Structured risk assessment instruments are increasingly used in juvenile justice systems to support judicial decision making. They help juvenile justice authorities identify youths with a higher likelihood of repeat delinquency and reduce discretion associated with disposition decision making. To be effective, these instruments should be accurate across diverse populations. This study describes the predictive validity of the North Carolina Assessment of Risk (NCAR) in a sample of 9,534 adjudicated juveniles in North Carolina. Results show the predictive validity of the NCAR to differ by gender and race/ethnicity. Closer inspection reveals that risk factors for recidivism differed according to demographic group and that brief risk assessment instruments such as the NCAR leave other risk factors unmeasured. The results support the utility of risk assessment for juvenile justice decision making and suggest strategies to improve the validity of risk assessment for all offender groups.
Baird, C., Wagner, D., Healy, T., & Johnson, K. (1999). Risk assessment in child protective services: Consensus and actuarial model reliability. Child Welfare, 78, 723-748.
2.
Blum, R. W., Beuhring, T., Shew, M. L., Bearinger, L. H., Sieving, R. E., & Resnick, M. D. (2000). The effects of race/ethnicity, income, and family structure on adolescent risk behaviors. American Journal of Public Health, 90, 1879-1884.
3.
Brownfield, D., Sorenson, A. M., & Thompson, K. M. (2001). Gang membership, race, and social class: A test of the group hazard and master status hypotheses. Deviant Behavior, 22, 73-89.
4.
Chesney-Lind, M., & Shelden, R. G. (1998). Girls, delinquency, and juvenile justice (2nd ed.). Belmont, CA: West/Wadsworth.
5.
Clogg, C. C., Petkova, E., & Haritou, A. (1995). Statistical methods for comparing regression coefficients between models. American Journal of Sociology, 100, 1261-1293.
6.
Collett, D. (1994). Modeling survival data in medical research. New York: Chapman & Hall.
7.
Cottle, C. C., Lee, R. L., & Heilbrun, K. (2001). The prediction of criminal recidivism in juveniles: A meta-analysis. Criminal Justice and Behavior, 28, 367-394.
8.
Funk, S. J. (1999). Risk assessment for juveniles on probation: A focus on gender. Criminal Justice and Behavior, 26, 44-68.
9.
Hawkins, D. F., Laub, J. H., Lauritsen, J. L., & Cothern, L. (2000). Race, ethnicity, and serious and violent juvenile offending. Washington, DC: Office of Juvenile Justice and Delinquency Prevention.
10.
Hoge, R. D. (2002). Standardized instruments for assessing risk and need in youthful offenders. Criminal Justice and Behavior, 29, 380-396.
11.
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.
12.
Howell, J. C. (2003). Preventing and reducing juvenile delinquency: A comprehensive framework. Thousand Oaks, CA: Sage.
13.
Ilacqua, G. E., Coulson, G. E., Lombardo, D., & Nutbrown, V. (1999). Predictive validity of the Young Offender Level of Service Inventory for criminal recidivism of male and female young offenders. Psychological Reports, 84, 1214-1218.
14.
Jung, S., & Rawana, E. P. (1999). Risk and need assessment of juvenile offenders. Criminal Justice and Behavior, 26, 69-89.
15.
Lahey, B. B., Goodman, S. H., Waldman, I. D., Bird, H., Canino, G., Jensen, P., et al. (1999). Relationship of age of onset to the type and severity of child and adolescent conduct problems. Journal of Abnormal Child Psychology, 27, 247-260.
16.
Leiber, M. J., & Mack, K. Y. (2003). The individual and joint effects of race, gender, and family status on juvenile justice decision-making. Journal of Research in Crime and Delinquency, 40, 34-70.
17.
Leiber, M. J., & Stairs, J. M. (1999). Race, contexts, and the use of intake diversion. Journal of Research in Crime and Delinquency, 36, 56-86.
18.
Lipsey, M. W., & Derzon, J. H. (1998). Predictors of violent or serious delinquency in adolescence and early adulthood. In R. Loeber & D. P. Farrington (Eds.), Serious and violent juvenile offenders (pp. 86-105). Thousand Oaks, CA: Sage.
19.
Loeber, R., & Farrington, D. P. (Eds.). (1999). Serious and violent juvenile offenders. London: Sage.
20.
MacDonald, J. M., & Chesney-Lind, M. (2001). Gender bias and juvenile justice revisited: A multiyear analysis. Crime & Delinquency, 47, 173-195.
21.
McDermott, P. A., & Spencer, M. B. (1997). Racial and social class prevalence of psychopathology among school-age youth in the United States. Youth & Society, 28, 387-414.
22.
Peck, R., Olsen, C., & Devore, J. (2001). Introduction to statistics and data analysis. Pacific Grove, CA: Duxbury.
23.
Peeples, F., & Loeber, R. (1994). Do individual factors and neighborhood context explain ethnic differences in juvenile delinquency?Journal of Quantitative Criminology, 10, 141-157.
24.
Pope, C. E., & Feyerherm, W. H. (1995). Minorities and the juvenile justice system. Washington, DC: Office of Juvenile Justice and Delinquency Prevention.
25.
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.
26.
Sharkey, J. D., Furlong, M. J., Jimerson, S. R., & O'Brien, K. M. (2003). Evaluating the utility of a risk assessment to predict recidivism among male and female adolescents. Education and Treatment of Children, 26, 467-494.
27.
Teplin, L. A., Abram, K. M., McClelland, G. M., Dulcan, M. K., & Mericle, A. A. (2002). Psychiatric disorders in youth in juvenile detention. Archives of General Psychiatry, 59, 1133-1143.
28.
Von Eye, A., & Bergman, L. R. (2003). Research strategies in developmental psychopathology: Dimensional identity and the person-oriented approach. Development and Psychopathology, 15, 553-580.
29.
Wagner, E. F., Lloyd, D. A., & Gil, A. G. (2002). Racial/ethnic and gender differences in the incidence and onset age of DSM-IV alcohol use disorder symptoms among adolescents. Journal of Studies on Alcohol, 63, 609-619.
