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Vera Institute of Justice - Closing the Distance The Impact of Video Visits in Washington State Prisons, 2017

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August 2017

Closing the Distance
The Impact of Video Visits in Washington State Prisons
Léon Digard, Jessi LaChance, and Jennifer Hill

This study was supported by Award Number 2012-IJ-CX-0035, awarded by the National Institute of Justice, Office of
Justice Programs, U.S. Department of Justice. The opinions, findings, and conclusions or recommendations expressed
in this publication are those of the authors and do not necessarily reflect those of the U.S. Department of Justice.

From the Director
Research has shown that continued connection to
family and friends is a critical factor in incarcerated
people’s successful post-prison outcomes. Because many
prisons around the country are in remote locations,
far from the communities where the majority of
incarcerated people live, in-person visits present ofteninsurmountable logistical and financial challenges. For
corrections officials looking to keep those in prison
in touch with those in the community, video visiting
offers a new route. Given its ability to bridge physical
separation, this technology lends itself to addressing the
difficulties incarcerated people and their loved ones in
the community face to keep in touch.
In 2016, the Vera Institute of Justice (Vera) published a
national study of state corrections systems’ adoption of
video telephony as a way to visit incarcerated people.
The study found that many state prison systems
were weary of adopting video visiting, given security
concerns and implementation costs. One early adopter
of the technology was the Washington State Department
of Corrections, which introduced video visiting using
computers in its prisons in 2014.
The current study examines the impact of video visiting
in Washington on incarcerated people’s in-prison
behavior and analyzes their experience of the service.
The principle finding was that using the service had a
positive impact on the number of in-person visits the
video visit users received. In at least one significant
sense, the findings follow what we know about the
digital divide: Younger people tended to adopt the new
technology more than older people. And video visit
users also had the most in-person visits both before
and after introduction of the service, suggesting that

those with strong social bonds tend to sustain them
in as many ways as possible. Vera’s researchers found
no significant correlation between video visiting and
people’s in-prison behavior, as measured by the number
of infractions they committed during the period under
study.
Overall, the analysis drew a sobering big picture:
Nearly half of the people in Washington’s prisons do
not have visitors of any kind. And those who do don’t
have many. One factor was constant across sub-groups:
The distance from home had a negative effect on
visiting. Travel is expensive and time-consuming; video
calls, while cheaper, cost more than a lot of people
can spend and are rife with technical glitches. Those
who used the service despite its costs and limitations
told poignant stories of its benefits: the opportunity
for parents and children to bond; the possibility for
people in prison to show their families and friends that
they are doing well; the chance to talk in a setting less
stressful than a prison.
Given the importance of sustained human ties for
people reentering the community from prison, it
behooves corrections officials and policymakers to
devote ongoing attention to promoting successful
family and community ties while reducing the factors
that strain these vital connections.

Fred Patrick
Director, Center on Sentencing and Corrections
Vera Institute of Justice

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Vera Institute of Justice

Contents
4	Introduction
6	Methodology
9	The use of video visits and their impact on
in-person visiting rates
12	

The video visit experience

15	

In-prison behavior and video visits

16	

In-person visits in Washington State prisons

21	Conclusion
22	Appendices
31	Endnotes

Closing the Distance: The Impact of Video Visits in Washington State Prisons

3

Introduction

O

f the many difficulties incarcerated people face, losing contact
with loved ones may be among the most damaging. Research
has shown that maintaining community ties can improve their
health and well-being, decrease their sense of isolation, reduce symptoms
of anxiety and stress, and improve their feelings of control and involvement
in family life.1 Furthermore, research suggests that receiving any visit at
all during incarceration reduces the risk of someone committing a new
offense or violating conditions of parole when they are released.2 Thus, visits
with loved ones form a lifeline to the outside world for incarcerated people
and help pave the way back into society. As the number of visits a person
receives increases, so do their chances of success in the community.3

One of the most significant barriers
to prison visits may be the long distances
visitors generally have to travel
to the facilities where their loved
ones are incarcerated.
Despite the value of in-person visits, people in prison receive few. A
survey conducted in 2003 and 2004 by the federal Bureau of Justice Statistics
(BJS) showed that in any given month, nearly 70 percent of incarcerated
people in state prisons had no visitors.4 There are many reasons why loved
ones do not or cannot visit incarcerated people, including the financial
strain (such as the cost of travel, missed workdays, and childcare); rules and
regulations governing visits (such as ID requirements, limited visiting hours,
and background checks); and the anxiety-producing experience of enduring
metal detectors and personal searches.5 One of the most significant barriers
to prison visits may be the long distances visitors generally have to travel to
the facilities where their loved ones are incarcerated. According to the same
survey by BJS, approximately 63 percent of state prison inmates were held
over 100 miles from their residence at arrest.6

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More recently, departments of corrections have been turning to
computer-based video technology to try to ameliorate the burden of
those distances and create opportunities for families to stay in touch
with incarcerated loved ones. However, opinions about the value of video
visiting to date are mixed. Some corrections professionals and advocates
for incarcerated people have expressed concern that the technology may
replace in-person visits—an outcome that could have negative impacts on
both incarcerated people and their loved ones in the community.7 In many
local jail systems, those fears have been realized: they have eliminated inperson visits in favor of on-site video links.8
In 2016, the Vera Institute of Justice (Vera) reported on the availability of
video visitation in state prisons, and the process and cost of implementing
the system by one recent adopter: the Washington Department of Corrections
(WADOC).9 Vera’s research showed that, at the time of implementation in
2014, Washington was one of 15 state corrections agencies deploying this
technology. WADOC reported that it did not intend video visits to replace
in-person visits, and hoped that, by enabling more sustained contact between
incarcerated people and their loved ones, the introduction of video visits
might even increase in-person visit rates. Video calls to people incarcerated
in Washington State prisons are made by pre-approved visitors using a home
computer or public terminals set up in the community. (At the time of the
study, video calls were not available via smartphones or tablets.)
A private vendor, JPay, provides the service. Washington’s decision
to provide video visits to increase contact opportunities for incarcerated
people seemed prudent in its attempt to address the needs of a
geographically dispersed population: 50 percent of respondents to a survey
Vera conducted of people incarcerated in Washington State prisons in 2014
were in facilities at least 129 miles from their home communities.10
Since the publication of that survey’s findings, Vera’s researchers have
been studying the use of video visits in Washington State prisons to
understand whether it is successfully providing a means for incarcerated
people to contact loved ones more regularly, and whether its use has
affected the number of in-person visits that they receive. Below, Vera
presents the findings of this recent study.
First, the study sought to assess who received video visits and how
frequently. Next, researchers assessed whether participating in video
visits affected in-person visit rates, and whether it affected incarcerated
people’s in-prison behavior. Interviews with incarcerated people about
the experience and perceived benefits and challenges of the video visit

