Predictors and correlates of re-incarceration among Australian young people in custody

Abstract

The aim of this paper is to describe the predictors and correlates of previous incarceration and re-incarceration among a sample of 319 young offenders in New South Wales, Australia. At baseline, most (78%) participants had been previously incarcerated and after 18 months follow-up, 50% of participants were re-incarcerated in either adult or juvenile custody. Significant correlates of any previous incarceration included heavy alcohol consumption, cannabis dependence, attention deficit hyperactivity disorder and possible borderline intellectual disability. Significant correlates of re-incarceration within 18 months included heavy drinking and using any cannabis. Heavy alcohol consumption and cannabis use are important risk factors for recidivism among young offenders. More research is needed to determine the nature of this association. Evidence-based interventions that address alcohol and cannabis use among this high risk population are needed.

Keywords

alcohol Australia cannabis offending youth

Introduction

While juveniles only comprise a fraction (8–21%) of current offenders (Richards, 2011a), and most will ‘grow out of crime’ (Fagan & Western, 2005; Loeber, 1990; Richards, 2011a), identifying young people most at risk of reoffending is an important research priority. Moreover, juvenile offending poses a unique challenge for criminal justice agencies given the distinct biological and psychological needs of young people (Lipsey & Wilson, 1998; Richards, 2011a). Estimates suggest that on an average day almost 7000 young people are under juvenile justice supervision in Australia, with the majority supervised in the community (86%) (AIHW, 2013). In Australia, juvenile justice legislation is guided by the principle that detention should be the last option, with various diversionary options available (Richards, 2011a). This suggests that young people in detention are likely to be chronic and/or serious offenders (Pritchard & Payne, 2005).

Research on young offender populations in Australia (Butler, Belcher, Champion, Allerton, & Fasher, 2008; Kinner et al., 2014), the United States (Morris et al., 1995; Patterson, Forgatch, Yoerger, & Stoolmiller, 1998) and the United Kingdom (Lader, Singleton, & Meltzer, 2003) have identified high rates of social disadvantage (care placements, parental incarceration, poor educational attainment, unemployment), poor physical and psychiatric health, engagement in sexual risk behaviours, experience of childhood maltreatment and interpersonal violence and problematic substance use. Even though a decrease has been observed in recent years, Australian Indigenous young people are still 14 times more likely to be under community based supervision, and 18 times more likely to be in detention, compared to non-Indigenous young people (AIHW, 2012; Richards, 2011b). Further, Indigenous young people are more likely to enter the juvenile justice system at a younger age, are more likely to complete more frequent, but shorter periods of supervision and are more likely to be referred to court compared to non-Indigenous young people (AIHW, 2012; Snowball, 2008). The disproportionate incarceration of indigenous people is also found internationally (La Prarie, 2002; Nielsen & Robyn, 2003).

Recidivism and reoffending are often used interchangeably to refer to repetitious criminal activity, but methodological differences (i.e. sample chosen, source of data, definitions used, observation periods, counting rules) make comparisons between studies difficult (Payne, 2007). For example, re-arrests and re-convictions are the most commonly used measures of reoffending due to their ease of measurement; arrests however do not capture undetected offending, and not all arrests will lead to a conviction (Mbuba & Grenier, 2008; Payne, 2007). Evidence from Australian research suggests high rates of reoffending among young people in custody (Lynch, Buckman, & Krenske, 2003; Pritchard & Payne, 2005; Putnins, 2003; Stevenson & Forsythe, 1998; Victoria Department of Human Services, 2001). For example, a survey of juvenile detainees in all Australian jurisdictions (n = 467) found over half (55%) reported a prior custodial episode (34% within the previous 12 months and 44% within the previous 24 months) (Pritchard & Payne, 2005). Similar rates of re-incarceration were found internationally (Benda & Tollet, 1999; Mulder, Brand, Bullens, & van Marle, 2011).

