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https://doi.org/10.1177/0093854819835277
CRIMINAL JUSTICE AND BEHAVIOR, 201X, Vol. XX, No. X, Month 2019, 1 –17.
DOI: 10.1177/0093854819835277
Article reuse guidelines: sagepub.com/journals-permissions
© 2019 International Association for Correctional and Forensic Psychology
1
PREVENTING JUVENILE TRANSITIONS TO
ADULT CRIME
A Pilot Study of Probation Interventions for Older,
High-Risk Juvenile Delinquents
JOSE B. ASHFORD
Arizona State University
JOHN M. GALLAGHER
University of Arkansas
This pilot study compared the recidivism risks of older, high-risk juvenile probationers exposed or unexposed to an experi-
mental case-management intervention to further the development of a supportive community intervention. The experimental
intervention targeted unmet basic needs before and after the exposed group aged out of the juvenile justice system to prevent
transition to adult crime. A prospective-cohort design compared the recidivism risks of the intervention group (n = 29) with
a randomly selected comparison group (n = 114) stratified by gender, race, and risks/needs. We followed both groups for 3
years after members turned 18. The results of this pilot study showed no effects on recidivism risks, but statistically signifi-
cant effects on the timing to recidivism for the group exposed to an innovative intervention. The study also revealed that the
intervention was able to recruit and maintain the probationers and members of their family for the duration of the interven-
tion.
Keywords: transition to adult crime; recidivism prevention; juvenile probation; natural supports; corrections of place
Studies of accountability-oriented intensive-supervision programs (ISPs) have shown
mixed results in reducing recidivism for both juvenile and adult offenders (Barton &
Butts, 1990; Krisberg, Rodriguez, Baake, Neuenfeldt, & Steele, 1989; Petersilia, 1999).
Nonetheless, researchers have found some promising results when interventions devote
AUTHORS’ NOTE: The authors would like to thank Elizabeth Ells, PhD, Jacqueline Picone, and other
employees of the Maricopa County Juvenile Probation Department for their assistance with this research proj-
ect. They would also like to thank social work students Rachel Williams (Arizona State University) and Elise
Warner (University of Arkansas) for their assistance with collecting recidivism data. The opinions expressed
are those of the authors. The authors contributed equally to this work. The authors evaluated the Maricopa
County Justice Support Services through a grant from the Maricopa County, AZ Human Services Department.
Correspondence concerning this article should be addressed to John M. Gallagher, School of Social Work,
University of Arkansas, SCSW 207, Fayetteville, AR 72701; e-mail: jmgallag@uark.edu.
835277CJBXXX10.1177/0093854819835277Criminal Justice and BehaviorAshford, Gallagher / Preventing Juvenile Transitions to Adult Crime
research-article2019
2 CRIMINAL JUSTICE AND BEHAVIOR
attention to issues of service provision (Davidson, Redner, Blakely, Mitchell, & Emshoff,
1987; Latessa & Lowenkamp, 2006; Paparozzi & Gendreau, 2005; Pearson, McDougal,
Kanaan, Bowels, & Torgerson, 2010). However, questions remain about the nature and
intensity of contacts that are likely to reduce recidivism for serious juvenile offenders
exposed to intensive and other forms of probation supervision (Altschuler, 1998; Gill,
Hyatt, & Sherman, 2010; Taxman, 2002). Austin, Joe, Krisberg, and Steele (1990) found,
for instance, that juvenile probationers “randomly assigned to either no contact probation,
routine supervision, or intensive supervision in Salt Lake, Utah were not significantly dif-
ferent in terms of incidence, frequency, nature, or timing of results” (Lane, Turner, Fain, &
Sehgal, 2005, p. 28). Other studies of intensive supervision have found similar results, in
that these intensive probation interventions had minimal impact on recidivism when com-
pared with other relevant correctional interventions (e.g., Elrod & Minor, 1992; J. Fagan &
Reinarman, 1991; Weibush, 1993).
The mixed evidence for ISP programs begs the question as to whether probation officers
implement the current assumptions about the nature and intensity of supervisory contacts in a
manner that is consistent with principles of effective offender interventions (National Institute
of Corrections, 2005). A number of criminal justice researchers (Andrews, 2006; Lowenkamp,
Latessa, & Smith, 2006) and policy organizations (Crime & Justice Institute at Community
Resources for Justice, 2009; National Institute of Corrections, 2005) promote principles of
effective intervention for reducing criminal recidivism. Yet, there is limited research on how
practitioners are implementing these principles in the process of probation supervision (Bonta,
Rugge, Scott, Bourgon, & Yessine, 2008; Lowenkamp et al., 2006).
Bonta and his colleagues (2008) have attempted to shed some light on the supervisory
process by audio-taping at least three interviews of 154 offenders supervised by 62 out of
108 probation officers in a Canadian province. They found that officers showed poor levels
of adherence to principles of effective intervention. Inasmuch as the probation officers in
their study identified the offenders’ criminogenic needs during their initial assessments,
their case plans rarely focused on meeting these needs (Bonta et al., 2008). Moreover, the
number of contacts that officers had with offenders failed to adhere to prescribed contacts
per level of assessed risk. In addition, the findings by Bonta and his colleagues showed that
officers were neither implementing their responsibilities effectively as brokers of services
nor as change agents in the supervisory process.
The added demand on probation officers for acting as change agents is gaining traction
in the probation literature. Bourgon, Guiterrez, and Ashton (2011) contended, for instance,
that probation officers now have the added responsibility of acting as change agents and not
acting simply as brokers of services. Indeed, proactive forms of supervision (Taxman, 2008)
are replacing broker of service models of probation supervision in many jurisdictions, but
probation officers do not appear to know how to implement this type of case management
without proper training (Gill et al., 2010). In response to this problem, there are some prom-
ising training programs affecting how officers design and implement their case plans
(Bourgon et al., 2011). However, many probation departments still believe that it is better
to rely on human service professionals with specialized expertise in implementing assertive
approaches to case management than to rely on probation officers in balancing their control
and change agent functions.
The Citizenship Project in England for adult offenders provided some preliminary empir-
ical support for the value of relying on multiagency collaborations for providing assertive
Ashford, Gallagher / PREVENTING JUVENILE TRANSITIONS TO ADULT CRIME 3
strategies of service delivery (Pearson et al., 2010). What differentiated this program from
others in community corrections was the emphasis that it placed on engaging with socially
supportive community agencies. Pearson and colleagues found in their evaluation of the
Citizenship Project that promoting contact with community support agencies resulted in
statistically significant reductions in rates of recidivism when compared with a relevant
historical comparison group. The South Oxnard Challenge Program (SOCP) in Ventura
County California also relied on supportive community agencies in the delivery of services,
but the results of this comprehensive community-based intervention did not have the desired
impact on recidivism outcomes. Lane and colleagues wrote, “although SOCP youths
received a more intense program in terms of amount and length of contacts and types of
services given, there were few significant differences between them and the comparison
group on recidivism or other outcomes” (Lane et al., 2005, p. 42).
