This is 3 Pages PSY 224 Milestone Two Worksheet: Hypothesis and Methodology Review the critical elements that must be addressed in the final project. Use this worksheet to develop Milestone Two. I. Introduction In recent years, psychologists have focused on developing therapeutic interventions that can help reduce recidivism among juvenile offenders. Given the rise in juvenile offenders of the decades and increased recidivism, one therapeutic intervention that has been put forth to help juvenile offenders is cognitive behavioral therapy (CBT). Cognitive behavioral therapy (CBT) can be used to target the criminal mind of juvenile offenders in order to decrease crime and recidivism and offer youths with an opportunity for a better future. This therapeutic intervention assumes that majority of individuals become mindful of their own thoughts and behaviors and seek positive changes to them. One’s thoughts are usually the outcome of experience and behavior is usually swayed and triggered by such thoughts. Various studies have shown that cognitive behavioral therapy can be used as a successful intervention among juvenile and adult offenders including substance abuse offenders, inmates, violent offenders, those on probation and parolees. Also, this intervention can be successful both in institutions and the community as key criminal justice systems. II. Hypothesis The hypothesis of this study is that: Cognitive behavior therapy (CBT) can be used as a successful intervention in juvenile offenders. Various studies have examined the effect of cognitive behavior therapy on juvenile recidivism. In a study titled “A multiyear follow-up study examining the effectiveness of a cognitive behavioral group therapy program on the recidivism of juveniles on probation,” Jewell et al., (2015) investigated the effectiveness of a cognitive behavioral group therapy program titled “Community Opportunity Growth (COG)” (Jewell et al., 2015). The researchers collected data from 394 juveniles that were either on probation or under the supervision of the court in southwestern Illinois. The juveniles participated in the COG group therapy program under supervision for 16 weeks (Jewell et al., 2015). The study found some indications of lasting effectiveness of CBT group therapy program in decreasing recidivism in juveniles (Jewell et al., 2015). Also, other studies have examined the effect of Victim-Offender Mediation (VOM) on the rate of recidivism (Schiff, 1998). VOM is a form of therapeutic intervention structured to enable victims and offenders the chance to reconcile and mutually consent on reparation (Schiff, 1998). The aim of VOM is to tackle crime as a conflict to be fixed between the individuals directly impacted rather than as a conflict between the state and the suspect (Schiff, 1998). Studies have shown that offenders that take part in VOM have lesser rates of recidivism compared to same offenders that undertake conventional juvenile justice system procedure (Schiff, 1998). Also, studies have shown that those juveniles that re-offend may perpetrate less serious crimes that offenders in comparable control groups (Schiff, 1998). Another study by Lipsey (2009) investigated the effectiveness of several therapeutic interventions on juvenile offenders (Lipsey, 2009). Lipsey (2009) paralleled varied counseling and skill building measures (Lipsey, 2009). The study revealed that cognitive behavioral skillbuilding approaches had greater effectiveness in decreasing further criminal conduct that all other interventions (Lipsey, 2009). The study also revealed that interventions focused on punishment and recidivism seemed to increase criminal recidivism (Lipsey, 2009). However, the study also found that therapeutic approaches focused on counseling, skill acquisition, and various other services has the biggest effect in decreasing further delinquent behavior. Among these, the study found cognitive behavioral skill-building approaches to be the most effective (Lipsey, 2009). These studies support my hypothesis that cognitive behavior therapy (CBT) can be used as a successful intervention in juvenile offenders. The studies demonstrate that CBT can be effective in reducing recidivism among juvenile offenders, as suggested by my hypothesis. III. Methodology The research design I have selected is a survey research design. Survey research is appropriate for this research as it would allow for a large population and thus, higher statistical power. Also, survey research design is more effective in testing the effectiveness of a program such as cognitive behavioral therapy. A questionnaire would be used to collect both quantitative and qualitative data. The research participants would comprise of juvenile offenders. The participants would be randomly selected and will comprise of offenders who have participated in two types of interventions including cognitive behavioral approaches and those that have participated in traditional criminal justice interventions. Questionnaires would be administered to the participants. Example of the questions that would be asked includes the type of intervention, a number of arrests before and after the intervention, crimes committed before and after the intervention, and rate of satisfaction with the specific intervention experienced and among other questions. The research will involve 800 juvenile offenders, both male and female. References: Jewell, J. D., Malone, M. D., Rose, P., Sturgeon, D., & Owens, S. (2015). A multiyear follow-up a study examining the effectiveness of a cognitive behavioral group therapy program on the recidivism of juveniles on probation. International journal of offender therapy and comparative criminology, 59(3), 259-272. Lipsey, M. W. (2009). The primary factors that characterize effective interventions with juvenile offenders: A meta-analytic overview. Victims and offenders, 4(2), 124-147. Schiff, M. (1998). Restorative justice interventions for juvenile offenders: A research agenda for the next decade. Western Criminology Review, 1(1), 1-16. PSY 224 Milestone One Worksheet: Topic Selection and Introduction Review the critical elements that must be addressed in the final project. Use this worksheet to develop Milestone One. You should build on the ideas from the Module One discussion to select your final topic. 1. Identify and briefly summarize the topic related to psychology that you will study. My interest is forensic psychology and I’d like to delve more into the subject of recidivism if Cognitive Behavioral Therapy (CBT) can be used as a successful intervention in early offenders. 2. Summarize at least two articles that you might use in the literature review section of the introduction that are relevant to the topic you want to research. List the APA reference citation followed by the summary. Article I: Thoder, V. J., & Cautilli, J. D. (2011). An independent evaluation of mode deactivation therapy for juvenile offenders. International Journal of Behavioral Consultation and Therapy, 7(1), 40-45. doi:10.1037/h0100925 The authors’ purpose of this article is to inform the reader about research conducted to demonstrate that adolescent youths, including younger children who display lengthy conduct problems and antisocial demeanors, may need more personally tailored interventions, such as cognitive behavioral treatment (CBT) or mode deactivation therapy (MDT) because prior research has shown that interventions like residential treatment programs have shown to be ineffective in decreasing recidivism among juvenile offenders (Thoder & Cautilli, 2011). Article II: Jewell, J. D., Malone, M. D., Rose, P., Sturgeon, D., & Owens, S. (2013). A multiyear follow-up study examining the effectiveness of a cognitive behavioral group therapy program on the recidivism of juveniles on probation. International Journal of Offender Therapy and Comparative Criminology, 59(3), 259-272. doi:10.1177/0306624x13509065 The authors’ purpose of this article is to inform the reader about the long-term effectiveness of juvenile delinquents participating in a group setting for CBT to reduce the rate of juvenile recidivism over a long period of time. The researchers theorized that graduates from the program, titled Community Opportunity Growth would have a revelatory lower rate of recidivism than the individual who terminated their participation by dropping out (Jewell, Malone, Rose, Sturgeon, & Owens, 2013). 2. Discuss the bias and limitations present in the articles. Support your discussion with specific examples from the articles. Jewell et al (2015) found that there were limitations to their study. For example, archival data was relayed upon and the sample size could have been bigger and included more females. I feel for this study, a larger random sample size would give a clearer picture when analyzing the data (Jewell, Malone, Rose, Sturgeon, & Owens, 2013). 3. Discuss other factors that might impact the credibility of those articles. You might look at how the research methods used influenced results, or you might look at the setting of the research. Anything in the article that might impact the outcome of the research could be discussed here. a. Explain how the bias and limitations may inform or influence your research. Jewel et al (2015) published that this article had no conflicts of interest or financial support regarding research, authorship and publications (Jewell, Malone, Rose, Sturgeon, & Owens, 2013). b. Summarize the research design and methods described in these articles. The research design and methods for An Independent Evaluation of Mode Deactivation Therapy for Juvenile Offenders (Thoder & Cautilli, 2011), included the use of questionnaires given to the 39 male participants, ages 14-17 years-old and their families upon entry to the Pine Treatment Center, and a reassessment tool at the time of exiting the program. The facility staff oversaw the above procedure. The research design and methods for A Multiyear Follow-Up Study Examining the Effectiveness of a Cognitive Behavioral Group Therapy Program on The Recidivism of Juveniles on Probation (Jewell et al., 2015) utilized participants in a single county in the Midwest with an uncustomary demographic composition (Jewell et al., 2015). Since the study was retrospective in nature (Jewell et al., 2015), a quasi-experimental design was utilized. c. Discuss the appropriateness of the research design and methods in these articles. Were they appropriate for the research questions and hypotheses? Both