Toward a Biopsychosocial Model of Domestic Violence
Author(s): Patrick C. McKenry, Teresa W. Julian and Stephen M. Gavazzi
Reviewed work(s):
Source: Journal of Marriage and Family, Vol. 57, No. 2 (May, 1995), pp. 307-320
Published by: National Council on Family Relations
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PATRICKC. MCKENRY
TERESAW. JULIAN
The Ohio State University
The Ohio State University*
STEPHENM. GAVAZZI
The Ohio State University**
Towarda Biopsychosocial Model
of Domestic Violence
A sample of 102 married men were interviewed
and physically assessed in an attempt to develop
a biopsychosocial model of male domestic violence. Because the dependent variable, domestic
violence, was censored, Tobit analysis was used
to identify significant predictors. When analyzed
separately, each domain was significantly related
to male domestic violence. However, when all domains were considered together, only the biological and social domains yielded independent effects. Significant independent variables included
alcohol, family income, and relationship quality,
with testosterone approaching significance.
It is widely accepted that the etiology of family
violence is a multifaceted phenomenon that can
Department of Family Relations and Human Development,
Department of Black Studies, and The Ohio Agricultural Research and Development Center, 315 Campbell Hall, 1787
Neil Avenue, The Ohio State University, Columbus, OH
43210.
*Department of Psychiatry, Upham Hall, 473 West 12th Avenue, The Ohio State University, Columbus, OH 43210.
**Department of Family Relations and Human Development,
Marriage and Family Therapy Program, 315 Campbell Hall,
1787 Neil Avenue, The Ohio State University, Columbus, OH
43210.
Key Words: biopsychosocial, domestic violence, spouse abuse.
best be understood from a multidisciplinary perspective. No single theory or discipline has been
adequate in thoroughly explaining spouse abuse
(Gelles & Loeske, 1993; Hotaling & Sugarman,
1986; Howell & Pugliesi, 1988). Reviews of the
literature on domestic violence typically have utilized three groupings of theories to account for
the separate contributions of biological, psychological, and sociological perspectives (e.g., Steinmetz, 1987; Van Hasslet, Morrison, Bellack, &
Hersen, 1988). However, to date, no studies have
attempted to integrate these perspectives into
what is commonly referred to as a biopsychosocial perspective.
THE BIOPSYCHOSOCIAL
PERSPECTIVE
The biopsychosocial perspective is an attempt to
understandhealth and illness through an appreciation of how biological, psychological, and social
elements persist in affiliation with one another.
Engel's (1977, 1980) innovative work within this
perspective has served to highlight the limitations
of reducing explanations of dysfunction to any
one of its three major components (biological
considerations, psychological variables, or social
context factors), and to emphasize the great benefits derived from their simultaneous inclusion.
From the standpoint of a physician, Engel (1977)
wrote:
Journal of Marriage and the Family 57 (May 1995): 307-320
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307
Journal of Marriage and the Family
308
The boundariesbetweenhealthand disease,between well andsick, arefarfromclearandnever
will be clear, for they are diffused by cultural,
social, andpsychologicalconsiderations.... By
evaluatingall of the factorscontributingto both
illness and patienthood,ratherthan giving primacy to biologicalfactorsalone, a biopsychosocial model would make it possible to explain
why some individuals experience as "illness"
conditions that others would regardmerely as
"problemsof living," be they emotional reactions to life circumstancesor somaticsymptoms
(pp. 132-133).
A more recent formulation of this perspective
is presented by McDaniel, Hepworth, and Doherty (1992), who utilized the term biopsychosocial
systems model to highlight the interactive nature
of biological, psychological, and social phenomena regarding health and illness. According to this
model, such phenomena are seen as not only existing in an arranged hierarchical ordering, but
also as having a consistent and reciprocal impact
on one another. Here, biological system factors
are thought to exist in and interact with psychological system factors, both of which are hypothesized to exist in and interact with family and other
social system factors. Hence, descriptions that result within this framework are not simply summative but rather assert multiplicative relationships
among these factors.
