Utility of Dynamic Risk Factors and Change in Treatment Planning in Prediction of Sexual Recidivism

Running Head: UTILITY OF DYNAMIC RISK FACTORS AND CHANGE

Utility of Dynamic Risk Factors and Change in Treatment

Planning in Prediction of Sexual Recidivism

Dena Faust

Southern New Hampshire University

UTILITY OF DYNAMIC RISK FACTORS AND CHANGE2

Abstract

This paper will explore how using dynamic factors and the effect of change can not only predict sex offender recidivism, but act as an effective treatment tool to identify appropriate treatment targets for sex offenders. Risk assessment continues tobe dynamic with the creation of the Violence Risk Scale-Sex Offender version. The Extended Mind Theory (EMT) implies cognition is an internal and external concept when applied to sexual offending (Ward, 2009; Ward & Casey, 2010). EMT suggests cognition is dynamic and suggests deviance begins internally through distortions and arousal and externally factors are also responsible for maintaining the deviance. The Extended Mind Theory supports VRS-SO use of dynamic factors as the risk assessment not only assesses for deviance, but also external factors as substance abuse, community support, release to high-risk situations, etc. Utilizing the EMT and VRS-SO supports placing sex offenders into a heterogeneous treatment population based upon the Risk-Needs-Responsivity model.


Introduction

Predicting sex offender recidivism is an evolving research

topic. Historically, assessing risk was based solely on insight

by professional performing the assessment (McGrath et al., 2012;

Hanson & Morton-Bourgon, 2009; Beggs & Grace, 2010). Risk

Assessment has developed into a “roller coaster” science, meaning

it ebbs and flows with the current trends of research. Due to the

harm sex offenses cause to victim and various stakeholders in the

community, researchers are always looking to improve their

prediction of sex offender recidivism. Current trends in sex

offender research have investigated the role of static and


dynamic risk factors, separate and combined, in predicting

recidivism. Incorporating static and dynamic risk assessment

tools can assess for risk, measure change a sex offender can go

to during supervision, and appropriate placement in the

treatment. The ability of an effective assessment tool gives the

treatment providers and individuals responsible for their

supervision the ability to adjust their case management based

upon risk. Researchers have begun to look at theories of sexual

offending and how understanding theories of behavior can aid in

understanding why an offender committed his sex offense and what

factors are going to continue that behavior. Theories that have

been applied to Sexual Offending are that of the Learning Theory

(Bandura, 1977; Grusec, 1992), Implicit Theory, Distortions

Theory (Abel, 1989), and the Extended Mind Theory (Ward, 2009;

Ward & Casey, 2010). Each of these theories have been able to

make some connection to sexual offending behavior, but the one

that stands out closest to utilizing static and dynamic factors

in assessing sex offending behavior is that of the Extended Mind

Theory (EMT). The Extended Mind Theory provides implications on

how deviance is maintained in sex offending behavior, not only by


internal distortions, but external factors as well. These

external factors are represented in the VRS-SO as dynamic

variables. The VRS-SO has been introduced as a tool that not only

assesses for dynamic and acute risk factors, but also takes into

consideration the stages of change an offender goes through after

supervision and treatment have been implemented into their lives

(Olver & Wong, 2003). This paper will explore the Extended Mind

Theory (EMT), the Generations of Risk Assessment, the Violence

Risk Scale-Sex Offender Scale, and conclusions on how the VRS-SO

can increase effectiveness of the Risk-Needs-Responsivity (RNR)

model that places sex offenders into a heterogeneous population.

The change that can be made in treatment will be reflected within

the dynamics of the VRS-SO based upon the Extended Mind Theory.

This paper will explore the Extended Mind Theory, the Generations

of Risk Assessment, the Violence Risk Scale-Sex Offender Scale,

and Applying EMT to RNR Principle.

The Extended Mind Theory

The Extended Mind Theory is a theory developed and founded

upon cognitive neuroscience and philosophy of the mind (Ward,


2009). Its foundation encompasses previous theories including the

Cognitive Distortions Theory (Abel et al., 1984) and Implicit

Theory (Ward, 2000), and utilizes them to build upon a more

dynamic theory that is Extended Mind. Ward (2009, 2010) apply the

Extended Mind Theory to sex offending behavior and how an

offender can not only maintain sexual deviance, but how to

effectively use the theory to incorporate more effective

assessment and treatment. To understand The Extended Mind Theory

and its applications in sex offenders it is important to

recognize the foundations of EMT, theories behind EMT, and its

correlation with Sex Offending behavior.

Foundation of the Extended Mind Theory

Elements of the Extended Mind Theory (EMT) were briefly

introduced by Richard Menary in 2007. In his research of the

Extended Mind, Menary (2007) proposed that cognitive systems

extend into the external environment based upon a hybrid system

that makes up humans cognition. According to Ward & Casey (2010),

studies (Gallagher, 2005; Menary, 2007) as of late have looked

into the Extended Mind Theory (EMT); however, their views of how


to apply EMT are found to be diverse. Despite their

discrepancies, they share three (3) implications: human cognitive

agents are physically embodied, human agents have soft selves

(flexible), and human agents possess hybrid cognitive systems

that incorporate internal and external components (Ward, 2009;

Ward & Casey, 2010). Taking this approach towards sexual

offending behavior causes us to look differently at the

relationship between internal and external cognitions and how

they can connect with deviance.