articles used appropriate research design and methods; the researchers in both studies wanted to calculate the rates of recidivism before and after treatment interventions. d. Discuss whether or not the research design and methods in these articles align to the expectations of the APA Ethical Principles of Psychologists. Support your discussion with specific examples from the articles. There are no blatant errors regarding the studies not complying with the high expectations of the specific ethical principles by the APA. e. Based on your evaluation of these articles, discuss which research design and methods you feel will be most appropriate for the research you want to conduct. I feel the most appropriate research design and methods for the research I want to conduct would be a longitudinal study with frequent follow-up. For example, Jewell et al (2013) claims that their own multiyear study allowed them to see some indications that CBT did provide long term effectiveness in reducing the juvenile recidivism rate. f. Explain the steps you will take to ensure your research aligns to the expectations of the APA Ethical Principles of Psychologists. All researchers in psychology must adhere to American Psychological Association’s (APA) Ethical Compliance Checklist found in the Publication Manual of the American Psychological Association. The information about ethics presented in this scenario adheres to the Ethical Compliance Checklist including having all participants sign an Informed Consent, being able to leave the study at any point during the study, and all participants being debriefed at the end of their time in the study. The study does not include animal subjects, and I assume the protection of the confidentially of the research participants, as well as the study being submitted to the research teams Institutional Review Board (IRB) for approval before starting the study. Resources: Jewell, J. D., Malone, M. D., Rose, P., Sturgeon, D., & Owens, S. (2013). A multiyear follow-up study examining the effectiveness of a cognitive behavioral group therapy program on the recidivism of juveniles on probation. International Journal of Offender Therapy and Comparative Criminology, 59(3), 259-272. doi:10.1177/0306624x13509065 Thoder, V. J., & Cautilli, J. D. (2011). An independent evaluation of mode deactivation therapy for juvenile offenders. International Journal of Behavioral Consultation and Therapy, 7(1), 40-45. doi:10.1037/h0100925 The International Journal of Behavioral Consultation and Therapy 2011, Vol. 7, No. 1, 41–46 ©2011, All rights reserved. ISSN: 1555 - 7855 An Independent Evaluation of Mode Deactivation Therapy for Juvenile Offenders Vincent J. Thoder Joseph D. Cautilli Behavior Analysis & Therapy Partners Behavior Analysis & Therapy Partners Juveniles who commit crimes are likely to exhibit conduct problems in their youth. Persistent and long-term antisocial behavior can be seen in very young children. To treat these children, programs must be designed to meet the needs of them on an individualized basis. Residential treatment, typically, is the answer, but research has shown its ineffectiveness. Longitudinal studies and meta-analyses have shown cognitive behavioral therapy (CBT) to be effective. Mode deactivation therapy (MDT) is a form of CBT based on the theory of a network of cognitive, affective, motivational, and behavioral components that create a personality – “modes.” Modes are activated and create emotional dysregulation and behavioral disorders. In MDT, using a manualized treatment, the therapist reduces symptoms of behavior disorder, physical and sexual aggression, anxiety, and traumatic stress while keeping the juvenile offenders out of long-term, out-of-home placements. This present study examines 39 adjudicated Pennsylvania males (ages ranging from 14 to 17). Using baseline scores and comparing them to posttreatment scores, outcomes are measure and the effectiveness of MDT can be observed. It is important to note that all measures of the DSMD, the CBCL, the Beliefs about Victims, the Beliefs about Aggression, and the JSOP-A show a significant decreases in antisocial behaviors. Additionally, at the one year mark, recidivism rates were 7% and none were personal or sexual offenses. Keywords: Juvenile offenders, Mode Deactiviation therapy, recividism the antisocial behavior and often can be very intensive (e.g., Thoder, Hesky, & Cautilli, 2010). Often, the youth with more ingrained antisocial thoughts and behaviors are placed in residential treatment programs by adolescents (Barker, 1998;Underwood, Baggett-Talbott, Mosholder, & Von Dresner, 2008 ). Many of the evidenced based treatments that exist in Residential Treatment Centers (RTCs) have been normed on groups with less intense problems then residential youth (Underwood, Baggett-Talbott, Mosholder, & Von Dresner, 2008). In addition, the opportunities for youth in residential facilities to learn inappropriate behavior is high (Barker, 1998). These factors may contribute to why overall, the U.S. Surgeon General Report (1999) residential programs to be ineffective. Non-behaviorally based residential programs have shown a failure to reduce aggressive and antisocial behavior (Joshi & Rosenberg, 1997). In longitudinal study, by year seven, children discharged from publicly funded RTCs in six states in the United States were either readmitted to mental health facilities (about 45%) or incarcerated in a correctional setting (about 30%) (Greenbaum et al.,1998). That makes the rate of failure approximately 75%. The need for effective residential treatment is critical. The use of behavioral principles in more intensive programs have been found to reduce aggressive and disruptive behavior (Chen & Ma, 2007). When taken into a psychologically informed context, contingency management systems can have a powerful effect (Andrew, Zinger, Hoge, Bonta, Gendereau„ & Cullen, 1990). Residential programs based on behavioral principles have had mixed results, but recent re- About 5% of juvenile offenders are responsible for the majority of crimes committed by juveniles (Moffit, 1993; Mulder, Brand, Bullens, & Van Marle, 2010; Schumacher & Kurz, 2000). This group continues with their criminal careers into adulthood and evolves into committing more serious offenses (Mulder et al., 2010; Moffitt & Caspi, 2001). Conduct problems are observed early in this group of adolescents (Patterson, 2002). In fact, some of the initial behavioral difficulties are manifested and observed in children as young as two or three years of age (Keenan, 2001; Loeber and Farrington, 2000; Nee & Ellis, 2005). The peer groups of these children are exposed to their deviant attitudes and behaviors and can show a related increase in their own deviancy. Deviancy training often occurs through deviant talk and the bonding and reinforcement of such talk in other children (Snyder, Stoolmiller, Patterson, Schrepferman, Oeser, Johnson, & Soetaert, 2003). Nee and Ellis (2005) purported that for treatment to be effective, it needs to be responsive to the evolving needs of the child and, later, the adolescent. It is important that interventions for antisocial behavior be dictated by the needs of the clients and be provided at a level of intensity corresponding to the level of disruptive behaviors present. As the problems are solidified, later programs need to target the function of Special thanks to Jack Apsche for his support in providing the data from his work at the Pines Treatment Center. This data is provided one year after Dr. Apshes’s leaving the center. 41 42 THODER & CAUTILLI search suggests that they may be helpful in breaking the cycle of violence both in the program and after discharge (Kingsley, 2006). However, the mechanism for change and which adolescents will respond remain unclear (Kingsley, Ringle, Thompson, Chmelka, & Ingram, 2008). Overall, behavioral and cognitive behavioral programs have been successful in reducing recidivism (Redondo Illescas, Sánchez-Meca and Garrido Genovés & 2001) and misconduct in correctional settings (French & Gendreau, 2006). Several well-conducted meta-analyses have identified cognitive behavioral therapy (CBT) as a particularly effective intervention for reducing recidivism (Landenberger & Lipsey, 2005). Specifically with adolescents, CBT has been identified as an effective approach to treating juvenile delinquency and reducing recidivism (Latessa, 2006; Lipsey, 1999; Pealer & Latessa, 2004; Roush, 2008). Mode deactivation therapy (MDT) is offshoot of CBT that examines aspects of personality that lead to criminality and delinquency and, ultimately, remediate problematic schemas. MDT is based on the work of Aaron Beck, M.D. Beck (1996) suggests that the model of individual schemas do not adequately address a number of psychological problems. Incorporating this premise, MDT addresses a more global methodology (Apsche & Ward, 2002; Beck, 1996). The concept of modes is defined as a network of cognitive, affective, motivational, and behavioral components that integrate sections of a personality (Beck, 1996). Modes consist of beliefs that contain the specific memories, the system on solving specific problems, and the experiences that produce memories, images, and language that form perspectives (Apsche & Ward, 2002). These modes can be charged – or activated – to explain the fluctuations in the intensity gradients of cognitive structures. According to Apsche and Ward (2002), “modes are activated by charges that are related to danger in the fear [F0E0?] avoids paradigm” and “the understanding of conscious and unconscious fears being charged and activating the mode explains the level of emotional dysregulation and impulse control” in the targeted population (p. 461). To return these modes to the unexcited phase is the goal of the treatment. MDT has been shown to be an effective treatment for emotional and behavioral disorders, physical aggression, sexual aggression, anxiety, and traumatic stress (Apsche, Bass, & Siv, 2006; Apsche & Ward-Bailey, 2004; Apsche, Bass, Murphy, 2006; Apsche, Bass, & Houston, 2007a; Apsche, Bass, Jennings, Murphy, Hunter, & Siv, 2005; Apsche & Bass, 2006). MDT has shown to be more effective than treatment as usual (TAU) in reducing arguments between family members, displays of anger, and physical and sexual aggression while keeping adolescents out of restrictive, long-term, out of home settings, all the while reducing recidivism (Apsche, Bass, & Houston, 