RNR-Based Assessment Feedback: Reception by Offenders and Impact on Self-

Perceived Risk and Needs, Motivation for Change, and Treatment Readiness

A Thesis

Submitted to the Faculty

of

Drexel University

by

Christopher Michael King

in partial fulfillment of the

requirements for the degree

of

Master of Science in Psychology

June 2014

© Copyright 2014

Christopher Michael King. All Rights Reserved.

ii Acknowledgements

I begin with thanks to my advisor, Dr. Kirk Heilbrun, for his kind and supportive

mentorship. Dr. Heilbrun’s exemplary professionalism, work ethic, acumen, and wisdom

are qualities I continue to strive toward. I also wish to thank Dr. David DeMatteo, who

has treated me like a colleague from day one and been there for me through periods of

frustration and self-doubt. I attribute much of the confidence I have developed in my

abilities to Dr. DeMatteo’s encouragement and tutelage. In addition, this project would

not have been possible without the blessing and support of Dr. Ralph Fretz, Matthew

Foran, and their colleagues at the Albert M. “Bo” Robinson Assessment and Treatment

Center and Community Education Centers, Inc. Dr. Fretz’s joshing, I must add, made the

whole thing more fun. I also owe a great deal of gratitude to, and harbor a great deal of

respect for, the men who freely volunteered their time, views, and personal information to

this study while residing at Bo Robinson. Further thanks are due Dr. Stephanie Brooks

Holliday, who kindly allowed me to ride her coattails as I got my bearings as a

researcher, and Kellie McWilliams and Na Young Kim for their assistance with data

entry. Next, I gratefully acknowledge the New Jersey Department of Corrections

Departmental Research Review Board, Drexel University Institutional Review Board,

and American Psychology-Law Society Grants-in-Aid Committee for providing the

authorizations and financial support necessary for the completion of this research.

Finally, my utmost love and thanks belong to my family: my fiancé, Sarah Filone, for her

love, laughter, brilliance, and patience; my parents, Archie and Susan King, and brother,

Michael King, for their love, interest, and support; and Sarah’s parents, Nick and Carol

Filone, for all they do for Sarah and me.

iii Tables of Contents

List of Tables ....................................................................................................................... v!

List of Figures ..................................................................................................................... vi!

Abstract .............................................................................................................................. vii!

1. Introduction ..................................................................................................................... 1!

1.1 Specific Responsivity, Motivation, and Readiness ....................................................... 7!

1.2 Psychological Assessment and Feedback .................................................................... 14!

1.2.1 Assessment Feedback ............................................................................................... 15!

1.2.2 Ethical Considerations Bearing on Feedback Appropriateness ................................ 17!

1.3 Present Study ............................................................................................................... 18!

2. Method ........................................................................................................................... 20!

2.1 Participants .................................................................................................................. 20!

2.2 Measures ...................................................................................................................... 27!

2.2.1 Level of Service/Case Management Inventory (LS/CMI) ....................................... 27!

2.2.2 University of Rhode Island Change Assessment (URICA) ..................................... 28!

2.2.3 Corrections Victoria Treatment Readiness Questionnaire (CVTRQ) ...................... 29!

2.2.4 Risk Need Perception Survey (RNPS) ..................................................................... 30!

2.2.5 Feedback Helpfulness Survey (FHS) ....................................................................... 32!

2.3 Procedures ................................................................................................................... 33!

3. Results ........................................................................................................................... 40!

4. Discussion ...................................................................................................................... 53!

4.1 Study Limitations ........................................................................................................ 59!

4.2 Implications and Future Directions ............................................................................. 62!

List of References .............................................................................................................. 65!

Appendix A: University Of Rhode Island Change Assessment (Long Form) .................. 77!

iv Appendix B: Corrections Victoria Treatment Readiness Questionnaire ........................... 81!

Appendix C: Risk Need Perception Survey (All Versions) .............................................. 83!

Appendix C.1 Risk Need Perception Survey (Version 1) ................................................. 83!

Appendix C.2 Risk Need Perception Survey (Version 2) ................................................. 85!

Appendix C.3 Risk Need Perception Survey (Version 3) ................................................. 87!

Appendix D: Feedback Helpfulness Survey ...................................................................... 90!

Appendix E: Standardized Feedback Form ....................................................................... 91!

Appendix F: Feedback Sessions Curriculum .................................................................... 95!

Appendix G: Demographic Information ......................................................................... 103!

Appendix H: LS/CMI And RNPS Concordance Scores ................................................. 105!

Appendix I: URICA Continuous-Method Score ............................................................. 107!

Appendix J: CVTRQ Score ............................................................................................. 108!

Appendix K: FHS Score .................................................................................................. 109!

v List of Tables

1. Sample Demographics ................................................................................................... 22

2. Means, Standard Deviations, and 95% Confidence Intervals for Study Measures at Baseline and Follow-up ................................................................................................. 42

3. Means, Standard Deviations, and 95% Confidence Intervals for FHS Items ............... 51

vi List of Figures

1. Bar Graph of Average Risk Need Perception Survey and Level of Service/Case Management Inventory Need Concordance Scores ...................................................... 44

2. Bar Graph of Average University of Rhode Island Change Assessment Total Scores ............................................................................................................................ 46

3. Bar Graph of Average Corrections Victoria Treatment Readiness Questionnaire Total Scores ............................................................................................................................ 48

4. Bar Graph of Average Feedback Helpfulness Survey Scores, Compared to the Mid-point of the Measure ...................................................................................................... 50

vii Abstract

RNR-Based Assessment Feedback: Reception by Offenders and Impact on Self-Perceived Risk and Needs, Motivation for Change, and Treatment Readiness

Christopher Michael King Kirk Heilbrun, Ph.D.

Although there is growing focus in correctional psychology on offenders’ motivation for

change and readiness for treatment, empirical research on these topics is sparse. This pre-

post-control study examined offender receptiveness to Risk-Need-Responsivity-based

assessment feedback and evaluated the effects of that feedback on self-perceptions of risk

and criminogenic needs, motivation for change, and treatment readiness. Sixty-seven

adult male prisoners at a private reentry facility were randomly selected and assigned to

receive discussion-based feedback, form-based feedback (involving reading a feedback

form, listening to a brief explanation, and having the opportunity to ask questions), or no

feedback regarding their risk and needs assessment results (Level of Service/Case

Management Inventory). Measures of self-perceived risk and needs (Risk Need

Perception Survey), motivation for change (University of Rhode Island Change

Assessment), and treatment readiness (Correction Victoria Treatment Readiness

Questionnaire) were administered prior and subsequent to receipt of feedback. A

satisfaction measure (Feedback Helpfulness Questionnaire) was also administered post-

feedback. Mixed two-way analysis of variance indicated that motivation for change

significantly increased for the discussion-based group after receipt of feedback, and

treatment readiness increased for each condition between baseline and follow-up. Both

effects were of a moderate magnitude. Post-hoc contrasts also revealed significant

differences for treatment readiness both within the discussion-based feedback condition

viii (a moderate-strength effect), and between the discussion-based feedback condition and

the control condition at follow-up (a strong effect). Feedback recipients rated the

helpfulness of the feedback well above the midpoint of the satisfaction questionnaire.

Results suggest that risk-relevant assessment feedback is favorably received by offenders

and may impact their motivation for change and treatment readiness, thus representing a

promising area for future research.

1 Chapter 1: Introduction

Criminal recidivism is an important societal challenge. Data reported by the

Bureau of Justice Statistics and the PEW Center on the States make the gravity of the

problem in the United States clear. The estimated number of persons under the

supervision of adult correctional authorities in the United States at yearend 2012 was

6,937,600 (Glaze & Herberman, 2013). This figure broke down into 2,228,400 persons

incarcerated in jails (744,500) and prisons (1,483,900) and 4,781,300 persons under

probation (3,942,800) and parole (851,200) supervision (Glaze & Herberman, 2013). The

number of prisoners under the jurisdiction (versus custody) of state and federal

correctional agencies at yearend 2012 was estimated at 1,570,397 (Carson & Golinelli,

2013).

The estimated number of prisoners released throughout 2012 was 637,411

(Carson & Golinelli, 2013). Studies tracking large, multistate samples of prisoners

released in 1994, 1999, and 2004 found three-year return-to-prison rates of 51.8%,

45.4%, and 43.3%, respectively (Langan & Levin, 2002; Pew Center on the States, 2011).

A more recent study of a large sample of offenders released in 2005 from 30 states’

prisons estimated that 67.8% of prisoners had been rearrested within three years of

release, a figure that increase to 76.6% by five years follow-up. Additional analyses of

data from 23 of these states revealed that 49.7% and 55.1% of state prisoners had been

returned to prison for a violation of community supervision or a new arrest by three and

five years out, respectively. In absolute terms, multiplying the recent three-year return-to-

prison estimate (49.7%) by the number of prisoners released in 2012 results in a predicted

return-to-prison figure of 316,793 by the start of 2016. If recidivism was defined less

2 strictly (e.g., as an arrest), and if recidivism rates exhibited by offenders released from

local jails were similar to those of released prisoners, then the true magnitude inmate

recidivism becomes clearer. Add to this the reoffending engaged in by individuals under

community supervision; Bureau of Justice Statistics data estimated that the 1,248,337

parolees and probationers at risk of reincarnation in 2007 had a 16% within-year return-

to-incarceration rate (Glaze & Bonczar, 2009). These high rates of recidivism are

associated with substantial human and budgetary costs (Kyckelhahn, 2013; Romani,

Morgan, Gross, McDonald, 2012; Kyckelhahn & Martin, 2013).

A variety of strategies have been pursued to address the problem of repeat

criminality (Andrews & Bonta, 2010b; Dvoskin, Skeem, Novaco, & Douglas, 2012;

Lipsey & Cullen, 2007). Human service interventions are a loosely related collection of

rehabilitation services that have been attempted to facilitate behavior change among

offenders, and to improve offender’s life circumstances, toward the end of reducing rates

of reoffending (Aos, Miller, & Drake, 2006; Lipsey & Cullen, 2007). Notwithstanding

the lack of any right to such treatment or services for most offenders in the United States

(“Developments in State Constitutional Law,” 2002; Frase, 2008; Palmer, 2010; Rotman,

1986), correctional agencies have been relatively keen on implementing rehabilitation

programs in recent years. This interest is attributable to growing correctional populations

and budgets, coupled with consistent empirical findings that many forms of correctional

human services yield moderate reductions in recidivism (Dvoskin, Skeem, Novaco, &

Douglas, 2012; Lipsey & Cullen, 2007). Furthermore, consistent reports of moderate,

positive effects for rehabilitation become even more appealing when juxtaposed against

3 the smaller or negative effects observed with variable supervision intensity and sanction

severity (Lipsey & Cullen, 2007; Smith, Gendreau, & Swartz, 2009).

The risk-need-responsivity (RNR) model (Andrews, Bonta, & Hoge, 1990a;

Andrews et al., 1990b) constitutes a general rehabilitation theory that casts effective

criminal justice responses to offenders in terms of underlying principles (Andrews &

Bonta, 2010a, Chapters 2, 15; Andrews & Dowden, 2007; Gendreau, Smith, & French,

2006; Ward, Mesler, & Yates, 2007). It is the most widely recognized theory of offender

rehabilitation, and some aspects of the model have received strong empirical support

(Andrew & Bonta, 2010a, Chapters 2, 15, 2010b; Brooks-Holliday et al., 2011; Dvoskin,

Skeem, Novaco, & Douglas, 2012; Ward, Mesler, & Yates, 2007). At the principles and

practices level, the model provides guidance to courts and justice agencies in their crime

reduction efforts by specifying who and what to target with rehabilitative programming

and how to most justly, humanely, and effectively deliver and monitor those services.

Pragmatically speaking, the empirically derived RNR, being first articulated as an

interpretation of the results of a meta-analysis (Andrews et al., 1990a, 1990b), has much

to offer in regard to prediction and treatment in its own right. However, its originators

situated the model within a general psychological theory of human behavior relevant to

criminal conduct (referred to by Andrews and Bonta (2010a) as a Psychology of Criminal

Conduct), adopting Andrews’s (1982) earlier articulated Personal, Interpersonal, and

Community-Reinforcement (PIC-R) perspective. PIC-R constitutes a multilevel

application of a general personality and cognitive social learning theory (referred to as a

General Personality and Social Psychological Perspective on Criminal Conduct) to

explain variations in individual criminal behavior within different social-structural

4 arrangements (Andrews & Bonta, 2010a, Chapters 1, 4). It pulls from biological,

personality, and social-structural perspectives to help account for the development,

maintenance, and modification of situational contingencies, but it emphasizes behavioral

and cognitive social learning principles (which regard the person in the immediate

psychological situation as the appropriate level of analysis for explaining variation in

individual behavior) due to their demonstrated efficacy in applied contexts (Andrews &

Bonta, 2010a, Chapters 1, 4). In their analysis and critique of the RNR model, Ward,

Mesler, and Yates (2007) argue that much about the relationships between and among

these three underlying theories and the RNR model is unclear.

According to RNR, effective correctional programs or systems facilitate

reductions in recidivism chiefly because they do the following. First, they vary

restriction, supervisory, and treatment intensity as a function of an individual’s

propensity to reoffend (risk principle). Second, they focus interventions on the

modification of common and idiosyncratic risk factors for criminality that are capable of

change (termed criminogenic needs; need principle). Third, they tailor interventions to

the characteristics of the individual offender that moderate treatment engagement and

gain (specific responsivity principle and need principle, respectively). Fourth, they

predominantly utilize cognitive-behavioral change strategies (general responsivity

principle).

Some specific observations about these central principles are useful for present

purposes. Under the responsivity rubric, general responsivity posits that interventions

predicated upon contemporary learning (i.e., cognitive-behavioral) theories and

techniques are likely to be most effective with offenders, just as they tend to be with non-

5 justice-involved persons. The second component of the responsivity principle, specific

responsivity, directs that interventions be tailored to the individual characteristics of an

offender so as to enhance treatment effects. Assessment of gender, culture, personality,

emotionality, and cognitive capability, among other factors, helps to illuminate

appropriate and inappropriate types and modes of treatment, person-specific obstacles to

change, and idiographic issues in need of attention that might otherwise be overlooked.

The Central Eight risk factors are espoused under the need principle. At least

seven of these are considered dynamic and thus represent intermediate targets for change:

antisocial history; antisocial attitudes and cognitions; antisocial associates; antisocial

personality pattern; substance abuse; and problematic family/marital, school/work, and

leisure/recreation circumstances. These are the model’s primary treatment targets—the

criminogenic needs it formally recognizes. The focus afforded them stems from meta-

analytic evidence of the strength of their covariation with criminal conduct (Andrews &

Bonta, 2010a), although recent evidence highlights that there is still a lot that is unknown

about the nature of dynamic risk factors (Douglas & Skeem, 2005; Kroner & Yessine,

2013; Morgan, Kroner, Mills, Serna, & McDonald, 2013). The same sources of evidence

also indicate that outside of the Central Eight are numerous factors unrelated or

minimally related to reoffending (Andrews & Bonta, 2010a). The RNR model thereby

distinguishes between criminogenic needs and noncriminogenic needs. Per the model,

when the goal is to reduce recidivism, effective correctional interventions should

primarily target criminogenic needs. But some noncriminogenic needs should nonetheless

be addressed on clinical, ethical, or humanitarian grounds. Furthermore, it is conceivable

that changes in noncriminogenic needs may sometimes indirectly elicit changes in

6 criminogenic needs. For example, to motivate an offender (a specific responsivity issue)

to engage in treatment targeting criminogenic needs, it may be helpful or necessary to

address various noncriminogenic life problems that are functionally preventing treatment

engagement (Andrews, Bonta, & Wormith, 2011).

The RNR model further envisions the linkage of assessment and treatment so that

the prescribed level of restriction, monitoring, and interventions are informed by an

appraisal of risk level, criminogenic needs, and responsivity factors (Andrews et al.,

2011). Indeed, newer iterations of some of the Level of Service (LS) tools provide for

assessment–treatment linkage via a systematic approach (see Andrews, Bonta, &

Wormith, 2010). As a tool for linking assessment with treatment, the RNR model

recommends the sharing of assessment results with offenders to help motivate them for

the task of modifying dynamic risk factors (Andrews et al., 2011). It also officially

recognizes motivational interviewing as a core provider practice (Andrews & Dowden,

2007).

Outside of the corrections context, assessment feedback is considered clinically

advantageous for a variety of reasons: to facilitate open discussions between clinicians

and clients, to help clients better understand their problems, and to increase client well-

being and motivation to follow treatment recommendations (e.g., Smith, Wiggins, &

Gorske, 2007). Moreover, there is evidence to support its role as an important component

of effective assessment and treatment linkage, insofar as the feedback process can be

therapeutic (Finn, 2007). However, the role of assessment feedback in RNR, in contrast

to traditional clinical settings, has yet to be empirically examined (McMurran & Ward,

2010). Motivational interviewing, in turn, has a large general research base (McLouth,

7 2013; Miller & Rollnick, 2013), and a moderate number of studies have been conducted

evaluating motivational interviewing with offenders (McLouth, 2013; McMurran, 2009).

Given the relatively limited state of the literature in this area, the following sections set

forth the case for how assessment feedback fits within the growing interest in offender

motivation and related concepts (e.g., violence risk from the subjective or first-person

perspective; Yang & Mulvey, 2012).

Specific Responsivity, Motivation, and Readiness

Although the specific responsivity principle has historically been the most

understudied of the three RNR principles (Andrews, Bonta, & Wormith, 2006), the call

for its move to the forefront of research priorities (e.g., Andrews et al., 2011) has gained

traction in recent years. Interest in understanding, measuring, and influencing offender

motivation to engage in treatment has been particularly noteworthy, stimulated by the

problem of high treatment attrition rates among higher risk offenders (Jewell & Wormith,

2010; Olver, Stockdale, & Wormith, 2011; Wormith & Olver, 2002). Here it is important

to note evidence that an offender’s desire to change, by itself, has been found to be

unrelated to reoffending, regardless of risk level (Stewart & Millson, 1995). Consistent

with this finding, offender motivation is generally considered a process variable or

instrumental outcome that facilitates greater engagement in treatment. It is the actual

participation in appropriately designed and delivered treatment, however, and the

resultant change of criminogenic needs into strengths, that is thought to effect reductions

in recidivism (Andrews & Bonta, 2010a, p. 291; Ward, Day, Howells, & Birgden, 2004;

but see Anstiss, Polaschek, & Wilson, 2011).

8 Recent advances in the offender motivation literature include increased

definitional clarity, measure development, and a growing number of outcome studies

examining the impact of motivation-influencing strategies. In general, models of

motivation tend to suggest that behavioral change is most likely to occur when

individuals anticipate that a change will be beneficial for them, and when the perceived

costs of perpetuation of the prior behavior sufficiently outweigh its benefits (McCrady,

2008). The transtheoretical model of change proposed by Prochaska, DiClemente, and

Norcross (1992) is a popular model that envisions readiness to change along a continuum

of stages. It has been widely adopted for criminal behavior (Andrews et al., 2011; Day,

Bryan, Davey, & Casey, 2006; Polaschek, Anstiss, & Wilson, 2010), albeit not

unquestioningly (Burrowes & Needs, 2009; Casey, Day, & Howells, 2005; West, 2005).

Howells and Day (2003) argue that the transtheoretical model fails to account for

secondary gains, and so they consider Deci and Ryan’s (2000) self-determination theory

to add unique insights about intrinsic motivation being influenced by innate

psychological needs, and the interplay of extrinsic motivation (or contingencies) and

intrinsic motivation. Offender-specific models for motivation (Drieschner & Boomsma,

2008; Drieschner, Lammers, & van der Staak, 2004) and the more expansive concept of

treatment readiness (Serin, 1998; Serin & Kennedy, 1997; Ward, Day, Howells, &

Birgden, 2004) have also been proposed. These crime-specific models, in turn, have

resulted in offender-focused adaptions to measures designed to assess readiness for

change of other problem behaviors, as well as the development of new instruments

designed particularly for use with offenders (McMurran, Sellen, & Campbell, 2011;

McMurran & Ward, 2010; Polaschek et al., 2010).