Lane and colleagues (2005) offered some potential explanations of why they found no
differences on outcomes in the SOCP evaluation. One potential explanation was that the
study was not able to control for the levels of services received by youth who were included
in the comparison group sample. If the comparison youth received similar community-
based services, then this could explain why they observed no differences. In addition, they
found a lack of correspondence between the theory of corrections in place that guided how
the intervention was conceptualized and how the program was implemented. For instance,
the intervention continued to focus on the probationer and minimal attention was given to
targeting the family and “the multiple problems that led youths to commit crime” (Lane
et al., 2005, p. 44).
The assumption that family relationships and family resources need to change to create a
context of support for probationers is widely acknowledged in the current literature on pro-
bation supervision (Farrall, 2004; Shapiro & DiZerega, 2010; Trotter, 2010). This trend
toward taking into account an offender’s social and familial context is in Australia
(Australian Institute of Criminology, 2005) and the United States (Karp & Clear, 2002)
known as the new corrections of place. Older models of community corrections only focused
on changing the offender and neglected addressing the natural supports and the social con-
text of the offender (National Institute of Corrections, 2005). Many older models of com-
munity supervision also left the intervention to a single agency that focused on the risks and
needs of offenders (i.e., probation departments) without giving due regard to the need for
collaboration with other agencies with expertise in supporting families and other individu-
als in the offenders’ social context (Farrall, 2004; Shapiro & DiZerega, 2010; Trotter, 2010).
The present study examined a cohort of older, high-risk juvenile offenders placed on the
highest level of nonintensive probation supervision in Maricopa County, Arizona, with and
without exposure to an assertive case-management intervention that targeted high-risk juve-
niles not connected to school, employment, or training. The probation officers identified a
group of youth on their caseloads experiencing adjustment difficulties associated with
unmet housing, employment, life skills, inadequate family resources, emotional supports,
and other needs that could affect their transition to adulthood. Unlike other youth on their
caseloads, the referred youth lacked connections to work, training, or school and needed
interventions to connect them to these domains of functioning associated with the develop-
ment of self-sufficiency. Indeed, there is limited attention in the current criminological lit-
erature to determining whether addressing unmet needs associated with making a prosocial
transition to adulthood can diminish an older, high-risk juvenile’s transition to adult crime.
4 CRIMINAL JUSTICE AND BEHAVIOR
Much more attention has been devoted to examining the effects of criminogenic risks/needs
and not on addressing basic needs such as employment, housing and financial resources
during this important transitional period in the development of youthful offenders.
During the transition period to adulthood, most youth depend on their families for finan-
cial and emotional support, and this support is often lacking for high-risk juveniles (Institute
of Medicine and National Research Council, 2014; Settersten, Furstenberg, & Rumbut,
2008; Zajac, Sheidow, & Davis, 2015). For this reason, this study examined a cohort of
older, high-risk juveniles referred or not referred to an experimental treatment intervention
to describe their recidivism risks and types of recidivism. The study also examined timing
differences to recidivism for youth exposed or unexposed to an intervention that provided
supports to the juveniles and members of their family after they turned 18 and aged-out of
the juvenile justice system.
Although we explored narrower research questions about risk for and timing to recidi-
vism, the primary aims of this pilot study were as follows: (a) to determine whether it is
feasible to engage and maintain older, high-risk juveniles in an intensive case-management
intervention after they aged out of probation supervision; and (b) identify ways of improv-
ing on study designs for the type of intervention employed in this study. This is consistent
with the role of pilot studies generally in that they place greater emphasis on informing
subsequent research than on having sufficient power to identify statistically significant out-
comes (Connelly, 2008; Leon, Davis, & Kraemer, 2011).
WHY TARGET HIGH-RISK AND OLDER JUVENILE PROBATIONERS?
The initial intent behind the development of standardized risks and needs assessment
instruments in community corrections was to limit probation and parole officer discretion in
assigning juvenile and adult offenders to differential levels of community supervision
(Altschuler, 1998; Ashford & LeCroy, 1988; Baird, 1981; Clear & Gallagher, 1983; Van
Voorhis & Brown, 1996). Youth with high scores on risks and needs assessments were
assigned to high levels of supervision and youth with low scores were assigned to low levels
of supervision (Andrews, Bonta, & Hoge, 1990). Actuarial risks and needs assessments rep-
resented, therefore, important management tools for aiding administrators in the allocation
of limited resources (O’Leary & Clear, 1995). In addition, they enabled researchers eventu-
ally to assess the effectiveness of correctional interventions for specific risk classifications
(Andrews & Bonta, 1998; Dowden & Andrews, 1999; Lowenkamp & Latessa, 2004).
Andrews and Bonta (1998) reanalyzed data from an earlier meta-analysis (Andrews
et al., 1990) and the results of their reanalysis showed that correctional programs that
included mostly higher-risk offenders had improved reductions in recidivism. Lowenkamp
and Latessa (2004) concluded from their examination of Andrews and Bonta’s (1998)
reanalysis that mixing higher-risk offenders with lower-risk offenders can aggravate the
rates of recidivism for lower-risk offenders. The rates of recidivism that Andrews and Bonta
(1998) found were an 11% improvement for correctional programs that treated mostly high-
risk offenders and a 2% improvement for programs that included low and high-risk offend-
ers. Lowenkamp and Latessa (2004) observed similar results in other examinations of
different types of interventions and concluded that there are harms for lower-risk offenders
when mixed with high-risk offenders. For this reason, they recommended that because of
the potential harmful effects associated with the treatment of low-risk offenders that
Ashford, Gallagher / PREVENTING JUVENILE TRANSITIONS TO ADULT CRIME 5
administrators should consider diverting scarce resources primarily to the treatment of
high-risk offenders. Andrews, Kiessling, Robinson, and Mickus (1986) took a similar posi-
tion in their study of the Youth Level Service/Case Management Inventory where they
found that the mixing of low- and high-risk juveniles exacerbated the recidivism of the low-
risk group.
Inasmuch as there are a number of validated risks and needs assessment instruments for
juveniles, Loeber, Hoeve, Slot, and van der Laan (2012) observed that none provide predic-
tions on how many juveniles would transition to adult crime. Instead, they had the goal of
predicting recidivism, while juveniles were under the jurisdiction of the juvenile justice
system. Furthermore, Loeber and colleagues (2012) have contended that the validation of
most of the instruments used in the assessment of risks for juveniles were primarily on
follow-ups limited to 1 year in duration, which did not include the period when juveniles
transition to young adulthood. This transition period has been included mostly in studies
attempting to explain the aggregate increase in crime rates during late adolescence and early
adulthood. Far less attention in the transition period to young adulthood has been devoted
to examining the effectiveness of standard probation in preventing the transition to adult
crime strictly for high-risk juvenile offenders.
