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2 Research Report Altering Antisocial Attitudes in Federal Male Offenders on Release: The Final Report of the Counter-Point Program Ce rapport est également disponible en français. Pour en obtenir un exemplaire, veuillez vous adresser à la Direction de la recherche, Service correctionnel du Canada, 340, avenue Laurier Ouest, Ottawa (Ontario) K1A 0P9. This report is also available in French. Should additional copies be required, they can be obtained from the Research Branch, Correctional Service of Canada, 340 Laurier Ave. West, Ottawa, Ontario K1A 0P N 0 R-187

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4 Altering Antisocial Attitudes in Federal Male Offenders on Release: The Final Report of the Counter-Point Community Program Daryl G. Kroner Correctional Service of Canada Andrew J.R. Harris Correctional Service of Canada & Annie K. Yessine Carleton University May 2009

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6 Acknowledgements The authors would like to thank Franca Cortoni for her administrative support, as well as Jennifer Walsh and Colette Cousineau for data collection and coding. ii

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8 Executive Summary This study extends a previous evaluation of the effectiveness of the Counter-Point program in reducing recidivism. Counter-Point is a community-based anti-social attitude program for released male federal offenders. In this study, we included: (1) a longer follow-up period, (2) calculations of percent drop in antisocial attitudes and cognitions, and (3) an additional outcome variable, offence density (number of offences committed). This investigation compared 331 Counter-Point participants to a group of 331 offenders who did not participate in the Counter-Point program. Program participants and comparison offenders were matched on actuarial risk and prior program participation. Outcome measures included new offences, the presence or absence of recidivism, and offence density, the frequency of new offences. The analysis involved three groups. Program participants were categorised into Completers (offenders who completed the program) and Drop-outs (offenders who started but failed to complete the program). The third group was a matched comparison group of offenders who did not take the program. After follow-up of 6.3 years, unadjusted rates showed that 36% of the Completers had committed a new offence. In contrast, 52% of the Drop-outs and 64% of the comparison group had committed a new offence. The effectiveness of the Counter-Point program was examined via a series of Cox and binomial regression analyses. These analyses statistically control for pre-existing differences in criminogenic need ratings and time-at-risk to yield risk ratios. Risk ratios can be interpreted as the differences in rates of reoffending between offenders who participated in Counter-Point and the comparison group. Results showed that offenders who participated in Counter-Point (regardless of whether they completed the program or not) had a 20% reduction in the likelihood of re-offending, compared to offenders who were not exposed to the program content. Analysis also revealed significant reductions (23%) in the number of new offences committed by offenders who participated in the Counter-Point program. In addition, analysis suggested that the Counter-Point program responded equally well to the needs of Aboriginal and non-aboriginal offenders. Similarly, Counter-Point participation resulted in a significant reduction of new offences for both high risk and low risk offenders, and reductions for all categories of risk when the offence density was considered. An examination of treatment changes showed that program participants had significantly less antisocial attitudes and cognitions following completion of the program. Interestingly, though, they also reported an increase in criminal friends. It is speculated that the program helped these offenders more accurately identify their antisocial peers. Overall, the Counter-Point program was successful in reducing antisocial attitudes and cognitions and the commission of new offences among participants. These results indicated that Counter- Point is an appropriate correctional program for offenders who require intervention for antisocial attitudes while on community supervision. iii

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10 Table of Contents Acknowledgements... iii Executive Summary... ii Table of contents... iv List of tables... vi Introduction... 1 Purpose... 1 Method... 3 Participants and measures... 3 Outcome measures and time-at-risk... 3 Results... 5 Treatment outcome comparison group results... 5 Equivalency of the program participant and comparison groups... 5 Statistical analyses... 5 Impact of the counter-point participation... 7 Group failure rates... 7 The general impact of the counter-point program on recidivism... 8 The impact of the counter-point program on recidivism across risk levels... 9 The impact of the counter-point program on recidivism across races The impact of the counter point program on antisocial attitudes Percent change Dynamic areas/mechanisms of change Drop-out analyses Reasons for failure to complete the program Recidivism rates of counter-point completers and drop-outs Discussion Limitations of findings Implications and suggestions for future research Conclusion iv