9 In their treatment of the subject, Ward, Day, Howells, and Birgden (2004) suggest

that offender motivation is usefully embedded within a more comprehensive treatment

readiness framework. Their model outlines hypothesized and reciprocally interacting

internal (person) and external (contextual) factors with which an offender presents that

might influence instrumental (treatment engagement) and ultimate outcomes (change in

criminogenic needs) in his or her correctional treatment. Stated another way, treatment

readiness has been “broadly defined as the presence of characteristics (states or

dispositions) within either the client or the therapeutic situation, which are likely to

facilitate engagement in therapy, and which, as a consequence of this investment, are

likely to augment the process of therapeutic change” (McMurran & Ward, 2010, p. 78).

Arguably aligned more closely to RNR’s responsivity principle (Howells & Day, 2003),

Serin (1998), Serin and Kennedy (1997), and Stewart and Picheca (2001) provide

additional lists of motivation and readiness factors.

One aspect internal to the person that most of the above models acknowledge is

the concept of problem recognition. Relevant to offenders’ problem awareness is research

that has examined offenders’ self-perceptions of their likelihood of post-release success

or reoffending (among other reentry- or desistance-related outcomes; Burnett, 2004;

Cobbina & Bender, 2012; Dhami, Mandel, Loewenstein, & Ayton, 2006; Friestad &

Hansen, 2010; Kivivuori & Linderborg, 2010; Maruna, 2001; Sedikides, Meek, Alicke, &

Taylor, 2013; Souza, Lösel, Markson, & Lanskey, 2013; Visher, La Vigne, & Castro,

2003; Zamble & Quinsey, 1997), as well as the applicability of criminogenic needs to

themselves and others (Brooks Holliday, Heilbrun, DeMatteo, Fretz, & King, 2014;

Brooks Holliday, King, & Heilbrun, 2013). More distal but still related areas of research

10 includes psychiatric inpatients’ self-appraised short-term risk of violence upon release

(Skeem, Manchak, Lidz, & Mulvey, 2013), self-report risk/need measures (e.g., the

Classification of Violence Risk, and the Self-Appraisal Questionnaire; Monahan et al.,

2005; Loza, 2005), and the recent call for increased attention to subjective processes in

violence risk research (Yang & Mulvey, 2012).

In the largest study of self-assessed recidivism risk (which is also the most

comparable to the present research), Dhami et al. (2006) asked 241 high-security federal

male prisoners in the United States and 283 medium-security male prisoners in the

United Kingdom to forecast their chances of post-release success. The United States

prisoners estimated their percentage chance of reoffending to be 30.51% (SD = 32.36)

and of being reincarcerated, 26.23% (SD = 31.21); the prisoners from the United

Kingdom provided average estimates of 29.27% (SD = 31.55) and 27.90% (SD = 31.17)

for reoffending and reincarceration, respectively. After combining the reoffending and

reincarceration estimates for each sample (United States prisoners: 28.21%, SD = 29.11;

United Kingdom prisoners: 28.62%, SD = 30.56) and comparing those figures to three-

year recidivism estimates for United States federal offenders released in 1987 (41%) and

two-year reconviction rates for adult male prisoners release from prison in the United

Kingdom in 1999 (55%), Dhami et al. (2006) found that both samples, on average,

significantly underestimated their chances of recidivism, by 12.79% (d = 0.44) and

26.38% (d = 0.89), respectively. They also found that the degree of calibration for

estimates varied by offender ethnicity, offense type, sentence length, and number of

previous convictions.

11 In addition, for the United States prisoners in Dhami et al. (2006), having

committed an offense against the person and anticipating return to family and friends

upon release significantly predicted lower self-estimates of recidivism, whereas more

frequent prison misconduct was significantly predictive of the opposite. For United

Kingdom prisoners, a higher rate of past drug use was significantly predictive of higher

self-appraised recidivism, as contrasted with greater participation in “regime activities

such as education, employment, and religion” and more optimistic forecasts about

obtaining employment in the community, which were both significantly predictive of

lower self-estimates of recidivism (Dhami et al., 2006, p. 633). A higher number of prior

offenses and prison misconducts were predictive of higher self-assessed recidivism risk

for both samples. The United Kingdom prisoners were also uniquely asked to opine on

the likelihood of reoffending for others and themselves using a 7-point Likert scale

(“very unlikely” to “very likely”). The researchers found that the prisoners predicted that

they would be significantly less likely (M = 2.87, SD = 2.18) than their peers (M = 5.01,

SD = 2.00) to reoffend (d = −1.02).

Turning to research examining offenders’ views about criminogenic needs,

Brooks Holliday and colleagues (2013, 2014) found that offenders tended to endorse

many of the Central Eight risk factors, as well as many non-predictive but treatment-

relevant factors, as increasing a hypothetical person’s likelihood of committing a crime.

Conversely, offenders marked as irrelevant many factors known to be unrelated to

offending risk. When asked to answer which factors applied to themselves, and increased

their own risk for reoffending, offenders tended to endorse only two criminogenic needs

as personally salient at statistically significant levels (financial problems and cognitions),

12 and tended to agree with evaluator ratings for only a few criminogenic needs (antisocial

pattern, substance misuse, and family and marital circumstances). Brooks Holliday et al.

(2014) also observed that the degree of concordance between evaluator-rated and self-

endorsed criminogenic needs did not significantly predict recidivism at 18 months

follow-up. Taken together, the above three studies suggest that many offenders may be

poorly calibrated in terms of their self-perceived risk and needs when referenced against

aggregate recidivism rates and evaluation-indicated criminogenic needs.

To address this disconnect and related issues, the application of motivation

enhancement techniques to offenders is an area of particular enthusiasm at present

(Bogue & Nandi, 2012; Walters, Clark, Gingerich, & Meltzer, 2007), although supportive

evidence is still limited (Anstiss et al., 2011; Farbring & Johnson, 2008; Ginsburg, Mann,

Rotgers, & Weeks, 2002; McMurran, 2009). In general, these approaches view

motivation as an internal state (e.g., position along an ambivalence continuum)

influenced by the client’s experiences as well as others’ interpersonal behaviors (e.g., that

of a therapist; McCrady, 2008). The FRAMES acronym is commonly invoked, which

refers to the idea that providers effectuate enhancement of client motivation by providing

personalized assessment feedback; assigning clients the responsibility for change and

emphasizing that prerogative; offering clear, supportive, and professional advice or

guidance; presenting clients with a menu of change strategies and goals from which they

can choose; demonstrating accurate empathy for the client’s plight or experience; and

support clients’ self-efficacy for change (McCrady, 2008; Ogrodniczuk et al., 2005;

Walitzer, Dermen, & Connors, 1999). Ogrodniczuk et al. (2005) noted additional

strategies that have been suggested in the literature, including addressing any

13 misconceptions about the therapeutic process; incentivizing and reinforcing consideration

of, movement toward, and effectuated change; eliciting self-motivational client speech;

and reframing problems or obstacles in a way that makes them seem less formidable and

more susceptible to alteration by the client.

Motivational interviewing (Miller & Rollnick, 1991, 2002, 2013), or aspects of

the approach, has been the most widely adopted method for addressing client motivation

issues. The method, although often coupled with the aforementioned transtheoretical

model of change, is in fact not based on it, although the two coexist quite complimentary

(Miller & Rollnick, 2009). For instance, a common conceptualization posits that one’s

readiness to change is influenced by factors focused upon in motivational interviewing,

such as a person’s awareness of the severity of his or her problem behavior and the

positive consequences that would flow from changing it, as well as the perception of

choice in the matter (McCrady, 2008). Consequently, during preliminary interventions

and treatment planning (both which might possibly take the form of motivational

interviewing), therapists should attend to client stage of change, which encompasses self-

perceptions regarding problem areas (McCrady, 2008). The general motivational

interviewing approach does not require client feedback per se; Motivational Enhancement

Therapy, however, is a particular form of motivational interviewing that explicitly

includes the provision of structured assessment feedback (Miller & Rollnick, 2009;

Miller, Zweben, DiClemente, & Rychtarik, 1992).

A few studies have evaluated pretreatment motivational interventions with

corrections clients and obtained promising results in terms of reductions in recidivism,

advancements in participants’ stage of change, and increases in referrals to correctional

14 programming (e.g., Anstiss et al., 2011). However, there are as yet no studies of

pretreatment interventions that target other responsivity or readiness factors, or of the

effects of such interventions on program retention rates (McMurran & Ward, 2010).

Examples of pre-treatment or readiness interventions (i.e., those designed to prevent

dropout) include “role induction” (explanations of therapy rationale, process, outcome

expectations, and therapist and client responsibilities), “vicarious therapy pre-training”

(review of pre-recorded therapy examples), and “experiential pre-training” (undergoing a

simulation of therapy; McMurran & Ward, 2010, pp. 80–81; Ogrodniczuk, Joyce, &

Piper, 2005; Walitzer et al., 1999). The importance of more work in this area, of course,

is to learn more about ways to increase the probability that offenders will enter,

meaningfully participate in, adhere to, and persist in treatment (McMurran & Ward,

2010).

Psychological Assessment and Feedback

Formalized assessment is a distinguishing feature of psychology relative to other

mental health fields, and it is an enterprise reputed to be scientifically valid and of

significant practical value (e.g., Meyer et al., 2001). In their review of meta-analytic

evidence of psychological test validity and multimethod assessment, Meyer et al. (2001)

concluded that the evidence of the validity of psychological tests is “strong and

compelling . . . [and] comparable to [that of] medical test[s]” (p. 128). They further

concluded that multimethod assessment yields unique information and so an exclusive

reliance on only one method (e.g., clinical interview) tends to paint an incomplete picture

of an examinee. The practical value of psychological assessment, they noted, is the ability

15 to offer services to patients and referring professionals that are informed by test results

(Meyer et al., 2001).

Within corrections, RNR directs that assessments be used to inform offender

management (Andrews & Bonta, 2010a, Chapter 2). RNR-based assessments and case

conceptualizations are valuable in that they facilitate well-informed restriction,

supervision, and treatment decisions (Andrews & Bonta, 2010a, Chapters 2, 10;

DeMatteo, Hunt, Batastini, & LaDuke, 2010). When treatment intensity and foci are not

directly linked to the results of RNR-based assessment, either because no risk and needs

assessment was conducted or because risk and needs assessment results were not utilized

in the planning and delivery of intervention services, treatment impact is likely to be

reduced if not eliminated (DeMatteo et al., 2010). This is attributable to the fact that if

correctional treatment is disconnected from assessment, there is a serious risk that

treatment will not be of sufficient duration or intensity, will target factors unrelated or

weakly related to recidivism, or will not be appropriately individualized.

Assessment Feedback. Meyer et al. (2001) recommended that future research

“focus on the practical value of assessment clinicians who provide test-informed services

to patients and referral sources” (p. 155). To this end, he and is colleagues noted that

because “the main purpose of assessment is to provide useful information to patients and

referral sources, key outcomes would directly address these issues (e.g., resolution of

patient and therapist referral questions, congruence over treatment goals, confidence that

treatment is moving in a helpful direction)” (p. 154). They offered as an example of a

potential study design one in which participants in need of psychological assessment

services were administered a battery of multimethod assessment tools that are in regular

16 clinical use and selected for their relevance to each individual participant, followed by the

provision of personal assessment feedback to the participant and his or her referring

provider. These participants could then be compared to a control group of participants

equally in need of psychological assessment but who instead just received comparable

therapy without the more searching assessment services beforehand. A takeaway from

Meyer et al.’s (2001) review is that at least one benefit of psychological assessment is the

fact that results can be shared with examinees.

Clinician-perceived benefits of providing assessment feedback include that it may

prove illuminating for the client and thereby increase client well-being and treatment

motivation, the client may validate the proffered feedback, and the feedback may evoke

client concerns and doubts for subsequent discussion (Addis & Carpenter, 2000; Curry &

Hanson, 2010; Nezu, Nezu, & Cos, 2007; Smith, Wiggins, & Gorske, 2007). The clinical

effects of psychological assessment combined with collaborative, personalized, and

involved feedback—an assessment model considered by some to be a therapeutic

intervention in itself (Finn, 2007; see also Weiner & Greene, 2008)—has recently

received meta-analytic support, with the impact on treatment process having been found

to be particularly large (Poston & Hanson, 2010; but see Lilienfeld, Garb, & Word, 2011,

for a critique). Research has also found that clients who agree with a tendered case

formulation and corresponding treatment logic manifest better therapy outcomes (Addis

& Carpenter, 2000). In short, the value of assessment feedback has long been recognized

(e.g., Zaro, Barach, Nedelman, & Dreiblatt, 1977) and is a common component of many

evidence-based treatment protocols (see, e.g., Barlow, 2008).

17 Presumably for the foregoing reasons, the provision of assessment feedback has

been recommended for RNR-based work with offenders, especially to increase offender

motivation for treatment via the facilitation of “mutually agreed on service plans”

(Andrews et al., 2011, p. 742). The model’s originators direct that “the results of RNR-

based assessments [be used] to review strengths, problem areas, and responsivity issues,”

which, if accepted, should include relative comparisons to normative recidivism data and

coverage of the consequences of choosing to participate in RNR-based services or not

(Andrews et al., 2011, p. 742). Viewing such “open reviews of the results and

implications of RNR-based assessments with moderate and higher risk individuals . . .

[as] a fundamental approach” to RNR-based interventions, Andrews et al. (2011, p. 742)

indicate that the inclusion of case management sections in the newer iterations of the LS

tools was precisely for the purpose of “increas[ing] the likelihood that service providers

will conduct these important discussions with offenders,” something which is also

stressed in training for providers.

Ethical Considerations Regarding Feedback Appropriateness. It is

important to recognize that the provision of assessment feedback is not appropriate in all

contexts—principally when an offender cannot be regarded as the client. Standard 9.10

(Explaining Assessment Results) of the American Psychological Association’s (2010)

Ethical Principles of Psychologists and Code of Conduct, for instance, provides that

when psychologists conduct testing, they are to “take reasonable steps to ensure that

explanations of results are given . . . unless the nature of the relationship precludes

provision of an explanation . . . (such as in some . . . forensic evaluations), and this fact

has been clearly explained to the person being assessed in advance” (emphasis added).

18 The Specialty Guidelines for Forensic Psychology (American Psychological Association,

2013) are consistent; Standard 10.05 provides that “[f]orensic practitioners take

reasonable steps to explain assessment results to the examinee or a designated

representative in language they can understand . . . . In those circumstances in which

communication about assessment results is precluded, the forensic practitioner explains

this to the examinee in advance.”

Heilbrun’s (1997) distinction between violence prediction and risk management

offers further guidance on the feedback-appropriateness decision. If the goal is solely to

predict an individual’s risk of recidivism, assessment feedback is not needed for two

reasons: (1) the examinee is unlikely to be the party requesting the evaluation (i.e., he or

she is not the client); and (2) modification of recidivism risk is not part of the task,

obviating the need to delve into the constituent components of one’s risk. However, if the

objective is risk management and reduction, RNR is, at present, the best-supported model

for informing and guiding such efforts, and that model explicitly calls for assessment-

informed interventions and the sharing of assessment results with corrections clients.

Present Study

In response to the call for increased research on offender motivation and treatment

preparation (McMurran & Ward, 2010; Wormith et al., 2007), as well as to build upon

recent work examining offenders’ self-perceived criminogenic needs (Brooks Holliday et

al., 2014; Brooks Holliday et al., 2013), this study tested the effects of RNR-based

assessment feedback on offenders’ beliefs about their personal risk of reoffending and

criminogenic needs, their motivation for behavior change, and their readiness for

correctional treatment. Participants’ motivation for change and readiness for treatment

19 were evaluated via self-report. For probabilistic risk and criminogenic needs, we

evaluated the concordance between actuarial risk score and self-reported likelihood of

reoffending, and evaluator-indicated Central Eight risk factors and personally endorsed

criminogenic needs. Theoretically, assessing the pattern of congruence between

assessment-identified and self-regarded risk and needs may have treatment implications

for work with offenders. A relative match may suggest that a corrections client is likely to

buy into RNR-informed treatment, while a non-match may be indicative of a lack of

treatment readiness or motivation (e.g., the client is ignorant of his or her risk factors or is

engaged in denial or minimization) or, alternatively, that the case conceptualization is

incorrect. If there is a lack of concurrence and a clinician suspects readiness or

motivation problems on the part of the corrections client, then pretreatment interventions

targeting such deficits may be indicated (e.g., education to improve problem recognition,

motivational interviewing).

20 Chapter 2: Method

Participants

After securing all necessary institutional review board approvals, the study

commenced at a privately operated reentry facility in New Jersey. Pursuant to an a priori

power analysis, with alpha set at .05, power at .95, effect size (f) at .25 (a medium-

magnitude effect according to Cohen (1992)), correlation among repeated measures at

0.5, and nonspherity correction ε at 1, the necessary sample size was determined to be N

= 66.1 A moderate effect size was anticipated for all hypotheses based on the large effect

sizes, per Cohen (1992), observed in a similar study of a more intensive motivation-

enhancement service (η2 = .23, .23, and .27; Anstiss et al., 2011). A 15% attrition rate

was anticipated, and so a sample size of N = 75 with 25 participants in each group was set

as the enrollment target.

Male facility residents who were under the jurisdiction of the New Jersey

Department of Corrections—the two study inclusion criteria—were randomly solicited to

participate in the study within approximately a week of their arrival at the facility (N =

127).2 Prospective participants had either been sent forward from a secure facility (e.g.,

1 The power analysis was conducted using G*Power 3.1.9.2 (Faul, Erdfelder, Lang, & Buchner, 2007; http://www.gpower.hhu.de/en.html). The selected statistical test was “ANOVA: repeated measures, within-between interaction.” The number of groups was set as three, and the number of measurements as two. The value of effect size f, which G*Power 3 uses in conducting a mixed ANOVA power analysis, was determined via approximate conversion of ηp

2; specifically, from a moderate effect size of ηp2 = .06 as

defined by Cohen (1988). The effect size was specified according to “G*Power 3.0” procedures, however, rather than the “as in SPSS” or “as in Cohen (1988)” options. Specifying the effect size in this way resulted in a substantially smaller requisite sample size estimate, in part because the anticipated correlation between repeated measures was taken into account. By contrast, a power analysis with similar parameters—the differences being the effect size was “Effect size f(V)” = .25 rather than “Effect size f” = .25, and there was no option to set the correlation among repeated measures)—conducted pursuant to the Cohen (1988) procedure yielded an estimated necessary sample size of 252. A sample this large was not feasible given the author’s resources, and so the study could be regarded as underpowered from the outset.

21 state prison) to begin the process of reentry or backward from a halfway house for

administrative reasons or for being charged with a violation of halfway house rules. The

only exclusion criterion was the reported or otherwise noticed inability to understand or

read English at a level sufficient to understand study materials (n = 2). Individuals who

provided informed consent to participate (N = 82) were randomly assigned to one of the

three study conditions. Enrolled participants were removed from the study if they were

transferred from the study site without completing both phases of the study (e.g., if they

were moved for administrative or disciplinary reasons, or if they were released on parole

or for having reached their maximum sentence date; n = 6); if they had incomplete

LS/CMI Section 1 information in their records (n = 2);3 or if they expressed a desire to

withdraw before completing the study (n = 7). The final sample consisted of 67

participants who completed both phases of the study, 22 of whom were in the discussion-

based feedback group, 21 in the form-based feedback group, and 24 in the control group.

Demographic information for the study participants, obtained via file

information (and recorded using the form in Appendix H), is provided in Table 1.

2 The mean number of days between entry data and study enrollment date was 3 days, with a standard deviation of 2 days and a range of 1 to 8 days). 3 One participant had 39 of the LS/CMI’s 42 Section 1 items scored (versus 19 and 22 for the two participants who were removed from the study due to incomplete LS/CMI data). The author scored the remaining four items for this participant by briefly interviewing him.