In the transitional period to young adulthood, criminal involvements peaks between
15 years and 19 years of age and begins to decline in the 20s (Loeber, Farrington, &
Petechuk, 2013; Loeber et al., 2012). This well-established phenomenon in criminology
is the age–crime curve (Farrington, 1986; Nagin & Tremblay, 2005). It has been docu-
mented in the United States and other developed countries, but there are a number of
debates about how to interpret this peak in rates of crime across the life course (A. A.
Fagan & Western, 2005; Farrington, 1986). Does this peak reflect an increase in the
incidence, prevalence, or some combination of both? Another concern raised in the lit-
erature about this phenomenon is that, while the aggregate rates of recidivism peak dur-
ing this period, there are some variations in when specific types of crime tend to decrease
(Blokland & Palmen, 2012; Rosenfeld, White, & Esbensen, 2012; Sampson & Laub,
2003; Steffensmeir, Allan, Harer, & Streifel, 1989). The results of the Pittsburg longitu-
dinal study found, for instance, that violent crimes tend to peak later than property crimes
(Loeber et al., 2012). Rosenfeld and colleagues (2012) found that marijuana had a longer
duration than theft and violent offenses (Rosenfeld et al., 2012). In addition, Rosenfeld
and colleagues (2012) found that minor offenses such as vandalism and shoplifting
tended to cease prior to the age of 18 years.
European scholars also found variations in when crime peaks for specific types of crime
in studies. Soothill, Ackerley, and Francis (2004) found that the peak age of conviction for
crimes such as burglary was around 16 years of age, but motor vehicle and drug offenses
peaked between 21 years and 25 years and remained high until around 30 years of age
(Loeber et al., 2012). These variations within crime classifications has prompted research-
ers to try to unpack the aggregate rates by offense types to obtain a better understanding of
what crimes persist into adulthood.
Thus far, most of the extant research on the persistence of offending into young adult-
hood by type or category of crime has not focused on evaluating the extent to which older,
high-risk youth placed on a specific level of probation supervision prevented the transition
and the timing of transitions to adult crime. Most studies mixed the subjects exposed to
standard and intensive probation supervision, which is not the case in this study.
6 CRIMINAL JUSTICE AND BEHAVIOR
METHOD
PARTICIPANTS
The present study limits its investigation to two groups of older, high-risk juveniles
placed on the same form of standard probation supervision during the same period of time
and from the same area of a large, urban county. This cohort of older, high-risk juveniles
represents the youth placed on probation and not sentenced to a secure facility because of
the seriousness of their offense(s). The individuals referred to the program and who met all
eligibility requirements were the study’s intent-to-treat group.1 Probation officers referred
29 individuals to the intervention between October 1, 2011 and November 2013. We exam-
ined this group as the intent-to-treat group because the treatment literature has strongly
recommended that “attrition problems are best handled by analyses in which all individuals
initially assigned to each group are examined” (Ashford, Sales, & Reid, 2001, p. 19).
Besides, when researchers only examine the completed treatment group, there is a risk of
overestimating the effectiveness of the group exposed to the enhanced treatment group
(Ashford et al., 2001; Chambless & Hollon, 1998; Flick, 1988; Foa & Emmelkamp, 1983).
The average age for the intent-to-treat group was 16.7 years of age. The intent-to-treat
group was 93.1% male and 6.9% female, and the racial makeup of this group was 39.3%
White, non-Hispanic and 60.7% non-White. All participants in this group were on Level 1
probation supervision and assigned to a high-risk-need classification. A 10-item instrument
developed by the National Council on Crime and Delinquency (NCCD) for Maricopa
County, Arizona, generates three risk/need levels, and this study only included individuals
assigned to the high-risk classification. This actuarial instrument considers familial, social,
behavioral health, and criminal justice factors in the assignment of juveniles to a high-risk/
need classification. Schwalbe (2009) provided a detailed description of NCCD’s instrument
and its revalidation.
The comparison group consisted of a sample of 114 older, high-risk juveniles. The aver-
age age of the comparison group was 16.9 years of age. The comparison group was 91.2%
male and 8.8% female. The racial breakdown for this group of participants is 45.6% White,
non-Hispanic and 54.4% non-White participants.
The sizes of both the treatment and comparison groups are consistent with the recom-
mendation of experts that the sample in a pilot study be at least 10% of the number pro-
jected to be necessary for the full study (Connelly, 2008). Based on a sample size analysis
conducted, and described later in the article, the samples of 29 and 114 in the present pilot
study are both 23% of the projected samples necessary to conduct a full study.
INTERVENTIONS
All individuals in the study received Level I supervision. This is the highest level of
nonintensive supervision in the jurisdiction and calls for the probation officers to have two
face-to-face contacts with the juvenile and one face-to-face or telephonic contact with the
parent or guardian each month. They also should visit the probationer within 45 calendar
days after the youth is on supervision and have one contact every 3 months with schools to
review the juvenile’s attendance. Lastly, officers need to verify employment by speaking
with the juvenile’s employer, seeing the juvenile’s pay stub, and if appropriate, observing
the juvenile at their place of employment.
Ashford, Gallagher / PREVENTING JUVENILE TRANSITIONS TO ADULT CRIME 7
In addition to the standard probation services described above, the exposed group
received an experimental intervention that employed a team approach to case management
in which two support specialists offered support to one probationer and the probationer’s
family, but one of the two specialists was the primary person responsible for the case. Each
specialist had primary responsibility for 15 cases and an adjunctive level of responsibility
for another 15 cases. The program’s supervisor and the other specialists operated as a team
in developing self-sufficiency plans. The specialists assertively supported and connected
the probationers and their families with other services in the community. This approach dif-
fers from traditional approaches in probation supervision that only focus on the offender.
This active support included accompanying youth on referrals to other community-based
services and agencies. It also included taking proactive steps in promoting opportunities for
change in the lives of the probationers and the lives of members of their families. There
were no penalties for the juveniles, and their parents not volunteering to participate. Both
the parents and the juveniles were actively encouraged to collaborate in setting relevant
service goals.
The specialists were located at a Workforce Connections Center that serves the zip codes
of the study’s target population. Within this agency setting, the specialists focused on con-
necting the youth to training, education, and work opportunities. The support specialists
also developed strategies to address other support needs geared to promoting the offenders’
self-sufficiency. The program assumed that if youth lack the capacity for self-sufficiency,
then they will not make a positive transition to adulthood. The instrument the specialists
employed in identifying youth needs (Parker, 2006) focused on identifying barriers to self-
sufficiency for homeless individuals (e.g., income, housing, food, health care, community
involvement, life skills, and employment) and unaddressed criminogenic needs (e.g., sub-
stance abuse, mental health treatment, or family dysfunctions). For instance, many of the
youth were without stable housing and the specialists helped the family obtain appropriate
housing. They also helped the juveniles with transportation issues that previously prevented
them from obtaining employment or participating in relevant training programs. If skill
levels were a barrier, then they would connect them with opportunities for skill develop-
ment at workforce connections or at other relevant opportunities in the community. They
also counseled or referred the families to other services, targeting issues that were affecting
the youth’s adjustment to probation supervision or their completion of their case plans for
achieving self-sufficiency.
