Corrective Services NSW

Corporate Research, Evaluation and Statistics

The Utility of Level of Service Inventory –Revised (LSI-R) Assessments within NSW Correctional Environments
Ian Watkins
The Level of Service Inventory – Revised (LSI-R) is an actuarial assessment tool designed to identify theoffenders’ risks and needs with regard to recidivism. That is, the LSI-R seeks to classify an offender’s risk of
re-offending as well as to identify their particular criminogenic needs. While the LSI-R itself has been
extensively validated internationally its use within the NSW correctional environment remains relatively
unsubstantiated due to methodological limitations of previous research. The current study sought to rectify
limitations of previous studies and to provide a sound statistical evaluation of the instrument’s psychometricproperties with a sample of NSW custody-based offenders whose sentences were equal to or shorter than
two years. In addition to evaluating the instrument’s psychometric properties differences due to gender andAboriginal/Torres Strait Islander (ATSI) status were also examined. The results revealed an encouraging
pattern of discrimination with proportionally more recidivists in the high risk categories and proportionallymore non-recidivists in the lower risk categories. An examination of offenders’ criminogenic needs profiles
revealed that the LSI-R did not meaningfully discriminate between males and females or between non-ATSIand ATSI offenders. While the instrument’s predictive utility was acceptable with the majority of offenders,point estimates were notably lower with ATSI females. These findings are consistent with international
research and provide empirical justification for the application of the LSI-R to specific populations.

KEY FINDINGS•Of the 11,051 offenders assessed whose custodial sentences were equal to or shorter than two years,
3,694 (33%) were re-incarcerated within two years following release.

•

Of the 3,374 recidivist male offenders, 341 (10%) were classified as low or low/medium-risk, 1,330(39%) were classified as medium risk, and 1,703 (51%) were classified as medium/high or high risk.

•

Of the 6,646 male offenders who did not re-offend, 2,329 (35%) were classified as low or low/mediumrisk, 2,611 (39%) were classified as medium risk, and 1,706 (26%) were classified as medium/high or
high risk.

•

While differences on the LSI-R due to sex and ATSI status were observed, they were considered
inconsequential due to their very low explanatory power (less than 7%) with regards to the observed
variance in total LSI-R scores. These outcomes suggest that the groups scored similarly on the LSI-R.

•

Measures of discriminative ability suggest that the LSI-R is performing similarly to its use internationally,
with the highest point estimates observed with non-ATSI males and the lowest occurring with ATSI
females. This means that the LSI-R is performing appropriately with non-ATSI males and females and
ATSI males yet may not accurately predict ATSI female recidivism.

•

Analysis of survival time by risk classifications revealed that as risk classifications progressively
increase from low to high, the survival time in the community decreases. That is, high risk offenders reoffend at higher rates and do so faster than lower risk offenders.

•

Estimates of the LSI-R’s reliability (internal consistency) are satisfactory. This means that eachindividual item purported to measure the same underlying construct produced similar scores.

INTRODUCTION

R within Australia. A search of the extant literature
revealed only three studies relevant to LSI-R
predictions of general recidivism within Australia.
Eyland, et al. (2009) examined the power of LSI-R
assessments to predict recidivism within a large
sample of NSW offenders. While their results did
indicate some degree of predicative accuracy, thestudy had some methodological limitations; namely:

The Level of Service Inventory – Revised is an actuarialassessment tool designed to identify the offenders’risks and needs with regard to recidivism. In otherwords, the LSI-R seeks to classify an offender’s risk of
re-offending as well as to identify their particularcriminogenic needs. Within Australia, the application of
the LSI-R adheres to the principles of risk, needs andresponsivity that underlie offender assessment andrehabilitation (see Andrews and Bonta, 1994). These
principles, posit that offenders posing a high risk of reoffending should receive higher intensity interventions
including increased supervision and monitoring. These
interventions should also be tailored to the offender’sindividual criminogenic needs with the aim ofminimising overall recidivism and enhancing
community security.