22 Table 1

Sample Demographics Condition

Variable Non-completers (n = 15)

Control (n = 24)

Form-based (n = 21)

Discussion-based (n = 22)

Completers (n = 67)

Age 35 (11) 39 (8) 35 (9) 33 (8) 36 (9)

Raceab

African American/Black 6 (40) 15 (63) 19 (91) 14 (64) 48 (72)

Caucasian 5 (33) 7 (29) 0 (0) 6 (27) 13 (19)

Hispanic/Latino 4 (27) 2 (8) 2 (10) 2 (9) 6 (9)

Black 6 (40) 15 (63) 19 (91) 14 (64) 48 (72)

Non-black 9 (60) 9 (68) 2 (10) 8 (36) 19 (28)

Marital statusa

Single/never married 9 (60) 15 (63) 15 (71) 17 (77) 47 (70)

Married 2 (13) 6 (25) 4 (19) 1 (5) 11 (16)

23 Table 1 (continued)

Divorced 3 (20) 3 (13) 1 (5) 2 (9) 6 (9)

Engaged 0 (0) 0 (0) 1 (5) 1 (5) 2 (3)

Widower 1 (7) 0 (0) 0 (0) 1 (5) 1 (2)

Married 2 (13) 6 (25) 4 (19) 1 (5) 11 (16)

Non-married 13 (87) 18 (75) 17 (81) 21 (96) 56 (84)

Education levelabc

Some high school 3 (21) 8 (35) 3 (15) 1 (5) 12 (19)

Finished high school/GED 5 (36) 13 (57) 14 (70) 15 (68) 42 (65)

Some college 4 (29) 2 (9) 2 (10) 5 (23) 9 (14)

Associate’s degree 1 (7) 0 (0) 1 (5) 0 (0) 1 (2)

Bachelor’s degree 1 (7) 0 (0) 0 (0) 1 (5) 1 (2)

No high school diploma/GED 3 (21) 8 (35) 3 (15) 1 (5) 12 (19)

24 Table 1 (continued)

At least a high school diploma/ GED

11 (79) 15 (65) 17 (85) 21 (96) 53 (82)

Most serious index offense (by degree)a

Violent 0 (0) 1 (4) 0 (0) 1 (5) 2 (3)

Robbery 2 (13) 3 (13) 0 (0) 2 (9) 5 (8)

Property 2 (13) 1 (4) 4 (19) 3 (14) 8 (12)

Drugs/alcohol 4 (27) 12 (50) 10 (48) 10 (50) 32 (48)

Firearms-related 5 (33) 1 (4) 4 (19) 4 (18) 9 (13)

Violation of supervision 1 (7) 2 (8) 1 (5) 1 (5) 4 (6)

Other 1 (7) 4 (17) 2 (10) 1 (5) 7 (10)

Primary substance-related 4 (27) 12 (50) 10 (48) 10 (46) 32 (48)

Not primarily substance-related 11 (73) 12 (50) 11 (52) 12 (55) 35 (52)

25 Table 1 (continued)

Violation of community supervision

No 8 (53) 15 (63) 16 (76) 16 (73) 47 (70)

Yes 7 (47) 9 (38) 5 (24) 6 (27) 20 (30)

Minimum sentence length (in months) 28 (14) 53 (47) 39 (21) 46 (32) 46 (36)

Maximum or determinate sentence (in months) 47 (19) 89 (81) 77 (46) 78 (46) 81 (60)

LS/CMI General Risk/Need score 19 (9) 21 (5) 20 (5) 22 (4) 21 (5)

LS/CMI General Risk/Need levelabd

Low 4 (27) 0 (0) 1 (5) 0 (0) 1 (2)

Medium 3 (20) 8 (33) 9 (43) 8 (36) 25 (37)

High 6 (40) 14 (58) 11 (52) 13 (59) 38 (57)

Very High 2 (13) 2 (8) 0 (0) 1 (5) 3 (5)

26 Table 1 (continued)

< High 8 (53) 8 (33) 10 (48) 8 (36) 26 (39)

≥ High 7 (47) 16 (67) 11 (52) 14 (64) 41 (61)

Note. Means are reported for continuous variables, accompanied by standard deviations in parentheses; for categorical variables, frequency counts are reported, with within-group percentages in parentheses. Significant differences (p < .05, non-corrected) are indicated in boldface. Levels of variables that had no cases (e.g., some levels of the race variable) have been omitted from this table. aSmall expected cell sizes (< 5) necessitated that the variable be collapsed into a dichotomous form, and the two feedback conditions be collapsed into one, for significance testing. bPercentages may not add up to 100% due to rounding. cVariable was not available for all cases. dThere were no Very Low risk cases.

27 One-way ANOVAs and chi-square tests for independence were used to test for

significant demographic differences between study completers and non-completers, and

among the three study conditions. Results indicated that there were few significant

differences on demographic variables. Compared to participants who dropped out, study

completers were significantly more likely to be Black (72% vs. 40%) and to have longer

maximum or fixed sentences (M = 81 months vs. 47 months). Among study conditions,

control participants were significantly less likely to have graduated high school or

obtained a GED than were participants in the discussion-based feedback condition (65%

vs. 93%). But participants in each study condition were substantially similar to one

another overall, as well as to study non-completers, evidencing success of the random

selection and assignment procedures. Study participants were, on average, in their mid-

30s, and they were predominantly Black and single. A majority of them had graduated

high school or earned a GED. Participants were serving sentences for a variety of

offenses, most typically drug-related, and they were high risk on average.

Measures

Level of Service/Case Management Inventory (LS/CMI). The LS/CMI

(Andrews, Bonta, & Wormith, 2004) is a member of the LS family of risk/need

assessment tools, which are widely used risk/need instruments (Andrews, Bonta, &

Wormith, 2010). Consistent with the hallmarks of a good forensic measure (Heilbrun,

Rogers, & Otto, 2003), the measure has demonstrated good psychometric properties (see

Andrews, Bonta, & Wormith, 2010, for a review); it is available for commercial

purchase; and it comes with a detailed manual that covers administration, scoring,

interpretation, and supporting research. Section 1 (General Risk/Need) of the LS/CMI

28 was utilized for the present study; it consists of 43 items grouped pursuant to the Central

Eight risk factor domains. The items are combined in an actuarial manner to predict

general recidivism by assigning an individual to one of five risk bins (Very Low: 0–4;

Low: 5–10; Medium: 11–19; High: 20–29; and Very High: 30+). Each risk level has a

probabilistic point-estimate associated with it for the criterion of reincarceration within

one year.

University of Rhode Island Change Assessment (URICA). The URICA

(Appendix A; McConnaughy, DiClemente, Prochaska, & Velicer, 1989; McConnaughy,

Prochaska, & Velicer, 1983) is a 34-item self-report questionnaire designed to assess a

respondent’s stage of change (based on the transtheoretical model). It is the most widely

used and researched stage of change measure across settings and problem behaviors

(Casey et al., 2005; Polaschek et al., 2010), including motivation to change criminal

behavior (Campbell, Sellen, & McMurran, 2010; McMurran et al., 2011). However,

research on the URICA’s applicability to offending and related behaviors is limited. The

few studies that examined the psychometric properties of the measure with offender

samples produced mixed findings regarding its component/factor structure and cluster

profiles (see Polaschek et al., 2010, for a review). Nevertheless, the weight of available

evidence preliminarily suggests that the URICA is acceptably reliable and valid for

assessing stage of change for offending behavior.

Examinees are unlikely to endorse items from only a single stage of change, and

so interpretation of URICA responses sometimes proceeds via comparison to stage of

change profiles derived from principal components analysis and cluster analysis

(McConnaughy et al., 1983, 1989; Polaschek et al., 2010). Others have used the highest

29 subscale score to assign a single stage of change (e.g., Ronan, Gerhart, Bannister, &

Udell, 2010). Researchers have also employed a continuous scoring method that entails

subtracting the total score on the Precontemplation subscale from the sum of the

Contemplation, Action, and Maintenance subscales, based on the assumption that people

in later stages of change will endorse fewer Precontemplation items (e.g., Polaschek et

al., 2010). This was the method used for the present study, selected on the basis of the

promising results it has yielded with offender samples (e.g., Polaschek et al., 2010;

Appendix H). The minimum possible score via this method is 2 and the maximum is 14.

Much of the language in the directions was taken from the sample directions at

http://www.uri.edu/research/cprc/Measures/urica.htm; a clarification that the problem of

interest was offending behavior was also included.

Corrections Victoria Treatment Readiness Questionnaire (CVTRQ). The

CVTRQ (Casey, Day, Howells, & Ward, 2007; Day, Casey, Ward, Howells, & Vess,

2010) is a self-report questionnaire designed to measure the construct of offender

readiness for correctional treatment (based on the multifactor offender readiness model).

Individual CVTRQ items map onto four subscales that were derived via principal

components analysis: Attitudes and Motivation, Emotional Reactions, Offending Beliefs,

and Efficacy. Responses are made on a five-point Likert scale, and some items are

reversed scored. The minimum possible score is 20 and the maximum is 100. Higher

scores on the measure suggest increased readiness to participate in and benefit from

treatment. In their initial examination of the psychometric properties of the CVTRQ,

Casey et al. (2007) reported promising levels of discriminant and convergent validity, and

30 of predictive validity for treatment engagement. The authors are offered a tentative

recommended cutoff score of 72 as indicative of treatment readiness.

CVTRQ items found to be redundant or uninformative via factor analysis in an

original 40-item version were excluded in a reformulated 20-item measure (A. Day,

personal communication, January 18, 2012). Slight word substitutions were also made to

questions on the abbreviated measure to tailor it for use with violent offenders (the

Violence Treatment Readiness Questionnaire (VTRQ); Day et al., 2009). The VTRQ

evidenced comparable psychometric properties to the original CVTRQ (Day et al., 2009).

The current version of the CVTRQ was verified by the author to consist of the same 20

items as the VTRQ (a copy of the latter is provided in the appendix of Day et al. (2009)),

but with some instances of variations of the word “offend” replaced with variations of the

word “violence” (A. Day, personal communication, January 19, 2012). This shortened

version of the CVTRQ was used in the present study (Day et al., 2010; Appendix B). For

consistency’s sake, the included directions were similar to the directions provided for the

URICA, with slight alterations as appropriate. These directions differ somewhat from the

directions provided in Day et al. (2010).

Risk Need Perception Survey (RNPS). Brooks-Holliday (2012) developed the

RNPS to measure offenders’ endorsement of risks factors for others and themselves. A

slightly updated and exclusively self-referential version of the RNPS (i.e., that asks all

questions in relation to the self rather than for others) was used for the present study

(Appendix C). Also, based on common questions from participants about the RNPS

directions and response options, slight adjustments were made to the directions and

response options on two occasions during the course of the study (first version: n = 2;

31 second version: n = 73; third version: n = 7).4 Each version is reproduced in Appendix C.

Participants who completed earlier iterations of the measure were given verbal

clarifications—consistent with the adjustments that were later made—if they had

questions about either the directions or response options. Three of the four primary RNPS

results (concordance with LS/CMI results, number of Central Eight risk factors endorsed

as problem areas, and categorically self-assessed risk of reoffending) did not significantly

differ among the three versions of the measure. The RNPS item pertaining to

probabilistically self-appraised risk did significantly differ among the three versions (ps =

.03 for baseline and follow-up), but given the high variability that was observed of the

item, and the small number of participants who completed versions 1 and 3 of the RNPS,

this difference was not interpreted as meaningful.5

The RNPS presents a listing of 30 items: the Central Eight risk factors, weaker

covariates of recidivism and other factors denoted as responsivity factors (e.g.,

psychopathology; race/ethnicity), and factors with no known relationship to reoffending

(e.g., sexual ability and athleticism). Some risk factors are measured via a single item

(e.g., criminal history) whereas others constitute an index of related items (e.g., antisocial

pattern). Using a three-point Likert scale, participants are asked to indicate whether each

factor could make them more likely to reoffend if not changed: 1 = No (Not problem); 2

= Somewhat (Medium problem); 3 = Yes (Major problem). Two questions about

participants’ self-assessed likelihood of reoffending were also appended to the RNPS for

4 Version 1: control (n = 0), form-based feedback (n = 1), discussion-based feedback (n = 1); Version 2: control (n = 25), form-based feedback (n = 25), discussion-based feedback (n = 23); Version 3: control (n = 2), form-based feedback (n = 1), discussion-based feedback (n = 4). 5 Baseline: version 1 (M = 80, SD = 28), version 2: (M = 51, SD = 37), version 3 (M = 88, SD = 21); Follow-up: version 1 (M = 90, SD = 14), version 2: (M = 57, SD = 34), version 3 (M = 89, SD = 16).

32 the present study: “How likely do you think it is that you’ll reoffend if you don’t

change?” (1 = Not at all; 2 = Slightly; 3 = About 50/50; 4 = More likely than not; 5 =

Definitely); and “What probability out of 100% would you say your chance of

reoffending is if you don’t change?” (0–100%).

The RNPS was scored in reference to participants’ Section 1 LS/CMI results

(Appendix G). If a participant’s risk level for a Central Eight risk factor was Very Low or

Low on the LS/CMI, a concordance point was assigned if the participant endorsed the

corresponding risk factor as No (Not problem) or Somewhat (Medium Problem) on the

RNPS. If an LS/CMI risk factor score fell within the Medium risk range, then a RNPS

response of Somewhat (Medium Problem) or Yes (Major Problem) was assigned a

concordance point. Finally, if a risk factor score on the LS/CMI was within the High or

Very High risk categories, only an endorsement of Yes (Major Problem) by a participant

on the RNPS was assigned a concordance point. This method—(1) collapsing the five

LS/CMI risk levels into three and (2) allowing for participants to endorse slightly higher

risk for a factor while still be considered in concordance with the corresponding LS/CMI

result—yielded a total concordance score ranging from 1 to 8 for each participant.

Feedback Helpfulness Survey (FHS). The six-question FHS was developed for

the present study to measure how helpful participants found the feedback (Appendix D).

Response choices for each item were as follows: Strongly Disagree = 1; Slightly Disagree

= 2; Slightly Agree = 3; and Strongly Agree = 4. Participants were thus forced to select at

least a slightly directional response. The minimum possible score for the questionnaire is

6; the maximum is 24.

33 Procedure

During the initial solicitation, informed consent, and random assignment contact,

all participants who consented to participate were administered the URICA, CVTRQ, and

RNPS. The order in which measures were presented was counterbalanced, both here and

at follow-up administration. Participants in all groups then received treatment as usual at

the facility (milieu-based rational emotive behavior therapy and specialty programming),

which included an assessment conducted by a master’s-level company assessment

counselor within the first few weeks of the participants’ intake to the facility. The

LS/CMI is included in the standard assessment battery used by facility assessment

counselors and is scored on the basis of file information, resident interview, and

psychological testing. Participants who had been administered the LS/CMI by company

staff within two years of their assessment date (e.g., if they had recently been through the

study site or a similar facility) were typically not readministered the LS/CMI; for these

participants, their most recently recorded LS/CMI results were used for the purposes of

the study.

Within approximately a month of a participant’s LS/CMI results being recorded

by facility staff,6 experimental participants were provided with either discussion-based

feedback (typically lasting approximately one-and-a-half hours) or form-based feedback

(typically lasting approximately a half-hour). Both forms of feedback were developed

using principles derived from writings about therapeutic assessment (Finn, 2007; Poston

6 For experimental participants who had new LS/CMI results entered during the study period (n = 24), the average amount of time between LS/CMI entry date and the first or only feedback date was 16 days, with a standard deviation of 9 days and a range of 1 to 32 days. For all experimental participants (n = 43), the gap between LS/CMI entry date and feedback averaged 101 days, with a standard deviation of 133 days and a range of 1 to 645.

34 & Hanson, 2010; Weiner & Greene, 2008), therapeutic alliance (Ross, Polaschek, &

Ward, 2008), and motivation interviewing (Andrews & Bonta, 2010a, pp. 289–291;

Anstiss et al., 2011; McCrady, 2008). So as not to overwhelm recipients with too much

information at once, and because of time constraints posed by mandatory facility counts

and movements, discussion-based feedback was sometimes split over two sessions. All

feedback was delivered one-on-one. The guiding principles for the feedback, a scripted

curriculum, and the two feedback forms that were used with participants are provided in

Appendices C and D.

The primary content that was conveyed during feedback pertained to participant’s

LS/CMI risk and needs results and corresponding treatment targets (the latter derived

from Andrews and Bonta (2010a, pp. 58–60, 500)). This content was conveyed to all

feedback participants via two standardized forms. The author was present during each

type of feedback session, and participants in both experimental conditions were

encouraged to ask questions, bring up results or concepts with which they disagreed, and

opine on how the feedback was or was not consistent with their experiences, all for

discussion. The primary difference between the discussion-based and form-based

feedback was the depth of explanation of general information about risk, needs, and

treatment; the amount of discussion of a participant’s prior experiences with reoffending

and his plans for reentry; and the extent of discussion afforded to how assessment results

might inform a participant’s release plans.

During feedback, participants were provided with somewhat different estimates of

risk than those yielded by the LS/CMI (1, 6, 28, 45, and 61%; Andrews et al., 2004, p.

36); they were instead presented with approximately five-year reconviction base rates

35 from a retrospective validation study of the LS/CMI with 441 female inmates and

probationers in Canada (4, 15, 44, 80, 100%; Rettinger, 1998, as cited in Andrews et al.,

2004, p. 120). The decision to use recidivism rates observed among Canadian female

offenders with male participants located in the United States was made for two reasons.

First, the Rettinger (1998) study is the only study in the LS/CMI manual for which (1)

actual (versus estimated) recidivism rates are reported, (2) that are broken down by

LS/CMI risk level, and (3) that form a distribution of observed recidivism rates that is

completely positively linear, consistent with the distribution of LS/CMI absolute risk

estimates (Andrews et al., 2004; K. M. Williams, personal communication, April 17,

20127). It was decided that presenting the simplest indicia of the risk–reoffense

relationship—i.e., observed recidivism rates for each risk level—was preferable to

misleadingly presenting LS/CMI absolute risk estimates as observed recidivism rates, or

having to try and explain the concept of predicted recidivism rates. Second, with some

qualifications about gender responsive risk assessment (Rettinger & Andrews, 2010; van

der Knaap, Alberda, Oosterveld, & Born, 2012; Van Voorhis, Wright, Salisbury, &

Bauman, 2010) and the difference between estimated and observed recidivism rates

(Helmus, Hanson, Thornton, Babchishin, & Harris, 2012), current evidence suggests that

the LS instruments operate comparably for males and females (Olver, Stockdale,

Wormith, 2014; Vitopolos, Peterson-Badali, & Skilling, 2012), and that both genders

7 Dr. Williams, Senior Research Associate, Public Safety Division, Multi-Health Systems, Inc., provided the following in response to my inquiry regarding the availability of observed recidivism rates for the LS/CMI’s U.S. incarcerated normative sample:

I contacted the LS/CMI authors to inquire about your question re: recidivism rates in the LS/CMI U.S. incarcerated sample. Unfortunately these data are unavailable; recidivism data is generally much easier and relevant to collect in probationary samples. 'Recidivism' for incarcerated samples is generally defined as institutional misconduct. All information relating to recidivism is presented or referenced in the manual. We are currently updating the LS/CMI and plan to collect recidivism data for the update.

36 exhibits similar recidivism rates at higher levels of risk (Andrews et al., 2012). Thus,

although participants were presented with recidivism rates higher than those estimated by

the LS/CMI (which defines recidivism as reincarceration within one-year), it was

reasonable to assume that had the LS/CMI normative sample’s follow-up period been

extended to five years, the observed recidivism rates, at least at higher risk levels, would

have roughly approximated those reported by Rettinger (1998).

After receipt of feedback, half of the experimental participants were immediately

readministered the URICA, CVTRQ, RNPS, and administered the FHS (n = 24).8 To

allow for an examination of possible immediacy effects of feedback on outcomes, the

other half of feedback participants waited approximately one week (M = 8 days, SD = 4

days, range = 7–21 days) to fill out theses measures (n = 19). Control participants

completed second administrations of the URICA, CVTRQ, and RNPS along

approximately the same schedule,9 and were then either directed to treatment staff for

feedback or given brief feedback by the author. The author solicited all potential

participants, administered all study measures except the LS/CMI, conducted all feedback

sessions, and scored all measures besides the LS/CMI. Two undergraduate research

assistants separately entered the data into two electronic data sets. The author then

merged the double-entered data and resolved any discrepancies by referring back to paper

materials.