Closing the Distance: The Impact of Video Visits in Washington State Prisons

5

system supplemented the data analyses. Last, to contextualize the findings
of the evaluation and to identify the unmet visitation needs of incarcerated
people, the study looked at the prevalence and frequency of in-person
visits across the system. While previous studies have noted that distance
from home may inhibit in-person visits, Vera sought to identify the specific
nature of the relationship between being housed far from home and
incarcerated people’s ability to maintain contact with their loved ones.11

Methodology
Vera set out to answer the following research questions using the
methods and sources outlined below. (A detailed description of the study’s
methodology can be found in Appendix A.)

Did video visit use affect in-person
visit rates?
To understand who received video visits in Washington State prisons, and
how often they received them, Vera researchers analyzed administrative
data from both WADOC and JPay. WADOC introduced video visits in its
prisons gradually throughout 2013. Vera researchers identified the date on
which video visitation was first made available to each incarcerated person,
from a full dataset that included people incarcerated for any length of time
between January 1, 2012, and November 30, 2015. To estimate the impact
of using the video visit service, Vera researchers compared pre- and postvideo visit implementation outcomes of service users and nonusers. For
the analysis, the researchers chose all 9,217 people who were in WADOC
custody for at least one year prior to and at least one year following service
implementation. From this sample, the researchers identified 1,058 users of
the video visit service. Under the assumption that people who rarely used
the service were unlikely to be affected by it, the researchers identified a
group of 459 very low users—people averaging fewer than 1.5 video visits
per year during the study period—and removed them from the analysis.
They also identified a group of high users, comprising those who were
in the 90th percentile of service use, each receiving an average of nine or

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more video visits per year. This resulted in a total sample of 8,758 people,
divided into three groups: 8,159 nonusers; 488 users; and 111 high users.
The researchers compared nonusers, users, and high users of the
service to identify demographic differences between the groups; Vera then
used two statistical methods to estimate the impact of participating in
video visits on subsequent in-person visits, while controlling for those
differences—Inverse Probability of Treatment Weighting, with Difference
in Differences tests (IPTW/DID) and Bayesian Additive Regression
Trees (BART). Using two methods allows the researchers to have greater
confidence in the findings when the results of the analyses agree. The first
method, IPTW/DID, reweighted the control group so that it looked like the
treatment group, and then compared changes in in-person visits over time
between the groups. The second method, BART, capitalizes on a machinelearning-based approach to adjust for the sample characteristics. The BART
analysis allowed the researchers to predict, for each person who had
video visits, how many in-person visits they would have received if they
had not participated in the program. See Appendix A for a more detailed
description of these methods and the variables controlled for.

What were the strengths and weaknesses
of the video visit experience?
To better understand how users of the video visit system experienced the
service, Vera conducted interviews with 20 incarcerated people who had
used the service within the previous month. The participants (10 men
and 10 women) were asked open-ended questions about their satisfaction
with the service, why they chose video visits, and their perceptions of the
benefits and challenges associated with using the system.

Did video visits affect users’ in-prison
behavior?
Using the same sample and methods used to determine the impact of
video visits on service-users’ in-person visit rates, Vera researchers
conducted analyses to determine whether using the service affected
in-prison behavior. Researchers compared the groups to identify any
significant changes between the periods of time before and after video

Closing the Distance: The Impact of Video Visits in Washington State Prisons

7

visits were introduced in the overall number of infractions of prison rules
service users committed, the number of serious infractions (as defined by
WADOC policy), or the number of general infractions they committed. To
supplement these analyses, they drew upon the experiences of incarcerated
people, as reflected in the 20 interviews described above.

How frequently did people have in-person
visits?
To understand how often people in Washington State prisons received
in-person visits and determine the extent to which long distances from
home created a barrier to such visits, Vera analyzed administrative data
from WADOC about all people who were incarcerated during a one-year
period (11,524 people incarcerated from November 30, 2014 to November
30, 2015). The data included demographic information, home ZIP Codes,
and information on in-person visits. Vera analyzed the data to describe
demographic variation in visit rates and conducted statistical analyses to
identify the relationship between being incarcerated far from home and
in-person visit rates.

Video visitation in Washington State prisons
People incarcerated in Washington State prisons can make
video visits in addition to their standard phone-call allowance,
which varies by their security level. A video visit takes place
at a kiosk installed in a housing-unit day room. Depending on
the prison’s security level, the kiosks may look like computer
monitors, with a webcam and a headset for the person to
speak into and listen to his or her visitor. The visit, which an
approved visitor must schedule in advance, lasts 30 minutes
at a cost to the person who is incarcerated of $12.95. For
an additional $12.95, participants can extend the visit to an
hour at the time of the call if no one else has reserved the
kiosk for that time slot. While the hours during which people
can access kiosks vary by prison facility, some visits take
place as late as 10 p.m., substantially expanding the time for
families to connect beyond in-person visiting hours. The visitor

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Vera Institute of Justice

participates in the visit using any computer with Internet
access and a webcam. The vendor records all video visits,
which the WADOC staff can review following completion of the
visit. Corrections staff can also opt to monitor the visits in real
time, and can end a call immediately if they witness prohibited
behaviors or interactions, such as gang signs or nudity.
The first video visitation pilot began in February 2013 at the
Washington Corrections Center for Women. By June 2014, all
12 of the state’s adult prison facilities offered video visitation.
JPay, a private vendor that also provides prison services
such as e-mail, music, and commissary accounts, operates
the video visitation program. Securus Technologies, a large
criminal-justice technology and prison telecommunications
company, acquired JPay in July 2015.

