Predicting juvenile offender recidivism: Risk-need assessment and juvenile justice officers

Psychiatry, Psychology and Law

Volumn 14, Issue 1, 2007, Pages 138-146

  Upperton, Rachel A ^a   Thompson, Anthony P ^a,b  

^a CHARLES STURT UNIVERSITY   (Australia)

^b CHARLES STURT UNIVERSITY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; CONTROLLED STUDY; FEMALE; FOLLOW UP; HIGH RISK BEHAVIOR; HUMAN; JUSTICE; JUVENILE DELINQUENCY; MALE; PREDICTIVE VALIDITY; RATING SCALE; RECIDIVISM; RISK ASSESSMENT;

EID: 34250010073     PISSN: 13218719     EISSN: None     Source Type: Journal    
DOI: 10.1375/pplt.14.1.138     Document Type: Article

References (51)

1. These Juvenile Justice Officers were volunteers from a group of 40 who had participated in a related qualitative study by the authors. They had previously been interviewed about how they normally determine whethet a young person is going to reoffend and their views about using a structured risk inventory. Preliminary results were reported by Upperton and Thompson (2003).
2. Scores were coded 0-9 because the scale was inadvertently printed with 9 rarher than 10 equal intervals.
3. Andrews, D.A. (1991). Recidivism is predictable and can be influenced: Using risk assessments to reduce recidivism. Forum on Corrections Research, 1(2), 11-17.
4. Andrews, D.A., & Bonta, J. (1994). The psychology of criminal conduct. Cincinnati, OH: Anderson Publishing.
5. Andrews, D.A., & Bonta, J.L. (2000). The Level of Service Inventory-Revised. User's manual. North Tonawanda, NY: Multi-Health Systems Inc.
6. Baker, K., Jones, S., Roberts, C., & Merrington, S. (2003). ASSET-The evaluation of the validity and reliability of the Youth Justice Board's assessment for young offenders. Findings from the first two years of the use of ASSET. Oxford: Centre for Criminological Research.
7. Bonta, J. (2002). Offender risk assessment: Guidelines for selection and use. Criminal Justice and Behavior, 29, 355-379.
8. Bonta, J., Law, M., & Hanson, K. (1998). The prediction of criminal and violent recidivism among mentally disordered offenders: A meta-analysis. Psychological Bulletin, 123, 123-142.
9. Catchpole, R.E.H., & Gretton, H.M. (2003). The predictive validity of risk assessment with violent young offenders. A 1-year examination of criminal outcome. Criminal Justice and Behavior, 30, 688-708.
10. Coolbaugh, K., & Hansel, C.J. (2002, March). The comprehensive strategy: Lessons learned from the pilot sites. Juvenile Justice Bulletin. Washington, DC: US Office of Juvenile Justice and Delinquency Prevention. Retrieved August 15, 2006, from http://www.ncjrs.gov/html/ojjdp/ jjbul2000_03_1/contents.html
11. Cottle, C.C., Lee, R.J., & Heilbrun, K. (2001). The prediction of criminal recidivism in juveniles: A meta-analysis. Criminal Justice and Behavior, 28, 367-394.
12. Cumberland, A.K., & Boyle, G.J. (1997). Psychometric prediction of recidivism: Utility of the risk needs inventory. The Australian and New Zealand Journal of Criminology, 30, 72-86.
13. Dawes, R.M., Faust, D., & Meehl, P.E. (1989). Clinical versus actuarial judgement. Science, 243, 1668-1674.
14. Day, A., Howells, K., Rickwood, D. (2004). Current trends in the rehabilitation of juvenile offenders. Trends & Issues in Crime and Criminal Justice No. 284. Canberra, Australian Capital Territory, Australia: Australian Institute of Criminology. Retrieved April 4, 2005, from http://www.aic.gov. au/publications/tandi2/tandi284t.html
15. Dembo, R., Schmeidler, J., Nini-Gough, B., Chin Sue, C., Borden, P., & Manning, D. (1998). Predictors of recidivism to a juvenile assessment center: A three year study. Journal of Child & Adolescent Substance Abuse, 7, 57-77.
16. Flores, A.W., Travis III, L.F., & Latessa, E.J. (2003). Case classification for juvenile corrections: An assessment of the Youth Level of Service/Case Management Inventory (YLS/CMI). Cincinnati, OH: Centre for Criminal Justice Research, University of Cincinnati.
17. Fullet, J., & Cowan, J. (1999). Risk assessment in a multi-disciplinary forensic setting: Clinical judgement revisited. The Journal of Forensic Psychiatry, 10, 276-289.
18. Gavazzi, S.M., Slade, D., Buettner, C.K., Partridge, C., Yarcheck, C.M., & Andrews, D.W. (2003). Toward conceptual development and empirical measurement of global risk indicators in the lives of court-involved youth. Psychological Reports, 92, 599-615.
19. Glueck, S., & Glueck, E. (1950). Unraveling juvenile delinquency. Cambridge, MA: Harvard University Press.
20. Glueck, S., & Glueck, E. (1974). Of delinquency and crime: A panorama of years of search and research. Springfield, IL: Charles C. Thomas.
21. Gray, N.S., Snowden, R.J., MacCulloch, S., Phillips, H., Taylor, J., & MacCulloch, M.J. (2004). Relative efficacy of criminological, clinical, and personality measures of future risk of offending in mentally disordered offenders: A comparative study of HCR-20, PCL:SV, and ORGS. Journal of Consulting and Clinical Psychology, 72, 523-530.