11 References v

12 List of Tables Table 1 Mean Differences on Risk and Prior Program Participation for Counter-Point Participants and Comparison Offenders... 6 Table 2 Racial Composition, Marital Status, and Previous Youth conviction for Counter- Point Participants and Comparison Offenders... 7 Table 3 Unadjusted Recidivism Rates (%) of Counter-Point Participants and Comparison Group... 8 Table 4 Cox Regression Analyses for New Offences of Counter-Point Participants and Comparison Offenders, Controlling for Criminogenic Need... 9 Table 5 Cox Regression Analyses for New Offences of Low, Medium, and High Risk Counter-Point Participants, Controlling for Criminogenic Need Table 6 Cox Regression Analyses for New Offences of Caucasian, Aboriginal, and Other Racial Minority of Counter-Point Participants vs. Comparison Group, Controlling for Criminogenic Need Table 7 Paired Sample t-tests on Psychometric Measures Table 8 Reasons for Program Non-Completion (N = 89) Table 9 Cox Regression Analyses for New Offences of Counter-Point Completers (vs. Drop-outs), Controlling for Criminogenic Need, Risk, and Previous Program Participation vi

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14 Introduction The presence of antisocial attitudes as an antecedent of crime is well established in both crime-related theory and empirical research (Agnew, 1994; Andrews & Bonta, 2003; Andrews & Kandel, 1979; Andrews, Zinger, Hoge, Bonta, Gendreau & Cullen, 1990; Hoge, Andrews and Leschied, 1994; Mills, Kroner & Forth, 2002; Shields & Simourd, 1991; Shields & Whitehall, 1991; Simourd, 1997; Simourd & Van de Ven, 1999). Based on this accumulated literature, the Counter-Point program was developed within the Correctional Service of Canada to reduce the presence of antisocial attitudes and to increase the presence of prosocial attitudes, with the goal of reducing criminal behaviour. Counter-Point is a group intervention program aimed at federal offenders under community supervision. Participants are provided with the skills necessary to identify, challenge, and enhance their willingness to alter antisocial attitudes, and develop more prosocial attitudes. The program consists of 25 sessions, divided into 3 processes: intake, intervention, and closure. 1 Program entry and participation guidelines are clearly outlined and program integrity is maintained through ongoing process evaluations, and standardized manuals. The Counter-Point program is facilitated by Program Delivery Officers (PDOs) who have experience working with correctional clients, have access to clinical support and guidance, and have received training in the principles of effective intervention and standards of professional conduct. Yessine and Kroner (2004 [N R-152]) conducted a preliminary evaluation of Counter- Point and found that, with a 1.4 year follow-up period, 25% of offenders who completed the Counter-Point program were suspended, 14% were revoked, and 28% committed a new offence. In that study, the comparison group had rates of suspension, revocation, and new offence of 37%, 26%, and 45%, respectively. Results also showed that greater reductions were achieved for higher risk offenders who completed the program compared to lower risk offenders. Purpose The purpose of the present study was to extend and expand the outcome evaluation of Counter-Point. The results accounted for race, risk level, previous programs and drop-outs. More 1 A more detailed description of the Counter-Point Program is available in the original report (2004, N R-152). 1

15 specifically, we asked: 1. Are the reductions in recidivism maintained with a longer follow-up period, 2. Do the reductions in recidivism apply to the outcome of offence density, 3. What level of reduction in antisocial attitudes can be expected? 2