Age has been shown to be the most reliable predictor of reoffending, with younger offenders more likely to reoffend, and to reoffend sooner, even after controlling for confounders (Broadhurst & Loh, 1995; Lipsey & Derzon, 1998; Makkai, Ratcliffe, Veraar, & Collins, 2004; Mbuba & Grenier, 2008; Payne, 2007). Studies citing gender differences consistently report young females to be less likely to reoffend and more likely to commit less serious offence types, compared to young males (Cottle, Lee, & Heilbrun, 2001; Payne, 2007). Research suggests Indigenous offenders are more likely to reoffend compared to non-Indigenous offenders (Payne, 2007), however, a study using multivariate survival analysis to predict re-arrest among a sample of property offenders controlling for age, gender, education, drug use and offending history found no association (Makkai et al., 2004). Prior contact with the criminal justice system, including length of criminal career, has also been associated with increased risk of reoffending (Mbuba & Grenier, 2008; Payne, 2007). Socio-economic and lifestyle factors have also been found to increase the risk of reoffending including unemployment, lower educational attainment, assisted housing or homeless, poor family and social supports, psychiatric problems and drug use (Lynch et al., 2003; Makkai et al., 2004; Mbuba & Grenier, 2008; Payne, 2007; Pritchard & Payne, 2005; Putnins, 2003; Salmelainen, 1995). Post-release difficulties have been identified as barriers to successful re-integration into the community, but they are rarely considered in the context of juvenile reoffending (Payne, 2007). Importantly, few studies, particularly in Australia, have examined potential correlates for offending simultaneously in the same cohort of young offenders (Mbuba & Grenier, 2008).

Drug use has been identified as a risk factor in juvenile offending but the strength of the association differs by drug type, frequency of use and offence type (Mbuba & Grenier, 2008; Payne, 2007; Pritchard & Payne, 2005; Putnins, 2003; Salmelainen, 1995; Weisner, Kim, & Capaldi, 2005). Putnins (2003) identified a significant relationship with reoffending only for recent use of alcohol or inhalants. Whereas, Salmelainen (1995) noted associations for cannabis use, amphetamines and polydrug use for break/enter offences, but not shoplifting. Pritchard & Payne (2005) found juvenile detainees not only reported an extensive history of offending (mainly violent and property crimes) and drug use (predominately alcohol and cannabis), but also childhood abuse/neglect, family substance use and difficulties at school. The degree to which risk factors for offending mediate or moderate the association with drug use remains unclear.

Given the limited research, we aimed to describe the predictors and correlates of previous incarceration and re-incarceration among a sample of Australian young offenders. With the challenges of obtaining adequate response rates in a longitudinal follow-up study, we have included a retrospective analysis of correlates of previous incarceration using the total sample. The value of the retrospective analysis is to provide supporting evidence to the findings of the prospective study and to identify additional correlates to direct relevant interventions.

Method

Study design

The 2009 NSW Young People in Custody Health Survey was conducted between August and October 2009 in eight Juvenile Justice Centres (managed by Juvenile Justice NSW) and one Juvenile Correctional Centre (managed by Corrective Services NSW, for young people at a higher security level). The survey included a baseline questionnaire, physical and dental exams and psychological testing. Shorter follow-up surveys were conducted at 3, 6 and 12 months. The full description of the study methodology is reported elsewhere (Indig et al., 2011). Ethics approvals were obtained from the Justice Health Human Research and Ethics Committee, the Juvenile Justice Research Committee, the Corrective Services NSW Ethics Committee and the Aboriginal Health and Medical Research Council Ethics Committee.

Participants

Participation in the study was open to all young people who were in custody on the first day the study team visited a centre. Exclusion criteria for participation included inability to speak sufficient English, a mental illness that prevented informed consent, or being unavailable at the time the survey was implemented due to work or court commitments. Informed consent was obtained for all participants, including parental/guardian consent for those aged less than 14 years. A total of 361 young people (out of a possible 452 in custody at the time) consented to participate, an 80% overall response rate (and 100%, N = 40, of the young women in custody in New South Wales at the time). Of those recruited, 319 (88%) completed the baseline health survey and were released from custody at some point during the 18 month follow-up period.

