Ashford 5: - Week 4 - Assignment Principles of Effective Intervention There are four general principles of effective intervention that have become organizing concepts of community corrections. They have stimulated what has become known as the \"what works\" movement. Write a paper outlining the four general principles of the \"what works\" movement. Thesis: Your thesis (which is part of your first paragraph) should list the four principles of the effective intervention. Body: The body of your paper (your entire paper excluding the thesis and conclusion) should give a thoughtful analysis of the four general principles of effective intervention in a sequential order. Explain what the principles mean. Look for examples. Determine if the principles are effective. Explain why the principles either are, or are not, effective. Conclusion: The conclusion (which is part of the last paragraph) should, at the very least, restate the thesis. The paper must be four pages in length (excluding title and reference pages) and formatted according to APA style. You must use at least three scholarly resources from the Ashford University Library, other than the textbook, to support your claims. Cite your sources within the text of your paper and on the reference page. For information regarding APA, including samples and tutorials, visit the Ashford Writing Center, located within the Learning Resources tab on the left navigation toolbar. 467942 CJBXXX10.1177/0093854812467942Crimi nal Justice And BehaviorSperber et al. / Interaction Between Risk And Dosage 2012 Examining the Interaction between Level of Risk and Dosage of Treatment Kimberly Gentry Sperber Talbert House Edward J. Latessa University of Cincinnati Matthew D. Makarios University of Wisconsin-Parkside The risk principle suggests that effective correctional interventions should vary the intensity of treatment by offender risk, with higher risk offenders receiving more intense services than lower risk offenders. Although much research indicates that programs that target higher risk cases are more likely to be effective, relatively little research has examined the impact of varying levels of treatment dosage by risk. Consequently, this study seeks to identify the number of hours of treatment that are necessary to reduce recidivism in a sample of offenders placed in a residential community corrections facility. The sample for this study includes 689 adult male offenders successfully discharged from a Community-Based Correctional Facility in Ohio. The results provide support for providing higher levels of dosage to high-risk offenders, with substantial reductions in recidivism for high-risk offenders receiving 200 or more hours of treatment. Keywords: risk principle, dosage, correctional treatment, recidivism. T he substantial amount of empirical research that has examined community-based correctional treatment programs suggests that adherence to the risk principle is a key characteristic of many effective programs (see Lowenkamp & Latessa, 2005, for a review). The risk principle suggests that correctional practitioners should differentiate services by offender risk, with higher risk offenders receiving more intense services than lower risk offenders (Andrews, Bonta, & Hoge, 1990). To accomplish this, correctional practitioners must first identify the risk level of each offender and then provide increasing service dosage as risk level increases. Although the extant research regarding the assessment of criminogenic risk is substantial (Bonta, 2002), the body of research that has sought to identify appropriate dosage levels of treatment is limited. As a result, many community-based correctional treatment programs invest resources in allocating services by risk level with limited empirical research to guide them. This study seeks to build upon the limited body of research on treatment dosage by examining the impact of allocating treatment dosage by risk level in a sample of offenders placed in a residential community corrections facility. In doing so, it will provide practitioners with a better understanding of the number of treatment hours that are necessary to effectively reduce recidivism. AUTHORS' NOTE: Correspondence concerning this article should be addressed to Kimberly Gentry Sperber, Talbert House, 2600 Victory Parkway, Cincinnati, OH 45206, USA; e-mail: kimberly.sperber@talberthouse.org. CRIMINAL JUSTICE AND BEHAVIOR, Vol. 40, No. 3, March 2013, 338-348. DOI: 10.1177/0093854812467942 2013 International Association for Correctional and Forensic Psychology 338 Downloaded from cjb.sagepub.com at Ashford University on July 20, 2015 Sperber et al. / INTERACTION BETWEEN RISK AND DOSAGE 339 The Risk Principle Research by Andrews, Bonta, and Gendreau has helped translate research into practice by identifying some broad principles or operational strategies for correctional programs (see Cullen & Gendreau, 2000, for a review). Simply stated, these strategies include (a) targeting higher risk offenders and providing higher risk offenders more intensive programs, (b) targeting relevant criminogenic risk factors, and (c) implementing a cognitivebehavioral approach with a high degree of fidelity. The first of these practices, often referred to as the risk principle, is the focus of the current research. The risk principle (see Andrews & Bonta, 2006) has three key elements: (a) target offenders with a higher probability of recidivism, (b) provide most intensive treatment to higher risk offenders, and (c) avoid intensive treatment for lower risk offenders. Many programs seek to adhere to the risk principle by targeting