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failing on a certain type <strong>of</strong> crime. Since many <strong>of</strong> the specialized caseloads were drugsfocused, <strong>of</strong>fenders may have been monitored more closely for substance abuse and violated for failing drug tests. This could explain the significant difference in technical violations between specialized and general caseloads (Q B = 3.95, p ≤ .047; specialized: N = 6, OR = 2.44, p ≤ .002; general: N = 10, OR = 1.19, p ≤ .430). <strong>The</strong> final set <strong>of</strong> moderator variables we examined relate to the type and ‘dosage’ <strong>of</strong> supervision intensity, which are a key part <strong>of</strong> our inquiry. We attempted to examine how the programs we studied attempted to increase intensity, and whether it is possible to draw any conclusions about what magnitude <strong>of</strong> increased intensity is necessary to really affect outcomes. Too few studies reported enough information to assess the second question, so we examine this separately using only the studies that did report target caseload sizes and numbers <strong>of</strong> contacts and drug tests. Tables 1.3 and 1.4 show the moderator analyses for the effects <strong>of</strong> intensity type on recidivism and technical violations respectively. On recidivism, we see little effect <strong>of</strong> any <strong>of</strong> the three main types <strong>of</strong> intensity increases (reduced caseloads, increased contacts, and mandatory drug tests), either within treatment groups or compared to controls. For technical violations, the raw effect sizes are considerably different between studies reporting and not reporting specific increases in intensity, but not in the direction expected. Studies that did not report reduced caseloads or increased contact reported higher odds <strong>of</strong> violations in the treatment groups. For increased drug testing, we also see significantly higher odds <strong>of</strong> violations in the treatment groups where drug tests were not a component <strong>of</strong> the program. <strong>The</strong>se results may need no further explanation than the fact that there are very few studies involved, so they may be highly skewed. In both analyses, 35
it should be noted that those programs not reporting a particular type <strong>of</strong> increase (e.g., caseload size) will still have increased intensity in other ways. Furthermore, studies assessing reduced caseloads will most likely also have involved more contacts simply because the probation <strong>of</strong>ficers had more time with their clients, even if increased contacts were not a stated component <strong>of</strong> the program. Thus, we cannot say much about the effects <strong>of</strong> specific changes in intensity with these results. We examined whether studies reporting increases in one or more components <strong>of</strong> intensity reported actual or planned ratios (e.g., planned caseload size in the treatment group compared to average caseloads on regular probation). Due to the amount <strong>of</strong> variability and the fact that planned amounts <strong>of</strong> supervision did not always translate into practice, we simply dichotomized dosage variables according to whether or not the dosage was changed by more or less than 100 per cent in the treatment group compared to the control group. Tables 1.5 and 1.6 show the results <strong>of</strong> this investigation for recidivism and technical violations respectively. ‘High’ dosage programs are those in which the number <strong>of</strong> contacts or drug tests was more than 100 per cent greater than control group standards. We were unable to include caseload size in the analysis because only one study reported a planned caseload difference <strong>of</strong> less than 100 per cent. Table 1.5 shows that neither high nor low dosages <strong>of</strong> contacts or drug tests appeared to greatly affect recidivism compared to regular probation. <strong>The</strong> results are similar for technical violations (Table 1.6). While we observe some large effects for drug test dosage and violations, the number <strong>of</strong> studies is very small. <strong>The</strong> finding for contact frequency and technical violations is unsurprising: the odds <strong>of</strong> failure for probationers in high contact ISPs compared to controls were higher than for those in low contact ISPs 36
Page 1 and 2: University of Penn
Page 3 and 4: In memory of Edwar
Page 5 and 6: Janel McCaffrey and Knakiya Hagans,
Page 7 and 8: traditional practice, we find no ev
Page 9 and 10: Methodology .......................
Page 11 and 12: LIST OF FIGURES Figure 1.1: Effect
Page 13 and 14: intensity makes no difference to re
Page 15 and 16: isk of committing
Page 17 and 18: impact of probatio
Page 19 and 20: which perhaps suggests that ISP is
Page 21 and 22: program intended to reduce the stra
Page 23 and 24: supervision with probation
Page 25 and 26: 3. To what extent do the risk/need
Page 27 and 28: Methods Scale (SMS: Farrington et a
Page 29 and 30: Types of Outcomes
Page 31 and 32: Description of met
Page 33 and 34: actual behavior. We analyze technic
Page 35 and 36: Treatment of quali
Page 37 and 38: treatment group, and those to the r
Page 39 and 40: Discussion of Resu
Page 41 and 42: were evaluated in the same report (
Page 43 and 44: direction of effec
Page 45 and 46: To what extent does program philoso
Page 47 and 48: Which other components of</
Page 49: .450; technical violations: Q B < .
