Factors That Influence Employment for Justice-Involved Youth: The Juvenile Justice Work Qualifications Scale
DOI:
https://doi.org/10.52935/25.1851.3Keywords:
Juvenile Justice, Work Qualifications, Employers’ Perspectives, Workforce DevelopmentAbstract
Understanding employer perspectives toward necessary work qualifications for justice-involved youth and aligning transition planning and employment preparation activities with these perspectives is integral in increasing employment rates and decreasing recidivism for this population. This study investigated the psychometric properties of the Juvenile Justice Work Qualifications Scale (JJ-WQS), a measure of the importance of work qualifications for entry level employees previously involved in juvenile services from the
perspective of employers. Analyses explored and confirmed the scale’s factor structure, measured internal consistency, and examined group differences based on geographic location, business structure, and business size. Results indicated evidence of a four-factor structure, strong internal consistency, and mean differences based on company size. Implications for both research and practice are discussed including the need for further replication research on this instrument to confirm these findings and generate additional evidence of its efficacy with entry-level employers to inform supports for justice-involved youth in preparing for employment.
References
Ashford, J., & Gallagher, J. (2019). Preventing juvenile transitions to adult crime: A pilot study of probation interventions for older, high-risk juvenile delinquents. Criminal Justice and Behavior, 46(8), 1148–1164. https://doi.org/10.1177/0093854819835277
Batastini, A., Bolanos, A., Morgan, R., & Mitchell, S. (2017). Bias in hiring applicants with mental illness and criminal justice involvement: A follow-up study with employers. Criminal Justice and Behavior, 44(6), 777–795. https://doi.org/10.1177/0093854817693663
Bengtsson, H. (2020). matrixStats: Functions that apply to rows and columns of matrices (and to vectors). R package version 0.56.0. https://CRAN.R-project.org/package=matrixStats
Bland, J. M., & Altman, D. G. (1997). Statistics notes: Cronbach's alpha. British Medical Journal, 314, 572-572. https://doi.org/10.1136/bmj.314.7080.572
Brame, R., Mulvey, E. P., Schubert, C. A., & Piquoro, A. R. (2018) Recidivism in a sample of serious adolescent offenders. Journal of Quantitative Criminology, 34(1), 167-187. https://doi.org/10.1007/s10940-016-9329-2
Burnham, K. P., & Anderson, D. R. (2004). Multimodel inference: Understanding AIC and BIC in model selection. Sociological Methods & Research, 33(2), 261–304. http://doi.org/1 0.1177/0049124104268644
Carter, A. (2019). The consequences of adolescent delinquent behavior for adult employment outcomes. Journal of Youth and Adolescence, 48(1), 17-29. https://doi.org/10.1007/as10964-018-0934-2
Cavendish, W. (2014). Academic attainment during commitment and postrelease education: Related outcomes of juvenile justice-involved youth with and without disabilities. Journal of Emotional and Behavioral Disorders, 22(1), 41-52. https://doi.org/10.1177/1063426612470516
Cerda, J. A., Stenstrom, D. M., & Curtis, M. (2015). The role of type of offense and work qualifications on perceived employability of former offenders. American Journal of Criminal Justice, 40(2), 317–335. https://doi.org/10.1177/1063426612470516
Cohen, M.A., & Piquero, A.R. (2009). New evidence on the monetary value of saving a high risk youth. Journal of Quantitative Criminology, 25(1), 25-49. https://doi.org/10.1007/s10940-008-9057-3
Collins, M. E., Spindle-Jackson, A., & Yao, M (2021). Workforce development systems efforts for system-involved youth: Opportunities and challenges. Children and Youth Services Review, 128(1), 106-158. http://doi.org/10.1016/j.childyouth.2021.106158
Decker, S. H., Ortiz, N. R., Spohn, C., & Hedberg, E. (2015). Criminal stigma, race, and ethnicity: The consequences of imprisonment for employment. Journal of Criminal Justice, 43(2), 108–121. http://doi.org/10.1016/j.jcrimjus.2015.02.002
Dillman, D. A. (2007). Mail and internet surveys: The tailored design method. Wiley: New York, NY.