From this perspective, all theoretical, empirical, and clinical efforts must account for the complex interplay of biological, psychological, and
social facets of a given intrapsychic or interpersonal dysfunction. Hence, psychiatry and associated medical models, schools of psychology, various family systems theories, and sociological
models all contain their own unique limitations
because of their disciplinary viewpoint on dysfunction. In addition, those who subscribe in principle to a biopsychosocial model often note how
difficult the model is to carry out in practice, as
exemplified in literature emanating from a variety
of contexts such as pediatric illness (Wood,
1993), medical education (Engel, 1982), family
medicine (Doherty, Baird, & Becker, 1986), psychiatry (Amchin, 1991), and family psychoeducational approaches (Moltz, 1993).
In the area of interpersonal violence, some theoretical work has been done that attempts to integrate the biopsychosocial aspects of interpersonal
violence. Dutton (1985) utilized a variety of theoretical frameworks in presenting an ecologically
nested theory of interpersonal violence, including
factors related to genetic predisposition, physio-
logical arousal, emotional labeling, power issues,
neighborhood influences, unemployment, and the
effect of cultural and societal characteristics.
Also, treatment models can be found that
touch on all aspects of the biopsychosocial model.
For instance, Goldner and colleagues (Goldner,
Penn, Sheinberg, & Walker, 1990) have utilized a
family systems orientation to conceptually link
the biological, psychological, and social roots of
skewed gender identities in partners presenting
with domestic violence complaints. Further, the
adoption of a biopsychosocial approach is consistent with newer federal funding initiatives that
recognize and encourage interdisciplinary research and intervention approaches, in essence directing attention to biological components in addition to social science factors.
The research literature on interpersonal violence has been moving toward the integration of
these three perspectives. While not fully biopsychosocial in their conceptual underpinnings, some
studies within the interpersonal violence literature
have generated data that directly speak to the interactive nature of certain biological, psychological, and social phenomenon. For example, Dabbs
and Morris (1990) found that relationships between testosterone and antisocial tendencies in a
sample of males were moderated by their socioeconomic status. Julian and McKenry (1993) reported that men's intimate relationship quality
and depression levels predicted male violence toward female partners, although alcohol usage and
testosterone were not significant predictors in this
study. And Leonard and Blane (1992), in a national sample of young men, found that the relationship between alcohol use and marital aggression was moderated by both the male's level of
hostility and level of marital satisfaction.
The purpose of this study is to develop a model
that incorporates salient predictors from the biological, psychological, and social domains that traditionally have been associated with domestic violence. The relative contribution of each domain, as
well as selected interactions within and across domains, is also assessed. This article focuses on
husbands' abuse toward wives because this is by
far the most common form of domestic violence
(Stets & Straus, 1989; Van Hasslet et al., 1988).
OVERVIEW OF THE CONCEPTUAL DOMAINS
Biological Factors
Meyer-Bahlburg (1981) contended that to understand aggression, there is a need to increase our
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309
Biopsychosocial Model
understanding of the role of androgens. A recent
comprehensive literature review has indicated
that, in a majority of studies, high testosterone
levels tend to covary with high probability of aggressive behaviors, dominance status, and pathologic forms of aggression (Archer, 1991; MeyerBahlburg, 1981), especially with antisocial populations (Dabbs, Frady, Carr, & Besch, 1987;
Dabbs, Ruback, Frady, Hopper, & Sgoutas, 1988;
Udry, 1989). For example, Rada (1978), in a
study of rapists, child molesters, and normal controls, found significantly elevated plasma testosterone levels in subjects judged most violent.
In a normative sample of over 4,000 male
United States military veterans, Dabbs and Morris
(1990) found that individuals higher in testosterone more often reported the following: having
trouble with parents, teachers, and classmates;
being assaultive toward other adults; going
AWOL in the military; using hard drugs, marijuana, and alcohol; and having more sexual partners.
Udry (1989) also found that testosterone levels
were related to a variety of problem behaviors
among a sample of male adolescents.
Studies of the relation between testosterone
and marital relations have focused on coital frequency but little else (Booth & Dabbs, 1993). Because testosterone has consistent and moderately
strong links with aggression, dominance, depressed occupational achievement, and antisocial
behavior such as fighting, nontraffic arrests, drug
use, and sensation-seeking, it would appear that
elevated testosterone has the potential to affect
marriage adversely (Booth & Dabbs, 1993). The
recurring link between testosterone and aggression and antisocial behavior could mean that men
with high testosterone levels tend to carry contentious and hostile behavior into relationships
with the opposite sex. Booth and Dabbs (1993)
found in their sample of former servicemen that
testosterone was positively and linearly related to
every aspect of marital quality, including hitting
or throwing things at spouses. Similarly, Julian
and McKenry (1989) found a negative relationship between testosterone and marital happiness
in a study of middle-aged males.
