ISSN 1862-2941



WelcomeOnline-Issues2-20191-20191/2-20182-20171-20172-20161-20162-20151-20152-20141-20142-20131-20132-20121-20122-20111-20112-20101-20102-20091-20092-20081-20082-20071-20073-20062-20061-2006Guidelines to authorsAbout usLegal NoticePrivacy

 

 

The Supervision of Known Sex Offenders in the Community: Monitoring Progress and Providing Feedback

Andrew Day
School of Psychology, Faculty of Health, Deakin University

[Sexual Offender Treatment, Volume 8 (2013), Issue 2]

Abstract

Case management is the process by which most known sex offenders who live in the community are currently supervised. However, by itself, case management has been shown to have only a modest impact on rates of re-offending, and it is only when case work and/or treatment sessions are introduced, that the benefits become apparent. This paper considers how routinely collecting and feeding back standardized data about client progress towards supervisory goals can be integrated into the offender supervision and case management process. Based on methods that have been shown to be associated with enhanced outcomes in mental health, it is suggested that the implementation of feedback approaches have the potential to both enhance the case management process and improve the effectiveness of those policies which require it.

Key words: Sex offender, supervision, case management, feedback


Recent years have seen the introduction and implementation of a range of new programs and policies that have been designed to manage the risks of known sex offenders committing further offenses (CSOM, 2008). It is probably fair to say while many of these initiatives have been warmly welcomed both by the public and their political representatives (see Zgoba, Witt, Dalessandro, & Veysey, 2008), they have also met with criticism from those professionals who work with offenders. Critics have pointed to the lack of consistent evidence that is currently available to show that initiatives such as sex offender registries and community notification schemes are indeed effective in reducing rates of offending (e.g., Petrunik, Murphy, & Fedoroff, 2008). For example, Sandler, Freeman, and Socia (2008) examined differences in sexual offense arrest rates before and after the enactment of New York State's Sex Offender Registration Act in 1995 by analyzing monthly arrest counts over a period of 21 years between 1986 and 2006. The results, based on over 170,000 sexual offense arrests involving over 160,000 sex offenders, provided no support for the effectiveness of registration and community notification in reducing sexual offending by rapists, child molesters, sexual recidivists, or first time sex offenders. Others have argued that the restrictions placed on some offenders are not always proportional to the seriousness of their offences or the likelihood of them re-offending (e.g., Erooga, 2008), as well as expressing concern that such policies, albeit unintentionally, may create circumstances in which offending is more likely to occur (Day et al., under review).

Given that it is unlikely that the legislation that has led to the introduction of these measures will be repealed (at least in the foreseeable future), there is a need to carefully consider how the ongoing supervision and monitoring of known offenders that is required under current legislation can be implemented in ways that ensure that it is most likely to succeed in meeting the goal of reducing further offending. One obvious way to do this is to integrate current knowledge about sexual offending and risk of sexual re-offence with how the current offender registration and monitoring schemes are enacted. Indeed, accounting for the various levels of risk that are posed by different sex offenders has been identified as one of the most significant steps that legislators and policymakers can take in the development of effective supervisory practices (CSOM, 2008), and it is typically recommended that the frequency and intensity of supervisory activities should not only be based on an ongoing assessment of risk, but also change over time in light of changes to individual circumstances (see Vess, Langskail, Day, Powell, & Graffam, 2011). In practice this does not always seem to happen - one recent study by Blasko, Jeglic, and Mercado (2011) concluded that actuarial risk scores and risk information were not routinely used to make determinations about sex offender risk status for the purpose of enhanced registration and community notification.

The focus of this paper, however, is not on the further development of public policy in this area, nor on how progress in treatment might be assessed. Nor is it directly concerned with the structure of offender case management (see Day, Hardcastle, & Birgden, 2012; Trotter, 2006) or the need for different professionals and agencies to collaboratively manage risk (see English, Jones & Patrick, 2003). Rather, this paper considers a specific aspect of the process of case management, or case work practice, for front-line workers who are responsible for supervising known sex offenders in the community. This task is usually given to community correctional officers, but other professional groups (including non-government agency support workers and police officers who administer offender registries) also play important roles. Specifically, the aim of this paper is to consider the merits of routinely collecting standardized data on progress towards supervisory goals and the provision of feedback to individual clients based on their data. This is something that rarely happens outside of the treatment context and yet, it will be argued, has the potential to improve supervisory outcomes.

