Validity of initial, exit, and dynamic juvenile risk assessment: An examination across gender and race/ethnicity

References

• Andrews, D., Bonta, J., & Wormith, J. (2006). The recent past and near future of risk and/or need assessment. Crime and Delinquency, 52(1), 7–27. doi:10.1177/0011128705281756
   Web of Science ®Google Scholar
• Andrews, D. A., Hoge, R. D., & Leschied, A. W. (2002). Youth level of service and case management inventory. Toronto, Ontario, Canada: Multi-Health Systems.
   Google Scholar
• Andrews, D. A., Robinson, D., & Balla, M. (1986). Risk principle of case classification and the prevention of residential placements: An outcome evaluation of the share the parenting program. Journal of Consulting and Clinical Psychology, 54(2), 203–207. doi:10.1037/0022–006x.54.2.203
   PubMed Web of Science ®Google Scholar
• Andrews, D. A., Robinson, D., & Hoge, R. D. (1984). Manual for the youth level of service inventory. Ottawa, Ontario, Canada: Department of Psychology, Carleton University.
   Google Scholar
• Baglivio, M., & Jackowski, K. (2012). Examining the validity of a juvenile offending risk assessment instrument across gender and race/ethnicity. Youth Violence and Juvenile Justice, 11(1), 26–43.
   Web of Science ®Google Scholar
• Baglivio, M., & Jackowski, K. (2015). Evaluating the effectiveness of a victim impact intervention through the examination of changes in dynamic risk scores. Criminal Justice Policy Review, 26(1), 7–28.
   Google Scholar
• Beggs, S. M., & Grace, R. C. (2011). Treatment gain for sexual offenders against children predicts reduced recidivism: A comparative validity study. Journal of Consulting and Clinical Psychology, 79(2), 182–192. doi:10.1037/a0022900
   PubMed Web of Science ®Google Scholar
• Betchel, K., Lowenkamp, C., & Latessa, E. (2007). Assessing the risk of reoffending for juvenile offenders using the youth level of service/case management inventory. Journal of Offender Rehabilitation, 45(3/4), 85–108. doi:10.1300/j076v45n03_04
   Google Scholar
• Bonta, J., Rugge, T., Scott, T., Bourgon, G., & Yessine, A. (2008). Exploring the black box of community supervision. Journal of Offender Rehabilitation, 47(3), 248–270. doi:10.1080/10509670802134085
   Google Scholar
• Brown, S. L., Amand, M. D. S., & Zamble, E. (2009). The dynamic prediction of criminal recidivism: A three-wave prospective study. Law and Human Behavior, 33(1), 25–45. doi:10.1007/s10979–008-9139–7
   PubMed Web of Science ®Google Scholar
• Catchpole, R., & Gretton, H. (2003). The predictive validity of risk assessment with violent young offenders: A 1-year examination of criminal outcome. Criminal Justice and Behavior, 30(6), 668–708. doi:10.1177/0093854803256455
   Web of Science ®Google Scholar
• Cohen, M., Piquero, A., & Jennings, W. (2010). Estimating the costs of bad outcomes for at-risk youth and the benefits of early childhood interventions to reduce them. Criminal Justice Policy Review, 21(4), 391–434. doi:10.1177/0887403409352896
   Google Scholar
• Cohen, T. H., & VanBenschoten, S. W. (2014). Does the risk of recidivism for supervised offenders improve over time: Examining changes in the dynamic risk characteristics for offenders under federal supervision. Federal Probation, 78, 41–54.
   Google Scholar
• Cottle, C. C., Lee, R. J., & Heilbrun, K. (2001). The prediction of criminal recidivism in juveniles: A meta-analysis. Criminal Justice and Behavior, 28(3), 367–394. doi:10.1177/0093854801028003005
   Web of Science ®Google Scholar
• DeLong, E. R., DeLong, D. M., & Clarke-Pearson, D. L. (1988). Comparing the areas under two or more correlated Receiver Operating Characteristic Curves: A nonparametric approach. Biometrics, 44(3), 837–845. doi:10.2307/2531595
   PubMed Web of Science ®Google Scholar
• Flores, A., Travis, L., & Latessa, E. (2003). Case classification for juvenile corrections: An assessment of the youth level of service/case management inventory (YLS/CMI). Cincinnati, OH: Center for Criminal Justice Research, Division of Criminal Justice.
