Sage Journals: Discover world-class research

Abstract

This study evaluates the Youth on Track program, launched by the New South Wales Government in 2013 to improve outcomes and reduce recidivism among young people (aged 10–17) who are at risk of offending. Using a quasi-experimental design and Propensity Score Matching, the study compares individuals referred to Youth on Track (Oct 2016–Mar 2020, n = 1,997) with a matched group (n = 3,994) from the Human Services DataSet, a de-identified dataset of over 7 million New South Wales service records. Analysis includes Youth on Track administrative data and survival analysis to assess outcomes. Youth on Track referrals had similar or higher engagement with services and higher probabilities of adverse outcomes such as reoffending, custody placement, risk of significant harm reports, out-of-home care placement, homelessness support, and mental health service use. Although the findings suggest that Youth on Track referrals did not achieve better outcomes compared to the matched control group, they are prone to detection bias due to factors such as increased supervision and unmeasured traits like peer/sibling involvement in crime or motivation to stop offending. Thus, results should not guide decision-making without further research. Despite limitations, the study highlights the value of rigorous quasi-experimental methods and Human Services DataSet in evaluating complex interventions and informing future program assessments.

Keywords

recidivism Youth on Track (YoT) program descriptive statistics Human Service DataSet program evaluation propensity score matching

Get full access to this article

View all access options for this article.

References

Adler

J. R.

Edwards

S. K.

Scally

Gill

Puniskis

M. J.

Gekoski

Horvath

M. A. H.

(2016). What works in managing young people who offend? A summary of the international evidence. Ministry of Justice. (Report). https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachmentdata/file/498493/what-works-in-managing-young-people-who-offend.pdf

Allison

P. D.

(2014). Event history and survival analysis. Sage.

Andrews

D. A.

Bonta

Hoge

R. D.

(1990). Classification for effective rehabilitation: Rediscovering psychology. Criminal Justice and Behaviour, 17(1), 19–52.

Athey

Imbens

G. W.

(2016). Recursive partitioning for heterogeneous causal effects. Proceedings of the National Academy of Sciences, 113(27), 7353–7360. https://doi.org/10.1073/pnas.1510489113

Austin

P. C.

(2011). An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivariate Behavioral Research, 46(3), 399–424. https://doi.org/10.1080/00273171.2011.568786

Austin

P. C.

(2014). The use of propensity score methods with survival or time-to-event outcomes: Reporting measures of effect similar to those used in randomized experiments. Statistics in Medicine, 33(7), 1242–1258. https://doi.org/10.1002/sim.5984

CIRCA . (2017). Youth on track social outcomes evaluation: Final report. NSW Department of Justice. (Report) Accessed: 2025-02-11.https://www.youthontrack.justice.nsw.gov.au/Documents/youth-on-track-social-outcomesevaluation-final-report-19-april-2017.pdf

Cox

D. R.

(1972). Regression models and life-tables. Journal of the Royal Statistical Society: Series B (Methodological), 34(2), 187–202. https://doi.org/10.1111/j.2517-6161.1972.tb00899.x

Davis

(2019). Independent review of aboriginal children in OOHC. Family Is Culture. (Report). https://apo.org.au/sites/default/files/resource-files/2019-10/apo-nid267061.pdf

10.

Dellar

Roberts

Bullen

Downe

Kane

(2022). Validation of the YLS/CMI on an Australian juvenile offending population. International Journal of Offender Therapy and Comparative Criminology, 67(8), 861, 883. https://doi.org/10.1177/0306624X221086556

11.

Department of Communities and Justice . (2023). What do you report and when? [Accessed: 2025-02-11].https://reporter.childstory.nsw.gov.au/s/what-do-you-reportand-when

12.

Diamond

Sekhon

J. S.

(2013). Genetic matching for estimating causal effects: A general multivariate matching method for achieving balance in observational studies. Review of Economics and Statistics, 95(3), 932–945. https://doi.org/10.1162/REST_a_00318

13.

