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Perpetrator Programs: What we know about completion and re-offending

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Presentation on theme: "Perpetrator Programs: What we know about completion and re-offending"— Presentation transcript:

1 Perpetrator Programs: What we know about completion and re-offending
A/Prof Reinie Cordier

2 Introductory notes Results based on findings from systematic reviews and meta-analysis which allows pooling of data from several studies Cohen-d and Olkins- interpretation: ≤0.2: small; ≤0.5 medium; ≥0.8 large effect size Rate of reporting reoffence Police vs official reports Rate of reoffending higher when reported by couples, compared with OR

3 Factors that influence treatment and recidivism?
Measurement of recidivism Study design Follow-up time Type of intervention Duration of intervention

4 Measures of recidivism
Official reports: police/court/prison databases Couple/partner reports: both couples Victim and perpetrator reports respectively Rate of reoffending is significantly higher as measure by couple reports rather than official reports +0.156, z = 13.0, p < .001 (Arias 2013) Explained by under-reporting of official reports Rate of reporting reoffence Police vs official reports Rate of reoffending higher when reported by couples, compared with OR

5 Study design Official reports (Feder 2005)
Experimental: d= .26, significant, positive reduction in recidivism 20%  13% Quasi: comparing offenders mandated to treatment to those not (therefore no treatment), small negative effect size, non sig (d = ) Quasi: comparing treatment completers to non-completers, significant, positive effect (d = .97, p < .05) RCT were more effective in reducing re-offending than in quasi experimental studies Quasi: comparing offenders mandated to treatment to those not (therefore no treatment), small negative effect size, non sig (d = -0.14) (page 251) Quasi: comparing treatment completers to non-completers, significant, positive effect (d = .97, p < .05) (page 252)

6 Study design Police report (Arias 2013)
Experimental: d = .12, (95%CI ) (Arias 2013) Quasi: d = .23, (95%CI: 0.14 – 0.32) Partner report (Arias 2013) Experimental: d = .09, (95%CI: – 0.21) (Arias 2013) Quasi: d = 0.34 (95%CI: ) Victim report: null overall effect for victim reports (Feder 2005) Experimental: d = 0.01 non-significant positive effect Quasi: d = non-significant negative, effect RCT were more effective in reducing re-offending than in quasi experimental studies Quasi: comparing offenders mandated to treatment to those not (therefore no treatment), small negative effect size, non sig (d = -0.14) (page 251) Quasi: comparing treatment completers to non-completers, significant, positive effect (d = .97, p < .05) (page 252)

7 Follow up time Official reports (Arias 2013)
≤12 months: non-significant positive  = .18 > 12 months: non-significant negative  = 0.04 Couple reports (Arias 2013) ≤12 months: non-significant negative = 0.03 >12 months: non significant positive at  = 0.12 Follow-up period was not a differential indicator of treatment efficacy Arias page 158

8 Type of intervention Official reports (Arias 2013)
Duluth: non-significant positive effect  = 0.41 (38% efficacy rate), CBT: non-significant positive effect  = 0.47 (42% efficacy rate), “Other”: significant positive effect  = 0.52 (moderate size) Police reports (Babcock 2004) Experimental designs: Duluth: significant positive effect (d = 0.19) CBT and “other”: unknown, analysis lacked power Quasi: Duluth: significant positive effect (d = .32) CBT: non-significant positive effect (d = .27) “Other”: significant positive effect (d = .27) No significant difference between Duluth and “Other” Other Pscho dynamic; anger management; mind body bridging = psychological-psychiatric treatment with a focus on psychopathology rather than gender violence Positive means reduce recidivism

9 Duration of intervention
Official reports (Arias 2003) Brief (< 16 weeks/sessions): non-significant positive effect  = .18, Long-term (> 16 weeks/sessions): significant positive effect  = 0.49 Couple reports (Arias 2003) Brief: non-significant positive effect  = 0.16 long term: non-significant positive effect  = 0.14 Long-term interventions are more efficacious in OR, but not in the daily life of couples

10 What factors influence program attrition?
Employment Age Income Education Race Marital status History of previous offenses Court mandated attendance Attitude/motivation to change Treatment type

