Motives for Physical Dating Violence Among College Students.docx

Motives for Physical Dating Violence Among College Students:
A Gendered Analysis
Erika L. Kelley
Ohio University
Katie M. Edwards
University of New Hampshire
Christina M. Dardis and Christine A. Gidycz
Ohio University
Objective: Little research examines factors contributing to
specific motives for physical dating violence
(DV) perpetration. This study explores this gap in the literature
with a specific focus on gender, coping,
DV perpetration and victimization, and attitudes toward
violence. Method: The sample included 221
college students who reported a history of physical DV
perpetration and completed surveys for course
credit. Results: Physical DV motivated by emotional
expression/dysregulation was associated with
physical DV perpetration frequency and disengagement coping
for the full sample, and associated with
accepting attitudes toward physical DV among women only.
Physical DV motivated by control/tough
guise was associated with accepting attitudes toward physical
DV for the full sample, and physical DV
perpetration frequency more strongly for men than women.
Physical DV motivated by self-defense was
associated with disengagement coping for the full sample, DV
perpetration frequency for men, and

physical DV victimization frequency more strongly for women
than men. Conclusion: Results suggest
that DV prevention programming for college students should
incorporate focus on coping skills and
decreasing accepting attitudes of DV. Results also provide
preliminary support for gender-specific
tailoring of programs that incorporate emotion regulation and
communication skills for women; and
among men, deconstructing patriarchal values among frequent
perpetrators.
Keywords: dating violence, college students, motives, attitudes,
gender
Because of the high rates of dating violence (DV) and its
associated negative outcomes among college students,
researchers
have focused on increasing our understanding of the correlates
and
predictors of DV perpetration to inform primary prevention
efforts
(for a review see Flynn & Graham, 2010). Whereas most of the
past research has examined variables that predict whether or not
an
individual perpetrates DV, there has been a growing recognition
of
the importance in understanding motives for DV defined as the
“underlying psychological processes that impel people’s
thinking,
feeling, and behaving” (Fiske, 2004, p. 14). However, there has
been no research to date that has comprehensively explored the
individual-level variables (e.g., coping, victimization history)
that
are related to different motives for DV perpetration, which
could

provide critical information for DV prevention efforts. The
current
study utilized a sample of young men and women who all perpe-
trated physical DV and examined the types of motives for their
use
of physical DV and the correlates of these motives, which based
on
social learning theory (Akers, 1985) may include DV victimiza-
tion, attitudes toward DV, and strategies to cope with dating
conflict (e.g., Flynn & Graham, 2010; Swan & Snow, 2006).
Existing theory and research on the relationship between gender
and motives for physical DV have documented some gender
differences. For example, research and theory assert that men’s
use
of violence is typically related to power and control, for instru-
mental reasons, or in retaliation for being hit first (but not
neces-
sarily to protect oneself from immediate harm), whereas
women’s
use of violence is more commonly related to reactive or
emotional
expression (e.g., anger or jealousy) motives (Flynn & Graham,
2010; Follingstad, Wright, Lloyd, & Sebastian, 1991; Harned,
2001). Other research has been more equivocal, with some
studies
finding that women’s, and not men’s, use of DV occurs in self-
defense (Flynn & Graham, 2010), whereas others have found no
differences between men and women regarding self-defense as a
motive for physical DV (Follingstad et al., 1991; Harned, 2001).
Some potential reasons for these equivocal findings include lack
of
direct comparisons between men’s and women’s motives for DV
as well as a lack of comprehensive, psychometrically sound
mea-
sures of motives; the current study addressed this gap in the

literature with a sample of college men and women and use of
the
This article was published Online First April 7, 2014.
Erika L. Kelley, Department of Psychology, Ohio University;
Katie M.
Edwards, Department of Psychology and Women’s Studies,
University of
New Hamshire; Christina M. Dardis and Christine A. Gidycz,
Department
of Psychology, Ohio University.
This project was funded by the Department of Psychology at
Ohio
University. Special thanks are given to Gary Ellis who
contributed to data
collection and management for this study, and to the
undergraduate re-
search assistants who assisted in the management of data
collection and
entry. Additionally, the authors would especially like to thank
the individ-
uals who participated in this study.
Correspondence concerning this article should be addressed to
Erika L.
Kelley, Department of Psychology, Ohio University, Athens,
OH 45701.
E-mail: [email protected]
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Psychology of Violence © 2014 American Psychological
Association
2015, Vol. 5, No. 1, 56 – 65 2152-0828/15/$12.00
http://dx.doi.org/10.1037/a0036171
56
mailto:[email protected]
http://dx.doi.org/10.1037/a0036171
Motives and Reasons for IPV scale (Caldwell, Swan, Allen, Sul-
livan, & Snow, 2009). Furthermore, previous work on motives
for
DV perpetration has lacked theoretical grounding. The current
study used social learning theory to examine potential correlates
of
motives for DV perpetration including: DV victimization,
attitudes
toward DV, and the ways in which individuals cope with dating
conflict (e.g., Flynn & Graham, 2010; Swan & Snow, 2006).
First, history of DV victimization has been documented as a
specific correlate of DV perpetration (Flynn & Graham, 2010),
and
may also contribute to specific, self-identified motives for
physical
DV perpetration, such as self-defense or power/control motives
because an individual who experiences DV victimization may
resort to physical violence (e.g., striking back) to defend them-
selves or regain a sense of control in the relationship or

conflict.
However, this has not yet been examined to date. Second, more
accepting attitudes toward DV are related to physical DV perpe-
tration in multiple studies with both men and women (e.g.,
Archer
& Graham-Kevan, 2003; Nabors, Dietz, & Jasinksi, 2006),
though
men consistently endorse more accepting attitudes toward DV
than
women (e.g., Archer & Graham-Kevan, 2003). Given that
attitudes
help shape cognitions and behaviors, accepting attitudes of DV
may relate to specific motives, especially those such as control,
for
engaging in physical DV. For example, attitudes or beliefs that
it
is acceptable to slap a partner who has cheated may contribute
to
the use of physical DV motivated by control. Third,
understanding
how coping relates to specific motives for the use of DV will
shed
light on how and why physical violence is used in dating
relation-
ships. For example, avoidance of feelings or talking to others
about
problems may lead to difficulty with healthy expression of emo-
tions and the use of physical DV motivated by the need to
express
negative emotions may result. Indeed, expressing anger is
related
to poor emotion regulation (that might reflect maladaptive
coping)
and is commonly reported as a motive for physical DV among
both
men and women (Caldwell et al., 2009; Flynn & Graham, 2010;

Makepeace, 1986). Thus, as research documents that emotional
expression is frequently reported as a motive for violence,
coping
strategies, specifically maladaptive disengagement coping skills
(i.e., tactics used to disengage from, or avoid, the person-
environment interaction) in response to dating relationship
stress
might help explain the motivations for physical DV.
Taken together, research suggests that there are potential gender
differences in the motivations for the use of physical DV,
although
a more thorough understanding of the correlates of these
motives,
and potential gender differences in these correlates, has yet to
be
established. Prior research grounded in social learning theory
suggests that several specific individual-level variables (i.e.,
more
positive attitudes toward DV, avoidance coping, and having a
history of DV victimization) are related to the act of
perpetrating
physical DV. We assert that these same variables may be related
in
important ways to motives for DV. Thus, the aim of the current
study was to assess how individual-level variables (i.e.,
attitudes,
coping, and victimization history) related to different motives
for
DV in a sample of college students who report use of physical
DV,
and how these relationships may vary between men and women.
We hypothesized that individual-level variables would be
associ-
ated with specific motives for physical DV. Specifically, that
more

positive attitudes toward DV will be associated with DV
motivated
by control; greater DV victimization history will be related to
DV
motivated by self-defense; and disengagement coping will be
associated with DV motivated by emotional expression. The
mod-
erating role of gender in these relationships was an exploratory
aim
of the study and we ventured no a priori hypotheses for the
moderated regression analyses.
Method
Participants
The sample included 221 college students (89 men and 132
women) who reported a history of physical DV perpetration ob-
tained from a sample of 726 participants (361 men and 365
women) and who participated in a larger mixed-methodological
study assessing students’ perceptions of abuse in dating
relation-
ships (Edwards, Dardis, Kelley, & Gidycz, 2013). The average
age
of participants was 19.00 (SD � 1.19, range � 18 –26) and most
participants (86.9%) self-identified as White, followed by Black
(5.4%), Other/Multiracial (4.5%), Asian/Pacific Islander
(2.3%),
and Latino/Hispanic (0.9%). Most (86.4%) of the sample
reported
exclusively heterosexual experiences, whereas 13.6% of the
sam-
ple reported more heterosexual experiences than homosexual
ex-
periences, more homosexual than heterosexual experiences, or

equal heterosexual and homosexual experiences. With regard to
family income, 62.1% reported an annual income of $51,000 or
greater, 18.3% reported an annual income less than $51,000,
and
the remaining 19.6% reported that they did not know their
family’s
income.
Measures
Adolescent/adult dating violence victimization and
perpetration. The Conflict Tactics Scale—Revised (CTS2;
Straus, Hamby, Boney-McCoy, & Sugarman, 1996) Physical As-
sault subscale was utilized to measure physical DV
victimization
(12 items; e.g., “My partner pushed or shoved me”) and DV
perpetration (12 items; e.g., “I pushed or shoved my partner”) in
any dating relationship. Instructions of the CTS2 were utilized,
with the exception that the phrase “please circle how many
times
you did each of these things in the past year, and how many
times your partner did them in the past year” was modified to
read: “Please circle how many times a dating partner has done
these things to you” (victimization) or “Please circle how many
times you have done these things to a dating partner” (perpe-
tration). This measure was used to select the subsample of
individuals who had engaged in any type of physical DV perpe-
tration. Each of these 221 participants received a summed score
by
adding the midpoints (ranging from 0 to 25) for each of the
response categories endorsed by the participant as recommended
by Straus and colleagues (1996), representing the total number
of
instances across all physical DV items for the physical DV vic-
timization and perpetration subscales. Adequate validity has
been

