712481
research-article2017

TPJXXX10.1177/0032885517712481The Prison Journalvan Wormer et al.

ArticleDigging Deeper:
Exploring the Valueof Prison-Based Dog
Handler Programs

The Prison Journal
﻿1­–19© 2017 SAGE Publications
Reprints and permissions:sagepub.com/journalsPermissions.nav
https://doi.org/10.1177/0032885517712481
DOI: 10.1177/0032885517712481
journals.sagepub.com/home/tpj

Jacqueline van Wormer1, Alex Kigerl1,
and Zachary Hamilton1

Abstract
As U.S. correctional systems continue to rollout evidence-based programs, theutility of “complimentary” programs that do not address recidivism reduction
remains in question. Many U.S. prisons have a variety of prison-based animal
programs, yet the outcomes are largely unexplored. This research addresses
a literature gap by evaluating the intermediate outcomes associated witha statewide prison-based dog handler program. Using propensity scorematching, we compared 1,001 inmates in a pretest, postentry design, aimed
at measuring change across four outcomes. Results indicate that dog handler
program inmates experienced significant improvement in three of four areas.
Implications and further research needs are explored.
Keywords
prison, prison-based animal programs, intermediate outcomes, propensity
score matching

Introduction
As part of the Washington State Department of Corrections (WADOC)
Sustainability in Prisons Project, the majority of Washington prisons offer a
1Washington State University, Spokane, WA, USA

Corresponding Author:
Jacqueline van Wormer, Institute for Criminal Justice, Washington State University,
701 Johnson Tower, Pullman, WA 99163, USA.
Email: jvanwormer@wsu.edu

2

The Prison Journal 00(0)dog training and/or adoption program. The programs aim to build offenderaccountability and skills, while providing a needed service to the community.
The program, along with other sustainable programs such as horticulture andendangered species restoration programs, are considered “complimentary”
programs to an array of evidence-based-offender-change programming
efforts that have recently been adopted under legislative mandate. Program
operations vary by facility, but include training and developing service dogs
to assist those with disabilities (Cedar Creek, Monroe, Mission Creek, andWashington Corrections Center), as well as working with troubled dogs to
make them adoption ready. The dog adoption program is available in six malefacilities across the state.
Washington prisons are not alone in their use of prison-based animal programs (PAPs). Furst (2006) identified 71 different programs operating in 36
U.S. states, although the types of programs vary and include dog handler
programs, equine programs, general livestock management and even domestic cat programs. Despite the prolific use of these programs, very little is
known about the impact of programs on offender behavior while in the institution, or if positive effects do exist, whether they extend beyond the prison
walls in the form of recidivism reduction. Research to date has been limitedby small sample sizes, reliance on internal file data reviews and anecdotal
stories, and the use of surveys to measure inmate and staff perceptions of thevarious programs (Bachi, 2013; Furst, 2006).
The purpose of this outcome evaluation is to determine whether WADOC
inmates that participate in the various dog handling programs experience
fewer infractions, less grievances, and improved behavior across the facilities. Using record data of 1,001 inmates in a matched treatment and control
group design, this research aims to address the question of whether operationof the dog programs creates a safer and healthier prison environment among
the participant inmates, as compared with those inmates who do not participate in the program.

Literature Review
The idea of creating and operating prison-based animal training and companion programs originates from the medical field where animal-assisted therapy(AAT) programs are widely utilized to address a myriad of health issues suchas depression, abuse, and aging disorders (Furst, 2006). The use of the AAT
is considered therapeutic, and, in some cases, is even used as part of a clinicaltechnique. Animals are known to have a calming effect, and it is not uncommon to see dogs and cats in nursing homes, hospitals, and, increasingly, inplaces of work and even elementary schools (as visiting pets).

van Wormer et al.