The developers of this experimental program wanted the study’s case-management inter-
vention to serve as a bridge between older juvenile probationers who were unlikely to have
their needs met while on standard probation supervision and service providers located in the
probationer’s natural environment. The study’s target group was selected because the chief
of probation at that time assumed that many juveniles in the system who were 16.5 years of
age or older would not be on probation long enough to properly address many of their needs
before turning 18.
PROCEDURES AND DESIGN
The study employed a prospective-cohort design. This longitudinal approach allowed for
an examination of an older cohort of juvenile probationers exposed or unexposed to an
enhanced intervention that we followed forward in time to determine their relative risks for
8 CRIMINAL JUSTICE AND BEHAVIOR
recidivating and their types of recidivism. In addition, the study compared the timing to
recidivism for the two groups.
We completed a stratified random sample of older, high-risk juveniles assigned to Level
1 probation supervision in the same geographic area to construct the comparison group. We
followed the participants in both of our study groups for 3 years beginning when each par-
ticipant turned 18 to determine absolute risk differences, relative risks, types of risks, and
timing to recidivism. Although stratified to resemble the intent-to-treat group, we conducted
tests of difference between the intent-to-treat and the comparison group on key demographic
variables. The results of these analyses in Table 1 show that the groups did not differ on
these demographic variables. We did not need to do so for risks and needs because the study
only included participants classified as high risks based on their risk-need scores.
To evaluate the possibility that the seven individuals who were eligible, but did not enter
differed from those who enrolled, we took two steps. First, we conducted an independent t
test and Fisher’s exact test (FET) on the same background characteristics. These analyses
show that the groups did not differ based on age (p = .200), gender (p = .431), or minority
status (p = .174). The seven eligible individuals also had equivalent risk needs as the sub-
jects who entered the program. Second, while the core of the analyses focuses on differ-
ences between the intent-to-treat group and the comparison group, we also conducted
parallel tests between the 22 individuals who entered and remained in the program and the
comparison group. These parallel tests of the completed treatment group do not alter the
findings and we describe them briefly in the “Results” section.
MEASURES
The juvenile probation department provided the demographic and risk-level data. We
dichotomized race and ethnicity into a binary variable contrasting White, non-Hispanic indi-
viduals with all others. Older, high-risk juveniles was defined for the purposes of this study
as any youth 16.5+ years of age on Level 1 supervision with a high-risk score on the proba-
tion department’s risk/needs assessment instrument developed by NCCD (Schwalbe, 2009).
We operationalized recidivism as the filing of a charge in a felony-level court during a
period of 3 years that began on the 18th birthday of each individual. The study focused on
the filing of a new charge for two reasons. Conceptually, it represents a midpoint between
the less stringent arrest and more stringent conviction/guilty plea thresholds.
Methodologically, we utilized a data system maintained on the Internet by the state’s supe-
rior court system. Although the system readily identifies filing dates, arrest data are unavail-
able and final disposition dates are only available through a complicated review of minute
entries. In addition, we did not include data from misdemeanor-level courts because a
TABLE 1: Background Characteristics by Group
Characteristic Intent to treat (n = 29) Comparison (n = 114) Tests of difference
Age, M16.70 16.90 t(27.38) = 1.39, p = .176
Male gender, n (%) 27 (93.1%) 104 (91.2%) p = 1.00 (FET)
White, non-Hispanic, n (%) 11 (39.3%) 52 (45.6%) χ2(1) = 0.37, p = .55
Note. FET = Fisher’s exact test (two tailed).
Ashford, Gallagher / PREVENTING JUVENILE TRANSITIONS TO ADULT CRIME 9
modest number of them did not participate in the superior court’s data management system
and a pilot test we conducted identified some inconsistencies in reporting practices among
those that did. Thus, focusing on charges filed in felony-level courts maximized validity
from the data source employed in this study.
In addition to the any-felony category, we used the filing charges listed from the superior
court’s system to create three dichotomous variables to identify individuals charged with
the following types of felonies during the same 3 years: substance-related, person, and
property. Our coding of offense types generally followed categorizations used by the Federal
Bureau of Investigation in the National Incident-Based Reporting System (U.S. Department
of Justice, Federal Bureau of Investigation, 2017). In this system, person offenses refer to
crimes such as murder, rape, assault, and any other offense involving an individual. Property
crimes, on the contrary, are crimes in which the object of the crime is property, for example,
bribery, robbery, burglary, and so on. The one exception to the National Incident-Based
Reporting System is that we focused only on a subset of crimes against society: those tied
to drug or alcohol use.
Finally, we created a time-to-recidivism variable. This variable focused on the number of
days that elapsed between the individual’s 18th birthday and the earliest filing date for any-
felony offense.
ANALYSIS PLAN
We completed the study’s research questions in two steps. In the first, we computed abso-
lute risk difference and relative risks as measures of the effects of the exposed group on
rates of felony recidivism after each participant turned 18. We employed these same mea-
sures of effect to assess different types of felony recidivism (substance-related, person, and
property) and at varying time points (1, 2, and 3 years).
Absolute risk reduction refers to the proportion of at-risk individuals who will not expe-
rience the negative outcome (here, recidivism) following exposure to the treatment inter-
vention (Ranganathan, Pramesh, & Aggarwal, 2016). The absolute risk in the control group
minus the absolute risk in the treatment group equals the absolute risk reduction. Relative
risk is another descriptive measure of effects that is widely employed in cohort studies that
provides “an estimate of the baseline risk that is removed as a result of the new therapy”
(Ranganathan et al., 2016, p. 52). In this study, we examined the extent to which we removed
the baseline risks by exposing the older, high-risk offenders with unmet needs to an inten-
sive case-management intervention. This measure represents a relative risk ratio, which
measures the ratio of the probability of recidivism occurring in the exposed group to the
probability of recidivism in the unexposed group. Values below 1 are associated with a
decreased risk for the intervention group, whereas values above 1 indicate an increased risk
of recidivism for the intervention group.
In the second step, we conducted Kaplan–Meier survival analysis to evaluate if the
intent-to-treat and comparison groups differed on time to recidivism for any felony fol-
lowed for 3 years. We treated nonrecidivists in the survival analysis as right-censored cases,
used median days-to-recidivism to compare the groups, and used the Tarone–Ware test to
evaluate if the survival curves differed significantly. We also performed a life-table analysis
to partition the observation periods into smaller time intervals of 6 months to enhance the
policy implications of the Kaplan–Meier results.