established for the CTS2; for example, construct validity
reflected
higher correlations between the physical assault perpetration
and
injury scales for men than for women (Straus et al., 1996).
Motives for dating violence perpetration. The Motives and
Reasons for IPV scale (MRIPV; Caldwell et al., 2009) was used
to
assess for the perceived motives for why physical DV was used.
Participants responded to the question, “How often did you or
do
you use aggression, such as pushing, slapping, hitting, and so
forth
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57MOTIVES FOR DATING VIOLENCE
toward a partner for the following reasons?” in terms of 26-
items
on a 4-point scale ranging from 0 (never) to 3 (almost always),
in
reference to their general use of physical DV rather than to a
specific incident or timeframe. Items on the MRIPV were

slightly
modified to incorporate nongender specific language (i.e.,
modi-
fied from “him” to “your partner” or “him/her”) as well as other
slight language changes to make the measure more appropriate
for
our sample (e.g., removing the phrase “something for your chil-
dren” from the item “because you wanted him to give you some-
thing, like money, or something for your children” given the
vast
majority of college students do not have children). The original
MRIPV scale consists of five subscales: expression of negative
emotions, control, tough guise, self-defense, and jealousy.
Given
the MRIPV is a newer measure that has not yet been used with a
college sample, an exploratory factor analysis (EFA) using the
principal axis factoring extraction method (given the nonnormal
distribution of the items) and an oblique rotation (Promax) of
the
26 original MRIPV items was conducted specific to this sample.
From analysis of eigenvalues and the scree plot, a three factor
solution was retained after elimination of five items because of
cross-loadings less than or equal to .2. After conceptual
examina-
tion of the remaining items loading onto each of the three
factors,
it was determined that this factor structure represented the
follow-
ing three subscales: emotional expression/dysregulation,
control/
tough guise, and self-defense. Furthermore, one item (“to scare
your partner”) from the emotional expression/dysregulation
factor
and one item (“because you knew he or she was going to
become
aggressive toward you and you wanted to get it over with”)

from
the control/tough guise factor was eliminated because of lack of
conceptual fit with the factors. After elimination of these two
items, the final three factor solution accounted for 52% of the
variance and is presented in Table 1. For each participant, a
subscale score was derived by taking the mean of their scores
on
the subscale items. Cronbach’s � for these factors were
acceptable:
emotional expression/dysregulation (.89), control/tough guise
(80), and self-defense (.83).
Coping strategies. The Coping Strategies Inventory-Short
Form 32 (CSI-S; Tobin, Holroyd, Reynolds, & Wigal, 1989) was
used to assess disengagement coping strategies in response to
dating relationship stress. The instructions to the CSI-S were
slightly modified for the current study. The original CSI-S in-
structed participants to refer to how they handled a self-
identified
stressful event that occurred in the past month, asking
participants
to “Please read each item below and determine the extent to
which
you used it in handling your chosen event.” In the current study,
these instructions were modified such that instructions read:
“Take
a moment to think about how you generally respond to difficult
or
stressful events in your dating relationships, such as conflict.
Then
please read through each item below and determine the extent to
which you use each when confronted by a difficult or stressful
event in your dating relationships.” Thus, these instructions and
all
items were in reference to general coping strategies in dating

relationship; a specific incident was not referenced for
participants.
The disengagement subscale consists of 16 items related to
prob-
lem avoidance, wishful-thinking, social withdrawal, and self-
criticism. An example item is “I avoided thinking or doing any-
thing about the situation.” Participants respond to each item on
a
5-point Likert scale, which are summed; higher scores indicate
greater use of disengagement coping in response to relationship
stress (Cronbach’s � � .88). The authors of the CSI-S note that
Table 1
Factor Loadings for Final Three-Factor
Solution
of the MRIPV Scale
Factor loading
Item 1 2 3
1. Emotional expression/Dysregulation
Because your partner made you angry .93 �.18 �.05
Because your partner said something that hurt you .85 �.09
�.01
Because you were fed up with your partner’s behavior .76 .04
.03

Because you were frustrated .68 .01 �.10
To get him or her to take you seriously .66 .12 .04
Because you were jealous .62 �.06 .03
Because you thought your partner was unfaithful .59 .19 �.02
Because you wanted to let your partner know he or she could
not get away with
mistreating you .54 .10 .23
Because you were drinking or using drugs .41 .22 .12
2. Control/Tough guise
Because you wanted your partner to give you something, like
money �.06 .81 �.14
To intimidate your partner .10 .68 �.13
To get turned on sexually �.10 .64 �.10
To physically hurt your partner �.17 .62 .34
Because you wanted him or her to do something .26 .58 �.12
Because you feel better after a fight .07 .53 .23
3. Self-defense
To get your partner to stop hitting or hurting you .11 �.20 .84
To get away as he or she was being aggressive towards you
�.09 .04 .83
To defend yourself from your partner �.02 �.06 .79
Because your partner became aggressive when he or she drank

.03 .05 .59
% of variance 37.00 8.47 6.78
Eigenvalue 7.03 1.61 1.29
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58 KELLEY, EDWARDS, DARDIS, AND GIDYCZ
scores on the full CSI discriminate well between nondepressed
and
depressed individuals and are predictive of depression among
individuals who are under high levels of stress (Tobin et al.,
1989).
Attitudes toward dating violence. The Attitudes Toward Fe-
male Physical Dating Violence and Attitudes Toward Male
Phys-
ical Dating Violence subscales of the Attitudes Toward Dating
Violence Scales (ATDVS; Price et al., 2000) were used to
assess

attitudes toward men’s use of physical DV toward women (39
items; e.g., “Some girls deserve to be slapped by their
boyfriends”)
and women’s use of physical DV toward men (37 items; e.g.,
“Sometimes girls just cannot stop themselves from punching
their
boyfriends”). For each item, participants are directed to “please
express your feelings about each statement by using the scale
below,” which is a 5-point scale ranging from 1 (strongly
disagree)
to 5 (strongly agree). Summed scores were computed separately
for each of the two subscales; higher scores were indicative of
more accepting attitudes toward DV. Cronbach’s � was .93 for
ATDVS male-to-female; and .93 for ATDVS female-to-male
sub-
scales. Validity for the ATDVS has been established; for
example,
criterion validity was demonstrated such that girls’ and boys’
positive attitudes toward physical violence were significantly
cor-
related with physically abusive behavior (Price et al., 1999).
Procedure
Following Institutional Review Board approval, participants

were recruited from introductory psychology courses and
received
course credit for their participation. After completing informed
consent, men and women completed the identical paper-and-
pencil
surveys in separate group testing environments administered by
same-gender graduate students, followed by debriefing and
referral
information.
Results
Descriptive and Basic Inferential Statistics
Before examining the aim of this study, means and SDs for each
variable of interest were calculated (see Table 2). To evaluate
all
possible intercorrelations among these variables, Pearson
product–
moment correlations were also conducted (see Table 3).
Relationships Among Interpersonal Variables and
Motives for DV

To address the aim of this study, a series of hierarchical linear
regressions was performed using the full sample to assess the
multivariate relationships of gender, frequency of physical DV
perpetration, physical DV victimization, attitudes toward
gender-
specific physical DV, and disengagement coping with each of
the
factors resulting from the EFA conducted on the MRIPV; as
well
as to examine the potential moderating role of gender on the
relationship between each of the individual-level variables and
motives for physical DV. Before conducting regression
analyses,
all continuous independent variables were mean centered, as
rec-
ommended by Aiken and West (1991) to reduce
multicollinearity
among these variables in the models. Gender was recoded, using
effects coding, as �1 (males) and 1 (females) to aid in interpre-
tation. For each regression, gender and frequency of physical
DV
perpetration (given that greater endorsement of motives is
associ-
ated with greater frequency of physical DV perpetration; e.g.,
Caldwell et al., 2009) were entered in the first block to control

for their effects in the remaining blocks. In the second block,
each of the individual-level variables was entered and included
attitudes toward women’s use of physical DV, attitudes toward
men’s use of physical DV, physical DV victimization, and
disengagement coping. In the third and final block, gender was
entered as an interaction term with all other variables to exam-
ine its role as a moderator. Nonsignificant interaction terms
were dropped from all final regression models that are pre-
sented below. Significant interaction terms were further ex-
plored utilizing the MODPROBE macro developed by Hayes
and Matthews (2009) to examine the simple slopes (Aiken &
West, 1991). Simple slopes are estimated for the effects of the
focal independent variable on the dependent variable at each
value (i.e., male, female) of the moderator while taking into
account the remaining independent variables in the model.
Regression model statistics for all blocks of each model are
Table 2
Means, SDs, and t-Tests Comparing Genders On Study
Variables of Interest
Men M (SD) Women M (SD) t-value p-value
MRIPV mean scores
Emotional expression/Dysregulation 0.18 (0.37) 0.42 (0.54)

�3.91 .001��
Control/Tough guise 0.15 (0.36) 0.09 (0.26) 1.48 .139
Self-defense 0.25 (0.43) 0.35 (0.62) �1.30 .193
ATDVS subscale totals
Male physical DV perpetration 21.96 (8.40) 15.62 (5.71) 6.11
.001��
Female physical DV perpetration 30.65 (8.37) 23.52 (8.72) 5.98
.001��
CSI Disengagement coping 42.20 (11.22) 38.86 (12.88) 1.95
.052
CTS-R
Total physical DV victimization 21.59 (28.55) 13.18 (34.19)
1.90 .058
Minor physical DV victimization 15.39 (20.51) 9.08 (20.55)
2.24 .026�
Severe physical DV victimization 5.16 (10.99) 3.96 (15.35) 1.15
.250
Total physical DV perpetration 7.63 (14.03) 9.20 (20.47) �0.63
.528

