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The Effects of Prison Visitation on Offender Recidivism, MN DOC, 2011

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THE EFFECTS OF PRISON VISITATION ON OFFENDER
RECIDIVISM

1450 Energy Park Drive, Suite 200
St. Paul, Minnesota 55108-5219
651/361-7200
TTY 800/627-3529
www.doc.state.mn.us
November 2011
This information will be made available in alternative format upon request.
Printed on recycled paper with at least 10 percent post-consumer waste

Table of Contents
Research Summary .......................................................................................................... iii
Introduction ....................................................................................................................... 1
Present Study ................................................................................................................................ 2

Prison Visitation Policies .................................................................................................. 2
Prison Visitation Policies in Minnesota........................................................................................ 4

Reentry and Social Support ............................................................................................. 5
Prison Visitation Research ............................................................................................... 7
Recent Studies .............................................................................................................................. 8

Data and Methodology ................................................................................................... 10
Measures ..................................................................................................................................... 10
Dependent Variable ................................................................................................................ 10
Visitation Measures ................................................................................................................ 11
Inmate-Visitor Relationship ................................................................................................... 13
Independent Variables ............................................................................................................ 13
Analysis ...................................................................................................................................... 16

Results .............................................................................................................................. 17
Conclusion ....................................................................................................................... 27
Implications for Correctional Policy and Practice ...................................................................... 29

References ........................................................................................................................ 33

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Tables
Table 1. Descriptive Statistics........................................................................................... 19
Table 2. Cox Regression Models: Impact of Visitation on Time to First Felony
Reconviction ..................................................................................................................... 20
Table 3. Cox Regression Models: Impact of Visitation on Time to First Revocation...... 22
Table 4. Cox Regression Models: Inmate-Visitor Relationship on Time to First
Reconviction ..................................................................................................................... 23
Table 5. Cox Regression Models: Inmate-Visitor Relationship on Time to First
Revocation ........................................................................................................................ 24
Table 6. Effects of Inmate-Visitor Relationship on Recidivism Controlling for Number of
Individual Visitors ............................................................................................................ 26

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Research Summary
Following recent studies in Florida (Bales and Mears, 2008) and Canada (Derkzen,
Gobeil, and Gileno, 2009), this study examines the effects of prison visitation on
recidivism among 16,420 offenders released from Minnesota prisons between 2003 and
2007. Using multiple measures of visitation (any visit, total number of visits, visits per
month, timing of visits, and number of individual visitors) and recidivism (new offense
conviction and technical violation revocation), the study found that visitation
significantly decreased the risk of recidivism, a result that was robust across all of the
Cox regression models that were estimated. The results also showed that visits from
siblings, in-laws, fathers, and clergy were the most beneficial in reducing the risk of
recidivism, whereas visits from ex-spouses significantly increased the risk. The findings
suggest that revising prison visitation policies to make them more “visitor friendly” could
yield public safety benefits by helping offenders establish a continuum of social support
from prison to the community. It is anticipated, however, that revising existing policies
would not likely increase visitation to a significant extent among unvisited inmates, who
comprised nearly 40 percent of the sample. Accordingly, it is suggested that correctional
systems consider allocating greater resources to increase visitation among inmates with
little or no social support.

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Introduction
As the number of individuals housed in state and federal prisons quadrupled over the
past 30 years, so did the number of individuals returning to communities from prisons (Sabol,
West, and Cooper, 2009). Newly released offenders are often unprepared for life outside
(Irwin and Austin, 1994). Returning prisoners face a number of obstacles to successful
reintegration, including unemployment, debt, homelessness, substance abuse, and family
conflict (Travis, Solomon, and Waul, 2001; Visher, La Vigne, and Travis, 2004).
Saddled with large budget deficits in the wake of the recent financial crisis, many
states are realizing the high cost of housing record numbers of prisoners (Pew Center on the
States, 2008). Reducing prison populations, and thereby reducing corrections spending, has
become a central concern for many states. Indeed, given that research has shown that roughly
two-thirds of prisoners will be rearrested within three years of release (Hughes and Wilson
2003; Langan and Levin, 2002), successfully reintegrating former prisoners is crucial to
reducing recidivism and prison populations (Irwin and Austin, 1994).
Findings from recent research have underscored the importance of social support in
helping offenders desist from crime and, more narrowly, recidivism (Duwe, 2011; Shinkfield
and Graffam, 2009). While offenders are in prison, visits from family and friends offer a
means of establishing, maintaining, or enhancing social support networks. Strengthening
social bonds for incarcerated offenders may be important not only because it can help prevent
them from assuming a criminal identify (Clark, 2001; Rocque, Bierie, and MacKenzie,
2010), but also because many released prisoners rely on family and friends for employment
opportunities, financial assistance, and housing (Berg and Huebner, 2010; Visher et al.,
2004). The results from recent studies on prisoners in Florida (Bales and Mears, 2008) and

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Canada (Derkzen, Gobeil, and Gileno, 2009) suggest that both the presence and frequency of
prison visits during the last year of confinement were associated with reduced recidivism.
Present Study
In this study, the relationship between prison visitation and recidivism is examined
among 16,420 offenders released from Minnesota prisons between 2003 and 2007. Rather
than focusing on the impact of visitation during the last year of imprisonment, this study
extends research on prison visitation and recidivism by using multiple measures of visitation
over the entire confinement period to assess the effects of the number, timing, and type of
visits (e.g., friend, sibling, mentor, etc.) on reoffending. It also examines whether the size of
an offender’s social support network, as reflected by the number of individual visitors, is
associated with recidivism. Further, given that offenders in the sample were tracked through
June 2010, a relatively lengthy follow-up period (an average of nearly five years) is used for
recidivism, which was measured two different ways.
In the ensuing section, common prison visitation policies that often inhibit visits from
family, friends, and others are discussed. Next, the study reviews the literature pertaining to
prisoner reentry, social support, and prison visitation. Following a description of the data and
methods used in this study, the findings from the statistical analyses are presented. The study
concludes by discussing the implications of the findings for correctional policy and practice.
Prison Visitation Policies
As prison sentences have increased, offenders have had an increasingly difficult time
maintaining social support networks (Lynch and Sabol, 2001). Mailed letters are slow, and
phone calls are prohibitively expensive (La Vigne et al, 2005). Visits from family and friends

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may be a prisoner’s best option for maintaining social support networks, but they are often
limited.
Families of prisoners have a difficult time visiting inmates for three major reasons.
First, although a majority of prison inmates are from urban areas, most major prisons are
located in rural areas far from the city center (Austin and Hardyman, 2004; Coughenour,
1995; Holt and Miller, 1972). For example, 30 percent of Florida state prison inmates are
from the Miami-Dade County area, but only 5 percent of all Florida inmates are housed in
Dade County (Austin and Hardyman, 2004). Data from the Bureau of Justice Statistics
revealed that more than half of prisoners with children live more than 100 miles from where
they lived before prison, and 10 percent lived more than 500 miles away (Schirmer, Nellis,
and Mauer, 2009). Given that many prisoners come from poverty, their families cannot
typically afford the costs associated with visiting prisons so far away (Christian, 2005).
The second impediment to prison visitation are the administrative policies of prisons
(Austin and Hardyman, 2004). Few prison visitation programs are designed to encourage
visits. Rather, most visitation programs are subordinate to safety and security procedures.
Many prisons perform background checks on potential visitors and bar anyone with a
criminal background. The state of Arizona has begun charging visitors for background
checks, adding to the financial burdens of visiting families (Goode, 2011). Also, visitation
hours are usually limited to a few hours and only on certain days of the week. The Supreme
Court has affirmed the rights of prison administrators to limit visitation programs for the sake
of facility security and safety (Farrell, 2004).
The last major barrier to visitation involves the nature of many visitation programs
and the uncomfortable settings. Generally speaking, prisons are not designed for the comfort