22. Grove, W.M., & Meehl, P.E. (1996). Comparative efficiency of informal (subjective, impressionistic) and formal (mechanical, algorithmic) predictions procedures: The clinical-statistical controversy. Psychology, Public Policy, and Law, 2, 293-323.
23. Hoge, R.D. (2002). Standardized instrument for assessing risk and need in youthful offenders. Criminal Justice and Behavior, 29, 380-396.
24. Hoge, R.D., & Andrews, D.A. (1995). Australian Adaptation of the Youth Level of Service/Case Management Inventory. North Tonawanda, NY: Multi-Health Systems Inc.
25. Hoge, R.D., & Andrews, D.A. (1996). Assessing the youthful offender: Issues and techniques. New York: Plenum.
26. Hoge, R.D., & Andrews, D.A. (2003). Youth Level of Service/Case Management Inventory. User's manual. North Tonawanda, NY: Multi-Health Systems.
27. Howell, J.C. (1995). Guide for implementing the comprehensive strategy for serious, violent, and chronic juvenile offenders. Washington, DC: Office of Juvenile Justice and Delinquency Prevention.
28. Jung, S., & Rawana, E.P. (1999). Risk and need assessment of juvenile offenders. Criminal Justice and Behavior, 26, 69-89.
29. Katsiyannis, A., & Archwamety, T. (1997). Factors related to recidivism among delinquent youths in a state correctional facility. Journal of Child and Family Studies, 6, 43-55.
30. Kleinmuntz, B. (1990). Why we still use our heads instead of formulas: Toward and integrative approach. Psychological Bulletin, 107, 296-310.
31. Krysik, J., & LeCroy, C.W. (2002). The empirical validation of an instrument to predict risk of recidivism among juvenile offenders. Research on Social Work Practice, 12, 71-81.
32. Marczyk, G.R., Heilbrun, K., Lander, T., & DeMatteo, D. (2003). Predicting juvenile recidivism with the PCL:YV, MAYSI, and YLS/CMI. International Journal of Forensic Mental Health, 2, 7-18
33. McLaren, K.L. (2000, June). Tough is not enough - Getting smart about youth crime. A review of research on what works to reduce offending by young people. Wellington, New Zealand: Ministry of Youth Affairs.
34. Meehl, P.E. (1954). Clinical versus statistical prediction. A theoretical analysis and a review of the evidence. Minneapolis, MN: University of Minnesota Press.
35. National Council on Crime and Delinquency (2000). Almeda county placement risk assessment validation. Draft of Final Report. Oakland, CA: Author.
36. Parker, R.J. (2002). Intersource agreement on the prediction of recidivism. Unpublished master's thesis, University of Canberra, Canberra, Australian Capital Tterritory, Australia
37. Putnins, A.L. (2005). Assessing recidivism risk among young offenders. The Australian and New Zealand Journal of Criminology, 38, 324-339.
38. Rice, M. E., & Harris, G.T. (1995). Violent recidivism: Assessing predictive validity. Journal of Consulting and Clinical Psychology, 63, 737-748.
39. Rice, M.E., & Harris, G.T. (2005). Comparing effect sizes in follow-up studies: ROC area, Cohen's d, and r. Law and Human Behavior, 29, 615-620.
40. Risler, E.A., Sutphen, R., & Shields, J. (2000). Preliminary validation of the juvenile first offender risk assessment index. Research on Social Work Practice, 10, 111-126.
41. 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, 329-344.
42. Schwalbe, C.S., Fraser, M.W., Day, S.H., & Arnold, E.M. (2004). North Carolina Assessment of Risk (NCAR): Reliability and predictive validity with juvenile offenders. Journal of Offender Rehabilitation, 40, 1-22.
43. th APS Annual conference (pp. 343-347). Melbourne, Victoria, Australia: The Australian Psychological Society Ltd.
44. Thompson, A.P. (2006). Do we need to worry about subgroup differences in juvenile offender risk-need assessment? In M. Katsikitis (Ed.), Proceedings of the 2006 Joint Conference of the APS and NZPsS (pp. 445-449). Auckland, New Zealand: The Australian Psychological Society Ltd.
45. Thompson, A.P., & Pope, Z. (2005). Assessing juvenile offenders: Preliminary data for the Australian Adaptation of the Youth Level of Service/Case Management Inventory (Hoge & Andrews, 1995). Australian Psychologist, 40, 207-214.
46. Thompson, A.P., & Putnins, A.L. (2003). Risk-need assessment inventories for juvenile offenders in Australia. Psychiatry, Psychology and Law, 10, 324-333.
47. Upperton, R., & Thompson, A.P., (2003). Risk assessment in juvenile justice: Predictive and practical utility. In M. Katsikitis (Ed.), Proceedings of the 38th APS Annual Conference (pp. 236-241). Melbourne, Victoria, Australia: Australian Psychological Society Ltd.
48. Warner, S.B. (1923). Factors determining parole from the Massachusetts reformatory Journal of Criminal Law & Criminology, 14, 172-207.
49. Walters, G.D. (2006). Risk-appraisal versus self-report in the prediction of criminal justice outcomes. A meta-analysis. Criminal Justice and Behaviour, 33, 279-304.
50. Webster, C.D., Harris, G.T., Rice, M.E., Cormier, C., & Quinsey, V.L. (1994). The violence prediction scheme: Assessing dangerousness in high risk men. Toronto, Canada: Centre of Criminology, University of Toronto.
51. Westen, D., & Weinberger, J. (2004). When clinical description becomes statistical prediction. American Psychologist, 59, 595-613.