3

In the prison environment, the introduction and training of animals (primarily dogs) is generally not offered as a therapeutic milieu, but rather as acommunity service and a program to assist prisoners with social reintegration(Mulcahy & McLaughlin, 2013). Commonly referred to as PAPs, such efforts
are generally concentrated around dog training/handling programs, taming ofwild horses, farm animals, and even domestic cats.
Furst (2006) and Bachi (2013) maintained that through the eyes of correctional administrators, PAPs serve multiple purposes. It is believed that PAPs
provide some level of rehabilitation function for inmates; some programs generate revenue for the prison (e.g., the taming and eventual sale of horses).
Furthermore, the programs build ties to the community, inmates learn a valuable vocational skill, and such programs may lead to healthier prison environments (Deaton, 2005). Although not developed as a therapeutic intervention,
early results of PAPs, most often collected through survey results or directly
through researcher observation, revealed an increase in offender self-esteem,
displays of greater patience and compassion, and increased levels of responsibility and even autonomy (Cushing &Williams, 1995; Harbolt & Ward, 1991).
It is important to note that PAPs are not a new or trendy correctional programming effort. Strimple (2003) traced dog-based programs and interventions
back to 1919 in an eastern state prison. In her national survey of state correctional administrators, Furst (2006) found that the first documented PAP program (livestock care) began in Wisconsin in 1885, with several other programs
built throughout the early 1900s. The strong surge in PAPs took hold over the
past few decades with 48 programs established since 1990 (Furst, 2006). The
proliferation of the programs can be contributed to multiple factors, including
the relative inexpensive nature of the programs and the highlighting of suchprograms on cable television (Animal Planet). It can even be argued that the
PAP movement began in earnest in Washington state, when Kathy Quinn and
Dr. Leo Bustad (of the Washington State University Veterinary School) begana dog training program at the Washington Corrections Center for Women(WCCW) in Gig Harbor, Washington, in the 1980s (Strimple, 2003). Although
the stories were anecdotal, female inmates reported experiencing stronger selfesteem and learned marketable skills. Quinn and Bustad expanded the program
across 17 different institutions based on the results at WCCW.
Although recent research has found that many state correctional facilities
offer PAPs, outcomes of these programs have rarely been measured, and those
programs that have been evaluated tend to rely more heavily on qualitative
methods (Furst, 2006). A recent review of the relevant outcome literature on
PAPs found only 19 studies that completed quantitative and/or mixed methods
approaches to evaluate program outcomes. The research designs on all projects varied considerably, and suffered from small sample sizes, lack of

4

The Prison Journal 00(0)comparison groups, and questionable methodological designs (Bachi, 2013;
Mulcahy & McLaughlin, 2013). Of the evaluations of PAPs that have been
completed, outcome measures can generally be grouped into the following:measuring recidivism (five studies), measuring changes in disciplinary behaviors (five studies), emotional/psychological effects (14 studies), and sociobehavioral effects (11 studies) (Bachi, 2013; Mulcahy & McLaughlin, 2013).
Studies of the impact of participation in PAP’s on prison-based disciplinary
behaviors, such as infractions and grievances, have been minimal and hampered by small study sizes and limited controls. For example, Fournier, Geller,
and Fortney (2007) found a statistically significant reduction in institutional
fractions for the dog handlers (treatment) versus a control group, but with alimited sample of 48 males. The number of institutional infractions as a baserate was very low, and both groups improved from baseline to postprogram.
Other research efforts focused on measuring changes in disciplinary
behaviors have been mixed, and have lacked official record data to draw solid
conclusions. Analysis of two separate dog programs conducted by Furst(2007) of both males (n = 14) and females (n = 15) did not include official
record data, and, instead, provided testimonials by prison administration officials who reported only anecdotal assessments of program success.
One of the earliest evaluations of a PAP was conducted by Moneymaker andStrimple (1991), and included measuring behavioral change in 98 male inmatesin a pet-keeping/vocational training program. In this study, the researchers wereconcerned with levels of participation, rates of termination from the program,work release participation, and self-reported indicators such as abstinence fromdrugs and alcohol. Although the authors found high levels of participation andlow levels of parole violations, the findings must be interpreted with caution, as
no comparison group was utilized and data collection methods were not reported.
Bachi (2013) argued that given the methodologically weak research completed in this area, coupled with the fact that programs continue to expand,“studies should be replicated with larger sample sizes to further clarify theeffects of PAPs on rates of disciplinary misconduct” (p. 60). This researchseeks to address a gap in the literature by conducting an evaluation of the
WADOC dog handler program participants against a matched comparisongroup (n = 1,001) across four core behavior domains. To the best of our knowledge, this is the largest study to date on the intermediate effects of PAPs.

WDOC Dog Handler Program
The WADOC is responsible for an average of 16,000 inmates across 12 prisonsthroughout Washington. Under legislative and administration directive, the
WADOC embarked on an aggressive agenda to build evidence-based programs

van Wormer et al.