10 CRIMINAL JUSTICE AND BEHAVIOR
RESULTS
To examine the effect of the intervention, the study compared recidivism rates, abso-
lute risk reduction and relative risk between the intent-to-treat (n = 29) and comparison
groups (n = 114). To allow examination of how the rates and risks varied (a) by offense
types and (b) over time, we presented the results for any felony, substance-related, person
and property offenses at 1, 2, and 3 years. As can be seen in Figure 1, for any felony and
substance-related felony offenses, the trend2 was toward a reductive effect in risks during
Year 1 that was decreased or no longer present at Year 2. By Year 3, individuals in the
treatment group trended to an increased risk of any recidivism, but not for drug felonies.
The only type of felony for which the intervention lacked a consistent reductive effect
overall was for the property felonies. Individuals in the intent-to-treat group had a ten-
dency toward an increased risk for property offenses, while that risk was smallest during
the first year. The small base rates of person felonies make meaningful interpretation—
even at a descriptive level—challenging, but suggest no meaningful difference between
the groups.
As was discussed in the “Methods” section, it is customary to conduct parallel tests
using the intent-to-treat group and the treated group to guard against overestimating the
effectiveness of the intervention. Thus, after conducting the core analyses with the
29-person intent-to-treat group reported above, the analyses of rates/risk, absolute risk
0
10
20
30
40
50
1-Year 2-Year 3-Year
Percentage Recidivating
ARR 9.9% -2.1% -13.2%
RR .58 1.07 1.38
Any Felony Offense
Comparison Intent-to-treat
0
10
20
30
40
50
1-Year 2-Year 3-Year
Percentage Recidivating
ARR 8.0% 1.2% 3.0%
RR .46 .94 .87
Substance-Related Felonies
Comparison Intent-to-treat
0
10
20
30
40
50
1-Year 2-Year 3-Year
Percentage Recidivating
ARR 0.1% -0.8% 1.1%
RR .98 1.12 .91
Person Felonies
Comparison Intent-to-treat
0
10
20
30
40
50
1-Year 2-Year 3-Year
Percentage Recidivating
ARR -3.3%-8.4% -9.2%
RR 1.47 1.68 1.62
Property-Related Felonies
Comparison Intent-to-treat
Figure 1: Rates and Risk of Recidivism by Group, Recidivism Type, and Time
Note. ARR = absolute risk reduction; RR = relative risk.
Ashford, Gallagher / PREVENTING JUVENILE TRANSITIONS TO ADULT CRIME 11
reduction and relative risk were repeated, comparing the 22 individuals who were retained
in the program with the same 114 individuals in the comparison group. Apart from a small
change in the direction of the risk ratio of person offenses in Year 1, the results did not
alter the trends3.
We examined the time to any-felony recidivism within the 3-year follow-up by perform-
ing Kaplan–Meier survival analysis between the intent-to-treat (n = 29) and comparison (n
= 114) groups. We observed a significant delay in time to recidivism for the intent-to-treat
group. Although the median time to recidivism was 252 days for the comparison group, it
was 578 days for the intent-to-treat group. This difference was statistically significant,χ2(1)
= 5.63, p = .018. To better illustrate the protective value of the intervention in delaying
recidivism, we present the results of the survival curves in Figure 2 and the proportion of
recidivists surviving at each 6-month interval during the 3-year review in Table 2. The pre-
cipitous drop in the comparison group’s survival curve provides graphical evidence that this
group had much higher rates of recidivism during the initial phases of the transition to
adulthood than did the intent-to-treat group.
We again conducted parallel analysis, comparing the 22 individuals who entered the
intervention with the same 114 individuals in the comparison group to ensure that the results
are not confounded by differential outcomes among those who were eligible but did not
enter. There were no changes in the results: The median days to recidivism were unchanged,
and the curves still differed at a statistically significant level.
n
n
Figure 2: Survival Curves for Any Felony Recidivism
12 CRIMINAL JUSTICE AND BEHAVIOR
DISCUSSION
We witnessed mixed results in this study like other studies involving the provision of
intensive case-management services. Indeed, as in other studies, no significant differences in
the types, incidence, and relative risks of recidivism existed between the exposed and unex-
posed groups to the study’s experimental intervention. Nonetheless, the exposed group expe-
rienced a significant delay in timing to recidivism for any felonies. The individuals identified
for inclusion in the exposed group required increased supports not available in their families
to facilitate self-sufficiency and a positive transition to adulthood. Although these supports
did not reduce the absolute, relative types of recidivism risks, the supports did insulate them
from early rates of recidivism during their transition period to adulthood.
Timing to recidivism is a measure to help understand processes underlying the effects of
interventions on propensities for committing crime (National Institute of Justice, 2008). To
this end, the results of the life-table analysis clarified how ineffective standard probation
was in preventing the transition to this specific measure of recidivism when comparing its
results with those of the exposed group. The results showed that by the end of Year 1 of the
study’s criminal follow-up that 71% of the exposed group had not recidivated compared
with 33% of the comparison group. The significant drop in the probability of surviving for
the exposed group occurs between 18 months and 2 years; whereas rates of survival for the
comparison group witnessed a substantial drop between 6 months and 1 year. Thus, the tim-
ing measure employed in this study demonstrated that an underlying process was poten-
tially influencing the transition to recidivism for the exposed group.
However, it was unclear how specific elements in the intervention influenced the timing
to recidivism for the exposed group. Was the delay in the timing to recidivism due to some
change in the quality of the service provision or to levels of engagement in the intervention
process by either the offender or members of their family? These questions require further
scrutiny in future studies that we were unable to address in this study because the only data
available on dosage and other intermediate outcomes were for study participants while on
probation supervision. In addition, this quasi-experiment only provided support services for
about 1 year after the participants turned 18. This might explain why we saw the absolute
risk reduction percentages for property felonies double and not decline for the treatment
group for Year 2. The study’s results must be weighed with a recognition that the sample
size used in this pilot study resulted in a lack of statistical power for proper evaluation of
the questions of relative risk and types of recidivism. A lack of reduction in risks for prop-
erty felonies might have been statistically significant with larger samples. Namely, we could
not rule out that the findings about no significant differences in overall recidivism risks
were correct because of a lack of statistical power for most of this series of analyses. In
TABLE 2: Cumulative Proportion Surviving With Standard Error, Any Felony Charge
Time period Intent to treat (n = 29) Comparison (n = 114)
6 months .93 (.07) .65 (.08)
1 year .71 (.12) .33 (.07)
18 months .64 (.13) .28 (.07)
2 years .36 (.13) .18 (.06)
30 months .29 (.12) .08 (.04)
3 years .00 (.00) .00 (.00)
Ashford, Gallagher / PREVENTING JUVENILE TRANSITIONS TO ADULT CRIME 13
addition, we could not eliminate the possibility that the positive statistical effect observed
for the timing variable was not a false positive because of the study’s sample size4.