2007). MDT has also been shown to be more effective in treating delinquent children and adolescents that CBT, especially with regards to internal distress, critical pathology, and externalizing aberrant behaviors (Apsche & Ward, 2002). M ETHOD Participants The population assessed is a high-risk population and are adjudicated Pennsylvania residents. This population consisted of 39 males between the ages of 14-17 years old. Description of Personnel and Staff Training Interventions According to Apsche, Bass, and Houston (2007), MDT “is an individual and family manualized treatment that incorporates treatment strategies from behavioral, cognitive, dialectical, and other supportive psychotherapy approaches” (p. 364). It includes weekly individual or group therapy session. MDT begins with an exhaustive case conceptualization that includes a diagnostic interview, a comprehensive behavioral history and a complete family history. A battery of assessments, dictated by the needs of the individual, are scored and used in the development of the conceptualization. A functional behavior assessment is also included (Apsche, Bass, & Houston, 2007). According to Apsche and Ward (2002), the “case conceptualization helps the clinician examine the underlying fears of the resident” (p. 462). MDT involves imagery and relaxation to enhance cognitive thinking. Balance training follows and the adolesent’s perception and interpretation of informational and internal stimuli are taught. Initially, the imagery is used to reduce external emotional dysregulation. Also important to MDT is the concept of validation, clarification, and redirection (VCR). Validation, defined by Linehan (1993), is the therapist’s ability to uncover the validity within the client’s beliefs; clarification refers to the ability to understand and agree with the truths; and it is important to redirect responses to other, pro-social possibilities on the continuum of truths (Apsche & Ward, 2002). Procedure Staff administered the instruments to the adolescents and their families upon entry. In addition, the families and adolescent were re-assessed at time of discharge. R ESULTS Descriptive Statistics The Behavior Support Program (BSP) at the Pines Treatment Center, uses several assessments to measure the outcomes of their residents. These include the Child Behavior Checklist (CBCL), the Youth Self-Report (YSR), the Devereux Scales of Mental Disorders (DSMD), the Fear Assessment [which is a measure of post traumatic stress disorder (PTSD)], the Beliefs Analysis of Aggression, the Beliefs Analysis of Victims, the Beliefs Analysis of Intimacy, the Beliefs Analysis of Control, the Juvenile Sex Offender Protocol – Adolescent EVALUATION OF MDT FOR JUVENILE OFFENDERS (JSOP-A), and a reading test. Found below is an abbreviated report of five of the assessments (the CBCL, the DSMD, the Beliefs Analysis of Aggression, the Beliefs Analysis of Victims, and the JSOAP). These results are intended to demonstrate preliminary outcome measures data. The DSMD has a mean score of 50 and a standard deviation (SD) of 10. It is important to note that any score of 60 is considered significant. Externalizing scores indicate the prevalence of negative overt behaviors or symptoms. Internalizing scores measure negative internal moods, cognitions, and attitudes. Critical pathology is behavior that represents severe disturbances of children and adolescents. The total scale, or T-Score, indicates a conglomerate of all scores. These include general Axis I pathology, delusions, psychotic symptoms, and hallucinations. All DSMD scores were significantly decreased. Additionally, scores were reduced by or near one Standard Deviation. Specifically, results related to the DSMD Externalizing scores indicate a slight, but negligible, increase in overt behaviors at six months. This might suggest the initial period of adjustment to group living in a residential program. By the 12 month mark, these behaviors were reduced from 54.4 to 48. With regards to internalizing problems, scores, at the six month mark, suggest that many internal symptoms, moods, cognitions, and attitudes were beginning to be aggressed and remediated. This reduction continued to the 12 months mark. Representing a reduction of internal symptoms of one SD from the mean, the score was reduced to 51.8. Examining the DSMD critical pathology scales, scores showed significant improvement with a decrease in scores from 55.9 to 46.4 at the 12 month timeline. These results suggest that the most serious of symptoms were reduced significantly in MDT treatment. The DSMD T-Score represents the composite of the sums of all the aforementioned scores. The total score mean for the BSP was 58.6 prior to the MDT implementation. This score is of a higher value, indicating significant pathology. The reduction of the DSMD total score to 48.5 represents a significant reduction of one Standard Deviation and it reduced to 1.5 under the DSMD mean for the total score. The CBCL Means and Standard Deviations are divided into three categories. These include internalizing behaviors that measure withdrawn, somatic complaints, and anxiety and depression, externalizing behaviors that measure delinquent and aggressive behavior, and total problems that represent the conglomerate of total problems and symptoms (both internal and external). All CBCL scores of the BSP residents were reduced by more than one SD from the man. The significance of the total score being reduced by more than one SD suggests that the residents participating in the BSP. MDT improved to the level of the sample that did not need treatment in the CBCL sample of non-referred children and adolescents. This suggests that the BSP residents significantly improved during their participation in Thought Change. Specifically, the CBCL internalizing problems mean score was 63 on the pre-test. It was 64 at the six month re-test and 53 at the one year re-test time. This represents a significant reduction of internal symptoms 43 for the residents at 12 months. The CBCL externalizing problems mean score at baseline was 63. It was reduced to a mean of 61 at six months and significantly reduced to 42 at the 12 months. This represents a significant reduction in aggression and delinquent behavior at the 12-month participation period in the Thought Change System program. CBCL total scores were reduced from a mean score of 63 to 47 at the 12-month score. Interestingly, the total score increased from a mean of 63 to a mean of 64 at the six month period. The actual reduction in the score occurred at the 12-month period of the resident’s participation in MDT. The Beliefs about Victims is a 20 question belief assessment based on faulty beliefs about victims of sexual offenses. It represents a measure of cognitive distortions that sex offenders endorse. The Belief Analysis is based on a Likertlike scale of seven items, ranging from totally disagree to totally agree. Baseline scores were 41.32 with a range of 20 to 140. The reduction of more than 50% of these beliefs is significant and helps reduce overall risk. If the child/adolescent can identify, change, and remediate their distorted thinking, they lower their risk of sexual offending. The Beliefs about Aggression is a 25 question assessment that measures dysfunctional beliefs/cognitive distortions about aggression. The scores ranged from a low of 25 to a high of 175. The reduction from a mean of 69.81 to 31 represents a 44.4% reduction of aggressive beliefs. This is significant in reducing the beliefs and cognitions about aggression which also resulted in a reduction of aggressive behaviors in these individuals. The JSOP-A is a 23 question risk assessment designed to measure risk factors of adolescent sexual offenders. With a maximum total score of 46 points possible, 1-12 is considered a low risk, 13-27 is considered a moderate risk, and 28+ represents a high risk for re-offending. The reduction of risk, as measured by the JSOP-A, is significant. It is an overall reduction of risk from 28.48 (high risk) to 22.22 (mildmoderate risk). Questions 1 to 13 on the JSOP-A do not change, as they are historical in nature and remain static. Questions 14-23 are risk factors to are remediable to treatment. The BSP mean score was 10.25 on the pre-treatment assessment. This score deduced nearly 60% to 4.86 in the 12-month follow-up assessment. In regards to Recidivism, at the intake, 60% of the residents displayed anti-social values. Over a four year period, the youth in this study had no felony arrests. Only two (5.13%) had criminal charges during the first six months following their discharge. The overall recidivism rate was 7%. Four of the seven new offenses were drug-related charges. It is important to note that none of the offenses were personal offenses and the sexual offense recidivism rate was 0%. D ISCUSSION Historically, the first CBT program used in the treatment of juvenile offenders was implemented by the Tennessee Department of Corrections’ Intensive Treatment Unit (ITU) (Glick, 2006; Roush, 2008). Largely, practitioners sensed 44 THODER & CAUTILLI Table 1 Mean scores of the CBCL Scales Internalizing Problems Externalizing Problems Total Problems Mean SD 1st Period 2nd Period 3rd Period 62 62.6 63.8 11.4 12.0 11.5 63 63 63 64 61 64 53 42 47 the ineffectiveness of non-directive, individual centered, and psychoanalytic models (Roush, 2008). Lipsey (1999) would later show the ineffectiveness of such programs in his meta analysis of nondirective intervention. Thus, newer, more novel treatments, such as the positive peer culture program, evidenced-based behavior therapy, and cognitive-behavior therapy, emerged (Roush, 2008). Roush (2008) remarks that CBT provided staff, clinicians, and practitioners with an understandable and more effective way of building relationships, managing behavior, and increasing safety. Additionally, CBT provides youth with a positive behavior change in very short periods of time and successfully teachers cognitive, behavioral, and interpersonal skills that result in a reduction in recidivism (Roush, 2008; Nee & Ellis, 2005; Gillis, Gass, & Russell, 2008). Research reports that the odds of success, defined as no recidivism in a post-intervention interval of approximately 12 months, is more than one and a half times as great for those receiving CBT (Landenberger & Lipsey, 2005). Over the last ten years, considerable research has been conducted on what leads to re-offense. A substantial amount of