Another biological indicator of violent behavior is serotonin-the ubiquitous neurotransmitter
that modulates the action of other brain chemicals. A variety of violent, impulsive behaviors has
been associated with low levels of serotonin as
measured through prolactin levels (Burrowes,
Halles, & Arrington, 1988; Coccaro et al., 1989).
Serotonin, however, does not covary with testos-
terone. Testosterone is thought to be more strongly correlated with outward-directed aggressiveness and lack of socialization than it is with impulsiveness, whereas serotonin is hypothesized to
be related to impulsive aggression (Virkkunen &
Linnoila, 1993).
Alcohol as a chemical substance has been
clearly linked to aggression, yet any direct causal
relationship between alcohol use and aggression
has proved difficult to demonstrate (Collins,
1986; Fagan, Barnett, & Patton, 1988; Lindman,
van der Pahlen, Ost, & Eriksson, 1992). In terms
of domestic violence per se, alcohol use has been
associated with 25% to 85% of cases (Kantor &
Straus, 1987). Explanations generally have been
of two overly simplistic types (Pernanen, 1991).
The first is a pharmacological approach, which
asserts that postdrinking violence results from alcohol acting as a catalyst for physiological
changes that lead to disinhibited behavior; however, such explanations fail to identify the internal
physiological mechanisms and overlook the influence of social processes on behavior. The second,
a sociocultural approach, focuses on learned and
shared beliefs from the cultural milieu that allow
drinkers to place the responsibility for violent behavior on alcohol. What is clear from the research
is that the relationship between alcohol and violence is shaped in ways as yet undetermined by a
combination of individual, situational, and sociocultural factors that mediate the physiological effects of alcohol consumption (Martin, 1992).
Some recent data have attempted to link
testosterone levels to alcohol in the etiology of
spouse abuse. Data indicate that men with high
levels of testosterone are more apt to suffer from
alcohol abuse (Dabbs & Morris, 1990). Udry
(1989) concluded from his studies of testosterone
among adolescent males that testosterone increases susceptibility to alcohol and that hormone levels interact with social variables in predicting a
variety of problem behaviors. Studies of squirrel
monkeys (Winslow & Miczek, 1985; Winslow,
Ellingboe, & Miczek, 1988) indicate that testosterone may activate alcohol-sensitive brain mechanisms involved in aggressive behavior. Lindman
et al. (1992) found that in abusive males high levels of testosterone often precede alcohol abuse,
although the use of alcohol itself results in a suppression of testosterone.
A similar interaction has been found in terms
of serotonin levels. Low serotonin levels are associated with a tendency to exhibit impulsive violent behavior under the influence of alcohol. This
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Journal of Marriage and the Family
is especially true for those with psychiatric diagnoses such as antisocial personality disorders
(Virkkunen & Linnoila, 1993).
Social Factors
A social perspective on domestic violence places
physiological and psychological variables within
a wider explanatory framework that considers the
impact of social institutions and social structures
on social behavior (Gelles, 1993b). Empirically,
much of this work has been centered in a social
stress or life events paradigm.
Gelles (1987) stated that a consistent finding
in domestic violence research is that violence is
highly related to social stress. Life events research has indicated that negative life events, especially those threatening the status of the traditional male role, are highly related to spousal
abuse (Gelles, 1989; Steinmetz, 1987). According
to stress theory, stress reactions such as violence
are mediated by coping resources; those men with
lower incomes, poorer marital quality, less social
support, and alcohol abuse have been found to be
most vulnerable to violent reactions (Gelles,
1994; Steinmetz, 1987).
Marital quality can serve as both a stressor and
resource in the etiology of domestic violence.
Gelles (1974) and Rounsaville (1978) have found
that almost one-half of all cases of domestic violence are preceded by sudden transitions in intimacy. Leonard and Blane (1992) and Pernanen
(1976) noted that marital conflict precedes marital
aggression and that marital conflict may interact
with alcohol use in predicting domestic violence.