Baseline questionnaire

The baseline questionnaire covered a broad range of areas, including socio-demographics, self-reported physical and mental health issues, smoking, alcohol and other drug use and other risk behaviours. Alcohol consumption prior to incarceration was measured by the Alcohol Use Disorder Identification Test (AUDIT) (Saunders, Aasland, Babor, De la Fuente, & Grant, 1993). Questions related to cannabis and other drug use were self-reported based on ‘ever’ using the drug and the frequency of drug use in the year before prior to coming into custody. Baseline dependence on cannabis (at time of incarceration) was measured by the Severity of Dependence Scale (SDS), using the recommended score of greater than four to indicate dependent use in adolescents (Martin, Copeland, Gates, & Gilmour, 2006).

Psychological disorders, including depression, anxiety, psychosis, conduct disorder and attention deficit hyperactivity disorder (ADHD), were assessed using the Kiddie Schedule for Affective Disorders for Children – Present and Lifetime Version (K-SADS-PL) 2009 Draft (Birmaher et al., 2009). The 1996 version of the K-SADS-PL included modifications to update it for the Diagnostic and Statistical Manual of Mental Disorders Fourth Edition (American Psychiatric Association, 2000). A composite score of any psychological disorder was calculated by the presence of at least one mental health (including substance abuse) diagnosis.

Cognitive functioning (intelligence testing) was determined using the Wechsler Adult Intelligence Scale – Fourth Edition (WAIS-IV), Australian and New Zealand Language Adaptation for young people aged 17 years and over (Wechsler, 2008). All participants aged 15 years or younger received the Wechsler Intelligence Scale for Children – Fourth Edition (WISC-IV), Australian Standardised Edition (Wechsler, 2003). Participants who were 16 years old were able to complete either test (on the advice of the research psychologist), due to the overlap in the age bracket for the tests. An intelligence quotient (IQ) test result of less than 70 was used to determine the presence of a possible intellectual disability, and an IQ of 70 to less than 80 was used to determine a possible borderline intellectual disability.

Offending behaviour was measured by self-reported age of first incarceration and data linkage to the NSW Department of Attorney General and Justice database for information related to previous, baseline and subsequent incarcerations. Length of baseline incarceration and subsequent offending resulting in re-incarceration in either adult or juvenile custody was measured at 18 months after the baseline interview.

A number of social determinants were included in the analysis which had a possible association with offending which were selected on the basis of previous studies (Loeber, 1990) and were measured in the baseline survey. These included unstable housing, school attendance prior to custody, involvement with out of home care, unemployment, a history of parental incarceration, peer influences and Aboriginal origin.

Follow-up survey

All participants who took part in the baseline survey consented to take part in the follow-up study. This included short follow-up questionnaires at 3, 6 and 12 months after the baseline survey. Follow-up questionnaires were conducted in custody (face-to-face or by telephone, both adult prison and juvenile detention) or by telephone if in the community. Of the 319 participants, 85% (N = 271) completed at least one follow-up survey, with 75% completed at 3 months, 52% at 6 months and 47% at 12 months. Among participants followed up, the majority were completed in custody, with 78% at 3 months, 76% at 6 months and 92% at 12 months conducted in custody. There were no statistically significant differences among socio-demographic variables (age, sex, Aboriginality) and predictors of re-offending between participants who completed or did not complete any follow-up survey (data not shown). The follow-up survey questionnaire included questions related to potential post-release difficulties such as: problems finding accommodation; not working, going to school or Technical and Further Education (TAFE); or not having support from family or friends. Questions were also included related to risky drinking and illicit drug use since release from custody and whether their subsequent arrest was related to being intoxicated or needing money for alcohol and other drugs.