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of prisoners or visitors (Austin and Hardyman, 2004). The families of inmates often travel
long distances to prisons, only to wait in line for hours in rooms that sometimes have no
bathrooms or vending machines, and poor circulation (Sturges, 2002). After waiting for
hours, visitors usually meet with inmates in large multi-purpose rooms, where they are
closely watched and allowed little physical contact.
Prison Visitation Policies in Minnesota
Unlike several other states, most Minnesota state correctional facilities are within 100
miles of the most populous area in the state, the Minneapolis-St. Paul metropolitan area. Of
the prisoners incarcerated on July 1, 2011, about 40 percent were committed from either
Hennepin or Ramsey counties, where Minneapolis and St. Paul are located, respectively
(Minnesota Department of Corrections, 2011). Although visitation policies vary across
facilities, the Minnesota Department of Corrections (MnDOC) has general rules that apply to
all state prisons. Visits, for example, cannot last longer than two hours, and prisoners receive
a maximum number of visiting hours each month. The monthly number of visiting hours
inmates may receive, however, depends on the security level of the facility. Offenders in the
most secure facilities may receive up to 16 hours of visits per month, while those in facilities
with lower security levels may receive up to 36 hours.
Much like other state prison systems, Minnesota has some visitation policies that may
inhibit visits from family, friends, and pro-social others. For example, offenders are primarily
responsible for conveying visitation rules and visitor application materials to potential
visitors. If a visitation application is denied, it is the prisoner’s responsibility to relay that
information to the would-be visitor. Passing this information along may be difficult for
prisoners given their limited communication privileges in the facilities. Also, with the

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exception of immediate family members, visitors are not permitted to be on more than one
current state inmate’s visitor list. Thus, volunteers, such as mentors, are not allowed to visit
multiple inmates during the same general timeframe.
Reentry and Social Support
The prison boom of the past three decades has resulted in a record number of former
inmates attempting to reintegrate back into communities (Hughes and Wilson, 2003; Visher
and Travis, 2003). The capacity of state and federal corrections systems to manage prisoner
reentry has not kept pace with the increasing number of returning prisoners (Lynch and
Sabol, 2001; Petersilia, 2003). Supervision agents, who are often overwhelmed with large
caseloads, must focus exclusively on supervision and are unable to assist with the reentry
process (Petersilia, 1999). Communities are reluctant to accept convicted felons, and released
prisoners are not eligible for many forms of public assistance (Travis et al., 2001).
Social bonds and social support are common elements in many criminological
theories, both as a key to crime prevention and a mechanism for desistance from crime.
According to Hirschi’s (1969) social control theory, an individual’s attachment, or bond, to a
conventional lifestyle prevents him or her from offending. Sensitivity towards family
members and other close contacts is a large component of this bond. Longer and more
frequent visits with family while in prison could strengthen a prisoner’s attachment (LaVigne
et al., 2005). Proponents of general strain theory would argue that family bonds and social
support would ease the stresses related to reentry, making the prisoners less likely to engage
in subsequent criminal behavior (Agnew, 1992). Life-course theorists view the release from
prison as a potential turning point in the lives of offenders (Sampson and Laub, 1993). An

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offender’s attachment to family members could give him or her both the opportunity and
incentive to desist from crime (Horney, Osgood, and Marshall, 1995).
In fact, research has demonstrated that family and friends are a returning prisoner’s
most valuable source of support. Anywhere from 40 to 80 percent of newly released
offenders rely on their families immediately after release (Berg and Huebner, 2010; Nelson,
Deess, and Allen, 1999; Visher et al., 2004). Family and friends are capable of helping
returning prisoners overcome reentry obstacles, including unemployment, debt, and
homelessness.
Because many offenders lack education, vocational skills, and a steady history of
employment (Berstein and Houston, 2000; Petersilia, 2003; Visher et al. 2004; Western,
Kling, and Weiman, 2001), obtaining employment represents one of the largest obstacles
encountered by returning prisoners (Brees, Ra’el, and Grant, 2000; Rocque et al., 2010;
Travis et al, 2001). Social ties are important for anyone seeking employment (Granovetter,
1983), but for a convicted felon they can be particularly salient. A history of serious
offending can make an individual appear untrustworthy and, therefore, less employable
(Pager, 2003; Petersilia, 2003; Western et al. 2001). An endorsement by a family member
can persuade potential employers to overlook the stigma of incarceration. For example, Berg
and Huebner (2010) found that released prisoners who had strong family ties were more
likely to maintain a job compared to less attached prisoners. Moreover, released prisoners
who had jobs and strong family ties were much less likely to reoffend.
In addition to unemployment, returning prisoners tend to have a lot of debt
(Levingston and Turetsky, 2007), and are likely to encounter housing issues. While
incarcerated, many prisoners accumulate debts from child support, court-imposed fines and

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assessments, restitution to victims, and other sources. Faced with unemployment and debt,
would-be private landlords are unlikely to rent to returning prisoners (Travis et al., 2001).
Similarly, federally-funded housing is not available to those who have histories of drug or
violence-related offenses. Because about half of returning prisoners were serving a sentence
for a drug or violence-related conviction, and even more ex-prisoners have at least one prior
drug or violence-related conviction, most returning prisoners are not eligible for federal
housing assistance (Petersilia, 2003).
Many newly released prisoners rely on their families for financial assistance and
housing (e.g., Nelson et al., 1999; Visher et al., 2004). For example, in a study that followed
205 men leaving prison, La Vigne et al. (2004) found that 59 percent of these men were
receiving financial support from spouses, family members, or friends, and 88 percent were
living with family members. Eighty-four percent of the ex-prisoners in Visher et al.’s (2010)
study were living with family seven months out of prison, and 92 percent received cash
assistance from their families. In Nelson’s (1999) qualitative study of reentry in New York
City, 40 out of the 49 participants lived with family immediately after release. Perhaps more
importantly, released prisoners who lived with family members were less likely to abscond
from parole. Although few of this study’s participants received cash support from family,
most received some other form of material support. Altogether, social support networks
appear to be an effective and cheap reentry tool.
Prison Visitation Research
It has been nearly 40 years since the National Advisory Commission on Criminal
Justice Standards and Goals (1973) recommended that prisons develop policies more
conducive to visitation. Yet, impediments to prison visitation continue despite the fact that

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researchers and prison administrators have long been aware of the benefits of visitation
programs (Farrell, 2004; Schafer, 1994). Decades of research indicate that visits from family
improve institutional behavior and lower the likelihood of recidivism for inmates (e.g.,
Borgman, 1985; Carlson and Cervera, 1992; Casey-Acevedo and Bakken, 2001; Bales and
Mears, 2008; Holt and Miller, 1972). In one of the first studies of the effects of prison
visitation on recidivism, Holt and Miller (1972) found that only 2 percent of prisoners who
had three or more visitors in their final year of incarceration returned to prison within a year
of release, compared to 12 percent of prisoners who had no visitors. In subsequent studies of
prison visits and furlough programs, researchers found similar results (e.g., Adams and
Fischer, 1976; Glaser, 1964; Howser and McDonald, 1982; Leclair, 1978). More frequent
and intense visits with family and friends, either through visits or furloughs, decrease the
likelihood of recidivism and parole failure.
Recent Studies
More recent research has found similar results. Bales and Mears (2008) examined the
effects of prison visitation on recidivism among 7,000 Florida state prison inmates. They
limited their sample to prisoners who were serving at least a one-year sentence, and they
looked only at visits that occurred during the final year of incarceration. The authors found
that the frequency, timing, and type of visitor were all related to the risk of recidivism. Any
and more frequent visits during the last year of imprisonment reduced the risk of recidivism.
Visits that occurred close to the time of release had the strongest effect on recidivism. Visits
from both family and friends reduced the risk of recidivism, but visits from spouses had an
even stronger negative effect on the risk of recidivism. Even among the individuals who did

