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An Australian risk-need inventory and what we have learnt about its accuracy Andrew McGrath & Tony Thompson.

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Presentation on theme: "An Australian risk-need inventory and what we have learnt about its accuracy Andrew McGrath & Tony Thompson."— Presentation transcript:

1 An Australian risk-need inventory and what we have learnt about its accuracy Andrew McGrath & Tony Thompson

2 Risk/Need Assessment The risk/need/responsivity (RNR) correctional agenda The Youth Level of Service/Case Management Inventory-Australian Adaptation (YLS/CMI-AA)

3 The YLS/CMI-AA 47 yes/no items across 8 domains: Prior and current offences (8 items) Family and living circumstance (7 items) Education/employment (7 items) Peer relations (4 items) Substance abuse (6 items) Leisure/recreation (3 items) Personality/behaviour (7 items) Attitudes/beliefs (5 items)

4 Research agenda 2000/2001, Initial norming study, N = 305 2003 – 2005, Re-norming study, N = 3568 2008 – 2010, N = 4401 first and previous YLS (2895 first assessment) 2012, N = 50, case reviews (with Jane Goodman-Delahunty)

5 Basic descriptive data and predictive validity SampleMean (SD)rAUC 2000/118.06 (9.66)0.280.67 2003/517.75 (9.65)0.260.65 2008/1015.11 (8.30)0.310.69

6 2008/2010 data: Further breakdown SampleMean (SD)rAUC First YLS14.69 (7.71)0.280.67 Previous YLS15.92 (9.28)0.350.71 YLS in custody23.59 (9.35)0.290.65

7 YLS: Use of cut-scores Risk category 2000-12003-52008-10 Low (0–12)100 (32.9%)1236 (34.6%)1892 (43%) Medium (13–23)106 (34.9%)1345 (37.7%)1758 (39.9%) High (24–48)98 (32.2%)987 (27.7%)751 (17.1%)

8 Hit/miss rates within DJJ risk categories Risk category 2003/5 Reoffence (12 months) 2008/10 Reoffence (12 months) Low (0-12)444 (35.9%)429 (22.7%) Medium (13-23)739 (54.9%)772 (43.9%) High (24-48)668 (67.7%)446 (59.4%) Total1851 (51.9%)1647 (37.4%)

9 Gender differences (2008/10) NrAUC Female7200.30.690 Male36810.32.694

10 Gender differences (2008/10) NrAUC Female7200.30.690 Male36810.32.694 One year reoffending N (%) by risk category LowMediumHigh Female32 (12%)87 (29.2%)75 (48.1%) Male397 (24.4%)685 (46.9%)371 (62.4%)

11 Ethnic differences (2008/10) NrAUC Indigenous14320.24.648 Non Indigenous19160.30.684 Other ethnic8210.35.716

12 Ethnic differences (2008/10) NrAUC Indigenous14320.24.648 Non Indigenous19160.30.684 Other ethnic8210.35.716 One year reoffending N (%) by risk category LowMediumHigh Indigenous179 (37.4)367 (55.8)199 (67.5) Non Indigenous161 (19.0)283 (37.8)169 (52.6) Other ethnic79 (18.9)115 (41.2)76 (60.8)

13 Case studies: some brief concluding remarks 10 year research agenda Predictive validity vs accuracy Case studies: help to increase validity Tension between assessment and intervention Role of contextual factors Follow-up data

14 References McGrath, A., & Thompson, A. P. (2012). The relative predictive validity of the static and dynamic domain scores in risk-need assessment of juvenile offenders. Criminal Justice and Behavior, 39, 250-263. doi: 10.1177/0093854811431917 Thompson, A. P., & McGrath, A. (2012). Subgroup differences and implications for contemporary risk-need assessment with juvenile offenders. Law and Human Behavior, 36, 345-355. doi: 10.1037/h0093930

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