Offender case management

Case management provides the structure in which sex offender management policies are enacted; setting out the objectives, tasks, activities, and planning the sequencing or scheduling of any required tasks or interventions. Palmiotto and MacNichol (2010) have described the process of sex offender case management in the following way:


"The supervisor's involvement begins with the initial case planning and continues throughout supervision. Depending on the nature of the case, various issues are commonly discussed, which include: assessment of registration requirements; assessment of third-party risk and notification requirements; development of supervision objectives and strategies; fostering relationships with law enforcement and other community resources; and review of treatment reports and polygraph examinations" (p.29).


Palmiotto and MacNichol (2010) go on to argue that those who supervise defendants charged with a sex offense should closely monitor any factor that presents the defendant with an opportunity or temptation to engage in criminal or antisocial behaviour, a suggestion that resonates with contemporary approaches to offender case management. For example, the Proactive Community Supervision model (Taxman, Yancey, & Bilanin, 2006) identifies the need for goal-directed case management plans which are very explicitly linked to relevant dynamic risk factors. In this model, community corrections workers are expected to apply behavioral strategies, risk and need tools, case plans, and compliance management to rehabilitate or manage the offenders that they supervise. An outcome evaluation reported by Taxman (2008) concluded that, after controlling for sentence length and prior history, those who received this type of proactive supervision were re-arrested less often (30% vs 42%) and were less likely to violate the conditions of their orders (34.7% vs 40%) than those who did not receive 'proactive' supervision. Although, these reductions may appear to be relatively modest, they can also be considered to be socially significant in terms of reducing both the direct and indirect costs of crime. In short, then, there is broad agreement that each individual offender will vary in the level of risk he or she presents with, and that this will not only vary over time, but also across situations. Accordingly, a key role of any effective supervisor will be to monitor these changes and intervene as and when it is appropriate.

Monitoring progress and providing feedback

Supervisors are often required to exercise their discretion in how to manage offenders on a regular basis. They are expected to decide when concerns about an individual become sufficiently serious to warrant some kind of intervention or response. Thus, supervisory practice is not always focused on gross breaches of supervisory conditions or on those circumstances in which mandatory reporting is required. Nor is it based on the need to share information about serious risks to others as part of multi-agency risk management approaches (for more on this see English, 1998; English, Jones & Patrick, 2003; Pimental & Muller, 2012). These are obviously critical components of effective supervision. This paper is concerned, however, with the circumstances in which the case manager might become aware of an issue that causes concern, but which does not trigger any formal response. These might include, for example, identifying behavioral signs of impending sexual offending such as establishing relationships with potential victims or with adult partners who have children, or engaging in activities that put the offender in closer proximity to victims. Other indicators might include increased alcohol or drug use, reduced compliance with treatment and supervision services, the loss of significant support systems, dysphoric mood states, as well as those behaviors that suggest active deviant sexual arousal, such as pornography use, the possession of fetishistic objects, self-reported masturbation to deviant fantasies, and so on (see Vess & Skelton, 2010). There are no practice guidelines available to guide decision making in such circumstances and the criteria for establishing when offender self-report can be relied upon (see below) and how seriously these behaviors should be regarded (and what should happen should they be observed) are often not clearly articulated. It is proposed that feedback data on these types of observations can be routinely and systematically collected, and considered against pre-determined thresholds. Further, it is suggested that the provision of feedback about progress to both supervisors and supervisees may be an effective intervention, in its own right, and one which potentially offers a more constructive response than simply increasing the levels of monitoring that are already in place.

This suggestion arises from a consideration of work conducted in the field of mental health, which over the last decade has seen the use of continuous assessment (or client feedback) methods to track client progress in treatment over time. Reese, Toland, and Slone (2010) have observed that the basic rationale for providing feedback about the progress, or otherwise, of clients is based on common sense - if information is available about what seems to be working, and what is not working, then both clients and practitioners can quickly and directly respond to problems. Although different types of feedback can be used (e.g., direct observation of client behavior or from the practitioners own reactions to the client, see Pinsof, Breunlin, Russell, & Lebow, 2011), standardized scales to assess progress throughout the course of treatment are being increasingly employed. These require the practitioner to clearly specify at the outset of treatment what clinically significant change (positive or negative) might look like, and then to create what have been called 'expected recovery curves' (Sundet, 2012) in relation to initial scores or severity. These can be graphically expressed and used to provide feedback to both therapists and clients about progress (see Harmon et al., 2007).