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reoffend, the prisoners who were visited took longer to do so compared to the 58 percent of
the sample who did not receive any visits.
In another recent study, Derkzen et al. (2009) compared post-release outcomes among
6,537 Canadian inmates who did not receive any visits, inmates that received standard prison
visits, and inmates who received special private family visits. Like Bales and Mears (2008),
Derkzen and colleagues (2009) examined visits during the last year of confinement for
offenders. The results of this study were similar to the results of the Bales and Mears (2008)
study, as prisoners who received visits from family and friends were significantly less likely
to reoffend or be readmitted to prison. Private family visits were associated with an even
larger reduction in recidivism compared to regular visits. Prisoners who participated in the
longer, more private family visits were much less likely to reoffend or be readmitted to
prison compared to inmates who had shorter, more restricted visits or no visits at all.
This study builds on the recent research by Bales and Mears (2008) and Derkzen et al.
(2009) in several ways. First, it examines the impact of visitation on recidivism for all
released offenders regardless of their length of stay (LOS) in prison. If inmates were limited
to a LOS of 12 months or more, 44 percent of the offenders in this study’s sample and 80
percent of those who were admitted to prison as parole violators would be excluded. By
including all offenders released from Minnesota prisons during the 2003-2007 period, this
study contains a more representative sample of released prisoners, thereby increasing the
generalizability of the findings. Second, despite the focus on visitation over the entire
confinement period, this study still examines whether the timing of visits matters by
developing a measure, as described later, that weights visits on the basis of when they
occurred during an offender’s term of imprisonment. Third, by examining twice the number

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of inmate-visitor relationship categories (16 vs. 8) than the recent studies on prisoners from
Florida and Canada, several types of relationships are identified hat have a significant
association with recidivism. Fourth, a more robust assessment of the effects of visitation on
recidivism is obtained by tracking a larger sample of offenders, on average, for nearly five
years following their release from prison, which is substantially longer than the two-year
follow-up period used in the Florida and Canada studies. Finally, whereas the Derzken et al.
(2009) study defined recidivism as 1) reincarceration for a new offense and 2) any
reincarceration, prior research is extended by including a recidivism measure that focuses
specifically on returns to prison for “technical violations.” Determining whether visitation
reduces the risk of a technical violation revocation is important considering that the average
revocation costs the State of Minnesota roughly $9,000 (the average LOS for a release
violator in Minnesota is five months and the marginal per diem is approximately $60).
Data and Methodology
The effects of prison visitation on recidivism were examined among 16,420 inmates
released from Minnesota prisons between 2003 and 2007. As noted above, all released
offenders in the sample were included regardless of how long they were incarcerated.
Because recidivism data were collected on these offenders through June 30, 2010, the followup period ranges from 2.5 to 6.5 years, with 4.5 being the average.
Measures
Dependent Variable
Recidivism, the outcome variable, was measured two different ways in this study. It
was operationalized as 1) a reconviction for a felony-level offense, and 2) a revocation for a
technical violation. Felony reconvictions strictly measure new criminal offenses, whereas

10

technical violation revocations represent a broader measure of rule-breaking behavior.
Offenders can have their supervision revoked for violating the conditions of their supervised
release. Because these violations can include activity that may not be criminal in nature
(e.g., use of alcohol, failing a community-based treatment program, failure to maintain agent
contact, failure to follow curfew, etc.), technical violation revocations do not necessarily
measure reoffending.
The analyses were limited to these two outcome measures due to the relatively large
number of visitation variables (five) examined. Although misdemeanor and gross
misdemeanor offenses were excluded, the analyses still capture serious instances of
reoffending (felony reconvictions) as well as less serious rule violations involving both
criminal and non-criminal behavior (technical violation revocations).
Data on felony reconvictions were obtained electronically from the Minnesota Bureau
of Criminal Apprehension (BCA), whereas technical violation revocation data were derived
from the MnDOC’s Correctional Operation Management System (COMS) database.
Consequently, a limitation with these data is that they measure only reconvictions and
revocations that took place in the State of Minnesota. Moreover, as with any recidivism
study, official criminal history data will likely underestimate the actual extent to which the
offenders examined here recidivated.
In the supervision revocation analyses, 775 offenders were excluded because they
were discharged at the time of release, leaving a total sample size of 15,645 offenders.
Because they were released to no supervision, they were not at risk for revocation.
Visitation Measures

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In examining the effects of visitation on recidivism, this study attempted to assess the
effects of any visit, the frequency of visits, and the timing of visits. Moreover, to determine
whether the size of an offender’s social support network is associated with recidivism, the
number of individual visitors an offender had was measured. As a result, visitation was
measured five different ways: 1) any visit, 2) number of individual visitors, 3) total number
of visits, 4) monthly number of visits, and 5) recent number of visits. The visitation data were
obtained from COMS.
To estimate the effects of any visitation, a dichotomous measure, any visit, was
created in which visited offenders received a value of 1 and those who were not visited were
given a value of 0. The extent of social support was assessed by measuring the total number
of individual visitors an offender had while incarcerated. To examine the frequency of
visitation, the total number of visits inmates received during their confinement was counted.
Yet, because the total number of visits is, to some extent, a function of how long an offender
is incarcerated, an additional layer of control was added for an offender’s length of stay in
prison by creating a measure, monthly number of visits, in which the total number of visits
was divided by the number of months an offender was incarcerated. For example, the
monthly number of visits for an offender visited 95 times during a 10-month incarceration
period would be 9.5.
In an effort to better measure the effects of more recent visits over the entire length of
stay in prison (as opposed to the last 12 months), a measure, Recency Score, was developed
to capture these effects. A value was first assigned to each visit an offender received on the
basis of the following formula: 1 – (Number of days between the visit date and the offender’s
release date/Number of days incarcerated). The recency value assigned to a visit therefore

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ranges from a low of 0 (not recent) to a high of 1 (very recent). An offender visited on the
first (i.e., oldest) day of his confinement would receive a recency value of 0, whereas a visit
on the last day (i.e., most recent) would garner a recency value of 1. The recency values for
each visit were then summed and divided by the number of months an offender was
incarcerated to form a Recency Score for each offender.
Inmate-Visitor Relationship
To determine whether the effects of visitation vary according to who visits inmates,
the visitation data were disaggregated into the following 16 visitor-offender relationship
categories: spouse, ex-spouse, son or daughter, mother, father, other parent or guardian,
sibling, in-law, other relative, grandparent, grandchildren, friend, clergy, mentor, other
professional, and other. For each of the 16 categories, measures were developed for any
visits, total number of visits, monthly number of visits, and recency score. These measures
are similar, therefore, to those discussed above for visitation in general except that these
pertain specifically to visits by spouses, mothers, fathers, clergy, and so on. These four
visitation measures (any visit, total number of visits, monthly number of visits, and recent
visits) were created for each visitor-offender relationship category because visits are the unit
of analysis. The individual number of visitors for each relationship category was not
measured, however, because the offender (rather than the visit) is the unit of analysis.
Independent Variables
The independent, or control, variables included in the statistical models were those
that were not only available in the COMS database but also might theoretically have an
impact on recidivism. The following lists these variables and describes how they were
created:

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Offender Sex: dichotomized as male (1) or female (0).
Offender Race: dichotomized as minority (1) or white (0).
Age at Release: the age of the offender in years at the time of release based on the date of
birth and release date.
Metro Area: a rough proxy of urban and rural Minnesota, this variable measures an
offender’s county of commitment, dichotomizing it into either metro area (1) or Greater
Minnesota (0). The seven counties in the Minneapolis/St. Paul metropolitan area include
Anoka, Carver, Dakota, Hennepin, Ramsey, Scott, and Washington. The remaining 80
counties were coded as non-metro area or Greater Minnesota counties.
Prior Supervision Failures: the number of prior revocations while under correctional
supervision (probation or supervised release).
Prior Felony Convictions: the number of prior felony convictions, excluding the
conviction(s) that resulted in the offender’s incarceration.
Admission Type: three dummy variables were created to measure prison admission type. The
three variables were new commitment (1 = new commitment, 0 = probation or release
violator), probation violator (1 = probation violator, 0 = new commitment or release
violator), and release violator (1= release violator, 0 = new commitment or probation
violator). Release violator serves as the reference in the statistical analyses.
Length of Stay (LOS): the number of months between prison admission and release dates.
Offense Type: five dummy variables were created to quantify offense type; i.e., the governing
offense at the time of release. The five variables were person offense (1 = person offense, 0
= non-person offense); property offense (1 = property offense, 0 = non-property offense);
drug offense (1 = drug offense, 0 = non-drug offense); felony driving while intoxicated

14

(DWI) offense (1 = DWI offense, 0 = non-DWI offense); and other offense (1 = other
offense, 0 = non-other offense). The person offense variable serves as the reference in the
statistical analyses.
Institutional Discipline: the number of discipline convictions received during the term of
imprisonment prior to release.
Chemical Dependency (CD) Treatment: this variable measures whether offenders had, by the
time they were released from prison, entered CD treatment (1) or were untreated (0) during
their current prison sentence.
Sex Offender Treatment: this variable measures whether offenders had, by the time they were
released from prison, entered sex offender treatment (1) or were untreated (0) during their
current prison sentence.
Type of Post-Release Supervision: five dummy variables were created to measure the level of
post-release supervision to which offenders were released. The five variables were intensive
supervised release (ISR) (1 = ISR, 0 = non-ISR); supervised release (SR) (1 = SR, 0 = nonSR); work release (1 = work release, 0 = non-work release); Challenge Incarceration
Program (CIP) (1 = CIP, 0 = non-CIP), and discharge (1 = discharge or no supervision, 0 =
released to supervision). Work release and CIP are early release programs operated by the
MnDOC. Offenders placed on work release are subject to regular supervised release, whereas
offenders who complete the institutional phase of CIP, a correctional boot camp that has been
found to be effective in reducing recidivism (Duwe and Kerschner, 2008), are placed on ISR.
Supervised release is the variable that serves as the reference in the statistical analyses.

15

Release Year: measuring the year in which offenders were first released from prison for the
instant offense, this variable is included to control for any unobserved differences between
the different release year cohorts from 2003-2007.
Supervised Release Revocations (SRRs): to control for the potential effects of technical
violation revocations on reoffending, this measure was included in the models that
specifically examined new criminal offenses (reconviction). This variable measured the
number of times an offender returned to prison as a supervised release violator (for a
technical violation) between the date of his/her release from prison and the date of his/her
first reoffense (for those who reoffended), or June 30, 2010, (the end of the follow-up
period), for those who did not reoffend.
Analysis
In analyzing recidivism, survival analysis models are preferable in that they utilize
time-dependent data, which are important in determining not only whether offenders
recidivate but also when they recidivate. As a result, this study uses a Cox regression model,
which uses both “time” and “status” variables in estimating the impact of the independent
variables on recidivism. For the analyses presented here, the “time” variable measures the
amount of time from the date of release until the date of first reconviction, technical violation
revocation, or June 30, 2010, for those who did not recidivate. The “status” variable,
meanwhile, measures whether an offender recidivated (felony reconviction or technical
violation revocation) during the period in which she/he was at risk to recidivate. In the
analyses presented below, Cox regression models were estimated for both recidivism
measures.

16

To accurately measure the total amount of time an offender was actually at risk to
reoffend (i.e., “street time”), it was necessary to account for instances in which an offender
was not at risk to recidivate following release from prison. Failure to do so would bias the
findings by artificially increasing the lengths of offenders’ at-risk periods. Accordingly, for
the felony reconviction analyses, the time offenders spent in prison as supervised release
violators was subtracted from their total at-risk period as long as it 1) preceded a felony
reconviction, or 2) occurred prior to July 1, 2010, (the end of the follow-up period) for those
who were not reconvicted.
As shown later, several of the Cox regression models contain a relatively large
number of predictors, which raises concerns about multicollinearity. To be sure, methods
such as principal components analysis (PCA) are often helpful in identifying a smaller
number of predictors that account for much of the variance observed within a larger set of
variables. PCA was not used, however, for several reasons. First, the degrees of freedom in
the analyses were sufficient due to the large sample size (N = 16,420). Second, the results
from the correlation matrix estimated, which are not shown here, indicate that while nine
correlations were above 0.50 (any sibling visit-any mother visit = 0.513; number of father
visits-number of mother visits = 0.555; monthly father visits-monthly mother visits = 0.542;
recent father visits-recent mother visits = 0.527; number of visitors-any mother visits =
0.555; number of visitors-any sibling visits = 0.610; number of visitors-any relative visits =
0.592; number of visitors-any friend visits = 0.577; and number of visitors-number of friend
visits = 0.514), none exceeded 0.610. Finally, ordinary least squares (OLS) regression
models were estimated with both outcome measures, and none of the covariates had tolerance
values below .05 or variance inflation factor (VIF) values that exceeded 20.

17

Results
As shown in Table 1, of the 16,420 inmates, 61 percent were visited at least once
during their confinement, which is higher than that reported by either Bales and Mears
(2008) (41 percent) or Derkzen et al. (2009) (46 percent). The higher visitation rate observed
here is likely due to the fact this study measured visitation over the entire incarceration
period, as opposed to the last year of confinement. The average number of visits per inmate
was 36, which amounted to nearly two visits each month. In addition, offenders were, on
average, visited by three individuals. When examining inmate-visitor relationship, the results
show that nearly half of the offenders (47 percent) were visited by a friend. Nearly one-third
of the inmates were visited by their mothers, and a little more than one-fourth were visited by
a sibling. Finally, the results show that 38 percent of the offenders were reconvicted of a
felony by the end of June 2010, whereas 42 percent had their supervision revoked for a
technical violation.
The findings from the Cox regression model presented in Table 2 show that each
measure of visitation has a statistically significant effect on the risk of reconviction. For
example, the hazard of reconviction for a felony was 13 percent lower for the visited inmates
than for those who were not visited. Each visit in prison reduced the risk of reconviction by
0.1 percent, whereas one visit per month was associated with a 0.9 percent decrease. The
findings also suggest that visits closer to an offender’s release date are more important, as
reflected by a 3.6 percent decrease in the reconviction hazard. Lastly, the results show that
the number of individual visitors had a significant effect, reducing the risk of reconviction by
3 percent for each additional visitor.