The use of video visits and their
impact on in-person visiting rates
Video visit rates
Overall use rates were low. In Vera’s sample, 11.5 percent of incarcerated
people (1,058) participated in at least one video visit. On average, people
who used video visits had 3.6 video calls per year. However, a substantial
proportion of this group could be considered very low users; the researchers
averaged each person’s video visits over the time the option was available to
them and found that 43 percent (459) of people who tried the service made
fewer than 1.5 video visits per year. Of Vera’s total sample (N=9,217), only
6.5 percent (599) could therefore be considered regular users of the service.
Possible reasons for the low usage rate are described below. The 459 verylow users were dropped from the impact analysis.

User demographics
The researchers observed some notable differences between nonusers,
users, and high users.12

Table 1

Demographics
Nonusers (n=8,159)

Users
(n=488)

High users (n=111)

34 years

28 years

27 years

Black

19%

39%

43%

Member of a security threat
group (a gang)

29%

54%

56%

Average age when admitted

Closing the Distance: The Impact of Video Visits in Washington State Prisons

9

As Table 1 shows, users of the video visit service tended to be slightly
younger than nonusers when they were admitted to custody for their current
sentence (though all groups had, on average, been in custody for similar lengths
of time—seven years—at the time of the study). It is possible that younger people
are more familiar with the technology and have greater experience and ease
connecting to people through video. It is also possible that people incarcerated
at a younger age are leaving behind stronger or larger social networks. Users and
very high users of the system were slightly less likely to have used mental health
services (14 percent and 12 percent, versus 28 percent of nonusers), were less
likely to be white and more likely to be black, and were more likely to have been
identified as belonging to a security threat group (a gang).
There were also clear differences in the sample members’ incarceration
experiences in the year prior to the introduction of video visits. (See Table
2.) Users of the service were moved between facilities more often and held,
on average, further from home than nonusers. It is noteworthy that, despite
these challenges, during the year prior to implementation, service users
already received more in-person visits from more visitors. In the year before
implementation of video visits, nonusers had an average of seven in-person
visits per year, while moderate users received over double this rate of visits,
averaging 15.6, and high users had an average of 19 visits. From the data available,
the researchers were unable to determine the cause of these differences. It is
possible that financial capacity accounted for the relationship between in-person
visit rates and subsequent video visit use—that is, family members who could
afford the cost of the video service were also better able to handle the expense of
traveling to their loved one’s facility. The higher rate of in-person visits may also
Table 2

Pre-exposure variables
Nonusers (n=8,159)

Users
(n=488)

High users (n=111)

5.3

6.6

7.8

128.3

149.4

160.6

Average number of in-person
visits per year

7.0

15.6

19.3

Average number of in-person
visitors per year

12.4

26.8

31.6

Average number of
facility moves
Weighted average distance from
home (miles)

Note: “Average number of visits” refers to the number of visit “events” that a person experienced, regardless of how many visitors were present at the
same time. A “person visit” means that the same person is counted each time he or she visits during the year.

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Table 3

Pre-exposure conduct
Nonusers (n=8,159)

Users
(n=488)

High users (n=111)

Average number of general
infractions (all)

1.9

2.1

2.0

Average number of serious
infractions

0.8

0.8

0.8

Average number of segregation
infractions

0.4

0.4

0.5

indicate that users of the video service had stronger relationships with people
in the community before video visits were introduced. (See “The effect of video
visits on in-person visiting rates” below for more information.)
There were few meaningful differences in the average number
of infractions committed by people during the year prior to service
implementation. The average number of infractions, serious infractions, and
infractions that resulted in a segregation sanction (commonly known as
“solitary confinement”) were low for all subgroups (see Table 3, above).

The effect of video visits on in-person
visiting rates
Vera researchers conducted two analyses to determine whether engaging
in video visits affected the number of in-person visits incarcerated people
received. They used two analytic techniques to control for the differences
between users and nonusers and to allow for an apples-to-apples
comparison. In both analyses, users and high users of the video service
saw a significant increase in the number of in-person visits they received
following implementation of the service, as compared to nonusers. The
IPTW/DID analyses show that use of the service resulted in a 40 percent
increase in the number of in-person visits, while very high use resulted
in a 49 percent increase. The results of the BART analysis were similar
(finding a 48 percent increase for users and a 49 percent increase for
very high users). For both users and high users, these findings held true
regardless of how far from home people were incarcerated. (See Appendix
B for the results of the IPTW/DID and BART.)

Closing the Distance: The Impact of Video Visits in Washington State Prisons

11

The video visit experience

T

o help understand the results of the data analyses, Vera interviewed
20 people (10 men and 10 women) incarcerated in Washington State
prisons who had used the video service within the previous month. The
information the interviewees provided illuminates how the system benefited
users and what mechanisms might explain the increase in in-person visits
Vera identified. The interviewees stressed the system’s technical challenges
and costs, which may account, at least in part, for the low use rates.13

Seeing and connecting
While Vera’s data analysis suggested that users of the video visit service
were already better connected to the community than nonusers, there was
still a high level of need among this group for more contact with loved ones.
Video visits helped ameliorate this need. Interviewees spoke expansively of
the video service’s benefits, and 18 of the 20 participants reported that they
would continue to use it. Video visits allowed users to connect with people
who would otherwise struggle to make an in-person visit because of the
distance. Participants noted long travel times, gas and hotel expenses, loss
of earnings, and child-care requirements as significant barriers to in-person
contact. Loved ones with limited mobility or in poor health faced additional
challenges to in-person visits. Indeed, one participant who was incarcerated
far from home reported that, prior to his first video visit, he had not had any
form of visit for 19 years.
While most interviewees preferred in-person visits to video calls, they
still found the opportunity for greater contact with loved ones to be highly
meaningful. Video visits allowed incarcerated parents to participate in and
connect to their children’s lives. One mother said that her young daughter
had not recognized her at the start of in-person visits for the first few years
of her incarceration. The more consistent visual contact made possible
through video visits helped to relieve the estrangement: “Now she does
[recognize me] and writes more and talks on the phone more.” Incarcerated
parents felt that opportunities to stay actively involved in their children’s
lives were mutually beneficial. As another woman said, “This would be
harder for both of us without [video visits]. I get to see my little monsters

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Video visits provided loved ones
with visual reassurance that they were
physically and emotionally well—something
phone calls and letters could not do.
grow.” Another participant reported that, through video visits, he could
counsel and support his son, who was struggling with drug addiction.
Interviewees said that video visits were a more comfortable mode of
communication for young children than phone calls. A father explained that
his young daughter, who struggled to talk over the phone, had started asking
questions about his prison sentence: “It’s easier to answer her questions
face-to-face—to look at her when I’m talking to her.” Via video, he said, his
daughter played while they talked and showed her father her room, toys,
and drawings: “I get to see her grow.” Similarly, participants noted that video
visits provided loved ones with visual reassurance that they were physically
and emotionally well—something phone calls and letters could not do.