Data collection and analysis

The data were compiled using both electronic data capture and paper-based forms which were read into SAS version 9.2 for statistical analysis (SAS Institute, 2007). Chi-squared statistics were used to compare the socio-demographic, family/peer group, substance use, mental health, criminal history and post-release difficulties in young people by re-incarceration. Variables hypothesized to have an association with offending behaviours were selected as potential risk factors, and those found to have significant univariate associations were included in the logistic regression models. Backwards stepwise elimination logistic regression was used to determine the adjusted odds ratio of risk of the following offending variables: any previous incarceration; having three or more previous incarcerations, first incarceration before 14 years of age, or re-incarceration (in adult or juvenile custody) over 18 months of follow-up from baseline. Significance of associations was at a p value of less than 0.05.

Results

Participant characteristics

Table 1 describes the participant (N = 319) characteristics stratified by whether participants were re-incarceration in 18 months. The overall sample was 87% male, 49% of Aboriginal origin and were on average 17.0 years of age, with 28% of the sample being less than 16 years of age. A high proportion of the sample had a history of out of home care (28%), had unstable housing before custody (35%) and 43% were not working, going to school or TAFE prior to custody. One in five (20%) reported usually drinking six or more drinks on a daily/almost daily basis and a third (34%) met criteria for cannabis dependence. Nearly all (87%) were diagnosed with a mental illness and almost half (48%) had an IQ of less than 80 suggesting a possible intellectual disability or borderline intellectual disability. At baseline, most (78%) participants had been previously incarcerated, 63% had three or more previous incarcerations and 35% had their first incarceration before age 14 years. After 18 months follow-up, 50% of participants were re-incarcerated in either adult or juvenile custody. Among the 271 participants who completed any follow-up survey at 3, 6 or 12 months post baseline survey, 43% were not working, going to school or TAFE in the community 21% reported drinking at least six drinks three or more times per week and 41% reported using cannabis while in the community.

Table 1.

Characteristics of young people in custody by re-incarceration in 18 months.

	Not re-incarcerated % (N = 161)	Re-incarcerated % (N = 158)	Total (N = 319)	p value
Socio-demographics
Male	90.1	84.2	87.2	0.116
Aboriginal origin	41.0	57.0	48.9	0.004
Age <16 years	24.8	29.1	27.9	0.390
Unstable housing prior to custody	34.4	36.2	35.3	0.744
Not working, school or TAFE prior to custody	28.5	40.3	42.8	0.032
Family/peer group
Placed in care before 16 years of age	25.8	30.9	28.3	0.332
Either parent ever in custody	47.0	43.6	45.3	0.555
Most or all friends have been in custody	34.2	44.2	39.2	0.078
Substance use
Usually drank 6+ drinks on daily/almost daily basis	16.7	23.8	20.4	0.134
Used any illicit drugs at least weekly	63.2	68.6	65.9	0.314
Cannabis dependence (SDS 4+)	33.6	34.0	33.8	0.936
Mental health/Intellectual disability
Any psychological disorder	85.9	88.2	87.0	0.575
ADHD	27.5	31.9	29.6	0.424
Possible ID/borderline ID (IQ < 80)	58.9	47.9	46.5	0.061
Criminal history
Any previous incarcerations	73.3	82.9	78.1	0.038
3+ previous incarcerations	55.3	70.9	63.0	0.004
Age <14 first incarceration	31.5	38.9	35.2	0.182
Re-incarceration in 18 month follow-up	−	−	49.5	−
Post-release difficulties in any follow-up survey (3, 6 or 12 months)^a
Accommodation problems	8.2	10.5	9.6	0.631
Not working, school or TAFE in community	45.9	41.0	42.8	0.534
No support/contact with family/ friends	17.8	32.4	25.5	0.006
Drank 6+ drinks, 3+ times per week	9.3	31.7	21.0	<0.001
Post-release drug use in any follow-up survey (3, 6 or 12 months)^a
Used any cannabis	23.3	56.3	40.6	<0.001
Used any ecstasy	3.9	22.5	13.7	<0.001
Used any amphetamines	5.4	21.1	13.7	<0.001
Used any cocaine	0.8	8.5	4.8	0.003
Used any heroin	0.8	6.3	3.7	0.015
Reason for arrest: intoxicated at time of arrest	54.8	49.4	50.9	0.605
Reason for arrest: needed money for drugs/alcohol	6.5	16.1	13.6	0.178

