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Predicting institutional misconduct using the Youth Level of Service/ Case Management Inventory

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Abstract

Offender assessment in corrections has advanced considerably over the last several decades. Currently, it is not uncommon to find correctional professionals using any number of objective standardized assessment instruments. While many of these instruments possess face validity as well as statistical predictive validity, more work is needed to test classification protocol on new populations, and in various correctional environments. The current paper investigates the predictive validity of the Youth Level of Service/Case Management Inventory (YLS/CMI) within an institutional setting. Specifically, the composite score rendered from the YLS/CMI is used to predict institutional misconduct. The YLS/ CMI was found to effectively differentiate between two levels of offender risk/ need, and was significantly related to outcome using several different statistical techniques.

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References

  • Andrews, D.A., & Bonta, J. (1994).The psychology of criminal conduct. Cincinnati, OH: Anderson.

    Google Scholar 

  • Andrews, D.A., & Bonta, J. (1998).The psychology of criminal conduct (2nd ed.). Cincinnati, OH: Anderson.

    Google Scholar 

  • Andrews, D.A., Bonta, J., & Hoge, R. (1990). Classification for effective rehabilitation: Rediscovering psychology.Criminal Justice & Behavior, 17(1), 19–52.

    Article  Google Scholar 

  • Ayers, C.D., Williams, J.H., Hawkins, J.D., Peterson, P.L., Catalano, R.F., & Abbott, R.D. (1999). Assessing correlates of onset, escalation, de-escalation, and desistance of delinquent behavior.Journal of Quantitative Criminology, 15(3), 277–306.

    Article  Google Scholar 

  • Barnoski, R. (1998).Juvenile rehabilitation administration assessments: Validity review and recommendations. Washington State Institute for Public Policy. Olympia, WA: U.S. Government Printing Office.

    Google Scholar 

  • Bonta, J., Law, M., & Hanson, R.K. (1998). The prediction of criminal and violent recidivism among mentally disordered offenders: A meta-analysis.Psychology Bulletin, 39, 127–144.

    Google Scholar 

  • Caggiano, A. D. (2000). Identifying violent-toward staff juvenile delinquents via the millon adolescent clinical inventory and neuropsychological measures.Journal of Offender Rehabilitation, 32(1/2), 147–165.

    Article  Google Scholar 

  • Calhoun, G.B., Glaser, B.A., & Petrocelli, J.V. (2002). Personality characteristics of male juvenile offenders by adjudicated offenses as indicated by the MMPI-A.Criminal Justice and Behavior, 29(2), 183–201.

    Article  Google Scholar 

  • Catchpole, R.E., & Gretton, H.M. (2003). Predictive validity of risk assessment with violent young offenders: A 1-year examination of criminal outcome.Criminal Justice and Behavior, 30(6), 688–708.

    Article  Google Scholar 

  • Clear, T. (1994).Harm in American penology: Offenders, victims, and their communities. Albany, NY: SUNY Press.

    Google Scholar 

  • Cottle, C.C., Lee, R.J., & Heilbrun, K. (2001). Prediction of criminal recidivism in juveniles: A meta-analysis.Criminal Justice and Behavior, 28(3), 367–394.

    Article  Google Scholar 

  • Dembo, R., & Schmeidler, J. (2003). Classification of high-risk youths.Crime and Delinquency, 49(2), 201–230.

    Article  Google Scholar 

  • Flores, A.W., Travis, L.F., & Latessa, E.L. (2003).Case classification for juvenile corrections: An assessment of the youth level of service/case management inventory (YLS/ CMI). National Institute of Justice. Rockville, MD: U.S. Government Printing Office.

    Google Scholar 

  • Gendreau, P., Goggin, C., & Law, M. (1997). Predicting prison misconducts.Criminal Justice and Behavior, 24(4), 414–431.

    Article  Google Scholar 

  • Gendreau, P., Little, T., & Goggin, C. (1996). A meta-analysis of the predictors of adult offender recidivism: What works!Criminology, 34, 575–607.

    Article  Google Scholar 

  • Grove, W.M., Zald, D.H., Lebow, B.S., Snitz, B.E., & Nelson, C. (1995).Clinical vs. mechanical prediction: A meta-analysis. Unpublished manuscript.

  • Hanson, R.K., & Bussiere, M.T. (1998). Predicting relapse: A meta-analysis of sexual offender recidivism studies.Journal of Consulting and Clinical Psychology, 66, 348–362.