5and practices throughout the prison and community settings and to utilize outside evaluators to not only guide the reform process but to measure program
outcomes as well. Throughout this effort, the WADOC has maintained thateven in light of the evidence-based practices push, there is a role and purpose
for what they consider “complimentary programs.” One such example is the(WADOC) Sustainability in Prisons Project that allows inmates to participate
in science and nature programs in the prison environment (http://sustainabilityinprisons.org), through partnerships with volunteers and local universities.
Through this program, inmates have the opportunity to participate in a range ofprograms, including green prisons, raising endangered species (frogs and butterflies), propagating rare native plants, and dog training/adoption programs.
At this time, the majority of Washington prisons offer a dog training and/or adoption program. The dog programs aim to build offender accountability
and skills, while providing a needed service to the community. The purposeof the program is not therapeutic in nature. In other words, the assignment ofa dog to an inmate is not intended to have therapeutic benefit, but rather provide inmate-targeted training, grooming, and general care of animal. Program
operations vary by facility, but include training and developing service dogs
to assist those with disabilities (Cedar Creek, Monroe, Mission Creek, andWashington Corrections Center), as well as working with troubled dogs to
make them adoption ready. For purposes of this study, we included both theservice dog and adoption programs in our analyses.
Inmates must complete an application to be part of either program. To be eligible, an inmate must have been major infraction-free (violent, serious) for theprior 6 months to application and have had no Class A infraction in the prior 2
years. Class A infractions include crimes that would be considered serious criminal acts, or felonies. Inmate applicants are subject to medical, mental health, andsex offender screening processes to ensure goodness of fit for the program.
Once selected for the program, inmates work with volunteer dog trainers
from the community who come into the various facilities to teach basic introductory skills such as leash handling, sit/down/stay commands, bail out
moves, proper feeding/grooming, and dog interaction and observation behaviors. All dog handlers are assigned reading materials (e.g., “Don’t Shoot theDog”) and attend classroom-based trainings, completing 20 separate modules. Topics vary from understanding breeds, to dog attention seeking,aggression toward other dogs, and how a dog learns. The inmates maintainjournals and inventory sheets as well, and receive US$45 a month once they
have passed all their skills and knowledge testing. More seasoned dog handlers can obtain “mentor” status at a rate of US$50 per month. Mentors mustalso be major infraction-free, have successfully trained and supervised atleast three dogs, and pass a knowledge/skills test.

6

The Prison Journal 00(0)In 2013, Administrators from the WADOC initiated contact with the
Washington State University Researchers at the Institute for Criminal Justice
to explore the possibility of evaluation of the dog programs. This, in part, wasdriven by need to understand whether the programs were having effects on
inmate behavior in terms of reducing general, serious, and violent infractions
among inmates, as well as grievances filed by inmates. WADOC was interested in exploring beyond the dozens of anecdotal stories that were brought
before headquarters regarding the positive and lasting impacts the program
was having on inmate behavior and self-esteem.

MethodSampling Frame
Data were acquired from the WADOC administrative database to evaluate theeffect of inmate participation in the dog handling program. According to
WADOC records, there were a total 597 participants across all facilities thatparticipated in the program since 2002. To measure the impact of program
participation, a comparison group was selected from inmates who were not in
the program, but were matched on similar preintervention characteristics.
When the “gold standard” of randomized assignment to a correctional program is not available, any and all possible efforts should be made to eliminate
selection bias. To address this, Propensity Score Modeling (PSM) was utilized tobalance the two study groups on all available measures that possess the potential
to systematically bias study findings. PSM is a statistical method that allows one
to simulate randomization by balancing the two study groups on preintervention
characteristics. The first step in identifying the comparison group was determining the mean (average) time from admission to prison and treatment start date fordog training participants. This was an average of 1,583 days. All eligible inmates,
incarcerated for at least this duration for the comparison, were selected. Key individual indicators were gathered from the Offender Needs Assessment (ONA)
interview conducted at prison admission and reassessed periodically. Inmates
who did not possess an ONA were also not eligible for study inclusion. The selection yielded a potential of 7,002 comparison group members in total.
To control for differences between the treatment and comparison groups,
inmates were matched based on their similarities with the treatment groupprior to their study entrance date. Specifically, comparison group members
who were similar to the treatment participants were selected and included in
the study, while unmatched or dissimilar cases were excluded. The match
was based on 40 variables gathered from needs assessment and demographic
data, as well as incarceration length, custody level, and preintervention, baseline measures of the outcome variables.

van Wormer et al.

7

Prior to matching, dog program participants differed from the comparisongroup pool on 30 of the 40 dimensions (75%), justifying the need for matching as there were substantial differences between the two groups. To examine
the sensitivity and specificity of the model, a receiver operating characteristics (ROC) curve was computed for the multivariate propensity score predicting treatment group assignment. The area under the curve (AUC) estimate
was .819, indicating that the model and its covariates were collectively strong
predictors of group assignment.
Using a matching caliper of .25 as a common support boundary for selecting an adequate match for each program participant, 113 of the 597 initial
participants could not be matched with a similar comparison group member,
resulting in 18.9% loss which was necessary to sufficiently match the twogroups. Following the match, there were 484 treatment group members and517 comparison group members. Postmatch, the two groups significantly differed on only two of the 40 dimensions (5%), which is the proportion anticipated to be significant based on accepted levels of chance. AUC estimates ofthe matched model were .503 (confidence interval [CI] = [.467, .539]), suggesting the included measures no longer predicted group assignment. The
results of the match are presented in Table 1.