18

Table 1. Descriptive Statistics
Any Visit
M
0.610
0.080
0.010
0.190
0.310
0.160
0.050
0.260
0.070
0.180
0.070
0.010
0.470
0.020
0.010
0.000
0.010
3.070
0.910
0.470
33.833
0.520
0.910
2.590

Visitation Measure
Spouse
Ex-spouse
Son or Daughter
Mother
Father
Other Parent/Guardian
Sibling
In-law
Other Relative
Grandparent
Grandchildren
Friend
Clergy
Mentor
Other Professional
Other
Number of Individual Visitors
Male
Minority
Age at Release (years)
Metro Commit
Prior Supervision Failures
Prior Felony Convictions
Admission Type
New Commitment
0.560
Probation Violator
0.340
Sentence Length
46.421
Offense Type
Criminal Sexual Conduct
0.120
Property
0.220
Drugs
0.280
Felony DWI
0.030
Other
0.120
Institutional Discipline
4.610
Drug Treatment
0.160
Sex Offender Treatment
0.020
Supervision Type
ISR
0.200
Work Release
0.170
CIP
0.060
Discharge
0.050
Release Year
2004.81
Dependent Variables
Felony Reconviction
0.380
Technical Violation Revocation
0.420
N
16,420
ISR = Intensive Supervised Release
CIP = Challenge Incarceration Program

SD
0.487
0.266
0.115
0.393
0.463
0.367
0.227
0.439
0.259
0.382
0.252
0.114
0.499
0.131
0.100
0.061
0.091
4.249
0.292
0.499
9.821
0.500
1.158
3.243

Total Number
M
35.720
2.670
0.130
2.900
4.260
2.020
0.410
2.500
0.420
1.340
0.500
0.140
9.960
0.120
0.140
0.010
0.070

0.497
0.475
70.363
0.329
0.417
0.449
0.174
0.324
10.003
0.362
0.145
0.403
0.372
0.236
0.212
1.447
0.486
0.494

19

SD
88.044
19.576
3.037
13.195
14.023
9.401
3.379
10.701
3.051
6.736
4.122
2.991
27.427
2.021
2.179
0.287
1.652

Per Month
M
1.773
0.125
0.007
0.146
0.217
0.104
0.020
0.110
0.020
0.060
0.025
0.005
0.535
0.005
0.004
0.001
0.003

SD
3.696
0.769
0.131
0.599
0.651
0.451
0.158
0.422
0.169
0.279
0.177
0.082
1.336
0.068
0.054
0.016
0.076

Recent
M
0.449
0.061
0.004
0.074
0.109
0.053
0.010
0.057
0.010
0.032
0.013
0.003
0.274
0.003
0.003
0.000
0.002

SD
0.880
0.397
0.073
0.311
0.333
0.234
0.083
0.226
0.092
0.149
0.095
0.040
0.705
0.042
0.039
0.012
0.042

Table 2. Cox Regression Models: Impact of Visitation on Time to First Felony Reconviction
Any
Number
Per Month
Recent
Hazard
Ratio
0.869**
1.283**
1.179**
0.966**
1.187**
1.089**
1.169**

Visitation
Male
Minority
Age at Release (years)
Metro Commit
Prior Supervision Failures
Prior Felony Convictions
Admission Type
New Commitment
0.866**
Probation Violator
0.919
Sentence Length
0.998**
Offense Type
Criminal Sexual Conduct
0.708**
Property
0.989
Drugs
0.964
Felony DWI
1.370**
Other
1.064
Institutional Discipline
1.003*
Drug Treatment
0.952
Sex Offender Treatment
0.613**
Supervision Type
ISR
0.953
Work Release
0.917*
CIP
0.559**
Discharge
1.225**
Release Year
0.907**
Supervised Release Revocations 1.014
N
16,420
ISR = Intensive Supervised Release
CIP = Challenge Incarceration Program
** p < .01
* p < .05

SE
0.027
0.050
0.028
0.002
0.027
0.011
0.003

Hazard
Ratio
0.999**
1.295**
1.198**
0.966**
1.188**
1.089**
1.169**

0.053
0.052
0.000

SE
0.000
0.050
0.027
0.002
0.027
0.011
0.003

Hazard
Ratio
0.991*
1.292**
1.200**
0.967**
1.181**
1.088**
1.169**

0.853**
0.906
0.998**

0.053
0.052
0.000

0.058
0.040
0.041
0.095
0.044
0.001
0.046
0.161

0.702**
0.987
0.957
1.336**
1.061
1.003*
0.955
0.611**

0.039
0.038
0.098
0.061
0.010
0.017

0.945
0.920*
0.548**
1.238**
0.908**
1.015
16,420

0.004
0.050
0.027
0.002
0.027
0.011
0.003

Hazard
Ratio
0.964*
1.292**
1.198**
0.967**
1.183**
1.089**
1.169**

0.838**
0.896*
0.998**

0.053
0.052
0.000

0.058
0.040
0.041
0.095
0.044
0.001
0.046
0.161

0.705**
0.991
0.957
1.348**
1.058
1.003*
0.936
0.604**

0.039
0.038
0.098
0.061
0.010
0.017

0.947
0.918*
0.560**
1.241**
0.905**
1.017
16,420

20

SE

SE

Visitors

0.015
0.050
0.027
0.002
0.028
0.011
0.003

Hazard
Ratio
0.970**
1.274**
1.171**
0.965**
1.194**
1.086**
1.169**

SE
0.004
0.050
0.028
0.002
0.027
0.011
0.003

0.838**
0.896*
0.998**

0.053
0.052
0.000

0.880*
0.927
0.999**

0.053
0.052
0.000

0.058
0.040
0.041
0.095
0.044
0.001
0.046
0.161

0.706**
0.992
0.956
1.350**
1.058
1.003*
0.937
0.603**

0.058
0.040
0.041
0.095
0.044
0.001
0.046
0.161

0.701**
0.979
0.963
1.347**
1.068
1.003*
0.977
0.614**

0.058
0.040
0.041
0.095
0.044
0.001
0.047
0.161

0.039
0.038
0.098
0.061
0.010
0.017

0.947
0.918*
0.556**
1.240**
0.905**
1.017
16,420

0.039
0.038
0.098
0.061
0.010
0.017

0.949
0.926*
0.557**
1.227**
0.909**
1.009
16,420

0.039
0.038
0.098
0.061
0.010
0.017

The findings presented in Table 3 suggest that visitation has a larger effect on
technical violation revocations. Indeed, compared to unvisited inmates, the hazard of
revocation was 25 percent lower for those who were visited. Although the reduction for each
visit was the same at 0.1 percent, we see that each monthly visit reduced the risk of
revocation by 3.3 percent. Whereas more recent visits reduced the hazard of revocation by
12.5 percent, each additional visitor lowered the risk of revocation by 4.8 percent.
In Tables 4 and 5, a closer look is taken at whether the beneficial effects of visitation
varied according to the relationship between the inmate and visitor. In Table 4, any visit from
a mentor reduced the risk of reconviction by 29 percent, while a visit by clergy lowered it by
24 percent. Visits from certain family members and relatives also had an impact. The risk of
reconviction was reduced by 21 percent for at least one in-law visit, 10 percent for a sibling
visit, and 9 percent for a visit by other relatives. In addition, we see that any visit from a
friend reduced the risk by 7 percent. Friends and mentors did not have a significant impact
for the other three visitation measures, although we see that siblings, in-laws, other relatives,
and clergy each a significant effect. The findings also suggest, however, that more recent
visits from ex-spouses significantly increased the risk of reconviction.
The results in Table 5 show that, once again, visits from siblings, in-laws, and other
relatives appeared to be important in reducing the risk of revocation. In these analyses,
however, we see that visits from fathers were significantly associated with a reduced risk of
revocation for each visitation measure. In addition, visits from friends were associated with a
decreased risk of revocation for two of the visitation measures. Again, visits from ex-spouses
significantly increased the risk of recidivism for at least one visitation measure.