A key element of this type of system is the prediction of treatment failure, and it has been suggested that the collection of standardized data about progress can help to overcome the tendency for practitioners to overlook or disregard obvious signs of deterioration (Hatfield, McCullough, Plucinski, & Krieger, 2010) and increase their awareness of the risk of attrition (Lambert & Shimokawa, 2011). There is also consistent evidence that the provision of feedback consistently improves client outcomes, especially for those who are identified as at risk for terminating prematurely. For example, Miller, Duncan, Brown, Sorrell, and Chalk (2006) used continuous feedback to explore the impact of telephonic employee assistance services, reporting that the use of outcome feedback doubled the treatment effect size from 0.37 to 0.79, as well as significantly increasing the rate of client retention. In a meta-analysis of five major randomized trials, Lambert (2010) reported that as many as 45% of treatment groups which received feedback achieved clinically significant change, compared with only 22% of groups which received treatment as usual. For example, in the meta-analysis of 30 randomized clinical trials conducted in community settings reported by Sapyta, Riemer, and Bickman, (2005), the typical client in the feedback group was better off than 58% of the control group (although the effect size was small; d = .21).

Practical recommendations

In seeking to apply this type of approach to the supervisory process, a number of key pieces of information are required. First, it will be important to determine which components of dynamic risk might be monitored. Assessments such as the STABLE and the ACUTE (Hanson, Harris, Scott, & Helmus, 2007) identify a number of domains within which risk might be monitored, and an initial decision would be to determine which of these are most relevant to the particular supervisee. The next step would be consider the tools that are available to monitor these domains on a routine basis. Some measures might be readily adapted, for example, to assess dysphoric mood states (e.g., the Depression Anxiety Stress Scale, Lovibond & Lovibond, 1995), compliance with treatment (e.g., the supervisory alliance scale, Patton, Brossart, Gehlert, Gold, & Jackson, 1992), social support (see Canty-Mitchell, & Zimet, 2000), or substance use (e.g., urinalysis or self-report measures such as that developed by Brown, Meyer, Lippke, Tapert, Stewart, & Vik, 1998). These measures are relatively brief and have been widely used in other contexts. Single item measures for other factors that could be monitored, such as deviant sexual fantasy, masturbation, or use of pornography, may need to be specifically developed for this purpose, although there is a need to consider the issue of measurement error here given the low reliability of single item measures. Once the criteria for monitoring have been set, the next stage is to set some thresholds which would trigger a specific response from the supervisor. For example, if stress was identified as an acute dynamic risk factor and this significantly increased to a clinically significant level from one supervision contact to the next, then the supervisor might request another meeting to clarify what had been happening or consider a referral to a support agency. Alternatively, it might be possible to establish a baseline against which change could be assessed. Perhaps the most obvious starting point for collecting data of this type, however, is in relation to positive and negative emotional states. Not only has the technology to do this been developed in mental health settings, but dysphoria is commonly identified as an important antecedent for sex offending (see Howells, Day, & Wright, 2004; Proulx, McKibben, & Lusignan, 1996). Langton and Marshall (2000), for example, have observed that: "Emotions exert a pervasive influence on motivation and appraisal both at [the] pre-offence stage and throughout the unfolding offense chain ... both trait measures of affective dispositions and the identification of affective states during the offense are important in understanding sex offenders' cognitions" (p. 172). Empirical studies have supported this idea, with one study by Pithers, Kashima, Cumming, Beal, and Buell (1988) identifying strong emotional states as precursors to relapse in 89% of a sample of sex offenders (with anxiety/depression being most common in paedophiles). Further, a substantial proportion of rapists appear to have problems with anger (Ward & Hudson, 2000).

