adolescent offenders

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Assessing juvenile offenders: Preliminary data for the Australian

Adaptation of the Youth Level of Service/Case Management Inventory

(Hoge & Andrews, 1995)*

ANTHONY P. THOMPSON & ZOE POPE

Charles Sturt University, Wagga Wagga, New South Wales, Australia

AbstractThe developmental phase and preliminary psychometric data are reported for an Australian adaptation of an assessmentinventory for juvenile offenders. Specifically, the Australian Adaptation of the Youth Level of Service/Case ManagementInventory (YLS/CMI-AA, Hoge, & Andrews, 1995) is used to assess risks, needs and strengths to inform decision makingwith juvenile offenders. Data from a sample of 290 juvenile offenders were used to analyse item and score characteristicswhich, with few exceptions, performed in keeping with traditional psychometric standards. Predictive validity in a subsampleof 174 males followed for recidivism between 6 and 32 months resulted in a correlation of 0.28 and area under the receiveroperating characteristic (ROC) curve of 0.67 for the total score on the inventory. The results and use of the inventory areplaced in the context of related developments in other jurisdictions.

Systematic assessment of the risks and needs of

juvenile offenders is widely accepted as a key

component of informed responses to juvenile crime

(Day, Howells, & Rickwood, 2003, 2004; Howell,

1995). This trend is consistent with a growingprofessional psychology emphasis on using forensi-

cally relevant tests to address criminal justice and

psycho-legal issues (Borum, 1996; Lally, 2003,

Martin, Allan, & Allan, 2001; Tolman & Mullendore,

2003). In recent years, the Department of Juvenile

Justice (New South Wales) has adopted such an

approach in a fashion that has progressively linked

research and practice. Central to this process has been

an inventory for assessing risk factors, psychosocial

needs and major strengths. The inventory is referred

to as the Australian Adaptation of the Youth Level of

Service/Case Management Inventory (YLS/CMI-

AA, Hoge, & Andrews, 1995). This report providespsychometric results from data collected during the

adaptation phase and draws links to related develop-

ments in other jurisdictions.

The philosophical, theoretical, empirical and prac-

tical underpinnings of risk assessment in juvenile

justice have been elaborated by various authors

(e.g. Bonta, 2002; Hoge, 2002; Thompson, 2001;

Thompson & Putnins, 2003). Essentially, the approach

views adverse developmental outcomes as arising from

the effect over time of antecedent risk factors. Juvenile

delinquency is one type of adverse outcome that isbeneficially conceptualised within the risk framework,

but the perspective can be applied to a wide range of

other health and social problems (Goldenring & Rosen,

2004). These propositions are supported by an

extensive empirical and theoretical literature (Cicchetti

& Rogosch, 2002; Durlak, 1998; Farmer & Farmer,

2001; Farrington, 2002; Loeber & Stouthamer-Loe-

ber, 1998; Maluccio, 2002; McLaren, 2000). Such

factors are also prominent in theories of juvenile

delinquency (Agnew, 2001; Andrews & Bonta, 1994;

Henggeler et al., 1998).

A structured approach to assessing such risk factors

is valuable because of its systematic and empiricalfeatures (Bonta, 2002; Hoge, 2002; Quinsey et al.,

1998). It is important to be aware that risk assessment

serves case management and intervention (Andrews,

1991). Assessments can be linked to future likelihood

of offending and high-risk cases should be managed

prudently. However, assessments are also designed to

Correspondence: Dr Anthony P. Thompson, Humanities and Social Sciences, Charles Sturt University, Locked Bag 678, Wagga Wagga, NSW 2678, Australia.

E-mail: [email protected]

*Some of the psychometric results were presented by Thompson, A. P., & Pope, Z. (2003). The conceptual and psychometric basis for risk need assessment in

juvenile justice. In M. Katsikitis (Ed.), Proceedings of the 38th APS Annual Conference (pp. 224 228). Melbourne: The Australian Psychological Society.

Australian Psychologist, November 2005; 40(3): 207 214

ISSN 0005-0067 print/ISSN 1742-9544 online 2005 Australian Psychological Society Ltd

Published by Taylor & Francis

DOI: 10.1080/00050060500243491


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identify modifiable difficulties that become targets for

change, particularly among higher risk offenders.

These ingredients are appealing because they are in

concert with some of the central principles underlying

contemporary models of criminal justice.

In the juvenile justice sector, there has been a

proliferation of risk need assessment inventories.