Sensitivity Tests
Due to the loss of treatment group participants because of an adequate
match with the comparison pool, sensitivity tests were completed for the
113 dog program participants who were not selected, in contrast with the
484 retained participants. The results of the comparisons can be found in
Table 2. The retained participants differed from the dropped participantson 45% of the 40 bivariate measures, suggesting substantial differences
between the two groups.
Upon examining the measures, those dropped from the model appear to belower risk inmates than the inmates who were successfully matched. Retained
subjects are at higher custody during admission (a lower custody score/number under WADOC supervision indicates a higher security rating) and commit more serious and violent infractions. However, the dropped inmatesappear to score higher on drug-related needs items.
The finding indicates a selection bias for inclusion in the dog training
programs which results in participants who are systematically different
from the WADOC inmate population at large. It may be that inmates who
self-select into the program are simply lower risk offenders to begin with.
Therefore, their removal from subsequent models to get a better match isdesirable, and makes those retained more representative of Washington
inmates in general.

8

MeasureCustody at admission
≤37
>37
>47
Custody post intervention
≤37
>37
>47
White
Never expelled/quit school
Never employed
No problems while employed
Barriers to employment
Financial issues
Saves money
No issues
Problems managing money
No employee health insurance
Friends
Friends willing to help
Pro social friends
No friends
Unstable relationships
Antisocial friends

7.86
37.86
39.36
22.78
16.75
5.53
77.72
81.74
27.3
6.2
44.22
33.5
3.35
8.71
87.94
79.4
14.41
7.71
17.42
8.21
50.08

55.46
34.74
9.78

9.09
6.38
84.81
69.98
26.89
12.51
39.23
36.46

5.09
11.95
82.94
71.12

15.41
8.84
20.72
11.61
41.66

Dog program
%/M

9.84

18.38

<.001
.002

13

25.89
0.93
19.42
10.2
6.16

<.001
.866
<.001
.019
.161
.007

23.29

45.05

Standard
Differences

<.001

<.001

p valueχ2/t test

Before matching

92.14

Comparison%/M

Table 1. Match Results (n = 1,001).

11.22
9.09
17.99
9.67
50.68

3.29
9.09
87.62
76.79

10.44
6.19
83.37
77.56
28.43
9.48
41.01
32.88

42.55
38.88
18.57

51.65

Comparison
%/M

14.67
8.26
17.36
9.5
47.73

3.93
8.47
87.6
77.27

10.12
4.34
85.54
79.34
27.27
6.61
43.18
34.71

41.74
39.46
18.8

48.35

Dog program
%/M

.456

.915

.822

.545
.735
.122
.527
.586

.41

.966

χ2/t test
p value

After matching(continued)

8.69

1.15

1.44

4.32
2.59
10.5
4.41
3.87

3.95

1.41

Standard
Differences

9

Occupants of residence
Minor children
Lives alone
Other
MotherNo current residence
Current partner is a positive influence
Family is a positive influence
No minor children
No current contact with minor child
Alcohol problems ever
Drug problems ever
Alcohol problems in the last 6 months
Drug problems in the last 6 months
Means for supporting drug habits
None
Legal income
Illegal income
Prior treatment for drug use
Never clean during recent 6 months
Documented mental health problems
Mental health outpatient previously
Aggressive or violent behaviors in thecommunity
Aggressive or violent behaviors while
confined

Table 1. (continued)

15.91
26.97
21.61
18.09
17.42
26.97
48.58
55.28
12.56
68.01
79.9
23.45
38.36
15.08
21.44
63.48
53.94
33.67
36.18
14.41
77.89
22.95

24.58
24.65
50.77
34.98
37.39
39.73
12.07
82.79

35.13

Dog program
%/M

19.02
29.45
20.44
14.78
16.31
14.97
29.48
66.22
9.97
64.71
65.85
26.59
28.62

Comparison
%/M

25.69

39.39
7.7
7.26
7.13
12.87

<.001
.078
.097
.108
.003
<.001

26.98

32.81
41.3
23
8.58
6.91
29.86
7.13
21.38

<.001
<.001
<.001
.052
.115
<.001
.104
<.001
<.001

10.57

Standard
Differences.067

χ2/t test
p value

Before matching

27.85

15.86
24.56
59.57
51.06
34.24
34.82
13.54
81.04

17.6
25.34
19.54
17.8
19.73
23.79
45.65
59.19
10.64
67.7
78.14
20.89
34.24

Comparison
%/M

25.62

17.56
23.35
59.09
49.59
34.09
36.36
14.05
78.72

14.88
27.89
22.11
17.98
17.15
23.35
42.77
57.44
11.98
69.01
76.65
24.59
34.71

Dog program
%/M

.468

.686
1
.656
.887
.402

.742

.928
.394
.619
.567
.706
.626
.187
.927

.485

χ2/t test
p value

After matching(continued)