Fazel

Hurton

Burghart

DeLisi

(2024). An updated evidence synthesis on the Risk-Need-Responsivity (RNR) model: Umbrella review and commentary. Journal of Criminal Justice, 92(1), 102197. https://doi.org/10.1016/j.jcrimjus.2024.102197

14.

Hainmueller

(2012). Entropy balancing for causal effects: A multivariate reweighting method to produce balanced samples in observational studies. Political Analysis, 20(1), 25–46. https://doi.org/10.1093/pan/mpr025

15.

Harris

(2007). Risk/needs assessment and response to criminogenic factors with young people. In: Proceedings of the young people, risk and resilience: the challenges of alcohol, drugs and crime conference p. 297. https://www.vscn.org.au/young-people-risk-and-resilience/

16.

Hosmer

D. W.

Lemeshow

(2004) Applied logistic regression (vol. 2). John Wiley.

17.

Ishwaran

Kogalur

U. B.

Blackstone

E. H.

Lauer

M. S.

(2008). Random survival forests. Annals of Applied Statistics, 2(3), 841–860. https://doi.org/10.1214/08-AOAS169

18.

Klauzner

Poynton

Weatherburn

Thorburn

(2022). Evaluating youth on track: A randomised controlled trial of an early intervention program for young people who offend. Bureau of Crime Statistics and Research. (Report no. Crime and Justice bulletin no. 249). https://www.bocsar.nsw.gov.au/Publications/CJB/2022-Report-Youthon-Track-Evaluation-CJB249.pdf

19.

Lipsey

M. W.

(2009). The primary factors that characterize effective interventions with juvenile offenders: A meta-analytic overview. Victims and Offenders, 4(4), 124–147. https://doi.org/10.1080/15564880802612573

20.

Mathews

(2015). Mandatory reporting laws: Their origin, nature, and development over time. In Mathews

Bross

(Eds.), Mandatory reporting laws and the identification of severe child abuse and neglect (vol. 4, pp. 3–25). Springer.

21.

McCarthy

(2021). How universal is the youth crime drop? disentangling recent trends in youth offending through a socio-economic lens. Victims and Offenders, 16(6), 796–818. https://doi.org/10.1080/15564886.2020.1855281

22.

Moffitt

T. E.

(2003). Life-course-persistent and adolescence-limited antisocial behavior: A 10-year research review and a research agenda. In Lahey

B. B.

Moffitt

T. E.

Caspi

(Eds.), Causes of conduct disorder and juvenile delinquency (pp. 49–75). The Guilford Press.

23.

Nastaly

(2019). Program attrition among juvenile justice involved youth and its relationship with reoffending outcomes from the changing habits and reaching targets (chart) program. https://unsworks.unsw.edu.au/entities/publication/425dc333-86ae-418a-ad97-a2c8138326a7

24.

Nelson

(2015). Characteristics of prolific offenders in NSW. NSW bureau of crime statistics and research (BOCSAR). (Bureau brief no. 112). https://www.bocsar.nsw.gov.au/Publications/BB/Report2016-Characteristics-of-prolific-offenders-in-NSWbb112.pdf

25.

Nelson

(2017). Predictive validity of risk/needs assessment for young offenders under community supervision. Bureau of Crime Statistics and Research. (crime and justice bulletin no. 205). https://www.bocsar.nsw.gov.au/Publications/CJB/Report-2017-Predictive-validityof-risk-needs-assessment-for-young-offenders-undercommunity-supervision-CJB205.pdf

26.

NSW Bureau of Crime Statistics and Research (BOCSAR) . (2022a). Re-offending statistics for NSW. https://www.bocsar.nsw.gov.au/Pages/bocsarpages/Re-offending.aspx

27.

NSW Bureau of Crime Statistics and Research (BOCSAR) . (2022b). Youth offending. https://www.bocsar.nsw.gov.au/Pages/bocsarpages/Young-people.aspx

28.