SDS: Severity of Dependence Scale; ADHD: attention deficit hyperactivity disorder; IQ: intelligence quotient; ID: intellectual disability; TAFE: Technical and Further Education.

Sample size N = 271 for completion of any follow-up survey.

Table 1 shows the significant associations between the correlates with re-incarceration in 18 months. Aboriginal young people were significantly more likely to be re-incarcerated (57% vs. 41%, p = 0.004) than non-Aboriginal young people. Other significant correlates from the baseline survey included not working, going to school or TAFE (40% vs. 29%, p = 0.032), having a history of previous incarcerations (83% vs. 73%, p = 0.038) and having a history of three or more previous incarcerations (71% vs. 55%, p = 0.004). Using the follow-up survey data, significant correlates of re-incarceration included not having support from family and friends (32% vs. 18%, p = 0.006), drinking six or more drinks three or more times per week (32% vs. 9%, p < 0.001) and using illicit drugs including cannabis (56% vs. 23%, p < 0.001), ecstasy (23% vs. 4%, p < 0.001) and amphetamines (21% vs. 5%, p < 0.001).

Correlates by incarceration history

Using the baseline data, Table 2 shows the significant associations using adjusted odds ratios between historical offending behaviours and potential correlates. Significant correlates of any previous incarceration included heavy alcohol consumption (drinking 6 or more drinks on a daily/almost daily basis), cannabis dependence, ADHD and possible borderline intellectual disability. Having a history of three or more previous incarcerations was significantly associated with heavy alcohol consumption and possible borderline intellectual disability. Significant correlates of being first incarcerated aged less than 14 years included being male, of Aboriginal origin, aged less than 16 years, placed in care before 16 years of age, using any illicit drugs at least weekly, ADHD and possible borderline intellectual disability.

Table 2.

Correlates by incarceration history among young people in custody at baseline (N = 319).

	Any previous incarceration	3+ previous incarcerations	<14 years first incarceration
	Adjusted OR (95% CI)	Adjusted OR (95% CI)	Adjusted OR (95% CI)
Socio-demographics
Male	−	−	4.51 (1.51–13.43)^a
Aboriginal origin	1.02 (0.50–2.07)	1.11 (0.57–2.18)	3.59 (1.73–7.45)^a
Age <16 years	−	−	3.65 (1.73–7.69)^a
Unstable housing prior to custody	−	1.56 (0.79–3.09)	−
Not working, school or TAFE prior to custody	−	1.33 (0.69–2.59)	1.57 (0.78–3.16)
Family/peer group
Placed in care before 16 years of age	1.63 (0.72–3.70)	1.89 (0.89–4.01)	2.73 (1.30–5.76)^a
Either parent ever in custody	−	1.07 (0.56–2.06)	0.66 (0.32–1.38)
Most or all friends have been in custody	1.19 (0.59–2.40)	1.65 (0.87–3.14)	1.81 (0.91–3.61)
Substance use
Usually drank 6+ drinks on daily/almost daily basis	7.15 (1.64–31.31)^b	3.30 (1.25–8.72)^b	−
Used any illicit drugs at least weekly	1.01 (0.49–2.10)	1.46 (0.74–2.88)	3.02 (1.25–7.30)^b
Cannabis dependence (SDS 4+)	2.53 (1.07–5.95)^b	1.66 (0.80–3.42)	2.10 (0.99–4.45)
Mental health/Intellectual disability
Any psychological disorder	−	1.29 (0.52–3.22)	1.40 (0.41–4.78)
ADHD	2.25 (1.02–4.98)^b	−	2.72 (1.28–5.77)^a
Possible ID/borderline ID (IQ <80)	2.24 (1.08–4.62)^b	2.13 (1.11–4.06)^b	2.78 (1.37–5.63)^a