research that identifies risk factors for recidivism that include family background measures and peer group factors (Benda & Tollet, 1999; Conger, Neppl, Kim, & Scaramella, 2003; Barnow, Luncht, & Freyberger, 2005; Hoeve, Blokland, Dubas, Loeber, Gerris, & van der Laan, 2008;). There is also research that places an emphasis on the personality characteristics and modifying these malleable risk factors (Carcach & Leverett, 1999; Loeber & Farrington, 2000; Cottle, Lee, & Heilbrun, 2001; Duncan, Duncan, & Strycker, 2001; Huang, White, Kosterman, Catalano, & Hawskin, 2001;Vermeiren, de Clippele, Schwab-Stone, Ruchkin, & Deboutte, 2002; Chang, Chen, & Brownson, 2003; van Dam, Janssens, De Bruyn, 2004; Lattimore, Macdonald, Piquero, Linster, & Visher, 2004; Lipsey, 2009). Overtime, both behavioral and cognitive programs like MDT have begun to target factors known to be associated with risk. MDT is a third generation cognitive behavior therapy. This study adds to the growing body of literature that supports the use of MDT in the treatment of adolescents with conduct difficulties (Apsche, Bass, & Siv, 2006; Apsche & Ward-Bailey, 2004; Apsche, Bass, Murphy, 2006; Apsche, Bass, & Houston, 2007a; Apsche, Bass, Jennings, Murphy, Hunter, & Siv, 2005; Apsche & Bass, 2006). In this study, it appears that considerable reduction in the overall symptomology, as measured by the DSMD and the CBCL occurred. Reduction in sympotomology is associated with decreased risk of re-offending. In this study specifically, this reduction related to the reduction of aggressive and sex offending cognitions in those measures. All of these significant reductions may account for the significant reduction in the JSOP-A as a measure of risk assessment of juvenile sexually based offenders. Core to the MDT approach is the use of case conceptualization (Apsche, & Bass, 2006). Case conceptualization also offers the opportunity for integrating risk assessment information into treatment (see Vess, Ward, and Collie, 2008; Collie, Ward, & Vess, 2008 ). In addition, the MDT model makes use of family involvement. Underwood, et al (2008) has suggested that family involvement will help skills learned in the residential program to generalize to the home environment. . Replication of effective interventions is of critical importance in residential treatment (see Fixsen Blasé, Timbers, and Wolf, 2007). The fact that this data was assessed after the formal program discontinued its ongoing relationship with the developer is a testament to the maintenance of the skills learned by the staff. R EFERENCES Andrew, D.A., Zinger, I., Hoge, R.D., Bonta,J., Gendereau„P., & Cullen, F.T. (1990). Does correctional treatment work? A clinically relevant and psychologically informed meta-analysis. Criminology, 28, 369-404. Apsche, J.A. & Bass, C.K. (2006). 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Journal of Behavior Analysis of Offender and Victim: Treatment and Prevention, 1(3) 284-295 www.baojournal.com AUTHOR C ONTACT I NFORMATION Joseph D. Cautilli, PhD. Behavior Analysis & Therapy Partners 183 Old Belmont Ave. Bala Cynwyd, PA 19004 Phone: (610) 664-6200 E-mail: jcautilli2003@yahoo.com Copyright of International Journal of Behavioral Consultation & Therapy is the property of Joseph D. Cautilli and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. 509065 research-article2013 IJO59310.1177/0306624X13509065International Journal of Offender Therapy and Comparative CriminologyJewell et al. Article A Multiyear Follow-Up Study Examining the Effectiveness of a Cognitive Behavioral Group Therapy Program on the Recidivism of Juveniles on Probation International Journal of Offender Therapy and Comparative Criminology 2015, Vol. 59(3) 259­–272 © The Author(s) 2013 Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/0306624X13509065 ijo.sagepub.com Jeremy D. Jewell1, Michael D. Malone2, Paul Rose1, Dennis Sturgeon1, and Sarah Owens1 Abstract The present study evaluated the long-term effectiveness of a cognitive behavioral group therapy program titled Community Opportunity Growth. This study monitored juvenile delinquents’ recidivism across a 7-year time period, with the average length to follow-up being 39 months. It was hypothesized that program graduates (N = 178) would have a significantly lower recidivism rate than a control group (program nonstarters; N = 66) and program dropouts (whose predisposing factors may have influenced their program participation; N = 150). Analyses controlled for sex, ethnicity, age, prior petitions, highest class of prior petition, and months to follow-up. Results show a general trend indicating the long-term effectiveness of the program as graduates had a lower incidence of petitions at follow-up compared with dropouts and fewer petitions compared with the other two groups. Keywords juvenile delinquency, cognitive behavioral therapy, treatment effectiveness, recidivism, group psychotherapy 1Southern 2Madison Illinois University Edwardsville, USA County Probation and Court Services, Edwardsville, IL, USA Corresponding Author: Jeremy D. Jewell, Department of Psychology, Southern Illinois University Edwardsville, Box 1121, Edwardsville, IL 62026, USA. Email: jejewel@siue.edu 260 International Journal of Offender Therapy and Comparative Criminology 59(3) While overall juvenile arrests have declined by 24% from 2001 to 2010 (Federal Bureau of Investigation [FBI], 2010), juvenile crime continues to be a national concern (Snyder, 2008; Stahl, 2008). In 2010, juveniles accounted for 13% of all arrests made in the United States (FBI, 2010). In addition, juveniles were the perpetrators of 13% of all violent crime arrests, 23% of all property crime arrests, 42% of all arson arrests, and 24% of all robbery arrests in that same year in the United States (FBI, 2010). Equally distressing is the fact that more than half of the juveniles tried in the United States in 2004 were younger than 16 (Stahl, 2008). The prognosis of these youths is often poor, as Snyder and Sickmund (2006) found that the juveniles who commit a crime are more likely to recommit as an adult offender than those who had not offended before age 17. Probation programs are an important component of the juvenile court system. Of the juveniles who are adjudicated, 62% are placed on court-ordered probation, which is the most widely used form of consequence in the juvenile justice system (Livsey, 2006). In 2002, 1.6 million juvenile cases were handled in U.S. courts (Livsey, 2006), and juvenile probation placement showed a significant increase between 1985 and 2005 (Puzzanchera & Sickmund, 2008). Given that a large number of juvenile offenders will be placed on probation, it is critically important that researchers identify any program that may reduce recidivism among these offenders. However, there continues to be a relative lack of research on this topic. Juvenile Delinquents and Mental Health Treatment In 2009, there were an estimated 2.11 million juvenile arrests (Puzzanchera & Adams, 2009). A large portion of these youths likely had serious mental health needs (Lyons, Griffin, Quintenz, Jenuwine, & Shasha, 2003). Many adolescents who have been arrested display disruptive behavior or aggression that is often linked to cognitive distortions and also a lack of appropriate social skills (Wasserman & Miller, 1998). This often leads to a lack of empathy for others as well. Specific problems include deficits in their ability to read certain social cues and the belief that aggressive behavior is a norm in civilized society (Wasserman & Miller, 1998). These cognitive and social skill deficits in juvenile offenders may contribute to a propensity to continue to commit crimes. Robertson, Grimes, and Rogers (2001) found, for example, that within 18 months, youth whose cognitive distortions were corrected through a cognitivebehavioral program required less future intervention by the criminal justice system than those receiving either traditional probation or intensive supervision and monitoring. A study by the Office of Juvenile Justice and Delinquency Prevention (OJJDP) revealed that a large majority of serious and violent juvenile offenders showed early signs of delinquency many years before the first arrest (Bilchick, 1999). Information was derived from interviews with both the mother and the offender. Although these juveniles were arrested for their first offense at an average age of 14, they showed emerging signs of delinquency as early as the age of 7, on average. The same study showed that a large majority of the delinquents had serious problems, such as substance abuse and mental health issues. Because the justice system is often the first Jewell et al. 261 agency that the juvenile comes into contact with, it is crucial to develop a better understanding of mental health issues and empirically supported psychological treatments that may be available to these young offenders. Although programs such as shock incarceration or boot camps have some popularity with the public because their rationale is often intuitive and easy to understand, these programs have consistently been found to be ineffective or harmful to program participants, as they often increase recidivism rates (Sherman et al., 1997). However, other programs that contain specific and empirically supported therapeutic approaches have been found to reduce recidivism rates among adolescent offenders (Lipsey, Wilson, & Cothern, 2000). One such program is cognitive-behavioral therapy (CBT), which is a form of therapy that provides juvenile offenders with skills to examine their distorted beliefs that are maintaining their criminal tendencies as well as offering behavioral coping skills. According to Dowden and Andrews (2000), highly structured programs that incorporate cognitive behavioral techniques and social learning approaches are associated with a greater reduction in overall criminal activity. The previously cited OJJDP report found that the most effective programs when dealing with delinquents were those programs that concentrated on building interpersonal skills and incorporated cognitive-behavioral techniques (Bilchick, 1999). One reason why CBT is so effective with this population is that juvenile offenders often engage in patterns of cognitive distortions that arise when they are faced with stressful situations (Lopez & Emmer, 2002; Wasserman & Miller, 1998). Examples of these distortions emerged in a qualitative study conducted by Lopez and Emmer (2002) that