Theories behind EMT

EMT differs from several theories that have been presented

to theorize sex offending. Abel’s cognitive distortion theory,

introduced the term distortions and applied it to sex offending

literature (Abel et al., 1984; Abel et al., 1989). Although EMT

is centered on distortions, it offers a broader context of the

dynamics of sex offending. Abel’s theory was focused more

specifically on distortions and their definitions (Ward, 2010).

Ward’s Implicit Theory implies that sexual offenders’ cognitive

distortions emerge from underlying schemas that stem from their


independent beliefs (Ward, 2000; Ward, 2009). This theory

specifically focused on the distortions of child molesters that

allowed them to justify their behavior of sexually assaulting

children (Ward, 2009). Implicit theories do not broach the topic

of external factors in cognitive distortions. It also failed to

be supported by experimental studies (Keown et al., 2008a; Keown

et al., 2008b).

Correlation with Sex Offending Behavior

We will be able to connect the Extended Mind Theory

throughout all generations of sex offender risk assessment, but

will find it fits most accurately in the last generation that

embodies both static and dynamic factors. The EMT is able to make

the connections between the internal (mind) and external (social

and cultural factors) that make up the sex offender (Ward, 2009;

Ward & Casey, 2010). This theory drives VRS-SO’s reasoning to use

dynamic risk factors in sex offender assessment. The creators of

the VRS-SO recognized the influence external factors had on a sex

offender’s justification of his criminal offense external

factors.


Generations of Risk Assessment

To understand the “roller coast” of risk assessment, it is

important to recognize the focus the researchers have taken on to

understand the dynamics of sex offending behavior. Going through

the generations of risk assessment will not only able to explain

how we have now gotten to using dynamic risk factors in assessing

risk, but how research has been able to pinpoint the number one

risk factor of sexually reoffending, which is sexual deviance.

The Static-99 is the most utilized risk assessment tool used

internationally in the prediction of sexual recidivism (Hanson &

Thornton 1999; Hanson & Morton-Bourgon, 2009; Smid et al., 2013).

However, at the same time there are other risk assessment tools

that measure different factors that can influence sex offender

recidivism. Although the Static-99R is an empirically sound risk

assessment tool, recent research has shown the use of it

individually does not have the same predictive powers as does

dynamic and static together(Andrews & Bonta, 2006; Hanson et al.,

2007). In conjunctions with this idea, Harris (2006) also finds

static risk assessment does not sustain utility in community-


based offender. Consequently, in the last few years researchers

have developed risk assessment tools that incorporate dynamic

risk factors that have been found to directly correlate to sex

offender recidivism. Olver, Wong, Nicholaichuk, & Gordon (2007)

identified these factors as being sexual deviance, criminality,

and treatment response. Current trends in sex offender research

have investigated the combination of static and dynamic risk

factors in predicting recidivism and managing caseloads in

community supervision (Olver & Wong, 2011). Going through the

first, second, and third generation of risk will demonstrate the

necessity of better predictors but also for increased utility of

the instruments.

First Generation

First generation risk assessment tools are based upon

unstructured professional judgment (McGrath et al., 2012).

According to McGrath et al. (2012), these first generational risk

assessments are subjective, inconsistent, biased and not

reliable. A first generational risk assessment could come in the

form of an interview, with the offender’s self-disclosure being


the product of the assessment. However, not all clinical judgment

should be discounted. Murray and Thomson (2010) identify the

controversy within research surrounding clinical judgment.

Although they identify clinicians as being more effective at

managing risk than predictors of risk, they also argue that

combining structured, informed clinical judgment can be

effectively compounded with empirically established risk factors

that will be explored more in depth within the literature review.

Douglas, Ogloff, & Hart (2003) supported the use of clinical

judgment as they proposed actuarial tools can be too rigid and

lack the ability to assess change. Not all research supports this

and argue the opposite that clinical judgment should be replaced

by actuarial tools (Quinsey, Harris, Rice, & Cormier, 1998;

Monahan et al., 2001).

A limitation within these studies, and many studies that

don’t support the use of clinical judgment is that they base

their judgments on “unstructured” clinical judgment versus

“structured” clinical judgment (Murray & Thomson, 2010). They

state if clinicians use their judgment to adjust actuarial


prediction to take into account dynamic risk they may use too

many adjustments and flaw the outcome of the actuarial (Dawes,

Faust, & Meehl, 1989 as referenced in Murray & Thomson, 2010).