SDS: Severity of Dependence Scale; ADHD: attention deficit hyperactivity disorder; IQ: intelligence quotient; ID: intellectual disability; TAFE: Technical and Further Education; CI: confidence interval.

p < 0.01. ^bp < 0.05.

Correlates of re-incarceration in 18 months

Table 3 shows the crude and adjusted odds ratio for potential correlates for re-incarceration in 18 months among young people in custody. No correlates measured as part of the baseline survey were found to be significant, including Aboriginality, other socio-demographics and offending history. Significant correlates of re-incarceration within 18 months included drinking six or more drinks at least three or more times per week (odds ratio (OR) = 3.41, 95% confidence interval (CI): 1.36–8.57) and using any cannabis (OR = 2.15, 95% CI: 1.09–4.22) during the follow-up period. The self-reported reason for offending related to alcohol or drugs (intoxication or needing money to buy alcohol/drugs) was not significantly associated with re-incarceration.

Table 3.

Correlates of re-incarceration among young people in custody over 18-month follow-up (N = 271).

	Crude OR (95% CI)	Adjusted OR (95% CI)
Socio-demographics at baseline
Male	0.59 (0.30–1.15)	−
Aboriginal origin	1.91 (1.22–2.97)^a	1.27 (0.72–2.24)
Age <16 years	1.24 (0.76–2.04)	−
Unstable housing prior to custody	1.08 (0.67–1.74)	−
Not working, school or TAFE prior to custody	1.69 (1.05–2.74)^b	1.17 (0.65–2.08)
Family/peer group at baseline
Placed in care before 16 years of age	1.28 (0.78–2.12)	−
Either parent ever in custody	0.87 (0.55–1.37)	−
Most or all friends have been in custody	1.52 (0.95–2.44)	−
Substance use at baseline
Usually drank 6+ on daily/almost daily basis	1.56 (0.87–2.81)	−
Used any illicit drugs at least weekly	1.28 (0.79–2.05)	−
Cannabis dependence (SDS 4+)	1.02 (0.63–1.64)	−
Mental health/Intellectual disability at baseline
Any psychological disorder	1.22 (0.61–2.45)	−
ADHD	1.23 (0.74–2.05)	−
Possible ID/borderline ID (IQ <80)	1.56 (0.98–2.49)	−
Criminal history
Any previous incarcerations	1.77 (1.03–3.04)^b	0.59 (0.22–1.59)
3+ previous incarcerations	1.97 (1.24–3.13)^b	1.79 (0.75–4.27)
Age <14 first incarceration	1.38 (0.86–2.23)	–
Post-release difficulties in any follow-up survey (3, 6 or 12 months)
Accommodation problems	1.31 (0.43–3.97)	–
Not working, school or TAFE in community	0.82 (0.43–1.54)	–
No support/contact with family/friends	2.21 (1.25–3.91)^a	1.88 (0.97–3.65)
Drank 6+ drinks, 3+ times per week	4.52 (2.27–9.03)^b	3.41 (1.36–8.57)^a
Post-release drug use in any follow-up survey (3, 6 or 12 months)
Used any cannabis	4.26 (2.52–7.21)^a	2.15 (1.09–4.22)^b
Used any ecstasy	7.22 (2.72–19.16)^a	3.58 (0.96–13.35)
Used any amphetamines	4.67 (1.97–11.05)^a	0.54 (0.16–1.82)
Used any cocaine	11.81 (1.51–92.18)^b	2.76 (0.29–26.12)
Used any heroin	8.66 (1.08–69.34)^b	4.01 (0.41–39.22)
Reason for offending: intoxicated drugs/alcohol	0.81 (0.35–1.83)	−
Reason for offending: needed money for drugs/alcohol	2.78 (0.59–13.01)	−

p < 0.01. ^bp < 0.05.