•••

Based on a social learning model of crime, the LSI-R
has 54 items, which are grouped into 10 subscales:
Criminal History, Education/Employment, Finances,family/Marital, Accommodations, Leisure/Recreation,
Companions, Alcohol/Drug, Emotional/Personal, andAttitude/Orientation. LSI-R total scores are generally
used to predict recidivism (risk) whereas subscalescores are used to identify criminogenic needs.

•

The use of the LSI-R in NSW

Failure to control for an individual’s eligibility to
re-offend. That is, the follow-up period for each
offender was not standardised
Utilisation of a more liberal definition ofrecidivism than Andrews and Bonta’s (1995)
original LSI-R validation assessment, making
comparisons to the original validation sample
more problematic
Boundary limits were not constructed around thelength of sentence. CSNSW has administrative
guidelines regarding custodial offenders
incarcerated for less than 2 years. Assessments
are based on their past 12 months in thecommunity and not their current circumstances incustody. These guidelines were introduced in2007 and span previous data captures,
Statistical analyses did not differentiate between
community and custody-based offenders.

In two similarly designed studies utilising NSW offender
samples, Hsu, Caputi, and Byrne (2009) and Hsu,
Caputi, and Byrne (2010) both failed to control for
offenders eligibility to re-offend. They state that “dataon re-offending were retrieved from OIMS andgathered for the entire sample at the same date”. This
limitation (not allowing all the sample as standardised’time to fail’) would necessarily distort classification
accuracy. The utility of LSI-R assessments remains tobe rigorously evaluated as appropriate data analyses
must take all these factors into account.

In 2002 Corrective Services NSW (CSNSW) introduced
the LSI-R as a means to assess the risk and needs ofoffenders. Arguments for the instruments widespread
use asserted that, compared to unstructured
professional judgments, LSI-R assessments afforded
greater consistency and credibility regarding decisions
made about offenders risk of re-offending. The
measure now forms the basis for all assessments andcase planning within CSNSW. In 2008/09, 37,221 LSIR assessments were completed for a variety of
purposes including pre-sentence and pre-release court
advice reports. An LSI-R was completed on 85.4
percent of offenders with a new supervision orderduring the same financial year (CSNSW annual report,
2008/09). However, despite its widespread use, there
is a scarcity of research validating the instrument
within NSW correctional environments. This can
primarily be traced to the longitudinal nature ofvalidation assessments. That is, the instrument must
be used with the population of interest before it can bevalidated against a sufficiently large scale sample.

Research Rationale
The three previous studies of NSW data have limited
interpretations of NSW data results, therefore, CSNSW
commissioned a further investigation into the LSI-R’s
utility within NSW.

Research Aims
The intention of the current project was to build on theprevious studies conducted in NSW on LSI-R validity
and reliability and further investigate the utility of the
LSI-R within the NSW jurisdiction. Specifically, thecurrent project aimed to:

Research examining the LSI-R within NSW
Numerous studies utilising international samples haveinvestigated the psychometric properties of the LSI-R.
Researchers have asked the question: Are LSI-R scores
reliable and are they valid?

•••Whilst the majority of psychometric evaluations
suggest that the LSI-R is a useful instrument withregards to measuring offenders’ risks and needs, there
is a paucity of rigorous evaluations establishing the LSI-•

2

Establish CSNSW normative statistics
Establish CSNSW criminogenic needs profiles
Investigate differences in LSI-R scores due to sex
and Aboriginal/Torres Strait Islander (ATSI) status,
andInvestigate the LSI-R’s psychometric properties
within CSNSW.

METHODOLOGY

Table 1: Distribution of LSI-R classification categories byrecidivism status of male offenders

The following methodology was designed to fulfil theaims and objectives of the research brief:

2005/2008 LSI-R Male offenders who
risk category
re-offended(N = 10020)
within 2 years

Data Source
The current research project used data retrieved fromthe CSNSW Offender Information Management System(OIMS). The sample consisted of the 11,051 offenders
released from incarceration between January 2005
and January 2008, who had been incarcerated for lessthan 2 years and who had been assessed with the LSIR instrument. Where offenders had multiple LSI-R
assessments the latest was taken and used for the
analysis.

The current study uses Andrews and Bontas (1995)
original definition of recidivism; re-incarceration
following release. In addition the offender’s eligibility to
re-offend was controlled. That is, upon release
offenders were followed for a standardised period of 2
years. This means that all offenders had equal time tore-offend.