Video visits built a foundation for
in-person visits
Interviewees described video visits as providing a space to reconnect with
loved ones that was free from many of the pressures and stresses of in-person
visiting. They described in-person visits as highly important, but also as an
emotionally difficult experience—especially for young children, who had to
endure long travel times and who may have been overwhelmed by the noise
and stress of the prison environment. The relative ease of video visits removed
some of these pressures. A male interviewee said that he found in-person
visits with his family to be “very emotional because they’re all nice people,”
while he considered himself to be “the bad apple.” He went on to say, “I like
that video visits aren’t like that—there’s not enough time to go into that. It’s all
laughs and giggles.” Video visits provided a less pressured medium through
which people could relax in each other’s virtual company. As one interviewee
explained, “Having the opportunity to video visit can make the first in-person
visit less awkward, particularly for women like me who’ve been separated

Closing the Distance: The Impact of Video Visits in Washington State Prisons

13

from their kids for a long time.” Video visits created a safe space for people to
strengthen their bonds before moving on to in-person visits.
Additionally, for loved ones in the community who were uncertain
about visiting an incarcerated person, video visits may have been a
medium for the incarcerated person to demonstrate why they should visit.
One man said that through participation in cognitive-behavioral group
therapy while in custody, he had developed as a person since he last saw
his family. Video visits allowed him to communicate this to them. “Contact
is important,” he concluded. “I try to let people know that I’ve changed.”

Users faced significant technical
challenges
Through its 2014 survey of people incarcerated in Washington State’s
prisons, Vera identified high levels of dissatisfaction with both the cost
and quality of the video visiting system.14 While the interviews described
here happened a year after the survey, most participants reported frequent
problems with their video visits’ picture and sound quality. Twelve of the
20 interviewees said they had experienced occasional or frequent problems
with the picture quality: Sometimes the image would flash, sometimes it
would freeze, and sometimes there would be no picture at all. Seventeen
participants reported poor audio quality, with voice delays making it
difficult to have a natural conversation. Interviewees said that if they lost
the connection entirely, they could usually get credit toward another visit.
These technical problems were a source of great frustration and upset
for the interviewed incarcerated people and their families, potentially
undermining the positive aspects of the service. As one interviewee
recounted, “When it didn’t work, my husband told me that my son was
sitting outside in the yard, totally crushed.” Another explained that, “When
I talk to my younger kids, sometimes they think I’m mad because I’m not
saying anything, but it’s because I can’t hear.”
The interviewees expressed dissatisfaction with the service cost,
especially given the problems with its quality. As one person said, “For what
we’re actually getting, it’s ridiculous.” Nine of the 20 interviewees said that
they would use the service more if it were more affordable. Nevertheless,
another person concluded, “It seems pretty expensive, but it’s all we’ve got.”

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In-prison behavior
and video visits

W

hile research has demonstrated the positive impact of inperson visits on post-release recidivism rates, fewer studies
have questioned whether in-person visits similarly influence
incarcerated people’s behavior while in custody. One recent study of people
incarcerated in Florida state prisons showed mixed results, including
short-lived and quickly reversed decreases in infraction rates associated
with the anticipation of a visit.15
Using the same methodology described above to identify the impact
of video-visit use on in-person visit rates, Vera researchers sought to
determine whether video visits affected the number of infractions people
in the sample committed. The researchers conducted BART and IPTW/
DID analyses to determine whether regular users of the service exhibited a
change in the number of infractions they committed, the number of serious
infractions they committed (as defined by WADOC policy), or the number of
general, non-serious infractions during the year following the video service’s
implementation. Neither analysis found any significant impact of video
visiting on any of the outcomes. It should be noted, however, that infraction
rates were already very low for all groups prior to implementation.
Infraction rates are a narrow and limited metric with which to assess
people’s conduct; they do not capture increases in positive behavior.
However, the interviews with incarcerated people suggest that video visits
may have some positive impacts. One interviewee explained, “[Video
visiting] makes you reconnect with society… Even though it’s only a
video, it makes you remember there’s something outside of here.” Other
interviewees suggested that these glimpses into life outside of the prison,
into the daily lives and homes of their loved ones, motivated them to
improve their lives; as one participant stated, video visiting “supports my
positive change, it reminds me why I’m trying to be a better person… even
though I’ve got life without parole, there is still a chance for me.”
Yet some participants cautioned that frustrations with video service
glitches could worsen people’s behavior. As one interviewee said, “When
you’re incarcerated and you expect something and don’t get it, it can be really
bad. If you let it get to you, you can end up back in [solitary confinement].”

Closing the Distance: The Impact of Video Visits in Washington State Prisons

15

Additional research can help to clarify the positive or negative effects
of both video and in-person visits on video service users’ in-prison
behavior. Vera’s analysis shows, as the findings below reveal, that during
the study period both video visit and in-person visit rates were low
throughout Washington’s prison system. Furthermore, visit rates varied
by the demographic characteristics of the people who were incarcerated.
Because staying connected with supportive people in the community
fosters good post-prison outcomes, the disparate visit rates for various
groups in the Washington prison population merit further scrutiny.

In-person visits in
Washington State prisons

V

era’s analysis established that participating in video visits increased
the number of in-person visits that incarcerated people received,
but also showed that only a small proportion of the prison
population used the service. To give context to these findings, Vera
analyzed the statewide prevalence and frequency of in-person visits in the
year following the implementation of the video visit service.
The analysis of WADOC administrative data revealed that nearly half
(45 percent) of incarcerated people did not receive in-person visits during
the year ending November 2015. As described below, visit rates varied:
Women and people under 45 were more likely to receive visits than men
and older incarcerated people. For all groups, however, the further people
were held from their homes, the fewer visits they received.16

In-person visits, from few to none
Nearly 45 percent of people incarcerated in Washington State’s prisons had
no visits during the year-long study period. Of those who had in-person
visits, the average number per person was between eight and nine. As
Figure 1 shows, over 13 percent of the sample received one to two inperson visits, 11 percent received three to five, and 18 percent received
more than 12 in-person visits during this one-year period.