Discussion

This paper aimed to explore the predictors and correlates of previous incarceration and re-incarceration among a sample of Australian young offenders. In this study of 319 young people, the majority had previously been incarcerated (78%) and half (50%) were incarcerated again within 18 months, suggesting that multiple incarcerations are the norm. Methodological differences in published studies make it difficult to compare recidivism rates. However, in the most conservative measure, i.e. reconviction (as opposed to appearances in court or police apprehensions) among older Australian research noted recidivism rates at 38% at two years (Luke & Lind, 2002) and between 37% at 12 months to 49% at two years (Victoria Department of Human Services, 2001) in similar cohorts. In an American study of 244 incarcerated adolescents in Arkansas, similar rates of re-incarceration were found with 60% re-incarcerated within three years (Benda & Tollet, 1999).

Results from this study also confirmed that this population has a high number of static and dynamic risk factors for re-incarceration. Specifically it was noted that Aboriginal young people were over-represented and moreover, they were incarcerated at a younger age and had a significantly higher proportion re-incarcerated than non-Aboriginal young people. However, when Aboriginality was included in logistic regression models with other potential predictors, it was only found to be a significant predictor of having the first incarceration before the age of 14 years. This suggests that Aboriginality itself is not a risk factor for a future re-incarceration but can be better attributed to the social and economic disadvantage experienced by Indigenous people (Commonwealth of Australia, 1991; Weatherburn, Snowball, & Hunter, 2008). It also points to the need to invest in prevention and early intervention for young Aboriginal people at risk of coming into contact with the criminal justice system (Homel, Lincoln, & Herd, 1999; National Indigenous Drug and Alcohol Committee, 2009).

Our research identified the strongest predictor of previous incarceration and re-incarceration to be related to problematic alcohol and drug use. In multivariate analysis, young people who were heavy drinkers were seven times more likely to have been previously incarcerated, three times more likely to have been previously incarcerated three or more times, and three times more likely to be re-incarcerated within 18 months. The association between alcohol and offending are well-documented, particularly with regard to binge drinking among young people (Dawkins, 1997; Fergusson, Lynskey, & Horwood, 1996; Richardson & Budd, 2003). Similarly, illicit drug use was another consistent predictor of incarceration, with young people dependent on cannabis being 2.5 times more likely to have been previously incarcerated and young people who used any cannabis post-release were two times more likely to be re-incarcerated. The associations of substance abuse and re-incarceration have been identified in numerous previous studies (Braithwaite, Conerly, Robillard, Stephens, & Woodring, 2003; Stoolmiller & Blechman, 2005).

Few studies have prospectively assessed predictors and correlates for re-incarceration post-release and have instead focused on socio-demographics and other baseline characteristics. Substance use problems have been found to predict recidivism (van der Put, Creemers, & Hoeve, 2013) and the findings of this study suggest that more attention needs to be given to supporting young people into programs and services to address underlying drug and alcohol problems post-release (Fazal, Bains, & Doll, 2006; Lattimore, Krebs, Koetse, Lindquist, & Cowell, 2005). Providing early holistic support across domains such as housing, education and training, and both physical and mental health can assist young people to improve their health and reduce their offending behaviours (Lennings, Kenny, & Nelson, 2006; McCausland, Baldry, Johnson, & Cohen, 2013). One promising way forward which could be explored for young offenders is a monthly recovery management check-up in the first 90 days post-release which has been shown to be both feasible and effective for adult female offenders for both reducing substance abuse and reoffending (Scott & Dennis, 2012). The evidence for the efficacy of post-release substance abuse treatment for offenders is limited but demonstrates some positive impacts on re-incarceration (Bright & Martire, 2013; McCollister et al., 2003).