■
■

■

(39)

9.6%

(636)

Low/Medium

9.0%

(302)

25.5%

(1,693)Medium39.4%(1,330)39.3%(2,611)

Medium/High

35.8%(1,207)20.3%(1,348)

High

14.7%

(496)

5.4%

(358)

Total

100.0%(3,374)100.0%(6,646)

and

their

In order to investigate LSI-R differences due to sex and
ATSI status and the relationship between LSI-R
components and recidivism, a multivariate analysis ofvariance (MANOVA) was conducted and point bi-serial
correlations were computed. The MANOVA analysis
revealed statistically significant main effects of sex and
ATSI status, as well as a significant two-way interaction
effect. However, the omnibus model accounted for only
6.7% of the variance in total LSI-R scores. Differences
due to sex and ATSI status were deemedinconsequential due to their very low explanatory
power. It should be noted, however, that ATSI offendersscored higher on every subscale except the emotional/
personal subscale. Table 3 displays the means andCharacteristics of the sample

■

1.2%

Criminogenic needs profiles
relationship with recidivism

RESULTS

The mean age of the sample group was 33
years.
10,020 (91%) were male whilst 1,031 (9%) werefemale.
8,169 (74%) identified themselves as nonIndigenous while 2,882 (26%) identified
themselves as Indigenous.
The most common current offence was ‘acts
intended to cause injury’ (26%), followed by‘offencesagainstjusticeprocedures,
government
security,
andgovernment
operations’ (19%), then ‘theft and related
offences’ (10%).
Of the 11,051 offenders assessed, 3,695 (33%)
were re-incarcerated during the follow-up periodof 2 years.

Low

offenders who did not re-offend, 2,329 (35.4%) wereclassified as low or low/medium-risk, 2,611 (39.3%)
were classified as medium risk, and 1,706 (25.7%)
were classified as medium/high or high risk. Table 1
presents the distribution of LSI-R classification
categories by recidivism status. Alternatively Figure 1
presents the percentage of male offenders withcomputed risk categories and re-offending outcome.

Defining Recidivism■

Male offenders who
did not re-offend
within 2 years

Figure 1: Percentage of male offenders with calculated LSI-R risk
categories and re-offending outcomes

45
40
35
30
25
20
15
10
5
0

Normative statistics
The current study investigated NSW normative
statistics through an examination of the distributional
proportions exhibited by male offenders with regard torisk classifications. This examination was notconducted with female offenders as the LSI-R’s users
manual does not specify risk category cut-off scores forfemale offenders. Of the 3,374 recidivist maleoffenders, 341 (10.2%) were classified as low or low/
medium-risk, 1,330 (39.4%) were classified as medium
risk, and 1,703 (50.5%) were classified as medium/high or high risk. Conversely, of the 6,646 male

Returned to custody w ithin 2
years

Low

3

Low/Medium

Did not return to custody
w ithin 2 years

MediumMedium/HighHigh

standard deviations of the LSI-R total and subscales
scores by sex and ATSI status. While MANOVA analysis
revealed no meaningful differences in LSI-R scores due
to sex and ATSI status, point bi-serial correlations
revealed typically smaller associations for females.
Point bi-serial correlations provide a measure of covariance between recidivism and each subscale withgreater values indicating greater co-variance. That is, apositive correlation for criminal history indicates that as
criminal history increases so do rates of recidivism.
Table 4 displays the calculated point bi-serial
correlations as well as their 95% confidence intervals.
The table shows that the observed correlations
decrease in magnitude and significance when applied
to female offenders. This means that the subscales of
the LSI-R may not be appropriate for measuring thecriminogenic needs of NSW females offenders. This isa significant finding and requires further research.

Figure 2: Survival rates as a function of time.