8 One of these participants actually completed follow-up measures after a two-day lag rather than immediately. 9 Descriptive statistics for the time in days between baseline and follow-up measurement among the three study conditions are as follows: control group (M = 34, SD = 9, range = 21–49), form-based group (M = 39, SD = 12, range = 13–56), and discussion-based group (M = 41, SD = 13, range = 7–56).

37 The study used a 3 × 2 mixed factorial design (i.e., a pre-post-control design).

Participants were randomly assigned to one of three groups: discussion-based feedback,

form-based feedback, or no feedback. Outcome measures were administered at baseline

and after the receipt of feedback (or after a similarly spaced interval for control

participants). An opinion questionnaire about the feedback was administered at follow-up

only. There were five sets of hypotheses.

1. It was hypothesized that participants in both feedback conditions would

evidence significantly higher risk concordance scores following the provision of feedback

compared to baseline. It was also hypothesized that feedback recipients’ risk concordance

scores would be significantly higher than control participants’ at follow-up. In addition, it

was hypothesized that discussion-based feedback participants would show the largest

within- and between-group effect sizes. A mixed two-way analysis of variance was used

to test these related hypotheses, along with partial eta squared, ηp2, as the measure of

effect size. Post-hoc contrasts (independent samples t-tests and paired samples t-tests, as

well as Cohen’s d as the effect size measure) were to be conducted if warranted.

2. It was hypothesized that participants in both feedback conditions would

evidence significantly higher need concordance scores following the provision of

feedback compared to baseline. It was also hypothesized that feedback recipients’ need

concordance scores would be significantly higher than control participants’ at follow-up.

In addition, it was hypothesized that discussion-based feedback participants would show

the largest within- and between-group effect sizes. A mixed two-way analysis of variance

was used to test these related hypotheses, along with partial eta squared, ηp2, as the

measure of effect size. Post-hoc contrasts (independent samples t-tests and paired

38 samples t-tests, as well as Cohen’s d as the effect size measure) were to be conducted if

warranted.

3. It was hypothesized that participants in both feedback conditions would

evidence significantly higher motivation for change scores following the provision of

feedback compared to baseline. It was also hypothesized that feedback recipients’

motivation for change scores would be significantly higher than control participants’ at

follow-up. In addition, it was hypothesized that discussion-based feedback participants

would show the largest within- and between-group effect sizes. A mixed two-way

analysis of variance was used to test these related hypotheses, along with partial eta

squared, ηp2, as the measure of effect size. Post-hoc contrasts were also conducted,

consisting of independent samples t-tests and paired samples t-tests, along with Cohen’s

d as the measure of effect size.

4. It was hypothesized that participants in both feedback conditions would

evidence significantly higher treatment readiness scores following the provision of

feedback compared to baseline. It was also hypothesized that feedback recipients’

treatment readiness scores would be significantly higher than control participants’ at

follow-up. In addition, it was hypothesized that discussion-based feedback participants

would show the largest within- and between-group effect sizes. A mixed two-way

analysis of variance was used to test these related hypotheses, along with partial eta

squared, ηp2, as the measure of effect size. Post-hoc contrasts were also conducted,

consisting of independent samples t-tests and paired samples t-tests, along with Cohen’s

d as the measure of effect size.

39 5. It was hypothesized that feedback recipients would rate the feedback

significantly higher (i.e., more favorably) than the midpoint of the six-item feedback

helpfulness questionnaire, with the effect size being larger for the discussion-based

feedback condition. To test this hypothesis, data was analyzed using one-sample t-tests;

Cohen’s d was used as the measure of the magnitude of effect.

40 Chapter 3: Results

Table 2 provides descriptive statistics for each study measure at baseline and

follow-up, and Figures 1–4 depict this information visually. Beginning with

probabilistically self-appraised risk of reoffending, ascertained using the RNPS, there

were no significant differences for time, Wilks’ Λ = .98, F (1, 64) = 1.45, p = .23, ηp2 =

.02; condition, F (2, 64) = 0.89, p = .42, ηp2 = .03; or time × condition, Wilks’ Λ = .99, F

(2, 64) = 0.29, p = .75, ηp2 = .01. The same was true for self-assessed risk using a

categorical scale: time, Wilks’ Λ = .97, F (1, 63) = 2.01, p = .16, ηp2 = .03; condition, F

(2, 63) = 0.09, p = .91, ηp2 = ; time × condition, Wilks’ Λ = .99, F (2, 63) = 0.27, p = .76,

ηp2 < .01. As for the concordance between participant-perceived risk of reoffending

(RNPS) and the recidivism rates participants were presented with during feedback (from

Rettinger (1998))—i.e., normative recidivism rate minus self-appraised probability of

reoffending—no significant differences were found for time, Wilks’ Λ = .98, F (1, 64) =

1.45, p = .23, ηp2 = .02; condition, F (2, 64) = 0.33, p = .72, ηp

2 = .01; or time ×

condition, Wilks’ Λ = .99, F (2, 64) = 0.29, p = .75, ηp2 = .01. The same pattern was

observed using the LS/CMI’s actuarial risk estimates, which participants were not

presented with; time, Wilks’ Λ = .98, F (1, 64) = 1.45, p = .23, ηp2 = .02; condition, F (2,

64) = 0.50, p = .61, ηp2 = .02; time × condition, Wilks’ Λ = .99, F (2, 64) = 0.29, p = .75,

ηp2 = .01.

A similar pattern of results was observed for the concordance between

participant-reported (RNPS) and evaluator-indicated (LS/CMI) criminogenic needs. No

significant interaction effect was observed between condition and time, Wilks’ Λ = .99, F

(2, 64) = 0.46, p = .63, ηp2 = .01; nor were significant main effects seen for time, Wilks’

41 Λ = 1.00, F (1, 64) = 0.02, p = .88, ηp

2 < .01, or condition, F (2, 64) = 0.02, p = .97, ηp2 <

.01. Together, these results suggested that neither form-based nor discussion-based

assessment feedback had an impact on risk or needs self-perceptions over time or in

comparison to control.

42 Table 2

Means, Standard Deviations, and 95% Confidence Intervals for Study Measures at Baseline and Follow-up

Condition

Control Form-based Discussion-based

Measure Baseline Follow-up Baseline Follow-up Baseline Follow-up

Self-reported risk % 53.96 (38.28) [37.80, 70.12]

63.92 (35.89) [48.76, 79.07]

51.67 (35.01) [35.73, 67.60]

53.33 (32.11) [38.72, 67.95]

62.45 (38.87) [45.22, 79.69]

67.27 (32.80) [52.73, 81.81]

Self-reported risk levelab

3.13 (1.33) [2.56, 3.69]

3.29 (1.37) [2.71, 3.87]

3.00 (1.41) [2.36, 3.64]

3.14 (1.39) [2.51, 3.77]

3.00 (1.64) [2.25, 3.75]

3.32 (1.49) [2.66, 3.98]

RNPS–Rettinger risk concordance

15.71 (42.62) [-2.29, 33.71]

5.75 (35.10) [-9.07, 20.57]

9.81 (40.06) [-8.43, 28.05]

8.14 (38.84) [-9.54, 25.82]

5.36 (42.49) [-13.47, 24.20]

0.55 (29.66) [-12.60, 13.70]

RNPS–LS/CMI risk concordance

-13.29 (39.52) [-29.98, 3.40]

-23.25 (33.87) [-37.55, -8.95]

-15.81 (35.83) [-32.12, 0.50]

-17.48 (34.57) [-33.22, -1.73]

-22.91 (40.13) [-40.70, -5.12]

-27.73 (29.75) [-40.92, -14.54]

RNPS–LS/CMI needs concordance

4.29 (1.16) [3.80, 4.78]

4.33 (1.34) [3.77, 4.90]

4.48 (1.66) [3.72, 5.23]

4.29 (1.93) [3.41, 5.16]

4.27 (1.28) [3.71, 4.84]

4.50 (1.44) [3.86, 5.14]

URICA 9.27 (1.59) [8.60, 9.94]

9.15 (1.63) [8.46, 9.84]

9.14 (1.87) [8.29, 9.99]

8.93 (2.46) [7.81, 10.05]

9.32 (1.35) [8.72, 9.92]

10.56 (1.72) [9.79, 11.32]

43 Table 2 (continued)

CVTRQ 75.67 (9.45) [71.68, 79.66]

76.88 (7.62) [73.66, 80.09]

76.90 (8.12) [73.21, 80.60]

78.48 (8.04) [74.82, 82.13]

77.95 (8.87) [74.02, 81.89]

83.64 (9.03) [79.63, 87.64]

FHSc -- 19.52 (3.49) [17.94, 21.11]

21.05 (2.98) [19.72, 22.37]

Note. Means are reported along with standard deviations in parentheses and 95% confidence intervals in brackets. URICA = University of Rhode Island Change Assessment; CVTRQ = Corrections Victoria Treatment Readiness Questionnaire; RNPS–Rettinger risk concordance = concordance score between the Risk Need Perception Survey and recidivism rates reported in Rettinger (1998); RNPS–LS/CMI risk concordance = concordance risk score between the Risk Need Perception Survey and Level of Service/Case Management Inventory; RNPS–LS/CMI needs concordance = concordance need score between the Risk Need Perception Survey and Level of Service/Case Management Inventory. Self-reported risk % = RNPS question about the likelihood of committing a new crime absent personal change, on a 0–100% scale; Self-reported risk level = Same RNPS item as the immediately foregoing but asked using a 1–5 Likert scale; FHS = Feedback Helpfulness Survey. aThe five response options were as follows: 1 = Not at all, 2 = Slightly, 3 = About 50/50, 4 = More likely than not, and 5 = Definitely. bVariable was missing for one discussion-based feedback participant at baseline. cAdministered at follow-up and to feedback participants only.

44

Figure 1. Bar graph of average Risk Need Perception Survey and Level of Service/Case Management Inventory need concordance scores. Error bars represent 95% confidence intervals. Turning next to URICA total scores, there were no main effects for time, Wilks’

Λ = .97, F (1, 64) = 2.26, p = .14, ηp2 = .03; or condition, F (2, 64) = 1.97, p = .15, ηp

2 =

.06; but there was a significant time*condition interaction effect, Wilks’ Λ = .86, F (2,

64) = 5.39, p = .007; ηp2 = .14. As can be seen in Table 2 and Figure 2, the discussion-

based feedback condition uniquely evidenced an increase in URICA scores following

45 receipt of feedback. This effect can be interpreted as the proportion of the total variability

of URICA total scores attributable to study condition as a function of time (14%), or

stated otherwise, that the effect for group differences over time accounted for 14% of the

group-by-time differences and associated error variance. More intuitively, at follow-up

(i.e., after feedback receipt), the standardized mean difference (d) of URICA total scores

between the discussion-based feedback and control conditions was 0.84, t (44) = −2.85, p

= .007, two-tailed, mean difference = −1.41, 95% CI [−2.40, −0.41], whereas it was 0.76

between the discussion-based versus form-based feedback conditions, t (41) = −2.52, p =

0.16, two-tailed, mean difference = −1.62, 95% CI [−2.93, −0.32]. That is, the average

discussion-based feedback participant’s URICA total score at follow-up was

approximately four-fifths of a standard deviation higher than the average participant in

the control condition. The URICA total score for the average participant in the

discussion-based feedback condition at follow-up was also approximately three-fourths

of a standard deviation larger than the average participant’s in the form-based feedback

condition. Relevant to the latter comparison, form-based feedback recipients actually

showed a slight decrease in self-reported motivation at follow-up, although this effect

was not significant.

46

Figure 2. Bar graph of average University of Rhode Island Change Assessment total scores. Error bars represent 95% confidence intervals. The dashed lines denote the thresholds for different stages of change: 2–8 = Precontemplator, 8.5–11 = Contemplator, and 11.5–14 = Preparator into Action Taker. For CVTRQ total scores, there was no significant main effect for condition, F (2,

64) = 2.01, p = .13, ηp2 = .06; nor significant time × condition interaction, Wilks’ Λ = .93,

F (2, 64) = 2.31, p = .11, ηp2 = .07. However, the main effect for time was significant,

Wilks’ Λ = .88, F (1, 64) = 8.90, p = .004, ηp2 = .12. As can be seen in Table 2 and Figure

3, CVTRQ scores increased between baseline and follow-up for each condition. In

47 contrast to the omnibus test, post-hoc between-group analyses at follow-up (using a

Bonferroni corrected alpha of .01 based on the 2 between-groups and 3 within-groups

post-hoc tests that were performed) revealed a significant difference between the

discussion-based feedback condition and control condition, t (44) = −2.75, p = .009, two-

tailed, mean difference = −6.76, 95% CI [−11.71, −1.81], d = 0.81. The difference

between the discussion-based and form-based feedback conditions only approached

significance prior to a Bonferroni correction, t (41) = −1.98, p = .055, two-tailed, mean

difference = −5.16, 95% CI [−10.43, 0.11], d = 0.60. A significant difference was not

detected between the form-based feedback condition and control condition at follow-up, t

(43) = −.69, p = .50, two-tailed, mean difference = −1.60, 95% CI [−6.31, 3.11], d =

−0.20. In addition to between-group differences, only the discussion-based feedback

condition showed a significant within-group difference, t (21) = −3.32, p = .003, two-

tailed, mean difference = −5.68, 95% CI [−9.24, −2.13], d = 0.71 (calculated with r = .60

in G*Power 3.1.9.2).

A post-hoc power analysis (using an ηp2 for the main effect of condition, .12,

converted to an f of 0.369, an ηp2 of .067 converted to an f of 0.267 for the time ×

condition interaction, and the correlation between repeated measures for the entire sample

of .59) indicated that the mixed ANOVA was sufficiently powered to detect both the

main effect of condition (1−β = .99) and the interaction term (1−β = .99). There are at

least two possibilities for the discrepant results obtained using the omnibus test and post-

hoc contrasts. First, the ordinal nature of the results (see Figure 3) may have obscured the

superiority of the discussion-based feedback condition in terms of the magnitude of the

increase in average CVTRQ total score between baseline and follow-up, and in

48 comparison to the average CVTRQ total score of control participants at follow-up.

Second, the smaller differences (at baseline and follow-up) between the discussion-based

feedback condition and the form-based feedback condition relative to the discussion-

based feedback condition versus the control condition may have further obscured these

effects.

Figure 3. Bar graph of average Corrections Victoria Treatment Readiness Questionnaire total scores. Error bars represent 95% confidence intervals. The dashed line denotes the readiness cutoff score (72) suggested by Casey et al. (2007).

49 Figure 4 displays FHS results and Table 3 reports descriptive statistics for

each of the measure’s six questions. Participants in both feedback conditions rated

feedback favorably; out of a total possible score of 24 on the FHS (and a

minimum score of 6), form-based feedback participants obtained an average score

of 19.52 (SD = 3.49, 95% CI [17.94, 21.11]) and discussion-based feedback

participants averaged a score of 21.05 (SD = 2.98, 95% CI [19.72, 22.37]). FHS

scores did not significantly differ between feedback conditions (t (41) = −1.54, p

= .13, two-tailed, mean difference = −1.52, d = 0.47). The average FHS score for

each feedback condition (see Table 2) was significantly higher than the mid-point

of the measure (15), and these effects were large by Cohen’s (1992) standards;

form-based: t (20) = 5.94, p < .001, two-tailed, mean difference = 4.52, 95% CI

[2.94, 6.11], d = 1.30; discussion-based: t (21) = 9.50, p < .001, two-tailed, mean

difference = 6.05, 95% CI [4.72, 7.37], d = 2.03; feedback conditions combined:

M = 20.30, SD = 3.29, t (42) = 10.56, p < .001, two-tailed, mean difference =

5.30, 95% CI [4.29, 6.32], d = 1.61.

50

Figure 4. Bar graph of average Feedback Helpfulness Survey scores, compared to the mid-point of the measure (the minimum possible score being 6). Error bars represent 95% confidence intervals.

51 Table 3

Means, Standard Deviations, and 95% Confidence Intervals for FHS Items Condition

Form-based Discussion-based

Item M SD 95% CI M SD 95% CI

1. I agree with the feedback. 3.24 0.83 [2.86, 3.62] 3.68 0.57 [3.43, 3.93]

2. I found the feedback helpful. 3.57 0.75 [3.23, 3.91] 3.77 0.43 [3.58, 3.96]

3. The feedback told me things about myself that I did not already know.

2.33 0.86 [1.94, 2.72]

2.73 0.94 [2.31, 3.14]

4. Because of the feedback, I now have a better understanding of the issues that might make me more likely to commit a crime.

3.33 0.80 [2.97, 3.70]

3.45 0.86 [3.07, 3.83]

5. Because of the feedback, I now have a better understanding of the things I need to work on in treatment.

3.52 0.81 [3.15, 3.89]

3.59 0.73 [3.27, 3.92]

6. I think the feedback would be helpful for other people who are in jail or prison for committing crimes.

3.67 0.73 [3.33, 4.00]

3.82 0.40 [3.64, 3.99]

Note. Each item had the same four response options: 1 = Strongly Disagree, 2 = Slightly Disagree, 3 = Slightly Agree, and 4 = Strongly Agree. Study results did not significantly differ for immediate versus lagged follow-up

measurement among feedback recipients. These analyses are therefore omitted. However,

there was a trend (p = .08 with equal variances not assumed) suggestive of higher

CVTRQ scores among feedback recipients who immediately completed follow-up

52 measures (immediate: M = 83.42, SD = 5.92 vs. delayed: M = 78.21, SD = 11.04, with a

corresponding d of 0.59).

53 Chapter 4: Discussion

The results of this study supported some of the hypotheses and failed to support

others. The first hypothesis—that feedback recipients would show significantly greater

risk concordance post-feedback, compared both to baseline measurement as well as the

control condition at follow-up—was not supported. Using the RNPS and LS/CMI, mixed

ANOVAs indicated no significant differences within or between study conditions for (1)

self-assessed risk, (2) concordance between self-assessed risk and the recidivism rates

reported by Rettinger (1998), and (3) concordance between self-assessed risk and the

recidivism estimates provided in the LS/CMI manual. Categorical measurement of self-

appraised risk yielded comparable results to measurement using a continuous scale,

suggesting that self-perceptions of reoffense risk are robust to variation of response

options. On average, participants across study conditions calculated that their odds of

reoffending were about even or slightly worse if they did not make changes in their lives.

This was true both before and after assessment feedback, which included presentation of

recidivism rates. Thus, the modal offender appeared to appreciate on his own that he was

at serious risk for recidivism absent personal change, with feedback slightly elevating his

self-perceived risk. There was a large amount of variability between participants,

however, with standard deviations ranging from approximately 30 to 40%. This suggests

that individuals differ in their self-perceived risk, which in turn suggests that personalized

assessment of risk self-perceptions and corresponding cognitive interventions may have

some utility in offender rehabilitation.

The finding that offenders tended to perceive their risk of reoffending as relatively

high differs from the more optimistic self-appraisals previously reported with offender

54 samples (Cobbina & Bender, 2012; Friestad & Hansen, 2010; Souza et al., 2013). One

potential explanation for this discrepancy is that the current sample was comprised of

higher-risk offenders who, in turn, had more experience with prior recidivism. Another is

the fact that we leadingly asked about self-appraised recidivism risk “if you don’t

change,” which may have measured the extent to which offenders believed that personal

change was necessary to avoid reoffending, rather than how likely they thought they were

to make such changes, and in turn, to reoffend or not. This may parallel the prior finding

in the literature (Kivivuori & Linderborg, 2010) that offenders’ self-assessed likelihood

of post-release reoffending varied by the type of crime considered (e.g., burglary and

shoplifting versus substance use and assault). The phrasing of questions about self-

predicted recidivism might matter.