    Article  Google Scholar 

  • Hoge, R. (2002). Standardized instruments for assessing risk and need in youthful offenders.Criminal Justice and Behavior, 29(4), 380–396.

    Article  Google Scholar 

  • Hoge, R., & Andrews, D.A. (1996).The youth level of service/case management Inventory: description and evaluation. Manuscript presented at the American Psychological Association, Toronto, Canada.

  • Holsinger, A.M., Lowenkamp, C.T., & Latessa, E.J. (2003). Ethnicity, gender, and the level of service inventory—Revised.Journal of Criminal Justice, 31(4), 309–320.

    Article  Google Scholar 

  • Jones, P. R., & Harris, P. W. (1999). Developing an empirically based typology of delinquent youths.Journal of Quantitative Criminology, 15(3), 251–276.

    Article  Google Scholar 

  • Jones, P.R, Harris, P.W., Fader, J., Burrell, J., & Fadeyi, A. (1999). Identifying chronic juvenile offenders.Corrections Compendium, 24(8), 1–23.

    Google Scholar 

  • Jung, S., & Rawana, E.P. (1999). Risk and need assessment of juvenile offenders.Criminal Justice & Behavior, 26(1), 69–89.

    Article  Google Scholar 

  • Lowenakmp, C.T., Holsinger, A.M., Brusman-Lovins, L., & Latessa, E.J. (2004). Assessing the inter-rater agreement of the level of service inventory—Revised.Federal Probation, 68(3), 34–38.

    Google Scholar 

  • Lowenkamp, C.T., & Latessa, E.J. (2005). Increasing the effectiveness of correctional programming through the risk principle: Identifying offenders for residential placement.Criminology & Public Policy, 4(2), 263–290.

    Article  Google Scholar 

  • Lowenkamp, C.T., Holsinger, A.M. & Latessa, E.J. (2001). Risk/need assessment, offendersclassification, and the role of childhood abuse.Criminal Justice & Behavior, 28(5), 543–563.

    Article  Google Scholar 

  • Marczyk, G.R., Heilbrun, K., Lander, T., & DeMatteo, D. (2005). Juvenile decertification: Developing a model for classification and prediction.Criminal Justice & Behavior, 32(3), 278–301.

    Article  Google Scholar 

  • Motiuk, L. L. (1995). Using familial factors to assess offender risk and need.Forum on Corrections Research, 7(2), 19–22.

    Google Scholar 

  • National Institute of Corrections (2000).Promoting public safety using effective interventions with offenders. Washington, DC.

  • Righthand, S., Prentky, R., Knight, R., Carpenter, E., Kecker, J.E., & Nangle, D. (2005). Factor structure and validation of the juvenile sex offender assessment protocol (JSOAP).Sexual Abuse: A Journal of Research and Treatment, 17(1), 13–30.

    Google Scholar 

  • Schmidt, F., Hoge, R., & Gomes, L. (2005). Reliability and validity analyses of the Youth Level of Service/Case Management Inventory.Criminal Justice & Behavior, 32(3), 329–344.

    Article  Google Scholar 

  • Shields, I.W, & Simourd, D.J. (1991). Predicting predatory behavior in a population of incarcerated young offenders.Criminal Justice & Behavior, 18(2), 180–194.

    Article  Google Scholar 

  • Simourd, D.J. (1997). The criminal sentiments scale-modified and pride in delinquency scale.Criminal Justice and Behavior, 24, 52–70.

    Article  Google Scholar 

  • Simourd, D.J., & Andrews, D.A. (1994). Correlates of delinquency: A look at genderdifferences.Forum on Corrections Research, 6(1), 26–31.

    Google Scholar 

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Authors and Affiliations

  1. Department Sociology/Criminal Justice and Crimingology, University of Missouri, Kansas City, 208 Haag Hall, 64110, Kansas City, MO

    Alexander M. Holsinger Ph.D.

  2. University of Cincinnati, USA

    Christopher T. Lowenkamp Ph.D. & Edward J. Latessa Ph.D.

Authors
  1. Alexander M. Holsinger Ph.D.
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  2. Christopher T. Lowenkamp Ph.D.
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  3. Edward J. Latessa Ph.D.
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Correspondence to Alexander M. Holsinger Ph.D..

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Holsinger, A.M., Lowenkamp, C.T. & Latessa, E.J. Predicting institutional misconduct using the Youth Level of Service/ Case Management Inventory. Am J Crim Just 30, 267–284 (2006). https://doi.org/10.1007/BF02885895

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