Another limitation of the first generational clinical assessments

is found in Kozo et al.’s (1972) study of mental health

clinician’s ability to identify future violence. Although the

study found the mental health clinicians were wrong two out of

three times in predicting future violence, the limitation is

found in who was conducting the evaluations. Mental Health

clinicians assessing for violence risk is more unstructured and

uninformed. According to the Criminal Justice Mental Health

Standards, not only does the evaluating individual need to be

educated, they need to hold the forensic knowledge gained through

specialized training (Standards 7-3.10; American Bar Association,

1989 as referenced in Murray & Thomson, 2010). Despite the

limitations found in the above studies, even structured,

informed, specialized clinicians have their own limitations and

can improve upon their assessments. These improvements begin with

static risk assessments (Bonta, 1996; Hanson & Morton-Bourgon,

2009).


Second Generation

Second-generation risk-assessment instruments were developed

in the late 1990s (McGrath et al., 2012; Parent, Guay, & Knight,

2011). Second generation risk actuarials are composed primarily

of static unchanging factors (i.e. criminal history and victim

characteristics) (Hanson & Thornton, 2000; McGrath et al., 2012;

Hanson & Morton-Bourgon, 2009). Instruments that were developed

during second generational risk assessments include, but are not

limited to: Rapid Risk Assessment for Sex Offender Recidivism

(RRASOR; Hanson, 1997), Static-99R (Helmus, Thornton, Hanson, &

Babchishin, 2011), and Static-2002 (Hanson, Helmus, & Thornton,

2010). For the purposes of the review, the Static-99R will be

used to identify the correlation of static risk factors and

sexual re-offending as it has been found to one of the most

validated measures of risk. The Static-99 was originally

developed in 2000 by Karl Hanson and David Thornton in an effort

to identify what risk factors correlate with sexual recidivism.

The Static-99 was revised in 2003 (Static-99R) to take into

account new data that reflected lower sexual arousal of older men


(Helmus et al. 2011). The Static-99R is composed of 10 items (age

at release, ever lived with a lover for at least two years, index

non-sexual violence, prior sex offenses, prior sentencing dates,

any convictions for non-convictions for not contact sexual

offense, any unrelated victims, any stranger victims, any male

victims), with a possible total score ranging from -3 to 12 and

place offenders into four risk categories: low (-3 to 1),

moderate-low (2-3), moderate-high (4-5), and high (6+) (Helmus et

al., 2011). The higher the score the greater indicator of sex

offender recidivism (Nunes, Babchishin, & Cortini, 2011). It is

now the most utilized, international tool to assess sexual

recidivism (Hanson & Morton-Bourgon, 2005; Hanson & Morton-

Bourgon, 2009; Helmus, et al., 2012).

Included in this international static tool, as indicated

above, is the static component of stable relationships (ever

lived with a lover for at least two years). Several studies,

support the notion that lack of a marriage or long-term

relationship has an effect on sexual recidivism (Rice et al.,

1991; Hanson et al., 1993; Hanson & Bussiere, 1998; Wong et al.,


2003). An implication of the Extended Mind Theory (EMT) is a

person’s ability to reach out past their internal cognitions and

become influenced by external factors (Ward, 2009; Ward & Casey,

2010). EMT states a part of the hybrid relationship of internal

and external cognitions can be influenced by social

relationships. EM theory and the Static-99R have both indicated

and supported the importance and influencing factors of a

relationship in an offender’s life at the time of his offense.

However, the Static-99R still implies a static composition, and

limits the offender’s ability to change within the use of this

instrument. Thus the reasoning for further research in increasing

the predicting powers of risk assessment tools.

Hanson & Morton-Bourgon (2009), took strides to identify

variables that had the highest predictive power that predicted

sex offender recidivism. They found the most accurate approaches

to predicting sex offender recidivism specifically was to utilize

actuarial measures designed for sexual recidivism and mechanical

measures designed for sexual recidivism (Hanson & Morton-Bourgon,

2009). Despite the high predictability of the Static-99R, its


utility is limited when it comes to predicting risk relevant to

change an offender can experience while on community supervision

(Harris, 2006; Olver, Wong, Nicholaichuk, & Gordon, 2007; ).It

was within second generation risk assessment that dynamic risk

factors were introduced (McGrath et al., 2012).

According to McGrath et al. (2012), these dynamic risk

factors were also identified as criminogenic needs. As static

factors are somewhat unchangeable, dynamic risk factors are

changeable and are amenable to interventions (i.e. attitudes

toward offending and offense-related sexual interests). Some

examples of these instruments include: Minnesota Sex Offender

Screening Tool-Revised (MnSOST-R; Epperson et al., 1998), Sexual

Violence Risk-20 (SVR-20; Boer, Hart, Kropp, & Webster, 1997) and

Vermont Assessment of Sex Offender Risk (VASOR; McGrath & Hoke,

2001) as reported by McGrath et al. (2012). These tools are not

considered third generational as they do not incorporate enough

dynamic risk factors to aid in case management. Third generation

tools build upon second generational instruments by integrating

additional dynamic with static factors in a single instrument.


