve as a basis for case management and treatment rather than in their capacity to accurately predict risk.

The role that risk assessment instruments can play in identifying the presence of dynamic risk factors that provide targets for treatment is particularly important, as is the role they can play in identifying the presence of protective factors and their potentially mitigating effects on risk.

Indeed, participants in the SOMAPI forum recommended that protective factors be incorporated into juvenile risk assessment instruments, both those currently in use and those that will be developed in the future.

Future research should be concerned with expanding the knowledge base concerning both risk and protective factors, including the mechanisms through which they affect the propensity to reoffend, particularly in combination with one another.

Finally, better risk assessment instruments for juveniles who sexually offend and better trained evaluators are both needed. In describing the "covenant" between the developers and users of risk assessment instruments, Rich underscored how important well-designed instruments and trained, experienced evaluators are for effective professional practice.

As Ward, Gannon and Birgden , p. Practitioners have obligations to always use such measures appropriately, ensure they are trained in their administration and, most importantly, make sure that the assessment process culminates in an etiological formulation that is based around the individual's features alongside those they share with other offenders.

Overall, the meta-analysis consolidated 33 studies involving more than 6, male adolescent sexual offenders. In their review of juvenile sexual risk assessment instruments, the researchers conclude that "the predictive validities of the risk assessment instruments for JSOs are still insufficient to accurately predict recidivism" p.

Aebi, M. Predicting sexual and nonsexual recidivism in a consecutive sample of juveniles convicted of sexual offences. The meta-analysis of clinical judgment project: Fifty-six years of accumulated research on clinical versus statistical prediction.

The Counseling Psychologist, 34, — Allan, M. Psychometric assessment of dynamic risk factors for child molesters. Andrews, D. Crime and Delinquency, 52, 7— Beggs, S. Treatment gain for sexual offenders against children predicts reduced recidivism: A comparative validity study.

Journal of Consulting and Clinical Psychology, 79 , — Boccaccini, M. Criminal Justice and Behavior, 39, 42— Boer, D. Manual for the Sexual Violence Risk Bonta, J. Risk-needs assessment and treatment. Harland Ed. Offender risk assessment: Guidelines for selection and use.

Criminal Justice and Behavior, 29, — Bremer, J. Protective factors scale: Determining the level of intervention for youth with harmful sexual behavior. Prescott Ed. Caldwell, M. Accuracy of sexually violent person assessments of juveniles adjudicated for sexual offenses. Sex offender registration and recidivism risk in juvenile sexual offenders. Ziemke, M. Evaluating the ability to predict sexual recidivism.

Psychology, Public Policy, and Law, 14, 89— Campbell, T. Assessing Sex Offenders: Problems and Pitfalls. Springfield, IL: Charles C. Carpentier, J. Correlates of recidivism among adolescents who have sexually offended.

Casey, E. Predictors of sexually coercive behavior in a nationally representative sample of adolescent males.

Journal of Interpersonal Violence, 24, — Chu, C. Craig, L. Comparing sex offender risk assessment measures on a UK sample. DeMatteo, D. Risk assessment with juveniles. In Heilbrun, K. Goldstein Eds. An esploration of protective factors supporting desistance from sexual offending. Epperson, D. Epps, K.

Managing risk. Hoghughi Ed. Fan, J. Understanding receiver operating characteristic ROC curves. Canadian Journal of Emergency Medicine , 8, Fanniff, A. Keep testing the taters: Fanniff and Letourneau reply. Farrington, D. Protective and promotive factors in the development of offending. Bliesener, A. Stemmler Eds. Antisocial behavior and crime: Contributions of developmental and evaluation research to prevention and intervention pp.

Cambridge, MA: Hogrefe Publishing. Graham, F. Grisso, T. Ethical issues in evaluations for sex offender re-offending. Grove, W.

Meehl's contribution to clinical versus statistical prediction. Journal of Abnormal Psychology, , — Grubin, D. A large-scale evaluation of Risk Matrix in Scotland.

Gunby, C. Sexually deviant juveniles: Comparisons between the offender and offence characteristics of "child abusers" and "peer abusers. Hall, J. Centers for Disease Control and Prevention's expert panel on protective factors for youth violence perpetration: Background and overview.

Hannah-Moffat, K. Hanson, R. Predicting relapse: A meta-analysis of sexual offender recidivism studies. Journal of Consulting and Clinical Psychology, 66 2 , — The characteristics of persistent sexual offenders: A meta-analysis of recidivism studies. Journal of Consulting and Clinical Psychology, 6, — Improving risk assessments for sex offenders: A comparison of three actuarial scales.

Law and Human Behavior, 24, — Harris, G. Characterizing the value of actuarial violence risk assessments. Criminal Justice and Behavior, 34, — Hart, S. Precision of actuarial risk assessment instruments: Evaluating the "margins of error" of group v. British Journal of Psychiatry, suppl. Hecker, J. Baby with the bath water: Response to Fanniff and Letourneau.