assessed how male offenders interpret their own violent criminal behavior. Lopez and Emmer conducted interviews with offenders that required the offenders to recall the time when they committed a particular crime. During the interviews, the offenders revealed that they strongly believed that their actions were justified. The results also indicated that two prevailing thought processes were often present when males under the age of 18 committed violent acts. The first thought is that the offender must protect his family and close friends ensuring that these individuals are safe and respected. The second is that that the offender must defend his own well-being or distinctiveness as a man by behaving violently. These results suggest that juvenile offenders may benefit from developing better cognitive and problem solving skills. Evidence of CBT Treatment Effectiveness Although the existing research on the effectiveness of CBT with juvenile offenders shows initial promise, there is a critical need for more research on this therapy as well as other, similarly promising psychological treatments. An important meta-analysis on this topic was conducted by Landenberger and Lipsey (2005). In this meta-analytic review of 58 previous studies, 17 of which were with juvenile offenders and 41 with adult offenders, the authors sought to understand the effects of CBT and what offender and program characteristics might moderate the effectiveness of CBT. Their initial findings underscored the effectiveness of CBT: Program completers had a 25% lower recidivism rate compared with those in a control group. When the authors focused on 262 International Journal of Offender Therapy and Comparative Criminology 59(3) only those studies that implemented a “best practices” CBT program, effectiveness increased significantly, the program completers showed a 50% decrease in recidivism compared with those in a control group. Although the authors (Landenberger & Lipsey, 2005) had initially sought to identify potential moderators of CBT effectiveness, results indicated that in general, few characteristics of CBT programs and study designs made a difference in treatment effectiveness. For example, type of population (juvenile vs. adult), specific CBT program implemented, treatment setting, and training and background of providers all proved to have no influence on effectiveness. The authors did find that offenders’ risk level, program quality, and certain treatment characteristics did impact treatment effectiveness. A more recent study of CBT effectiveness using a sample of mostly adult offenders in the community (Hollin et al., 2008) revealed similar results to those of Landenberger and Lipsey (2005). Specifically, these authors (Hollin et al., 2008) divided participants into four different groups: program completers, dropouts, nonstarters, and a comparison group. Results indicated that compared with the comparison group, the odds of reconviction were 0.61 for program completers. Strengths of this particular study are the size of the sample (N = 4,935) and the rigorous study design that allowed for the inclusion of a number of control variables including age, measured risk of reconviction, number of previous convictions, and severity of offense. Although the literature on the effectiveness of CBT has been building in recent years, most of this research has concentrated on adults, and research on juveniles has almost exclusively focused on juveniles who were in a controlled setting such as a treatment center or incarceration. Therefore, there has been little to no research examining CBT effectiveness with juveniles where the program is led by probation personnel. As probation is a very large component of the juvenile justice system (Livsey, 2006; Puzzanchera & Sickmund, 2008; Stahl, 2008), research on this topic is critically needed. Purpose of the Present Study and Hypothesis The purpose of the present study was to estimate the long-term effectiveness of a CBT program titled Community Opportunity Growth (COG). This study monitored juvenile delinquents’ recidivism across a 7-year period, with a 39-month average length to follow-up. This study seeks to fill a gap in the research literature on the effectiveness of cognitive behavioral therapy for juvenile delinquents administered by a probation department. It was hypothesized that program graduates would have a significantly lower recidivism rate compared with either youth who dropped out of the program (dropout group) or youth who did not start the program (control group). Method Participants Participants in the present study were juveniles placed on probation within a single county that is located in southwestern Illinois near the Missouri/Illinois border. The 263 Jewell et al. Table 1. Descriptive Statistics for the Graduated, Dropout, and Control Groups. Female (%) Caucasian (%) Age Prior petitions Highest class prior petition Months to follow-up Petitions at follow-up (%) Number of follow-up petitions N aThe Graduated Dropout Control M (SD) M (SD) M (SD) 21.30 60.70 15.27 (1.21) 1.97 (1.32) 5.61 (1.91) 38.08 (23.11) 31.60 0.59 (1.13) 177a 24.70 57.30 15.15 (2.23) 1.93 (1.31) 5.93 (1.79) 39.22 (25.06) 52.70 1.21 (1.60) 150 24.20 54.50 15.33 (1.35) 1.94 (1.29) 5.94 (1.70) 39.53 (32.95) 40.90 0.94 (1.51) 66 number (N) of graduates varies from 176 to 178 due to occasional missing data. county has a unique demographic makeup of rural, urban, and suburban communities and according to the 2000 census has a juvenile population of nearly 62,000. Archival data were gathered from 394 youth who were either on probation or under court supervision in the county between 2000 and 2007. During that time, these youth were referred to the COG program, which is described in a later section. Of these, 178 youth graduated from the COG program successfully (graduate group), while 150 youth began the program but dropped out and did not graduate successfully (dropout group). As dropouts are a somewhat problematic choice for a control group due to possible preexisting differences, an alternative control group was available. The control group of 66 youths included those who were referred to the COG program by their probation officer but either (a) the referral was made shortly after the deadline to begin the program and the youth did not begin the program at any time in the future, or (b) the referral was made in the county’s computerized system but due to human error, the program facilitator never received the referral. This control group utilized, although not ideal in some ways and not conforming procedurally to random assignment, a number of properties that allow it to be considered a true control group. Specifically, these youth were referred at or very near the same time as the dropout and graduated groups, and were referred using the same procedure and criteria. Thus, although random assignment prior to treatment would have been ideal, we consider the present control group to be at least adequate given the prevalent constraints that exist when doing research in a natural community context such as this. Descriptive statistics for juveniles who graduated, dropped out, or were in the control group (nonstarters) are presented in Table 1. A chi-square analysis indicated that the groups did not differ on the variables of sex or ethnicity. Analysis of variance (ANOVA) also indicated that the groups did not differ on the variables of age, number of petitions prior to group assignment, number of months from group assignment to follow-up, or average highest class petition prior to group assignment. Again, this lack of preexisting differences confirms to some extent the lack of selection bias in the control group. 264 International Journal of Offender Therapy and Comparative Criminology 59(3) Description of the COG Program The COG program is a 16-week group therapy program that occurred for approximately 1.5 hr per week and included both males and females in gender-specific groups. The beginning and end of the group coincided with the public school calendar, with fall groups beginning in September and ending before the winter break and spring groups beginning in January and ending before the summer break. The COG program was led by the same facilitator for the entire window of time encompassed by this study. The COG program is loosely organized, though not manualized, and was created by county probation staff and the first author, who serves as a consultant to the department. The program was built on the theoretical assumptions and clinical techniques described in Beck (1995). Regarding the organization of the program, the first session includes a description of the group’s purpose, group-building activities, and exploration of the negative consequences of criminal behavior. The second session includes a description of the cognitive model (Beck, 1995). The third and subsequent sessions focus on irrational thinking experienced by program participants, behavioral and emotional consequences of such thinking, and the legal repercussions of criminal behavior. The facilitator of the program relied primarily on Socratic questioning as the primary clinical technique, while significant peer discussion helped participants identify irrational thinking and produce rational replacement thoughts. It is important to note that juveniles in the COG program had a variety of primary probation officers who were responsible for their supervision while on probation. However, the facilitator of the program was on special assignment as director of the COG program and did not have responsibility for supervising the probation of any of the juveniles. Data Collection Procedures For the 7-year window chosen (from fall of 2000 to the end of 2007), archival data were gathered on all youth who were referred to the COG program. These data were gathered from the county’s computerized database that stores information regarding the youth, their criminal history, and other data relevant to their case. For the purposes of this study, recidivism was defined as a petition to the court related to a new criminal charge. Thus, recidivism did not include petitions to the court for technical violations (e.g., truancy) or when the youth was arrested on a new criminal charge but no petition to the court was made due to lack of evidence, and so on. In addition, the actual adjudication of the youth as guilty was not required to be considered as recidivism for this study. Related to this, a youth might