   Google Scholar
• Gardner, R. (2001). Psychological statistics using SPSS for windows. Upper Saddle River, NJ: Prentice Hall.
   Google Scholar
• Gatti, U., Tremblay, R., & Vitaro, F. (2009). Iatrogenic effect of juvenile justice. The Journal of Child Psychology and Psychiatry, 50(8), 991–998. doi:10.1111/j.1469–7610.2008.02057.x
   PubMed Web of Science ®Google Scholar
• Greiner, L. E., Law, M. A., & Brown, S. L. (2014). Using dynamic factors to predict recidivism among women a four-wave prospective study. Criminal Justice and Behavior, 42(5), 457–480. doi:10.1177/0093854814553222
   Web of Science ®Google Scholar
• Griffin, D., Murray, S., & Gonzalez, R. (1999). Difference score correlations in relationship research: A conceptual primer. Personal Relationships, 6(4), 505–518. doi:10.1111/j.1475–6811.1999.tb00206.x
   Web of Science ®Google Scholar
• Hanley, J., & McNeil, B. (1983). A method of comparing the areas under receiving operating characteristic curves derived from the same cases. Radiology, 148(3), 839–843. doi:10.1148/radiology.148.3.6878708
   PubMed Web of Science ®Google Scholar
• Hoge, R. D., Andrews, D. A., & Leschied, A. (2002). Youth level of service/case management inventory (YLS/CMI): User’s manual. Toronto, Ontario, Canada: MultiHealthServices.
   Google Scholar
• Howard, P. D., & Dixon, L. (2013). Identifying change in the likelihood of violent recidivism: Causal dynamic risk factors in the OASys violence predictor. Law and Human Behavior, 37(3), 163–174. doi:10.1037/lhb0000012
   PubMed Web of Science ®Google Scholar
• Jung, S., & Rawana, E. (1999). Risk and need assessment of juvenile offenders. Criminal Justice and Behavior, 26(1), 69–89. doi:10.1177/0093854899026001004
   Web of Science ®Google Scholar
• Labrecque, R. M., Smith, P., Lovins, B. K., & Latessa, E. J. (2014). The importance of reassessment: How changes in the LSI-R risk score can improve the prediction of recidivism. Journal of Offender Rehabilitation, 53(2), 116–128. doi:10.1080/10509674.2013.868389
   Google Scholar
• Mallett, C. A., & Stoddard-Dare, P. (2010). Predicting secure detention placement for African-American juvenile offenders: Addressing the disproportionate minority confinement problem. Journal of Ethnicity in Criminal Justice, 8(2), 91–103. doi:10.1080/15377931003761011
   Google Scholar
• Olver, M. E., Nicholaichuk, T. P., Kingston, D. A. & Wong, S. C. (2014). A multisite examination of sexual violence risk and therapeutic change. Journal of Consulting and Clinical Psychology, 82(2), 312–324. doi:10.1037/a0035340
   PubMed Web of Science ®Google Scholar
• Olver, M. E., Stockdale, K. C., & Wong, S. C. (2012). Short and long-term prediction of recidivism using the youth level of service/case management inventory in a sample of serious young offenders. Law and Human Behavior, 1(1), 1–15.
   Google Scholar
• Olver, M. E., Stockdale, K. C., & Wormith, J. S. (2014). Thirty years of research on the level of service scales: A meta-analytic examination of predictive accuracy and sources of variability. Psychological Assessment, 26, 156–176. doi:10.1037/a0035080
   PubMed Web of Science ®Google Scholar
• Onifade, E., Davidson, W., & Campbell, C. (2009). Risk assessment: The predictive validity of the youth level of service/case management inventory with African Americans and girls. Journal of Ethnicity in Criminal Justice, 7(3), 205–221. doi:10.1080/15377930903143544
   Google Scholar
• Onifade, E., Davidson, W., Campbell, C., Turke, G., Malinowski, J., & Turner, K. (2008). Predicting recidivism in probationers with the youth level of service case management inventory (YLS/CMI). Criminal Justice and Behavior, 35(4), 474–483. doi:10.1177/0093854807313427
   Web of Science ®Google Scholar
• Puzzanchera, C., & Adams, B. (2011). Juvenile arrests 2009. Washington, DC: U.S. Department of Justice, Office of Justice Programs, Office of Juvenile Justice.