primarily moderate- and high-risk cases. Although a step in the right direction, the risk principle also suggests that it is important to allocate the amount of treatment based on risk. In other words, higher risk offenders should receive more services than their lower risk counterparts. Targeting Higher Risk Cases Research has clearly demonstrated that correctional interventions are more likely to have a positive impact on moderate- and high-risk offenders than low-risk offenders (BrusmanLovins, Lowenkamp, Latessa, & Smith, 2007; Lowenkamp & Latessa, 2004). For example, treatment programs that target higher risk offenders produce better outcomes (Latessa, Brusman-Lovins, & Smith, 2010; Lipsey, 2009; Lowenkamp, Latessa, & Smith, 2006). Furthermore, within treatment programs, the effects on recidivism are greatest for high-risk offenders and minimal, if not detrimental, for low-risk offenders (Latessa et al., 2010; Lovins, Lowenkamp, & Latessa, 2009; Lowenkamp & Latessa, 2005). Finally, treatment programs that use risk assessment instruments to identify appropriate clients have been found to be more effective at reducing recidivism (Latessa et al., 2010; Lowenkamp, Latessa, & Smith, 2006). Issues Related To the Dosage Question Identifying who requires more services is only half of the equation. In other words, knowing that higher risk offenders should receive more services and supervision than lower risk offenders is not the same as knowing how much more service and supervision to provide to higher risk offenders. Most prior research has centered on the duration of treatment. In general, the longer someone is in treatment, the stronger the effects (Hser, Grella, Chou, & Anglin, 1998; Simpson, Joe, & Brown, 1997; Zerger, 2002). The caveat, however, is that if treatment extends too long, the success rates start to diminish (Loughran et al., 2009). The other problem is that some correctional programs do not have control over the amount of time someone is in the program due to sentence length and other constraints. Practitioners looking to the criminological literature for guidance are likely to find few studies that provide practical guidelines for matching treatment dosage to offender risk. Related to the issue of duration of treatment is the nature of risk factors. In general, there are two basic types of risk factors: static factors and dynamic factors. Static factors are Downloaded from cjb.sagepub.com at Ashford University on July 20, 2015 340 Criminal Justice and Behavior those factors that are related to risk of reoffending and do not change. Dynamic factors, or criminogenic needs, are related to recidivism and can change. Some examples are whether an offender is currently unemployed or currently has a drug/alcohol problem. There are two types of dynamic factors: acute factors that can change relatively quickly and stable factors that require more time and effort to change. For example, if someone is unemployed, it is conceivable that he or she could interview and get a new job almost immediately. The offender went from being unemployed (risk factor) to employed (no risk factor) very quickly. On the other hand, other dynamic factors, such as procriminal attitudes, lacking self-control, and having poor problem-solving or coping skills, require more time and effort to change and thus require more dosage of treatment to change. Evidenced-based treatment programs that focus on teaching offenders prosocial skills require a good deal of time spent observing role modeling as well as engaging in graduated role plays where they practice their skills in increasingly difficult scenarios (see Lowenkamp, Lovins, & Latessa, 2009; Wanberg & Milkman, 2007). Furthermore, when offenders present with multiple risk factors (e.g., substance abuse, anger management, and domestic violence), it becomes difficult to balance what the offender needs to change with the amount of time that the offender is available to the treatment provider. As a result, determining the appropriate dosage of treatment to offenders requires optimizing the balance between the time needed to create behavioral change, the length of time the offender is under supervision, and the intensity of the intervention (i.e., the percentage of the offender's daily time that is spent engaging in treatment activities). Research on Dosage by Risk In a study of 13,676 offenders from 97 treatment programs, Lowenkamp, Latessa, and Holsinger (2006) found that programs that did not adhere to any dimensions of the risk principle failed to reduce recidivism. Furthermore, programs were more effective if they (a) targeted higher risk cases, (b) provided increased treatment to highest risk cases, and (c) increased treatment length for the highest risk cases. Lipsey, Landenberger, and Wilson (2007) conducted a meta-analysis of over 40 cognitive behavioral programs and found that programs that targeted moderate and high-risk offenders were more successful. Furthermore, they found that increases in sessions per week or total programming hours resulted in increased effect sizes. Although no interaction was tested, the direct effects suggest that effective programs that targeted both higher risk offenders and increased treatment dosage were more effective. Although these two studies indicate general support for providing increased dosage to higher risk offenders, they fail to provide practitioners with operational guidelines to determine the number of hours of service to provide to a high-risk population. To date, there are two studies that provide quantifiable guidelines for service delivery based on risk. The first