Low
Med/
low

Med

Med/
high
High

Psychometric evaluation
Psychometric evaluations typically primarily focus upon
two concepts when investigating test properties;
reliability and validity. These concepts reflect how well
the LSI-R discriminates between re-offenders and non
re-offenders (validity), as well as how well each test
item measures the underlying construct (reliability/internal consistency).

observed AUC values split by sex and ATSI status aswell as their 95% confidence intervals. AUC statistics
for calculated risk classifications could not becomputed for female offenders as the cut-off points are
not specified in the LSI-R users manual.
In order to compare the AUC values, 95% confidence
intervals were computed and visually contrasted. The
results suggest that the only differences indiscriminative ability were between the non-ATSI males
and the ATSI females, with lower AUC values observedfor ATSI females. These comparisons, however, mustremain tentative as comparing the overlap of 95%
confidence intervals is not a direct test of departure.

Validity
While the previous Australian research pertaining to
the utility of LSI-R assessments computes measures ofvalidity based upon binary logistic regression modelling
procedures, the current study investigates validity via
receiver operator characteristic (ROC) analysis. Suchprocedure produces what is know as a “ROC curve”,
which plots true positive rates against false positive
rates displaying the trade-off between sensitivity andspecificity for all cut off values. This method waschosen as it has been shown to be base rate invariant,
as well as being independent of selection ratios (Riceand Harris, 1995). These qualities are particularly
important as re-offending base rates vary as a functionof sex and ATSI status. ROC analysis provides ameasure of discriminative accuracy with greater values
indicating greater discriminative ability. The observed
area under the curve (AUC) statistics can beinterpreted as the probability that a randomly selected
recidivist would have a higher LSI-R score than arandomly selected non-recidivist. Table 2 presents the

In addition to discriminative validity, the current study
investigated the relationship between survival time inthe community and risk classifications via Cox
regression analysis. The analysis revealed that as risk
classifications increase, the survival time in thecommunity decreases. This means that offenders
receiving higher risk classifications re-offend more
quickly and at greater rates than those receiving lower
risk classifications. All tests were statisticallysignificant at the 0.05 alpha level. Figure 2 presents
survival rates as a function of time.

Reliability

Table 2: (AUC) values and 95% confidence intervals split by sex
and ATSI status by recidivism status
LSI-R total score

LSI-R calculated risk
classification

Non-ATSI males.694 (.682 - .707).682 (.670 - .695)

Non-ATSI females.687 (.642 - .731)

N/A

ATSI males.655 (.634 - .676).636 (.614 - .658)

ATSI females.597 (.542 - .652)

N/A

Overall.690 (.680 - .700).677 (.666—.687)

Reliability analysis revealed that the internalconsistency estimates for LSI-R subscales range from
adequate (Cronbach’s alpha for the accommodation
subscale = 0.509) to good (Cronbach’s alpha for the
Education/Employment subscale = 0.784). That is, the
LSI-R exhibits acceptable reliability. This means thateach individual item purported to measure the sameunderlying construct produced similar scores. Thesefindings are similar to those reviewed by Andrews andBonta (1995).

4

DISCUSSION

low to high, rates of recidivism increase and survival
time in the community decreases. These estimates are
similar to those obtained when analysing international
samples (Flores, Lowenkamp, Smith, & Latessa, 2006;
Lowenkamp, Levine, & Latessa, 2009; Manchak,
Skeem, & Douglas, 2008).

The current study investigated the utility of LSI-R
assessments within NSW correctional environments.
The study sought to establish CSNSW normative
statistics by examining the pattern of discrimination
exhibited by the LSI-R. This examination revealed an
encouraging pattern, with proportionally more
recidivists in the high risk categories and proportionallymore non-recidivists in the lower risk categories. While
this pattern is encouraging, it is inconsistent withresults reported by Eyland, et al. (2009). Several
factors may account for this discrepancy, namely;

•

•

•

The results of the current study should be interpreted
within the risk, needs, and responsivity theoreticalframework. Higher risk offenders, as identified by the
LSI-R, should receive high intensity interventions.
Conversely, low risk offenders should receive low
intensity or no intervention. This study reinforces that it
is appropriate for CSNSW to use the LSI-R to adhere to
the risk principle and rehabilitative practice.
Furthermore, the unique LSI-R profile exhibited by each
offender will assist service providers in tailoring
intervention plans in CSNSW.