The second hypothesis paralleled the first in form but pertained to needs

concordance, and it likewise was not supported. No significant differences within or

between study conditions were observed using mixed ANOVA. Participants’ self-

perceptions regarding their criminogenic needs tended to be partly consistent with their

LS/CMI results. They tended to agree on the presence or absence of about four of the

Central Eight risk factors, both before and after feedback. This suggests that more

intensive feedback or other preparatory interventions may be necessary if an early goal of

offender intervention is client buy-in to the treatment goals suggested by structured

risk/need assessment. Also, the importance of offender buy-in to a risk/need case

conceptualization, as has been studied in clinical populations (e.g., Addis & Carpenter,

2000), is another important question for future research.

55 This study’s approach to analyzing the relationship between self-perceived and

evaluator-appraised criminogenic needs differed from the one used by Brooks Holliday et

al. (2013), who simply correlated each of the corresponding Central Eight risk factors on

the RNPS and LS/CMI (which revealed significant associations for antisocial pattern,

substance misuse, and family and marital circumstances). It thus contributes unique

information about the concordance between offenders’ self-perceptions regarding

criminogenic needs, and criminogenic needs as measured by the LS/CMI. Also,

compared to many prior studies that have examined offenders’ views about a variety of

potential barriers to success upon release (Burnett, 2004; Cobbina & Bender, 2012;

Dhami et al., 2006; Friestad & Hansen, 2010; Kivivuori & Linderborg, 2010; Maruna,

2001; Sedikides et al., 2013; Souza et al., 2013; Visher et al., 2003; Zamble & Quinsey,

1997), this study had the unique advantage of being able to contrast offenders’ self-

perceived criminogenic needs with ratings made by evaluators. Moreover, because the

RNR model explicitly guided study design and interpretation, this study seems

conceptually clearer than past research, with more straightforward implications given the

widespread acceptance of RNR. Future studies exploring criminal persistence and

desistance processes from the first person perspective (Maruna, 2001, Yang & Mulvey,

2012) might be augmented by incorporating RNR, rather than relying upon more

disparate criminological or sociological views.

The third hypothesis was that feedback recipients would report significantly

greater motivation for change on the URICA at follow-up, in comparison to both baseline

measurement and the control condition at follow-up. This hypothesis was supported.

Participants receiving the discussion-based feedback uniquely showed an increase in

56 URICA scores post-feedback. All study conditions started and ended within the

contemplation stage of change, and each stated closer to the precontemplation cutoff

score. However, the discussion-based feedback recipients uniquely scored closer to the

preparation/action cutoff score at follow-up. The effect of study condition over time

accounted for 14% of the total variability of URICA total scores (i.e., ηp2 = 0.14, or if

converted to f = 0.40). Observed effects sizes were moderate to large in magnitude by

Cohen’s (1992) suggested standards. They were also comparable in magnitude to the

effect sizes reported in Anstiss et al. (2011), who measured stage of change using a

different measure before and after participation in a four- to five-session motivational

interviewing-based intervention (comparable to Motivational Enhancement Therapy; see

Miller & Rollnick, 2009; Miller, Zweben, DiClemente, & Rychtarik, 1992).

Increases in reported motivation for change tended to follow receiving discussion-

based feedback. This might be explained by the greater reliance on discussion processes

in that condition. The form-based feedback began with participants reviewing

standardized, personally tailored risk and need feedback forms, after which the

experimenter briefly explained their central concepts and asked whether the participants

had any questions. The discussion-based feedback, in contrast, involved many more

questions being posed to participants and greater attention being paid to motivational

interviewing principles. This included placing a greater emphasis on elucidating,

validating, building upon, and supporting participants’ past experiences, future plans,

self-determination and self-efficacy, and views about the feedback. The

psychoeducational components of the discussion-based feedback also incorporated

lengthier and more involved explanations of key concepts (e.g., using analogies).

57 Moreover, the discussion-based feedback lasted longer than the form-based feedback—

about two hours, on average, versus approximately a half-hour.

The stylistic and content differences between the two feedback conditions, alone

or in combination, may have accounted for the superior gains observed among

discussion-based feedback participants. Indeed, this would be predicted based on a

motivational interviewing perspective. Future research might isolate and examine these

various possibilities more closely, as has been done with motivational interviewing in

general (e.g., Miller & Rose, 2009). Moreover, the promising results in this study

regarding assessment feedback and motivation for change, coupled with Anstiss et al.’s

(2011) findings regarding the association between recidivism and both motivation for

change and participation in a motivational interviewing intervention, warrant future

research on the relationships among stages of change, motivational enhancement

interventions, treatment engagement (e.g., program attendance, program participation),

amount of change in dynamic risk factors, and ultimate recidivism outcomes. At least one

research team has recently been conducting this sort of sophisticated research (Lewis,

Olver, & Wong, 2013; Olver, Lewis, & Wong, 2013; Olver, Nicholaichuk, Kingston, &

Wong, 2014; Olver & Wong, 2009; Olver, Wong, Nicholaichuk, & Gordon, 2007).

The fourth hypothesis paralleled the third but pertained to treatment readiness as

measured by the CVTRQ. Support for this hypothesis was mixed. Treatment readiness

increased at follow-up for all conditions. Despite sufficient power, however, the analysis

did not indicate any significant differences between baseline and follow-up, or among the

study conditions at follow-up. Post hoc analyses revealed a significant difference between

baseline and follow-up treatment readiness scores for the discussion-based feedback

58 condition. Furthermore, unlike form-based feedback recipients, participants in the

discussion-based feedback condition produced a significantly higher treatment readiness

score at follow-up compared to the control condition. The effect sizes would be

considered moderate and large, respectively, by common convention (Cohen, 1992).

Thus, this study produced some evidence that treatment readiness increased following the

provision of discussion-based assessed feedback.

Treatment readiness can be conceptualized quite broadly (e.g., Ward et al., 2004),

with motivation being but one of a number of relevant factors. The CVTRQ, however,

although affiliated with the multifactor offender readiness model, is actually much

narrower in scope. It measures only four constructs: attitudes and motivation, affect,

cognitions, and self-efficacy beliefs. That similar results were observed for the CVTRQ

and URICA suggests that these two instruments measure partially overlapping constructs.

The strong associations that have been reported among earlier versions of the CVTRQ

and different stage of change measures support this interpretation (Casey et al., 2007;

Day et al., 2009). Accordingly, the preceding discussion pertaining to motivation for

change, and corresponding implications, can be extended in large measure to this finding

as well.

The fifth and final hypothesis was that feedback recipients, and particularly

discussion-based feedback participants, would find assessment feedback helpful and

recommend it for others. Results strongly supported this hypothesis. Participants rated

both the form-based and discussion-based feedback as helpful and worthwhile at levels

that were significantly higher than the midpoint of the FHS. The effect size for both of

the feedback conditions was moderate to large, indicating that assessment feedback was

59 well-regarded by participants. Participants slightly disagreed with only one item on the

FHS: that the feedback told them things about themselves that they did not already know.

This is actually a promising result, as it suggests that offenders may have some untaught

appreciation of the risk/need case conceptualization. Arriving at mutually agreeable

treatment targets and service plans, then, may not require extensive psychoeducation and

related preparation. This hypothesis is worth testing in the future.

Study Limitations

The present study was subject to a number of limitations. Those having the

strongest potential impact are discussed here. First, the overall sample size was relatively

small, as were the numbers of participants in each of the three study conditions.

Participant dropout also resulted in slightly unequal sample sizes among conditions.

Nonetheless, a priori and post-hoc power analyses indicated that the study was

sufficiently powered to detect significant differences, and actual attrition only exceeded

the anticipated dropout rate by 3%. Still, the reliability and generalizability of the

findings await future replications.

Second, the author recruited and consented all participants, administered all

measures, conducted all feedback sessions, and scored all study measures besides the

LS/CMI. Two researchers then double-entered data, after which the author resolved all

discrepancies and analyzed the data. The absence of experimenter blindness raises the

particular concern of demand characteristics. Feedback sessions were not recorded,

preventing assessment of the extent to which experimenter bias manifested itself. To help

guard against this threat to internal validity, the author remained mindful of this potential

for bias; employed standardized self-report measures, some with known psychometric

60 properties; and staggered follow-up measurement within conditions. Future research

should more rigorously guard against the potential for experimental bias by examining

responsivity-relevant interventions, using a design in which the individual providing the

feedback is blind to the study’s hypotheses.

Third, two of the five measures used in this study (the RNPS and FHS) have no

known psychometric properties, and study personnel did not administer the LS/CMI. In

addition, three slightly different versions of the RNPS were administered during the

course of the study, based on common points of confusion reported by participants. The

development of the initial version of the RNPS did, however, include use of a focus

group of offenders (S. Brooks Holliday, personal communication, May 24, 2014). The

author also offered participants similar explanations about how to complete the RNPS

regardless of which version was used. Furthermore, the FHS was designed to be face

valid (see Table 3), although it is possible that the FHS was influenced more by the

participants’ satisfaction with the feedback provider than the content of the feedback they

received. Moreover, risk/need data were obtained from LS/CMI evaluations conducted by

master’s-level facility assessment counselors who were trained in the proper use of the

instrument, alleviating some concerns about the quality of the relied-upon risk/need data.

To address these measurement limitations, future research should examine and report the

psychometric characteristics of the RNPS and FHS, and examine FHS scores with

different providers.

Fourth, although baseline self-report measures were readminstered after the

provision of feedback, data on instrumental outcomes—such as increased program

attendance and participation—were not collected. Even if reductions in recidivism were

61 observed among feedback recipients, the absence of a more comprehensive evaluation of

process variables following assessment feedback would limit the confidence in

conclusions regarding any relationship between assessment feedback and recidivism

outcomes. Given the promising present findings using self-report measures, research on

correctional assessment feedback that measures a wider range of instrumental (e.g.,

program attendance, participation, and attrition) and ultimate outcomes (e.g., change in

risk and needs, recidivism rates) is warranted.

Fifth, because feedback sessions were not recorded, the quality of assessment

feedback across sessions could not be evaluated, nor could the service’s consistency with

its theoretical underpinnings be assessed. The author delivered all feedback sessions

using a structured outline with sample language, thereby decreasing some of the potential

variability that might have resulted from multiple providers and unstructured feedback.

Also, the author was able to consult with a doctoral-level and licensed clinical

psychologist when questions arose, although this was a rare occurrence. Nonetheless, it is

recommended that future studies of correctional assessment feedback include systematic

quality control mechanisms in their designs.

Sixth, the amount of experimental separation between the form-based and

discussion-based feedback conditions was not as wide as it could have been. For instance,

the form-based feedback condition could have involved furnishing participants with

feedback forms to read on their own without any accompanying explanation of the

content therein or opportunity to ask questions. As a consequence of this limitation, the

extent to which interpersonal variables, including the possibility of attention alone,

accounted for observed effects remains unclear. An alternative explanation entirely

62 consistent with the obtained results is that participants regarded increasing amounts of

attention increasingly favorably, and that the more attention one received, the more

motivated for change and ready for treatment he appeared via self-report. However, even

if this were the case, it would still be consistent with Andrew and Bonta’s (2010a,

Chapter 2) observation that human service in general is empirically superior to no human

service in facilitating desistance among offenders. It might be that content and specific

techniques are less important than effective interpersonal interactions in the early stages

of treatment. Future studies might address these open questions by including two

additional conditions in their designs: one in which feedback recipients receive no human

contact and one in which participants receive a properly conceived placebo service in lieu

of structured feedback.

Implications and Future Directions

Study results suggested that offenders’ self-perceptions regarding their

criminogenic risk and needs were not particularly consistent with their risk/need

assessment results measured by a specialized tool—even after they were provided with

feedback about these assessment results. Nevertheless, offenders still showed some

appreciation of the importance of criminogenic risk (i.e., that they would be fairly likely

to reoffend absent personal change) and needs (i.e., agreeing about the presence or

absence of at least some of the Central Eight risk factors). Because self-evaluations and

evaluations made by others both uniquely contribute to and bias the prediction of

behavior (e.g., Epley & Dunning, 2006), future research should further examine the

extent to which offenders’ self-perceived risk and needs add to the predictive validity of

risk/need assessments by evaluators (see Brooks Holliday et al., 2014; Loza, 2005;

63 Skeem et al., 2013). That is, does incorporating subjective or first person perceptions of

risk or needs add significant incremental validity to predictions of recidivism risk with

risk/need assessment tools?

In the present study, assessment feedback did have significant effects on self-

reported motivation for change and treatment readiness, and the magnitude of these

effects was practically significant. For example, discussion-based feedback participants,

who mostly fell within the contemplation stage of change before and after feedback,

began closer to precontemplation but shifted toward a preparation and action stage of

change following feedback. Results suggested that discussion-based feedback had greater

effects than form-based feedback. Offenders, however, regarded assessment feedback

favorably regardless of whether it was form-based or discussion-based.

An interesting question for future research is whether form-based feedback

without human contact would still be well received by offenders. Conversely, future

studies could examine whether more intensive assessment feedback and other motivation

enhancing services yield more substantial outcomes than those observed in the present

study. Indeed, the most involved condition in the present study (the discussion-based

feedback condition) was simplistic and limited in numerous ways. That significant results

were observed for some relevant outcomes is thus quite promising, particularly when one

considers the relatively small sample utilized in this study. More intensive, involved, or

coordinated assessment-informed services might take a variety of forms, including

having assessment and treatment staff routinely and systematically collaborate on

treatment planning, conducting more frontend feedback sessions, providing clients with

more written psychoeducational materials, periodically reviewing and updating the case

64 conceptualization and intervention plan (with the client) throughout the course of

treatment, and periodically reassessing stage of change, risk, and needs.

Taken together, study findings lend support to Andrews, Bonta, and Wormith’s

(2011) recommendation that assessment feedback be provided in RNR-based work with

offenders for informative and motivational purposes. Discussion-based feedback, in

particular, had significant positive effects on self-reported treatment motivation and

readiness, and even brief, form-based feedback (with some human contact) was well

received by offenders. Thus, findings suggest that organizations engaged in the

supervision and treatment of criminal offenders, and those who are guided by RNR

principles, in particular, would be well served to implement such feedback into their

programming and to evaluate the results. The two variations of feedback used in the

present study could be readily incorporated into a variety of program structures using

minimal resources. Unless an organization could articulate a strong reason why offenders

should not be informed about their assessment results, the failure to provide correctional

clients with information pertaining to their risk level, risk-relevant needs, clinical

treatment needs, and treatment recommendations is unjustified. Without compelling

justification, such a failure has no discernible advantages while losing numerous potential

benefits.

65 List of References

1. Addis, M. E., & Carpenter, K. M. (2000). The treatment rationale in cognitive behavioral therapy: Psychological mechanisms and clinical guidelines. Cognitive and Behavioral Practice, 7, 147–156. doi:10.1016/S1077-7229(00)80025-5

2. American Psychological Association. (2010). Ethical principles of psychologists and code of conduct (2002, Amended June 1, 2010). Retrieved from http://www.apa.org/ethics/code/index.aspx

3. American Psychological Association. (2013). Specialty guidelines for forensic psychology. American Psychologist, 68, 7–19. doi:10.1037/a0029889

4. Andrews, D. A., & Bonta, J. (2010a). The psychology of criminal conduct (5th ed.). New Providence, NJ: LexisNexis Matthew Bender.

5. Andrews, D. A., & Bonta, J. (2010b). Rehabilitating criminal justice policy and practice. Psychology, Public Policy and Law, 16, 39–55. doi:10.1037/a0018362

6. Andrews, D. A., Bonta, J., & Hoge, R. D. (1990). Classification for effective rehabilitation: Rediscovering psychology. Criminal Justice and Behavior, 17, 19–52. doi:10.1177/0093854890017001004

7. Andrews, D. A., Bonta, J., & Wormith, S. J. (2004). Level of service/case management inventory (LS/CMI). Toronto, Ontario, Canada: Multi-Health Systems.

8. Andrews, D. A., Bonta, J., & Wormith, S. J. (2006). The recent past and near future of risk and/or need assessment. Crime and Delinquency, 52, 7–27. doi:10.1177/0011128705281756

9. Andrews, D. A., Bonta, J., & Wormith, S. J. (2010). The Level of Service (LS) assessment of adults and older adolescents. In R. K. Otto & K. S. Douglas (Eds.), Handbook of violence risk assessment (pp. 199–225). New York, NY: Routledge.

10. Andrews, D. A., Bonta, J., & Wormith, S. J. (2011a). The Risk-Need-Responsivity (RNR) Model: Does adding the Good Lives Model contribute to effective crime prevention? Criminal Justice and Behavior, 38, 735–755. doi:10.1177/0093854811406356

11. Andrews, D. A., & Dowden, C. (2007). The Risk–Need–Responsivity model of assessment and human service in prevention and corrections: Crime-prevention jurisprudence. Canadian Journal of Criminology and Criminal Justice, 49, 439–464. doi:10.3138/cjccj.49.4.439

66 12. Andrews, D. A., Guzzo, L., Raynor, P., Rowe, R. C., Rettinger, L. J., Brews, A., & Wormith, J. S. (2012). Are the major risk/need factors predictive of both female and male reoffending? A test with the eight domains of the Level of Service/Case Management Inventory. International Journal of Offender Therapy and Comparative Criminology, 56, 113–133. doi:10.1177/0306624X10395716

13. Andrews, D. A., Zinger, I., Hoge, R. D., Bonta, J., Gendreau, P., & Cullen, F. T. (1990). Does correctional treatment work? A clinically relevant and psychologically informed meta-analysis.

14. Anstiss, B., Polaschek, D. L. L., & Wilson, M. (2011). A brief motivational intervention with prisoners: When you lead a horse to water, can it drink for itself? Psychology, Crime and Law. Advanced online publication. doi:10.1080/10683160903524325

15. Aos, S., Miller, M., & Drake, E. (2006). Evidence-based public policy options to reduce future prison construction, criminal justice costs, and crime rates. Olympia, WA: Washington State Institute for Public Policy. Retrieved from http://www.wsipp.wa.gov/ReportFile/952

16. Barlow, D. H. (Ed.). (2008). Clinical handbook of psychological disorders: A step-by-step treatment manual (4th ed.). New York, NY: Guilford Press.

17. Bogue, B., & Nandi, A. (2012). Motivational interviewing in corrections: A comprehensive guide to implementing MI in corrections (NIC Accession Number 025556). Retrieved from U.S. Department of Justice, National Institute of Corrections website: http://nicic.gov/Library/files/025556.pdf

18. Bonta, J., Law, M., & Hanson, R. K. (1998). The prediction of criminal and violent recidivism among mentally disordered offenders: A meta-analysis. Psychological Bulletin, 123, 123–142. doi:10.1037/0033-2909.123.2.123

19. Brooks Holliday, S., Heilbrun, K., DeMatteo, D., Fretz, R., & King, C. (2014, March). Self-reported and LS/CMI measured risk factors: Relation to RNR adherence and criminal recidivism. Paper presented at the meeting of the American Psychology-Law Society, New Orleans, LA.

20. Brooks Holliday, S., King, C., & Heilbrun, K. (2013). Offenders’ perceptions of risk factors for self and others: Theoretical importance and some empirical data. Criminal Justice and Behavior, 40, 1044–1061. doi:10.1177/0093854813482308

21. Brooks-Holliday, S., Yasuhara, K., Shah, S., Bingham, A., King, C., Hamilton, D., . . . & Heilbrun, K. (2011, Summer). The application of risk-need-responsivity to risk assessment and intervention planning: Opportunities, current limitations, and relevant research needs. American Psychology Law Society NEWS, 31(2), 1, 4–5. Retrieved from http://www.apadivisions.org/division-41/publications/newsletters/news/2011/07-issue.pdf

67 22. Burnett, R. (2004). To reoffend or not to reoffend? The ambivalence of convicted property offenders. In S. Maruna & R. Immarigeon, After crime and punishment: Pathways to offender reintegration (pp. 152–180). Cullompton, Devon, United Kingdom: Willan.