is a meta-analysis of 200 studies examining the effect of correctional treatment on serious juvenile offenders (Lipsey, 1999). Not only did Lipsey seek to identify whether correctional treatment was capable of reducing recidivism, he also sought to identify program characteristics that resulted in larger recidivism reductions. His analysis revealed that one of the program characteristics that affected the magnitude of recidivism reduction was program duration. Specifically, programs that lasted a minimum of 6 months demonstrated greater effect sizes. This was true for institutional programs and noninstitutional programs. Downloaded from cjb.sagepub.com at Ashford University on July 20, 2015 Sperber et al. / INTERACTION BETWEEN RISK AND DOSAGE 341 The results of the study also indicate that approximately 100 hours of programming was necessary for recidivism reduction. In the second study, Bourgon and Armstrong (2005) examined treatment dosage and recidivism in a sample of 620 incarcerated adult males and attempted to identify the number of treatment hours required to reduce recidivism at different risk levels. The authors compared the 12-month recidivism rate of 482 offenders who received prison-based treatment to the recidivism rate of 138 untreated offenders. The study results demonstrated that 100 hours of treatment was sufficient to reduce recidivism for offenders deemed to be moderate risk or to have few needs (defined as three or less). For offenders deemed to be high risk with fewer needs or moderate risk with multiple needs (defined as more than three), 200 hours of treatment were required to reduce recidivism. For the high-risk and high-need offenders, 300 hours of treatment did not produce reductions in recidivism. Although Bourgon and Armstrong's (2005) study suggests dosage cutoffs at 100 or 200 hours based on the risk/need levels, questions remain as to whether those prison-based findings apply to community-based programs. Thus, the current study examines the interaction between treatment dosage and risk level in a community-based residential treatment program. More specifically, this study examines whether Bourgon and Armstrong's (2005) levels of dosage are generalizable to a sample of offenders released from a communitybased correctional center and whether this dosage level varies in its effect by offender level of risk. Method Research Question The risk principle suggests that effective correctional interventions should vary the intensity of treatment by offender risk, with higher risk offenders receiving more intense services than lower risk offenders. Although much research indicates that programs that target higher risk cases are more likely to be effective, relatively little research has examined the impact of varying levels of treatment dosage by risk. That is, a strong empirical foundation for identifying appropriate dosage in a community-based treatment setting does not yet exist. Consequently, this study seeks to identify the number of hours of treatment that are necessary to reduce recidivism in a sample of offenders placed in a residential community corrections facility. Setting The sample for this study includes 689 adult male offenders successfully discharged from a Community-Based Correctional Facility (CBCF) in Ohio between August 30, 2006 and August 30, 2009. Ohio law established CBCFs as a sentencing alternative for individuals convicted of a felony that does not carry a mandatory prison sentence. The CBCF in this study serves felony probationers from three rural counties, and the primary focus of the facility is the provision of correctional treatment. The program targets criminogenic needs such as antisocial attitudes, substance abuse, anger management, and employment. The average length of stay is 4 months. The program uses a cognitive-behavioral treatment modality, and all core treatment groups use manualized curricula. Examples of curricula in Downloaded from cjb.sagepub.com at Ashford University on July 20, 2015 342 Criminal Justice and Behavior Table 1: Descriptive Statistics Variable N Percent 612 77 89 11 138 427 124 20 62 18 139 300 250 20 44 36 374 315 54 46 Metric Variables M SD Range Age Treatment length 33.1 3.4 9.3 .68 18 to 63 1 to 5 Race White Minority LSI Risk Low Moderate High Dosage level Low (0 to 99) Moderate (100 to 199) High (200+) Return to prison Yes No Note. LSI = Level of Service Inventory. use include Charting a New Course (Truthought, 1999) to address irresponsible attitudes and decision making and Criminal Conduct and Substance Abuse Treatment (Wanberg & Milkman, 2007) to address substance abuse. Measures Measures for the current study come from three sources. Independent variables were gathered from agency electronic treatment records and from hard copy case files. The ODRC provided outcome data on recidivism using a state database on prison intakes. Control variables. Table 1 presents descriptive statistics for the sample. Demographic data indicate that the sample is predominately Caucasian (88.8%) and the average age is 33.1 years. The minimum follow-up period for recidivism was 12 months, with an average follow-up period of 19 months. Risk level. At intake, all offenders admitted into the program are assessed for risk using the Level of Service Inventory-Revised (LSI-R; Andrews & Bonta, 1995). The LSI-R is a structured interview that consists of 54 items that assess 10 risk/need domains. Research has found that the LSI-R consistently predicts recidivism across settings and offender populations (for a review, see Gendreau, Goggin, & Smith, 2002; Lowenkamp & Bechtel, 2007; Lowenkamp