21

Table 3. Cox Regression Models: Impact of Visitation on Time to First Revocation
Any
Number
Per Month
Recent
Hazard
Ratio
0.751**
1.352**
1.246**
0.980**
1.146**
1.140**
1.061**

Visitation
Male
Minority
Age at Release (years)
Metro Commit
Prior Supervision Failures
Prior Felony Convictions
Admission Type
New Commitment
0.921
Probation Violator
0.928
Sentence Length
0.999**
Offense Type
Criminal Sexual Conduct
1.665**
Property
0.937
Drugs
0.796**
Felony DWI
1.374**
Other
0.884**
Institutional Discipline
1.016**
Drug Treatment
0.974
Sex Offender Treatment
0.625**
Supervision Type
ISR
1.761**
Work Release
1.971**
CIP
1.361**
Release Year
1.006
N
15,645
ISR = Intensive Supervised Release
CIP = Challenge Incarceration Program
** p < .01
* p < .05

SE
0.026
0.051
0.027
0.001
0.026
0.011
0.004

Hazard
Ratio
0.999**
1.367**
1.289**
0.981**
1.142**
1.143**
1.061**

0.052
0.050
0.000

SE
0.000
0.051
0.026
0.001
0.026
0.011
0.004

Hazard
Ratio
0.967**
1.342**
1.277**
0.981**
1.146**
1.141**
1.061**

0.890*
0.897*
0.999**

0.052
0.050
0.000

0.043
0.040
0.041
0.077
0.045
0.001
0.041
0.097

1.649**
0.931
0.784**
1.316**
0.878**
1.015**
0.973
0.619**

0.034
0.035
0.075
0.009

1.736**
1.969**
1.304**
1.008
15,645

0.004
0.051
0.026
0.001
0.026
0.011
0.004

Hazard
Ratio
0.885**
1.345**
1.274**
0.981**
1.150**
1.141**
1.061**

0.868**
0.885*
0.999**

0.052
0.050
0.000

0.043
0.040
0.041
0.077
0.045
0.001
0.041
0.097

1.656**
0.937
0.789**
1.331**
0.883**
1.015**
0.956
0.607**

0.034
0.035
0.075
0.009

1.744**
1.981**
1.348**
1.005
15,645

22

SE

Visitors
SE

0.017
0.051
0.026
0.001
0.026
0.011
0.004

Hazard
Ratio
0.952**
1.335**
1.233**
0.979**
1.157**
1.138**
1.059**

SE
0.004
0.051
0.027
0.001
0.026
0.011
0.004

0.863**
0.882**
0.999**

0.052
0.050
0.000

0.939
0.931
1.000

0.052
0.050
0.000

0.043
0.040
0.041
0.077
0.045
0.001
0.041
0.097

1.668**
0.939
0.786**
1.337**
0.880**
1.015**
0.958
0.607**

0.043
0.040
0.041
0.077
0.045
0.001
0.041
0.096

1.623**
0.916*
0.786**
1.313**
0.884**
1.016**
1.010
0.633**

0.043
0.040
0.041
0.077
0.045
0.001
0.042
0.096

0.034
0.035
0.075
0.009

1.746**
1.980**
1.320**
1.003
15,645

0.034
0.035
0.075
0.009

1.741**
2.012**
1.336**
1.010
15,645

0.033
0.035
0.075
0.009

Table 4. Cox Regression Models: Inmate-Visitor Relationship on Time to First Reconviction
Any
Number
Per Month
Recent
Hazard
Ratio
Inmate-Visitor Relationship
Spouse
0.920
Ex-spouse
1.147
Son or Daughter
1.015
Mother
1.037
Father
0.967
Other Parent/Guardian
0.979
Sibling
0.898**
In-law
0.792**
Other Relative
0.912*
Grandparent
0.999
Grandchildren
0.979
Friend
0.935*
Clergy
0.756*
Mentor
0.706*
Other Professional
1.565
Other
0.917
Male
1.262**
Minority
1.177**
Age at Release (years)
0.966**
Metro Commit
1.189**
Prior Supervision Failures
1.086**
Prior Felony Convictions
1.169**
Admission Type
New Commitment
0.882*
Probation Violator
0.931
Sentence Length
0.999**
Offense Type
Criminal Sexual Conduct
0.711**
Property
0.982
Drugs
0.964
Felony DWI
1.354**
Other
1.069
Institutional Discipline
1.003*
Drug Treatment
0.973
Sex Offender Treatment
0.623**
Supervision Type
ISR
0.951
Work Release
0.922*
CIP
0.558**
Discharge
1.228**
Release Year
0.906**
Supervised Release Revocations
1.009
N
16,420
ISR = Intensive Supervised Release
CIP = Challenge Incarceration Program
** p < .01
* p < .05

SE

Hazard
Ratio

SE

Hazard
Ratio

SE

Hazard
Ratio

SE

0.056
0.125
0.040
0.037
0.043
0.064
0.040
0.069
0.043
0.059
0.146
0.030
0.123
0.170
0.188
0.152
0.051
0.029
0.002
0.027
0.011
0.003

1.000
1.002
0.999
0.999
0.996
0.998
0.994**
0.982*
0.993*
1.006
1.002
1.000
0.950**
0.989
1.047
1.000
1.261**
1.183**
0.966**
1.191**
1.085**
1.170**

0.001
0.005
0.001
0.002
0.002
0.005
0.002
0.008
0.003
0.004
0.008
0.001
0.016
0.010
0.037
0.009
0.051
0.028
0.002
0.028
0.011
0.003

0.996
1.169
0.999
1.002
0.973
0.950
0.891**
0.737*
0.894*
1.164
0.992
1.003
0.483**
0.703
2.393
1.074
1.253**
1.193**
0.967**
1.183**
1.086**
1.171**

0.019
0.088
0.024
0.027
0.039
0.094
0.040
0.122
0.053
0.071
0.232
0.010
0.256
0.321
0.541
0.181
0.051
0.028
0.002
0.028
0.011
0.003

0.997
1.353*
0.982
1.014
0.943
0.917
0.818**
0.579*
0.816*
1.367
1.192
1.008
0.284**
0.618
2.787
1.059
1.255**
1.196**
0.967**
1.182**
1.086**
1.171**

0.035
0.155
0.045
0.052
0.071
0.176
0.072
0.225
0.098
0.128
0.413
0.019
0.458
0.440
0.755
0.314
0.051
0.028
0.002
0.028
0.011
0.003

0.053
0.052
0.000

0.862**
0.913
0.999

0.053
0.052
0.000

0.848**
0.904
0.998**

0.053
0.052
0.000

0.847**
0.904
0.998**

0.053
0.052
0.000

0.058
0.040
0.041
0.095
0.044
0.001
0.047
0.161

0.706
0.979
0.957
1.331**
1.059
1.003*
0.956
0.616**

0.058
0.040
0.041
0.095
0.044
0.001
0.047
0.161

0.707**
0.983
0.959
1.344**
1.058
1.003**
0.939
0.605**

0.058
0.040
0.041
0.095
0.044
0.001
0.046
0.161

0.706**
0.985
0.958
1.344**
1.058
1.003*
0.938
0.605**

0.058
0.040
0.041
0.095
0.044
0.001
0.046
0.161

0.039
0.038
0.098
0.061
0.010
0.017

0.947
0.921*
0.552**
1.238**
0.906**
1.012
16,420

0.039
0.038
0.098
0.061
0.010
0.017

0.947
0.919*
0.565**
1.245**
0.904**
1.014
16,420

0.039
0.038
0.098
0.061
0.010
0.017

0.947
0.919*
0.561**
1.245**
0.903**
1.014
16,420

0.039
0.038
0.098
0.061
0.010
0.017

23

Table 5. Cox Regression Models: Inmate-Visitor Relationship on Time to First Revocation
Any
Number
Per Month
Recent
Hazard
Ratio
Inmate-Visitor Relationship
Spouse
0.927
Ex-spouse
1.196
Son or Daughter
0.946
Mother
0.934
Father
0.850**
Other Parent/Guardian
0.987
Sibling
0.890**
In-law
0.806**
Other Relative
0.887**
Grandparent
1.046
Grandchildren
1.047
Friend
0.902**
Clergy
1.064
Mentor
0.898
Other Professional
1.274
Other
0.995
Male
1.343**
Minority
1.215**
Age at Release (years)
0.979**
Metro Commit
1.151**
Prior Supervision Failures
1.137**
Prior Felony Convictions
1.059**
Admission Type
New Commitment
0.943
Probation Violator
0.942
Sentence Length
0.999
Offense Type
Criminal Sexual Conduct
1.644**
Property
0.924
Drugs
0.794**
Felony DWI
1.354**
Other
0.887**
Institutional Discipline
1.016**
Drug Treatment
0.995
Sex Offender Treatment
0.637**
Supervision Type
ISR
1.757**
Work Release
2.001**
CIP
1.385**
Release Year
1.008
N
15,645
ISR = Intensive Supervised Release
CIP = Challenge Incarceration Program
** p < .01
* p < .05