5.04

2.95
0.31
3.23
1.48
5.8

2.87

1.54
5.79
3.55
4.25
2.81
3.56
8.82
0.99

1.54

Standard
Differences

10

Acceptance of responsibility for behavior
Accepts responsibility
Superficially accepts responsibility
Does not accept responsibility
Needs individual living services
Total days incarcerated
Infraction rate pretest
Serious infraction rate pretest
Grievance rate pretest
Sanction rate pretest
Violent infraction rate pretest
Age at admission
Aggressive characteristics scale
Aggressive motives scale
Antisocial attitudes motive scale
Antisocial attitudes characteristics
scale
Recent impact scale

Table 1. (continued)

1.043

44.19
4.28
51.53
48.07
4,095.06
0.142
0.1192
0.167
0.159
0.013
32.108
2.182
1.586
2.091
1.870

Comparison
%/M

1.460

39.87
3.18
56.95
48.74
2,104.08
0.126
0.046
0.136
0.112
0.006
33.293
1.686
1.467
2.063
1.564

Dog program
%/M

27.02

1.34
82.37
7.05
33.9
7.94
18.84
28.68
10.63
28.68
12.22
3.33
15.03

.785
<.001
.098
<.001
.01
<.001
<.001
.008
<.001
.004
.434
<.001
<.001

9.99

Standard
Differences.029

p valueχ2/t test

Before matching

1.305

45.07
1.55
53.38
49.13
2,994.64
0.102
0.066
0.112
0.110
0.008
33.021
1.839
1.489
2.023
1.688

Comparison
%/M

1.307

42.36
3.51
54.13
49.38
2,430.39
0.121
0.056
0.148
0.117
0.007
33.272
1.764
1.473
2.039
1.626

Dog program
%/M

.983

.987
<.001
.085
.232
.018
.543
.37
.714
.466
.798
.762
.613

.116

χ2/t test
p value

After matching

.14

0.5
26.92
−10.91
7.56−15.09
−3.85
5.67
−2.32
4.61
1.62
−1.91
3.2

3.52

Standard
Differences

11

van Wormer et al.
Table 2. Sensitivity Tests (n = 597).

MeasureCustody at admission
≤37
>37
>47
Custody post intervention
≤37
>37
>47
White
Never expelled/quit school
Never employed
No problems while employed
Barriers to employment
Financial issues
Saves money
No issues
Problems managing money
No employee health insurance
Friends
Friends willing to help
Pro social friends
No friends
Unstable relationships
Antisocial friends
Occupants of residence
Minor children
Lives alone
Other
MotherNo current residence
Current partner is a positive influence
Family is a positive influence
No minor children
No current contact with minor child
Alcohol problems ever
Drug problems ever
Alcohol problems in the last 6 months
Drug problems in the last 6 months
Means for supporting drug habits
None
Legal income
Illegal income
Prior treatment for drug use
Never clean during recent 6 months

Droppedparticipants%/M

Selected
participants
%/M

18.93

81.07

21.24
38.94
39.82

χ2/t test
p valueStandard
Differences

41.74
39.46
18.8

<.001

54.3

45.13
10.62
44.25
92.04
27.43
4.42
48.67
28.32

10.12
4.34
85.54
79.34
27.27
6.61
43.18
34.71

<.001

100.71

.003
1
.515
.341
.236

32.84
0.36
9.06
11.05
13.53

0.88
9.73
89.38
88.5

3.93
8.47
87.6
77.27

.255

10.84

.012

27.73

13.27
5.31
0.88
17.7
2.65

14.67
8.26
2.48
17.36
9.5

.067

15.92

60.18
20.35
23.01
18.58
18.58
42.48
73.45
46.02
15.04
63.72
93.81
18.58
53.98

47.73
14.88
27.89
17.98
17.15
23.35
42.77
57.44
11.98
69.01
76.65
24.59
34.71

.565

1.94

<.001
<.001
.036
.468
.33
<.001
.218
<.001

43.07
61.34
22.95
9.23
11.33
42.76
14.16
39.6

4.42
13.27
82.3
72.57
31.86

17.56
23.35
59.09
49.59
34.09

<.001

48.91

<.001
.733

46.06
4.72
(continued)

12

The Prison Journal 00(0)Table 2. (continued)