et al., 2009). Program staff uses the instrument to produce a composite risk score that delineates an offender's probability of reoffending as low, low/moderate, moderate, moderate/high, or high. Because there were few offenders designated as either low risk or high risk in the current sample, we collapsed the data into three risk categories: low, moderate, and high. Low-risk offenders were combined with the low/moderate-risk offenders to create the low-risk group, and the high-risk offenders were combined with the Downloaded from cjb.sagepub.com at Ashford University on July 20, 2015 Sperber et al. / INTERACTION BETWEEN RISK AND DOSAGE 343 moderate/high-risk offenders to create the high-risk group. Table 1 indicates that 20% of the current sample were low risk, 44% were moderate risk, and 36% were high risk. Treatment dosage. Treatment dosage measures categories that identify the number of hours of group treatment each offender received using Bourgon and Armstrong's (2005) categories. The low-dosage group had between 0 and 99 hours of treatment, the moderatedosage group had between 100 and 199 hours, and the high-dosage group had 200 or more hours of treatment. There were 138 offenders in the low-dosage group, 427 in the moderatedosage group, and 124 offenders in the high-dosage group. Recidivism. The measure of recidivism used in the current study is return to prison. This measure was gathered from a state database and was chosen because it was the most valid and reliable measure available. Although incarceration data can include noncriminal technical violations, it provides a valid measure of recidivism because the sentencing structure of CBCFs in Ohio typically involves incarceration if the offender gets into trouble again. In fact, CBCFs are designed to reduce prison crowding by diverting offenders into programming and returning them to the community. Thus, a valid outcome measure is whether the CBCF achieved its goal by keeping offenders out of prison. Additionally, return to prison was the most reliable measure available. Arrest data were available only at the county level, which involved collecting data from agencies with different reporting practices. County-level arrest records also were problematic when offenders moved out of the reporting counties. On the other hand, reconviction resulting in incarceration in Ohio is consistently tracked statewide and available through the Ohio Department of Rehabilitation and Corrections' (ODRC) reporting website. Data Analysis This research seeks to examine the impact of treatment dosage on recidivism. To answer this research question, the current analyses use logistic regression to examine whether the level of treatment dosage predicts recidivism while controlling for the level of risk, age, and minority status. Next, since the risk principle suggests increased dosage should benefit higher risk cases, an interaction term is entered into the regression equations to examine whether the impact of treatment dosage increases by risk level. Results The goal of this research is to examine the impact of treatment dosage on recidivism at different risk levels. Table 2 presents logistic regression equations that predict the odds of recidivism occurring. The first series examines the predictive power of the control variables alone. Together, the control variables provide a significant model fit (2 = 34.65) and suggest that a modest portion of the variation in the odds of recidivating are explained by these factors (Nagelkerke R2 = .066). The second series includes the treatment dosage variables. The significant step chi-square (2 = 9.70) indicates an increase in model fit and explained variation when the dosage variables are added (Nagelkerke R2 = .083). These results suggest that net of control variables, a 38% reduction in odds of recidivism is observed for cases receiving 200+ hours of treatment dosage (Exp B = .62). Furthermore, Downloaded from cjb.sagepub.com at Ashford University on July 20, 2015 344 Criminal Justice and Behavior Table 2:Logistic Regression Predicting Any Return to Prison Variable b SE Wald Exp(B) Age -.03 .01 11.26*** .97 Minority .28 .25 1.29 1.32 Moderate risk .48 .21 5.38** 1.62 High risk 1.09 .26 17.39*** 2.99 100 to 199 treatment hours 200+ treatment hours Treatment Hours Risk Constant .25 .35 .53 1.29 Model chi-square 34.65*** Step chi-square Nagelkerke R2 .066 N 689 b -.03 .27 .64 1.36 -.25 SE Wald Exp(B) .01 12.55*** .25 1.17 .22 8.30** .30 20.94*** .22 1.36 -.48 .24 .48 .38 3.96** 1.57 .97 1.31 1.89 3.79 .78 b -.03 .27 .65 1.42 -.23 SE Wald .01 12.55*** .25 1.17 .26 6.29 .61 5.33 .29 .64 .62 -.41 .57 -.03 .25 1.61 .46 .40 44.35*** 9.70** .083 689 .53 .02 1.36 Exp(B) .97 1.31 1.93 4.15 .80 .66 .97 1.59 44.37*** .016 .083 689 *p < .10. **p < .05. ***p < .01. Percent Returned to Prison 0-99 Tx hours 100 90 80 70 60 50 40 30 20 10 0 0-99 Tx hours 100-199 Tx hours 200+ Tx Hours 100-199 Tx hours 200+ Tx Hours low moderate high Overall 39 26 52 45 43 81 57 46 43 48 Figure 1: Percentage Returned to Prison by Treatment Dosage and Risk Level ** Low risk cases that received 200+ hours of treatment and high risk cases that received less than 100 hours of treatment are excluded because of the small number of cases in these categories (n < 10). although the Wald statistic for moderate dosage (100 to 199 hours) is not significant, the coefficients suggest that net of control variables, there is a 22% reduction in the odds of recidivism (Exp B = .78) for this group of cases. The last series in Table 2 examines the interaction between treatment dosage and risk level. The risk principle