Goode (1971) contended that as marriages decline
in satisfaction, a growing sense of anger and frustration emerges that increases the potential for violence. Inability to communicate and negotiate
conflict has been found to be highly related to
physical violence between spouses (Steinmetz,
1978). Feminists and others view male abuse of
female intimates as coercive control, growing out
of a threat to male superior status in the marital
relationship. Husbands who acknowledge and relate positively to their wife's autonomy are least
at risk for violent behaviors (Steinmetz, 1987;
Yllo, 1993).
Social support, in general, is a major insulator
for family violence. The ability to call on friends,
family, and community for assistance appears to
mediate violent reactions to stress (Gelles, 1994;
Steinmetz, 1987). In general, the more a family is
integrated into a community, the less likelihood
there is of violent behaviors (Milner & Chilamkurti, 1991; Straus, Gelles, & Steinmetz,
1980).
Lower income males appear far more vulnerable to violent reactions than upper income males,
although violence is by no means limited to lower
income groups (Gelles & Straus, 1988; Straus et
al., 1980). It is suggested that members of the
middle class are socialized to mediate conflicts
and are more likely to rely on verbal skills to settle marital disputes (Steinmetz, 1978). Lower income groups are also faced with more negative
life events and fewer resources to mediate the impact of such events (Gelles, 1993a; Milner &
Chilamkurti, 1991; Straus et al., 1980).
Psychological Factors
After rejecting psychological approaches to understanding domestic violence that were based on
early work characterizing violent behaviors as a
form of pathology, recent work has empirically
and conceptually validated a psychological analysis of domestic violence (Hotaling & Sugarman,
1986; O'Leary, 1993). O'Leary (1993) concluded
from his own work and that of others that personality traits or disorders play a role in the etiology
of domestic violence. Although such factors have
small, but statistically significant, effects at lower
levels of physical violence, men who are involved
in higher levels of physical aggression have much
higher levels of psychological disorders than men
in the general population. Psychological styles or
disorders most often identified include impulsivity, suspicion of others, antisocial behavior, and
compulsivity (O'Leary, 1993).
Abram (1989) contended that antisocial disorders may trigger violent behaviors often associated with alcoholism. She noted, however, that antisocial behavior has rarely been controlled for in
studies of violence. And, as noted above, such
disorders may interact with both testosterone and
serotonin to predict violent behaviors (Virkkunen
& Linnoila, 1993). From a more normative, life
events perspective, psychological functioning is
viewed as a resource that mediates the stress response to stress-producing events (Steinmetz,
1987).
Based on this review of the biopsychosocial
domains related to male domestic violence, we
hypothesized that each domain would be independently related to male violence and that each domain would significantly add to the variance accounted for in a model containing all three do-
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Biopsychosocial Model
mains. Because of the strong research support for
social factors as predictors of domestic violence,
it was proposed that this domain would account
for more variance in the dependent measure than
would psychological factors after the biological
base was entered. Also, the following selected interactions within and across domains were hypothesized to contribute additional variance to the
dependent measure: testosterone x alcohol use,
prolactin x alcohol use, hostility x alcohol use,
hostility x prolactin, testosterone x hostility, and
relationship quality x alcohol use.
METHODS
Subjects
A total of 105 males (and their marital partners)
were interviewed to test the hypotheses of this
study. Three subjects were eliminated from the
final data analysis because of incomplete interviews, resulting in a final sample size of 102. In
order to be eligible to participate in this study,
couples had to be married or considered married
by common law (a minimum of 7 years of cohabitation). Thirty-four of the dyads were defined as
violent, and 68 were defined as nonviolent according to scores on the Conflict/Tactics Scale (Straus,
1979), indicating male physical violence toward a
marital partneras reported by either spouse in the
past year. The demographic characteristics of the
sample are presented by violence status in Table 1.
The groups were similar in terms of all demographic characteristics with the exception of family income. The mean income (M = $26,644) for
the violent group was significantly (p < .001) less
than the nonviolent group (M = $44,539). The
mean age of the violent group was 34.76 (SD =
9.71), and the mean age of the nonviolent group
was 36.97 years (SD = 9.70). The violent males
were married an average of 8.15 years (SD =
7.88), whereas the nonviolent males were married
an average of 9.18 years (SD = 8.42). Most study
participants were Caucasian, reported being either
Protestant or Catholic, and self-evaluated their
health status as good or excellent. In addition, the
sample reported similar numbers of children,
years of education, and years lived with their marital partner.