Third Generation

The development of the Sex Offender Need Assessment Rating

(SONAR) was based upon Hanson and Harris’s (1998) findings

regarding five stable dynamic factors: intimacy deficits,

negative social influences, attitudes tolerant of sexual

offending, sexual self-regulation, and general self-regulation

and four acute factors: substance abuse, negative mood, anger and

victim access (Hanson and Harris, 2001). With the limitations of

dynamic risk assessment for community supervision, the measure of

stable risk factors were designed for the Dynamic Supervision

Project (Hanson et al., 2007). As a result of the research

conducted by Hanson and colleagues in 2007 in the Dynamic

Supervision Project, third generational risk assessments rely on

a combination of static and increased number of dynamic risk

factors in one instrument (McGrath et al., 2012; Hanson, et al.,

2007).

Third generation risk assessment tools include changeable

factors that are more applicable to sex offender supervision, and

the increase and decrease of risk one can experience in


supervision. Examples of the dynamic risk factors are that of

personal skill deficits, predictions, and learned behaviors that

are positively correlated with sex offender recidivism (Hanson et

al., 2007). There are two different types of dynamic risk

factors; stable dynamic factors are changeable; however, endure

over time (alcoholism, intimacy deficits) and acute dynamic

factors, which are also changeable; however, are considered red

flags and do not endure (drunkenness and acute distress)(Hanson

et al., 2007; Beggs & Grace, 2010).

The Stable-2007 and Acute-2007 are examples of tools created

to increase the efficacy of case management with dynamic risk

factors that have been found to correlate with sexual recidivism

(Hanson & Harris, 2001). The Dynamic Supervision Project

indicated a significant relationship between the following stable

variables and sexual recidivism (Stable-2007): negative social

influences, hostility towards women, rejection of loneliness,

lack of concern for others, lack of cooperation with supervision,

impulsive acts, poor cognitive problem-solving, sexual pre-

occupations, relationships (modified), and sex as coping (Hanson


et al., 2007). The acute variables indicated to have the

strongest correlation with sexual crime recidivism were that of

(Acute-2007): victim, access, hostility, substance abuse, sexual

preoccupations (Hanson et al., 2007).

The study found that the combined scores of the Static-99R

(static factors), Stable-2007 (dynamic factors) and Acute-2007

(dynamic factors) were more predictive of SO recidivism than

static scores alone (Hanson et al., 2007). Hanson, Harris, Scott,

& Helmus (2007) utilized the Static-99, Stable-2007 (13

changeable dynamic risk factors), and Acute-2007(seven rapidly

changing factors) to predict sexual recidivism compared to static

factors alone. This study’s sample size of more than 900 sex

offenders provided enough validation to support increased

efficacy of the combination of stable and dynamic risk factors

compared to those factors alone. It built upon the foundation

that dynamic characteristics will have influence over static

factors in an environment of interventions i.e. community

supervision and sex offender treatment (Beech et al., 2001 as

referenced in Hanson et al., 2007; Marques et al., 2005).


Although the steps made to identify further measures to predict

recidivism, the most relevant difference between static and

dynamic risk is the ability to change over time, thus the need to

continue identifying ways to implement risk assessment in

community supervision and treatment. The Dynamic Supervision

Project was a respectable beginning, the change scores computed

by rerating the dynamic items were not related to any recidivism

outcomes (Hanson et al., 2007; Olver & Wong, 2011). Assessing how

change impacts dynamic risk scores is the basis of fourth

generational sex offender risk measures, the Violence Risk Scale-

Sex Offender Version (Olver & Wong, 2011; Olver et al., 2007;

Canales, Olver, & Wong, 2009; Beggs & Grace, 2010)

Violence Risk Scale- Sex Offender Version

The Violence Risk Scale- Sex Offender (VRS-SO) was designed

to assess for risk, as well as provide treatment targets that

were based upon static and dynamic factors that have been found

to positively correlate with recidivism (Olver & Wong, 2011;

Olver et al., 2007; Canales, Olver, & Wong, 2009; Beggs & Grace,

2010). The VRS-SO incorporates a static score, dynamic score, and


a change score using the Trans-Theoretical Model and computes a

pre- and post-test score that identifies if there has been a

change in the offender’s level of risk over a period of time

while in treatment (Olver & Wong, 2011). The functioning power of

the pre- and post-test scores allows the Probation and Parole

Agent and Treatment Provider better manager the sex offender

while in the community. This follows the principle of the

Risk/Need/Responsivity Model that states a sex offender’s needs

are best met among those who match his risk (Andrews et al.,

1990; Lovins, Lowenkamp, & Latessa, 2009). The dynamic variables

that have been incorporated into the VRS- SO, are ones that have

found to positively correlate with sexual offending. The Extended

Mind Theory (EMT) drives the use of these variables as it

confirms that although sexual deviance is an important factor in

assessing for sexual recidivism (most correlated factor),

identifying external factors is also important when assessing

risk and then using for treatment planning. Within the scope of

the section, the VRS-SO will be explored in its validity, as a

risk tool alone, the Trans-Theoretical Model (TTM) that is


imposed within the tool, and how risk change and recidivism

prediction is a result of using this instrument.