Minor physical DV perpetration 4.59 (6.99) 6.94 (14.44) �1.67
.110
Severe physical DV perpetration 3.03 (8.63) 2.27 (7.46) 1.26
.482
Note. MRIPV � Motives and Reasons for IPV scale, potential
scores range 0 to 3; ATDVS � Attitudes Towards Dating
Violence Scales, potential scores
for ATDVS- male perpetration range from 12 to 52, ATDVS-
female perpetration potential scores range from 12 to 50; CSI �
Coping Strategies Inventory;
potential scores range from 16 to 80; CTS-R � Conflict Tactics
Scale-Revised, potential scores range from 0 to 300.
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presented in Tables 4, 5, and 6. Details of the final model and
unique significant contributions of individual variables of each

regression are discussed in the following sections.
The final model assessing correlates of the emotional expres-
sion/dysregulation motive was significant, F(7, 205) � 21.37, p
�
.001, and represented 43.0% of the variance in this motive.
More
specifically, greater frequency of physical DV perpetration and
greater disengagement coping were significant correlates of
phys-
ical DV motivated by emotional expression/dysregulation. The
gender by attitudes toward women’s use of physical DV interac-
tion term (see Figure 1 for a graphical depiction) was also
signif-
icant and examination of this term showed that among women,
more accepting attitudes toward women’s use of physical DV
was
associated with greater physical DV motivated by emotional ex-
pression/dysregulation (b � 0.015, SE � 0.004, p � .001).
How-
ever, among men, the relationship between attitudes toward
wom-
en’s use of physical DV and violence motivated by emotional
expression/dysregulation was nonsignificant (b � �0.0001, SE
�

0.006, p � .982).
The final model assessing correlates of the control/tough guise
motive was significant, F(7, 205) � 29.35, p � .001, and repre-
sented 50.9% of the variance in this motive. More accepting
attitudes toward both women’s and men’s use of physical DV
were
significant correlates of physical DV motivated by tough guise.
The significant gender by frequency of physical DV
perpetration
interaction showed that greater frequency of physical DV perpe-
tration was associated with violence motivated by control/tough
guise, among both men, (b � 0.018, SE � 0.002, p � .001) and
women (b � 0.004, SE � 0.001, p � .001). However, the rela-
tionship was stronger for men than women (see Figure 2).
When assessing correlates of the self-defense motive, the final
model was also significant, F(8, 205) � 16.90, p � .001, and
represented 40.7% of the variance in this motive. More specifi-
cally, greater disengagement coping was positively associated
with
physical DV motivated by self-defense. Examination of the
gender
by frequency of physical DV perpetration interaction (see

Figure 3
for a graphical depiction) showed that greater frequency of
phys-
ical DV perpetration was associated with violence motivated by
self-defense, among men, (b � 0.009, SE � 0.004, p � .05); but
that this relationship was nonsignificant among women (b �
0.001, SE � 0.002, p � .731). The interaction of gender and
physical DV victimization (see Figure 4) revealed that more fre-
Table 3
Correlation Matrix of All Continuous Variables Used In
Analyses
1 2 3 4 5 6 7 8 9
1. Emotional expression/Dysregulation 1
2. Control/Tough guise .60�� 1
3. Self-defense .45�� .42�� 1
4. ATDVS-Female .19�� .33�� .07 1
5. ATDVS-Male .22�� .43�� .24�� .47�� 1
6. Disengagement coping .17� .17� .24�� .05 .12 1
7. DV victimizationa .30�� .29�� .54�� .19��
.36�� .15� 1
8. DV perpetrationb .56�� .54�� .42�� .20�� .30��
.18�� .56�� 1

9. Gender .24�� .10 .08 �.38�� .41�� .13 �.13
.04 1
a Physical dating violence victimization. b Physical dating
violence perpetration.
� p � .05. �� p � .01. �� p � .001.
Table 4
Results of Hierarchical Linear Regression Analyses Examining
Emotional Expression/Dysregulation
Variable �F p �R2 B SE B � p-value
Block 1 57.64 .001 .36
Physical DV perpetration frequency�� 0.02 0.001 0.56 .001
Gender�� 0.10 0.03 0.20 .001
Block 2 4.60 .001 .05
Gender�� 0.16 0.03 0.32 .001
Attitudes towards women’s physical DV�� 0.01 0.003 0.18
.005
Attitudes towards men’s physical DV 0.01 0.01 0.10 .157
Physical DV victimization 0.00 0.001 �0.02 .831
Disengagement coping� 0.01 0.002 0.12 .034

Block 3 4.94 .027 .01
Gender�� 0.16 0.03 0.31 .001
Attitudes towards women’s physical DV� 0.01 0.004 0.13 .042
Disengagement coping� 0.01 0.002 0.13 .017
Gender � attitudes towards women’s physical DV� 0.01 0.003
0.13 .027
� p � .05. �� p � .01. �� p � .001.
T
hi
s
do
cu
m
en
t

is
co
py
ri
gh
te
d
by
th
e
A
m
er
ic
an
P
sy

ch
ol
og
ic
al
A
ss
oc
ia
ti
on
or
on
e
of
it
s

al
li
ed
pu
bl
is
he
rs
.
T
hi
s
ar
ti
cl
e

is
in
te
nd
ed
so
le
ly
fo
r
th
e
pe
rs
on
al
us

e
of
th
e
in
di
vi
du
al
us
er
an
d
is
no
t
to

be
di
ss
em
in
at
ed
br
oa
dl
y.
quent physical DV victimization was associated with violence
motivated by self-defense, among both men (b � 0.006, SE �
0.002, p � .001) and women (B � 0.009, SE � 0.002, p �

.001),
but that the relationship was stronger for women than men.
Discussion
The current study examined male and female college student
perpetrators’ motives for the use of physical DV. Factor
analytic
results demonstrated the emergence of three distinct motives:
emotional expression/dysregulation, control/tough guise, and
self-
defense. Further, block one regression model statistics revealed
no
gender differences in the self-defense motive, yet female perpe-
trators were more likely than male perpetrators to report
motives of
emotional expression/dysregulation and male perpetrators were
more likely to report motives of control/tough guise than female
perpetrators. These findings, which were based on direct
compar-
isons between genders and the use of a comprehensive and psy-
chometrically sound measure of motives, help to shed light on
some of the conflicting findings documented in previous
studies.

However, these findings regarding gender differences in
specific
motives are qualified by significant interactions between gender
and attitudes toward women’s use of physical DV and the fre-
quency of DV perpetration and victimization.
The current study’s most significant contribution is its ground-
ing in social learning theory to examine how DV victimization
and
perpetration frequency, attitudes toward gender-specific use of
Table 5
Control/Tough Guise
Block 1 44.87 .001 .31
Gender� �0.04 0.02 �0.12 .001
Block 2 7.35 .001 .09
Gender�� 0.01 0.02 0.04 .001
Attitudes towards women’s physical DV 0.01 0.002 0.13 .210

Attitudes towards men’s physical DV�� 0.01 0.003 0.27 .001
Physical DV victimization �0.001 0.001 �0.11 .270
Disengagement coping 0.002 0.001 0.08 .110
Block 3 45.77 .001 .11
Gender 0.01 0.02 0.02 .724
Attitudes towards women’s physical DV� 0.01 0.002 0.16 .006
Attitudes towards men’s physical DV�� 0.01 0.003 0.21 .001
Disengagement coping 0.002 0.001 0.07 .209
Gender � physical DV perpetration frequency�� 0.01 0.001
�0.41 .001
� p � .05. �� p � .01. �� p � .001.
Table 6
Self-Defense
Block 1 22.80 .001 .18
Gender 0.03 0.04 0.05 .463

Block 2 15.32 .001 .19
Physical DV perpetration frequency 0.003 0.002 0.10 .157
Gender� 0.10 0.04 0.17 .009
Attitudes towards women’s physical DV 0.00 0.004 �0.01 .915
Physical DV victimization�� 0.01 0.001 0.46 .001
Disengagement coping�� 0.01 0.003 0.16 .006
Block 3 5.20 .006 .03
Physical DV perpetration frequency� 0.01 0.002 0.15 .044
Gender� 0.09 0.04 0.16 .016
Attitudes towards women’s physical DV 0.001 0.004 0.02 .785
Physical DV victimization�� 0.01 0.001 0.46 .001
Disengagement coping�� 0.01 0.003 0.14 .015
Gender � physical DV perpetration frequency�� 0.003 0.001
0.18 .013
Gender � physical DV victimization� �0.01 0.002 �0.22 .003
� p � .05. �� p � .01. �� p � .001.
T
hi

s
do
cu
m
en
t
is
co
py
ri
gh
te
d
by
th
e
A

m
er
ic
an
P
sy
ch
ol
og
ic
al
A
ss
oc
ia
ti
on

or
on
e
of
it
s
al
li
ed
pu
bl
is
he
rs
.
T

hi
s
ar
ti
cl
e
is
in
te
nd
ed
so
le
ly
fo
r
th

e
pe
rs
on
al
us
e
of
th
e
in
di
vi
du
al
us
er

an
d
is
no
t
to
be
di
ss
em
in
at
ed
br
oa
dl

y.
DV, and disengagement coping relate to various motives for
phys-
ical DV perpetration. In this study we also explored how gender
interacted with other key variables to predict motives for
physical
DV and identified some interesting effects. When examining the
regression model for physical DV motivated by emotional
expres-
sion/dysregulation, disengagement coping was a significant
corre-
late of emotional expression/dysregulation motives. This
finding
provides support for the application of social learning theory,
such
that young adults who learn to cope with maladaptive strategies
(e.g., disengagement) may apply such strategies when dealing
with
relationship conflict, leading them to resort to physical DV
when

they need to express their emotions. In this way, use of violence
for emotional expression may be a form of disengagement
coping
(i.e., one is avoiding emotional expression and using violence to
cope with distress instead). As conflict is ubiquitous within
rela-
tionships, it was not surprising that individuals whose violence
is
motivated by needs for emotional expression would have a
greater
frequency of previous physical DV perpetration, as was found in
the current study. In this sense, individuals who have a more
difficult time expressing negative emotions related to their rela-
tionship issues or conflict may more often resort to physical
violence. Additionally, there was an interaction between
attitudes
toward women’s use of violence and gender, such that among
women, positive attitudes toward women’s use of violence were
related to greater physical DV perpetration for emotional
expres-
sion/dysregulation (see Figure 1). This result suggests that
women
who have learned that violence is an acceptable form of
emotional

expression will be more likely to turn to violence for
emotionally
expressive reasons when conflict arises. That this interaction
was
nonsignificant among men was unsurprising, given that one
would
not expect that men’s use of violence for emotional expression
would be impacted by their attitudes toward women’s use of
physical violence. However, it is interesting that men’s attitudes
toward men’s use of physical DV was not associated with
physical
0
0.5
1
1.5
2
2.5
3