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Figure 1

Number of in-person visits received between
November 30, 2014 and November 30, 2015

> 12 visits
18%

10-12
visits
4%

0 visits
45%

6-9 visits
8%
3-5 visits
11%
1-2 visits
14%

n = 11,524

Demographic disparities in visit rates
Vera analyzed the demographics of people who received in-person visits
during the study period. The findings below show that many of the people
who were least likely to receive video visits—such as older people or those
with mental health needs—were also less likely to receive in-person visits,
meaning the service was not benefiting those who needed it the most.

Women had more in-person visits than men
While 54 percent of men in the sample received visits during the year, 74
percent of the women had visits. Consistent with national trends, women
received more visits on average than men—12.5 per year compared to 8.3.17
Vera’s analysis found that women received more visits than men independent
of the distance they were held from their homes. However, Washington
State’s two women’s prisons are located near Seattle and Tacoma—the state’s
largest and third-largest cities, respectively—making them more accessible
than the more remote male facilities. Factors such as the availability of public
transport or direct routes to the facilities may correlate with the number of
visits people receive, in addition to physical proximity.

Closing the Distance: The Impact of Video Visits in Washington State Prisons

17

Figure 2

Average number of in-person visits by gender and race
14

Female

14

Male

10
9.5
Number of visits

8.6

7.8

8.4

7
6.5

0
Black

Hispanic

Native American

White

n = 11,524

There were racial disparities in visiting rates
among women
White women, on average, received about 14 in-person visits throughout
the year, while black women received 9.5, and Hispanic women received
approximately seven in-person visits. This disproportionate pattern was
less pronounced for men.

Younger people received more in-person visits
The average number of in-person visits decreased among people over the
age of 45.18 People in age groups under 45 received an average of between
nine and 10 in-person visits; however, those over 45 received six in-person
visits on average. (See Figure 3.)

People with mental health disorders received fewer visits
On average, people living with mental health disorders received six inperson visits during the year, compared to members of the general prison
population who did not have a diagnosed disorder, who received between
nine and 10 visits on average.19

18

Vera Institute of Justice

Figure 3

Average number of in-person visits by age
10
9.3

9.2

10

5.9

6

46-55

56+

0
25 and under

26-35

36-45

n = 11,524

Visit rates were higher for people who had been
incarcerated for long sentences
Researchers found a slight upward trend in the number of visits that
people received in relation to the length of time that they had been
incarcerated. Those in the first year of their sentence received an average
of eight in-person visits, while those who had already served 10 or more
years received an average of 10 in-person visits a year. (See Figure 4.)

People received fewer visits the further they were
incarcerated from their homes
Vera found that, in Washington State, the mean distance from home for
incarcerated people was nearly 130 miles (median = 113 miles)—about a twohour car ride. Because Vera researchers calculated distance using straightline measurements (or “as the crow flies”), actual distances by road and the
associated travel times are greater. Further, for people without access to a
car who rely on public transportation, with the constraints of timetables and
fixed routes, traveling this distance would likely take even longer.

Closing the Distance: The Impact of Video Visits in Washington State Prisons

19

Figure 4

Average number of in-person visits by length of incarcertion
10
10

9
8.3

8.5

7.5

0
0-1 year

1-3 years

3-5 years

5-10 years

10+ years

n = 11,524

Vera researchers created a model that would test the significance of the
relationship between in-person visits and individual-level characteristics,
including distance from home, gender, race, age, mental health status,
and length of incarceration. Each of these variables was found to be
significantly correlated to the number of visits people received (p<0.001).
The model is presented in Appendix C.
The model shows that the number of in-person visits people received
decreased by about 1 percent for every additional mile in distance from
home they were incarcerated. For men, all else being equal, the predicted
average number of visits for someone held 58 miles from home is eight per
year; for men held 184 miles from home, this number drops to three, and at
327 miles from home the model predicts 1.5 visits per year.
Gender differences in visiting rates remained even when controlling for
distance from home, with women being more likely than men to receive visits.
Consistent with the descriptive statistics presented above, the model also
found that, for every year increase in a person’s age, the rate of in-person visits
decreases by about 2 percent. However, there was a 2 percent increase in the
number of visits received for every year a person had been incarcerated.

20

Vera Institute of Justice

Conclusion

S

taying connected to loved ones outside of prison is important to the
well-being and success of incarcerated people in leading safe and
crime-free lives after release. Video visits provide another avenue for
incarcerated people to reconnect with family and friends. Vera’s analysis
shows that use of the service may strengthen people’s relationships to those
on the outside, as demonstrated by a subsequent increase in the number of
in-person visits they received. However, only a small portion of incarcerated
people used the service during the period under study, and even those who
did reported that the service’s cost limited their use. Although the $12.95 fee
is less than the cost of a long-distance trip, the calls are short and the sound
and video quality are often poor. Furthermore, $12.95 is a significant sum for
incarcerated people, who may rely on friends and family to send them money
to supplement the small amounts they can earn in prison-based jobs.
In-person visit rates were low across the state, and the small proportion
of incarcerated people who used video visits on a regular basis indicated that
the service alone cannot be relied on to increase contact with their loved
ones. Further, Vera’s analysis of in-person visits shows that some of the very
groups within the prison population who may be most in need of additional
support from family and friends, such as older people and those with mental
illness, received both the fewest in-person visits and the fewest video visits.
It does not appear that video visits themselves can reverse disparities in
outside support for some of the most vulnerable people in prison.
While research has demonstrated that in-person visits can benefit
incarcerated people, their families, and the wider community by increasing
well-being and decreasing recidivism, structural factors in U.S. corrections
systems impede efforts to encourage this connection. Throughout most
of the country, people convicted of crimes wind up incarcerated in
facilities in remote locations. The fact that typically people are held at
great distances from their home communities continues to be a significant
barrier to meaningful contact. Although video visits contribute to easing
the separation, it would be far preferable if corrections departments
nationwide eliminated this factor entirely. Housing people in their custody
in facilities that are close to, and accessible from, their home communities
could go a long way toward supporting people during their incarceration
and as they reenter society and seek to build stable, connected lives.
Closing the Distance: The Impact of Video Visits in Washington State Prisons

21

Appendix A

Methodology
Vera analyzed administrative datasets from WADOC and

The first analytic method used inverse probability of

JPay and conducted interviews with incarcerated people.

treatment weighting/difference in differences (IPTW/

Vera first looked to see how often people had video
visits and who took part in them. Vera also conducted
analyses to determine whether participation in video
visits affected users’ in-person visit rates or the number
of disciplinary infractions they received. To do so, the
researchers analyzed administrative data from WADOC
and JPay on all people who passed through WADOC’s
custody between January 1, 2012 and November 30, 2015,
including people’s disciplinary records, in-person visit
records, and (from JPay) the dates and times of
video visits.