Documented mental health problems
Mental health outpatient previously
Aggressive or violent behaviors in thecommunity
Aggressive or violent behaviors while
confined
Acceptance of responsibility for behavior
Accepts responsibility
Superficially accepts responsibility
Does not accept responsibility
Needs individual living services
Total days incarcerated
Infraction rate pretest
Serious infraction rate pretest
Grievance rate pretest
Sanction rate pretest
Violent infraction rate pretest
Age at admission
Aggressive characteristics scale
Aggressive motives scale
Antisocial attitudes motive scale
Antisocial attitudes characteristics scale
Recent impact scale

Droppedparticipants%/M

Selected
participants%/Mχ2/t test
p valueStandard
Differences

35.4
15.93
74.34

36.36
14.05
78.72

.933
.716
.376

2.01
5.35
10.55

11.5

25.62

.002

33.54

29.2
1.77
69.03
46.02
706.41
0.149
0.003
0.082
0.09
0
33.381
1.354
1.442
2.168
1.301
2.115

42.36
3.51
54.13
49.38
2,430.4
0.121
0.056
0.149
0.118
0.007
33.273
1.764
1.473
2.039
1.626
1.308

.015

28.92

.59
<.001
.259
<.001
.015
.101
<.001
.908
.012
.771
.129
.098
<.001

6.72
54.3
100.71
32.84
0.36
9.06
11.05
13.53
10.84
27.73
15.92
1.94
43.07

Measures
Four outcome measures were captured and analyzed to assess the impact of
the intervention. These measures, reported as rates, included the following:(a) serious infractions, (b) violent infractions, (c) grievances filed, and (d)number of sanctions imposed. Serious infractions are coded internally by the
WADOC, and tend to be infractions that are more aggressive (destroying
property, inciting riot, possession of a weapon).
Data on the above measures were collected to assess preprogram behavior,as well as postentry behavior across the four outcomes. For the comparisongroup, an enrollment date was replaced with a fixed 1,583-day follow-up. Allfour outcomes were analyzed as a rate based on exposure time before andafter the intervention date. That is, outcomes are measured as the number of
events over the number of months incarcerated after the intervention date.

Analytic Plan
Because the Washington inmates studied can reside within the same institutions,
possible dependency may exist within each facility. That is, because inmates may

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van Wormer et al.
Table 3. Serious Infraction Models (n = 1,001).
Model I
MeasureIntercept
Dog program participant
Current facility
Variance of random effects
Analysis of deviance test

Model II

B

SE

t

p

B

SE

t

p

0.072
−0.149

0.044
0.063

1.64
−2.361

.101
.018

0.047
−0.210

0.071
0.066

0.663
−3.182

.507
.002

0.037
28.74

<.001

share the same prison environment, their propensity to engage in misconduct
might be correlated due to this shared setting. If there is such clustering within
facilities without being accounted for, any treatment effect may be due to differences between the facilities, and not due to the treatment itself. To account for thispossible bias, random effects regression models were selected to test each of thefour outcome measures. For each model, the outcome is regressed on treatmentgroup member status, once with and once without a random effect parameter
included representing the categorical facility of each inmate’s residence.
In addition, because the outcome measures are operationalized as rates,
they are not sufficiently normal enough for a traditional parametric approach.
Rate measures tend to be highly skewed toward higher values, with lower
frequencies of events being more common. Outcomes are therefore rank
transformed before inclusion in each linear regression. Such transformations
are termed the rank transformation (RT) approach, and make the data amenable to a traditional linear regression model (Conover & Iman, 1981; Iman
& Conover, 1979). The final model used would be a rank regression, a typeof generalized linear model that serves as a nonparametric test.

Results
Serious Infractions
Table 3 contains the results of the two regression models assessing the impact
the dog handler program has on serious infractions following the intervention
date. Model I is a standard linear regression, whereas Model II contains an
added random effect that captures any unexplained heterogeneity due to ashared environment in each facility. The two models were compared with ananalysis of deviance goodness-of-fit test. Model II demonstrated a significant
improvement over Model I by including the random effect for the institution(χ2 = 28.74, p < .001). Model II is therefore the preferred model.
Referring to Model II, dog program participation was found to significantly and negatively predict serious infraction rates (B = −0.21, p = .002),

14

The Prison Journal 00(0)Table 4. Violent Infraction Models (n = 1,001).
Model I
MeasureIntercept
Dog program participant
Current facility
Variance of random effects
Analysis of deviance test

Model II

B

SE

t

p

B

SE

t

p

0.106
−0.219

0.044
0.063

2.421
−3.482

.016
<.001

0.094
−0.238

0.055
0.065

1.704
−3.655

.089
<.001

0.012
4.276

.039

suggesting that membership in the program is associated with fewer serious
infractions. It should also be noted that the effect size is larger in the random
effects model, suggesting that dog handler participants may be situated in
facilities with higher serious infraction rates.