Low High
Physical DV
Motivated by
Emotional
Expression/Dysreg
ulation
Attitudes Toward Women's Use of Physical DV
Men
Women
Figure 1. Plot of significant interaction term for model
examining the
emotional expression/dysregulation motive.
0
0.5

1
1.5
2
2.5
3
Low High
Physical DV
Motivated by
Control/Tough
Guise
Physical DV Perpetration Frequency
Men
Women

examining the
control/tough guise motive.
0
0.5
1
1.5
2
2.5
3
Low High
Physical DV
Motivated by Self-
Defense
Physical DV Perpetration Frequency

Men
Women
examining the
self-defense motive.
0
0.5
1
1.5
2
2.5
3
Low High

Physical DV
Motivated by Self-
Defense
Physical DV Victimization Frequency
Men
Women
examining the
self-defense motive.
T
hi
s
do
cu
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en

t
is
co
py
ri
gh
te
d
by
th
e
A
m
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ic
an
P

sy
ch
ol
og
ic
al
A
ss
oc
ia
ti
on
or
on
e
of

it
s
al
li
ed
pu
bl
is
he
rs
.
T
hi
s
ar
ti
cl

e
is
in
te
nd
ed
so
le
ly
fo
r
th
e
pe
rs
on
al

us
e
of
th
e
in
di
vi
du
al
us
er
an
d
is
no

t
to
be
di
ss
em
in
at
ed
br
oa
dl
y.
DV motivated by emotional expression/dysregulation and addi-

tional research should attempt to replicate and understand this
finding further. Perhaps these gender-parallel attitudes toward
DV
were more salient for women with respect to DV motivated by
emotional expression in part because of the finding that women
are
more motivated than men by emotional expression to engage in
physical DV, making their attitudes more salient.
Although accepting attitudes toward DV were not consistently
related for both genders to motives of emotional
expression/dys-
regulation, accepting attitudes toward both women’s and men’s
use of physical DV were significant correlates of physical DV
motivated by control/tough guise across the full sample. This
suggests that college students with more accepting attitudes
toward
the use of physical DV may more often engage in physical DV
as
a means of establishing or maintaining control in a relationship
or
to put on a tough guise in a relationship. Some college students
may perceive that it is acceptable to engage in physical DV for
more instrumental reasons in relationships. To better understand
this relationship between attitudes and physical DV motivated

by
control/tough guise, it is helpful to examine the items within the
ATDVS (Price et al., 2000); for example, several items reflect
that
a partner is “deserving” of a violent act (e.g., slap). This may
indicate that some young men and women perceive violence as
an
appropriate form of repercussion for the other partner’s
behavior.
Additional items reflect acceptance of violent behaviors that a
person engages in toward a partner because they “cannot help”
it
or they “just cannot stop themselves.” Thus, perhaps some
young
men and women, who believe violence that is conducted
involun-
tarily is acceptable, may justify their use of violence as a means
of
establishing control in the relationship. Although speculative, it
is
possible that such attitudes toward DV are most closely tied to
the
use of violence motivated by control/tough guise because the
items
on the ATDVS tap more directly into overt or instrumental vio-

lence similar to items reflected on the control/tough guise
motive
subscale. Furthermore, greater frequency of physical DV perpe-
tration was associated with violence motivated by control/tough
guise for both genders, but more strongly for men (see Figure
2).
This finding suggests that men and women who report greater
frequencies of physical DV may do so to establish or maintain a
sense of control or tough guise in a relationship. This finding
appears to be more salient for men than for women, which might
be consistent with previous research finding that men tend to
engage in physical DV for more controlling reasons (e.g.,
Harned,
2001).
Finally, regression analyses documented several important cor-
relates of physical DV motived by self-defense. Past
victimization
was related to physical DV motivated by self-defense across the
sample, although this relationship was stronger for women than
for
men (see Figure 4). This may reflect that women who are
experi-
encing DV victimization have a stronger need or desire to
engage

in physical DV as a means of protecting themselves in response
to
this violence than do men who may be more easily able to walk
away or stop their partner’s aggression because of physical size
differences. Indeed, differences in physical size between
genders
has been identified as an important variable in understanding
perceptions of DV and the significance of power imbalances in
terms of gender (Hamby & Jackson, 2010). Whereas the
findings
regarding the interaction between gender and victimization
history
are consistent with what might be expected given the power
imbalances between genders and differences in size, the
interaction
between gender and perpetration history (see Figure 3) warrants
further investigation to explore the mechanisms behind this
inter-
action. Given the nature of the research design it is not possible
to
determine the sequence of violence reported upon, which would
be
important to better understand participants’ report of self-
defense

as a motive. Given that men are socialized to “fight back” when
confronted with aggression unlike women who experience
barriers
to engaging in self-defense (Gidycz & Dardis, in press), it is
possible that the men who perpetrated more frequently, but not
the
women, were more likely to report self-defense as a motive.
Additional results indicating disengagement coping as a
correlate
of physical DV motivated by self-defense may be
counterintuitive
to the notion of self-defense as a form of active resistance (i.e.,
engagement coping) and warrants additional study. One
hypothesis
is that women and men who are experiencing high levels of DV
victimization may also be experiencing high levels of
psycholog-
ical distress and avoidance coping, which is consistent with the
bivariate correlations between victimization and disengagement
coping and with the conceptualization that greater coping re-
sources are engaged in as stressors (e.g., victimization)
increase.
When taking into account that disengagement coping was a sig-
nificant correlate of physical DV motivated by emotional
expres-

sion/dysregulation across the full sample, it appears that some
college men and women who experience relationship conflict
may
resort to the use of violence to communicate or express their
frustration, anger, or fear from this conflict and their perception
that they need to protect themselves from physical aggression.
Although it is interesting that disengagement coping was not
significant in the model examining physical DV motivated by
control/tough guise, the correlation between disengagement
coping
and use of control/tough guise as a motive was identical to the
correlation between disengagement coping and the use of emo-
tional expression/dysregulation as a motive. Thus, whereas
these
results should be further assessed in future research, the
salience of
attitudes toward physical DV in the prediction of the
control/tough
guise motive may have precluded disengagement coping from
entering the model.
In general, it is notable that frequency of DV perpetration
was a salient correlate of violence across all motives for men
(and for women in emotional expression/dysregulation and less
strongly for women in violence motivated by control/tough

guise). This might suggest that young college students, partic-
ularly men, may engage in physical DV for a multitude of
reasons; this is also reflected in the significant bivariate corre-
lations between the three motives for physical DV. Thus, there
remains a need for additional research to examine how the
extent (e.g., frequency, form, severity) of DV relates to moti-
vations for violence in relationships.
Limitations
The current study was retrospective and cross-sectional in de-
sign, limiting the ability to determine temporal relationships
among variables. Additionally, the measures utilized reflected
overall past experiences with DV, general current attitudes
toward
DV and coping strategies in response to dating conflict, and
general motivations for use of current and/or past use of DV.
Thus,
these items were not anchored in any specific period of time or
T
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A
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er
ic
an
P
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ch
ol
og
ic
al
A
ss
oc
ia
ti
on
or

on
e
of
it
s
al
li
ed
pu
bl
is
he
rs
.
T
hi
s

ar
ti
cl
e
is
in
te
nd
ed
so
le
ly
fo
r
th
e

pe
rs
on
al
us
e
of
th
e
in
di
vi
du
al
us
er
an

d
is
no
t
to
be
di
ss
em
in
at
ed
br
oa
dl
y.

partner, which may limit conclusions that can be made
regarding
the stability of the relationships between these constructs across
all
relationships (e.g., Capaldi & Kim, 2007). Furthermore, it may
be
that men and women utilize different motives for DV at
different
times, and potentially use multiple motives at the same time
(e.g.,
control/tough-guise, self-defense); as suggested by previous re-
search (e.g., Caldwell et al., 2009) and the significant positive
bivariate correlations among motive subscales found in the
current
study. Additional research should address the degree of overlap
between specific types of motives for DV, especially given the
moderate intercorrelations. Additionally, given the assessment
of
more global use of motives for physical DV, the current study
may
have neglected some behaviors important to motives for

physical
DV (e.g., in retaliation for being hit first, horseplay, joking
around;
Foshee, Bauman, Linder, Rice, & Wilcher, 2007). Results
regard-
ing the self-defense motive should be interpreted with some
cau-
tion, given that the items in the current study reflecting the self-
defense motive may not accurately reflect the legal definition of
self-defense, but rather retaliatory behaviors, as the researchers
cannot assess whether the violence is in proportion to that
inflicted
by one’s partner. The current study also focused on physical
DV,
neglecting other forms of DV (i.e., sexual and psychological
abuse) that tend to co-occur in violent relationships, and for
which
different motives may exist (Sabina & Straus, 2008). Finally,
given
the focus on a nondiverse sample of college men and women,
generalizations are limited to this population. Consideration of
these limitations is important for conceptualization of the
findings
and for guiding future research.