Discussion

The aim of this paper was to consider a new approach to enhance the current supervision of sex offenders in the community from non-treatment staff. There is a particular need to develop case work practice in this area in light of growing evidence that case management is, by itself, insufficient to prevent many offenders from committing new offenses. This literature is summarized by Lipsey and Cullen (2007) who concluded that there are only modest favorable effects for supervision when compared to no supervision (or when intensive supervision is compared to regular supervision). A key finding from this research, however, is that recidivism outcomes do appear to be better when both case work and/or treatment sessions are introduced to the supervisory process (see Jalbert, Rhodes, Flygare, & Kane, 2010). Thus, whilst supervisors should not be expected to become treatment providers, there may be value in them focusing their attention more on those aspects of dynamic risk that can change over time. Bonta, Rugge, Scott, Bourgon, and Yessine (2008) explained the disappointing findings of their meta-analysis of community correctional case management outcomes in terms of the failure of case managers to deliver interventions that were consistent with what is currently known about effective rehabilitation. Bonta and colleagues concluded that probation officers often spend too much time on the enforcement aspect of supervision and insufficient time engaging offenders in a process of behavior change. Using supervision sessions to routinely and formally consider feedback data on issues such as social support, mental health, and engagement with supervision might contribute positively to the rehabilitative process. It would encourage supervising officers to maintain not only a caring, but also a fair, trusting, and authoritative style with offenders which has shown to be associated with better outcomes in mandated settings (Skeem, Eno Louden, Polaschek, & Camp, 2007).

Case managers and supervisors are not, however, always well-placed or indeed qualified to provide treatment or rehabilitation services, and are often subject to significant constraints that restrict this from happening. For example, some correctional case managers carry large caseloads which prohibit them from spending sufficient time with supervisees to deliver rehabilitative interventions. Some of those who supervise offenders, such as police officers, may not have the therapeutic skills to provide appropriate intervention. Tracking the progress of offenders toward supervisory goals, and providing feedback about progress is an approach that can be built into current supervisory practice without too many additional demands on the supervisor or case manager.

One of the key differences between current practice and what is being proposed lies in the routine collection of systematic data about client progress and the setting of criteria by which progress can be assessed. This requires the development of case plans in which the markers of improvement or deterioration (increased and decreased risk) are clearly articulated. The current focus of supervision plans is often on the prevention of negative behavior (such as avoiding particular situations or people, or not thinking about certain topics), which makes progress difficult to assess. Not only is there a danger that this leads to a continuing focus on re-offending that has the potential to increase the salience of the deviance and paradoxically increase risk (Thornton, 1997), but the feedback that results is more likely to be negatively framed and to be perceived by the offender as critical. Jones (2009) has argued that some offenders (particularly those with narcissistic personality traits) are fragile in the face of confrontation, and can respond by attempting to re-establish a sense of power either through offending or engaging in offence-paralleling behavior. Alternatively, those who feel that they are being forced to engage in a change process may respond by becoming more entrenched in their conviction not to change. Rather, the provision of routine feedback might be most useful when it relates to progress toward goals which are both positive and pro-social.

Jones (2009) also notes that there is been relatively little emphasis given to identifying ways in which offenders have successfully desisted from offending, and that a useful starting point in any work with sex offenders is to consider what it is that is happening when the individual is not offending. The practitioner is then able to look for examples of when an individual has effectively managed his or her behavior (both before and after an offense) and develop a set of goals for the individual case based on what has worked in the past. Such recommendations resonate with the broad goal of client capacity building that has been articulated in the Good Lives Model (see Willis, Yates, Gannon, & Ward, 2013). Indeed, structured assessments of offenders' pursuit of 'primary goods' and their constitutive problems are beginning to emerge (see Yates, Prescott, & Ward, 2010), and these may provide opportunities to routinely collect data about progress towards relevant goals. Willis et al. (2013) give the example of how goals associated with achieving 'relatedness' (a commonly prioritized primary good among sexual offenders) can be included in case plans by operationalizing what it means to make more friends, re-connect with family, find a romantic partner, and so on. It will be important to progress this work, especially through the development of methods of measuring progress towards such goals.