IMPLICATIONS FOR FUTURE RESEARCH
This pilot study did identify, however, some potential improvements for future studies,
which is the primary objective of a pilot study. Preventing the transition to adult crime is an
important public safety issue, and this study provides some preliminary evidence that it is
feasible to design a study for measuring the effects of supportive interventions for high-risk
juveniles after they age out of the juvenile justice system. Indeed, this study showed that it
is feasible to recruit and maintain youth and members of their family in a voluntary inter-
vention that extends beyond the period when older, high-risk juveniles were no longer under
the jurisdiction of the juvenile justice system. It retained 22 (76%) of the probationers
referred to this intervention, which is consistent with overall offender attrition rates in psy-
chological interventions, but better than what Olver, Stockdale, and Worthmith (2011)
found for high-risk offenders in their meta-analysis of offender treatment attrition.
This study also identified the need for selective modifications in the duration of the inter-
vention after the youth turned 18. Indeed, future studies need to extend the duration of the
intervention given the potential effects this intervention had on timing to recidivism. Clearly,
this modification is needed when creating an ideal efficacy study because older juveniles are
in a stage of development “when adjustments and passages in the life-course are at their most
challenging and when those already involved in offending are at risk of becoming more pro-
lific” (Burnett & Hanley Santos, 2010, p. 4). This issue is especially true of probationers who
live in communities with inadequate prosocial support networks and institutions.
Future studies should consider, therefore, randomly assigning larger numbers of high-
risk juveniles with basic unmet needs to regular forms of probation supervision and others
to an enhanced supportive intervention that provides a service bridge for a designated
period of time after youth age out of probation supervision to identify appropriate dosages
for this kind of intervention. However, the randomization of subjects to an intervention
that denies additional services to a group not assigned to the experimental intervention
might encounter push back from correctional administrators for ethical and cost-related
concerns. Under such circumstances, a randomized control trial would not be feasible.
However, the protocol employed in this study—drawing a random sample of probationers
from the same jurisdiction stratified to resemble the exposed group on key variables—
proved feasible and with the larger sample recommended above will allow for a rigorous
testing of the intervention described in this pilot study. Utilizing propensity score matching
in the development of the comparison group would also help control for potential group
differences as an alternative strategy.
Although this study showed a possible effect on the question of timing to recidivism, it
could not answer a number of questions about dosage issues. For instance, what is an appro-
priate duration for continuing to support high-risk juveniles after aging-out of probation
supervision? In addition, how long is it reasonable to assume that supportive case managers
can effectively engage the offender and members of the offender’s family in an intervention
that bridges services before and after the juvenile ages out of the juvenile justice system?
Each of the prior questions are also relevant for other interventions that are attempting to
provide a supportive bridge to the offender and the offender’s family during the transition
14 CRIMINAL JUSTICE AND BEHAVIOR
from juvenile delinquency to adulthood. In essence, this pilot study identified a number of
important improvements for future efficacy studies of the type of intervention examined in
this study.
IMPLICATIONS FOR POLICY
Unlike other studies examining the effects of collaborative community supports to juve-
nile probationers, the results of this study demonstrate that a support program that contin-
ued the services after juveniles completed probation had a potential effect on a specific
measure of recidivism—timing to recidivism. This finding suggests that policy makers and
program planners should not rule out trying to increase the timing to recidivism for high-
risk juveniles after aging out of probation supervision. We base this recommendation not
solely on the findings for the participants in the exposed group, but also on the fact that
large numbers of participants in the comparison group recidivated at 6 and 12 months after
aging out of probation supervision. That is, a small group of youth without support after
probation supervision are recidivating. For this reason, future studies need to focus on
obtaining a better understanding of this small group of youth who had comparable crimino-
genic needs when they were originally placed on probation supervision, but recidivated
very shortly after terminating regular probation supervision.
Other countries and some states allow juveniles to remain in the juvenile justice system
through the age of 21 years and even up to 25 years; this is one-policy solution to addressing
risk during the transition period. Oregon, for instance, allows for probation beyond 18 years
of age, but a probationer’s length of supervision cannot extend beyond 23 years. Moreover,
the juvenile court in Oregon can maintain its jurisdiction for up until the juvenile is 25 years
of age. However, the findings of this pilot study suggest that the expansion of the juvenile
system’s jurisdiction alone is not necessarily the best solution for delaying the timing to
recidivism. That is, the enhanced intervention potentially affected recidivism risks from 18
to 24 months after probation ended, but dramatically increased after 24 months. The exposed
group did not receive services for more than 1 year after they turned 18 years of age.
Therefore, the intervention could have continued to reduce rates of recidivism if it contin-
ued for a longer period of time. Thus, future partnerships between justice systems and
researchers should not only increase the number of enrolled individuals, but also consider
increasing the duration of the supportive intervention.
In the area of parole supervision, interventions already exist that bridge the transition
period prior to an inmate’s release and after an inmate enters the community. However,
there is a major gap in current literature about the efficacy of such an approach for older,
high-risk juveniles after aging out of probation supervision. For this reason, the results of
this pilot study are significant because they provide some preliminary evidence that we
need further research and experimentation concerning the adoption of interventions that can
bridge gaps in services during the transition from probation supervision to the stage of
development known as emerging adulthood.
NOTES
1. Youth younger than 16.5 years of age with a serious mental illness, low-to-medium assessed risks/needs, and who were
placed on probation for a violent or sexual offense were not eligible for the program. The probation department uses a risk/
needs assessment instrument developed by NCCD (National Council on Crime and Delinquency) to determine supervision
level. Level 1 supervision is the second highest level of probation supervision. Intensive supervision is the highest level of
Ashford, Gallagher / PREVENTING JUVENILE TRANSITIONS TO ADULT CRIME 15
supervision and is for juveniles classified as high risk with the department’s risk/needs assessment with a sexual or violent
offense history.
2. Although not depicted in the figure for brevity, we conducted statistical tests of difference between the risk/rates for
the groups and confidence intervals generated for the relative risk ratios. In all cases, the results were that the groups did not
statistically differ at the .05 level. The results are reported descriptively nonetheless as (a) the small size of the treatment group
and resultant power suggest that the trends may be noteworthy and (b) the approach taken offers a solid foundation for future
researchers to build upon in better-powered studies.
3. These results are not reported as the analyses were only conducted to verify that using the full intent-to-treat group did
not affect the results. Results are available by contacting the lead author.
4. Using the data obtained in the present pilot study to set effect sizes, sample size estimates were determined based on
chi-square difference test (using Gpower, Version 3.1.92) and the Tarone–Ware test statistic in survival analysis (using PASS,
Version 16). Based on the 3-year, any recidivism rate, a treatment group of 126 and a comparison group of 502 would be suf-
ficient to detect differences with alpha and beta values of .05 and .2, respectively.