16 Method Participants and Measures The present study consisted of 331 Counter-Point program participants and 331 comparison offenders 2. The mean age of Counter-Point participants and offenders in the comparison group was 35.1 (SD = 9.3) and 35.6 (SD = 10.0) years, respectively. The length of sentence for the treatment and comparison groups averaged, 5.0 (SD = 4.2) and 5.2 (SD = 3.8) years, respectively. Further group comparisons are detailed in the Results section of the report. The psychometric tests for the present analyses included: 3 1. Criminal Sentiments Scale - Modified (CSS-M; Shields & Simourd, 1991) 2. Pride in Delinquency Scale (PID; Shields & Whitehall, 1991) 3. Neutralization Measure - Modified (NM-M; Atkinson, 1998) 4. Measure of Criminal Attitudes and Associates (MCAA; Mills & Kroner, 1999) 5. Criminal Attribution Inventory (CRAI; Kroner & Mills, 2003). Actuarial risk was measured by the Statistical Information of Recidivism (SIR-R1, Correctional Service of Canada, 1996). Criminogenic need was measured by the Offender Intake Assessment (Motiuk, 1997). Outcome Measures and Time-at-Risk For the purpose of this follow-up study, only new offences were considered as outcome measures. The first outcome measure was new offence: the presence or absence of a new offence, regardless of the number for a particular offender. The second outcome measure was offence density. The offence density measure is a count of the number of post-treatment convictions per offender, which is considered to be a conservative measure of criminal activity (Farrell, 2005). As offence density tallied the number of new offences for each participant, it allowed for a calculation of criminal frequency. 2 One case was keyed wrongly into a group in the original report, thereby dropping two cases for the present analysis. 3 Full descriptions of the measures and assessment procedures are in the original report (2004, N R-152). 3

17 Time-at-risk for the Counter Point program participants began in November, 1999, when the first participants completed the program, and ended on May 31, It is noted that these participants had already been in the community prior to entering the Counter-Point program. Their time in the community prior to the program, however, was not included in the analyses. The average time-at-risk for program participants was 6.2 years (M [days] = 794 (2.1 years); range = 1 to 2,321). For the comparison group, the time-at-risk was 9.1 years (M = 981 days (2.7 years), range = 3 to 3,314). This follow-up period began on November 14, 1997 and ended on May 31, The total release time for the program participants and comparison group were similar, but as already mentioned, the calculation of follow-up time for the program participants began upon treatment completion. This makes the comparisons more conservative. 4

18 Results Treatment Outcome Comparison Group Results Equivalency of the Program Participant and Comparison Groups As expected, given the matching procedure, the two groups of offenders did not significantly differ on actuarial risk (t =.13, ns) nor on prior program participation (t = 1.31, ns) (see Table 1). As noted in Table 2, there were no significant differences between these two groups on race, marital status, or previous youth conviction. Statistical Analyses To determine the impact of the Counter-Point program on recidivism rates, a series of Cox regression and negative binomial regression analyses were conducted. Cox regression analyses tested for new offences (i.e., the presence or absence of recidivism) and negative binomial regression analyses tested for offence density (i.e., frequency of new offences). Both Cox and binomial regression analyses allow for the examination of the independent effect of a predictor variable on the dependent variable, while controlling for other variables. In this study, all regression analyses examined whether participation in the Counter-Point program had an effect on new offences and offence density independent of time-at-risk and criminogenic need. Cox and binomial regression analyses provide a risk ratio. A risk ratio less than 1 indicates a positive impact of Counter-Point participation on recidivism (i.e., Counter-Point participants showed less recidivism than the comparison group). A risk ratio greater than 1 would indicate a negative impact of Counter-Point on recidivism (i.e., rates of recidivism for Counter-Point participants would be higher than those of the comparison group). For each risk ratio, if the range of the 95% confidence interval does not specifically contain the value 1.00, the risk ratio is statistically significant (Tables 4 6, 9). The analyses were conducted in three stages. First, regression analyses were conducted to compare all Counter-Point participants, including drop-outs, to the comparison group on new offences and offence density. These analyses also examined race and risk level categories. Second, the pre- and post-treatment psychometric tests results of the program completers were examined. Third, as shown in Table 3, the Counter-Point program participant group was divided into those 5