An obvious concern that arises in any approach that relies heavily on self-report is the extent to which offenders will attempt to portray themselves in a favorable light. Lambert and Shimokawa (2011) have advised that it is important to be aware of those situations in which clients feel it may be in their interest to understate (or overstate) their problems and produce inaccurate ratings on feedback systems. This is an obvious issue in sex offender management, and as such it is suggested that feedback of this type is not used to determine the type of supervision that is offered, but rather as one source of information that can guide practice. It is worth noting, however, that self-report is likely to have greater validity when a strong therapeutic alliance exists (see Kozar & Day, 2012), and that methods to assess the strength of the alliance are available (see, for example, McGuire-Snieckus, McCabe, Catty, Hansson, & Priebe, 2007).

In summary, this paper considers the possibility that the routine collection of data on indicators of both protective factors and dynamic risk can assist with the development of effective supervisory practice. This data would need to be monitored over time and expected 'recovery curves' articulated (i.e., to specify the criteria for assessing when change, both positive and negative, has occurred). At the very least, it seems possible that the very process of collecting data about supervisory outcomes in such a systematic manner would prove to be an interesting and engaging activity (for both the case manager and offender). While some may express concerns about the additional work that might be implied, it is our view that these concerns are most frequently expressed when the connection between administrative tasks and the overarching goals of offender management are not explicit or when adequate training and support is not made available. It would not only ensure that supervisors paid careful attention to markers of risk and signs of deterioration that can lead to offending at every contact, but also ensure that there is a consistent focus on supporting the offender to implement changes in his or her life that reduce risk.

For offenders, there would be an opportunity to develop greater insight and control into the circumstances in which they are most at risk of committing new offenses. It is, however, evident that the adoption of such a system would constitute a major shift in service philosophy from one that is largely input-oriented (e.g., number of contacts, compliance with reporting requirements), to one that is truly outcome-based (i.e., to what extent has the level of risk diminished over the course of supervision?). Such an approach would help to improve the accountability of both supervisors and supervisees and would be broadly consistent with recent moves, such as the UK government's 'Breaking the Cycle' initiative (Ministry of Justice, 2010), towards systems of outcome based funding models across the criminal justice system. It is suggested, then, that there is a reasonable case to develop these ideas further such that they can be evaluated in practice. 