Page 53 and 54: up in unpublished reports than thos
Page 55 and 56: violations first went before a judg
Page 57 and 58: 2 One U.S. estimate indicates that
Page 59 and 60: Tables Table 1.1: Characteristics <
Page 61 and 62: Table 1.3: Moderator Variable <stro
Page 63 and 64: Table 1.4: Moderator Variable <stro
Page 65 and 66: Figures Figure 1.1: Effect
Page 67 and 68: Figure 1.5: Effect of</stro
Page 69 and 70: CHAPTER 2. ‘Low-Intensity
Page 71 and 72: What Works in Probation Supervision
Page 73 and 74: to do with it. Furthermore, the mor
Page 75 and 76: to the New York City and Oregon stu
Page 77 and 78: Barnes et al. (forthcoming) have su
Page 79 and 80: paradox.” He suggests that ‘not
Page 81 and 82: fatal shootings in Philadelphia are
Page 83 and 84: the proportions of
Page 85 and 86: Interventions and Follow-Up Probati
Page 87 and 88: officers more <str
Page 89 and 90: 1. Does the effect of</stro
Page 91 and 92: all, resulting in a large number <s
Page 93 and 94: Differential treatment take-up and
Page 95 and 96: control group members who received
Page 97 and 98: effect of LIS on r
Page 99 and 100: incarcerated must also be removed f
Page 101 and 102:
offenders in our s
Page 103 and 104:
ecidivists in the sample, 77 commit
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(IRR = 1.41, p ≤ .107). SES did n
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probability of fai
Page 109 and 110:
The count model ou
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estimate is also practically identi
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twice the risk of
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an end. On the other hand, research
Page 117 and 118:
low-intensity supervision would imp
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Conclusion The aim
Page 121 and 122:
We found that low-risk of</
Page 123 and 124:
7 LIS participants who were transfe
Page 125 and 126:
Tables Table 2.1: Sample Characteri
Page 127 and 128:
Table 2.3: Frequency of</st
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Table 2.5: Instrumental Variables M
Page 131 and 132:
Table 2.7: Prevalence of</s
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Table 2.9: Time to Failure (Violent
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Table 2.12: Treatment Effect by Sub
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Table 2.14: Frequency of</s
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Table 2.16: Instrumental Variables
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Figures Figure 2.1: Risk-Based Allo
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Figure 2.5: Survival Time for LIS E
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CHAPTER 3. Risk Prediction for Effe
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sensitivity of the
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Programs should be designed to adhe
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weight information in an appropriat
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statistical model that would predic
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The Philadelphia m
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assignment pool. Backfill probation
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Little research has been done on th
Page 161 and 162:
already predicted to be at low risk
Page 163 and 164:
It assumes that if of</stro
Page 165 and 166:
involved. Crimes that obviously met
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We examine the potential interactio
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age is based on this date regardles
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obberies. The only
Page 173 and 174:
of low-intensity s
Page 175 and 176:
classified as low risk. The
Page 177 and 178:
All the risk ratios in Table 3.9 in
Page 179 and 180:
0.55. Raising the threshold results
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are partly selected on the basis <s
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make up the majority of</st
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strategy allows probation o
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Notes 1 In this study, murder, atte
Page 189 and 190:
Table 3.2: Sample Characteristics (
Page 191 and 192:
Table 3.6: Predictive Ability at Al
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Table 3.9: Post-Random Assignment O
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APPENDICES Appendix A: Systematic R
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combination. The s
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B. ELIGIBILITY CHECKLIST B1. First
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Other: txcxloth C6d. Additional pro
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D. SAMPLE LEVEL CODING SHEET Instru
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E. DEPENDENT VARIABLE CODING SHEET
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F14. Comparison group sample size f
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weight w is then recalculated (6),
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Study Sheffield (Males) 1976 (Folka
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Study Dallas TX 1992 (Turner & Pete
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Study Minnesota ISR 1995 (Deschenes
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Study Clark WA 2003 (Barnoski, 2003
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Study Whatcom WA 2003 (Barnoski, 20
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Study Los Angeles CA 2005 (Zhang &
Page 223 and 224:
Fed. Prob., 56, 12-17. Turner, Pete
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Study Reference Benekos & Sonnenber
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Study Reference Giblin (2002) Using
Page 229 and 230:
Study Reference Lasater et al. (n.d
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Study Reference Robertson (2000) Co
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Study Reference Turner & Greene (19
Page 235 and 236:
Appendix E: Philadelphia APPD Low-<
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Prevalence of Reci
Page 239 and 240:
Frequency of Recid
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Instrumental Variables Model: Preva
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Instrumental Variables Model: Preva
Page 245 and 246:
Post-RA Months in Jail and Probabil
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Scaled Schoenfeld Residuals Time =
Page 249 and 250:
BIBLIOGRAPHY Chapter 1 ** Denotes t
Page 251 and 252:
Cook, T. D., & Campbell, D. T. (197
Page 253 and 254:
Glaze, L. E, & Bonczar, T. P. (2009
Page 255 and 256:
MacKenzie, D. L. (2006a). What work
Page 257 and 258:
Petersilia, J., Turner, S., & Desch
Page 259 and 260:
safety first: 13 strategies for suc
Page 261 and 262:
Wilson, D. B. (2010). Meta-analysis
Page 263 and 264:
Angrist, J. D. (2006). Instrumental
Page 265 and 266:
Clear, T. R., & Hardyman, P. L. (19
Page 267 and 268:
period266.pdf Lowenkamp, C. T., Lat
Page 269 and 270:
Rosch, J. (2006). Deviant peer cont
Page 271 and 272:
Taxman, F. S., & Thanner, M. (2006)
Page 273 and 274:
statistical learning. Journal <stro
Page 275 and 276:
Federal Bureau of
Page 277 and 278:
Marsh, K., & Fox, C., (2008). <stro
Page 279:
Sherman, L. W. (1993). Defiance, de
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