Epskamp, S. (2019). semPlot: Path diagrams and visual analysis of various SEM packages' output. R package version 1.1.2. https://CRAN.R-project.org/package=semPlot
Foley, R. M. (2001). Academic characteristics of incarcerated youth and correctional educational programs: A literature review. Journal of Emotional and Behavioral Disorders, 9(4), 248-259. https://doi.org/10.1177/106342660100900405
Griller Clark, H., Mathur, S. R., & Helding, B. (2011). Transition services for juvenile detainees with disabilities: Findings on recidivism. Education and Treatment of Children, 34(4), 511–529. https://doi.org/10.1177/106342660100900405
Griller Clark, H., Mathur, S. R., Ott, M., & McTier, T.S. (2020). Employers’ perceptions of hiring juvenile offenders. Criminal Justice and Behavior, (47)9, 1156–1175. https://doi.org/10.1177/0093854820919914
Harrison, B., & Schehr, R. C. (2004). Offenders and post-release jobs: Variables influencing success and failure. Journal of Offender Rehabilitation, 39(3), 35–68. https://doi.org/10.1300/J076v39n03_03
Haslewood-Pocsik, I., Brown, S., & Spencer, J. (2008). A not so well-lit path: Employers’ perspectives on employing ex-offenders. Howard Journal of Criminal Justice, 47(1), 18–30. https://doi.org/10.1111/j.1468-2311.2008.00501.x
Haynes, S. N., Richard, D. C. S, & Kubany, E. S. (1995). Content validity in psychological assessment: A functional approach to concepts and methods. Psychological Assessment, 7(3), 238-247. https://doi.org/10.1037/1040-3590.7.3.238
Holzer, H. J., Raphael, S. & Stoll, M. A. (2003). Employer demand for ex-offenders: Recent evidence from Los Angeles. Urban Institute Reentry Roundtable.
Holzer, H. J., Raphael, S., & Stoll, M. A. (2004). How willing are employers to hire ex-offenders? Focus, 23(2), 40–43.
Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55. https://doi.org/10.1080/10705519909540118
Irvine A, & Canfield A. (2016). The overrepresentation of lesbian, gay, bisexual, questioning, gender nonconforming and transgender youth within the child welfare to juvenile justice crossover population. Journal of Gender, Social Policy & the Law, 24(2), 243-261. https://digitalcommons.wcl.american.edu/jgspl/vol24/iss2/2/
Jorgensen, T. D., Pornprasertmanit, S., Schoemann, A. M., & Rosseel, Y. (2019). semTools: Useful tools for structural equation modeling. R package version 0.5-2. Retrieved from https://CRAN.R-project.org/package=semTools
Joseph, M. M., Osmanu, K., & Moss, K. (2017). Ethical considerations for working with transition aged youth and students with disabilities given the implications of WIOA. Journal of Applied Rehabilitation Counseling, 48(2), 42–47. https://doi.org/10.1891/0047-2220.48.2.42
Justice Policy Institute. (2020). Sticker shock 2020: The cost of youth incarceration. Retrieved from: https://justicepolicy.org/research/policy-brief-2020-sticker-shock-the-cost-of-youth-incarceration/
Kirk, D. S. & Sampson, R. J. (2013). Juvenile arrest and collateral educational damage in the transition to adulthood. Sociology of Education, 86(1), 36-62. https://doi.org/10.1177/0038040712448862
Kline, R. B. (2016). Principles and practice of structural equation modeling (4th ed.). New York, NY: The Guilford Press.
Latessa, E. (2012). Why work is important, and how to improve the effectiveness of correctional reentry programs that target employment. Criminology & Public Policy, 11(1), 87-91. https://doi.org/10.1111/j.1745-9133.2012.00790.x
Mathur, S. R., & Griller Clark, H. (2014). Community engagement for reentry success of youth from juvenile justice: Challenges and opportunities. Education and Treatment of Children, 37(4), 713–734. https://www.jstor.org/stable/44683944
Mathur, S. R., Griller Clark, H., Grayson, A., & Robertson, K. S. (2023). Preparing justice involved youth for transition: Employer perceptions. Children and Youth Services Review, 155, 1-9. https://doi.org/10.1016/j.childyouth.2023.107270
Messick, S. (1995). Validity of psychological assessment. American Psychologist, 50, 741-749.