Research Implications
Future research could benefit from consideration of motives for
other forms of violence (e.g., sexual and psychological), the use
of
longitudinal designs to assess for temporal relationships, and
more
diverse samples. Methodologies that utilize daily diary or
experi-
encing sample methodologies could be useful in avoiding recall
bias and allow for a more nuanced understanding of motives for
DV. Measures that are specific to one dating partner or a
specific
period of time (e.g., critical incident studies) may help clarify
the
relationships between DV, attitudes toward DV, motivations for
the use of DV, and coping strategies. Along these lines, includ-
ing both members of a dyad could be useful in determining if
perpetrators’ self-reported motives for DV perpetration are
consistent with the meaning that the violence has to the victim.
It is also worth considering ways to experimentally study mo-
tives for DV perpetration, perhaps through implicit association
tasks that elicit specific emotions (e.g., anger, control) and
associated aggressive behaviors within a controlled laboratory
environment, using techniques such as couple conflict protocols

or noxious stimuli to a confederate. Further, the factor analyses
performed using the MRIPV indicated a different factor struc-
ture than that obtained by Caldwell and colleagues (2009) in
their sample of community members, implicating the impor-
tance of age and developmental and contextual factors in un-
derstanding partner violence. Thus, future research is needed to
replicate this result and inform valid measurement of motives
for DV.
Clinical and Policy Implications
Although several evidence-based DV prevention programs (e.g.,
Safe Dates; Foshee, Bauman, Arriaga, Helms, & Koch, 1998)
have
been developed, all of the work addressing these programs
effec-
tiveness has been with middle and high school students. There
are
no comprehensive, evidence-based DV prevention programs that
have been developed and systematically evaluated for college
students, specifically (although there are programs focusing
more
specifically on sexual assault; e.g., Banyard, Eckstein,
Moynihan,
2010; Gidycz, Orchowski, & Berkowitz, 2011). Although it is

presumable that programs such as Safe Dates may be effective
in
reducing DV perpetration among college students, Safe Dates is
a
mixed-gender program, and results from the current study
suggest
that prevention programs with college students may need to take
into consideration some of the differences in men’s and
women’s
physical DV perpetration patterns. Overall, results indicate that
both young men and women would benefit from programming
focused on decreasing positive attitudes toward men’s and wom-
en’s use of physical DV in general to reduce DV motivated by
control/tough guise. Among women, programming should focus
on the minimization of attitudes toward women’s use of
physical
DV especially for reasons pertaining to emotional expression
(e.g.,
communication of anger or jealousy). Furthermore, men’s DV
programming should focus on deconstructing patriarchal values
that legitimize controlling behavior toward women. Further,
find-
ings suggest that DV interventions could benefit from more
focus
on increasing adaptive coping strategies in response to

relationship
stress or conflict including aggressive or unwanted behaviors by
a
partner, as well as assertive communication skills for the
expres-
sion of emotions (e.g., anger). Additionally, focus groups might
be
beneficial that target young men and women who report greater
frequency of physical DV overall (motivated by many reasons).
Further, because of the result that men who perpetrate more
physical DV were more likely to self-report that they were
moti-
vated by self-defense, there are two considerations: (1)
exploring
the bidirectional nature of violence in provoking men’s
perpetra-
tion in self-defense as well as men’s stay/leave decision-making
in
abusive relationships, and (2) examining the rationalization that
men may use to perpetrate violence. By more clearly
understand-
ing the complex predictors of motives for DV among young
adults,
we will be better able to tailor prevention and intervention pro-
grams to meet the needs of both genders.

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Received January 17, 2013
Revision received January 8, 2014
Accepted January 23, 2014 �
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http://dx.doi.org/10.1016/j.cpr.2006.09.001
http://dx.doi.org/10.1016/j.avb.2010.01.002
http://dx.doi.org/10.2307/585658
http://dx.doi.org/10.1177/0886260506298829
http://dx.doi.org/10.2105/AJPH.88.1.45
http://dx.doi.org/10.1177/1077801211409727
http://dx.doi.org/10.1007/s11199-010-9816-0
http://dx.doi.org/10.1007/s11199-010-9816-0
http://dx.doi.org/10.3758/BRM.41.3.924
http://dx.doi.org/10.3758/BRM.41.3.924

http://dx.doi.org/10.2307/584365
http://dx.doi.org/10.1891/vv-v21i6a007
http://dx.doi.org/10.1023/A:1022830114772
http://dx.doi.org/10.1891/0886-6708.23.6.667
http://dx.doi.org/10.1177/019251396017003001
http://dx.doi.org/10.1177/019251396017003001
http://dx.doi.org/10.1177/1077801206293330
http://dx.doi.org/10.1007/BF01173478Motives for Physical
Dating Violence Among College Students: A Gendered
AnalysisMethodParticipantsMeasuresAdolescent/adult dating
violence victimization and perpetrationMotives for dating
violence perpetrationCoping strategiesAttitudes toward dating
violenceProcedureResultsDescriptive and Basic Inferential
StatisticsRelationships Among Interpersonal Variables and
Motives for DVDiscussionLimitationsResearch
ImplicationsClinical and Policy ImplicationsReferences
AGGRESSIVE BEHAVIOR
Alcohol and Drug Abuse in Men Who Sustain Intimate
Partner Violence
Denise A. Hines1� and Emily M. Douglas2

1Clark University, Worcester, Massachusetts
2Bridgewater State University, Bridgewater, Massachusetts
: : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : :
Extensive work has documented an association between
sustaining intimate partner violence (IPV) and alcohol/drug
abuse among
women, yet little research has documented the same association
in men, even though men comprise 25–50% of all IPV victims
in a
given year. This study investigates the associations among
sustaining IPV and alcohol/drug abuse among both a clinical
and
community sample of men. The clinical sample is comprised of
302 men who sustained intimate terrorism—a form of IPV that
is
characterized by much violence and controlling behavior—from
their female partners and sought help. The community sample is
composed of 520 men, 16% of whom sustained common couple
violence, a lower level of more minor reciprocal IPV. Analyses
showed that among both groups of men who sustained IPV, the
prevalence and frequency of alcohol/drug abuse was
significantly
higher than in men who did not sustain IPV. However, a dose–

response relationship between sustaining IPV and alcohol/drug
abuse was found only among men in the community sample.
Path modeling showed that, for the community sample, the best
fitting
models were ones that showed that the alcohol/drug abuse
predicted IPV victimization, an association that was fully
mediated by
r 2011 Wiley Periodicals, Inc.
: : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : :
Keywords: domestic violence; male victims; intimate terrorism;
alcohol abuse; drug abuse
INTRODUCTION
A significant association between alcohol/drug
abuse and women sustaining intimate partner
violence (IPV) has been well-documented [Amaro
et al., 1990; Kantor and Asdigian, 1997; Salomon
et al., 2002; Stark and Flitcraft, 1988; Stith et al.,
2004], yet little research has documented whether
there is an association between alcohol/drug abuse
and men sustaining IPV. To our knowledge, only a

handful studies have investigated this association,
with no focus on men who report sustaining more
severe types of IPV. For example, Halford and
Osgarby [1993] investigated, among other issues, the
association between female partners’ violence and
men’s alcohol abuse among 56 men seeking marital
therapy in Australia. Although they found no
association, their sample size was small, had limited
generalizability, and did not investigate the abuse of
other substances. Among male college students,
Simons et al. [2008] found that IPV victimization
was associated with higher rates of both alcohol and
drug use, but this study also has limited general-
izability and does not test possible mediators of this
association. More research among men who sustain
IPV is warranted, especially given that between 25
and 50% of people who sustain IPV in a given year
are men [Archer, 2000; Catalano, 2007; Straus, 1995;
Tjaden and Thoennes, 2000], and men are more
likely than women to abuse alcohol or other
substances in response to a stressful event [Cooper
et al., 1992]. We propose to address these limitations
in this article.

Theoretical Models Explaining Associations
Among IPV and Alcohol/Drug Abuse
In this study, we investigated whether there was an
association between alcohol/substance abuse and
sustaining IPV among two samples of men: a
Published online in Wiley Online Library
(wileyonlinelibrary.com).
DOI: 10.1002/ab.20418
Received 10 September 2010; Revised 22 March 2011;
Accepted 5
August 2011
Grant sponsor: National Institute of Mental Health; Grant
number:
5R21MH074590.
�
Correspondence to: Denise A. Hines, Clark University,
Department

of Psychology, 950 Main St., Worcester, MA 01610.
E-mail: [email protected]
r 2011 Wiley Periodicals, Inc.
Volume 38, pages 31–46 (2012)
their use of IPV. Aggr. Behav. 38:31–46, 2012.
community sample and those who sustained IPV
from their female partner and sought help. We then
investigated possible reasons for any association.
Specifically, if alcohol/substance abuse is related to
sustaining IPV in men, previous research on female
IPV victims suggests at least two possibilities for
explaining that relationship [Kilpatrick et al., 1997].
The first possibility is that alcohol/drug abuse is a
risk factor for sustaining IPV [Kilpatrick et al.,
1997]. This possibility is thought to be related to
one’s lifestyle, such that alcohol/drug abuse leads
one into certain situations or relationships in which

sustaining IPV is more likely. Another explanation
is that alcohol/drug abuse can lead to certain
behaviors that increase the likelihood of sustaining
IPV, and one such behavior could be IPV perpetra-
tion. It has been well-documented that both alcohol
and drug abuse are risk factors for men using IPV
against their female partners [Fals-Stewart, 2003;
Fals-Stewart et al., 2005; Leonard, 1993; Murphy
et al., 2001; O’Farrell et al., 2003], and the strongest
risk for sustaining IPV is perpetrating IPV [Kessler
et al., 2001; Stets and Straus, 1990]. Thus, IPV
perpetration can be a mediator for the relationship
between alcohol/drug abuse and sustaining IPV.
A second possibility is that sustaining IPV is a risk
factor for alcohol/drug abuse [Kilpatrick et al.,
1997]. This association is typically thought to be
related to the overwhelmingly negative emotions or
posttraumatic stress symptoms that someone who
experiences a traumatic event, such as IPV, would
experience. In an effort to cope with and reduce these
emotions, the person might use alcohol or other
drugs [Jacobsen et al., 2001; Simons et al., 2005;
Stewart, 1996]. In fact, post-traumatic stress disorder
(PTSD) and alcohol/drug abuse are highly comorbid

disorders that are functionally related [Chilcoat and
Breslau, 1998; Jacobsen et al., 2001; Stewart, 1996;
Stewart et al., 1998], and the model with the most
support to explain this association is the self-
medication model [Chilcoat and Breslau, 1998;
Jacobsen et al., 2001; Stewart, 1996; Stewart et al.,
1998]. In this model, alcohol and other drugs seem to
provide acute symptom relief of PTSD; in particular,
they seem to lessen the hyperarousal components
and facilitate forgetting traumatic memories through
their effects on the central nervous system [Chilcoat
and Breslau, 1998; Jacobsen et al., 2001; Stewart,
1996; Stewart et al., 1998, 1999,]. In other words,
alcohol and other drugs seem to be used in an effort
to self-medicate for the distressing symptoms of
PTSD [Chilcoat and Breslau, 1998]. Thus, PTSD
symptoms may serve as a mediator for any associa-
tion between sustaining IPV and alcohol/drug abuse.
In addition, it is well-documented that sustaining
physical abuse or witnessing interparental violence
during childhood can put one at risk for abusing
alcohol or other drugs [e.g., Liebschutz et al., 2002]
and for sustaining IPV [e.g., Stith et al., 2000]. Thus,
any model investigating the associations among