Violent Infractions
Table 4 presents the violent infraction models, testing the impact treatment
had on violent infractions with and without a random effect for facility.
Analysis of deviance goodness-of-fit tests indicated that Model II was an
improvement over Model I, with inclusion of a random effect (χ2 = 4.276, p= .039). Referring to Model II, the effect of treatment participation was significant and in the same direction as that found for serious infractions (B =−0.238, p < .001). Program participation is associated with fewer violent
infractions during follow-up.

Grievances Filed
Table 5 contains the results of the number of grievances filed by inmates.
Analysis of deviance tests indicated that Model II was a significant improvement over Model I (χ2 = 15.189, p < .001). Referring to Model II, treatment
is a significant predictor of grievances (B = −0.179, p = .007). Those in the
dog handler’s program appear to file fewer grievances posttest.

Sanctions Imposed
Table 6 presents the sanctions imposed on inmates models. Model II, the random
effects model, was found to be a significant improvement over Model I (χ2 =5.889, p = .015). However, treatment participation did not significantly predict
the number of sanctions received by inmates (B = −0.099, p = .137). Although theeffect size is in the same direction as that of previous models, the effect is small.

15

van Wormer et al.
Table 5. Grievances Filed Models (n = 1,001).
Model I
MeasureIntercept
Dog program participant
Current facility
Variance of random effects
Analysis of deviance test

Model II

B

SE

t

p

B

SE

t

p

0.067
−0.139

0.044
0.063

1.536
−2.208

.125
.027

0.064
−0.179

0.066
0.066

0.964
−2.697

.336
.007

0.028
15.189<.001

Table 6. Sanctions Imposed Models (n = 1,001).
Model I
MeasureIntercept
Dog program participant
Current facility
Variance of random effects
Analysis of deviance test

Model II

B

SE

t

p

B

SE

t

p

0.032
−0.067

0.044
0.063

0.735
−1.057

.463
.291

0.025
−0.099

0.061
0.066

0.406
−1.489

.685
.137

0.02
5.889

.015

Discussion
Our findings provide strong support for the utility of the PAPs in the preventionof prison-based intermediate outcomes. Specifically, significant reductions inthree of the four outcomes examined (serious infractions, violent infractions,and grievances filed) were observed. Reductions were also identified in the
fourth outcome, sanctions imposed, but the test failed to reach significance.
Given the rigorous methods used to collect and analyze the data (i.e., PSM andrandom effects modeling), it would be difficult to argue that the provision ofthis program is anything but a promising practice; however, additional confirmation with further study testing sites will be needed to bear that out.
One argument that some might maintain diminishes the impact of ourfindings was the lack of outcomes with regard to offender recidivism. Given
the program’s intent and location, we focused on what the field refers to as“intermediate outcomes” or those not directly related to recidivism. Although
recidivism reduction and rehabilitation are common goals of prison-based
programs, these are not typically the only intent. Evidence of reducing negative/unwanted behavior is a goal of all correctional programs, and evidenceof effectiveness must not hinge on a simple assessment of recidivism alone.
Infractions, and to a lesser extent grievances, are important outcomes forinmates and correctional staff. The term intermediate outcome suggests that

16

The Prison Journal 00(0)the outcome may impact the ultimate goal, recidivism, or it may not.
However, we argue that serious and violent infractions have a cost withregard to staff and inmate safety, case management, and will often be criteria
for program prioritization for those treatments and services deemed to havea more direct influence on recidivism. Reducing serious infractions andgrievances by over 10%, as was found in this research, allows for a strong
pool of inmates to be considered for further interventions and supports post–
dog handler programming.
Furthermore, as prisons often backload offender programming (providing
interventions in the months just prior to release), programs such as PAPs canbe important provisions along the continuum of care. Although we are notsuggesting that an animal care/training program should take the place of cognitive behavioral therapy or substance abuse treatment, certainly there is aplace for evidence-based programs that are intent on improving inmate conduct and safety as a result.
In addition, prison is a difficult place to learn and not every skill can be
instructed in a classroom setting. There are many domains that are outlined
for rehabilitation which simply do not have evidence-based, prison-provided
interventions to plug in to (Wooditch, Tang, & Taxman, 2014). In addition,some established programs may be supplemented by those that focus onintermediate outcomes such as these. Skills, such as learning empathy, dealing with others, forming relationships with family and pro-social peers, aredifficult concepts to fully teach in a classroom setting. Given that a researchshows little to no evidence that incarceration (incapacitation alone) reduces
recidivism and that in some prison environments, it can actually increase thepropensity to reoffend (Cullen, Johnson, & Nagin, 2011), having programs
available that teach such skills and characteristics can no doubt provide a
counterbalance to the criminogenic effect of the prison environment. An
inmate’s time spent on training and being responsible for an animal may be
the perquisite or booster needed to enhance program effectiveness andincrease responsivity. Given the positive indicators PAPs have had on intermediate outcomes related to violence and antisocial behavior, it is hard toargue against the success achieved.
Finally, skills learned should improve offender employability. Participants
are responsible for training and maintenance of these animals. Now notevery participant will obtain employment in this specific industry, but thosein the community will be aware of what these programs offer, and an
inmate’s resume will be bolstered by the skills attained. Obviously, additional follow-up is needed in the community to identify the long-term impactof the program and whether skills learned translate into greater employment
viability.