23. Burrowes, N., & Needs, A. (2009). Time to contemplate change? A framework for assessing readiness to change with offenders. Aggression and Violent Behavior, 14, 39–49. doi:10.1016/j.avb.2008.08.003

24. Campbell, J., Sellen, J. L., & McMurran, M. (2010). Personal Aspirations and Concerns Inventory for Offenders: Developments in the measurement of offenders’ motivation. Criminal Behaviour and Mental Health, 20, 144–157. doi:10.1002/cbm.761

25. Carson, E. A., & Golinelli, D. (2013). Prisoners in 2012: Trends in admissions and releases, 1991–2012 (NCJ 243920). Retrieved from Office of Justice Programs, Bureau of Justice Statistics website: http://www.bjs.gov/content/pub/pdf/p12tar9112.pdf

26. Casey, S., Day, A., & Howells, K. (2005). The application of the transtheoretical model to offender populations: Some critical issues. Legal and Criminological Psychology, 10, 157–171. doi:10.1348/135532505X36714

27. Casey, S., Day, A., Howells, K., & Ward, T. (2007). Assessing the suitability for offender rehabilitation: Development and validation of the treatment readiness questionnaire. Criminal Justice and Behavior, 34, 1427–1440. doi:10.1177/0093854807305827

28. Cobbina, J. E., & Bender, K. A. (2012). Predicting the future: Incarcerated women’s views of reentry success. Journal of Offender Rehabilitation, 51, 275–294. doi:10.1080/10509674.2012.683323

29. Cohen, J. (1992). A power primer. Psychological Bulletin, 112, 155–159. doi:10.1037/0033-2909.112.1.155

30. Committee on the Revision of the Specialty Guidelines for Forensic Psychology (in press). Specialty guidelines for forensic psychologists. American Psychologist. Retrieved from http://www.ap-ls.org/aboutpsychlaw/SpecialtyGuidelines.php

31. Curry, K. T., & Hanson, W. E. (2010). National survey of psychologists’ test feedback training, supervision, and practice: A mixed methods study. Journal of Personality Assessment, 92, 327–336. doi:10.1080/00223891.2010.482006

32. Day, A., Bryan, J., Davey, L., & Casey, S. (2006). The process of change in offender rehabilitation programmes. Psychology, Crime and Law, 12, 473–487. doi:10.1080/10683160500151209

33. Day, A., Casey, S., Ward, T., Howells, K., & Vess, J. (2010). Transition to better lives: Offender readiness and rehabilitation. Cullompton, United Kingdom: Willan.

68 34. Day, A., Howells, K., Casey, S., Ward, T., Chambers, J. C., & Birgden, A. (2009). Assessing treatment readiness in violent offenders. Journal of Interpersonal Violence, 24, 618–635. doi:10.1177/0886260508317200

35. DeMatteo, D., Hunt, E., Batastini, A., & LaDuke, C. (2010). The disconnect between assessment and intervention in the risk management of criminal offenders. Open Access Journal of Forensic Psychology, 2, 59–74.

36. Developments in state constitutional law: 2001: IV. Due process. (2002). Rutgers Law Journal, 33, 1299–1338.

37. Dhami, M. K., Mandel, D. R., Loewenstein, G., & Ayton, P. (2006). Prisoners’ positive illusions of their post-release success. Law and Human Behavior, 30, 631–647. doi:10.1007/s10979-006-9040-1

38. Douglas, K. S., & Skeem, J. L. (2005). Violence risk assessment: Getting specific about being dynamic. Psychology, Public Policy, and Law, 11, 347–383. doi:10.1037/1076-8971.11.3.347

39. Dowden, C., & Andrews, D. A. (1999a). What works for female offenders: A meta-analytic review. Crime & Delinquency, 45, 438–452. doi:10.1177/0011128799045004002

40. Dowden, C., & Andrews, D. A. (1999b). What works in young offender treatment: A meta-analytic review. Forums on Corrections Research, 11, 21–24.

41. Drieschner, K. H., & Boomsma, A. (2008). The Treatment Engagement Rating scale (TER) for forensic outpatient treatment: Description, psychometric properties, and norms. Psychology, Crime and Law, 14, 299–315. doi:10.1080/10683160701858206

42. Drieschner, K. H., Lammers, S. M. M., & van der Staak, C. P. F. (2004). Treatment motivation: An attempt for clarification of an ambiguous concept. Clinical Psychology Review, 23, 1115–1137. doi:10.1016/j.cpr.2003.09.003

43. Dvoskin, J. A., Skeem, J. L., Novaco, R. W., & Douglas, K. S. (Eds.) (2012). Using social science to reduce violent offending. New York, NY: Oxford University Press.

44. Epley, N., & Dunning, D. (2006). The mixed blessings of self-knowledge in behavioral prediction: Enhanced discrimination but exacerbated bias. Personality and Social Psychology Bulletin, 32, 641–655. doi:10.1177/0146167205284007

45. Farbring, C. A., & Johnson, W. R. (2008). Motivational interviewing in the correctional system. In H. Arkowitz, H. A. Westra, W. R. Miller, & S. Roonick (Eds.). Motivational interviewing in the treatment of psychological problems (pp. 304–323). New York, NY: Guildford Press.

69 46. Faul, F., Erdfelder, E., Lang, A. G., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39, 175–191. doi:10.3758/BF03193146

47. Finn, S. E. (2007). In our clients’ shoes: Theory and techniques of therapeutic assessment. Mahwah, NJ: Erlbaum.

48. Frase, R. S. (2008). Limiting excessive prison sentences under federal and state constitutions. University of Pennsylvania Journal of Constitutional Law, 11, 39–72.

49. Friestad, C., & Hansen, I. L. S. (2010). Gender differences in inmates' anticipated desistance. European Journal of Criminology, 7, 285–298. doi:10.1177/1477370810363375

50. Gendreau, P., Andrews, D. A., Goggin, C., & Chanteloupe, F. (1992). The development of clinical and policy guidelines for the prediction of criminal behavior in criminal justice settings. Unpublished manuscript, Department of Psychology, University of New Brunswick, St. John, New Brunswick, Canada.

51. Gendreau, P., Little, T., & Goggin, C. (1996). A meta-analysis of the predictors of adult offender recidivism: What works! Criminology, 34, 575–607. doi:10.1111/j.1745-9125.1996.tb01220.x

52. Gendreau, P., Smith, P., & French, S. A. (2006). The theory of effective correctional intervention: Empirical status and future directions (pp. 419–446). In F. T. Cullen, J. P. Wright, & K. R. Blevins (Eds.), Taking stock: The status of criminological theory (pp. 419–446). New Brunswick, NJ: Transaction Publishers.

53. Ginsburg, J. I. D., Mann, R. E., Rotgers, F., & Weekes, J. R. (2002). Using motivational interviewing with criminal justice populations. In W. R. Miller & S. Rollnick (Eds.), Motivational interviewing: Preparing people for change (pp. 333–346). New York, NY: Guilford Press.

54. Glaze, L. E., & Bonczar, T. P. (2009). Probation and parole in the United States, 2007 statistical tables (NCJ 224707). Retrieved from Office of Justice Programs, Bureau of Justice Statistics website: http://www.bjs.gov/content/pub/pdf/ppus07st.pdf

55. Glaze, L. E., & Herberman, E. J. (2013). Correctional population in the United States, 2012 (NCJ 243936). Retrieved from Office of Justice Programs, Bureau of Justice Statistics website: http://www.bjs.gov/content/pub/pdf/cpus12.pdf

56. Hanson, R. K., & Morton-Bourgon, K. (2004). Predictors of sexual recidivism: An updated meta-analysis (Report No. 2004-02). Retrieved from Public Safety Canada website: http://www.publicsafety.gc.ca/res/cor/rep/_fl/2004-02-pred-se-eng.pdf

57. Heilbrun, K. (1997). Prediction versus management models relevant to risk assessment: The importance of legal context. Law and Human Behavior, 21, 347–359. doi:10.1023/A:1024851017947

70 58. Heilbrun, K., Rogers, R., & Otto, R. (2002). Forensic assessment: Current status and future directions. In J. Ogloff (Ed.), Psychology and law: Reviewing the discipline (pp. 120–147). New York, NY: Kluwer Academic/Plenum Press.

59. Helmus, L., Hanson, R. K., Thornton, D., Babchishin, K. M., & Harris, A. J. R. (2012). Absolute recidivism rates predicted by Static-99R and Static-2002R sex offender risk assessment tools vary across samples: A meta-analysis. Criminal Justice and Behavior, 39, 1148–1171. doi:10.1177/0093854812443648

60. Howells, K., & Day, A. (2003). Readiness for anger management: Clinical and theoretical issues. Clinical Psychology Review, 23, 319–337. doi:10.1016/S0272-7358(02)00228-3

61. Jewell, L. M., & Wormith, J. S. (2010). Variables associated with attrition from domestic violence treatment programs targeting male batterers: A meta-analysis. Criminal Justice and Behavior, 37, 1086–1113. doi:10.1177/0093854810376815

62. Kivivuori, J., & Linderborg, H. (2010). Negative life events and self-control as correlates of self-assessed re-offending probability among Finnish prisoners. European Journal of Criminology, 7, 123–139. doi:10.1177/1477370809354139

63. Kyckelhahn, T. (2013). Local government corrections expenditures, FY 2005–2011 (NCJ 243527). Retrieved from Office of Justice Programs, Bureau of Justice Statistics website: http://www.bjs.gov/content/pub/pdf/lgcefy0511.pdf

64. Kyckelhahn, T., & Martin, T. (2013). Justice expenditure and employment extracts, 2010 - Preliminary (NCJ 242544) [data and explanatory files]. Retrieved from Office of Justice Programs, Bureau of Justice Statistics website: http://www.bjs.gov/index.cfm?ty=pbdetail&iid=4679

65. Kroner D. G., & Yessine A.K. Changing risk factors that impact recidivism: In search of mechanisms of change. Law and Human Behavior, 37, 321–336. doi:10.1037/lhb0000022

66. Langan, P. A., & Levin, D. J. (2002). Recidivism of prisoners released in 1994 (NJC 193427). Retrieved from Office of Justice Programs, Bureau of Justice Statistics website: http://bjs.ojp.usdoj.gov/content/pub/pdf/rpr94.pdf

67. Lewis, K., Olver, M., & Wong, S. C. P. (2013). The Violence Risk Scale: Predictive validity and linking changes in risk with violent recidivism in a sample of high risk offenders with psychopathic traits. Assessment, 20, 150–164. doi:10.1177/1073191112441242

68. Lilienfeld, S. O., Garb, H. N., & Wood, J. M. (2011). Unresolved questions concerning the effectiveness of psychological assessment as a therapeutic intervention: Comment on Poston and Hanson (2010). Psychological Assessment, 23, 1047–1055. doi:10.1037/a0025177

71 69. Lipsey, M. W. (2009). The primary factors that characterize effective interventions with juvenile offenders: A meta-analytic overview. Victims and Offenders, 4, 124–147. doi:10.1080/15564880802612573

70. Lipsey, M. W., & Cullen, F. T. (2007). The effectiveness of correctional rehabilitation: A review of systematic reviews. Annual Review of Law and Social Science, 3, 297–320. doi:10.1146/annurev.lawsocsci.3.081806.112833

71. Lipsey, M. W., & Derzon, J. H. (1998). Predictors of violent or serious delinquency in adolescence and early adulthood: A synthesis of longitudinal research. In R. Loeber & D. P. Farrington (Eds.), Serious and violent juvenile offenders: Risk factors and successful interventions (pp. 86–105). Thousand Oaks, CA: Sage.

72. Loza, W. (2005). Self-appraisal questionnaire (SAQ). Multi-Health Systems. Toronto, Ontario.

73. Maruna, S. (2001). Making good: How ex-convicts reform and rebuild their lives. Washington, DC: American Psychological Association. doi:10.1037/10430-000

74. McConnaughy, E. A., Prochaska, J. O., & Velicer, W. F. (1983). Stages of change in psychotherapy: Measurement and sample profiles. Psychotherapy: Theory, Research and Practice, 20, 368–375. doi:10.1037/h0090198

75. McConnaughy, E. A., DiClemente, C. C., Prochaska, J. O., & Velicer, W. F. (1989). Stages of change in psychotherapy: A follow-up report. Psychotherapy: Theory, Research and Practice, 26, 494–503. doi:10.1037/h0085468

76. McCrady, B. S. (2008). Alcohol use disorders. In D. H. Barlow (Ed.), Clinical handbook of psychological disorders: A step-by-step treatment manual (4th ed.) (pp. 493–546). New York, NY: Guilford Press.

77. McMurran, M. (2009). Motivational interviewing with offenders: A systematic review. Legal and Criminological Psychology, 14, 83–100. doi:10.1348/135532508X278326

78. McMurran, M., & Ward, T. (2010). Treatment readiness, treatment engagement and behaviour change. Criminal Behaviour and Mental Health, 20, 75–85. doi:10.1002/cbm.762

79. McMurran, M., Sellen, J., & Campbell, J. (2011). Offenders’ motivation: measurement, structure, and content. In W. M. Cox & E. Klinger (Eds.), Handbook of motivational counseling: Goal-based approaches to assessment and intervention with addiction and other problems (pp. 253–272). Chichester, United Kingdom: Wiley-Blackwell. doi:10.1002/9780470979952.ch10

72 80. Meyer, G. J., Finn, S. E., Eyde, L. D., Kay, G. G., Moreland, K. L., Dies, R. R., . . . Reed, G. M. (2001). Psychological testing and psychological assessment: A review of evidence and issues. American Psychologist, 56, 128–165. doi:10.1037/0003-066X.56.2.128

81. Miller, W. R., & Rollnick, S. (1991). Motivational interviewing: Preparing people to change addictive behavior (1st ed.). New York, NY: Guildford Press.

82. Miller, W. R., & Rollnick, S. (2002). Motivational interviewing: Preparing people for change (2nd ed.). New York, NY: Guildford Press.

83. Miller, W. R., & Rollnick, S. (2013). Motivational interviewing: Helping people change (3rd ed.). New York, NY: Guildford Press.

84. Miller, W. R., & Rollnick, S. (2009). Toward a theory of motivational interviewing. American Psychologist, 64, 527–537. doi:10.1037/a0016830

85. Miller, W. R., Zweben, A., DiClemente, C. C., & Rychtarik, R. C. (1992). Motivational Enhancement Therapy manual: A clinical research guide for therapists treating individuals with alcohol abuse and dependence (NIH Publication No. 94-3723). Rockville, MD: National Institute on Alcohol Abuse and Alcoholism.

86. Monahan, J., Steadman, H., Appelbaum, P., Grisso, T., Mulvey, E., Roth, L., . . . & Silver, E. (2005). The classification of violence risk [Software]. Lutz, FL: Psychological Assessment Resources.

87. Morgan, R. D., Kroner, D. G., Mills, J. F., Serna, C., & McDonald, B. (2013). Dynamic risk assessment: A validation study. Journal of Criminal Justice, 41, 115–124. doi:10.1016/j.jcrimjus.2012.11.004

88. Morris, S. B., & DeShon, R. P. (2002). Combining effect size estimates in meta-analysis with repeated measures and independent-groups designs. Psychological Methods, 7, 105–125. doi:10.1037/1082-989X.7.1.105

89. Nezu, A. M., Nezu. C. M., & Cos, T. A. (2007). Case formulation for the behavioral and cognitive therapies: A problem-solving perspective. In T. D. Eells (Ed.), Handbook of psychotherapy case formulation (2nd ed., pp. 349–378). New York, NY: Guilford Press.

90. Ogrodniczuk, J. S., Joyce, A. S., & Piper, W. E. (2005). Strategies for reducing patient-initiated premature termination of psychotherapy. Harvard Review of Psychiatry, 13, 57–70. doi:10.1080/10673220590956429

91. Olver, M., Lewis, K., & Wong, S. C. P. (2013). Risk reduction treatment of high-risk psychopathic offenders: The relationship of psychopathy and treatment change to violent recidivism. Personality Disorder: Theory, Research, and Treatment, 4, 160–167. doi:10.1037/a0029769

73 92. Olver, M. E., Nicholaichuk, T. P., Kingston, D. A., & Wong, S. C. P. (2014). A multisite examination of sexual violence risk and therapeutic change. Journal of Consulting and Clinical Psychology, 82, 312–324. doi:10.1037/a0035340

93. Olver, M. E., Stockdale, K. C., & Wormith, S. J. (2011). A meta-analysis of predictors of offender treatment attrition and its relationship to recidivism. Journal of Consulting and Clinical Psychology, 79, 6-21. doi:10.1037/a0022200

94. Olver, M. E., Stockdale, K. C., & Wormith, S. J. (2013). Thirty years of research on the Level of Service Scales: A meta-analytic examination of predictive accuracy and sources of variability. Psychological Assessment, 26, 156–176. doi:10.1037/a0035080

95. Olver, M. E., & Wong, S. C. P. (2009). Therapeutic responses of psychopathic sexual offenders: Treatment attrition, therapeutic change, and long-term recidivism. Journal of Consulting and Clinical Psychology, 77, 328–336. doi:10.1037/a0015001

96. Olver, M. E. Wong, S. C. P., Nicholaichuk, T., & Gordon, A. (2007). The validity and reliability of the Violence Risk Scale-Sexual Offender version: Assessing sex offender risk and evaluating therapeutic change. Psychological Assessment, 19, 318–329. doi:10.1037/1040-3590.19.3.318

97. Palmer, J. W. (2010). Constitutional rights of prisoners. New Providence, NJ: Matthew Bender.

98. Pew Center on the States (2011). State of Recidivism: The Revolving Door of America’s Prisons. Retrieved from http://www.pewcenteronthestates.org/uploadedFiles/Pew_State_of_Recidivism.pdf

99. Polaschek, D. L. L., Anstiss, B., & Wilson, M. (2010). The assessment of offending-related stage of change in offenders: psychometric validation of the URICA with male prisoners. Psychology, Crime and Law, 16, 305–325. doi:10.1080/10683160802698766

100. Poston, J. M., & Hanson, W. E. (2010). Meta-analysis of psychological assessment as a therapeutic intervention. Psychological Assessment, 22, 203–212. doi:10.1037/a0018679

101. Prochaska, J. O., DiClemente, C. C., & Norcross, J. C. (1992). In search of how people change: Applications to addictive behaviors. American Psychologist, 47, 1102–1114. doi:10.1037/0003-066X.47.9.1102

102. Rettinger, L. J. (1998). A recidivism follow-up study investigating risk and need within a sample of provincially sentenced women (Unpublished doctoral dissertation, Carleton University). Retrieved from http://www.collectionscanada.gc.ca/obj/s4/f2/dsk2/tape15/PQDD_0002/NQ37054.pdf

103. Rettinger, L. J., & Andrews, D. A. (2010). General risk and need, gender specificity, and the recidivism of female offenders. Criminal Justice and Behavior, 37, 29–46. doi:10.1177/0093854809349438

74 104. Romani, C. J., Morgan, R. D., Gross, N. R., McDonald, B. R. (2012). Treating criminal behavior: Is the bang worth the buck? Psychology, Public Policy, and Law, 18, 144–165. doi:10.1037/a0024714

105. Ronan, G., Gerhart, J., Bannister, D., & Udell, C. (2010). Relevance of a stage of change analysis for violence reduction training. Journal of Forensic Psychiatry and Psychology, 21, 761–772. doi:10.1080/14789949.2010.483285

106. Ross, E. C., Polaschek, D. L. L., & Ward, T. (2008). The therapeutic alliance: A theoretical revision for offender rehabilitation. Aggression and Violent Behavior, 13, 462–480. doi:10.1016/j.avb.2008.07.003

107. Rotman, E. (1986). Do criminal offenders have a constitutional right to rehabilitation? Journal of Criminal Law and Criminology, 77, 1023–1068. doi:10.2307/1143667

108. Sedikides, C., Meek, R., Alicke, M. D., & Taylor, S. (2013). Behind bars but above the bar: Prisoners consider themselves more prosocial than non-prisoners. British Journal of Social Psychology. Advanced online publication. doi: 10.1111/bjso.12060

109. Serin, R. (1998). Treatment responsivity, intervention and reintegration: A conceptual model. Forum on Corrections Research, 10, 29–32.

110. Serin, R., & Kennedy, S. (1997). Treatment readiness and responsivity: Contributing to effective correctional programming (Research Report R-54). Correctional Services of Canada.