The current study used a more contracted
definition of recidivism; defined as reincarceration following release as opposed toreturning to prison or supervision of CSNSW.
The studies differed in their criteria for sample
inclusion (sentence length less then 2 years toaccommodate for CSNSW LSI-R guidelines
regarding incarcerated offenders).
Standardisation of eligibility to re-offend as
opposed to collecting recidivism data based on aset of data.

An examination of offender criminogenic needs profiles
split by sex and ATSI status revealed that while
significant differences were observed, the varianceaccounted for by the statistical model wasinconsequential. That is to say, Andrews and Bonta’s
claim of gender and ethnic neutrality is confirmed
within the current sample. This means that the LSI-R
does not appear to discriminate between males andfemales or non-ATSI and ATSI offenders. Each group
scored similarly on the LSI-R. While the different groups
may have scored similarly, it should be noted that the
LSI-R does not appear to function as well with
Table 3: LSI-R total and subscales means and standard deviations split
ATSI females. There is a notable decline in theby sex and ATSI status.
LSI-R’s predictive power when applied to female
Non-ATSI
Non-ATSI
ATSIATSI offenders. This may be due to ATSI females
ATSI males
males
femalesfemales
LSI-R Dimension
manifesting different criminogenic needs than(n=2465)(n=7555)(n=614)(n=417)those measured by the LSI-R. ATSI females as agroup appear to have different pathways to
6.1 (2.2)
6.6 (1.9)
Criminal history
5.7 (2.3)
7.1 (1.8)
offending than the other groups. This finding
requires further research.
6.0 (2.6)
7.4 (1.6)
Education/Employment

While the distributional proportions exhibited by
offenders is encouraging, investigating the LSIR’s psychometric properties within NSW
required more detailed analyses, including the
calculation of point bi-serial correlations, ROC
analysis, Cox regression, as well as measures ofreliability (internal consistency). When taken
together the results suggest that the LSI-R
exhibits acceptable psychometric properties
when applied to a sample of NSW custody-based
offenders. That is, there is a good likelihood thata randomly selected recidivist would have ahigher LSI-R score than a randomly selected
non-recidivist and that higher LSI-R scores areassociated with increased rates of recidivism. As
risk classifications progressively increase from

6.6 (2.2)

7.3 (2.1)

Financial

1.4 (0.8)

1.7 (0.5)

1.6 (0.6)

1.8 (0.4)

Family/Marital

1.7 (1.3)

2.3 (1.2)

2.4 (1.2)

2.6 (1.1)

Accommodation

1.0 (1.0)

1.2 (1.0)

1.3 (1.0)

1.6 (1.0)

Leisure/Recreation

1.5 (0.7)

1.7 (0.6)

1.7 (0.6)

1.8 (0.5)

Companions

2.1 (1.2)

2.5 (1.2)

2.5 (1.1)

2.6 (1.0)

Alcohol/Drug problems

5.0 (2.3)

5.2 (2.4)

6.0 (1.8)

6.0 (1.7)

Emotional Personal

1.4 (1.4)

2.0 (1.5)

1.3 (1.4)

1.9 (1.5)

Attitudes/Orientation

1.5 (1.4)

1.4 (1.4)

1.9 (1.2)

1.8 (1.5)

LSI-R total score27.7 (9.2)

30.2 (8.7)

33.0 (7.6)

34.2 (6.3)

5CONCLUSION

LIMITATIONS

Collectively, the results of the present study indicatethat the LSI-R is functioning similarly to its use
internationally. The test appears to assign higher risk
levels to offenders more likely to re-offend for the
majority of offenders. This finding is encouraging andprovides empirical evidence for the continued
application of the LSI-R to all populations; including
non-ATSI males and females and ATSI males in NSW.
When applied to NSW ATSI females, however, the LSIR’s appropriateness is questionable. The magnitude of
the LSI-R subscale correlations and the instruments
discriminative ability regarding recidivism is reduced
for this population compared to the majority ofoffenders. This finding suggests that LSI-R
assessments of risk may not be valid and may be
misleading when applied to NSW ATSI females. Further
research is required to investigate why the LSI-R is not
functioning as well with this particular subgroup.