NSW Bureau of Crime Statistics and Research (BOCSAR) . (2025). Custody statistics for young people in NSW. https://www.bocsar.nsw.gov.au/media/2025/mr-custody-jun2025.html

29.

Payne

Brown

Broadhurst

(2018). Where have all the young offenders gone? examining changes in offending between two NSW birth cohorts. https://www.aic.gov.au/sites/default/files/2020-05/ti553091118.pdf

30.

Pooley

(2020). What are the characteristics of effective youth offender programs? Australian Institute of Criminology. (Report no. Trends and issues in crime and criminal justice no. 604). https://www.aic.gov.au/sites/default/files/2020-09/ti604whatarethecharacteristicsofeffectiveyouthoffenderprograms.pdf

31.

Rosenbaum

P. R.

(2002). Observational studies (2nd ed.). Springer.

32.

Rosenbaum

P. R.

Rubin

D. B.

(1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41–55. https://doi.org/10.1093/biomet/70.1.41

33.

Rotter

(2013). Collaborative family work: A practical guide to working with families in the human services (1st). Routledge. https://doi.org/10.4324/9781003115199

34.

Royston

Parmar

M. K. B.

(2013). Restricted mean survival time: An alternative to the hazard ratio for the design and analysis of randomized trials with a time-to-event outcome. BMC Medical Research Methodology, 13(1), 152. https://doi.org/10.1186/1471-2288-13-152

35.

Shadish

W. R.

Cook

T. D.

Campbell

D. T.

(2002). Experimental and quasi-experimental designs for generalized causal inference. Houghton Mifflin.

36.

Shepherd

S. M.

Luebbers

Ogloff

J. R. P.

Fullam

Dolan

(2014). The predictive validity of risk assessment approaches for young Australian offenders. Psychiatry, Psychology and Law, 21(5), 801–817. https://doi.org/10.1080/13218719.2014.904262

37.

Smith

N. E.

Jones

(2008). Monitoring trends in re-offending among adult and juvenile offenders given non-custodial sanctions. https://www.bocsar.nsw.gov.au/Publications/CJB/cjb110.pdf

38.

Spiranovic

Cockburn

Bartels

Julian

(2015). Outcome measures for evaluating the effectiveness of juvenile justice programs. Victoria University Law and Justice Journal, 5(1), 23–34.

39.

Thompson

A. P.

McGrath

(2012). Subgroup differences and implications for contemporary risk-need assessment with juvenile offenders. Law and Human Behavior, 36(4), 345–355. https://doi.org/10.1037/h0093930

40.

Trimboli

(2019a). NSW trends in the age-specific rates of offending, 1995 – 2018. https://www.bocsar.nsw.gov.au/Publications/BB/2019-Report-NSW-trends-intheage-specific-rates-of-offending-BB143

41.

Trimboli

(2019b). Youth on track randomised controlled trial: Process evaluation. Bureau of Crime Statistics and Research. (Report no. Bureau brief no. 141) (Accessed: 2025-02-11).https://www.bocsar.nsw.gov.au/Publications/BB/2019-Report-Youth-on-track-randomised-controlled-trial-BB141.pdf

42.

VanderWeele

T. J.

Ding

(2017). Sensitivity analysis in observational research: Introducing the E-value. Annals of Internal Medicine, 167(4), 268–274. https://doi.org/10.7326/M16-2607

43.

Wilson

H. A.

Hoge

R. D.

(2013). The effect of youth diversion programs on recidivism. Criminal Justice and Behavior, 40(5), 497–518. https://doi.org/10.1177/0093854812451089

44.

Woldgabreal

Day

Daffern

Lloyd

Graffam

(2022). An empirical test of the factor structure of the violence risk scale and its measurement invariance across time and cultural groups. Criminal Justice and Behavior, 49(9), 1255–1275. https://doi.org/10.1177/00938548221084984

45.

Woldgabreal

Day

Tamatea

(2020). Do risk assessments play a role in the enduring ‘colour line? Advancing Corrections Journal, 10, 18–28. https://doi.org/10.65264/cauu1184

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.02 MB