van Wormer et al.

17

Limitations
Although relatively comprehensive in our review, there were a few notable
limitations. First, our focus was on the intermediate outcomes of infractions
and grievances. Minimal attempts to track the impact of animal care programs on recidivism (Moneymaker & Strimple, 1991) have been completed,and Mulcahy and McLaughlin (2013) argued that any new attempt at establishing a PAP within a prison should entail an extensive outcome evaluation
design from inception. This is a future goal of the project but one that was not
feasible at the time of completion. With that said, prior studies attempts to
examine the direct impact of similar programs on recidivism were fraught
with methodological and sample limitations that will be avoided in future
research. We intend to support the positive findings here through further
examinations of reconvictions and reentry employment of participants once
requisite data can be gathered.
Whenever a statistical technique like PSM is used over a more traditional
method like random assignment, it comes with limitations. The first is obviously the unobserved bias that is not accounted for through our preintervention measures. We feel the variety and compressive nature of our measures
limits the impact of this technical drawback of the PSM method. An issue ofgreater concern is with regard to the removal of nearly 150 treatment participants in which a comparison subject match was not found. What is a somewhat positive result of our sensitivity analysis is that those removed were
notably lower risk. Therefore, it would seem that their removal prevented anevaluation of the “best of the best” inmates, or what is known in the field as“creaming.” However, based on our findings, it is likely that, at least at the
selection process, there may be a bias to provide the opportunity to participate to those of lower risk. Their inadvertent removal from our analysis provides an evaluation sample that is more representative of the general
population but one might also question whether the “worst of the worst” wereallowed to participate would the same results have been obtained? If it is thecase, then our findings may not support the general use of the PAP to all levels of inmate risk. Further research is needed with higher risk populations toconfirm (or refute) this point.
To reduce the likelihood that findings were as a result of the prison facility
environment, we utilized random effects modeling. This form of multilevel
regression techniques allowed us to control for the effect of individuals being
nested within the facility they reside. The result of this technique is a sort of“general accounting” of the facility-level variance, in which the analyses do
not indicate specificities about what makes a given facility more (or less)likely to produce violations or grievances. Although not feasible for the

18

The Prison Journal 00(0)current study, future prison-based evaluations conducted using state-level
data sources should make an effort to examine predictors at the facility-levelthat may contribute to violations and/or program responsivity.

Summary and Future Directions
The intent of the dog handler programs across multiple WADOC institutions
is to build offender accountability and skills, while providing a needed service to the community. This research was not focused on the training of theoffender and skill adoption, but rather sought to address whether or not the
program created a safer environment in the prison via stronger inmate
accountability to their dogs and the institution as a whole.
As the findings above highlight, the program has clearly succeeded in building a higher level of accountability, as witnessed by the statistically significant
decreases in infractions, grievances and sanctions among the dog handlers. The
program lends to a safer and healthier prison environment in those pods andfacilities where the programs are offered, at least among this selected population. Further research should include targeting measures of psychosocial changes(via survey assessment) in participants, as well as following the treatment andcontrol group post release to measure for potential recidivism reductions.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research,authorship, and/or publication of this article.

Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.

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Author Biographies
Jacqueline van Wormer, PhD, is a senior researcher at the Institute for Criminal
Justice at Washington State University. Her research interests include corrections,risk-needs assessment, juvenile justice, and problem solving courts. Her most recent
publications have appeared in Criminal Justice & Behavior and The Journal of
Offender Rehabilitation.
Alex Kigerl, PhD, is an assistant research professor of criminal justice and criminology, Washington State University. His research interests include risk assessment
development, quantitative methods, and cybercrime, with a focus on illicit email
spam. His work has appeared in Social Science Computer Review and Justice
Quarterly.
Zachary Hamilton, PhD, is an assistant professor of criminal justice and criminology, Washington State University. His research areas include corrections, offender
reentry, risk-needs assessment, substance abuse treatment, and quantitative methods.
His most recent publications have appeared in Justice Quarterly, Experimental
Criminology, and Criminal Justice & Behavior.