Various jurisdictions in the United States havedeveloped instruments (see for example Ashford &

LeCroy, 1990; Gavazzi et al., 2003a; Howell, 1995;

LeCroy, Krysic, & Palumbo, 1998; National Council

on Crime and Delinquency, 2000; Schwalbe et al.,

2004). A risk need assessment tool has also been

recently developed and adopted by the youth justice

system in England and Wales (Baker et al., 2003). In

Australia, the Secure Care Psychosocial Screening

assessment (Putnins, 1999) has been used for youth in

detention since the beginning of 1994. The Depart-

ment of Human Services, Victoria also developed a

risk need inventory (Day, Howells, & Rickwood,

2003; Greville, 2002). In juvenile justice in NSW, the

inventory that has been used is a version of the Youth

Level of Service/Case Management Inventory (YLS/

CMI, Hoge, & Andrews, 2002) and preliminary data

from the NSW trial adaptation are presented here. The

parent inventory (YLS/CMI) was developed over a

number of years in Ontario, Canada (Hoge, 2002;

Hoge & Andrews, 1996; Jung & Rawana, 1999) and is

itself an adaptation of a prominent inventory used in

adult corrections for over 20 years (The Level of

Service Inventory Revised; Andrews, & Bonta, 2000).

The multiplicity of risk need inventories for use

with juvenile offenders is a situation with bothbenefits and disadvantages. Widespread efforts at

bringing structure to the assessment process in a way

that distills much of what is known about juvenile

offending is a decided advantage. So, too, is the

development of inventories that cater to the jurisdic-

tional context of offenders and juvenile justice

systems. A drawback, however, is that effort is

distributed and the research needed to support a

given inventory is slow to accumulate. It will also be

a challenge to draw together and integrate findings

from such a diversity of activity a considerable

proportion of which is yet to appear in peer-reviewed

journals. However, increasingly more research isappearing, particularly in relation to the psycho-

metric features of such inventories and the current

report is in keeping with that objective.

Method

Australian Adaptation of the Youth Level of Service/

Case Management Inventory (YLS/CMI-AA)

An Australian adaptation of the inventory began

prior to the commercial availability of the parent

inventory. Permission was obtained in 1999 from

Robert D. Hoge, Carleton University to make

changes to the unpublished inventory to suit its

anticipated use in the NSW Department of Juvenile

Justice1. In particular, an Australian trial version of

Part I (Assessment of Risks and Needs) and Part II

(Summary of Risk and Needs) was adapted. The

50-item (Part I) trial version corresponded closelywith the unpublished 42-item parent version.

Changes involved: (1) revisions in language to reflect

the New South Wales context (e.g. custodial order

replaced detention, supervised order replaced

probation, wags and misses classes replaced

missing school days or skipping classes, (2)

inclusion of several new items that were empirically

or conceptually related to relevant risk domains (e.g.

age at first court order because of the link between

early onset of offending and recidivism, home-

lessness because of its relevance to family

circumstances and risk/need considerations, occa-

sional alcohol use so that degree of use could be

evaluated consistent with the existing drug use items),

(3) revising the item related to prior probation with an

item concerning the outcome and nature of the first

court order, (4) tightening the operational definition

of selected items (the meaning and parameters of

various items were specified further and a number of

these clarifications have been included in the com-

mercialised parent version), (5) minor reorganisation

of items in some domains to improve the logical flow

(e.g. personality items followed by behaviour items

rather than mixed together), (6) the addition of three

items to identify major strengths that may operateas protective factors, and (7) printing operational

definitions of all items on the inventory rather than in

a separate manual.

As with the parent version, items in the Australian

trial version were organised into the following

domains: (1) Prior and current offences (eight

items), (2) Family and living circumstances (seven

items), (3) Education/employment (seven items),

(4) Peer relations (four items), (5) Substance abuse

(six items), (6) Leisure/recreation (three items),

(7) Personality/behaviour (seven items), and (8)

Attitudes/orientation (five items). A new domain,

Assessment of major strengths, was included forthe three items related to protective factors. Items are

scored in a binary fashion to indicate whether the

operationally defined item describes the young

person. One item related to the outcome of the first

conviction had two parts, both scored in the binary

fashion. One item related to age at first court order

was scored 0, 1, and 2 with more weight given to

younger offenders. Major strengths are indicated as

present or not at the individual level (social and

personal skills), family level (strong, positive parent-

child relationship) and community level (support

208 A. P. Thompson & Z. Pope


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YLS/CMI-AA items resembled the risk domains.