DID), which reweights the control group so that it looks
like the treatment group. The first step is to estimate the
propensity score, or conditional probability that a given
person was treated (that is, received the given level of
video visiting) conditional on their observed covariates.
Then, everyone in the treatment group was given a
weight of 1, while everyone in the comparison group was
given a weight equal to e(x)/ (1 - e(x)), where e(x) is the
estimated propensity score. The treatment group was
compared to the reweighted control group to see whether
the two groups were sufficiently similar, or balanced, with
respect to the confounding covariates. If balance was not

Researchers identified the date on which each person was
first exposed to video visiting—that is, the date on which
it was first introduced to the facility in which they were
housed. To conduct a pre- and post-exposure test, Vera
selected a sample of people who had been in custody for at
least one year prior to their first exposure and at least one
year afterward. From an original dataset of 42,049 people,
this criterion produced a study sample of 9,217.
To estimate the effect of the treatment (video calls) on the
treated (those who used the system), researchers used
two different methods, described below. When the two
methods produced the same result, the researchers could
have greater confidence in the findings. The outcome
measures for both analyses were 1) the average number
of in-person visits per year, 2) the average number of
infractions per year, 3) the average number of general
infractions per year, and 4) the average number of serious
infractions per year. Both methods assume that the
researchers have measured all the covariates that act as
confounders—that is, those variables that are predictive of
both using the video visiting program and are predictive of
the outcomes (infractions and in-person visits).

sufficiently close, the propensity score model was tweaked
until the reweighting yielded adequate balance.20 After
adequate balance was achieved for a given treatment
variable, a regression analysis was performed on the
reweighted sample for each outcome of interest where the
response variable in each case was the difference between
the pre-treatment version of the outcome and postimplementation of the variable. This differencing over time,
combined with the differencing across treatment (exposed)
and comparison (not exposed) groups yields a differencein-differences estimate of the estimand.
Results of the IPTW/DID analysis were compared with
the findings of the second method, Bayesian additive
regression trees (BART).21 This method capitalizes on
a machine-learning-based approach to adjust for the
covariates. The idea is to fit a very flexible model for
the outcomes given the confounders that allows the
researchers to predict, for each person who participated
in the video visiting program what would have happened
to them (regarding infractions and in-person visits) if
they had not used the service. Comparing the average
predicted outcome for everyone in the treatment and
control groups allows the researchers to obtain an
unbiased estimate of the treatment effect.

22

Vera Institute of Justice

In both approaches, the researchers controlled for

Vera researchers visited two WADOC prison facilities in

the potential impact of the following variables on the

December 2015 and conducted semi-structured interviews

outcome measures:

with 20 incarcerated people (10 men and 10 women)
about their experiences of in-person visits and the video

>> race;

visiting system. Participants were selected at random

>> gender;

from a list of people who had used the service within the

>> age;

previous month. Researchers conducted the interviews

>> whether this was the person’s first admission to
prison;
>> mental health needs;
>> gang membership;
>> weighted average distance from home;
>> number of readmissions to custody during the study
period;

in a private room without corrections staff. Everyone
approached for interviews agreed to participate.
Next, Vera investigated the frequency of in-person visits,
and sought to understand the factors associated with
the number of visits that people received. To do so, Vera
analyzed individual-level data from WADOC. The data
referred to a one-year cohort (November 30, 2014 to
November 30, 2015) and consisted of the 11,524 people who

>> number of facility moves in the year prior to
implementation;
>> number of visits and visitors prior to implementation;
>> number of infractions and infractions resulting in
segregation prior to implementation; and
>> length of time in custody prior to implementation.
The figures on page 22 show the standardized differences
for the covariates used in propensity score matching
before and after weighting. Seventeen covariates were
included for the service user treatment group (left) and
16 covariates were included for the high user group
(right). Balance was easier to achieve for the user group
than for the high user group. Researchers prioritized
achieving balance on weighted average distance in the
pre-exposure period (weighted_avg_dist_pre) and the
number of visits in the pre-exposure period (nvisits_preS).
The results of the IPTW/DID regression and BART are presented in Appendix B.
To aid in the interpretation of the quantitative analysis,

were incarcerated in WADOC facilities for the entire period.
Of this sample, 94.4 percent (10,883 people) were men and
5.6 percent (641 people) were women.22 The majority of the
population (63.5 percent) was white, while black people
made up 19.5 percent of the population, Hispanic people
made up 7.7 percent, Native Americans made up 4.2 percent,
and other minority groups made up 5 percent.
The data Vera received included demographic and
incarceration information, home ZIP Codes, and
information on in-person visits (including the dates and
the number of visitors). For each person in the dataset,
Vera calculated the distance between their prison
facility and their home. To approximate this value, Vera
calculated the direct distance between the central point
of the ZIP Code of their prison facility and the central
point of their home ZIP Code (as recorded on admission
to custody). Where home ZIP Codes were unavailable
(n=4,368), the research team used the ZIP Code of their
county of commitment. Ninety people in the cohort
had neither ZIP Code and were thus excluded from the
analysis. Incarcerated people are often moved between
different facilities, meaning they may be held at multiple

Closing the Distance: The Impact of Video Visits in Washington State Prisons

23

Figure 5

Differences in covariates before and after matching

Black
White
Released
First admission
Mental health needs
Gang membership
Male
Weighted average distance from home before video visits
Multiple admissions to prison
Facility transfers before video visits
Unique visitors before video visits
In-person visits before video visits
Disciplinary segregation sentence before video visits
Serious infractions before video visits
Total infractions before video visits
Incarceration days before video visits
Age at admission

Black
White
Released
First admission
Mental health needs
Gang membership
Male
Weighted average distance from home before video visits
Multiple admissions to prison
Facility transfers before video visits
In-person visits before video visits
Disciplinary segregation sentence before video visits
Serious infractions before video visits
Total infractions before video visits
Incarceration days before video visits
Age at admission