IPV and alcohol/drug abuse should consider any
potential trauma of previous childhood abuse.
Previous longitudinal research among female
victims of IPV and assault in general provide some
support for the hypothesized models [Kilpatrick
et al., 1997; Martino et al., 2005; Salomon et al.,
2002; Testa et al., 2003], yet there are some caveats.
For example, in a longitudinal population-based
sample of women, drug abuse, but not alcohol
abuse, may put one at risk for sustaining any kind of
assault; and sustaining an assault puts one at risk for
alcohol and drug abuse, a relationship that is
particularly strong for alcohol abuse [Kilpatrick
et al., 1997]. In a multiyear panel study of women
living with a male partner, drug use did not predict
subsequent IPV nor did IPV predict subsequent
drug use, but IPV did predict later heavy drinking
[Martino et al., 2005]. In a longitudinal random-
digit dial phone survey of Buffalo-area women, drug
abuse predicted subsequent IPV victimization; and
although alcohol abuse did not predict subsequent
victimization, IPV victimization did predict alcohol
abuse [Testa et al., 2003]. Among poor women in a
longitudinal study, sustaining IPV put one at risk

for abusing drugs, but not alcohol; sustaining child
abuse also contributed to drug abuse, PTSD was
only a weak mediator of the association between
sustaining IPV and drug abuse; and there was no
support for a model positing that alcohol/drug
abuse put one at risk for sustaining IPV [Salomon
et al., 2002].
Overall, there is support for IPV victimization
predicting subsequent alcohol abuse, some support
for IPV victimization predicting drug abuse, some
support for drug abuse predicting subsequent IPV
victimization, and no support for alcohol abuse
predicting IPV victimization. In addition, there is
support for child abuse as a contributor to drug
abuse and PTSD as a possible mediator. Given these
caveats, it is important to test models separately for
alcohol and drug abuse.
Although there is little research on the association
between alcohol/drug abuse and IPV victimization
among men, studies mentioned previously suggest
that such association exists [Simons et al., 2008].
Moreover, there are studies investigating whether
alcohol/drug abuse is linked with violent victimiza-

tion in general among males. For example,
2 Hines and Douglas
Aggr. Behav.
32
in adolescent males, problem alcohol use is a risk
factor for subsequent violent victimization as
assessed with longitudinal data [Thompson et al.,
2008], and cross-sectional studies show that experi-
encing a physical or sexual assault either within the
home or in general is associated with subsequent
drug abuse and that PTSD increases the risk of drug
abuse [Kilpatrick et al., 2000]. In addition, among
male college students, sustaining a sexual assault is
associated with a subsequent increased risk of using
alcohol or drugs [Amos et al., 2008]. Given these
findings, it is important to further investigate these
associations among men who sustain IPV.
Intimate Terrorism vs. Common Couple

Violence
In addition to studying these associations among
men who sustain IPV, it is also important to
investigate whether these associations may differ
among men who represent two different types of
IPV: intimate terrorism (IT) and common couple
violence (CCV). According to Johnson [Johnson,
1995, 2006; Johnson and Ferraro, 2000], IT is a type
of IPV that is characterized by frequent and severe
physical IPV and controlling behaviors, and has
traditionally been used to describe and is consistent
with samples of battered women seeking shelter. He
labeled the IPV found in community and popula-
tion-based samples CCV, which is characterized by
low-level (e.g., slapping, pushing), low-frequency
violence in a couple where both members are about
equally violent; this IPV is not part of an overall
pattern of control of one partner over the other, but
is the result of a conflict ‘‘getting out of hand.’’
This study utilizes both ‘‘help-seeking’’ and
‘‘community’’ samples of men with regard to IPV.
The help-seeking sample is comprised of men who
sustained IPV from their female partners and sought

help of some sort; the community sample is
comprised of a convenience sample of men recruited
from the community to participate in a study on
how men and women get along. In a previous
analysis that focused on describing the IPV in these
two samples [Hines and Douglas, 2010], we found
that the help-seeking sample conformed to
Johnson’s [1995, 2006; Johnson and Ferraro, 2000]
definition of IT; the frequency of physical IPV the
men sustained was comparable to the frequency with
which shelter samples of battered women sustained
physical IPV [Giles-Sims, 1983; Johnson, 2006;
McDonald et al., 2009; Okun, 1986; Straus, 1990];
the physical assaults were accompanied by high
levels of controlling behaviors, severe psychological
aggression, and physical injuries. Moreover, the
overwhelming majority of the physical arguments
were reportedly initiated by the female partner
[Hines and Douglas, 2010].
On the other hand, the 16% of the men in our
community sample who sustained physical IPV
conformed to Johnson’s [1995, 2006; Johnson and
Ferraro, 2000] conceptualization of CCV. These

men reported that they and their female partners
used low-level, low-frequency IPV at approximately
the same rates, with an equal likelihood that either
the man or his female partner hit first, and the
aggression did not involve frequent and severe
physical IPV or controlling behaviors [Hines and
Douglas, 2010].
Johnson [1995] argues that such help-seeking and
community samples are functionally different and
should, therefore, have different patterns of pre-
dictors and consequences of IPV. For example, he
would argue that the conceptual models outlined
above would be different between the community
and help-seeking samples of men. Therefore,
although we will test the above models on both
samples, we hypothesize that they will operate
differently between them. Moreover, Johnson would
argue that any potential consequences of IPV, such
as alcohol/drug abuse, would be more severe among
men in help-seeking samples vs. men in community
samples, because their experiences of IPV are much
more severe, and thus more traumatic. Therefore, in
this study, we hypothesized that in comparison to
men in the community sample who sustained either

CCV or no violence, alcohol/drug abuse would
be more severe among the men who sustained IT
(i.e., the help-seeking sample). Previous analyses of
these datasets did not focus on the associations
between alcohol/drug abuse and the IPV these men
experienced.
METHOD
Participants and Procedure
Two separate samples of male participants were
recruited for this study: a help-seeking sample and a
community sample. For both samples, the men had
to speak English, live in the United States, and be
between the ages of 18 and 59 to be eligible; they
also had to have been involved in an intimate
relationship with a woman lasting at least 1 month
in the previous year. In addition, to be eligible for
the help-seeking sample, the men had to have
sustained a physical assault from their female
partner within the previous year, and they had to
3Alcohol/Drug Abuse in Men Who Sustain IPV

Aggr. Behav.
33
have sought help/assistance for their partner’s
violence. Help/assistance was broadly defined and
included seeking help from formal sources, such as
hotlines, domestic violence agencies, the police,
mental health and medical health professionals,
lawyers, and ministers, to more informal help-
seeking efforts, such as talking with friends and
family members and searching the Internet for
information on IPV or support groups for IPV
victims in general or male IPV victims specifically.
The help-seeking sample of men (n 5 302) was
recruited from a variety of sources, including the
Domestic Abuse Helpline for Men and Women
(DAHMW; a U.S. national hotline specializing in
male victims of domestic violence), and online
websites, newsletters, blogs, and listservs that
specialized in treatment of IPV, male victims of
IPV, fathers’ rights issues, divorced men’s issues,

men’s health issues, and men’s rights issues. Men
who called the DAHMW seeking assistance and
who met the eligibility criteria were invited to
participate in this study either by calling a survey
research center to complete the interview over the
phone or by visiting the study website to complete
an anonymous secure version of the study ques-
tionnaire online. Men who saw an advertisement for
the study online were directed to the study website
to complete the online version of the study. Screener
questions regarding the study criteria were on the
first page of the survey, and men who were eligible,
given the stated criteria for the help-seeking sample,
were allowed to continue the survey. Men who did
not meet the eligibility requirements were thanked
for their time and were redirected to an ‘‘exit page’’
of the survey. Sixteen men completed the interview
over the phone; the remaining 286 completed it
online. Demographics of the help-seeking sample
can be found in Table I.
Participants also included 520 men from the
community. Approximately half the community
sample (n 5 255) was recruited to participate in a
phone version of the survey by a survey research

center, using a random digit dialing technique and
CATI administration. The interviewers attempted to
reach each phone number on 15 different days, at
different times of the day, and made call-back
appointments whenever possible. They also
made refusal conversion efforts when appropriate.
Because of low response rates (8%) during the first 2
months, advanced letters were sent to potential
participants informing them that they were ran-
domly selected to participate in a study sponsored
by the National Institutes of Health that was
focusing on how men and women get along and
that they would be contacted within a week by a
survey research center interviewer. The response rate
for the participants who received an advanced letter
was 15.5%. The overall response rate was 9.8%. The
other half of the community sample (n 5 265) was
recruited through a panel of survey participants
maintained by Survey Sampling, Inc. (SSI), to
complete an online version of the same survey.
Email invitations were sent to 16,000 male SSI panel
members inviting them to participate in a study on
how men and women get along. They were directed
to an anonymous, secure, online version of the

survey. The first page of the survey included screener
questions testing for eligibility (i.e., between 18 and
59 years of age; in an intimate relationship with a
woman lasting at least 1 month in the previous
year). Eligible men were able to continue to the
survey, whereas noneligible men were thanked for
their time. The survey was closed after we met our
target sample size of 265 men. Because data
collection ceased when the target goal for the
number of completed surveys was reached and we
did not wait for all men who received invitations to
complete the survey, response rates for the Internet
sample cannot be reliably calculated. Demographic
information on the full community sample (n 5 520)
can be found in Table I. Multivariate analyses
indicated that the only differences between the
phone and online community samples were that
men in the phone sample had more social support,
were less likely to score above a clinical cut-off for
PTSD symptoms, and were more likely to have ever
used drugs. There were no differences in IPV
victimization or perpetration. Further information
on the phone and online community samples that is
beyond the scope of the current analysis can be
found in Hines et al. [2010].