ORCID ID
John M. Gallagher https://orcid.org/0000-0002-3677-8397
REFERENCES
Altschuler, D. M. (1998). Intermediate sanctions and community treatment for serious and violent juvenile offenders. In R.
Loeber & D. P. Farrington (Eds.), Serious & violent juvenile offenders: Risk factors and successful interventions (pp.
367-385). Thousand Oaks, CA: SAGE.
Andrews, D. A. (2006). Enhancing adherence to risk-need-responsivity: Making quality a matter of policy. Criminology &
Public Policy, 5, 595-602. doi:10.1111/j.1745-9133.2006.00394.x
Andrews, D. A., & Bonta, J. (1998). The psychology of criminal conduct. Cincinnati, OH: Anderson Publishing.
Andrews, D. A., Bonta, J., & Hoge, R. D. (1990). Classification for effective rehabilitation: Rediscovering psychology.
Criminal Justice and Behavior, 17, 19-52. doi:10.1177/0093854890017001004
Andrews, D. A., Kiessling, J. J., Robinson, D., & Mickus, S. (1986). The risk principle of case classification: An outcome
evaluation with young adult probationers. Canadian Journal of Criminology and Criminal Justice, 28, 377-383.
Ashford, J. B., & LeCroy, C. W. (1988). Decision-making for juvenile offenders in aftercare. Juvenile & Family Court
Journal, 39, 47-53. doi:10.1111/j.1755-6988.1988.tb00611.x
Ashford, J. B., Sales, B. D., & Reid, W. H. (2001). Treating adult and juvenile offenders with special needs. Washington, DC:
American Psychological Association.
Austin, J., Joe, K., Krisberg, B., & Steele, P. A. (1990). The impact of juvenile court sanctions: A court that works. San
Francisco, CA: National Council on Crime and Delinquency.
Australian Institute of Criminology. (2005). Interventions for prisoners returning to community. Canberra: Author.
Baird, C. S. (1981). Classifying juveniles: Making the most of an important management tool. Corrections Today, 43, 36-41.
Barton, W. H., & Butts, J. A. (1990). Viable options: Intensive supervision programs for juvenile delinquents. Crime &
Delinquency, 36, 238-256. doi:10.1177/0011128790036002004
Blokland, A. A., & Palmen, H. (2012). Criminal career patterns from adolescence to early adulthood. In R. Loeber, M. Hoeve,
N. W. Slot, & P. H. van der Laan (Eds.), Persisters and desisters in crime from adolescence into adulthood: Explanation,
prevention and punishment (pp. 13-50). Aldershot, UK: Ashgate.
Bonta, J. A., Rugge, T., Scott, T., Bourgon, G., & Yessine, A. (2008). Exploring the black box of community supervision.
Journal of Offender Rehabilitation, 47, 248-270. doi:10.1080/10509670802134085
Bourgon, G., Guiterrez, L., & Ashton, J. (2011). From case management to change agent: The evolution of “What Works”
community supervision. Irish Probation Journal, 8, 28-48.
Burnett, R., & Hanley Santos, G. (2010). Found in transition? Local inter-agency systems for guiding young adults into bet-
ter lives: Final report of the formative evaluation of the T2A pilots. Oxford, UK: Centre for Criminology, University of
Oxford.
Chambless, D. L., & Hollon, S. D. (1998). Defining empirically supported therapies. Journal of Consulting and Clinical
Psychology, 66, 7-18.
Clear, T. R., & Gallagher, K. W. (1983). Screening devices in probation and parole: Management problems. Evaluation
Review, 7, 217-234.
Connelly, L. M. (2008). Pilot studies. Medsurg Nursing Journal, 17, 411-412.
Crime & Justice Institute at Community Resources for Justice. (2009). Implementing evidence-based policy and practice in
community corrections. Washington, DC: National Institute of Corrections.
Davidson, W. S., Redner, R., Blakely, C. H., Mitchell, C. M., & Emshoff, J. G. (1987). Diversion of juvenile offenders: An
experimental comparison. Journal of Consulting and Clinical Psychology, 55, 68-75. doi:10.1037/0022-006X.55.1.68
16 CRIMINAL JUSTICE AND BEHAVIOR
Dowden, C., & Andrews, D. A. (1999). What works in young offender treatment: A meta-analysis. Forum on Corrections
Research, 11, 21-24.
Elrod, H. P., & Minor, K. I. (1992). Second wave evaluation of a multi-faceted intervention for juvenile court probationers.
International Journal of Offender Therapy and Comparative Criminology, 36, 247-262.
Fagan, A. A., & Western, J. (2005). Escalation and deceleration of offending behaviours from adolescence to early adulthood.
Australian & New Zealand Journal of Criminology, 38, 59-76. doi:10.1375/acri.38.1.59
Fagan, J., & Reinarman, C. (1991). The social context of intensive supervision: Organizational and ecological influences on
community treatment. In T. L. Armstrong (Ed.), Intensive interventions with high risk youths: Promising approaches in
juvenile probation and parole (pp. 341-394). Monsey, NY: Criminal Justice Press.
Farrall, S. (2004). Social capital and offender reintegration: Making probation desistance focused. In S. Maruna & R.
Immarigeon (Eds.), After crime and punishment: Pathways to offender reintegration (pp. 57-82). New York, NY:
Routledge.
Farrington, D. P. (1986). Age and crime. In M. Tonry & N. Morris (Eds.), Crime and justice: An annual review of research
(Vol. 7, pp. 189-250). Chicago, IL: University of Chicago Press.
Flick, S. N. (1988). Managing attrition in clinical research. Clinical Psychology Review, 8, 499-515.
Foa, E. B., & Emmelkamp, P. M. G. (1983). Failures in behavior therapy. New York, NY: Wiley.
Gill, C. E., Hyatt, J., & Sherman, L. W. (2010). Systematic review protocol: Probation intensity effects on probationers’
criminal conduct. Available from www.campbellcollaboration.org
Institute of Medicine and National Research Council. (2014). Investing in the health and well-being of young adults.
Washington, DC: The National Academies Press.
Karp, D. R., & Clear, T. R. (2002). The community justice frontier: An introduction. In D. R. Karp & T. R. Clear (Eds.),
What is community justice: Case studies of restorative justice and community supervision (pp. ix-xvi). Thousand Oaks,
CA: SAGE.
Krisberg, B., Rodriguez, O., Baake, A., Neuenfeldt, D., & Steele, P. (1989). Demonstration of post adjudication non-residen-
tial intensive supervision programs: Assessment report. San Francisco, CA: National Council on Crime and Delinquency.
Lane, J., Turner, S., Fain, T., & Sehgal, A. (2005). Evaluating an experimental intensive juvenile probation program:
Supervision and official outcomes. Crime & Delinquency, 51, 26-52.