Validity

The VRS-SO is a newer developed tool and continues to be

subject to research in attempts to validate the original

findings. In order to support the validity of the VRS-SO’s static

items, Olver et al., (2007) utilized the Static-99 as a control

instrument. The VRS-SO was found to positively correlate with the

Staic-99. The pretreatment dynamic score and post treatment

dynamic tool with the following derived factors also performing

well in validity tests: sexual deviance, criminality, and

treatment responsivity.

In addition to positively correlating with static item, the

VRS-SO dynamic and factor scores were significantly correlated

with sexual recidivism (Olver et al., 2007; Beggs & Grace, 2010).

The pre- and post-treatment scores continued to correlate with

sexual recidivism with different offender risk level groups;

however, as more changed occurred within the groups, the

correlation reduced (Olver et al., 2007). However, this could be


somewhat expected as Stages of Change, although quantified in the

VRS-SO, could still be more subjective than objective. The only

item to negative correlate with sexual recidivism was the pre-

and post- treatment scores within change; however, this was to be

assumed as a positive correlation with change would disprove

positive change can have a negative effect on sexual recidivism

(Olver et al., 2007). Despite being a newer risk tool, the VRS-SO

has had success in achieving validity in comparison and

confidence measures and can be looked at how it performs when

applying it to change in treatment and the recidivism level after

the treatment targets are identified

The Risk Tool

The Violence Risk Scale was created to incorporate static

risk predictors, dynamic risk predictors, and assessment of

change within one instrument for a risk prediction and treatment

planning tool (Wong, Olver, Nicholaichuk & Gordon, 2003). It is a

fourth-generation risk assessment tool as it incorporates stages

of change as well as treatment targets. As identified above,

static risk has been validated over the years for long term


recidivism prediction and dynamic risk can be used in recidivism

prediction as well as treatment planning (Beggs & Grace, 2010;

Olver & Wong, 2011). In addition to the integration of risk, the

VRS-SO uses the TTM (Stages of Change) as additional pre- and

post- testing to identify offender’s risk and need through

treatment (Olver et al., 2007). The creators of the VRS-SO

utilized components of static and dynamic risk research to use to

create their own risk tool (Olver et al., 2007; Beggs & Grace,

2010).

Initially, there were 24 static variables that were

collected from literature that correlated with sexual recidivism

(Olver et al., 2007). These variables were coded and the ones

with the highest univariate relationship (most densely

congregated around) were used in the VRS-SO static scale. The

seven static items include: (a) age at release (b) age at first

sex offense (c) sex offender type (d) prior sex offenses (e)

unrelated victims (f) victim gender (g) prior sentencing dates.

These were placed on a four point scale and the total score was

added up for a static score (Wong et al., 2003; Olver et al.,


2007). The next part of the VRS-SO was the development of the

dynamic scale.

The dynamic scale was developed based upon a review of the

meta-analysis works of Hanson & Bussiere, relapse prevention work

(Pithers et al., 1988 as referenced in Olver et al., 2007), Ward

& Hudson, 1998 as referenced Olver et al., 2007), and The

Psychology of Criminal Conduct (Andrews & Bonta, 2003). Through

the review the following dynamic risk components were found to be

the highest correlating dynamic risk factors to sexual

recidivism: (a) sexually deviant lifestyle (b) sexual

compulsivity (c) offense planning (d) criminal personality (e)

cognitive distortions (f) interpersonal aggression (g) emotional

control (h) insight (i) substance abuse (j) community support (k)

released to high-risk situation (l) sexual offending cycle (m)

impulsivity (n)compliance with community supervision (o)

treatment compliance (p) deviant sexual preference (q) intimacy

deficits (Wong et al., 2003; Olver et al., 2007; Olver & Wong,

2011).


The dynamic factors are also added up on a Likert scale with

a scale ranging from 0 to 3- the higher the score the bigger of

an indicator to sexually inappropriate behavior (Wong et al.,

2003; Olver et al., 2007). The VRS-SO is conducted through a

file review and a semi-structured interview with the VRS-SO

coding manual (descriptions of the dynamic factors) guiding the

interview. The dynamic targets that receive the highest rating (0

to 3) should be considered a treatment target and be subject to a

pre-treatment stages of change baseline rating to assess the

individuals’ motivation (Olver et al., 2007). An offender

demonstrates change after a follow-up rating is performed after a

set amount of treatment is received and the difference between

the scores is determined by 0.5 change (Wong et al., 2003; Olver

et al., 2007). The higher the overall score the higher risk for

recidivism. The dynamic factors that have just been described to

reflect indicators of sexual recidivism, have found to correlate

in the Extended Mind Theory.