The methods for this study were approved by the
boards of ethics at the participating institutions. All
the men participated anonymously, were apprised of
their rights as study participants, and gave their
consent to participate before beginning the survey.
Steps were taken to ensure their safety: at the
completion of the survey, the participants were given
information about obtaining help for IPV victimiza-
tion and how to delete the history on their Internet
web browser.
Measures
Both the help-seeking and community samples
were given the same core questionnaires regarding
demographics, aggressive behaviors that they and
their female partners may have used in the previous
4 Hines and Douglas
Aggr. Behav.
34

year, more detailed information regarding their last
physical argument (if applicable), their mental
health, and various risk factors. The help-seeking
sample was given additional questions pertaining to
their specific help-seeking experiences in an aggres-
sive relationship and what prevents them from
leaving the relationship. Only the questionnaires
used in the current analyses will be described below.
Demographic information. Men were asked
basic demographic information about both themselves
and their partners, including age, race/ethnicity,
personal income, education, and occupation. Men
were also asked about the current status of their
relationship, the length of their relationship with
their partners, how long ago the relationship ended
(if applicable), and how many minor children were
involved in that relationship, if any.
Revised conflict tactics scales. The revised
conflict tactics scales (CTS2) [Straus et al., 1996] was
used to measure the extent to which the men in the

TABLE I. Demographics, Intimate Partner Violence Sustained,
PTSD, and Childhood Aggression Experiences
Help-seeking sample (n 5 302) Community sample (n 5 520)
% or M (SD) % or M (SD) w2 or t
Demographics
Age (in years) 40.49 (8.97) 43.68 (10.88) 4.52
��
Education
a
4.40 (1.56)
(n 5 300)
4.04 (1.72)
(n 5 514)
3.13

��
Income (in thousands) $50.44K (25.69)
(n 5 296)
$48.98K (26.13)
(n 5 508)
0.77
% white 86.8 84.8 0.59
% currently in a relationship 56.3% 95.8% 193.70
��
% with minor children 73.2% 45.3% 64.60
��
Length of relationship (in months) 97.90
(82.06)
164.90

(131.01)
8.93
��
% sustaining IPV
% sustaining controlling behaviors 93.4 20.0 412.20
��
% sustaining severe psychological aggression 96.0 13.7 526.31
��
% sustaining physical aggression 100.0 16.3 536.60
��
% sustaining injury in previous year 78.5 4.0 491.56
��
Mean ] of acts of IPV sustained among those sustaining IPV
] of controlling acts in previous year 42.62 (36.25)
(n 5 282)

11.36 (16.31)
(n 5 104)
11.64
��
] of severe psychological aggression acts in previous year 28.90
(26.20)
(n 5 290)
9.13 (13.26)
(n 5 71)
8.98
��
] of physically aggressive acts in previous year 46.72 (53.48)
(n 5 302)
12.22 (33.29)
(n 5 85)

7.27
��
] of injuries sustained in previous year 11.68 (15.61)
(n 5 237)
5.52 (11.42)
(n 5 21)
2.29
�
% using IPV
% using controlling behaviors 45.7 11.5 121.90
��
% using severe psychological aggression 40.1 10.4 100.44
��
% using physical aggression 55.0 13.8 159.19
��
% using injury in previous year 26.2 4.6 80.90

��
Mean ] of acts of IPV used among those using IPV
] of controlling acts in previous year 7.20 (8.99)
(n 5 138)
12.29 (16.99)
(n 5 60)
2.19
�
] of severe psychological aggression acts in previous year 5.74
(8.59)
(n 5 121)
6.07 (14.49)
(n 5 54)
0.19
] of physically aggressive acts in previous year 7.71 (14.25)

(n 5 166)
8.68 (24.21)
(n 5 72)
0.40
] of injuries partner sustained in previous year 5.19 (6.40)
(n 5 79)
6.96 (12.01)
(n 5 24)
0.69
Levels of PTSD symptoms and childhood aggression
experienced
PCL score 46.56 (14.22) 20.43 (8.28) 29.19
��
% sustaining child physical aggression 46.8 35.3 10.65
��

% witnessing IPV between parents 21.5 14.3 7.03
��
a
Educational status: 1 5 less than high school; 2 5 high school
graduate or GED; 3 5 some college/trade school; 4 5 2-year
college graduate; 5 5
4-year college graduate; 6 5 some graduate school; 7 5 graduate
degree.
�
Po.05; ��Po.01; ��Po.001.
Aggr. Behav.
35
study used and sustained psychological, physical,
and sexual aggression, and injuries in their relation-
ships. The items used for this study included five

items assessing minor physical aggression (e.g.,
grabbing, shoving, slapping); seven items assessing
severe physical aggression (e.g., beating up, using
knife/gun) that were combined into a total physical
aggression scale; and six items assessing injuries
[e.g., having a small cut or bruise, broken bone,
passing out). The eight CTS2 items regarding
psychological aggression were supplemented with
seven items from the Psychological Maltreatment of
Women Inventory [Tolman, 1995]. To investigate
the factor structure of this combined psycho-
logical aggression scale, a factor analysis that
combined the two samples was conducted using
the victimization items [see Hines and Douglas,
2010, for further details on this analysis). The factor
analysis revealed that there were three subscales:
Minor Psychological Aggression (e.g., insulting/
swearing, shouting/yelling, doing something to spite
partner), Controlling Behaviors (e.g., not allowing
to leave the house, monitoring time and where-
abouts), and Severe Psychological Aggression (e.g.,
threatening to harm partner, intentionally destroy-
ing something belonging to partner). For this study,
only the controlling behaviors and severe psycholo-
gical aggression scales were used because they

theoretically differentiate IT from CCV [Johnson,
1995].
Participants responded to items depicting each of
the conflict tactics by indicating the number of
times these tactics were used by the participant and
his partner in the previous year. Participants
indicated on a scale from 0 to 6 how many times
they experienced each of the acts in the previous
year, 0 5 0 times; 1 5 1 time; 2 5 2 times; 3 5 3–5
times; 4 5 6–10 times; 5 5 11–20 times; and 6 5 more
than 20 times. These data were then trans-
formed in order to obtain an approximate count of
the number of times each act occurred in the
previous year, using the following scale: 0 5 0 acts
in previous year; 1 5 1 act in the previous year; 2 5 2
acts in the previous year; 3 5 4 acts in the previous
year; 4 5 8 acts in the previous year; 5 5 16 acts in
the previous year; and 6 5 25 acts in the previous
year.
The CTS2 has been shown to have good
construct and discriminant validity and good
reliability, with internal consistency coefficients
ranging from .79 to .95 [Straus et al., 1996].

Reliability statistics for these samples were
.82 for both the Controlling Behaviors and
Severe Psychological Aggression scales, .92 for the
Physical Aggression scale, and .68 for the Injury
scale.
Abusive childhood experiences of the
participant. Childhood abusive experiences were
assessed using two questions that condensed the
eight items from the violence socialization (VS) scale
of the Personal and Relationships Profile [Straus
et al., 1999]. Participants indicated the extent to
which they agreed or disagreed (1 5 strongly dis-
agree, 4 5 strongly agree) with each statement:
‘‘When I was less than 12 years old, I was spanked
or hit a lot by my mother or father’’ (sustaining child
physical aggression), and ‘‘When I was a kid, I saw
my mother or father kick, punch, or beat up their
partner’’ (witnessed interparental IPV). Reports of
the psychometric properties of the full VS scale
indicate adequate validity and an overall a of .73
[Straus and Mouradian, 1999].
Posttraumatic stress symptoms. The PTSD

Checklist (PCL) [Weathers et al., 1993] is a 17-item
self-report measure of the severity of PTSD symp-
tomology. Items reflect three symptom clusters:
reexperiencing, numbing/avoidance, and hyperarou-
sal. Consistent with the concept of PTSD and per
the instructions of the PCL, questions were
anchored to one potentially traumatic event: parti-
cipants were asked to think about their worst
argument with their female partner, and then
indicate the extent to which they were bothered
by each symptom in the preceding month using a
5-point scale (1 5 not at all, 5 5 extremely). The
items were then summed to create a continuous
measure of PTSD symptoms. One item, ‘‘Feeling as
if your future will somehow be cut short,’’ was not
included in the survey because participants reported
that they did not understand the item during pilot
testing of the instrument. The PCL has been
validated for use in both combat and civilian
populations and the civilian version was used for
this study. The PCL has been shown to have
excellent reliability [Weathers et al., 1993] and
strong convergent and divergent validity [Blanchard
et al., 1996; Ruggiero et al., 2003]. For these
samples, the a was .97.