often incur several petitions to the court for a particular set of crimes. For example, a youth who stole a car and was eventually arrested might incur petitions for automobile theft, reckless driving, speeding, and resisting a peace officer. Rather than considering these as four separate petitions, the date for all petitions was examined and any number of petitions filed on the same date was counted as only one petition, with the most serious charge noted. Thus, in the previous example, the youth’s auto theft would be counted as one petition, and a Class 3 felony (for automobile theft). This procedure was enacted to reduce variability in the Jewell et al. 265 data due to changes over time in how the State’s attorney might choose to file petitions for lesser charges related to a single incident. For all three groups, the creation of an index date was required to define what would be considered prior petitions as opposed to petitions at follow-up. For the graduated group, the index date was the date of graduation from the COG program, so that the follow-up period was defined after this index date, and prior petitions were those that were filed prior to this index date. For the control group, the index date was considered to be the date the COG program began for which they had been referred but did not begin. For the dropout group, the index date was considered to be the date at which their COG program began. Follow-up data were gathered at the beginning of 2008. Design Given the retrospective nature of the study, a quasi-experimental design was used, and differences between the three groups on several variables were controlled for. These control variables included sex, ethnicity, age, prior petitions, highest class of prior petition, and months to follow-up. The independent variable was group as we compared youth who graduated from the program with those who dropped out of the program or those who were referred but never started the program. For a similar design, see Hollin et al. (2008). Results To examine the effectiveness of the COG program, we conducted analyses with two dependent variables: a dichotomous variable representing whether at least one petition was or was not generated at follow-up and a continuous variable representing number of petitions generated at follow-up. The continuous dependent variable may be more sensitive to change in response to treatment, but the dichotomous variable may also be important when there is interest in factors that may eliminate petitions completely. The first analysis was a hierarchical logistic regression with the dichotomous dependent variable (i.e., whether or not at least one petition was generated at followup). Approximately 41% of the control group generated petitions at follow-up, whereas 53% of the dropout group and 32% of the graduated group generated such petitions. In the first block, the following control variables were entered: sex (1 = male, 0 = female), ethnicity (1 = Caucasian, 0 = non-Caucasian [95% of this group was African American]), age, prior petitions, highest class of prior petition, and months to followup. This model produced a good model fit, as indicated by a nonsignificant Hosmer and Lemeshow goodness-of-fit test, χ2(8) = 4.73, p = .79, and respectable R2 values (Cox and Snell R2 = .16; Nagelkerke R2 = .21). This model was significantly better than a constant-only model (which included only the intercept), Δχ2(6) = 66.15, p < .001. In the second block, the crucial group variable was added (generating two dummy-coded variables with the control group as the reference group). This model accounted for significantly more variance, Δχ2(2) = 16.69, p < .001, and the 266 International Journal of Offender Therapy and Comparative Criminology 59(3) Table 2. Petitions at Follow-Up Logistic Regression With Control Variables and Group as Predictors. 95% CI for Exp (B) Constant Sex Ethnicity Age No. of prior petitions Highest class prior petitions Months to follow-up Group Group (1) Group (2) B (SE) Wald statistic Lower Exp (B) Upper −0.95 (1.33) 0.90 (0.29) −0.38 (0.24) −0.08 (0.08) 0.40 (0.10) −0.08 (0.07) 0.02 (0.01) — −0.47 (0.33) 0.57 (0.34) 0.51 9.35* 2.52 0.99 16.42* 1.50 26.85* 16.13 1.94 2.82† — 1.38 0.43 0.79 1.23 0.81 1.01 — 0.33 0.91 0.39 2.45 0.69 0.92 1.49 0.92 1.02 — 0.63 1.76 — 4.36 1.09 1.08 1.81 1.05 1.03 — 1.21 3.40 Note. CI = confidence interval. Model χ2 (8, N = 391) = 82.84, p < .001. Cox and Snell R2 = .19; Nagelkerke R2 = .26. Group (1) = Graduate (1) vs. Control (0). Group (2) = Dropout (1) vs. Control (0). *p < .05. †p < .10. percentage of correct classifications increased from 67.50% (for the Block 1 model) to 70.80% (for the Block 2 model). For the second block, model χ2(8) = 82.84, p < .001, Hosmer and Lemeshow goodness of fit χ2(8) = 3.69, p = .88, Cox and Snell R2 = .19; Nagelkerke R2 = .26. The coefficients for each of the predictors included in the Block 2 model are presented in Table 2. Although the difference between the graduated and control groups was not significant (p = .16) in this logistic regression, it is worth noting that the odds ratio of 0.63 suggests that the odds of incurring a petition at follow-up were lower for the graduated group (32% of whom experienced a petition at follow-up) than for the control group (41% of whom experienced a petition at follow-up). For the sake of making a complete presentation of the data, we note that the difference between the dropout and control groups approached statistical significance (p = .09). However, we acknowledge that a plausible explanation for this difference is that juveniles in the dropout group were especially resistant to treatment before the treatment started. The associated odds ratio (1.76) suggests that the odds of experiencing a petition at follow-up was higher for the dropout group (53% of whom experienced a petition at follow-up) than for the control group. Because of the possibility that juveniles in the dropout group may differ from those in the control group in several ways, we do not consider comparisons with the dropout group to provide strong tests of the effectiveness of the COG program. However, to make a complete presentation of differences between the groups, we did compare the graduated and dropout groups in a hierarchical logistic regression. In the first block, the same control variables used earlier were entered: sex (1 = male, 0 = female), ethnicity (1 = Caucasian, 0 = non-Caucasian), age, prior petitions, highest class of prior petition, and months to follow-up. This model produced a good model fit, as indicated 267 Jewell et al. Table 3. Petitions at Follow-Up Logistic Regression With Control Variables and Graduated vs. Dropout Variable as Predictors. 95% CI for Exp (B) Constant Sex Ethnicity Age Number of prior petitions Highest class prior petitions Months to follow-up Graduated vs. Dropout B (SE) Wald Lower Exp (B) Upper −0.92 (1.45) 0.80 (0.32) −0.51 (0.26) −0.11 (0.09) 0.38 (0.11) −0.03 (0.07) 0.41 6.34* 3.85* 1.40 12.66* 0.19 — 1.20 0.36 0.75 1.19 0.84 0.40 2.23 0.60 0.90 1.47 0.97 — 4.17 1.00 1.07 1.81 1.12 0.02 (0.01) 0.99 (0.25) 14.32* 15.13* 1.01 1.63 1.02 2.69 1.03 4.42 Note. CI = confidence interval. Model χ2 (7, N = 325) = 62.13, p < .001. Cox and Snell R2 = .17; Nagelkerke R2 = .24. *p < .05. by a nonsignificant Hosmer and Lemeshow goodness-of-fit test, χ2(8) = 4.62, p = .80, and good R2 values (Cox and Snell R2 = .13; Nagelkerke R2 = .18). This model was significantly better than a constant-only model (which included only the intercept), Δχ2(6) = 46.50, p < .001. In the second block, the crucial Graduate versus Dropout variable was added. This model accounted for significantly more variance, Δχ2(1) = 15.63, p < .001, and the percentage of correct classifications increased from 66.50% (for the Block 1 model) to 71.10% (for the Block 2 model). For the second block (comparing the graduate and dropout groups), model χ2 (7) = 62.13, p < .001, Hosmer and Lemeshow goodness of fit χ2 (8) = 4.62, p = .80, Cox and Snell R2 = .17; Nagelkerke R2 = .24. The coefficients for each of the predictors included in the Block 2 model are presented in Table 3. In this logistic regression, the difference between the graduated and dropout groups was significant (p < .001). The odds ratio of 2.69 suggests that the odds of incurring a petition at follow-up were higher for the dropout group (53% of whom experienced a petition at follow-up) than the graduated group (32% of whom experienced a petition at follow-up). Again, it is unknown to what extent this difference can be attributed to the effectiveness of the COG program or the possibility that the juveniles in the dropout group were more treatment resistant before entering treatment. We next examined the effectiveness of the COG program by conducting a hierarchical multiple regression with number of petitions (a continuous variable) at follow-up as the dependent variable. The mean number of petitions at follow-up for the control, dropout, and graduated groups was 0.94, 1.21 and 0.59, respectively. In the first block, the same control variables used in the logistic regression analyses were entered. This control-variable-only model accounted for a significant portion of the variance in number of petitions at follow-up, F(6, 384) = 13.04, p < .001, R2 = .17. In the second block, two dummy-coded group variables were 268 International Journal of Offender Therapy and Comparative Criminology 59(3) Table 4. Number of Petitions at Follow-Up Multiple Regression With Control and Group Variables as Predictors. Constant Sex Ethnicity Age Number of prior petitions Highest class prior petitions Months to follow-up Group (1) Group (2) B (SE) β 0.55 (0.67) 0.70 (0.16) −0.15 (0.13) −0.05 (0.04) 0.20 (0.05) −0.04 (0.04) 0.02 (0.003) −0.37 (0.19) 0.26 (0.19) — 0.21* −0.05 −0.06 0.18* −0.05 0.27* −0.13* 0.09 Note. Model F(8, 382) = 12.63, p < .001, R2 = .21. Group (1) = Graduate (1) vs. Control (0). Group (2) = Dropout (1) vs. Control (0). *p < .05. added (Graduated vs. Control, and Dropout vs. Control) and this model accounted for significantly more variance, ΔF(2, 382) = 9.65, p < .001, ΔR2 = .04. For the second-block model, F(8, 382) = 12.63, p < .001, R2 = .21. Coefficients for the second-block model are presented in Table 4. In this model focused on number of petitions at follow-up, the difference between the graduated and control groups was significant, p < .05, part r = −.09. As is evident in the penultimate row of Table 1, graduates (M = 