suggests that the interaction between risk and dosage should indicate greater effects of dosage for higher risk cases. The results from the third model in Table 2 do not provide support for the interaction between dosage and risk. The stepwise chi-square (2 = .016) is very small and suggests that almost no improvement to model fit is observed when adding the interaction term into the model. The coefficient for the interaction term (b = -.03) also fails to reach significance and indicates that the effect of treatment dosage does not vary by risk in these data. In all, the results here suggest that higher levels of dosage result in reductions of recidivism for all risk levels. To better understand the relationship between risk and dosage, Figure 1 provides a visual representation of the impact of dosage on recidivism by risk level. It presents the percentage Downloaded from cjb.sagepub.com at Ashford University on July 20, 2015 Sperber et al. / INTERACTION BETWEEN RISK AND DOSAGE 345 of offenders who recidivated by treatment dosage levels at different levels of risk. It is important to note that a small number of offenders fell into categories on the ends of each spectrum. In categories with a small number of cases (i.e., low-risk cases that received high dosage and high-risk cases with low dosage), percentages tend to become unstable and should be interpreted with caution. For this reason, the outliers are not depicted in Figure 1. Given the caveat of limited generalizability to these categories, the figure indicates lower rates of recidivism with higher dosage levels at all three risk levels. A 13 percentage point reduction in recidivism is observed for low-risk cases when dosage increased from minimal (less than 99 hours) to moderate (from 100 to 199 hours of treatment). Reductions in recidivism were more modest for moderate-risk offenders, with an overall drop of 9 percentage points as cases moved from the lowest level of dosage to the highest level of dosage. Of particular importance is that the largest reduction in recidivism from dosage occurs for the group of high-risk offenders who received the highest levels of dosage. That is, the recidivism rate for high-risk offenders moves from 81% to 57% when treatment hours are increased from 100 to 199 hours to 200 or more hours. This indicates a reduction of 24 points in the percentage of offenders who recidivated for those who received the highest level of dosage. These findings provide support for providing high-risk cases with over 200 hours of treatment dosage. They also suggest that increasing dosage results in reductions in recidivism for all risk levels. Discussion This research sought to examine the interaction between treatment dosage and risk level in a sample of offenders who attended a community corrections facility that used a cognitivebehavioral approach. The risk principle suggests that reductions in recidivism will increase when higher risk cases receive more dosage. Although the findings from this research indicate increasing dosage resulted in reductions in recidivism, the examination of the interaction between dosage and risk provided limited support for this hypothesis. It is worth noting that this study is not without its limitations. The first limitation involves the generalizability of the current sample. The men in the sample were from a single program serving only three rural counties in the state of Ohio. Clearly, future research should seek to replicate these methods in other areas and with other populations. Still, it is worth noting that the findings presented here are consistent with prior research that has examined treatment dosage in incarcerated populations (Bourgon & Armstrong, 2005). The second limitation is that the outcome in the current study was return to prison, which included new criminal behavior as well as technical violations. The presence of new criminal charges, particularly for serious felony offenses, would provide a substantively different measure of recidivism since it involves crime that poses a great cost to society. Unfortunately, reliable measures of felony arrests were not available in the current study. We chose return to prison because it provided a reliable indication of recidivism given the limitations of available arrest data. Furthermore, the current outcome of return to prison does provide an answer as to whether the program was able to fulfill its intended mission to divert prison-bound offenders. The third limitation is the definition of treatment dosage used in the study. Because there has been little research to date on the impact of varying dosage on correctional outcomes, Downloaded from cjb.sagepub.com at Ashford University on July 20, 2015 346 Criminal Justice and Behavior a standardized definition of dosage does not yet exist in corrections. In addition, if we look to other disciplines for guidance, we find varying approaches to measuring treatment dosage. For example, the psychotherapy literature typically defines dosage by the number of sessions attended by the participant (Hansen, Lambert, & Forman, 2002). On the other hand, the substance abuse treatment literature often defines dosage as the number of days in treatment (e.g., Hser et al., 1998). For this study, we chose to measure the number of hours of participation in group treatment services. This was for three reasons. The first reason was that sessions can vary in length within residential programs. Because treatment was individualized based on risk and need in this facility, two clients could conceivably attend the same number of sessions but spend different amounts