A component of EMT that links with the VRS-SO is the

proposition that some distortions may persist only for the


duration of a unique task or may endure because of an offender’s

environment (Wade, 2009; Wade, 2010). An example of a “unique

task” would be intoxication, environments with high intoxication

etc. There has not been a consistent link between substance abuse

and/or a substance related problems to sexual offending, as

Hanson and Bussiere (1998) and Hanson et al., (2007) found a link

to general recidivism, but not a specific one to sexual

recidivism. In contrast, Hanson and Harris (2000) and Hanson and

Morton-Bourgon (2004) found any substance abuse problem,

including intoxication had as significant relationship to sexual

recidivism. Another example of a unique situation as suggested by

Wade (2009) is child pornography. Coupling an offender who has a

distorted belief about children and sex with child pornography

and others who also engage in those beliefs systems. In

situations outside of the computer, the offender may be able to

disassociate with their belief systems and have what appears to

be a normal life. However, when presented with the “unique”

situation (computer) he engages and feels more comfortable in his

distorted belief system about children.


Deviant sexual preferences, including a distorted belief

system about children, has shown to be the most predictive factor

in sexual recidivism (Hanson & Bussiere, 1998; Hanson & Harris,

2000; Wong et al., 2003; Hanson & Morton-Bourgon, 2005). Applying

the Extended Mind Theory (EMT) to this application supports the

hybrid notion of cognitive processes. The distorted belief of

children being sexual beings combined with the external factors

of child pornography makes up the pedophiles cognitive

distortions, both internal and external. The combination of these

factors make up the cognitive practices of an individual and has

the potential to increase the offender’s justifications and

minimizations while in treatment.

Trans-Theoretical Model of Change

The Trans-theoretical Model (TTM) looks at what an

individual experiences and how they utilize those changes to

create new behaviors, modify existing behaviors, or stop

problematic patterns of behavior (DiClemente, 2007). Each step

within the model demonstrates a change that is evidenced by an

individual’s behavior; however, it is not an instantaneous


change, it is one with many movements forward and backward,

stalls and surges. The TTM is based upon five stages that

encompass five cognitive/experiential and five behavioral

processes (DiClemente, 2007)

The stages of change include: Precontemplation,

Contemplation, Preparation, and Maintenance (Tierney & McCabe,

(2005); DiClemente, 2007). In each of the stages there is an

experiential/cognitive component and a behavioral component

(Tierney & McCabe, 2005). This model is characterized by

different cognitive, experiential, and behavioral changes (Olver

et al., 2007). The TTM has been applied to many different

forensic populations, included drug and alcohol and sex offender

populations; however, it has not been incorporated into a sex

offender risk scale until the Violence Risk Scale- Sex Offender

(VRS-SO). The measures of change within the VRS-SO will increase

the usage of the dynamic and acute risk assessment to inform

treatment planning, identify treatment targets, and assessing an

offender’s change within their participation in treatment (Olver


et al., 2007: Beech, Friendship, Erikson, & Hanson, 2002; Hanson

& Harris, 2000) implementation

The ability to change behavior is motivation to comply with

community supervision and “buy-in” to community treatment. To

measure behavior change, a pre- and post-test is conducted based

upon the dynamic factors found to correlate to recidivism (Nunes,

Babchishin, & Cortoni, 2011). Despite this knowledge, the ability

to measure change within treatment and correlating it to sexual

recidivism has continued to be a need through the generations of

risk assessment (Hanson et al., 2007). One important outlook

would be the identification of recidivism based upon treatment

drop-out and the possible change in risk (Nunes & Cortoni, 2008).

It would also be informative for case planning and treatment

matching to identify how high-risk sex offenders compare to low-

risk offenders in their ability to change in response to a

treatment intervention. The Trans-Theoretical Model (TTM) allows

to look at intentional behavior change (Tierney & McCabe, 2005;

DiClemente, 2007), while the Violence Risk Scale- Sex Offender

(VRS-SO) will use the model and apply it the dynamic factors that


have the strongest correlation to sex offender recidivism (Olver

et al., 2007; Beggs and Grace, 2010; Olver & Wong, 2011).

The VRS-SO incorporates community support as a dynamic

variable as it has been found that a lack of positive community

support or refusal to acknowledge its importance, has the ability

to increase an offender’s risk to sexually re-offend (Hanson &

Harris, 2000). The VRS-SO assesses change by identifying the

steps an offender has taken in not only identifying the

importance to change but has actively pursued positive community

support and have withstood challenges in high-risk situations

(Wong et al., 2003). A positive level of change also indicates

the overall ability to avoid high-risk situations. EMT is able to

support the use this variable, as it talks about change. Ward

(2009) indicates the need to not only focus on risk reduction,

but on creating a more appropriate life. An offender can address

his inner distortions about deviance throughout whatever means he

has learned in treatment; however, if he only addresses his

deviance and does not avoid congregating in areas where children

area he has only changed one part of the hybrid system the Extend


Mind Theory is based upon (Ward, 2009). If an offender has only

applied change to one part of their cognitive system, their

ability to justify their deviance or deviant norms increases.