19 who completed the program, called Completers, and those who started but failed to complete Counter-Point, called Drop-outs, resulting in a three-group comparison. Table 1 Mean Differences on Risk and Prior Program Participation for Counter-Point Participants and Comparison Offenders Counter-Point Mean (SD) Comparison Risk (SIR-R1) ª (9.33) (9.31).13 Prior Program (# previous programs) 1.70 (1.37) 1.57 (1.23) 1.31 ª Some cases missing due to unavailability of data. b All analyses yielded non-significant results. t b 6

20 Table 2 Racial Composition, Marital Status, and Previous Youth conviction for Counter-Point Participants and Comparison Offenders % Counter-Point % Comparison ² a Racial Composition 6.98 Caucasian Aboriginal 8.5 b 12.7 Black Asian Hispanic Other Marital Status 2.53 Common Law Single Married Divorced Separated Widowed Previous Youth Conviction c a All analyses yielded non-significant results; b Eleven cases were wrongly keyed in the initial study; c n = 502. Impact of the Counter-Point Participation Group Failure Rates For descriptive purposes only, Table 3 shows the unadjusted rates of new offences for the Counter-Point program participants, the subgroups of Completers and Drop-outs, and the comparison group. These rates are unadjusted in that they do not take into account time-at-risk. As explained in the statistical analysis section, the impact of Counter-Point participation on recidivism will be determined via regression analyses 7

21 Table 3 Unadjusted Recidivism Rates (%) of Counter-Point Participants and Comparison Group New Offences % All Program Participants (n = 331) 40.1 Completers (n = 242) 35.7 Drop-outs (n = 89) 51.6 Comparison Group (n = 331) 63.6 The General Impact of the Counter-Point Program on Recidivism The risk ratios and confidence intervals obtained for new offences are reported in Table 4. These analyses compared the Counter-Point program participants (including those who started but failed to complete the program) with the comparison group. Results showed that after controlling for criminogenic need ratings, the rate of recidivism for Counter-Point program participants was 20% lower than for the comparison group [(0.80-1)*100 = -20]. The inclusion of drop-outs group (N = 89) with the completers makes these analyses a conservative result. In predicting offence density, negative binomial regression results indicated that program participation was highly significant (.23, p <.001). Thus, participating in the Counter-Point program, even after controlling for criminogenic need and days of opportunity to re-offend (not offset), reduced the frequency of criminal offences. 8

22 Table 4 Cox Regression Analyses for New Offences of Counter-Point Participants and Comparison Offenders, Controlling for Criminogenic Need Risk Ratio (95% Confidence Intervals) New Offences Criminogenic Need 1.24** ( ) Program Participation 0.80* ( ) * p =.06. ** p <.01. The Impact of the Counter-Point Program on Recidivism across Risk Levels To examine whether Counter-Point had a differential impact across risk levels, separate Cox regression analyses were conducted within each of the low, medium, and high risk categories (Table 5). As expected, greater reductions in rates of recidivism were observed for the high risk program completers (50%) compared to the high risk comparison group. In other words, completion of the Counter-Point program did benefit higher risk offenders. Surprisingly, the low risk group also received benefit from the program (39%). In predicting offence density, negative binomial regression results indicated that offenders who participated in the Counter-Point program had significantly reduced density of offending for all three levels of risk: high risk (.06, p <.001), medium risk, (.16, p <.001) and low risk (.17 (not offset) p <.001). Thus, completion of Counter-Point, even after controlling for criminogenic need and days of opportunity, reduced the frequency of criminal offences at all levels of risk. 9