Procedures
These dyads were purposefully recruited through
mental health center and therapist referrals and
TABLE 1. MEANS AND PERCENTAGES OF SELECTED
DEMOGRAPHIC CHARACTERISTICSOF STUDY PARTICIPANTS
Violent
Variable
Males
(n = 34)
(n = 68)
34.76 (9.71)
Age
Income
$26,644 ($15,753)
Education
14.03 (2.34)
Numberof
8.15 (7.88)
years married
Numberof
children
Nonviolent
Males
36.9 (9.70)
$44,539 ($22,327)
14.85 (2.1)
1.56 (1.24)
9.18 (8.42)
1.31 (1.27)
Race
Caucasian
Hispanic
Native American
AfricanAmerican
85%
0%
3%
12%
88%
2%
0%
10%
Religion
Protestant
Catholic
Moslem
Jewish
Atheist
Agnostic
Other
None
44%
21%
0%
3%
3%
3%
12%
15%
46%
19%
2%
6%
0%
3%
12%
13%
Health status
Excellent
Good
Fair
Poor
29%
50%
15%
6%
38%
47%
10%
4%
Note: Standard deviations are shown in parentheses
following means.
through newspaper advertisements in a large,
Midwestern city. The request indicated that marital couples were sought to participate in a study
of physical health and marital relationships. The
vast majority of the dyads were obtained through
newspaper advertisements (n = 93); only nine
were therapeutic referrals. In return for their participation, potential subjects were promised $60
per couple ($30 for each spouse). Utilizing data
from the authors' preliminary study, a medium effect size (f-square = .15) was used to calculate the
necessary sample size.
The couples were initially screened by telephone for marital status and relationship quality
in an attempt to get a larger number of maritally
distressed couples. It was predicted that many of
the distressed couples would also manifest violent
behaviors. After the screening, an appointment
was scheduled with each dyad for an hour-long
face-to-face interview, the administration of a 15minute paper and pencil questionnaire, and the
drawing of a blood sample from the male. All
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Journal of Marriage and the Family
subjects were individually interviewed by clinically trained interviewers, matched by sex of the
subject. Male subjects were scheduled so that a
sample of blood could be drawn between 9:00
a.m. and 10:00 a.m. The scheduling of the data
collection was necessary to control for circadian
influences on plasma testosterone levels. At the
time of the blood draw, various other health measures were taken (i.e., blood pressure, pulse,
urine, etc.). Data collection for all dyads took
place at a university medical research center, and
all health measures were obtained by registered
nurses.
Instrumentation
Participants were asked to respond to a series of
largely forced-choice interview questions and
paper and pencil instrumentation. In addition, the
blood serum of the males was analyzed for testosterone and prolactin levels as well as for illicit
drug use. Use of prescription drugs was determined through responses to questions regarding
general health status.
Violence. The Conflict/Tactics Scale (CTS;
Straus, 1979) was used to indicate the extent and
level of violence of males toward marital partners. The CTS has been used and refined in a
number of studies of intrafamily violence (cf.
Allen & Straus, 1980; Giles-Sims, 1983; Straus &
Gelles, 1986). This 18-item inventory taps several
categories of conflictual behavior including: (a)
not physically violent, (b) indirect threats of violence, (c) direct threats of violence, and (d) severe
violence. Items are organized from least to most
violent, ranging from discussing the issue calmly
to using a knife or gun, and yield an overall violence score or a very severe violence score, depending upon the severity of the items included
(Straus, 1979). Statements that represent each category are measured by the length of time since
the behavior last occurred (i.e., 2, 4, 8, or 12
months ago). In this study only the items from the
subscale of males self-reporting physical violence
toward the marital partner and from the subscale
of females reporting male partner physical violence were used. The spouses' scores were
summed to avoid underreporting associated with
male self-report of violent behaviors (Walker,
1984). Instead of dichotomous scores (violent/
nonviolent), cumulative scores were used because
of their greater sensitivity to changes in the independent variables (Makepeace, 1983).