This would then be reflected in the VRS-SO as negative point of

change. If an offender not only addresses his deviance towards

children (beliefs, cognitive processes) and avoids parks and

playgrounds (institutions and people) his level of risk according

to the VRS-SO would decrease.

Risk Change and Recidivism

In Olver & Wong (2011), two hypothesis were proposed: (a)

Reductions in risk in the moderate to high risk group would be

associated with larger reductions in sexual recidivism rates

compared to the lower risk groups (b) The predictive accuracy of

the static scores within the VRS-SO would be decrease as positive

change increased, while the dynamic correlations would continue

to match with the level of change. Although research has been

unable to determine an exact effect treatment has on an

offender’s risk, Hanson et al. (2002) did find that treatment

groups had a 12.3% recidivism rate while comparison groups had a


16.8% recidivism rate; with cognitive-behavioral and systemic

treatments demonstrated stronger treatment effects for sexual

recidivism (17% to 10%) and general recidivism (51% to 32%). This

study was done through a meta-analysis. Although there are plenty

of studies attempting to refute the above findings of Hanson et

al., (2002) (Bilby, Brooks-Gordon, and Wells (2006); Quinsy,

Khanna, and Malcolm (1998); Rice, Quinsey, and Harris (1991) as

referenced in Lovins, Lowenkamp, and Latessa (2009), Hanson et

al., (2002) large sample size argues the validity of the study.

Supporting Olver and Wong’s (2011) hypothesis would be able to

demonstrate the ability of change in dynamic risk to increase or

decrease sexual recidivism.

As predicted, the high-risk/low-change had significantly

higher rates of sexual recidivism compared to all other groups

(low risk/low change, low risk/high change, and high risk/high

change) (Olver & Wong, 2011). The high risk/low change group

sexually re-offended 43 times compared to the high-risk/high

change group who had 27 sexual reconvictions. It is important to


recognize no other significant differences were observed between

the remaining three groups.

The second hypothesis was also supported as the Static-99

(used for the purpose of control) lost its utility to predict

recidivism as the change factor increased (Olver & Wong, 2011).

This only was significant in the moderate and high level of

change groups, regardless of their initial risk score. The

Static-99 was able to maintain its predictive accuracy in the low

and moderate-low change groups (Olver & Wong, 2011). The findings

within this study supports dynamic variables as being a

predictable tool for sexual recidivism as their predictive power

somewhat maintained throughout the groups, in spite of the level

of change. There did appear to be some drop in predictive power

in the high-change group (Olver & Wong, 2011). It is also

important to observe the change in recidivism levels between the

two high risk groups as the high change group appeared to have an

actual reduction in recidivism, while the low change group did

not (Olver & Wong, 2011). Using the theory behind Extended Mind


and the VRS-SO as the tool, can help treatment providers use

change in risk for better treatment placement.

Applying EMT to RNR Principle

The Risk-Needs-Responsivity (RNR) correlates closely with

the VRS-SO as its driving methodology is the use of risk and

needs in order to place an offender in appropriate treatment

(Lovins, Lowenkamp, and LaTessa, 2009). EMT supports that

implication that offenders rely on others when they are

attempting to change their deviant distortions (Wade, 2009; Wade

& Casey, 2010). Keeping a low risk offender in high risk group

can impede the change process and implicates why it is important

to look at not only the Risk Needs Responsivity Model, how it EMT

and RNR are used in conjunction, and then applying the combined

theory and model to Sex Offending Behavior.

Risk Needs Responsivity

Identifying a person’s risk and relate it to treatment

readiness and treatment change is an element of the Risk-Needs-

Responsivity (RNR) principle. Andrews & Bonta (2006, 2010) have

further identified that an offender’s risk to recidivate should


be matched with the level of treatment they receive. The method

of treatment matching according to the level of risk is called

the risk principle. The components of risk principle are that of

risk, need, and responsivity (RNR) (Andrews & Bonta, 2006, 2010).

Although research studies (Andrews & Bonta, 2006, 2010) have

indicated there is a link between dynamic risk factors, dynamic

risk reduction, and recidivism reduction in a single-time-point

risk estimates, there still remains the need for research showing

the correlation between those factors in multiple point risk

estimates and assessments.

Olver and Wong (2011) further investigated the relationship

of treatment related changes and actuarial risk to a sexual

offense. Their study identified treatment can be most effective

after a screening has been established pre-treatment as discussed

above. Using only static instruments has the potential of taking

away any treatment gains and motivation an offender may have

experienced through their treatment program. This could lead to a

harm model of the treatment of sex offenders; providing high

levels of intensive treatment to low and low-moderate sex


offenders and vise-versa. Olver, Wong, Nicholaichuk, and Gordon

(2007) tested the same hypotheses replication studies and also

found static actuarials had little correlation to treatment or

change within treatment. They found a need to integrate dynamic

risk variables into a sex offender assessment tool to appraise

risk, complement treatment, and assessment treatment change.