References

  1. Blasko, B. L., Jeglic, E. L., Mercado, C. C. (2011). Are actuarial risk data used to make determinations of sex offender risk classification?: An examination of sex offenders selected for enhanced registration and notification. International Journal of Offender Therapy and Comparative Criminology, 55, 676-692.
  2. Bonta, J., Rugge, T., Scott, T.-l., Bourgon, G., & Yessine, A. K. (2008). Exploring the black box of community supervision. Journal of Offender Rehabilitation, 47(3), 248-271.
  3. Brown, S. A., Meyer, M. G., Lippke, L., Tapert, S. F., Stewart, D. G. & Vik, P. W. (1998). Psychometric evaluation of the customary drinking and drug use record (CDDR): A measure of adolescent alcohol and drug involvement. Journal of Studies on Alcohol, 59(4), 427-438.
  4. Canty-Mitchell, J. & Zimet, G. D. (2000). Psychometric properties of the Multidimensional Scale of Perceived Social Support in urban adolescents. American Journal of Community Psychology, 28,391-400.
  5. Center for Sex Offender Management. (2008). The Comprehensive Approach to Sex Offender Management. Retrieved March 7, 2011, from http://www.csom.org/pubs/Comp_Approach_Brief.pdf
  6. Day, A., Hardcastle, L., & Birgden, A. (2012). Case management in community corrections: Current status and future directions. Journal of Offender Rehabilitation, 51, 484-495.
  7. Day, A., Vess, J., Carson, E., Powell, M., Casey, S., & Hobbs, G. (under review). Sex Offender Public Policy: From Law to Practice. Journal of Offender Rehabilitation.
  8. English, K. (1998). The Containment Approach: An Aggressive Strategy for the Community Management of Adult Sex Offenders, Psychology, Public Policy and Law, 4, 218-235.
  9. English, K., Jones, L., & Patrick, D. (2003). Community containment of sex offender risk: A promising approach. In B. J. Winick & J. Q. La Fond (Eds.), Protecting society from sexually dangerous offenders. Washington, DC: American Psychological Association.
  10. Erooga, M. (2008). A human rights-based approach to sex offender management: The key to effective public protection? Journal of Sexual Aggression, 14, 171-183.
  11. Hatfield, D., McCullough, L., Plucinski, A., & Krieger, K. (2010). Do we know when our clients get worse? An investigation of therapists' ability to detect negative client change. Clinical Psychology & Psychotherapy, 17, 25-32.
  12. Hanson, R. K., Harris, A. J. R., Scott, T. L. & Helmus, L. (2007). Assessing the risk of sexual offenders on community supervision: The Dynamic Supervision Project. Public Safety Canada 2007-05.
  13. Harmon, C. S., Lambert, M. J., Smart, D. M., Hawkins, E., Nielson, S. L., Slade, K., & Lutz, W. (2007). Enhancing outcome for potential treatment failures: Therapist- client feedback and clinical support tools. Psychotherapy Research, 17, 379 -392.
  14. Howells, K., Day, A., & Wright, S. (2004). Affect, emotions and sex offending, Psychology, Crime and Law, 10, 179-195.
  15. Jalbert, S., Rhodes, W., Flygare, C., & Kane, M. (2010). Testing probation outcomes in an evidence-based practice setting: Reduced caseload size and intensive supervision effectiveness. Journal of Offender Rehabilitation, 49, 233-253.
  16. Jones, L. F. (2009) Working with sex offenders with personality disorder diagnoses. In A. R. Beech, C. A. Leam, & K. D. Browne (Eds.), Assessment and treatment of sex offenders: A handbook. Chichester: Wiley.
  17. Kozar, C., & Day, A. (2012). The therapeutic alliance in offending behavior programs: A necessary and sufficient condition for change? Aggression and Violent Behavior, 17, 482-487.
  18. Lambert, M. J. (2010). Yes, it is time for clinicians to routinely monitor treatment outcome. In B. L. Duncan, S. D. Miller, B. E. Wampold, & M. A. Hubble (Eds.), The heart and soul of change. Delivering what works (2nd ed., pp. 239-266). Washington, DC: American Psychological Association Press.
  19. Lambert, M. J., & Shimokawa, K. (2011). Collecting Client Feedback. Psychotherapy, 48, 72-79.
  20. Langton, C. M., & Marshall, W. L. (2000). The role of cognitive distortions in relapse prevention programs. In D. R. Laws, S. M. Hudson and T. Ward (Eds.), Remaking Relapse Prevention with Sex Offenders (pp. 167-186). Thousand Oaks, CA: Sage.
  21. 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.
  22. Lovibond, S. H. & Lovibond, P. F. (1995). Manual for the Depression Anxiety Stress Scales. (2nd Ed). Sydney: Psychology Foundation.
  23. McGuire-Snieckus, R., McCabe, R., Catty, J., Hansson, L., & Priebe, S. (2007). A new scale to assess the therapeutic relationship in community mental health care: STAR. Psychological Medicine, 37, 85-95.
  24. McNeill, F., & Whyte, B., Connelly, M. (2008). Towards effective practice in offender supervision: source document. Retrieved 4/6/2012 from [DOC] from cjsw.ac.uk <http://www.cjsw.ac.uk/cjsw/files/Towards%20Effective%20Practice.doc>