While the current study sought to re-examine the utilityof the LSI-R in light of the methodological limitations
observed with previous research, certain limitations
still exist. These include:•

The sample consisted only of custody-based
offenders. The results may not hold forcommunity based offenders.

•

Sampled offenders were drawn from only one
correctional jurisdiction. Thus, re-offences
occurring in other states would not be captured.

•

Where offenders had multiple assessments thelast assessment was used in the analysis. These
assessments may be artificially inflated/deflated
due to statistical regression. The impact of thiseffect was not investigated.

•

The impact of treatment was unable to beassessed. This means that sampled offenders
may or may not have undergone treatment while
incarcerated. Given that CSNSW targets medium
to high risk offenders as those in most needfor intervention, recidivism rates within
Table 4: Point bi-serial correlations and 95% confidence intervals split by sex
these groups may be partly deflated.
and ATSI status.
LSI-R Dimension

Non-ATSI
males(n=7555)

Non-ATSI
females(n=614)

ATSI males(n=2465)

ATSI females(n=417)

RECOMMENDAITONS

Criminal history

0.277**
0.328**
0.183**
0.268**(0.26 to 0.31) (0.26 to 0.40) (0.15 to 0.22) (0.18 to 0.36)

The following recommendations are madebased on the findings of this study.

Education/
Employment

0.236**
0.168**
0.199**
0.113*(0.22 to 0.26) (0.09 to 0.25) (0.16 to 0.24) (0.02 to 0.21)■

Financial

0.187**
0.106**
0.134**
0.081(0.17 to 0.21) (0.03 to 0.19) (0.10 to 0.17) (-0.02 to 0.18)

Family / Marital

0.136**
0.073
0.144**
0.042(0.11 to 0.16) (-0.01 to 0.15) (0.11 to 0.18) (-0.05 to 0.14)

Accommodation

0.163**
0.164**
0.131**
0.026(0.14 to 0.19) (0.09 to 0.24) (0.09 to 0.17) (-0.07 to 0.12)

Leisure /Recreation

0.160**
0.045
0.127**
0.094(0.14 to 0.18) (-0.03 to 0.12) (0.09 to 0.17) (-0.03 to 0.16)

Companions

0.175**
0.186**
0.158**
0.041(0.15 to 0.20) (0.11 to 0.27) (0.12 to 0.20) (-0.06 to 0.14)

Alcohol/Drugproblems

0.201**
0.239**
0.173**
0.062(0.18 to 0.23) (0.16 to 0.31) (0.14 to 0.21) (-0.03 to 0.16)

Emotional
Personal

0.051**-0.001
0.068**-0.028(0.03 to 0.07) (-0.08 to 0.08) (0.03 to 0.11) (-0.12 to 0.07)

Attitudes/
Orientation

0.174**
0.092*
0.176**
0.109*(0.15 to 0.20) (0.01 to 0.17) (0.14 to 0.22) (0.01 to 0.21)

LSI-R total score0.306**
0.271**
0.270**
0.175**(0.29 to 0.33) (0.20 to 0.35) (0.24 to 0.31) (0.08 to 0.27)** Correlation significant at the 0.01 level (2 tailed)* Correlation significant at the 0.05 level (2 tailed)( ) 95% confidence intervals

6

The analyses presented in thecurrent study should be repeated with asample of community-based offenders.

■

Further research into why the LSI-R
is not functioning as well with ATSI females
should be commissioned.