23 Table 5 Cox Regression Analyses for New Offences of Low, Medium, and High Risk Counter-Point Participants, Controlling for Criminogenic Need Risk Ratio (95% Confidence Interval) Risk Level New Offences Low Risk (n = 134) 0.61* ( ) Medium Risk (n = 63) 0.80 ( ) High Risk (n = 134) 0.50** ( ) *p <.05. ** p <.01. The Impact of the Counter-Point Program on Recidivism across Races Table 6 presents the results obtained by performing Cox regression analyses on the recidivism rates of each race group. While all race groups showed reductions in recidivism (Caucasian 25%; Aboriginal 25%; Other Racial Minorities 35%) only the Caucasian group results reached statistical significance. The lack of statistical significance in reductions of recidivism for the Aboriginal and the Other Racial Minorities groups are due to the small sample size. With the offence density outcome, the negative binomial results indicated that all three racial categories of Counter-Point Program Participants were less likely to have new multiple offences than the comparison group. Specifically, results showed the following likelihood of reduction in frequency of offending: Caucasians = 0.34 (p <.001), Aboriginal = 0.22 (p <.01), and the Other Racial Minorities category Risk Ratio = 0.16, p <.001). 10

24 Table 6 Cox Regression Analyses for New Offences of Caucasian, Aboriginal, and Other Racial Minority of Counter-Point Participants vs. Comparison Group, Controlling for Criminogenic Need Risk Ratio (95% Confidence Interval) Program Participants New Offences Caucasian (n = 255) 0.75* ( ) Aboriginal (n = 28) 0.75 ( ) Other Racial Minorities (n = 48) 0.65 ( ) * p <.05. The Impact of the Counter Point Program on Antisocial Attitudes Complete pairs of pre- and post-program psychometric tests were only available for approximately two-thirds of the Counter-Point participants due to either missing values or failure to complete. The exact sample size for each test is indicated in Table 7. Paired sample t-tests and effect sizes were used to determine whether the psychometric measures exhibited dynamic validity. Dynamic validity relates to the ability of a psychometric instrument to measure change. Effect sizes measure the magnitude of the change. For this study, effect sizes were calculated via a within standard deviation statistic (Dunlop, Cortina, Vaslow, & Burke, 1996). Effect sizes around.30 are considered to be between small and medium effect sizes (Cohen, 1988). As presented in Table 7, most measures exhibited statistically significant improvements in the expected direction (p <.01) at post- versus pre-program. There was one notable exception: following completion of the program, offenders reported an increase in Number of Criminal Friends. Percent Change One of the purposes of calculating pre-post test results is to determine how much 11

25 treatment gain occurred. To facilitate an understandable figure, the data were put into a common metric, the Percent of the Maximum Possible (POMP), where 0 represents the minimum possible score and 100 represents the maximum possible score. The POMP score is calculated for each participant's score by (observed - minimum) / (maximum - minimum) x 100, where observed = the observed raw scale score for a single case, minimum = the minimum possible score on the scale, and maximum = the maximum possible score on the scale (Cohen, Cohen, Aiken, & West, 1999). The post-test POMP score was then subtracted from the pre-test POMP score. The difference between the raw pre-test scores and between the POMP will produce similar statistical results. But with the POMP, the size of the mean difference will be conveyed in a percent format. Using POMP scores allows for different scales to be compared. As shown in Table 7, most of the change percentages are in the five percent range. Overall, these results indicate that the Counter- Point program was effective at reducing the endorsement of antisocial attitudes and/or unproductive or damaging criminal attributions. Dynamic Areas/Mechanisms of Change More important than dynamic validity however is the presence of predictive dynamic criterion validity. Predictive dynamic criterion validity refers to the ability of the change scores observed on an instrument to predict rates of recidivism. This type of predictive validity allows for two observations. First, it shows that a changeable content area is sufficiently dynamic to predict recidivism. Second, a changeable content area is indicative of the mechanisms involved in treatment change. Following a decision tree developed by Zumbo (1999) each set of difference scores were evaluated as to whether raw or residual scores should be used. All the evaluations by the decision tree suggested that using raw change scores would maximize the reliability of the outcome. Raw gains consisted of the simple differences between the post-assessment scores and the pre-assessment scores. These simple difference scores were the bases for the assessment of predictive dynamic validity. Results showed that reductions in rates of recidivism were associated with raw change scores for only one psychometric scale. Specifically, decreases on the Attitudes towards Violence (MCAA) significantly predicted a reduction in the New Offence outcome (r =.15, p <.05). None of the pre- post-scale change scores predicted offence density. 12