Another significant finding of this research was that participants with borderline intellectual functioning were significantly more likely to have had a previous incarceration, three or more previous incarcerations or to have been first incarcerated before age 14 years. In a study of 628 American juvenile offenders, young people with intellectual disability were found to have committed more offences and to have more problems with alcohol and other drugs (Asscher, van der Put, & Stams, 2012). Other studies in Australia have found that people with an intellectual disability had a significantly higher rate of re-arrest and re-incarceration than the general population (Cockram, 2005; Holland & Persson, 2011). There is a need for better and earlier identification of intellectual disability in young people who come into contact and are over-represented within the criminal justice system (Hayes, 2002; Haysom, Indig, Moore, & Gaskin, 2014). More research is needed into the pathways that people with an intellectual disability take into the criminal justice system to design improved prevention and early intervention strategies (Raina, Arenovich, Jones, & Lunsky, 2013). The Mental Health Disorders and Cognitive Disability in the Criminal Justice System project, a data linkage project across criminal justice, health and human service agencies of 2731 people who have been incarcerated in NSW explores some of these pathways (Baldry, Dowse, & Clarence, 2012). This study explores the links and intersections between social exclusion, disability and the criminal justice system and suggests systems approaches are needed rather than a focus on the individual to find sustainable solutions (Baldry, Dowse, McCausland, & Clarence, 2012).

This study found that young people diagnosed with ADHD were found to be significantly more likely to have been previously incarcerated or first incarcerated before age 14 years. Some studies have also found significant links between ADHD and recidivism (Gordon, Diehl, & Anderson, 2012), but some have not (Mallett, Fukushima, Stoddard-Dare, & Quinn, 2013). Improving diversion of young people with mental health problems such as ADHD from the criminal justice system into appropriate treatment is an important strategy (Cueller, McReynolds, & Wasserman, 2005; Schwalbe, Gearing, MacKenzie, Brewer, & Ibrahim, 2012).

There are a number of limitations in this study. Firstly, the small sample size limits potential statistical power and the generalizability of these findings may or may not be relevant outside New South Wales. As not all young people were followed up at 3, 6 and 12 months, the follow-up survey data may not capture all changes in post-release difficulties and alcohol and other drug use. As these risk factors have been coded yes if any of the surveys were affirmative, there is a risk of over-estimating the association. On the other hand, participants may not have reported all of their risk behaviours as a result of the self-reporting format. Further, as most of these follow-up interviews took place in prison, many of the young people followed up may not have been released which reduces their exposure to alcohol and other drug use, among other risk factors for re-offending. Further, statistical comparisons were conducted on any socio-demographic differences between participants who completed or did not complete a follow-up survey, not on potential predictors of re-offending, which makes the accuracy of the findings difficult to determine. Another major limitation is we were not able to obtain comprehensive dates for when participants were released into the community so were not able to determine the amount of follow-up time in the community for each participant. Without this information, the risk profile is difficult to determine. For example, with alcohol and cannabis use found to be a significant predictor of re-offending, not knowing how long a participant was in the community complicates our understanding of the timing of when substance use is associated with re-offending.

Despite these limitations, this article adds to the literature by identifying that 50% of Australian young offenders are re-incarcerated within 18 months. Further, it illustrates that alcohol and other drug use is the primary significant predictor of re-incarceration and a history of incarceration. These findings point to the importance of increasing alcohol and other drug treatment in custody and referring young offenders with these problems into treatment upon their release.

Footnotes

Acknowledgements

The authors would like to acknowledge the participants and the other investigators of the 2009 NSW Young People in Custody Health Survey, and the staff from Juvenile Justice NSW and Justice Health and Forensic Mental Health Network who contributed to collecting the data for this survey.

Funding

This research was supported by funds from the following: Department of Juvenile Justice NSW, Justice Health and Forensic Mental Health Network and the Centre for Aboriginal Health at the NSW Ministry of Health.

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