Latessa, E., & Lowenkamp, C. (2006). What works in reducing recidivism? University of St. Thomas Law Journal, 3, 521-
535.
Leon, A. C., Davis, L. L., & Kraemer, H. C. (2011). The role and interpretation of pilot studies in clinical research. Journal
of Psychiatric Research, 45, 629-229.
Loeber, R., Farrington, D. P., & Petechuk, D. (2013). Bulletin 1: From juvenile delinquency to young adult offending (Study
group on the transition between juvenile delinquent and adult crime). Washington, DC: U.S. Department of Justice.
Loeber, R., Hoeve, M., Slot, N. W., & van der Laan, P. H. (2012). Introduction. In R. Loeber, M. Hoeve, N. W. Slot, & P. H.
van der Lann (Eds.), Persisters and desisters in crime from adolescence into adulthood (pp. 1-12). Surrey, UK: Ashgate.
Lowenkamp, C. T., & Latessa, E. J. (2004). Understanding the risk principle: How and why correctional interventions can
harm low-risk offenders. Topics in Community Corrections, 2004, 3-8.
Lowenkamp, C. T., Latessa, E. J., & Smith, P. (2006). Does correctional program quality really matter? The impact of adher-
ing to the principles of effective interventions. Criminology & Public Policy, 5, 575-594.
Nagin, D. S., & Tremblay, R. E. (2005). Developmental trajectory groups: Fact or a useful statistical fiction? Criminology, 43,
873-904. doi:10.1111/j.1745-9125.2005.00026.x
National Institute of Corrections. (2005). Implementing evidence-based practices in community corrections: The principles of
effective intervention. Washington, DC: Author.
National Institute of Justice. (2008). Measuring recidivism. Retrieved from https://www.nij.gov/topics/corrections/recidi-
vism/Pages/measuring.aspx
O’Leary, V., & Clear, T. R. (1995). Community corrections into the 21st Century. Washington, DC: National Institute of
Corrections.
Olver, M. E., Stockdale, K. C., & Worthmith, J. S. (2011). A meta-analysis of offender treatment attrition and its relationship
to recidivism. Journal of Consulting and Clinical Psychology, 79, 6-21.
Paparozzi, M. A., & Gendreau, P. (2005). An intensive supervision program that worked: Service delivery, professional orien-
tation, and organizational supportiveness. The Prison Journal, 85, 445-466. doi:10.1177/0032885505281529
Parker, W. D. (2006). Homeless evaluation project of the Arizona Department of Economic Security. Phoenix: Arizona
Department of Economic Security.
Pearson, D. A., McDougal, C., Kanaan, M., Bowels, R. A., & Torgerson, D. J. (2010). Reducing criminal recidivism:
Evaluation of citizenship, an evidence-based probation supervision process. Journal of Experimental Criminology, 7,
73-102.
Petersilia, J. (1999). A decade with experimenting with intermediate sanctions: What have we learned? Perspectives on Crime
and Justice, 23, 39-44.
Ashford, Gallagher / PREVENTING JUVENILE TRANSITIONS TO ADULT CRIME 17
Ranganathan, P., Pramesh, C. S., & Aggarwal, R. (2016). Common pitfalls in statistical analysis: Absolute risk reduction,
relative risk reduction, and number needed to treat. Perspectives in Clinical Research, 7, 51-53. doi:10.4103/2229-
3485.173773
Rosenfeld, R., White, H. R., & Esbensen, F. A. (2012). Special categories of serious and violent offenders: Drug dealers, gang
members, homicide offenders, and sex offenders. In R. Loeber & D. P. Farrington (Eds.), From juvenile delinquency to
adult crime: Criminal careers, justice policy and prevention (pp. 118-149). New York, NY: Oxford University Press.
Sampson, R. J., & Laub, J. H. (2003). Life course desisters? Trajectories of crime among delinquent boys followed to age 70.
Criminology, 43, 555-592. doi:10.1111/j.1745-9125.2003.tb00997.x
Schwalbe, C. S. (2009). Risk-assessment stability: A revalidation study of the Arizona Risk/Needs Assessment Instrument.
Research on Social Work Practice, 19, 205-213. doi:10.1177/1049731508317297
Settersten, R. A., Furstenberg, F. F., & Rumbut, R. G. (2008). On the frontier of adulthood: Theory, research and public
policy. Chicago, IL: University of Chicago Press.
Shapiro, C., & DiZerega, M. (2010). It’s relational: Integrating families into community. In F. McNeill, P. Raynor, & C.
Trotter (Eds.), Offender supervision: New directions in theory research and practice (pp. 241-256). New York, NY:
Willan Publishing.
Soothill, K., Ackerley, E., & Francis, B. (2004). Profiles of crime recruitment: Changing patterns over time. British Journal
of Criminology, 44, 401-418. doi:10.1093/bjc/azh018
Steffensmeir, D. J., Allan, E. A., Harer, M. D., & Streifel, C. (1989). Age and the distribution of crime. American Journal of
Sociology, 94, 803-831. doi:10.1086/229069
Taxman, F. S. (2002). Supervision: Exploring the dimensions of effectiveness. Federal Probation, 66, 14-27.
Taxman, F. S. (2008). No illusions: Offender and organizational change in Maryland’s proactive community supervision
efforts. Criminology & Public Policy, 7, 275-302.
Trotter, C. (2010). Working with families in criminal justice. In F. McNeill, P. Raynor, & C. Trotter (Eds.), Offender supervi-
sion: New directions in theory, research and practice (pp. 282-300). New York, NY: Willan Publishing.
U.S. Department of Justice, Federal Bureau of Investigation. (2017). Crimes against persons, property, and society. Retrieved
from https://ucr.fbi.gov/nibrs/2016/
Van Voorhis, P., & Brown, K. (1996). Evaluability assessment: A tool for program development in corrections (NCJ Number
193055). Retrieved from https://www.ncjrs.gov/App/Publications/abstract.aspx?ID=193055
Weibush, R. G. (1993). Juvenile intensive supervision: The impact on felony offenders diverted from institutional placement.
Crime & Delinquency, 39, 68-89. doi:10.1177/0011128793039001005
Zajac, K., Sheidow, A. J., & Davis, M. (2015). Juvenile justice, mental health, and the transition to adulthood: A review of
service system involvement and unmet needs in the U.S. Children and Youth Services Review, 56, 139-148.
Jose B. Ashford is a professor of social work and professor of law and behavioral science at Arizona State University. He has
affiliated appointments in the School of Criminology and Criminal Justice and in Sociology. His current research focuses on
assessments of maturity, juveniles serving life sentences, and transfers of undocumented Mexican nationals to adult courts.
John M. Gallagher is assistant professor of social work at the University of Arkansas. His current research focuses on vet-
eran’s treatment courts, reentry interventions, inmates with minor children, procedural justice, and legal legitimacy.