SE

Hazard
Ratio

SE

Hazard
Ratio

SE

Hazard
Ratio

SE

0.052
0.109
0.038
0.035
0.041
0.059
0.037
0.061
0.040
0.054
0.126
0.029
0.099
0.127
0.182
0.141
0.051
0.027
0.001
0.026
0.011
0.004

0.999
1.007**
0.999
1.000
0.993**
0.994
0.997
0.979**
0.989**
1.002
1.003
0.999
1.004
0.991
0.997
1.001
1.361**
1.268**
0.981**
1.143**
1.142**
1.060**

0.001
0.003
0.001
0.001
0.002
0.005
0.002
0.007
0.003
0.003
0.006
0.001
0.005
0.007
0.040
0.008
0.051
0.027
0.001
0.026
0.011
0.004

0.988
1.144
0.971
0.988
0.829**
0.809*
0.891*
0.802*
0.830**
1.072
1.151
0.965**
0.958
0.887
0.745
0.967
1.335**
1.249**
0.980**
1.148**
1.140**
1.060**

0.019
0.087
0.029
0.030
0.045
0.108
0.047
0.104
0.061
0.080
0.188
0.011
0.194
0.262
0.843
0.194
0.051
0.027
0.001
0.026
0.011
0.004

0.978
1.312
0.946
0.986
0.700**
0.689
0.820*
0.698*
0.701**
1.174
1.297
0.945**
0.926
0.838
0.83
0.941
1.339**
1.254**
0.980**
1.149**
1.140**
1.060**

0.035
0.149
0.053
0.057
0.086
0.200
0.086
0.184
0.116
0.147
0.368
0.021
0.315
0.355
1.084
0.336
0.051
0.027
0.001
0.026
0.011
0.004

0.052
0.050
0.000

0.901
0.905
0.999*

0.052
0.050
0.000

0.880*
0.895*
0.999**

0.052
0.050
0.000

0.880*
0.898*
0.999**

0.052
0.050
0.000

0.043
0.040
0.041
0.077
0.045
0.001
0.042
0.097

1.650**
0.929
0.782**
1.310**
0.879**
1.015**
0.973
0.628**

0.043
0.040
0.041
0.077
0.045
0.001
0.041
0.097

1.655**
0.931
0.786**
1.327**
0.882**
1.015**
0.959
0.609**

0.043
0.040
0.041
0.077
0.045
0.001
0.041
0.097

1.658**
0.933
0.784**
1.325**
0.881**
1.015**
0.96
0.608**

0.044
0.040
0.041
0.077
0.045
0.001
0.041
0.097

0.034
0.035
0.075
0.009

1.737**
1.981**
1.320**
1.009
15,645

0.034
0.035
0.075
0.009

1.747**
1.993**
1.371**
1.005
15,645

0.034
0.035
0.075
0.009

1.746**
1.991**
1.346**
1.003
15,645

0.034
0.035
0.075
0.009

24

Overall, the findings from Tables 4 and 5 suggest that visits from siblings, in-laws, and other
relatives matter the most when it comes to reducing recidivism. Is it possible, however, that
the salutary effects of these visits are due more to the fact that offenders visited by siblings,
in-laws, and other relatives simply have broader networks of social support? To address this
issue, the same Cox regression models presented in Tables 4 and 5 were estimated, except
this time the models included the number of individual visitors as a control. The findings
from these models are presented in Table 6 but, for the sake of brevity, only the hazard ratio
results for the visitation measures are included.
The results from Table 6 show that the salutary effects of visits from fathers
(technical violation revocation), clergy (felony reconviction), and mentors (the any visit
measure for felony reconviction) were relatively unaffected by the introduction of the
number of individual visitors, which was statistically significant in all eight models, as a
control variable. In addition, ex-spouse visits was not only a significant predictor of
recidivism for the same two measures shown earlier in Tables 4 and 5, but it significantly
increased the risk of revocation for any visit. In contrast, the findings reveal that the
significant effects for sibling, in-law, other relative, and friend visits were due, in part, to the
number of individual visitors an offender had. Most notably, whereas other relative visits
significantly reduced recidivism in all eight of the models shown earlier, it had only one
significant effect in Table 6. Similarly, after controlling for the number of individual visitors,
visits from friends were no longer significant. Although three of the effects for sibling visits
were no longer significant in Table 6, sibling visits still had an impact on three of the four
measures for reoffending. Further, while two of the effects for in-law visits failed to achieve
significance in Table 6, it still had a significant effect in the other six models.

25

Table 6. Effects of Inmate-Visitor Relationship on Recidivism Controlling for Number of Individual Visitors
Any
Number
Per Month
Recent
Felony
Inmate-Visitor Relationship
Spouse
Ex-spouse
Son or Daughter
Mother
Father
Other Parent/Guardian
Sibling
In-law
Other Relative
Grandparent
Grandchildren
Friend
Clergy
Mentor
Other Professional
Other
Number of Individual Visitors
N
** p < .01
* p < .05

0.943
1.180
1.054
1.062
0.997
1.007
0.933
0.827**
0.960
1.042
1.012
0.975
0.788*
0.721*
1.616
0.958
0.977**
16,420

Revocation
0.961
1.246*
0.999
0.969
0.892**
1.026
0.945
0.864*
0.960
1.112
1.125
0.963
1.135
0.934
1.327
1.064
0.966**
15,645

Felony
1.000
1.002
1.000
1.000
0.997
1.000
0.996*
0.986*
0.995
1.007
1.001
1.001
0.953**
0.990
1.051
1.001
0.976**
16,420

Revocation
1.000
1.007**
1.000
1.002
0.995*
0.998
1.000
0.988*
0.994*
1.004
1.001
1.001
1.004
0.993
1.004
1.004
0.953**
15,645

26

Felony
1.005
1.159
1.015
1.027
0.995
1.009
0.927*
0.796*
0.948
1.199
1.044
1.017
0.514**
0.764
2.516
1.104
0.969**
16,420

Revocation
0.999
1.109
1.002
1.025
0.871**
0.886
0.973
0.879
0.921
1.126
1.205
0.987
1.036
0.974
0.821
1.016
0.958**
15,645

Felony
1.013
1.310*
1.013
1.067
0.984
1.028
0.876*
0.673*
0.909
1.438
1.331
1.036
0.317**
0.694
2.927
1.125
0.968**
16,420

Revocation
0.999
1.210
1.001
1.063
0.771**
0.822
0.965
0.829
0.869
1.270
1.470
0.988
1.022
0.951
0.893
1.035
0.956**
15,645