  25. Miller, S. D., Duncan, B. L., Brown, J., Sorrell, R., & Chalk, B. (2006). Using outcome to inform and improve treatment outcomes. Journal of Brief Therapy, 5, 5-22.
  26. Ministry of Justice (2010). Breaking the Cycle: Effective Punishment, Rehabilitation and Sentencing of Offenders. London: HMSO.
  27. Palmiotto, M., & MacNichol, S. (2010). Supervision of Sex Offenders: A Multi-Faceted and Collaborative Approach. Federal Probation, 74, 27-30.
  28. Patton, M. J., Brossart, D. F., Gehlert, K. M., Gold, P. B., & Jackson, A. P. (1992). The Supervisory Working Alliance Inventory: A validity study. Paper presented at the annual meeting of the American Psychological Association, Washington, DC. (ERIC Document Reproduction Service No. ED360358).
  29. Petrunik, M., Murphy, L., & Fedoroff, J. P. (2008). American and Canadian approaches to sex offenders: A study of the politics of dangerousness. Federal Sentencing Reporter, 21, 111- 123.
  30. Pimentel, R., & Müller, J. (2010). The Containment Approach to Managing Defendants Charged with Sex Offenses. Federal Probation, 74, 24-26.
  31. Pinsof, W., Breunlin, D. C., Russell, W. P., & Lebow, J. (2011). Integrative Problem-Centered Metaframeworks Therapy II: Planning, Conversing, and Reading Feedback. Family Process, 50, 314-336.
  32. Pithers, W. D., Kashima, K. K., Cumming, G. F, Beal, L. S. and Buell, M. M. (1988). Relapse prevention of sexual aggression. In R. A. Prentky and V. L. Quinsey (Eds), Human Sexual Aggression: Current Perspectives. Annals of the New York Academy of Sciences, vol. 528 (pp. 244-260). New York: The New York Academy of Sciences.
  33. Proulx, J., McKibben, A., & Lusignan, R. (1996). Relationship between affective components and sexual behaviors in sexual aggressors. Sexual Abuse: A Journal of Research and Treatment, 8, 279-289.
  34. Reese, R. J., Toland, M. D., & Slone, N. C. (2010). Effect of client feedback on couple psychotherapy outcomes. Psychotherapy Theory, Research, Practice, Training, 47, 616-630.
  35. Sapyta, J., Riemer, M., & Bickman, L. (2005). Feedback to clinicians: Theory, research, and practice. Journal of Clinical Psychology, 62, 145-153.
  36. Skeem, J., Louden, J. E., Polashek, D., Camp, J. (2007). Assessing relationship quality in mandated community treatment: Blending care with control. Psychological Assessment, 19, 397-410.
  37. Sundet, R. (2012). Therapist Perspectives on the use of Feedback on Process and Outcome: Patient-Focused Research in Practice. Canadian Psychology, 53, 122-130.
  38. Taxman, F. S. (2008). No illusions: Offender and organisational change in Maryland's pro-active supervision efforts. Criminology & Public Policy, 7(2), 275-302.
  39. Taxman, F., Yancey, C., & Bilanin, J. E. (2006). Proactive community supervision in Maryland: changing offender outcomes. Retrieved 01/02/2012 from http://www2.dpscs.state.md.us/publicinfo/publications/pdfs/PCS_Evaluation_Feb06.pdf
  40. Thornton, D. (1997). Is relapse prevention really necessary? Paper presented at the meeting of the Association for the Treatment of Sexual Abusers, October, 1997, Arlington, VA.
  41. Trotter, C. (2006). Working with Involuntary Clients. Crows Nest: Allen & Unwin.
  42. Vess, J., & Skelton, A. (2010). Sexual and violent recidivism by offender type and actuarial risk: Reoffending rates for rapists, child molesters and non-contact offenders. Psychology, Crime and Law, 16, 541-554.
  43. Vess, J., Langskail, B., Day, A., Powell, M., & Graffam, J. (2011). A comparative analysis of Australian sex offender legislation for sex offender registries. Australian and New Zealand Journal of Criminology, 44, 404-424.
  44. Ward, T., & Hudson, S. (2000). A self-regulation model of relapse prevention. In D. R. Laws, S. M. Hudson, and T. Ward (Eds.), Remaking Relapse Prevention with Sex Offenders: a Sourcebook (pp. 79-101).Thousand Oaks, CA: Sage.
  45. Willis, G. M., Yates, P. M., Gannon, T. A., & Ward, T. (2013). How to integrate the Good Lives Model into treatment programs for sexual offending: An introduction and overview. Sexual Abuse, 25, 123-42.
  46. Yates, P. M., Prescott, D. S., & Ward, T. (2010). Applying the Good Lives and Self Regulation Models to sex offender treatment: a practical guide for clinicians. Brandon, VT: Safer Society Press.
  47. Zgoba, K., Witt, P., Dalessandro, M. & Veysey, B. (2008). Megan's Law: assessing the practical and monetary efficacy, New Jersey Department of Corrections. Retrieved 05/05/2011 from https://www.ncjrs.gov/pdffiles1/nij/grants/225370.pdf.

Author address

Professor Andrew Day
School of Psychology
Faculty of Health
Deakin University
Geelong Waterfront Campus
Geelong, Victoria 3220, Australia



 

alttext