REFERENCES
Andrews, D. A., & Bonta, J. (1995). The Level of Service
Inventory–Revised. Toronto, Canada: Multi-Health
Systems.
Andrews, D. A., & Bonta, J. L. (1994). The psychology ofcriminal conduct. Cincinnati, OH: Anderson.
Eyland, S., Heggie, K., de Almeida Neto, A., &McHutchison, J. (2009). Research Bulletin. NSW
Department of Corrective Services. (unpublished)
Flores, A. W., Lowenkamp, C. T., Smith, P., & Latessa,
E. J. (2006). Validating the Level of Service InventoryRevised on a Sample of Federal Probationers. Federal
Probation, 70 (2).
Hsu, C., Caputi, P., & Byrne, M. K. (2010). Level ofService Inventory-Revised: Assessing the risk and needcharacteristics of Australian Indigenous offenders.
Psychiatry, Psychology and Law, 17, 355-367.
Hsu, C., Caputi, P., & Byrne, M. K. (2009). The Level Of
Service Inventory—Revised (LSI-R). A useful risk
assessment measure for Australian offenders?
Criminal Justice and Behavior, 36, 728-740.
Lowenkamp, C. T., Levine, B., & Latessa, E. J. (2009).
Validating the Level of Service Inventory-Revised andthe Level of Service Inventory: Screening Version with a
Sample of Probationers. The Prison Journal, 89 (2),
192-204.
NSW Department of Corrective Services (2009).
Annual report 2008/09.
Rice, M. E., & Harris, G. T. (1995). Violent recidivism:
Assessing predictive validity. Journal of Consulting andClinical Psychology, 63, 737-748.
Manchak, S. M., Skeem, J. L., Douglas, K. S. (2008).
Utility of the Revised Level of Service Inventory (LSI-R)
in Predicting Recidivism After Long-Term Incarceration.
Law and Human Behaviour, 32, 477-488.

ABOUT THE AUTHOR
Ian Watkins is a registered psychologist in Australia
and an Honorary Associate/guest Lecturer at
Macquarie University. He has worked within a
specialised assessment unit within CSNSW and liaised
as a statistical consultant on many research projects.

7

OTHER TITLES IN THIS SERIES
28.

Women convicted of a violent offence in NSW
2000—2009. August 2010

11.

Parole in NSW: The interrelated problems ofeducation and unemployment. August 1982.

27.

Drug-related patterns and trends in NSW
inmates - Overview of the 2007-08 biennial
data collection. March 201010.

Parole in NSW: Weighing the Benefits, Dangers& Opportunities. August 1982.

9.

Violent offences and recidivism. June 1982.

26.

Offender Population Trends: convicted Sex
Offenders in NSW. November 20098.

Parole in NSW: Predicting successful
completion. August 1982.

25.

Profile of Violent Behaviour by Inmates in
NSW correctional centres. March 20087.

Migrants’ understanding of the legal process:A survey of prisoners in NSW gaols. 1982.

24.

Drug-related statistics on NSW inmates:
2005. June 2007.

6.

The threat from escapes: Some facts about
prison escapes. March 1982.

23.

Evaluation of the Drug and Alcohol Addiction
and Relapse Prevention Programs in
Community Offender Services. June 2007.

5.

Language background and release fromindeterminate sentences. October 1981.

22.

Escapes from NSW correctional centres - a
critical analysis. July 2006.

4.

The impact of enforced separation on
Prisoners’ Wives. October 1981.

21.

(Unpublished)3.

Prediction of Performance in a Work Release
Programme. June 1981.

20.

Remand Inmates in NSW – Some Statistics.
June 2001.

2.

Language background of prisoners. December
1980.

19.

The Alcohol and Other Drug Screen with
Inmate Receptions in New South Wales: A Pilot
Initiative. May 1997.

1.

Prisoner to population ratios in NSW, Victoria
and the Netherlands. December 1980.

18.

Trends in Custodial Sentences in NSW: 19901995. September 1996.

17.

Reasons for Escape: Interviews with
Recaptured Escapees. June 1992.

16.

Periodic Detention in NSW: Trends and Issues
1971-1991. August 1991.

15.

Profile of NSW Periodic Detainees, 1991. June
1991.

14.

NSW Corrective Services Industries andOffender Post-release Employment. April
1991.

13.

12.

Research Bulletin No. 29
ISSN 0729-2422© Corrective Services NSW

Escapes from NSW Gaols: What is the extent
of the problem, who are the escapees andwhat danger do they represent for thecommunity? 1st July 1983 - 30th June, 1989.
November 1989.

Corporate Research, Evaluation & Statistics
Corrective Services NSW
GPO Box 31
Sydney NSW 2001

Census of unemployed Probation and Parole
clients, February, 1983. February 1983.

Telephone: (02) 8346-1556
Facsimile: (02) 8346-1590
Email: research.enquiries@dcs.nsw.gov.au
Web: http://www.correctiveservices.nsw.gov.au

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