111. Skeem, J. L., Manchak, S. M., Lidz, C. W., & Mulvey, E. P. (2013). The utility of patients’ self-perceptions of violence risk: Consider asking the person who may know best. Psychiatric Services, 64, 410–415. doi:10.1176/appi.ps.001312012

112. Simourd, L., & Andrews, D. A. (1994). Correlates of delinquency: A look at gender differences. Forum on Corrections Research, 6, 26–31.

113. Smith, P., Gendreau, P., & Swartz, K. (2009). Validating the principles of effective intervention: A systematic review of the contributions of meta-analysis in the field of corrections. Victims and Offenders, 4, 148–169. doi:10.1080/15564880802612581

114. Smith, S. R., Wiggins, C. M., & Gorske, T. T. (2007). A survey of psychological assessment feedback practices. Assessment, 14, 310–319. doi:10.1177/1073191107302842

115. Souza, K. A., Lösel, F., Markson, L., & Lanskey, C. (2013). Pre-release expectations and post-release experiences of prisoners and their (ex-)partners. Legal and Criminological Psychology. Advanced online publication. doi:10.1111/lcrp.12033

116. Stewart, L., & Millson, W. A. (1995). Offender motivation for treatment as a responsivity factor. Forum on Corrections Research, 7(3), 5–7.

75 117. Stewart, L., & Picheca, J. C. (2001). Improving offender motivation for programming. Forum on Corrections Research, 13, 18–20.

118. van der Knaap, L. M., Alberda, D. L., Oosterveld, P., & Born, M. P. (2012). The predictive validity of criminogenic needs for male and female offenders: Comparing the relative impact of needs in predicting recidivism. Law and Human Behavior, 36, 413–422. doi:10.1037/h0093932

119. Van Voorhis, P., Wright, E. M., Salisbury, E., & Bauman, A. (2010). Women’s risk factors and their contributions to existing risk/needs assessment: The current status of a gender-responsive supplement. Criminal Justice and Behavior, 37, 261–288. doi:10.1177/0093854809357442

120. Visher, La Vigne, & Castro, 2003). Returning home: Preliminary findings from a pilot study of soon-to-be released prisoners in Maryland. Justice Research and Policy, 5, 55 – 74. doi:10.3818/JRP.5.2.2003.55

121. Vitopolos, N. A., Peterson-Badali, M., & Skilling, T. A. (2012). The relationship between matching service to criminogenic need and recidivism in male and female youth: Examining the RNR principles in practice. Criminal Justice and Behavior, 39, 1025–1041. doi:10.1177/0093854812442895

122. Walitzer, K. S., Dermen, K. H., & Connors, G. J. (1999). Strategies for preparing clients for treatment: A review. Behavior Modification, 23, 129–151. doi:10.1177/0145445599231006

123. Walters, S. T., Clark, M. D., Gingerich, R., & Meltzer, M. (2007). Motivating offenders to change: A guide for probation and parole. Washington, DC: National Institute for Corrections.

124. Ward, T., Day, A. Howells, K., & Birgden, A. (2004). The multifactor offender readiness model. Aggression and Violent Behavior, 9, 645–673. doi:10.1016/j.avb.2003.08.001

125. Ward, T., Melser, J., & Yates, P. M. (2007). Reconstructing the Risk–Need–Responsivity model: A theoretical elaboration and evaluation. Aggression and Violent Behavior, 12, 208–228. doi:10.1016/j.avb.2006.07.001

126. Weiner, I. B., & Greene, R. L. (2008). Handbook of personality assessment. Hoboken, NJ: Wiley.

127. West, R. (2005). Time for a change: Putting the transtheoretical (stages of change) model to rest. Addiction, 100, 1036–1039. doi:10.1111/j.1360-0443.2005.01139.x

128. Wormith, J. S., Althouse, R., Simpson, M., Reitzel, L. R., Fagan, T. J., & Morgan, R. D. (2007). The rehabilitation and reintegration of offenders: The current landscape and some future directions for correctional psychology. Criminal Justice and Behavior, 34, 879–892. doi:10.1177/0093854807301552

76 129. Wormith, J. S., & Olver, M. E. (2002). Offender treatment attrition and its relationship with risk, responsivity, and recidivism. Criminal Justice & Behavior, 29, 447–471. doi:10.1177/0093854802029004006

130. Yang, S., & Mulvey, E. (2012). Violence risk: Re-defining variables from the first-person perspective. Aggression and Violent Behavior, 17, 198–207. doi:10.1016/j.avb.2012.02.001

131. Zamble, E., & Quinsey, V. L. (1997). The criminal recidivism process. Cambridge, United Kingdom: Cambridge University Press. doi:10.1017/CBO9780511527579

132. Zaro, J. S., Barach, R., Nedelman, D. J., & Dreiblatt, I. S. (1977). A guide for beginning psychotherapsits. New York, NY: Cambridge University Press.

77 Appendix A: University of Rhode Island Change Assessment (Long Form)

This questionnaire is to help us improve services. Each statement describes how a person might feel when starting therapy or approaching problems in their lives. “Problem” refers to your offending behavior. "Here" refers to the place of treatment or the program. Please indicate the extent to which you tend to agree or disagree with each statement by circling a response to each. In each case, make your choice in terms of how you feel right now, not what you have felt in the past or would like to feel.

There are FIVE possible responses to each of the items in the questionnaire: 1 = Strongly Disagree 2 = Disagree 3 = Undecided 4 = Agree 5 = Strongly Agree

Strongly Disagree Disagree Undecided Agree

Strongly Agree

1 As far as I'm concerned, I don't have any problems that need changing.

1 2 3 4 5

2 I think I might be ready for some self-improvement.

1 2 3 4 5

3 I am doing something about the problems that had been bothering me.

1 2 3 4 5

4 It might be worthwhile to work on my problem. 1 2 3 4 5

5 I'm not the problem one. It doesn't make much sense for me to be here.

1 2 3 4 5

6

It worries me that I might slip back on a problem I have already changed, so I am here to seek help.

1 2 3 4 5

7 I am finally doing some work on my problem. 1 2 3 4 5

78

Strongly Disagree Disagree Undecided Agree Strongly

Agree

8 I've been thinking that I might want to change something about myself.

1 2 3 4 5

9

I have been successful in working on my problem but I'm not sure I can keep up the effort on my own.

1 2 3 4 5

10 At times my problem is difficult, but I'm working on it.

1 2 3 4 5

11

Being here is pretty much a waste of time for me because the problem doesn't have to do with me.

1 2 3 4 5

12 I'm hoping that this place will help me to better understand myself.

1 2 3 4 5

13 I guess I have faults, but there's nothing that I really need to change.

1 2 3 4 5

14 I am really working hard to change. 1 2 3 4 5

15 I have a problem and I really think I should work at it.

1 2 3 4 5

16

I'm not following through with what I had already changed as well as I had hoped, and I'm here to prevent a relapse of the problem.

1 2 3 4 5

17

Even though I'm not always successful in changing, I am at least working on my problem.

1 2 3 4 5

18

I thought once I had resolved my problem I would be free of it, but sometimes I still find myself struggling with it.

1 2 3 4 5

79

Strongly Disagree Disagree Undecided Agree Strongly

Agree

19 I wish I had more ideas on how to solve the problem.

1 2 3 4 5

20 I have started working on my problems but I would like help.

1 2 3 4 5

21 Maybe this place will be able to help me. 1 2 3 4 5

22

I may need a boost right now to help me maintain the changes I've already made.

1 2 3 4 5

23 I may be part of the problem, but I don't really think I am.

1 2 3 4 5

24 I hope that someone here will have some good advice for me.

1 2 3 4 5

25 Anyone can talk about changing; I'm actually doing something about it.

1 2 3 4 5

26

All this talk about psychology is boring. Why can't people just forget about their problems?

1 2 3 4 5

27 I'm here to prevent myself from having a relapse of my problem.

1 2 3 4 5

28

It is frustrating, but I feel I might be having a recurrence of a problem I thought I had resolved.

1 2 3 4 5

29

I have worries but so does the next guy. Why spend time thinking about them?

1 2 3 4 5

30 I am actively working on my problem. 1 2 3 4 5

31 I would rather cope with my faults than try to change them.

1 2 3 4 5

80

Strongly Disagree Disagree Undecided Agree

Strongly Agree

32

After all I had done to try to change my problem, every now and again it comes back to haunt me.

1 2 3 4 5

81 Appendix B: Corrections Victoria Treatment Readiness Questionnaire

This questionnaire is to help us improve services. Each statement describes how a person might feel when starting treatment or approaching problems in their lives. Please indicate the extent to which you tend to agree or disagree with each statement by circling a response to each. In each case, make your choice in terms of how you feel right now, not what you have felt in the past or would like to feel.

There are FIVE possible responses to each of the items in the questionnaire: 1 = Strongly Disagree 2 = Disagree 3 = Unsure 4 = Agree 5 = Strongly Agree

Strongly Disagree Disagree Unsure Agree Strongly

Agree

1 Treatment programs are rubbish. 1 2 3 4 5

2 I want to change. 1 2 3 4 5

3 Generally I can trust other people. 1 2 3 4 5

4 I am not able to do treatment programs. 1 2 3 4 5

5 I am to blame for my offending. 1 2 3 4 5

6 Treatment programs don’t work. 1 2 3 4 5

7 When I think about my last offense I feel angry with myself. 1 2 3 4 5

8 Others are to blame for my offending. 1 2 3 4 5

9 I am upset about being a corrections client. 1 2 3 4 5

10 Stopping offending is really important to me. 1 2 3 4 5

11 I am well organized. 1 2 3 4 5

12 I feel guilty about my offending. 1 2 3 4 5

82

Strongly Disagree Disagree Unsure Agree Strongly

Agree

13 I have not offended for some time now. 1 2 3 4 5

14 I don’t deserve to be doing a sentence. 1 2 3 4 5

15 Being seen as an offender upsets me. 1 2 3 4 5

16 When I think about my sentence I feel angry with other people. 1 2 3 4 5

17 I regret the offense that led to my last sentence. 1 2 3 4 5

18 I feel ashamed about my offending. 1 2 3 4 5

19 I hate being told what to do. 1 2 3 4 5

20 Treatment programs are for wimps. 1 2 3 4 5

83 Appendix C: Risk Need Perception Survey (All Versions)

Risk Need Perception Survey (Version 1) Think about whether each item below has been present in your life in a way that is a problem. How much do you think that if you don’t change, this problem will make it more likely that you’ll commit another crime in the future? There are THREE possible responses to each of the items in this questionnaire: 1 = No (not present in your life, or not a problem if it is) 2 = Somewhat 3 = Yes

Present and could make you more likely to reoffend if

not changed

No Somewhat Yes

1 Your criminal history 1 2 3

2 Your education level 1 2 3

3 Your physical attractiveness 1 2 3

4 Your sleeping habits 1 2 3

5 Your medical history 1 2 3

6 Your work life (over the past 3 years) 1 2 3

7 Your need to be perfect 1 2 3

8 Your self-esteem 1 2 3

9 Your friends and associates 1 2 3

10 Your patience level 1 2 3

11 Your family members 1 2 3

12 Your nervousness 1 2 3

13 Your significant other 1 2 3

14 Your stress level 1 2 3

15 Your friendliness toward other people 1 2 3

16 How you spend your free time (over the past 3 years) 1 2 3

17 Your sexual abilities 1 2 3

18 Your race or ethnicity 1 2 3

84

Present and could make you more likely to reoffend if not changed

No Somewhat Yes

19 That you smoke cigarettes or cigars 1 2 3

20 Your religion or religious beliefs 1 2 3

21 Your use of drugs or alcohol (in the past 3 years) 1 2 3

22 Your age 1 2 3

23 Your mental illness 1 2 3

24 Your athletic abilities 1 2 3

25 Your attitudes and thoughts 1 2 3

26 Your creativity 1 2 3

27 Your financial life 1 2 3

28 Your childhood 1 2 3

29 Your intelligence 1 2 3

30 Your feelings of depression 1 2 3

31 Your overall pattern of criminal, self-centered, and/or irresponsible behavior 1 2 3

How likely do you think it is that you’ll reoffend if you don’t change?

1

Not at all

2

Slightly

3

About 50/50

4

More likely than not

5

Definitely

What probability out of 100% would you say your chance of reoffending is if you don’t change?

_______ %

85 Risk Need Perception Survey (Version 2)

Think about whether each area below has been present or absent in your life in a way that is a problem. How much do you think that if you don’t change, this problem area will make it more likely that you’ll commit another crime in the future? There are THREE possible responses to each of the items in this questionnaire: 1 = No (area is not a problem for you) 2 = Somewhat (area is a medium problem for you) 3 = Yes (area is a major problem for you)

Present and could make you more likely to reoffend if

not changed

No Somewhat Yes

1 Your criminal history 1 2 3

2 Your education level 1 2 3

3 Your physical attractiveness 1 2 3

4 Your sleeping habits 1 2 3

5 Your medical history 1 2 3

6 Your work life (over the past 3 years) 1 2 3

7 Your need to be perfect 1 2 3

8 Your self-esteem 1 2 3

9 Your friends and associates 1 2 3

10 Your patience level 1 2 3

11 Your family members 1 2 3

12 Your nervousness 1 2 3

13 Your significant other 1 2 3

14 Your stress level 1 2 3

15 Your friendliness toward other people 1 2 3

16 How you spend your free time (over the past 3 years) 1 2 3

17 Your sexual abilities 1 2 3

18 Your race or ethnicity 1 2 3

19 That you smoke cigarettes or cigars 1 2 3

20 Your religion or religious beliefs 1 2 3

86

Present and could make you more likely to reoffend if not changed

No Somewhat Yes

21 Your use of drugs or alcohol (in the past 3 years) 1 2 3

22 Your age 1 2 3

23 Your mental illness 1 2 3

24 Your athletic abilities 1 2 3

25 Your attitudes and thoughts 1 2 3

26 Your creativity 1 2 3

27 Your financial life 1 2 3

28 Your childhood 1 2 3

29 Your intelligence 1 2 3

30 Your feelings of depression 1 2 3

31 Your overall pattern of criminal, self-centered, and/or irresponsible behavior 1 2 3

How likely do you think it is that you’ll reoffend if you don’t change?

1

Not at all

2

Slightly

3

About 50/50

4

More likely than not

5

Definitely

What probability out of 100% would you say your chance of reoffending is if you don’t change?

_______ %

87 Risk Need Perception Survey (Version 3)

Think about whether each area below has been present or absent in your life in a way that could be considered a problem. How much do you think that if you don’t change each area, it would make it more likely that you’ll commit another crime in the future? So for each item, first ask yourself if the area could be considered a problem for you. If it is, then ask yourself if you believe that if you don’t work on the problem area, it will increase your likelihood of reoffending by a medium amount (“Somewhat”) or a major amount (“Yes”). There are THREE possible responses to each of the items in this questionnaire: 1 = No (area is not a problem for you for reoffending) 2 = Somewhat (area is a medium problem for you for reoffending) 3 = Yes (area is a major problem for you for reoffending) Area could make you more likely to reoffend if not changed

No

(Not problem) Somewhat

(Medium problem) Yes

(Major problem) 1 Your criminal history 1 2 3

2 Your education level 1 2 3

3 Your physical attractiveness 1 2 3

4 Your sleeping habits 1 2 3

5 Your medical history 1 2 3

6 Your work life (over the past 3 years) 1 2 3

7 Your need to be perfect 1 2 3

8 Your self-esteem 1 2 3

9 Your friends and associates 1 2 3

10 Your patience level 1 2 3

11 Your family members 1 2 3

12 Your nervousness 1 2 3

13 Your significant other 1 2 3

14 Your stress level 1 2 3

15 Your friendliness toward other people 1 2 3

88

Area could make you more likely to reoffend if not changed

No

(Not problem) Somewhat

(Medium problem) Yes

(Major problem)

16 How you spend your free time (over the past 3 years)

1 2 3

17 Your sexual abilities 1 2 3

18 Your race or ethnicity 1 2 3

19 That you smoke cigarettes or cigars 1 2 3

20 Your religion or religious beliefs 1 2 3

21 Your use of drugs or alcohol (in the past 3 years)

1 2 3

22 Your age 1 2 3

23 Your mental illness 1 2 3

24 Your athletic abilities 1 2 3

25 Your attitudes and thoughts 1 2 3

26 Your creativity 1 2 3

27 Your financial life 1 2 3

28 Your childhood 1 2 3

29 Your intelligence 1 2 3

30 Your feelings of depression 1 2 3

31

Your overall pattern of criminal, self-centered, and/or irresponsible behavior

1 2 3

How likely do you think it is that you’ll reoffend if you don’t change?

1

Not at all

2

Slightly

3

About 50/50

4

More likely than not

5

Definitely

89 What probability out of 100% would you say your chance of reoffending is if you don’t change?

_______ %

90 Appendix D: Feedback Helpfulness Survey

Answer the following statements based on the feedback you received about things that might make you more likely to commit a crime and how you can turn these problems areas into strengths. Please circle your response. There are FOUR possible responses to each of the items in the questionnaire: 1 = Strongly Disagree 2 = Slightly Disagree 3 = Slightly Agree 4 = Strongly Agree

Strongly Disagree

Slightly Disagree

Slightly Agree

Strongly Agree

1 I agree with the feedback. 1 2 3 4

2 I found the feedback helpful. 1 2 3 4

3 The feedback told me things about myself that I did not already know. 1 2 3 4

4 Because of the feedback, I now have a better understanding of the issues that might make me more likely to commit a crime.

1 2 3 4

5 Because of the feedback, I now have a better understanding of the things I need to work on in treatment.

1 2 3 4

6 I think the feedback would be helpful for other people who are in jail or prison for committing crimes.

1 2 3 4

91 Appendix E: Standardized Feedback Form

Problem Areas

The biggest issues that make people more likely to commit crimes are listed below. Your assessment results suggest that you might have problems with some of them. 1 Having committed crimes in the past.

□ Not a problem for you

□ Somewhat of a problem for you

□ A major problem for you

2 Having been a generally difficult person and having acted like a criminal for a long time.

□ Not a problem for you

□ Somewhat of a problem for you

□ A major problem for you

3 Having attitudes, thoughts, and beliefs favoring or justifying crime.

□ Not a problem for you

□ Somewhat of a problem for you

□ A major problem for you

4 Having friends or associates who commit crimes.

□ Not a problem for you

□ Somewhat of a problem for you

□ A major problem for you 5 Having problems with your family, at home, and/or in your romantic life.

□ Not a problem for you

□ Somewhat of a problem for you

□ A major problem for you

92

6 Having not finished high school, not working, and/or being a bad employee.

□ Not a problem for you

□ Somewhat of a problem for you

□ A major problem for you 7 Not spending your free time doing positive and productive things.

□ Not a problem for you

□ Somewhat of a problem for you

□ A major problem for you

8 Using drugs at all and/or drinking too much.

□ Not a problem for you

□ Somewhat of a problem for you

□ A major problem for you If you add up your scores in all these areas for a total score, you can compare it to the scores of lots of other people who were in jail or prison but were later released and tracked to see if they committed a new crime. For example, one study found:

% of people who reoffended

Very low score Low score Medium score High score Very high score

4% 15% 44% 80% 100%

Based on this information, we think that about _____ % of the people with a score like yours will reoffend, so that is your risk of reoffending. While this should worry you, you can increase your chances of not falling back into crime by working to change these problem areas into strengths.

93 Treatment Targets/Goals

Wanting to/being motivated to remain crime free is a good thing, but its not enough. You’ll have to actually turn problem areas into strengths to lower the chance that you’ll commit another crime. If you take an interest in your treatment and really work at it, though, your problem areas can change into strengths. If they did, it would make it less likely that you would commit crimes in the future. And the more areas you work on, the better. You can increase your odds of not falling back into crime the most if you work on all of these areas, rather than just certain ones like getting a job. Research has shown that many people who were able to stop committing crimes and go totally straight did so by changing many of the below problem areas they had into strengths. 1 Having committed crimes in the past.

□

Things to work on in treatment: Your history cannot be changed. But you can build up new noncriminal thinking and behaviors to use in risky situations. You can also work on coming to believe in yourself, that you know what to do to avoid criminal activity and that you have the ability to do what is required. What this looks like as a strength: Your thinking when you have a chance to commit a crime is focused on responsible alternatives. But regardless of how you may think or feel, you do not commit crimes.