Two items with poor item-total correlation (noted

above) were excluded, as were the three items

dealing with major strengths. This left 45 items for

analysis. All principal components with an eigenva-

lue greater than 1 were extracted and oblique

rotation (direct oblimin) was applied. Oblique

rotation allows extracted factors to be correlated

(Reise, Waller, & Comrey, 2000), which concep-

tually would be expected for risk domains related to

juvenile offending. The analysis yielded 12 compo-

nents that accounted collectively for 61.72% of the

variance. Approximately 60% of the items hadcomponent loadings (0.30 and above) on more than

one component. Interpretation of the structure was

based largely on examining items with the highest

loadings on each component and the results pro-

vided support for some of the YLS/CMI-AA

domains. For example, the first component ac-

counted for 23.19% of the variance and was

characterised by prominent loadings (0.56 0.79)

on five items in the Family and living circum-

stances domain, with nine items from several other

domains loading in the 0.30 0.43 range. The

second component accounted for 5.31% of the

variance, with prominent loadings (0.70 0.85) onfour of the Substance abuse items and only four

items from other domains loading in the 0.30 0.45

range. The third component (5.17% of variance)

seemed to represent aggressiveness with three items

(tantrums, verbally aggressive, physically aggressive)

from the Personality/behaviour domain and the

item concerning violent school behaviour loading

between 0.52 and 0.72. The fourth component

(4.72% variance) represented the background

(static) risk dimension with prominent loadings

(0.65 0.76) on four items from the Prior and

current offences domain. The fifth component

(3.62% variance) incorporated all items from the

Personality/behaviour and Attitudes/orientation

domains (loadings 0.39 0.77) except one item,

related to physical aggression. The sixth component

(3.58% of variance) supported the Peer relations

domain. The two items related to the absence of

positive friends and acquaintances both loaded highly

(0.86), with many items from other domains loading

in the 0.3 0.4 range. Among the remaining six

components there was some support for the Educa-

tion/employment and Leisure/recreation domains.

Predictive validity

The relationship between YLS/CMI-AA scores and

future offending was investigated for a subsample of

males. Official recidivism was determined by reading

the offence record of each case on the Client

Information Data System of the NSW Department

of Juvenile Justice. The length of the follow-up was

based on the time (rounded to the nearest month)

from risk need assessment until follow-up data

system access or the young persons 18th birthday,

whichever came first. Only those young peoples with

at least a 6-month follow-up period were considered.Thus, the follow-up sample consisted of 174 males

who were followed-up between 6 and 32 months with

a median follow-up period of 17 months. In this

group, 70 males, or 40% of the sample, had convic-

tions after the time they were assessed with the risk

need inventory. The median time to conviction for

reoffence was 7.5 months and 79% of recidivists had

registered a new conviction within a year2.

Predictive validity for recidivism produced a point

biserial correlation with the YLS/CMI-AA total

score of 0.28 (p


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correlation with recidivism was 0.32 (P


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The three items concern protective factors from

different sources (individual, family, community)

that conceptually and empirically might not be highly

inter-related. Nevertheless, it is important to con-

sider potential protective factors (Howell, 1995).

The principle component analysis provided some

empirical support for the domains that are used

to organise risk need items. However, only onecomponent related to family functioning accounted

for a sizeable proportion of variance. The manual for

the YLS/CMI (Hoge & Andrews, 2002) provides no

data on the factor structure of the parent version and

the factor structure of the adult version has been

described as inconsistent (Andrews & Bonta, 2000).

Using confirmatory factor analysis with the global

risk indicator measure, Gavazzi et al. (2003) found

support for risk domains identical to those on the

YLS/CMI, but the structure was better for the longer

as opposed to the shorter instrument. Clearly, this is

an area for ongoing investigation with the YLS/CMI

and its Australian adaptation. The organisation of

items into risk domains as used on the YLS/CMI

makes sense conceptually and in terms of risk factors

that have been associated with juvenile recidivism

(Cottle, Lee, & Heilbrun, 2001). However, those

factors need to be translated into assessment items

that are empirically homogeneous. Also, domains are

implicitly weighted in the total risk need score by

virtue of their constituent items (3 8) and this also

needs empirical justification.

Predictive validity studies for risk need assess-

ment inventories are beginning to accumulate.

However, results are being reported over varyingtime-periods, with various criteria (e.g. arrest,

reconviction, frequency or seriousness of offence on

reconviction, intensity of diversion services), and in

varying ways such as percentage correctly predicted,

accuracy across score bands, correlation, ROC

analysis, survival analysis and mean group differ-

ences (e.g. Baker et al., 2003; Gavazzi et al., 2003b;

Jung & Rawana, 1999; National Council on Crime

and Delinquency, 2000; Schwalbe et al., 2004,

Putnins, in press). The predictive validity coefficients

from the trial phase of the YLS/CMI-AA (r= 0.28

and area under the ROC curve = 0.67 for total score

and recidivism, are in keeping with similar indicesreported elsewhere. Flores et al. (2003) found YLS/

CMI total score correlated 0.31 with re-arrest for

males. The risk index score used by Putnins (in

press) for male youth in secure care correlated 0.32

with recidivism 6 months after release. Validity

correlation coefficients around 0.3 are considered

to be a more than respectable result (Meyer et al.,

2001). Catchpole & Gretton (2003) found area

under the ROC curve of 0.74 for the YLS/CMI total

score and general recidivism in a sample of 74 violent

offenders in British Columbia, Canada. Total score

on the structured assessment used in the United

Kingdom produced an area under the ROC curve

value of 0.72 in a 1-year follow-up of reconviction in

over 1000 cases (Baker et al., 2003).