0.59, SD = 1.13) experienced fewer petitions at follow-up than youth in the control group (M = 0.94, SD = 1.51). This result, when compared with the results of the logistic regression analysis, suggests that the COG program may have had a stronger effect on the number of petitions at followup than on whether any petition at follow-up was generated. The results in both analyses were in the same direction, but the difference between the graduated and control groups was only significant when the number of petitions at follow-up was compared. In the same multiple regression analysis, the difference between the dropout (M = 1.21, SD = 1.60) and control groups (M = 0.94, SD = 1.51) was not significant (p = .17, part r = .06), even though, as shown in Table 1, dropouts experienced more petitions at follow-up than any other group. When compared with the comparable result that emerged in the logistic regression analysis, this nonsignificant difference suggests that dropouts and juveniles in the control group did not substantially differ in the number of petitions at follow-up, but did differ somewhat (p = .09) in whether they generated any petitions at follow-up. In a final analysis, we compared the graduated and dropout groups on number of petitions at follow-up. Although comparisons with the dropout group may not provide strong tests of the effectiveness of the COG program (because juveniles who dropped out may be more treatment resistant), it is appropriate to acknowledge how these groups differ. In the first block of a hierarchical multiple regression, the control 269 Jewell et al. Table 5. Number of Petitions at Follow-Up Multiple Regression With Control and Graduated vs. Dropout Variables as Predictors. Constant Sex Ethnicity Age Number of prior petitions Highest class prior petitions Months to follow-up Graduated vs. Dropout B (SE) β 1.11 (0.68) 0.65 (0.17) −0.23 (0.15) −0.07 (0.04) 0.22 (.06) −0.03 (0.04) 0.01 (0.003) −0.62 (0.14) — 0.20* −0.08 −0.09† 0.20* −0.03 0.22* −0.22* Note. Model F(7, 317) = 18.64, p < .001, R2 = .21. *p < .05. †p < .10. variables (the same used in previous analyses) accounted for a significant portion of the variance in number of petitions at follow-up, F(6, 318) = 9.90, p < .001, R2 = .16. In the second block, a Graduated versus Dropout variable was added. This secondblock model accounted for significantly more variance, ΔF(1, 317) = 18.90, p < .001, ΔR2 = .05. For the second-block model, F(7, 317) = 18.64, p < .001, R2 = .21. Coefficients for the second-block model are presented in Table 5. In this second-block model focused on number of petitions at follow-up, the difference between the graduated (M = 0.59, SD = 1.13) and dropout (M = 1.21, SD = 1.60) groups was significant, p < .001, part r = −.21. This result, when compared with results in the logistic regression analysis reported earlier, which also compared the graduated and dropout groups, suggests that the graduated and dropout groups differed in both the number of petitions at follow-up and whether any petition at follow-up was generated. Discussion Although there is a growing literature on the effectiveness of CBT with offender populations, there are relatively few studies that have focused on the effectiveness of CBT in juvenile populations (Landenberger & Lipsey, 2005). In addition, there are even fewer studies on this topic using community-based treatment providers such as probation departments. Given the large number of youth who have contact with probation departments each year (Livsey, 2006), these departments have the potential to play a critical role in the application of evidence-based interventions such as CBT. Results of the present study provided some signs of the long-term effectiveness of a CBT group therapy program in reducing recidivism in juveniles. In our study, we examined two indicators of effectiveness, which were whether program graduates had any reoffenses (a dichotomous variable) and also the number of offenses. When recidivism was dichotomously coded, these results indicated that although the difference between the graduated and control groups was not statistically significant (p = .16), the 270 International Journal of Offender Therapy and Comparative Criminology 59(3) odds ratio for the graduate group of 0.63 does indicate that there was a lower rate of petitions in the graduate group compared with the control group. However, these results were more robust when considering recidivism as the actual number of petitions. In this analysis, the graduated with control group comparison was significant (p < .05), with the graduated group experiencing about half as many petitions (0.59) as the control group (1.21; part r = −.21). We also found that the graduate group had significantly fewer petitions and were less likely to have a petition than the dropout group, although this difference does not necessarily attest to the effectiveness of the therapy program (see Hollin et al., 2008). Results of the present study are similar to other studies on this topic. For example, Lipsey, Wilson, and Cothern (2000) conducted a meta-analysis and review of 200 studies of program effectiveness with institutionalized and noninstitutionalized juveniles. The authors found that the 200 programs reviewed reported recidivism reductions ranging from negligible to a 40% reduction, with the average being a 12% reduction when comparing program participants with a control group. When examining simple recidivism rate reductions, the present study found that 32% of the graduate group had reoffended compared with 41% of the control group, which is a 22% reduction in recidivism and a favorable comparison with the results found by Lipsey et al. (2000). Although the present results point to the potential effectiveness of a group CBT program with juveniles probationees, one should also acknowledge the potential conflict that may occur when probation officers are called to both supervise as well as treat juveniles. The therapeutic treatment process relies on building rapport, which can be negatively affected when the client feels overly judged, admonished, or given strict rules to follow, such as may be the case with most probationee/probationer relationships. This potential role conflict was avoided as all participants were supervised by various probation officers who were not the facilitator of the COG program. However, if a program similar to COG were to be administered within other probation departments, potential role conflict would need to be considered. While juvenile crime continues to be a significant problem in society, treatment that is provided to these offenders is often not evidence based and is thus relatively ineffective (Lipsey et al., 2000). The consequences of using relatively ineffective treatments that fail to reduce recidivism are not only related to public safety, but also have financial considerations. Left without effective treatment, many of these offenders will continue to offend throughout their adolescent and adult years, costing taxpayers millions of dollars to prosecute and incarcerate in the future. In addition, although there are a number of effective treatments for juvenile offenders (for a review, see Kimonis & Frick, 2010), some of the most effective treatments (e.g., multisystemic therapy) are typically provided by clinicians rather than probation personnel. However, research shows that there are significant financial benefits to providing effective treatment to youths in the juvenile justice system. For example, Robertson et al. (2001) conducted a short-run cost analysis that focused on juveniles (N = 293) who were adjudicated and placed within a cognitive-behavioral group therapy program. Program participants were compared with a control group that followed the typical probation or parole guidelines. It was found that for nearly every dollar Jewell et al. 271 that was spent on the cognitive-behavioral treatment program, close to two dollars was saved by the courts (Robertson et al., 2001). Although the results of the present study fill a critical gap in the literature in terms of understanding the long-term effects of CBT therapy with a juvenile probationer population, limitations of the study should be noted. To begin, we acknowledge the limitations that exist when relying on archival data. For example, although a control group was obtained (youth referred but who did not start the program), the study did not involve random assignment. However, many possible confounding variables were considered in the analyses, thus minimizing the effect of any possible differences between the graduated and control groups. This study was also able to obtain a nonstarter control group, which has been noted by others as a favorable alternative when the design does not allow for random assignment (Hollin et al., 2008). Another limitation includes the fact that the sample size, and especially the low percentage of females in each group, did not allow for separate analyses by sex of the participant. It would be of interest to examine whether the COG graduates’ long-term recidivism rate differed for males and females in future studies. In addition, as previously mentioned, although group differences were found when comparing the dropout group with the graduate group, it is unknown whether such differences existed due to the effectiveness of the COG program or other preexisting variables such as treatment resistance that were not measured. Finally, this study drew participants from a single county in the Midwest and also relied on a single facilitator. Future research should seek to gather data from other counties and probation departments and also other similarly trained facilitators using the COG program to estimate the generalizability of these results. Available research on the effectiveness of CBT programs with juvenile probationers is scarce. The present study stands as one of the longest follow-up studies of a CBT treatment program with juvenile offenders, with the average time to follow-up at 39 months. CBT is empirically supported as being effective in reducing recidivism in the juvenile population and is also more cost-effective. In the current times of financial deficits by both federal and state agencies, it is crucial that the juvenile courts begin to implement programs that are both effective and cost efficient in the long term while discontinuing programs that may have popular support (e.g., boot camps or shock incarceration) but are known to be ineffective and even harmful to youth and society. Declaration of Conflicting Interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Funding The author(s) received no financial support for the research, authorship, and/or publication of this article. References Beck, J. (1995). Cognitive therapy: Basics and beyond. New York, NY: Guilford Press. 