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27 Table 7 Paired Sample t-tests on Psychometric Measures Measure Mean (SD) t Effect Size % Change Pre Post Pride in Delinquency Scale (n = 224) (38.66) (37.19) 2.94** Criminal Sentiments Scale -Modified ALCP (n = 222) (8.60) (8.16) 5.29** TLV (n = 222) 5.36 (3.73) 4.09 (3.50) 5.24** ICO (n = 222) 4.36 (2.09) 3.94 (2.16) 2.59* Total (n = 222) (12.73) (12.35) 5.75** Neutralization Measure - Modified (n = 217) Frequency 4.97 (4.73) 5.22 (5.48) Measure of Criminal Attitudes and Associates Part A Number of Criminal Friends (n = 7.54 (3.00) 7.98 (2.73) -1.97* ) Criminal Friend Index (n = 189) 5.38 (6.75) 5.38 (6.92)

28 Table 7 (cont.) Part B Violence (n = 228) 2.51 (2.79) 1.80 (2.20) 4.59** Entitlement (n = 228) 4.34 (2.26) 3.95 (2.09) 2.91** Antisocial Intent (n = 228) 3.05 (2.82) 2.29 (2.52) 5.23** Associates (n = 228) 5.99 (2.46) 5.86 (2.34) Part B Total (n = 228) (8.07) (6.85) 5.23** Criminal Attribution Inventory (n = 224) Psychopathology 3.60 (2.21) 3.45 (2.28) Personal 5.69 (2.33) 5.95 (2.28) Victim 3.15 (2.45) 2.55 (2.26) 4.49** Alcohol 3.90 (2.70) 3.16 (2.68) 4.75** Societal 3.42 (2.56) 2.62 (2.31) 4.73** Random 3.97 (1.96) 3.39 (2.03) 4.35** * p <.05. ** p <

29 Drop-out Analyses Reasons for Failure to Complete the Program In this study, 26.8% of offenders who enrolled in Counter-Point actually failed to complete the program. A breakdown of the various reasons for program non-completion is available in Table 8. Although some offenders (i.e., 14.6%) withdrew from the program for different reasons without any penalty, 25.8% terminated the program early due to a suspension, and 16.9% due to the commission of a new offence. Table 8 Reasons for Program Non-Completion (N = 89) % Non-Completers Withdrawal without Penalty 14.6 Suspension 25.8 New Offence 16.9 Unescorted Temporary Absence 22.5 Warrant Expiry Date 3.4 Inappropriate Behaviour 12.4 Other 4.5 Recidivism Rates of Counter-Point Completers and Drop-outs Supplementary Cox regression analyses were conducted to examine differences in recidivism rates between offenders who completed the Counter-Point program and those who started, but failed to complete the program. After controlling for criminogenic need, risk, and previous program participation, results show that offenders who started but failed to complete Counter-Point had double the rates of recidivism than program completers (see Table 9). 16

30 Table 9 Cox Regression Analyses for New Offences of Counter-Point Completers (vs. Drop-outs), Controlling for Criminogenic Need, Risk, and Previous Program Participation Risk Ratio (95% Confidence Interval) New Offences Program Completers 0.50** ( ) ** p <