2 Having been a generally difficult person and having acted like a criminal for a long time.

□

Things to work on in treatment: You can work on building up your self-control skills, anger management skills, and problem solving skills. What this looks like as a strength: You practice restraint, you think before acting, and you are agreeable with other people.

3 Having attitudes, thoughts, and beliefs favoring or justifying crime.

□

Things to work on in treatment: You can work on building up less negative and risky thoughts and feelings. What this looks like as a strength: You reject criminal thoughts or beliefs. You think of yourself as being a productive member of society, not a criminal.

94

4 Having friends or associates who commit crimes.

□

Things to work on in treatment: You can stop spending time with people who commit crimes and spend your time instead with people living productive, crime-free lives. What this looks like as a strength: You have close and frequent contact with positive people and you do not associate with people involved in crime.

5 Having problems with your family, at home, and/or in your romantic life.

□

Things to work on in treatment: Work on reducing conflict at home, building positive relationships, telling your family not to tolerate crime involvement from you, and spending more time caring for and supervising your children. What this looks like as a strength: Your relationship with your spouse, parents, and siblings is loving and caring, and you practice firm but fair monitoring of your children. Crime is not tolerated within your family.

6 Having not finished high school, not working, and/or being a bad employee.

□

Things to work on in treatment: You can work on increasing your involvement and performance at school and/or work. You can also work on viewing school/work as a source of reward and satisfaction. What this looks like as a strength: You have strong attachments to your fellow students/coworkers as well as your teachers/bosses. You also work hard to do a good job at school/work. Knowing that you did something meaningful in the form of school/work and that you did it to the best of your ability brings you satisfaction.

7 Not spending your free time doing positive and productive things.

□

Things to work on in treatment: You can work on using your free time to participate in organized, positive activities, like sports leagues, charities, or events hosted by your religious institution. These types of activities are highly rewarding and you will likely feel very satisfied by using your free time to participate in them. What this looks like as a strength: You are highly involved in organized, positive leisure pursuits.

8 Using drugs at all and/or drinking too much (or for many, drinking at all).

□

Things to work on in treatment: You can work to stop using drugs/alcohol and to stop associating with people who do. You can also work on building up alternatives to drug/alcohol use when faced with risky situations. Further, you can work on changing beliefs that might support drug/alcohol use. What this looks like as a strength: You are clean/sober from drugs/alcohol and you recognize that drugs/alcohol cause more problems than they are worth.

95 Appendix F: Feedback Sessions Curriculum

Structure and purpose: Hour-long feedback sessions (× 2) to aid in the linkage of assessment and treatment of offenders Guiding principles/components:

1. Assessment and feedback linkage: Curriculum links to treatment planning by explaining the idea of risk level to the client, informing the client of his or her assessment-derived risk factors, and presenting treatment goals derived from the Psychology of Criminal Conduct text.

2. Collaborative feedback and therapeutic assessment: Feedback is delivered in a

respectful, supportive manner that helps examinee feel comfortable and encourages him to discuss his reactions to the feedback. To increase the likelihood that the feedback will be perceived as supportive and beneficial, the discussion as to risk factors begins with a discussion of risk factors that are absent (i.e., low risk or strength areas), then proceeds to present high-risk areas, and finally to medium-risk areas. The feedback process should be interactive, with examinee being asked if he understands and agrees with the feedback. Confusion on part of examinee calls for further explanation; disagreement calls for further exploration. Ensure that the examinee feels heard, understood, and respected. The feedback process is aimed at helping the examinee learn new ways of thinking and feeling about himself and fostering his self-exploration of what he has learned and its application to his problems in living.

3. Therapeutic alliance: Establish a collaborative relationship with the client, seek

an affective bond between yourself and client, and seek to reach agreement on treatment goals and tasks.

4. Motivational interviewing spirit: Style of feedback delivery and curriculum incorporate motivational interviewing principles, including rapport building, and avoiding argumentation in favor of rolling with resistance:

a. FRAMES:

i. personalized feedback (F) to the client about his or her status; ii. an emphasis on the personal responsibility (R) of the client for

change; iii. provision of clear advice (A) about the need for change, given in a

supportive manner;

96 iv. providing the client with a menu (M) of options for how to go

about changing, rather than insisting upon one treatment or treatment goal;

v. providing treatment in a warm, emphatic (E), and supportive style; and

vi. enhancing the client’s perceived self-efficacy (S) for change.

b. DARES: i. develop discrepancy (D);

ii. avoid arguing (A); iii. roll with resistance (R); iv. express empathy (E); and v. support self-efficacy (S)

c. Ideas and language articulated in the Short Motivation Programme

(Anstiss, Steyn, Devereux, & Devereux, 2003, 2006, 2007), the successor program to the program evaluated by Anstiss et al. (2011).

97 Session 1 Outline

To do prior to meeting with client:

Review clients LS/CMI results. Score the risk factors section of the standardized feedback form pursuant to the LS/CMI results.

Practical task 1: Review assessment results Learning objective 1: Develop problem recognition

*** Initial explanation

Explain that, because the client agreed to participate in the research study, you are meeting with him or her to discuss his or her assessment results, how they might be of use to the client, and to get the client’s input. Let the client know that the assessment is already written, you’re not the assessment counselor, and what is discussed will likely not be shared with the assessment counselor, other facility staff, or DOC decisionmakers (i.e., unless the client admits to something serious, like an intention to harm themselves or someone else, or a flagrant violation of facility rules). Note the two-session format of the curriculum. Also, appeal to client’s self-interest—and emphasize personal responsibility—rather than simply telling them that they can better themselves through treatment:

“We all say things we have to say to get by. Let’s set this aside and talk about your future. If this test is right, if you don’t work on these things, you might be going back to prison— not me or anyone else. Let’s be honest and talk about what things you might need to do so that that doesn’t happen. Change is up to you.”

Something comparable to the following script can be used until you are able to develop your own natural script:

“Just before we get started I’ll spend a few minutes explaining what this is about. As a part of the study you previously agreed to participate in, I’d like to discuss your assessment results over the course of two meetings. So far you may have talked to a couple of different people about your offending and you will have definitely done an assessment with an assessment counselor. From these assessments, we’ve gathered some information about your offending, and about some of the things you may need to work on, or are already working on, to reduce your likelihood of re-offending. To be clear, your assessment is already written, I’m not the assessment counselor, and what is discussed between us will likely not be shared with the assessment counselor, other facility staff, or DOC

98 decisionmakers (unless you tell me something serious, like an intention to harm yourself or someone else, or a flagrant violation of facility rules).

We all say things we have to say to get by. Let’s set this aside and talk about your future. If this test is right, if you don’t work on these things, you might be going back to prison— not me or anyone else. Let’s be honest and talk about what things you might need to do so that that doesn’t happen. Change is up to you. Over the next two meetings we’re going to focus on your understanding of some of these things and your motivation and commitment towards potentially making some changes in certain areas. We’ll spend a little bit of time looking back at what has happened so far, and then do some planning for the future. The aim of our work together is to get you in the best shape possible for future programs and supports in the community once you are released. It is kind of like pre-season training in sports. You do the hard work before the season gets going and it makes things a lot easier during the season.

The plan is to meet for two sessions. At the end you should have a better idea about the areas that you need to work on and also the best way to do this. We don’t want you to attend programs that you don’t want to do—this sets you up to fail, and you’ll probably agree it isn’t a good use of yours or anyone else’s time and energy. You should think about what we talk about in the first session in between our second meeting. Do you have any questions before we get started?”

*** Explore how the client views his or her problems

Ask the client about his or her self-perceived risk factors and reflect what he or she provides you. Summarize the list they provide. Ask if any were missed, or if any others popped into the mind of the client.

***

Explore how his or her self-perceptions fit with his or her LS/CMI results

Explain the idea of risk level and changeable versus unchangeable risk factors:

“Although there are many unique issues that might make people more or less likely to commit crimes, there are 8 big issues that seem to play a role for most people who get into trouble with the law. We’ll be talking about these issues and whether some of them might be strengths or weaknesses for you. Also, if you add up someone’s scores on a measure of these 8

99 problem areas for a total score, you can compare it to the scores of lots of other people who were in jail or prison but were later released and tracked for whether they committed a new crime. This allows you to see how many of these people who scored the same as you committed new crimes.”

Explain that items on the measure are rated pursuant to rules to ensure that different assessors would likely rate the same person the same for each item (i.e., that the measure is reliable). Explain also that the measure predicts who is more or less likely to reoffend pretty well (i.e., that the measure is valid). Tell the client what their risk level is. Ask for their input and reflect any concerns. Explain that a person’s risk level is not dispositive, but that comparing the person to others who scored similarly nonetheless provides useful information. Tell the client that their risk level is composed of the 8 problem areas, and so changing problem areas into strengths reduces risk level. Next, using the standardized form, go through each of the central eight risk factors with the client, and explain what it is and whether it is a relative strength or weakness for the client. Begin with those risk areas that are absent for the client (i.e., low risk factors or strengths). Then proceed to high risk factors, and finally medium risk factors. Ask for the client’s input at the junction of each risk factor and reflect any concerns. You may not have reviewed the actual assessment report in full, so you can respond to the client who disagrees with a risk factor: “Why might the assessment counselor have thought this was an issue for you?” In addition, you will have the LS/CMI Section 1 subitem results available to describe to the client. If you and the client disagree sharply about a risk factor, tell him or her that you just want to “park” the risk factor between sessions so that you can both think about it between sessions and possibly re-explore this issue in the next session. Do not get into an argument about whether or not a particular need is present or not.

***

Try to come to a compromise with the client about what their risk level is. Then try to come to a compromise about what his or her risk factors are and which are most important to address.

*** Explain to the client that the first session is now complete. Explain that during the next meeting you will be discussing what the complete opposite of risk factors in certain areas (strengths) look like, and how to go about changing weaknesses into strengths.

100 Session 2 Outline

To do prior to meeting with client:

Score the treatment targets/goals section of the standardized feedback form pursuant to the risk factors section.

Practical task 2: Review treatment targets Learning objective 2: Achieve client buy in to treatment targets and value of treatment

*** Review from session 1

Briefly re-explain the concept of risk level and changeable versus unchangeable risk factors. Quickly review the client’s risk/need assessment profile as discussed during the first meeting and remind them of the agreed upon/compromised profile.

“Last session we discussed the 8 major factors that contribute to people committing crimes. I pointed out that most of these problem areas are changeable. We also talked about how you can measure these problematic issues and add them together, and then compare your total score to others who scored the same and were tracked to see if they recommitted crimes. In this way, we can get a sense for how likely or unlikely you are to also recommit a crime. The assessment results we discussed suggested that you had a [low, medium, or high] likelihood of reoffending. We also discussed issues that, if changed in a positive direction, will lower the likelihood that you will offend. For you, these areas were: [list pertinent risk factors from standardized form].” You and I ultimately decided that these issues (OR the issues of [compromised list of risk factors]) were your most problematic issues.

*** Introduce the concept of changing risk areas into strengths

“Wanting to/being motivated to remain crime free is a good thing, but its not enough. You’ll have to actually turn problem areas into strengths to lower the chance that you’ll commit another crime. If you take an interest in your treatment and really work at it, though, your problem areas can change into strengths. If they did, it would make it less likely that you would commit crimes in the future. And the more areas you work on, the better. You can increase your odds of not falling back into crime the most if you work on all of these areas, rather than just

101 certain ones like getting a job. Research has shown that many people who were able to stop committing crimes and go totally straight did so by changing many of their risk factors into strengths.”

***

Review risk factor treatment targets

Using the standardized form, review things to work on and what a strength looks like for each risk factor. Remind the client if the risk factor you are reviewing is a relatively big deficit for him or her. If a client had scored low for a particular risk factor that you are reviewing, show them how their situation resembles that of the strength description. At each risk factor junction, ask the client for his input and thoughts. Permit the client to disagree; if he or she does, it is acceptable to talk about what the participant wants to, but he or she must mention which aspects of his or her self-perceived issues he wants to talk about.

***

Review value of sufficient treatment

Ask the client how they might go about making the changes in the positive direction (i.e., his or her intended method(s)). Explore insufficiently articulated plans by questioning the client whether he or she believes their plan will be adequate given the difficulty of changing behavior. Explain that many non-offenders get professional help (e.g., therapy or counseling) to makes changes in their life because change is hard. Explain to the client that its even more important for them to get help in making these changes, because if they don’t, the consequences for criminal behavior are far more severe than for the behaviors that non-offenders in the community frequently seek therapy for (e.g., work-related performance; phobias) Explain that this is the reason for why we spend time in therapy/counseling: “We’re trying to give you more tools here.” Elaborate the tools/tool kits analogy: “A worker needs multiple tools for multiple circumstances; so to do people for dealing with problem areas and risky situations, whether the issue is committing crimes or any other problem behavior.” Put it also in financial terms: “Another analogy is that you’re investing in yourself by putting in the time and effort to address your risk factors to get the best possible cash out—staying out of prison so that you can pursue your goals in prosocial ways.” Explain that ultimately, the client will need to find a way—treatment or otherwise—to improve some of his problematic circumstances or situations, and also change some of his problematic feelings, beliefs, and behaviors.

Wind down

102 Tell the client that session 2 is now complete. Express your hope that they found the feedback helpful and that he or she now has a clearer perspective on what to work on going forward. Remind the client that awareness of his or her problems or even a resolve to not commit future crimes—while a good start—is not enough to keep them from reoffending. Rather, they will need to make the changes towards the direction of strengths in the problem areas discussed. Tell them offending is like any other behavior, being influenced by the client’s life situation, feelings, thoughts/beliefs, and related behaviors, and so can be fixed just like any other behavior—by making changes to life situation, feelings, thoughts/beliefs, and related behaviors. Complement the client on contributing to their feedback and the progress he or she has made in identifying the areas he or she needs to address. Remind the client that he or she also now has an appreciation for what positive changes in these areas look like. Tell the client that you have trust that he or she is capable of finding the necessary help to effect these changes in his or her life. Ask if the client has any questions

If the client asks about what happens to him or her next regarding placement or something similar, say that you don’t know, and recommend that he or she talk to his or her senior counselor about that. Explain that the feedback sessions were for his or her benefit only, and do not impact their trajectory at the facility or beyond.

Administer the follow-up instruments

“The final thing we need to do is have you retake a few short self-report questionnaires that you took when you first agreed to participate in the study.” Ensure that all items on all instruments are filled out completely

Thank the client for participating in the study when they finish filling out the instruments and it is verified that all items have been answered.

103 Appendix G: Demographic Information

Date of Entry: _________________________________________________________________ DOB: ______________________ Age: __________ Race:

African American/Black Hispanic/Latino Caucasian Asian

Native American Other Marital Status:

Single-Never Married Engaged Married Divorced Widowed Level of Education:

Less Some HS Finished HS/GED Some College Associate’s

Bachelor’s More Current Offense(s) Type (if multiple present offenses, circle all that apply):

Violent Robbery Property Drugs-Alcohol Firearms-Related

Status Violation of Supervision

104 Current Offense(s): ____________________________________________________________ Sentence Length: ______________________________________________________________

105 Appendix H: LS/CMI and RNPS Concordance Scores

The LS/CMI is only administered once and entered into both pre and post scoring tables. Risk/Need Perception Items without a Correlate: Physical attractiveness (3); Sleeping habits (4); Medical History (5); Being a perfectionist (7); Self-esteem (8); Anxiety (12); Stress (14); Being outgoing (15); Sexual abilities (17); Racial or ethnic background (18); Smoking cigarettes or cigars (19); Religious beliefs (20); Age (22); Having a mental illness (23); Athleticism (24); Creativity (26); Childhood experiences (28); IQ (29); Depression (30) The highest concordance score a participant can obtain is an 8, representing perfect self-awareness as to the presence or absence and strength of the Central Eight risk factors. The lowest is a 0, which represents a total lack of self-awareness. Scoring rules:

1. For risk factors that are comprised of multiple RNPS items, add the response value (1, 2, or 3) for each item and then divide by the number of items. If the returned answer is a decimal number, round up from .5. For example, if a participant answered Not at all (1) and Somewhat (2) to the two education/employment items on the RNPS, you would add 1 and 2 (which equals 3) and divide by the number of risk factor items (which is 2). Thus:

(1 + 2)/3 = 1.5

Because 1.5 rounds up to 2, you would select Somewhat (2) as the average score.

2. A participant will receive 1 point for each risk factor that he rates as either not at all or somewhat important for himself on the RNPS when section 1 of the LS/CMI identified this risk factor as very low or low.

3. A participant will receive 1 point for each risk factor that he rates as either

somewhat or very important for himself on the RNPS when section 1 of the LS/CMI identified this risk factor as medium.

4. A participant will receive 1 point for each risk factor that he rates as very

important for himself on the RNPS when section 1 of the LS/CMI identified this risk factor as high or very high.

106 5. A participant will receive 0 points for any other combination of LS/CMI-

and self-rated risk factors.

LS/CMI Category/Item RNPS Item L M H N S Y 1 Criminal History 1 Criminal history

□ L and N/S □ M and S/Y □ H and Y 2 Education/Employment 2 Education level

□ L and N/S □ M and S/Y □ H and Y 6 Employment history

Average score:

3 Family/Marital 11 Family members

□ L and N/S □ M and S/Y □ H and Y 13 Significant other

Average score:

4 Leisure/Recreation 16 How free time is spent

□ L and N/S □ M and S/Y □ H and Y

5 Companions 9 Friends and associates

□ L and N/S □ M and S/Y □ H and Y 6 Alcohol/Drug Problem 21 Use of drugs or alcohol

□ L and N/S □ M and S/Y □ H and Y 7 Procriminal Attitude 10 Patience

□ L and N/S □ M and S/Y □ H and Y 25 Attitudes and thoughts

Average score:

8 Antisocial Pattern 10 Patience

□ L and N/S □ M and S/Y □ H and Y

25 Attitudes and thoughts 27 Financial difficulties

6 Employment history 2 Education level

11 Family members 16 How free time is spent

9 Friends and associates Average score:

□ L and N/S □ M and S/Y □ H and Y 31 Antisocial pattern

Section 1 Total Score:[ ] Total Concordance Score (sum of checkmarks)= __________ Likert= __________ Percentage= __________ % Abbreviations: LS/CMI: L = very low or low; M = medium; H = high or very high; RNPS: N = not at all; S = somewhat; Y = yes

107 Appendix I: URICA Continuous-Method Score

Precontemplation Items Contemplation Items 1 ___

2 ___

5 ___

4 ___

11 ___

8 ___

13 ___

12 ___

23 ___

15 ___

26 ___

19 ___

29 ___

21 ___

31 ___

24 ___

Sum ___– #31 ___/7 ____

Sum ___– #4 ___/7 ____

Action Items Maintenance Items 3 ___

6 ___

7 ___

9 ___

10 ___

16 ___

14 ___

18 ___

17 ___

22 ___

20 ___

27 ___

25 ___

28 ___

30 ___

32 ___

Sum ___– #20 ___/7 ____

Sum ___– #9 ___/7 ____

Readiness Score (sum of C, A, and M subscale score means minus P subscale score mean) = __

2–8: Precontemplator 9–11: Contemplator 12–14: Preparator into Action Taker

108 Appendix J: CVTRQ Score

Total Readiness Score (sum of all items after reverse coding items 1, 4, 6, 8, 14, 16, 19, and 20) = __________ 72 = preliminary cut-off score indicative of treatment readiness (yes/no?) = __________ Attitudes and Motivation Score (sum of items 1, 2, 4, 6, 10, 20) = __________ Emotional Reactions Score (sum of items 7, 9, 12, 15, 17, 18) = __________ Offending Beliefs Score (sum of items 5, 8, 14, 16) = __________ Efficacy Score (sum of items 3, 11, 13, 19) = __________

109 Appendix K: FHS Score

Total Score (sum of all items) = __________ Item 1 = __________ Item 2 = __________ Item 3 = __________ Item 4 = __________ Item 5 = __________ Item 6 = __________