of time in treatment. Relying only on the number of sessions attended could mask these differences. The second reason was similar to the first in that individualization of treatment could result in clients spending the same number of days in the facility but spending varying amounts of time in treatment services during their stay. Again, relying on the number of days alone could mask differences in the total amount of treatment received while in the program. The final reason was that there is precedent from two previous studies for measuring correctional treatment dosage in hours (see Bourgon & Armstrong, 2005; Lipsey, 1999). In sum, relying on the number of hours of treatment received provided the most accurate and standardized measure of treatment dosage while providing a method of comparison to previous findings in the correctional literature. Notwithstanding the limitations of this study, the results have several important implications for correctional programming. First, increasing dosage had general impacts at all risk levels. This finding is consistent with prior research that demonstrates the benefit of providing increased dosage in correctional treatments that target offender populations (e.g., Lipsey et al., 2007). All too often resource constraints limit the ability of correctional treatments to provide intensive programming with high fidelity. This research suggests that investing resources in increased dosage and intensive programming is money well spent because it reduces returns to prison as well as reduces the threat that the offender poses to engage in new criminal behavior in the community. A second important finding is that the impact of dosage was largest for offenders who were high risk to recidivate and who received the highest level of dosage. As Figure 1 illustrates, the greatest reduction in recidivism was achieved in high-risk cases that received over 200 hours of treatment. A related finding of interest is that this study showed an impact of dosage on high-risk offenders when treatment hours reached only 200 or more hours in a community-based residential facility. This differs from the Bourgon and Armstrong (2005) study that found a need for more than 300 hours to reduce recidivism for high-risk/high-needs offenders in a prison setting. Although differing methodology between the two studies limits our ability to make direct comparisons, the finding that 200 hours of service reduces recidivism is of particular importance to community-based programs that are limited in their ability to provide more than 300 hours of treatment to offenders. Also of interest, the current results suggest that increasing dosage from minimal to moderate levels was effective at reducing recidivism in low-risk cases. This finding may be troubling for correctional practitioners who possess limited resources and seek to minimize the amount of dosage that low-risk cases receive. Although this study does indicate that low-risk cases benefit from moderate dosage levels, there are two important issues to remember here. First, recall that the low-risk category of offenders contained a mix of Downloaded from cjb.sagepub.com at Ashford University on July 20, 2015 Sperber et al. / INTERACTION BETWEEN RISK AND DOSAGE 347 low- and low/moderate-risk offenders. Further examination of the characteristics of offenders who fell into the group of low-risk offenders receiving 100 to 199 hours of treatment revealed that more than 70% of these individuals scored on the higher end of the low/ moderate scale (i.e., a score of 20 to 23 out of a range of 14 to 23). This means that the offenders categorized as low risk in this study may more closely resemble moderate-risk offenders. Second, this research clearly indicates that increasing dosage in high-risk cases provides greater reductions in recidivism. Stated differently, although increasing dosage in low-risk cases may reduce recidivism, the current research suggests that greater returns on outcome are observed when high-risk cases are targeted for increased dosage. As a result, this research indicates that the most efficient use of resources is to target high-risk cases. Despite the contribution of the current study, however, a number of questions regarding the implementation of risk-based dosage remain unanswered. First, the field has not empirically identified what activities and services count as dosage. For example, this study did not include case management sessions as dosage since typical case management practice does not incorporate cognitive-behavioral techniques. Second, research has not yet identified how to count dosage outside of a traditional treatment environment, such as while on probation or parole, nor has research investigated the relative impact of the sequence of dosage delivered as an offender moves across the system (e.g., from prison to a halfway house to postrelease supervision). Third, research has yet to identify whether there is a saturation effect, even for high-risk offenders. In other words, it may be of value to practitioners to know at what point they should expect to see diminishing returns on recidivism with the continued provision of services. Given these unanswered questions, correctional researchers should continue to partner with practitioners to outline a comprehensive research agenda designed to help move the field from a conceptual understanding of the risk principle to effective execution of the risk principle. 