Alcohol. The CDTect is a method for quantitative
determination of carbohydrate deficient transferrin (CDT) in human serum. CDT is a biochemical
marker of value in the diagnosis and management
of individuals at high risk of alcohol abuse and alcoholism. Normalization of CDT occurs only
after approximately 15 days of abstinence. The
CDTect assay has demonstrated a clinical sensitivity of 82% and a specificity of 97%, based on a
total of 2,500 individuals (Stibler, 1991). It detects consumption of as little as 20 g/day of alcohol. The validity of CDT as a marker of chronic
alcohol consumption was tested in a racially
mixed population and was found to be a highly
specific marker, irrespective of ethnic background
or race (Behrens, Worner, Braly, Schaffner, &
Lieber, 1988). The venous blood sample was
drawn between 9:00 and 10:00 a.m., then centrifuged, and plasma was withdrawn and refrigerated within 1 hour of the blood draw. The serum
samples were refrigerated at -70?C. All serum
samples were assayed on the same day by the
same medical technologist.
Testosterone. The Coat-A-Count No Extraction
Testosterone procedure was used to measure total
testosterone levels (Diagnostic Products Corporation, 1985; Jaffee & Behrman, 1974). Based on
the findings of past investigations that have reported intrasubject consistency of testosterone
levels when samples are drawn at the same time
on different days, only one blood sample was
drawn from each male subject (Ehrenkranz,Bliss,
& Sherod, 1974; Kreuz & Rose, 1972). The venous blood sample was drawn between 9:00 and
10:00 a.m. (to control for circadian rhythms), then
centrifuged, and plasma was withdrawn and refrigerated within 1 hour of the blood draw. The
serum samples were refrigerated at -70?C. All
serum samples were assayed on the same day by
the same medical technologist. The normal range
for serum testosterone is 3.6 ng/ml to 9.9 ng/ml.
Prolactin. Human prolactin is a single-chain
polypeptide of 199 amino acids. Prolactin is produced by the anterior pituitary and its secretion is
regulated physiologically by inhibitory and releasing factors of the hypothalamus (Bowers,
Friesen, Hwang, Guyda, & Folkers, 1971; Talwalker, Ratner, & Meites, 1963). It is a promising
index of overall, central 5-HT serotonin activity
(Coccaro et al., 1989). Its existence as a distinct
chemical entity, separate from growth hormone,
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Biopsychosocial Model
was established through a series of studies
(Frantz, Kleinberg, & Noel, 1972; Niall, 1972).
Quantitative measurement of serum prolactin levels were assayed by the IMx Prolactin assay, a
microparticle enzyme immunoassay (Abbott Laboratories, 1991). Sensitivity of the IMx Prolactin
assay was calculated to be better than or equal to
0.6 ng/ml. Specificity was determined by studying the interference of triglycerides (up to 1,000
mg/dl), hemoglobin (up to 750 mg/dl), and bilirubin (up to 50 mg/dl). No interference with the determination of prolactin using this assay was observed. Expected values range for males (n = 111)
between 1.58 and 23.12 (M = 6.75) (Abbott Laboratories, 1991). The venous blood sample was
drawn between 9:00 and 10:00 a.m., then centrifuged, and plasma was withdrawn and refrigerated within 1 hour of the blood draw. The serum
samples were refrigerated at -70?C. All serum
samples were assayed on the same day by the
same medical technologist.
Negative life events. The Life Experiences Survey
(LES) is a 57-item, self-report measure of events
that have occurred in the past year; 47 of the
items are designed for use with the general population (Sarason, Johnson, & Siegel, 1978). Events
include marriage, change in residence, major personal illness, loss of job, and detention in jail. For
each of the 47 events, respondents may indicate
whether or not they experienced the event in the
past year and, if they experienced it, the extent to
which they viewed the event as positive or negative on a 7-point rating scale, ranging from "extremely negative" (-3) to "extremely positive"
(3). Summing the ratings provided a negative
change score, a positive change score, and a total
change score. Only the negative change scores
were used in this study because this subscale is
theoretically most highly related to extreme stress
responses. Reliability data collected in several
past studies ranged from .56 to .88 (Sarason et al.,
1978).
Relationship quality. The Autonomy and Relatedness Inventory (ARI) assessed the quality of the
male's relationship with his female partner.