Alcohol and drug abuse. Alcohol and drug
abuse were measured using a scale developed for the
National Women’s Study to assess the association
between IPV victimization and alcohol/drug abuse
among female victims [Kilpatrick et al., 1997]. The
scale included up to 19 items asking respondents
about their use and abuse of alcohol and illicit drugs
(i.e., marijuana, cocaine, methamphetamines, crack,
LSD, heroin, or other such drug) in their lifetimes
and in the past year, and included items regarding
6 Hines and Douglas
Aggr. Behav.
36
negative experiences resulting from alcohol abuse.
Consistent with Kilpatrick et al.’s [1997] guidelines
for scoring this scale, we measured alcohol abuse
within the past year by two indicators that
approximated the diagnostic criteria for the

Diagnostic and Statistical Manual of Mental
Disorders IV [American Psychiatric Association,
1994]: (1) participants who answered affirmatively
to any of the six questions on negative experiences
(e.g., getting in trouble with the police or a boss)
within the past year because of alcohol were
classified as meeting the criteria for alcohol abuse
in the past year, and (2) frequency of intoxication
within the past year: participants were asked to
indicate how frequently they were intoxicated
in the past year on a scale from 0 5 never to
7 5 every day/almost every day.
Similarly, according to the guidelines established
by Kilpatrick et al. [1997], drug abuse was measured
by two indicators that approximate the frequency
of usage considered significant by the Diagnostic
Interview Schedule substance abuse screen
[Robins et al., 1988]: (1) if participants indicated
they used any illegal drugs more than four times in
the past year, they were considered nonexperi-
mental users/drug abusers, and (2) actual frequency
of drug use within the past year from 0 5 never to
3 5 more than ten occasions. This scale has demon-
strated excellent construct validity [Kilpatrick et al.,

1997].
RESULTS
Table I presents the demographics of the help-
seeking and community samples, and descriptive
information for all predictor, mediator, and out-
come variables. A full discussion of these samples
can be found in previous analyses of this dataset
[e.g., Hines and Douglas, 2010].
Hypothesis 1: Differences in Proposed
Conceptual Models
Bivariate correlations among IPV and alco-
hol/drug abuse. To test Hypothesis 1, we
first performed a series of correlational analyses
on the alcohol/drug abuse and IPV variables
(Table II). For each sample separately, we correlated
the frequency with which the participants
sustained all four forms of IPV with the four
alcohol/drug abuse variables: alcohol abuse
in the past year, frequency of intoxication in
the past year, drug abuse in the past year, and
frequency of drug use in the past year. As shown, T

A
B
L
E
II
.
B
iv
a
ri
a
te
C
o
rr
e
la
ti
o
n
s
A

m
o
n
g
S
u
st
a
in
e
d
IP
V
a
n
d
A
lc
o
h
o
l/
D
ru

g
A
b
u
se
fo
r
B
o
th
S
a
m
p
le
s
H
el
p
-s
ee
k

in
g
sa
m
p
le
(n
5
3
0
2
)
C
o
m
m
u
n
it
y
sa
m
p

le
(n
5
5
2
0
)
C
o
n
tr
o
ll
in
g
b
eh
a
v
io
rs

S
ev
er
e
p
sy
ch
o
lo
g
ic
a
l
a
g
g
re
ss
io
n
P
h

y
si
ca
l
a
g
g
re
ss
io
n
In
ju
ri
es
C
o
n
tr
o
ll
in

g
b
eh
a
v
io
rs
S
ev
er
e
p
sy
ch
o
lo
g
ic
a
l
a

g
g
re
ss
io
n
P
h
y
si
ca
l
a
g
g
re
ss
io
n
In
ju
ri

es
A
lc
o
h
o
l
u
se
/a
b
u
se
A
b
u
se
d
a
lc
o
h
o

l
in
p
a
st
y
ea
r
.0
8
�
.0
3
�
.0
5
�
.0
4

.1
8
�
�
�
.1
4
�
�
�
.1
6
�
�
�
.1
2
�
�
F

re
q
u
en
cy
o
f
in
to
x
ic
a
ti
o
n
in
p
a
st
y
ea
r

.0
0
�
.0
8
.0
2
.0
4
.1
1
�
.1
2
�
�
.2
4

�
�
�
.1
8
�
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�
D
ru
g
u
se
/a
b
u
se
A
b
u
se
d

d
ru
g
s
in
p
a
st
y
ea
r
.0
1
�
.1
1
�
.0
6

�
.0
2
.2
1
�
�
�
.1
3
�
�
.1
3
�
�
.0
1
F
re

q
u
en
cy
o
f
d
ru
g
u
se
in
p
a
st
y
ea
r
.0
0

�
.1
2
�
�
.0
5
�
.0
5
.2
5
�
�
�
.1
7
�
�
�

.1
8
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�
.0
7
�
P
o
.0
5
,
�
�
P
o
.0
1
,
�
�
�

P
o
.0
0
1
.
Aggr. Behav.
37
there was only one significant association for the
help-seeking sample, and it was in the opposite
direction hypothesized. For the community sample,
all but two of the associations were significant. The
results indicate that there is a dose–response
relationship between alcohol/drug abuse and sus-
taining IPV for the community sample, but not the
help-seeking sample.
Path models. Because only the community

sample showed associations among alcohol/drug
abuse and sustaining IPV, we then investigated
the hypothesized path models for the community
sample only (Fig. 1).
1
In the interest of parsimony,
we combined the scores on the two childhood
physical aggression measures (sustaining child
physical aggression and witnessing interparental
IPV) into a variable called Child Maltreatment.
For sustaining IPV, we only used the frequency
with which they sustained physical aggression
because CCV, the type of IPV that occurs
among a minority of couples in a community
sample, is not theoretically tied to controlling
behaviors and severe psychological aggression
[1995, 2006; Johnson and Ferraro, 2000]. Finally,
for the alcohol and drug abuse variables, we
used the frequency of intoxication and frequency
of drug use in the past year variables, respectively, to
have continuous outcome measures for our path
modeling.
As indicated, in the first model, we hypothesized

that child maltreatment would predict alcohol/drug
abuse, which would then predict sustaining IPV in
adulthood; this latter association would be partially
mediated by the use of IPV. In the second model, we
predicted that child maltreatment would predict
sustaining IPV, which would then predict alcohol/
substance abuse, and this latter association would be
partially mediated by levels of PTSD symptoms.
These full models were tested for alcohol and drug
abuse separately, and each model was evaluated
using four fit measures—w2, RMSEA, NFI, and
GFI—as recommended by Tabachnik and Fidell
[2006]. This method ensures a model fit is tested
from several different perspectives [Meyers et al.,
2006]. Nonsignificant paths were pruned one at a
time until an excellent fitting model was achieved.
This end model was compared with the original
model on their AIC and ECVI; smaller AIC values
represent better fitting models and smaller ECVI
values represent the greatest potential for replication
[Byrne, 2010].
Within the community sample, five cases (0.1%)

were removed because of incomplete data on
the child maltreatment measures. For the frequency
of drug usage variable, two cases (0.4%)
were missing and replaced with the mean on that
variable. For the frequency of intoxication variable,
seven cases (1.4%) were missing and replaced
with the mean on that variable. For physical
aggression used, there was one extreme outlier that
was replaced with a value that was one act higher
than the next closest value, as per Tabachnik and
Fidell [2006]. Similarly, for physical aggression
sustained, there were two extreme outliers that were
replaced with values that were one and two acts
higher than the next closest value. Models were
tested both with and without the outliers replaced
and there were some slight differences in the path
estimates (but no differences in model fits or
significance of path estimates); therefore, the results
for the models with the outliers replaced are
presented.
Initially, the full model for each analysis was
evaluated for its adherence to the assumption of
Model 1: Alcohol/Drug Abuse Predicts Sustaining IPV

Child
Maltreatment
Alcohol/Drug
Abuse
Used IPV
Sustained IPV
Model 2: Sustained IPV Predicts Alcohol/Drug Abuse
Child
Maltreatment
Sustained IPV
PTSD
Symptoms
Alcohol/Drug
Abuse
Fig. 1. Hypothesized path models for the associations between

alcohol/
drug abuse and sustaining IPV among community sample only.
Model
1: alcohol/drug abuse predicts sustaining IPV. Model 2:
sustained IPV
predicts alcohol/drug abuse.
1
To be certain, we did run the same models with the help-seeking
sample as we did with the community sample. As expected,
none of
the models were good fits to the data, even when nonsignificant
parameters were pruned. In fact, for the models where we were
using
alcohol/drug abuse to predict IPV victimization, the only
significant
paths were from IPV perpetration to IPV victimization, and for

the
models where we predicted alcohol/drug abuse from IPV
victimization,
the only significant paths were from IPV victimization to levels
of
PTSD symptoms and from levels of PTSD symptoms to drug
abuse.
8 Hines and Douglas
Aggr. Behav.
38
multivariate normality. Mardia’s [1970, 1974]
normalized estimate of multivariate kurtosis equaled
258.39 for the model where alcohol abuse predicted
IPV victimization, 98.89 for the model where
IPV victimization predicted alcohol abuse, 271.65
for the model where drug abuse predicted IPV

victimization, and 109.18 for the model where IPV
victimization predicted drug abuse. All these values
are well above the standard cut-off of 5 and
indicated nonnormal distributions [Bentler, 2005].
Therefore, we employed the bootstrapping proce-
dure for estimating standard errors and reducing
bias in our estimates of parameters and their
significance. Although not without its limitations,
bootstrapping is a procedure that is routinely used
when estimating path models with nonnormal data
[Byrne, 2010].
For alcohol abuse predicting IPV sustained, the full
hypothesized model achieved a moderate-to-good fit to
the data (w2 (2)512.27, P5 .002; NFI50.96;
GFI50.99; RMSEA5 .10, AIC528.27, ECVI5
.06). The final parsimonious model achieved an
excellent fit: w2 (1)50.05, P5 .82; NFI51.00;
GFI51.00; RMSEA5 .00, AIC512.00, ECVI5 .02.
This final model represents a significant improvement
in the w2 fit of the model (D w2 (1)512.23, P5 .0005),
and the parameter estimates for this model are shown
in Figure 3. Child maltreatment dropped out of the
model and the influence of alcohol intoxication on
sustaining IPV was fully mediated by the use of IPV.

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