Conclusion
Consistent with the results from prior research, the findings reported here suggest that
prison visitation can significantly improve the transition offenders make from the institution
to the community. Any visit reduced the risk of recidivism by 13 percent for felony
reconvictions and 25 percent for technical violation revocations, which reflects the fact that
visitation generally had a greater impact on revocations. The findings further showed that
more frequent and recent visits were associated with a decreased risk of recidivism. The
results also suggest that the more sources of social support an offender has, the lower the risk
of recidivism.
While visits in general reduced recidivism, visits from some individuals were more
beneficial than others. After controlling for the number of individual visitors offenders had,
visits from in-laws significantly reduced the risk of reconviction for all four visitation
measures and revocation for two of the measures. There were several relationships that had
an impact on a specific type of recidivism. For example, the risk of reconviction was reduced
by clergy visits for all four visitation measures and by sibling visits for three of the measures.
In contrast, the risk of revocation was decreased by father visits for all four visitation
measures. Visits by mentors and other relatives, meanwhile, reduced the risk of reconviction
and revocation, respectively, for at least one visitation measure. And not all types of
visitation have a beneficial effect on recidivism, as visits from ex-spouses significantly
increased the risk of recidivism for several visitation measures.
That ex-spouse visits increased recidivism is likely due to the conflict generally
present in severed relationships, which could create instability for offenders who remain in
contact with former spouses. But why were visits from fathers, siblings, in-laws, and clergy

27

the most important in reducing recidivism, whereas visits from presumably more significant
sources such as mothers, spouses, and children had less impact? Although the data and
methodology used in this study do not permit drawing firm conclusions, it is possible to
speculate why some of these relationships appeared to be more important than others. The
different effects of visits from mothers and fathers, for example, may reflect the fact that,
compared to growing up with a single parent (usually the mother), a two-parent household is
generally a protective factor against criminal offending (Entner Wright and Younts, 2009) or,
in this case, recidivism. In offering more of a peer perspective, siblings may help offenders
remain accountable by providing them with more honest support and feedback. For those
who are married, visits with either spouses or children may be difficult because they create
more stress and are often reminders of how their incarceration is preventing them from
raising their children or helping provide for their families. In-laws, on the other hand, may be
able to provide offenders with supportive visits from family members that are generally free
of the difficulties that may accompany visits with spouses or children. Finally, considering
that clergy often receive training in helping individuals through difficult life circumstances,
they may be able to give offenders effective counsel and support.
As with prior studies on prison visitation, the main limitation with this study is that it
was unable to control for whether the results obtained were due to pre-incarceration
differences in social support. That is, the findings may simply reflect that offenders with
stronger pre-incarceration social support systems were more likely to be visited and were
more likely to have support following their release from prison. As Bales and Mears (2008)
pointed out in their study, however, the effect that timing of visitation has on recidivism does
not support the idea that a prior bond is the cause of the recidivism reduction. Moreover, this

28

study statistically controlled for factors typically associated with an increased risk of
recidivism, such as prior supervision failures and prior felonies convictions, as well as those
that have been demonstrated to decrease the risk among Minnesota prisoners, such as
participation in prison-based chemical dependency treatment (Duwe, 2010), sex offender
treatment (Duwe and Goldman, 2009), and correctional boot camp programming (Duwe and
Kerschner, 2008).
Implications for Correctional Policy and Practice
Despite this limitation, the findings suggest that prison visitation can improve
recidivism outcomes by helping offenders not only maintain social ties with both nuclear and
extended family members (especially fathers, siblings, and in-laws) while incarcerated, but
also by developing new bonds such as those with clergy or mentors. In doing so, offenders
can sustain or broaden their networks of social support, which was important in lowering
recidivism. Given the public safety benefits that appear to be associated with prison
visitation, it is reasonable to suggest that correctional systems should make efforts to promote
greater visitation while still, at the same time, ensuring that these efforts do not compromise
the safety and security of correctional staff, inmates, and visitors.
In their study on Florida prisoners, Bales and Mears (2008) suggested that prisons can
foster greater visitation by: 1) placing inmates in facilities as close to their home
communities as possible, 2) encouraging community service agencies and organizations to
visit inmates, 3) ensuring parking is available for visitors, 4) expanding visiting hours to
evenings and weekends to accommodate visitors who are employed or have to travel long
distances, 5) decreasing bureaucratic barriers to visitation, 6) increasing the cultural
sensitivity of staff members, and 7) making sure that visitation rooms are clean, comfortable,

29

and hospitable. Because most of these suggestions would entail revising visitation policies,
the cost (mainly staff time) involved with revising these policies, which would be relatively
minimal in comparison to developing, implementing, and operating a visitation program,
would likely be more than offset by the public safety benefits resulting from decreased
recidivism. Recall, for example, that release violators cost the State of Minnesota, on
average, $9,000 for every return to prison. Moreover, research has shown that criminal
offending can be even more costly to society (Cohen and Piquero, 2009). Revising visitation
policies to make them more “visitor friendly” may therefore represent a relatively low costpotentially high benefit measure that correctional systems could take to help ease the burden
of prison overcrowding and budget deficits.
While policies that are more visitor friendly would likely help increase visitation
overall, it is anticipated that these types of policy changes would not necessarily increase
visitation to a significant extent among inmates who have little or no social support.
Moreover, prison caseworkers and community supervision agents typically have high
caseloads that make it challenging to adequately address offender social support issues in
either prison or the community. To encourage the development of social bonds among
unvisited inmates, who comprised nearly 40 percent of the sample, it is suggested that
correctional systems consider allocating greater resources that are geared towards identifying
sources of social support for high-risk offenders who are less likely to be visited. In
particular, it is proposed that the implementation of visitation programming, including the
addition of staff, could be an effective strategy to increase visitation among unvisited
inmates. Because many offenders have burned bridges with loved ones by the time they
reach prison, facilitating visits from friends and family may not be an option. Yet,

30

considering the impact visits from clergy and, to a lesser extent, mentors appear to have on
reoffending, it may be beneficial for visitation programs to focus on facilitating visits from
clergy, mentors, and other volunteers from the community.
To be sure, developing and implementing a visitation program would exact a greater
cost in comparison to policy revisions, but the potential public safety benefits resulting from
the identification of social support for unvisited inmates could be substantial. In addition to
increasing visitation among low social support inmates, the implementation of a visitation
program would provide an opportunity to further clarify the causal relationship between
visits and recidivism. Assuming that observed differences in pre-incarceration social support
would be controlled for statistically or by research design, an evaluation could help
determine the efficacy of visitation by assessing whether a visitation program 1) increased
visits and 2) decreased recidivism for inmate participants.
Future studies on prison visitation should also examine more closely the factors that
affect whether and to what extent prisoners receive visits. In particular, research should
determine the degree to which visitation is influenced by the physical distance between the
facility where an offender is incarcerated and the location(s) where friends and family
members reside. Although the proximity of friends and family is seldom an influential
criterion in determining the facility at which to place an offender, at least in Minnesota,
perhaps it should receive greater consideration in the event there is a significant association
between visitation and the distances sources of social support must travel to visit inmates.
Research suggests that correctional programming tends to be more effective when
there is a continuum of care, or service delivery, from the institution to the community.
Indeed, evaluations of drug treatment (Inciardi, Martin, and Butzin, 2004), employment

31

programming (Duwe, in press), and reentry programming in general (Duwe, 2011) have
shown that connecting programming delivered in the community to that provided in prison
produces better recidivism outcomes. Similarly, to strengthen the salutary effects of prison
visitation, it is suggested that efforts should also be made in the community to help to
preserve the social ties that were established or maintained in prison. Conceptualizing prison
visitation as part of a broader continuum of social support from the institution to the
community would likely require greater collaboration between institutional caseworkers,
community supervision agents, and community service agencies. Again, however, the public
safety benefits resulting from increased social support for offenders—both in the institution
and the community—would likely outweigh the costs involved to bring about systemic
change.

32

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37

 

 

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