Specifically, the scale measures relatedness versus detachment/rejection and autonomy versus
control. This scale is thought to be particularly
appropriate for the study of marital quality in
terms of violent communication because the conceptualization and measurement focuses on perceived autonomy and control by an intimate,
313
which is thought to be a major component of the
relationship dynamics in domestic violence. The
ARI is a short version of the Marital Autonomy
and Relatedness Inventory (MARI). Thirty-two
short statements about interpersonal behavior of
the intimate partner are asked, with five possible
responses that range from "not at all like her" (1)
to "very much like her" (5) (Schaefer & Edgerton, 1982). Instrumentitems include such descriptors as "talks over her problems with me," "is
there when I need her." Scale reliabilities are appropriate for research, and validity of the ARI is
supported by moderate to strong correlations with
the Spanier Dyadic Adjustment Scale (Schaefer &
Edgerton, 1982). The Cronbach alpha reliability
in this study was .71.
Family income. Family income was measured by
male self-report of the annual income provided by
his employment as well as by his marital partner's
employment. Some researchers contend that violent behavior may be best explained by structural
factors such as resource inequality (Vold, 1986).
The males' reports and their marital partners' reports of family income were very similar (violent
males and female partner:r = .87, p < .001; nonviolent males and female partner:r = .89, p < .001).
Social support. The Inventory of Social Supportive Behaviors (Barrera, Sandler, & Ramsay,
1981) was used to assess objective social support
or the frequency with which male subjects reported receiving specific types of support. This instrument consists of 40 items with a Likert-response
pattern that ranges from "not at all" (1) to "about
every day" (5). High scores indicate more frequent receipt of such support. Types of support
include the following: "did some activity together
to help you get your mind off things," "loaned
you over $25," "provided you with some transportation." This study utilized 28 of the original
40 items. The Cronbach alpha reliability in this
study was .94.
Psychological symptoms. The Psychiatric Symptom Checklist 90/Brief Symptom Inventory
(SCL-90, BSI) is a multidimensional paper and
pencil inventory designed to assess psychopathology in psychiatric and medical outpatients (Derogatis, Lipman, & Covi, 1973). Respondents are
asked to rate the extent to which they have been
bothered by each symptom in the last few
months. Likert-type responses range from "not at
all" (1) to "extremely" (5). Symptoms assessed
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314
Journal of Marriage and the Family
include such items as "nervousness or shakiness
inside," "feeling blue," and "never feeling close
to another person." The checklist is scored on 10
primary symptom dimensions plus three global
indices that reflect distinct aspects of psychological disorder. The primary symptom dimensions
are: (a) somatization, (b) obsessive-compulsive,
(c) interpersonal sensitivity, (d) paranoid ideation,
(e) depression, (f) anxiety, (g) hostility, (h) phobia, (i) psychoticism, and (j) addictive. The Global Severity Index (GSI) combines information on
the number of symptoms. Only three subscales
were used in this study: anxiety, hostility, and
paranoia. The SCL-90 has been normed on a
number of populations including psychiatric inpatients, alcoholics, and drug abusers. Validity studies have indicated high concurrent validity with
the Minnesota Multiphasic Personality Inventory
(MMPI) (Derogatis, 1992; Derogatis, Rickels, &
Rock, 1976). Cronbach alpha reliabilities in this
study were .73 for paranoid ideation, .72 for anxiety, and .85 for hostility.
RESULTS
The means, standarddeviations, and ranges of the
independent variables are presented in Table 2,
and the univariate correlations (Pearson's r) are
presented in Table 3 with a log score used for the
dependent measure for violence because of its
skewed distribution (Moore & McCabe, 1989).
As mentioned above, 34 of the couples were classified as maritally violent, that is, having experienced at least one male-initiated violent incident
in the past year. Husbands who were violent reported 3.7 incidents of violence toward their
wives, and their wives reported a mean of 3.3 incidents; the correlation between these spousal reports was statistically significant (r = .75,
p < .001). These mean scores were lower than the
TABLE 2. MEANS AND STANDARD DEVIATIONS
OF INDEPENDENT VARIABLES
Variable
Mean
Range
SD
Alcohol
Testosterone
Prolactin
Relationshipquality
Negative life events
Social support
Family income
Anxiety
Hostility
Paranoia
14.09
4.4
11.1
122.34
5.59
64.43
38,575
.61
.79
.74
5.2-56.5
1.6-10.6
3.7-43.5
79-154
0-22
28-125
5,000-99,000
0-2.16
0-3.67
0-3.2
6.95
1.62
6.49
18.05
5.27
19.57
12,292
.48
.71
.60
scores of 9.7 (Browning & Dutton, 1986) and 7.8
(Claes & Rosenthal, 1990) found in two recent
studies utilizing more clinical samples.