   Google Scholar
• Puzzanchera, C., & Robson, C. (2014). Delinquency cases in juvenile court, 2010. Washington, DC: Office of Juvenile Justice and Delinquency Prevention.
   Google Scholar
• Rice, M., & Harris, G. (1995). Violent recidivism: Assessing predictive validity. Journal of Consulting and Clinical Psychology, 63(5), 737–748. doi:10.1037//0022–006x.63.5.737
   PubMed Web of Science ®Google Scholar
• Schlager, M., & Pacheco, D. (2011). An examination of changes in LSI-R scores over time: Making the case for needs-based case management. Criminal Justice and Behavior, 38(6), 541–553. doi:10.1177/0093854811402300
   Web of Science ®Google Scholar
• Schmidt, F., Hoge, R. D., & Gomes, L. (2005). Reliability and validity analyses of the youth level of service/case management inventory. Criminal Justice and Behavior, 32(3), 329–344. doi:10.1177/0093854804274373
   Web of Science ®Google Scholar
• Schwalbe, C. (2007). Risk assessment for juvenile justice: A meta-analysis. Law and Human Behavior, 31(5), 449–462. doi:10.1007/s10979–006-9071–7
   PubMed Web of Science ®Google Scholar
• Schwalbe, C. (2008). A meta-analysis of juvenile justice risk assessment instruments: Predictive validity by gender. Criminal Justice and Behavior, 35(11), 1367–1381. doi:10.1177/0093854808324377
   Web of Science ®Google Scholar
• Schwalbe, C., Fraser, M., Day, S., & Arnold, E. (2004). North Carolina assessment of risk (NCAR): Reliability and predictive validity with juvenile offenders. Journal of Offender Rehabiliation, 40(1/2), 1–22. doi:10.1300/j076v40n01_01
   Google Scholar
• Simourd, L., Hoge, R. D., & Andrews, D. A. (1991). The youth level of service inventory: An examination of the development of a risk/needs instrument. Presentation at the annual conference of the Canadian Psychological Association, Calgary.
   Google Scholar
• Vieira, T., Skilling, T., & Peterson-Badali, M. (2009). Matching court-ordered services with treatment needs: Predicting treatment success with young offenders. Criminal Justice and Behavior, 36(4), 385–401. doi:10.1177/0093854808331249
   Web of Science ®Google Scholar
• Vitopolous, N., Peterson-Badali, M., & Skilling, T. (2012). The relationship between matching service to criminogenic need and recidivism in male and female youth: Examining the RNR principles in practice. Criminal Justice and Behavior, 39(8), 1025–1041. doi:10.1177/0093854812442895
   Web of Science ®Google Scholar
• Vose, B., Lowenkamp, C., Smith, P., & Cullen, F. (2009). Gender and the predictive validity of the LSI-R: A study of parolees and probationers. Journal of Contemporary Criminal Justice, 25(4), 459–471. doi:10.1177/1043986209344797
   Google Scholar
• Vose, B., Smith, P., & Cullen, F. T. (2013). Predictive validity and the impact of change in total LSI-R score on recidivism. Criminal Justice and Behavior, 40(12), 1383–1396. doi:10.1177/0093854813508916
   Web of Science ®Google Scholar
• Welsh, J., Schmidt, F., McKinnon, L., Chattha, H., & Meyers, J. (2008). A comparative study of adolescent risk assessment instruments: Predictive and incremental validity. Assessment, 15(1), 104–115. doi:10.1177/1073191107307966
   PubMed Web of Science ®Google Scholar