Dynamic factors are also useful for the identification of

criminogenic needs (Andrews & Bonta 2003). They are changeable or

have the potential to change that could be influenced by

psychological or social means (Wong & Gordon 2006). Of these

criminogenic treatment needs, antisocialist and sexual deviance

have been found to be strongly linked and the highest predictors

of sexual recidivism (Hanson & Morton-Bourgon, 2005, 2009).

Even though dynamic risk factors are a newer component in

sex offender risk assessment, they have always been present. For

instance, DiClemente et al., 1991 suggested process that were

cognitive and emotive based be used early on in treatment and

processes that were focused on behavior change were utilized in

the later stages of change. Unlike the majority of criminals, sex


offenders, including child molesters are pro-social (Nunes &

Cortoni, 2008). Due to this, they are assessed as low-risk;

however, by implementing the Stages of Change in the assessment

process as the VRS-SO does, it identifies the underlying

distorted belief systems that justify their sex offending

behavior. They may present as pro-social, but their deviance

level is still high and many do not wish to address it or get

caught in pretend normal, thus placing them into a pre-

contemplative state, giving the treatment provider a more

accurate treatment target than the risk assessment itself.

It is also important when identifying risk and utilizing the

VRS-SO, high-risk is reflective of a cluster of items that create

a score of high risk (Lovins et al., 2009). The most influential

factor of sexual recidivism is a pattern of sexual deviant

behavior (Hanson & Morton-Bourgon 2005, 2009), meaning all other

dynamic predictors are correlating to sexual recidivism at a

lower rate. The treatment provider would be identifying multiple

target areas to address to reduce the overall risk to recidivate

(Lovins et al., 2009).


EMT and RNR

The third implication of the Extended Mind Theory is the

offender’s level of risk, otherwise known as classification

(Ward, 2010). As the VRS-SO indicates with their dynamic risk

tool, the higher the score, the higher risk. This reflects on

EMT’s suggestion that an offender who has internal distortions

that are deviant, they are more than likely going to have an

external cognition system that reflects it. For example, an

offender who has a deviant preference for children, will more

than likely have an external network that supports the deviant

preference, i.e. child pornography and easy victim access.

Applying the Extended Mind Theory (EMT) to the Risk-Needs-

Responsive (RNR) uses the above example to place an offender into

appropriate level treatment. Once the VRS-SO identifies the

treatment targets via the pre-test, the RNR model recommends

placing this particular offender in a high-risk sex offender

treatment group along with other high-risk offenders. Placing a

high-risk offender into a low-risk offender group, has the

potential of increasing risk of the low-risk offender (Lovins et


al., 2009). EMT states that therapists, group members, and the

various physical and cognitive resources available to individuals

in treatment can be part of their (extended) cognitive resources.

If low-risk offenders are exposed to high-risk offenders, their

external cognitive resources are exposed to those risk

situations. This also reflects upon the soft nature of the human

agency (Clark, 2007, 2008 as referenced in Wade, 2010).

Conclusion

This review builds upon the generations of risk assessment

and integrating the efficacy of the VRS-SO and the positive

correlation of dynamic risk factors with sex offender recidivism.

The use of dynamic and static risk factors pre-treatment has the

potential to accurately assess and place sex offenders into

heterogeneous, cognitive-based sex offender program, thus having

the increased chances of reducing sex offender recidivism.

Dynamic factors appear to be the key in predicting

recidivism while in the community, as this is where change

(positive or negative) occurs at a higher rate than while

incarcerated due to psychosocial and environmental factors. If we


define dynamic variables as external factors, we can use the

Extended Mind Theory to drive the reasoning why dynamic factors

are able to assess risk and identify treatment targets. EMT

operates on three implications: human cognitive agents are

physically embodied, human agents have soft selves (flexible),

and human agents possess hybrid cognitive systems that

incorporate internal and external components.

Throughout the discussion, EMT supports the ideas that

external factors can affect the internal cognitions. In sex

offending behaving, the internal cognitions represents sexual

deviance and the external factors represent the dynamic variables

that can influence the deviance, negatively or positively

depending on the Stage of Change the offender is in. This multi-

dimensional approach is what links the VRS-SO and Extended Mind

Theory in a way that increases the predictive power for sexual

recidivism as well as creating a more efficient method of

treatment. Doern (2004) also supports have a multi-dimensional

approach to sex offender recidivism as the population itself is

not homogeneous, but complex and diverse with different reasons


and beliefs that they committed their offenses as supported by

the Extended Mind Theory (Wade, 2009; Wade & Casey, 2010). This

approach is also demonstrated by the RNR model, supporting a

heterogeneous approach to sex offender treatment. The VRS-SO has

taken a multi-dimensional approach to sex offender recidivism and

assumes they are a diverse population with the ability to change,

much like the four major propositions EMT offers as the basis of

sexual offending distortions.

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