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Treatment retention and follow-up outcomes in the Drug Abuse Treatment Outcome Study (DATOS). Psychology of Addictive Behaviors, 11, 294-307. Truthought. (1999). Charting a new course. Roscoe, IL: Author. Wanberg, K., & Milkman, H. (2007). Criminal conduct and substance abuse treatment: Strategies for self-improvement and change: Pathways to responsible livingThe provider's guide. Thousand Oaks, CA: SAGE. Zerger, S. (2002). Substance abuse treatment: What works for homeless people? A review of the literature. National Health Care for the Homeless Council. Retrieved from http://homeless.samhsa.gov/ResourceFiles/bqmqhxpf.pdf Kimberly Gentry Sperber, PhD, currently works as the Chief Research Officer for Talbert House, a nonprofit agency located in Southwest Ohio providing programs in community corrections, mental health, substance abuse, and welfare-towork. Her responsibilities include training staff on best practices, helping staff to operationalize research into practice, measuring program effectiveness, and analyzing outcomes data. Edward J. Latessa, PhD, is professor and director of the School of Criminal Justice at the University of Cincinnati. Over the past three decades, he has published more than 140 works in the areas of criminal justice, corrections, offender assessment, juvenile justice, and program evaluation. He is coauthor of seven books and has directed more than 150 funded research projects. He served as President of the Academy of Criminal Justice Sciences in 1989-90 and has received numerous awards. Matthew D. Makarios is an assistant professor in the criminal justice department at the University of Wisconsin-Parkside. He holds a PhD from the University of Cincinnati. His research interests focus on evidence-based corrections and life-course criminology. He has had recent research appear in Crime & Delinquency and Justice Quarterly. Downloaded from cjb.sagepub.com at Ashford University on July 20, 2015 Juvenile Justice News Applying the Principles of Effective Intervention To Juvenile Correctional Programs By Jennifer A. Pealer and Edward J. Latessa I n 1989, Gendreau and Andrews developed the Correctional Program Assessment Inventory (CPAI), This tool is designed to evaluate tbe integrity of a correctional program to determine tbe degree to wbich it meets certain principles. Over the years, the authors along with researchers from the University of Cincinnati have used the CPAI to assess hundreds of correctional programs. A total of 107 juvenile correctional programs in 17 states were assessed beginning May 1997 to June 2004. A large portion of the programs (56 percent) served males and females, 38,5 percent served only males, and 5.5 percent, only females. A wide range of programs were assessed, including those operated by both government and private agencies, institutional and community-based programs (both residential and nonresidential), programs serving specific offender populations, sucb as sex offenders, as well as those serving a more general cross section of delinquent offenders. The programs ranged in size from a group bome with eight beds to a diversion program serving more than 350 youths at one time. Tbe programs also covered a wide geograpbic area and included those located in small towns, as well as urban and rural areas. The 107 programs also offered a wide array of services, including, but not limited to: drug and alcobol, mental health, school and education, sexual behavior, family counselIng, individual counseling, anger management, domestic violence, life skills and antisocial thinking/attitudes. While the juvenile programs were not randomly selected, there is no reason to believe that the results are not reflective of tbe juvenile programs across tbe United States, 26 December 2004 Corrections Today The Principles of Effective Intervention During tbe past two decades, there bas been renewed interest in examining correctional researcb. These efforts have been led by researchers sucb as Gendreau, Andrews, Cullen, Lipsey and others.' Much evidence bas been generated, leading to tbe conclusion that many rehabilitation programs have, in fact, produced significant reductions in recidivism, Tbe next critical issue became the identification of those characteristics most commonly associated with effective programs. Through the work of numerous scholars (Andrews et al., 1990; Cullen and Gendreau, 2000; Lipsey 1999), several "principles of effective intervention" have been identified. These principles can be briefly categorized as the following: Risk principle Treatment interventions should be used primarily with higher risk offenders; Need principle Target the known crimlnogenic predictors of crime and recidivism; Treatment principle Treatment and services should be behavioral in nature; and Fidelity principle Program integrity sbould be maintained throughout tbe delivery of services. Examining Program Quality Few would argue tbat the quality of a correctional intervention program has no effect on outcome. Nonetheless, correctional researchers bave largely ignored tbe measurement of program quality. Traditionally, quality has been measured through process evaluations. This approach can provide useful information about a program's operations; however, tbese types of evaluations often lack the "quantifiability" of outcome studies. Previously, researcbers' primary issue has been tbe development of criteria or indicators by whicb a treatment program can be measured. Wbile traditional audits and accreditation processes are one step in tbis direction, tbus far, tbey have proved to be inadequate. For example, audits can be an important means to ensure if a program is meeting contractual obligations or a set of prescribed standards; however, these conditions may not have any relationsbip to reductions in recidivism. It is also important to note tbat outcome studies and assessment of program quality are not necessarily mutually exclusive. Combining outcome indicators witb assessments of program quality can provide a more complete picture of an intervention's effectiveness (Latessa and Holslnger, 1998). Fortunately, tbere bas been considerable progress in identifying tbe cbaracteristics of effective programs.