Heilbrun, K. Risk factors and intervention outcomes: Meta-analyses of juvenile offending. Heilbrun, N. Redding Eds. New York: Oxford University Press. Hempel, I. Review of risk assessment instruments for juvenile sex offenders: What is next? Hiscox, S. Jessor, R. Journal of Youth and Adolescence, 43, Protective factors in adolescent problem behavior: Moderator effects and developmental change. Developmental Psychology, 31, — Kim, K.

Improving the performance of risk assessments: A case study on the prediction of sexual offending among juvenile offenders. Taxman Ed. Klein, V. Protective factors and recidivism in accused juveniles who sexually offend. Knight, R. The developmental antecedents of sexual coercion against women: Testing alternative hypotheses with structural equation modeling. Annals of the New York Academy of Sciences, , 72— Testing an etiological model for male juvenile sexual offending against females.

Geffner, K. Falconer Eds. Binghampton, NY: Haworth Press. Ronis, S. Bootstrapping persistence risk indicators for juveniles who sexually offend. Behavioral Sciences and the Law , 27 , — Mapping an agenda for the study of youth sexual aggression in Europe: Assessment, principles of good practice and the multilevel analysis of risk factors.

Journal of Sexual Aggression, 33, Long-term follow-up of criminal recidivism in young sex offenders: Temporal patterns and risk factors. Langton C. Introduction to the special issues on factors positively associated with desistance for adolescents and adults who have sexually offended. Leroux, E. Victim age and the generalist versus specialist distinction in adolescent sexual offending. Litwack, T. Actuarial versus clinical assessments of dangerousness.

Psychology, Public Policy, and Law, 7, — Lodewijks, H. The impact of protective factors in desistance from violent reoffending: A study in three samples of adolescent offenders. Journal of Interpersonal Violence, 25, — Looman, J. International Journal of Behavioral Consultation and Therapy, 8, Mallie, A. Childhood abuse and adolescent sexual re-offending: A meta-analysis.

Child and Youth Care Forum, 40, — Martinez, R. McCann, K. Antisociality, sexual deviance, and sexual reoffending in juvenile sex offenders: A meta-analytical investigation. Youth Violence and Juvenile Justice, 6, — McGrath, A. The relative predictive validity of the static and dynamic domain scores in risk-need assessment of juvenile offenders.

Criminal Justice and Behavior, 39, — Meehl, P. Northvale, NJ: Jason Aronson. Miccio-Fonseca, L. MEGA: A new paradigm in protocol assessing sexually abusive children and adolescents. MEGA: An ecological risk assessment tool of risk and protective factors for assessing sexually abusive children and adolescents. MEGA: A new paradigm in risk assessment tools for sexually abusive youth. Journal of Family Violence, 28, Miner, M.

Robinson, B. Anxious attachment, social isolation and indicators of sex drive and compulsivity: Predictors of child sexual abuse perpetration in adolescent males? Monahan, J. The Clinical Prediction of Violent Behavior. Chicago: University of Chicago Press. Murrie, D. Rater dis agreement on risk assessment measures in sexually violent predator proceedings: Evidence of adversarial allegiance in forensic evaluation.

Psychology, Public Policy, and Law, 15, 19— Olver, M. Therapeutic responses of psychopathic sexual offenders: Treatment attrition, therapeutic change and long term recidivism.

Journal of Consulting and Clinical Psychology, 77, — Parks, G. Risk factors for adolescent sex offender recidivism: Evaluation of predictive factors and comparison of three groups based upon victim type. Pedersen, L. Risk assessment: The value of structured professional judgments. International Journal o f Forensic Mental Health, 9 , 74— Powers-Sawyer, A. Sexual Offender Treatment, 4 2 , 1— Relying on a single tool limits the quantity and quality of the data that you will have and, as a result, will limit your ability to make the most informed decisions.

This is in sharp contrast to where we are with adult sex offenders. In fact, there are several empirically—validated actuarial and empirically—guided tools designed to assess recidivism risk with adult sex offenders, but these tools are not designed for use with sexually abusive youth. It is designed to assess short term risk of juvenile males between 12 and 18 years of age. The items explore static, or unchangeable, factors as well as dynamic, or changeable, factors.

The ERASOR, too, is recommended to be used as a repeated risk assessment in order to capture changes that occur over time. Again, both of these measures are considered to be empirically—guided approaches to risk assessment.

The items in these tools are based on the factors that research seems to suggest are related to sexual recidivism among juveniles who commit sex offenses. And there is a growing body of research supporting the reliability and validity of these measures.

Remember, a significant strength of these tools is that they include dynamic, or changeable, risk factors, which makes them very useful for intervention planning and to make adjustments to case management plans over time based on reassessments.

Our training today is by no means designed to make you an expert on these tools! Our goal is simply to let you know that these tools are very promising, and through the references that are included in your materials, you can learn more about them. And as you can see, a substantial number of juvenile sex offender programs across the country have begun to incorporate one or both of these tools into their practices.