24

Vera Institute of Justice

distances from home during a year. To account for this,
Vera created an average weighted distance from home.
This adjusted the distance from home for each person,
depending on the length of time they spent in each
facility during the year. To do so, researchers used the
following formula:

Average weighted distance = (d1*t1) + (d2*t2)…
365
Where d1 = the distance (in miles) between a person’s
first facility and their home, and t1 = the number of days
they were held at that facility during the year period.
Distance and time at their second facility are marked
as d2 and t2, and so on. The resultant figures represent
a straight-line distance between prison and home. Vera
conducted regression analyses to determine the degree
to which different individual-level factors were associated
with the number of in-person visits each incarcerated
person received. Vera researchers used a negative
binomial model, a type of generalized linear model that
allows for discrete distribution (a count of the number of
visits received), restricts predicted values to non-negative
values, and accounts for the variance of the outcome
variable that is higher than the mean. An omnibus
test compared the model against a model without
any predictors and showed that it was a significant
improvement (p<.01).23 Full detail of the model can be
found in Appendix C.

Closing the Distance: The Impact of Video Visits in Washington State Prisons

25

Appendix B

BART and IPTW/DID results
The results for the video visit user group are presented

treatment resulted in a 40 percent increase in the number

in Table 4. Both BART and IPTW/DID regression show a

of in-person visits per year. The corresponding confidence

statistically significant positive treatment effect on the

interval is (1.15, 1.71). Based on the BART results, using the

number of in-person visits. Since the outcomes are logged,

video visit service results in a 47 percent increase in in-

the treatment effect estimates must be exponentiated

person visits per year, with confidence interval (1.37, 1.58).

to have a meaningful interpretation. A treatment effect

Using the service did not have any effect on infractions

estimate of 0.34 means that the treatment increased in-

regardless of method.

person visits by a factor of e

0.34

= 1.4. In other words, the

Table 4

Estimates of the effect of using video visitation on in-person visits and infractions
Outcome/method

Linear regression

IPTW regression

BART

Rate of in-person visits

0.19 (0.09)
[0.02, 0.36]

0.34 (0.10)
[0.14, 0.54]

0.39 (.04)
[0.32, 0.46]

Number of all infractions

-.01 (0.03)
[-.07, 0.06]

0.01 (0.03)
[-0.06. 0.07]

-0.00 (0.03)
[-0.05, 0.06]

Number of general infractions

0.00 (0.02)
[-0.05, 0.05]

0.01 (.03)
[-0.04, 0.06]

-0.02 (0.08)
[-0.17, 0.14]

Number of serious infractions

-.02 (0.03)
[-.07, 0.3]

-0.02 (0.03)
[-0.07, 0.03]

-0.05 (0.06)
[-0.17,0.07]

Note: Each cell displays the treatment effect estimate along with the standard error in parentheses and a 95 percent confidence interval in square
brackets. The results are on a log scale.

26

Vera Institute of Justice

Table 5 presents results for the high user group. Based
on IPTW/DID regression and BART, the treatment resulted
in 50 percent more in-person visits, with confidence
intervals of (1.03, 2.16) and (1.31, 1.72), respectively. For
both IPTW/DID regression and BART, the effect of the
high treatment was not statistically distinguishable from
zero for any of the infraction outcomes.

Table 5

Estimates of how the high use of video visitation affected in-person visits and infractions
Outcome/method

Number of in-person visits

Number of all infractions

Number of general infractions

Number of serious infractions

Linear regression

IPTW regression

BART

0.21 (0.18)

0.40 (0.19)

0.40 (0.07)

[-0.13, 0.56]

[0.03, 0.77]

[0.27, 0.54]

-0.01 (0.07)

-0.01 (0.06)

-0.01 (0.03)

[-0.14, 0.13]

[-0.12, 0.11]

[-0.60, 0.43]

0.01 (0.05)

0.02 (0.05)

-0.04 (0.05)

[-0.09, 0.12]

[-0.07, 0.11]

[-0.09, 0.10]

-0.05 (0.05)

-0.05 (0.05)

-0.05 (0.04)

[-0.15, 0.05]

[-0.15, 0.04]

[-0.13, 0.05]

Note: Each cell displays the treatment effect estimate along with the standard error in parentheses and a 95 percent confidence interval in square
brackets. The results are on a log scale.

Closing the Distance: The Impact of Video Visits in Washington State Prisons

27

Appendix C

Regression analysis
Vera conducted a negative binomial regression analysis to
estimate how distance from home, gender, race/ethnicity,

mental health status, age, and length of time spent in
prison relate to the number of visits received in a year.24

Table 6

Categorical variable information
Factor

N

Percent

10,785

94.4%

1,561

.000%

Asian/Pacific Islander

436

3.8%

Black

2,231

19.5%

Hispanic

882

7.7%

Native American

483

4.2%

White

7,247

63.4%

Other

146

1.3%

No

8,385

73.4%

Yes

3,040

26.6%

Gender

Male

Female

Race/ethnicity

Mental health needs

Note: Vera created a dummy variable where anyone with a mental health treatment code (PULSHES) of 2 or higher was considered to have mental
health needs and those with codes 0 or 1 were considered to have no mental health needs.

28

Vera Institute of Justice

Table 7

Continuous variable information
Minimum

Maximum

Mean

Standard
deviation

0

205

8.49

19.159

Age

15

96

39.29

12.336

Weighted average distance from
home (miles)

0

2,792

129.53

141.655

Length of incarceration (years)

0

67.85

5.729

7.171

Variable

Dependent variable

Number of visits

Covariates

Table 8

Omnibus test
Likelihood ratio chi-square

Df

Significance

4,245.82

11

.000

Closing the Distance: The Impact of Video Visits in Washington State Prisons

29

Table 9

Parameter estimates
95% Wald confidence interval

Hypothesis test

Parameter

Exp(B)

Lower

Upper

Significance

Intercept

23.669

21.654

25.873

.000

Weighted average distance

.991

.991

.992

.000

Weighted average distance squared

1.0

1.0

1.0

.000

1.431

1.312

1.561

.000

Asian/Pacific Islander

.808

.728

.897

.000

Black

.879

.834

.927

.000

Hispanic

.744

.688

.804

.000

Native American

.810

.732

.896

.000

Other

.865

.725

1.032

.108

1.576

1.504

1.652

.000

Age

.981

.979

.983

.000

Length of incarceration

1.02

1.016

1.023

.000

Gender (ref=male)

Female

Race (reference=white)

Mental health need (reference=yes)

No

Dependent variable: Number of visits per year

30

Vera Institute of Justice

Endnotes
1	John D. Wooldredge, “Inmate experiences and psychological wellbeing,” Criminal Justice and Behavior 26, 2 (1999): 235-250.
2	Grant Duwe and Valerie Clark, “Blessed be the social tie that bind
them: The effects of prison visitation on offender recidivism,” Criminal
Justice Policy Review 24, 3 (2011): 271-296.