31 Discussion This study extended the initial follow-up and confirmed the original conclusions that the Counter-Point program is effective in altering antisocial attitudes and reducing rates of reoffending. After controlling for pre-existing differences in criminogenic need, risk, and prior program participation, including offenders who started but failed to complete the program, participation in Counter-Point was associated with a 20% reduction in the risk of committing a new offence in the community. More striking is the reduction in the number of criminal convictions in program participants, indicating that Counter-Point participation not only decreases the likelihood that an offender will return to criminal behaviour, it also impacted on the overall frequency (number of convictions) of criminal conduct. These results are consistent with other research findings on the effectiveness of correctional programs (Andrews & Bonta, 2003). As noted by Gendreau, Goggin and Smith (1999), the meta-analyses of offender treatment indicate that a 15% to 30% reduction in recidivism is a reasonable objective under most conditions (p. 183). Interestingly, the risk principle (Andrews & Bonta, 2003), which suggests that greater treatment benefits are achieved for higher risk groups, received minimal support in this study as significant reductions in recidivism occurred for both high and low risk groups. As found in the initial evaluation of the program, Counter-Point continues to show that it works equally well within various racial categories. It is noted that while the Caucasians group showed greater treatment results, this was likely influenced by the significantly larger number of Caucasian participants. Before and after-program assessment of treatment targets allows for an examination of change. Following completion of the program, results showed that improvements in treatment were achieved: the majority of the psychometric measures utilized in the Counter-Point program changed in the anticipated direction, showing statistical reductions between four and seven percent. These results suggest that antisocial attitudes can be reduced, but that this reduction is a difficult task, involving programming over a 3-month period. It is noted that not all the measures showed improvements following the program participation. Counter-Point participants reported that the number of criminal friends increased at the end of treatment. This unexpected direction of 18

32 change may be due to the fact that the offenders in the program developed a better understanding of their friends, hence reporting (perhaps with greater honesty) a greater number of criminal associates. Alternatively, it is possible that the program does not sufficiently address this component. When compared to program Completers, partial exposure to the program content (i.e., Drop-outs) was associated with a 50% increase in the likelihood of recidivism. Most would agree that offenders who drop out of programs are actually at higher risk of reoffending as some of the client characteristics that put the offender at risk for not completing treatment are also likely to put him or her at risk for recidivism (Wormith and Olver, 2002, p. 449). This referenced study compared program completers to non-participants and found program non-completers showed poorer correctional outcomes following release. These combined results point strongly to the need to develop strategies to identify and help participants complete their correctional programs (Nunes & Cortoni, 2006). Limitations of Findings This study did not randomly select and assign offenders to groups. Although attempts were made to control for several potential confounding variables, a number of other, perhaps equally important variables (e. g., motivation level, institutional behaviour, and educational level) could have differed. Another limitation of the present study is the reliance on rates of new offences and offence density as the outcome measures. This may have underestimated other benefits of the intervention, such as the establishment of better interpersonal relationships, and prolonged involvement in employment and education (Henning & Frueh, 1996; Latessa & Travis III, 1992). Implications and Suggestions for Future Research While support for the effectiveness of the Counter-Point program in reducing rates of recidivism is provided, the drop-out rate raises some concerns regarding overall treatment efficiency. Given that 26.9% of the participants dropped out, more effort should be put into retaining participants in the treatment program. Such factors as motivational interviewing, group processes, cultural issues, mental health concerns, and personality characteristics are all factors 19

33 that should receive increased attention. These issues should be addressed in developmental research, the delivery of the program, and in program evaluation. The development of a theoretically sound and empirically valid understanding of responsivity issues would prove beneficial. Research into the interactive effects among different types of treatments, treatment providers, and participants would also be profitable. An area of investigation that would be particularly interesting relates to whether the reductions observed in antisocial attitudes would actually translate into a corresponding increase in prosocial attitudes. In other words, it is conceivable that Counter-Point is successful at altering offenders underlying antisocial attitudes, but does very little to increase prosocial attitudes. Reduction by itself may not be sufficient to induce a noticeable change in behaviour for some individuals. Future research should examine the potential moderating effect of prosocial attitudes on the relationship between antisocial attitudes, antisocial tendencies, and antisocial behaviour. Conclusion The Counter-Point program was associated with improved reintegration. This reaffirms the importance of the role of antisocial attitudes in criminal behaviour and provides support for the effectiveness of rehabilitative intervention. 20

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