11 Factors influencing attrition
Employment Employed 20% more likely to complete treatment than unemployed (Jewell 2010) Unemployment associated with increased attrition: rw = 15 (Olver 2001) Age Older men 16% more likely to complete treatment than younger (Jewell 2010) Younger age associated with increased attrition: rw,= -.10 (Olver 2001) Income Higher incomes 13% more likely to complete than lower (Jewell 2010) Low income levels associated with increased attrition: rw= -.13 (Olver 2001)

12 Factors influencing attrition cont.
Education Attrition related to education: r = .08 (Jewell 2010) lower levels of education associated with increased attrition: rw = (Olver, 2001) Race Attrition related to race: r = .09 (Jewell 2010) Ethnic minority status associated with increased attrition : rw = .07 (Olver, 2001) Marital status Attrition related to marital status: r = .08 (Jewell 2010) Single marital status associated with increased attrition: rw = .07 (Olver, 2001)

13 Factors influencing attrition cont.
Previous offense Men attending treatment after their first DV offense 14% more likely to complete than those previously arrested/convicted (Jewell 2010) Men with criminal history 10% more likely to drop out (Jewell 2010) Drug and/or alcohol abuse 12% and 10% respectively less likely to complete than those without (Jewell 2010) Court-mandated Men who were court-mandated to were 16% more likely to complete treatment than those not court mandated (Jewell 2010) Treatment type Lowest attrition rates observed in CBT (24.3% %) (Olver 2001)

14 Factors influencing attrition cont.
Attitude/motivation (Olver 2001) Negative treatment attitude associated with higher attrition: rw = .75 Greater levels of motivation (rw = -.13) and treatment engagement (rw = -.21) associated with lower attrition Drop out significantly associated with increased general (rw = .20), violent (rw = .10) and non-violent (rw = .23) recidivism

15 Moderators of attrition
Compared to younger, older men sig more likely to complete CBT (r = .18, 95%CI: 0.12 to .23, k = 10) or unspecified (r = .13, 95%CI: 0.01 to .24, k = 4) than feminist psycho-educational (r = .02, 95%CI: –0.10 to .13, k = 7). Compared to not court mandated, Men court mandated to treatments more likely to: complete feminist-educational (r = 0.31, 95%CI: 0.23 to 0.39, k = 3) than CBT (r = .10, 95%CI: 0.01 to 0.19, k = 6) or unspecified (r = .03, 95%CI: –0.12 to 0.18, k = 2)

16 Moderators of attrition
Compared to men with more education, men less educated more likely to: drop out of feminist psycho-educational (r = .14, 95%CI: .08 to .20, k = 6) than CBT (r = .10, 95%CI: .05 to .15, k = 11) or unspecified, (r = .01, 95%CI: –.05 to .06, k = 6) Compared to younger, Older men more likely to: complete programs of shorter duration (16 or less weeks; r = 0.18, 95%CI: to 0.24, k = 11) than longer (r = .08, 95%CI: 0.02 to 0.16, k = 9)

17 Recommendations Further studies needs to examine moderators that may explain why some offenders respond to treatment while others do not under similar treatment programmes (Arias 2013) Authors and reviewers to provide explicit details regarding the treatment contents, techniques and methods (Arias 2013) Studies to provide more detail on program participation, completion and attrition (e.g. number of sessions attended, length of treatment, reasons for non-compliance) (Olver 2001) Target treatment to specific sub-samples (motivational stages, types of violence, etc.) (Babcock 2004)

18 Recommendations Samples of offenders that are representative of the larger convicted population rather than a smaller subset of selected offenders (Feder 2005) Additional research to better understand the validity and reliability of official report and victim report measures (Feder 2005) Look at variables outside of demographics, and their relation to program attrition (i.e. motivation, therapeutic alliance, learning styles) (Jewell 2010) Pre-treatment sessions of motivational interviewing to prepare clients for formal treatment (Jewell 2010)

19 Conclusion Treatment of perpetrators had a positive non-significant effect Some treatments had negative effects for both CR and OR Overall – still had 38% efficacy rate Much still needs to be done: Program development Program evaluation Fitting the perpetrator to the best suited treatment


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