^ The Correctional Program Assessment Inventory Tbe CPAI was developed by Gendreau and Andrews (1989) and is a tool used to ascertain bow closely a correctional treatment program meets tbe principles of effective correctional treatment (Gendreau, 1996). There are six primary sections of the CPAI, including: Program Implementation The first area of the CPAI examines tbe program leadersbip and the design and implementation of tbe program. Offender Pre-Service Assessment The second section of tbe instrument looks at tbree areas regarding pre-service assessment: selection of program participants; the assessment of risk, need and personal cbaracteris- tics of the offender; and the manner in which these characteristics are assessed. Program Characteristics This section of the CPAI covers almost one-third of the items on the instrument. This area examines whether the program targets criminogenic behaviors and attitudes, the types of treatment used to target these behaviors and attitudes, specific treatment procedures, and the use of behavioral techniques. Staff Characteristics This staff area of the CPAI concerns the qualifications, experience, stability, training and involvement of the program staff. Evaluation The evaluation section centers on the types of quality assurance mechanisms in place and whether the program evaluates and monitors performance. Other Items The final section in the CPAI includes miscellaneous items pertaining to the program such as ethical guidelines, the comprehensiveness of the files, and stability in funding, programming and community support. Each section of the CPAI is scored as either "very satisfactory" (70 percent to 100 percent), "satisfactory" (60 percent to 69 percent), "needs improvement" (50 percent to 59 percent) or "unsatisfactory" (less than 50 percent). The scores from all six areas are totaled and the same scale is used for the overall assessment score. It should he noted that not all of the six areas are given equal consideration. Data for the CPAI are collected through structured interviews with selected program staff and participants. Other sources of information included the examination of representative case files and other selected program materials (e.g., assessment tools, treatment curricula), and observation of groups. Once the information is collected, each program is scored. Results Eigure 1 shows the average score of each of the six subcomponents of the CPAI along with the overall score. In the area of implementation, the average score was "Very satisfactory," with most programs having qualified and experienced program directors in place. The major deficiencies in this area were the general failure of programs to use research to design the interventions and treatment. The assessment section of the CPAI evaluates how programs measure risk, need and responsivity. The average score for this section was 44 percent or "unsatisfactory." Most programs assessed some risk and need factors of the offenders; however, the process was often subjective. For example, only about one-third of the programs used a standardized instrument to measure risk and need factors, and even fewer used an actuarial instrument that provided a score or level. Similarly, very few programs assessed responsivity factors such as motivation or readiness to change. The third subcomponent of the CPAI examines the actual treatment or services delivered by the program. The average score for this section was also in the "unsatisfactory" range. Research has shown that programs are more effective when they target the criminogenic needs of the offenders in a manner that allows the offenders to learn and practice pro-social skills (Goldstein and Glick, 1995). Of the 107 juvenile programs assessed, about two-thirds The Bachelor of Science Degree in Corrections Administration and Management from Bellevue University was developed in partnership with the National Institute of Corrections (NIC), Specifically for corrections professionals. Earn up to 14 credits for state correctional pre-service training. Earn additional credits for state-level law enforcement and military training, too! Ask about the 15 other online degrees we offer, including Criminal Justice Administration and Security Management. BELLEVUE 877-299-0009 Lutu Lu.be I levue.edu/info/corrections Real Learning for Real Life. SEE US A T B O O T H # 6 2 6 ACA WINTER i 0 t i K BeLevue UniiKRily doe n discriminale nn [he base of a^. nee, mloc relipon.. naftmal cmfin. w disability in ihe eduranoiial pragrams aid acOiiUEs ii December 2004 Corrections Today 27 Figure 1: Juvenile Corectional Programs CPAI Scores 107 Juvenile Programs Finally, the miscellaneous section of the CPAI was scored as "very satisfactory." Most programs had ethical guidelines in place, had complete files and were considered stable. The total scores across the six areas for the 107 juvenile programs are presented in Figure 2. These results indicate that only a small percentage of programs scored "satisfactory" or higher (18 percent), with the remaining classified as "needs improvement" or "unsatisfactory." Most Common Shortcomings Very sali