272 International Journal of Offender Therapy and Comparative Criminology 59(3) Bilchick, S. (1999). 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Victims and Offenders, 4:124–147, 2009 Copyright © Taylor & Francis Group, LLC ISSN: 1556-4886 print/1556-4991 online DOI: 10.1080/15564880802612573 The Primary Factors that Characterize Effective Interventions with Juvenile Offenders: A Meta-Analytic Overview 1556-4991 1556-4886 UVAO Victims and Offenders Offenders, Vol. 4, No. 1, November 2008: pp. 1–36 Effective M. W. Lipsey Interventions Mark W. Lipsey Peabody Research Institute, Vanderbilt University, Nashville, Tennessee, USA Abstract: Previous meta-analyses have identified many effective interventions for reducing the recidivism of juvenile offenders and various program factors that are associated with the best outcomes. Most of that work has been focused on only one intervention area and thus has limited scope. Notable exceptions are two relatively comprehensive meta-analyses that have identified a small number of factors or principles that appear to characterize the most effective programs. This paper presents a new analysis of data from one of those meta-analyses designed to test a broader range of intervention factors in a manner that allows identification of both the general principles and the distinct intervention types associated with the greatest reductions in recidivism. Only three factors emerged as major correlates of program effectiveness: a “therapeutic” intervention philosophy, serving high risk offenders, and quality of implementation. With other variables statistically controlled, relatively few differences were found in the effectiveness of different types of therapeutic interventions. Keywords: juvenile delinquency, rehabilitation, evaluation research, meta-analysis Meta-analytic reviews of research on the effects of interventions with juvenile offenders have provided ample evidence that a rather broad range of such The construction of the meta-analysis database on which the analyses in this paper are based was supported in part by grants from the National Institute of Mental Health, the Office of Juvenile Justice and Delinquency Prevention, and the Russell Sage Foundation. Thanks to Paul Gendreau, James Howell, and Darin Carver for useful comments on this paper. Address correspondence to Mark W. Lipsey, Peabody Research Institute, Vanderbilt University, Box 0181 GPC, 230 Appleton Place, Nashville, TN 37203. E-mail: mark.lipsey@vanderbilt.edu 124 Effective Interventions interventions reduces recidivism (Lipsey & Cullen, 2007). The vast majority of those systematic reviews, however, focus on a particular program or type of program, such as boot camps (MacKenzie, Wilson, & Kider, 2001), cognitivebehavioral therapy (Landenberger & Lipsey, 2005), prison visitation (Petrosino, Turpin-Petrosino, & Buehler, 2003), family therapy (Latimer, 2001), drug court (Wilson, Mitchell, & MacKenzie, 2006), victim-offender mediation (Nugent, Williams, & Umbreit, 2003), multisystemic therapy (Littell, Popa, & Forsythe, 2005), and the like. While those reviews are individually informative about the respective interventions, they provide only a limited angle of vision on the broad patterns that characterize the whole body of research on the effectiveness of programs for juvenile offenders. Rather than focusing on a predefined type of intervention, an alternate approach is to collect and meta-analyze all the available research on the effects of intervention with juvenile offenders, sorting it according to the types of interventions found, whatever they may be. Though a daunting task, this approach makes it possible to investigate certain important issues that are otherwise difficult to address. First, a comprehensive meta-analysis of this sort brings to light a number of program types that are unlikely to receive scrutiny in more focused reviews. Much of the delinquency intervention research involves rather generic kinds of programs not likely by themselves to attract the attention of a reviewer. For instance, a large number of studies have been conducted of service-broker-type programs—referral of juveniles to different services based on some assessment of their needs, a kind of program often used with diversion cases. Many of the programs actually used in the juvenile justice system are of this sort and it is informative to consider what is known about their effectiveness along with that of their more crisply defined counterparts. Another reason to examine the full body of research on delinquency programs in a single meta-analysis is that it allows an integrated analysis of the comparative effectiveness of different program types and approaches. A metaanalysis of, say, cognitive-behavioral programs may demonstrate that they have positive effects on recidivism while another meta-analysis shows that family counseling also has positive effects. But which programs are most effective and for whom and under what circumstances? Answers to those questions are especially critical for practitioners interested in using the most effective programs applicable to their situations. Such comparative assessments are not easy to make across different meta-analyses. The task is not as simple as determining which shows the largest mean effect sizes. Effect sizes are influenced by variation in the subject samples and settings used in the primary studies, by the research methods applied in those studies, and by the procedures employed by the meta-analyst in representing and analyzing the intervention effects. Under these circumstances, simple comparisons of summary effect sizes can be very misleading. Within an integrated meta-analysis, however, common procedures 125 126 M. W. Lipsey can be applied and statistical controls used to help level the playing field in a uniform manner so that comparative effectiveness can be better assessed. The most important advantage of a comprehensive meta-analysis, however, is the opportunity it provides to search for generalizations about the factors associated with effective programs (Cook, 1993). The most useful guidance for practitioners, and the most informative perspective for program developers and researchers, will not come from lists of the names of programs shown by research to have positive effects. Rather, they will come from identification of the factors that characterize the most effective programs and the general principles that characterize “what works” to reduce the recidivism of juvenile offenders. Various attempts have been made over the years to conduct more or less comprehensive meta-analyses of the research on interventions for juvenile offenders. The two most extensive efforts are those of Don Andrews and his colleagues (e.g., Andrews et al., 1990) and the present author (e.g., Lipsey, 1992; Lipsey & Wilson, 1998). Andrews et al. have focused especially on identifying the principles that characterize effective interventions for offenders (Andrews et al., 1990; Gendreau, 1996). From analysis of the available research guided by their theory of criminal behavior, they have put forward a need principle, a responsivity principle, and a risk principle for explaining the likelihood of positive effects on recidivism. According to the need principle, interventions have larger effects on recidivism if they address criminogenic needs—malleable risk factors predictive of subsequent criminal conduct such as antisocial attitudes and peer associations, self-control and self-management skills, drug dependencies, and the like. The responsivity principle identifies treatment capable of altering those criminogenic needs, especially interventions that use cognitivebehavioral and social learning approaches. The risk principle, in turn, indicates that larger effects are found for higher risk offenders who, thereby, have a greater need for treatment and also more room for improvement. The meta-analyses conducted by Andrews et al. have demonstrated that studies of interventions they judge as conforming to their need, responsivity, and risk principles show larger effects on recidivism than those that do not (Andrews & Bonta, 2006; Andrews et al., 1990; Dowden & Andrews, 1999, 2000; Gendreau, Smith, & French, 2006). One of those meta-analyses, for instance, reported that programs departing from the need, responsivity, and risk principles had a mean effect size of virtually zero—whereas those that conformed to these principles achieved an effect size of phi = .26, equivalent to a recidivism reduction of around 50% (Andrews & Bonta, 2006, p. 335). The meta-analysis work of the present author and his colleagues, in contrast, has been largely atheoretical and descriptive. It has involved a large database of studies and has focused on identification of the correlates of recidivism effects—that is, the characteristics of study methods, programs, offenders, and intervention circumstances most strongly associated with the differences between treatment and control recidivism rate (Lipsey, 1992, 1999, 2006; Effective Interventions Lipsey & Wilson, 1998; Wilson, Lipsey, & Soydan, 2003). These analyses have resulted in what, at a global level, is a relatively simple picture of the main factors related to recidivism effects. These fall into four categories. First, a considerable amount of the variability in observed intervention effects is associated with the methods used by the researchers to study those effects rather than substantive characteristics of the intervention. Moreover, methodological and substantive factors are often confounded in ways that make it difficult to disentangle actual program effects from methodological artifacts (Lipsey, 2003). The three categories of substantive factors most strongly associated with intervention effects are the intervention approach and modality (type of treatment), the quantity and quality of treatment provided, and the characteristics of the juveniles receiving that treatment. Consistent with the Andrews et al. framework, these meta-analytic investigations have found relatively large positi...
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