Predictive validity results for domain scores in the

current study (in particular, r= 0.32 between Prior

and current offences and recidivism) are also

consistent with research that shows static riskfactors are especially useful in predicting recidivism.

Flores, Travis, & Latessa (2003) found the Prior

and current offences domain score correlated 0.37

with re-arrest in their large sample. A meta-analysis

of risk factors and recidivism showed certain

offence history variables to be the best (Cottle

et al., 2001). Empirically, there may be grounds

for separating risk assessment, which could be

undertaken with a relatively small set of static

variables, from a more comprehensive consideration

of dynamic needs. This is in keeping with the

assessment framework recommended by the

US Office of Juvenile Justice and Delinquency

Prevention (Howell, 1995).

Overall, the retest results in the current data set

were lower at the second assessment than at the first.

This is encouraging at the system level. Given that

offender needs are not static states, high degrees of

test retest stability are not likely nor, for high-risk

offenders, are they desirable. Interventions should

maintain low-risk offenders at that level but

reduce the risk associated with medium- to high-risk

offenders. Retest scores also provided some support

for discriminating between recidivists and non-

recidivists. It has to be acknowledged, however, thatthe retest methodology in this study incorporated

many unknown sources of variation, including

idiosyncratic selection of cases for revaluation,

potential access to scores from the first assessment

and possible knowledge of reconviction. Rigorous

research on score changes is essential and future

efforts should attempt to differentiate cohorts (e.g.

those with score increases versus score decreases) as

well as explore the expectations and practices of

juvenile justice personnel responsible for assess-

ments. One overseas study in adult corrections

found some manipulation of risk assessment inven-

tory results in response to work demands and lack ofconfidence in the inventory (Schneider, Ervin, &

Snyder-Joy, 1996).

The experience and data from the trial phase with

this inventory led the NSW Department of Juvenile

Justice to include it in standard assessment proce-

dures for all juvenile offenders. Prior to finalising the

inventory for department wide use, there was further

fine-tuning of operational definitions and layout.

Two items were also changed substantively for

conceptual rather than psychometric reasons. The

item about inconsistent parenting was replaced with



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an item related to antisocial/criminal family values.

The reason was that parenting practices seemed well

covered by three other Family and living circum-

stances items and the new item extended the

content domain. A similar rationale applied to the

other change. The item relating to short attention

was expanded to define the broader concept of

impulsivity. A number of departmental procedureswere adopted to support implementation and quality

control including organisational support, operational

guidelines, a training programme and ongoing

monitoring. The inventory has been used in compu-

terised format since October 2002 under a licensing

agreement with the test publisher, Multi-Health

Systems Incorporated. With the inventory in regular

use, we are able to accumulate a sizeable YLS/

CMI-AA database and to undertake ongoing re-

search. For example, we are investigating the ways

in which Juvenile Justice Officers undertake and

understand risk assessment in their work with young

offenders, either with or without the benefits of

structured risk assessment. It is important to remem-

ber that the inventory is not only about risk. Its

domains provide a basis for case planning and

intervention. It serves as a basis for helping young

people to lead better lives. Ward (2002) has argued

that we can lose sight of this objective when needs are

viewed only as liabilities to be overcome to prevent

offending. It is important that inventories such as the

YLS/CMI-AA are not simply imported into practice

without a commitment to ongoing evaluation, re-

search and reflexivity. Our understanding of juvenile

offending and of best practice in the field is evolving,and we should embrace this reciprocal process.

Acknowledgements

The authors would like to thank the Collaborative

Research Unit of the NSW Department of Juvenile

Justice for their assistance in undertaking this

research. The opinions here do not necessarily reflect

the views of the NSW Department of Juvenile

Justice, or any of its officers. Zoe Pope is now at

Forensic Services, Mental Health ACT, Australia.

Notes

1 Apart from suiting the Australian context, the adaptation was

needed to accommodate, in particular, an older age-range. The

Canadian inventory was developed for use with 12 16-year-old

offenders and norms are for 12 17 years. In NSW, a single

government department deals with 10 18-year-old offenders.

2 There were seven instances in which the time to reconviction

was less than 2.5 months. It is possible that these were

outstanding rather than new charges. Reported predictive

validity analysis included these cases, as the results were

virtually identical to when they were excluded.

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