Na, C. (2017). The consequences of school dropout among serious adolescent offenders: More offending? More arrest? Both? Journal of Research in Crime and Delinquency, 54(1), 78-110. https://doi.org/10.1177/0022427816664118
O’Connell, D. J., Enev, T. N., Martin, S. S., & Inciardi, J. A. (2007). Working towards recovery: The interplay of past treatment and economic status in long-term outcomes for drug-involved offenders. Substance Use & Misuse, 42(7), 1089–1107. https://doi.org/10.1080/10826080701409453
Peoples, J. M. (1995). Helping pre-trial services clients find jobs. Federal Probation, 59(1), 14–18.
Pham, Y. K., Unruh, D. K., & Waintrup, M. (2015). Employers’ Perceptions on the Disclosure of Juvenile Records. Journal of Juvenile Justice, 4(2), 111-122.
Preacher, K. P., & MacCullum, R. C. (2003). Repairing torn swift's electric factor analysis machine. Understanding Statistics, 2(1), 13-43. http://hdl.handle.net/1808/1492
R Core Team. (2024). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. Retrieved from https://www.R-project.org/
Rahill-Beuler, C.M., & Kretzer, K. (1997). Helping offenders find employment. Federal Probation, 61(1), 35–37.
Revelle, W. (2018). psych: Procedures for personality and psychological research. https://CRAN.R-project.org/package=psych
Rosseel, Y. (2012). lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2), 1-36. https//doi.org/10.18637/jss.v048.i02
Sawyer W. Youth Confinement: The whole pie 2019. Prison Policy Initiative. 2019. https://www.prisonpolicy.org/reports/youth2019.html
Suhr, D. (2006). The basics of structural equation modeling. Presented: Irvine, CA, SAS User Group of the Western Region of the United States (WUSS).
Swanson, S. J., Langfitt-Reese, S., & Bond, G. R. (2012). Employer attitudes about criminal histories. Psychiatric Rehabilitation Journal, 35(5), 385–390. https://doi.org/10.1037/h0094498
Thorndike, R. M., & Thorndike-Christ, T. M. (2013). Measurement and Evaluation in Psychology and Education (8th Ed.). Boston, MA: Pearson.
Travis, J., & Petersilia, J. (2001). Reentry Reconsidered: A new look at an old question. Crime and Delinquency, 47(3), 291–313. https://doi.org/10.1177/0011128701047003001
Ullman, J. B. (2006). Structural equation modeling: Reviewing the basics and moving forward. Journal of Personality Assessment, 87(1), 35–50. https://doi.org/10.1207/s15327752jpa8701_03
Unruh, D. K., Reardon, K., & Strycker, L. (2023). Employer perspectives on hiring youth previously involved with juvenile justice: A national survey. Education and Treatment of Children, 46(4), 337-249. https://doi.org/10.1007/s43494-023-00110-z
Varghese, F. P., Hardin, E. E., & Bauer, R. L. (2009). Factors influencing the employability of Latinos: The roles of ethnicity, criminal history, and qualifications. Race and Social Problems, 1(3), 171-181. https://doi.org/10.1007/s12552-009-9014-2
Varghese, F. P., Hardin, E. E., Bauer, R. L., & Morgan, R. D. (2010). Attitudes toward hiring offenders: The roles of criminal history, job qualifications, and race. International Journal of Offender Therapy and Comparative Criminology, 54(5), 769–782. https://doi.org/10.1177/0306624X09344960
Wickham, H. (2017). Tidyverse: Easily install and load the ’tidyverse’. Retrieved from https://CRAN.R-project.org/package=tidyverse
Wickham, H., Hester, J., & Chang, W. (2019). Devtools: Tools to make developing r packages easier. Retrieved from https://CRAN.R-project.org/package=devtools
Wilson, S. J., Lipsey, M. W., & Soydan, H. (2003). Are mainstream programs for juvenile delinquency less effective with minority youth than majority youth? A meta-analysis of outcomes research. Research on Social Work Practice, 13(1), 3-26. https://doi.org/10.1177/1049731502238754
Yuan, K.-H., Yang-Wallentin, F., & Bentler, P. M. (2012). ML versus MI for missing data with violations of distribution conditions. Sociological Methods & Research, 41(4), 598-629. https://doi.org/10.1177/0049124112460373
Zopluoglu, C. (2018). itemanalysis: Classical test theory item analysis. R package version 1.0. https://CRAN.R-project.org/package=itemanalysis
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