14	Digard, diZerega, Yaroni, and Rinaldi, 2016.
15	Sonja E. Siennick, Daniel P. Mears, and William D. Bales, “Here and
gone: Anticipation and separation effects of prison visits on inmate
infractions,” Journal of Research in Crime and Delinquency 50, 3
(2013): 417-444.

3	William D. Bales and Daniel P. Mears, “Inmate social ties and the
transition to society: Does visitation reduce recidivism?” The Journal
of Research in Crime and Delinquency 45, 3 (2008): 287-321.

16	Exp(B)=0.991, p<0.001.

4	United States Department of Justice, Office of Justice Programs,
Bureau of Justice Statistics, “Survey of Inmates in State and Federal
Correctional Facilities, 2004, State Numeric Data.” Analysis ran on
2017/01/24 using SDA 3.5: Tables.

18	The average age of incarcerated people in Vera’s sample was 39
years (median = 37). Although most people were between the ages
of 26 and 45, nearly 30 percent of incarcerated people were over the
age of 45.

5	Megan L. Comfort, “In the tube at San Quentin: The ‘secondary
prisonization’ of women visiting inmates,” Journal of Contemporary
Ethnography 32 (2003); 77-107.

19	People were identified as having a mental health need in the data if
they were assigned a mental health code of 2 or higher. “A primary
therapist (a mental health provider responsible for coordinating
the offender’s mental health care) is assigned prior to arrival at the
facility for each offender with a PULHES “S” code of 2 or higher.”
(Mental Health Services, DOC 630.500).

6	Survey of Inmates in State and Federal Correctional Facilities, 2004,
State Numeric Data. Analysis ran on 2017/01/24 using SDA 3.5: Tables.
7	Allison Hollihan and Michelle Portlock, Video Visiting in Corrections:
Benefits, Limitations, and Implementation Considerations (New York,
NY: Osborne Association, 2014).
8	Bernadette Rabuy and Peter Wagner, Screening Out Family Time: The
for-profit video visitation industry in prisons and jails (Northampton,
MA: Prison Policy Initiative, 2015).
9	Léon Digard, Margaret diZerega, Allon Yaroni, and Josh Rinaldi, A
New Role for Technology? Implementing video visitation in prison
(New York: Vera Institute of Justice, 2016).
10	Ibid.
11	Johnna Christian, “Riding the bus: Barriers to prison visitation and
family management strategies,” Journal of Contemporary Criminal
Justice 21, 1 (2005): 31-48; Hollihan and Portlock, 2014.
12	Differences between the three sample groups were controlled for when
testing for the effect of service use. See Appendix A, Figure 4, for more
details of the covariates before and after matching.
13	The interviews supported and added detail to the findings of Vera’s
previous survey of people who are incarcerated in WADOC (Digard,
diZerega, Yaroni, and Rinaldi, 2016).

17	For national trends, see Bureau of Justice Statistics, 2004.

20	Guido W. Imbens, “Nonparametric estimation of average treatment
effects under exogeneity: A review,” Review of Economics and
Statistics 86, 1 (2004): 4-29; Tobias Kurth et al., “Results of
multivariable logistic regression, propensity adjustment, and
propensity-based weighting under conditions of non-uniform effect,”
Practice of Epidemiology 163, 3 (2006): 262-270.
21	Hugh A. Chipman, Edward I. George, and Robert E. McCullouch,
“BART: Bayesian additive regression trees,” Annals of Applied
Statistics 4, 1 (2010): 266-298.
22	This is roughly consistent with the snapshot population breakdown
on September 30, 2016. Men made up 92 percent of the population
and women made up 8 percent. See http://www.doc.wa.gov/docs/
publications/16-282-FC1.pdf.
23	This tests whether the model explains the variance in visits within
the dataset better than the baseline model (a model without any
predictors).
24	Data were used for all people held in WADOC custody for the entire
year period ending November 2015.

Closing the Distance: The Impact of Video Visits in Washington State Prisons

31

Acknowledgments
The authors would like to thank Dana Weisenfeld, Jacob Kang-Brown, and
Allison Hastings for their invaluable support in the collection and analysis
of data. We are grateful to Eric Martin and Cathy Girouard at the National
Institute of Justice for their support throughout the development of this report.
We would also like to thank Margaret diZerega, Christian Henrichson, and
Ram Subramanian for their help in drafting and reviewing the report. Thanks
to Alice Chasan for her expert editing, Carl Ferrero for the design, and Karina
Schroeder for proofreading. We would also like to thank Devon Schrum and
the staff of the Washington Department of Corrections for their assistance in
making this research possible.

About Citations
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Credits
© Vera Institute of Justice 2017. All rights reserved. An electronic version of this report is posted on
Vera’s website at http://www.vera.org/video-visitation-in-prison-Washington-State.
Cover image © B.O’Kane / Alamy Stock Photo
The Vera Institute of Justice is a justice reform change agent. Vera produces ideas, analysis, and
research that inspire change in the systems people rely upon for safety and justice, and works in
close partnership with government and civic leaders to implement it. Vera is currently pursuing
core priorities of ending the misuse of jails, transforming conditions of confinement, and ensuring
that justice systems more effectively serve America’s increasingly diverse communities. For more
information, visit www.vera.org.
For more information about this report, contact Ram Subramanian, editorial director, at
rsubramanian@vera.org. For more information on video visitation, contact Léon Digard, senior
research associate, Center on Sentencing and Corrections, at ldigard@vera.org.

Suggested Citation
Léon Digard, Jessi LaChance, and Jennifer Hill. Closing the Distance: The impact of video visits in
Washington state prisons. New York: Vera Institute of Justice, 2017.

32

Vera Institute of Justice

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