Multivariate data analysis was conducted to
assess the degree of relationship between the independent variables and the dependent variable.
The independent variables were analyzed by
structuring them into three groups of predictors
(i.e., biological, social, and psychological). These
groups first were introduced separately into the
equation with the dependent measure, husband violence toward his wife. Although the dependent
variable is continuous, it is censored. That is,
there is a "piling up" of cases at its lower limit of
zero. Thus, ordinary least squares regression, a
common statistical analysis in much of the violence literature, is not an appropriate statistical
technique in this study because it does not consider the concentration of cases at the lower limit of
zero (Stets, 1991). Tobit analysis was used instead because it provides maximum likelihood parameter estimates for equations in which the dependent variable is censored (Amemiya, 1974). A
log likelihood ratio is computed to test for statistical significance, and it has a chi-square distribution. Further, the Tobit model has a test analo-
TABLE 3. CORRELATION (PEARSON'S r) MATRIX OF STUDY VARIABLES
(1)
1. Alcohol
2. Testosterone
3. Prolactin
4. Relationshipquality
5. Negative life events
6. Social support
7. Family income
8. Anxiety
9. Hostility
10. Paranoia
11. Violence
*p<.05.
(2)
(3)
-.07
-.10
-.02
-.03
.04
.01
.04
.12
.18
.02
.12
-.03
-.07
-.06
.05
-.16
.00
.31**
.14
.05
.09
.12
-.18
-.02
-.02
.01
-.01
(4)
(5)
(6)
-.20*
.32** .08
.12
-.25*
-.18
-.33**
.36**
.06
-.36**
.35**
.06
-.40**
.28**
.02
-.31**
.10
.30**
(7)
-.14
-.21*
-.20*
-.38**
(8)
(9)
(10)
.68**
.53**
.19
.59**
.36**
.29**
**p<.01.
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(11)
315
Biopsychosocial Model
gous to the R2 goodness-of-fit statistic reported in
regression analysis. This statistic is called the
likelihood ratio index or rho-square, and is a measure of how well the model approximates the observed data. Likelihood ratios have an upper
bound of about .3 (Hensher & Johnson, 1981;
Tardiff, 1976).
Tobit analysis of male violence toward a female intimate using the group of biological variables resulted in a significant equation. Alcohol
use and testosterone were significant individual
predictors in the equation, indicating that males
with greater alcohol use and higher levels of
testosterone express violence against their female
partner more frequently. The Tobit analysis of
male violence toward a female intimate using the
group of psychological variables showed that only
hostility was significantly related to the dependent
measure, indicating that males with higher levels
of hostility are more inclined toward violence
against their female partner.The Tobit analysis of
male violence toward a female intimate using the
group of social variables showed that family income and relationship quality were significant independent predictors in the model. Males with
lower family incomes and lower relationship quality appear to express violence toward their female
partnermore frequently (see Table 4).
TABLE 4. TOBIT ANALYSIS FOR BIOLOGICAL, SOCIAL,
AND PSYCHOLOGICALMODELS
Parameter
Estimate
Domain
Social
Maritallife events
Negative life events
Social support
Family income
Log likelihood
Log likelihood ratio
Rho-square
Physiological
Alcohol
Prolactin
Testosterone
Log likelihood
Log likelihood ratio
Rho-square
Psychological
Anxiety
Hostility
Paranoia
Log likelihood
Log likelihood ratio
Rho-square
Chi-square
-.14
.18
.05
-.00
6.10**
1.06
1.28
11.49***
143.01
45.4***
.14
.05
.00
.19
TABLE 5. TOBIT ANALYSIS OF COMBINED MODEL
Domain
15.49**
.01
4.2*
148.05
35.32****
.11
-2.17
2.83
1.39
The complete Tobit model indicated that only
alcohol use, family income, and relationship quality were significantly related to domestic violence, with testosterone remaining marginally significant (See Table 5). The three groups then
were entered into Tobit equations in hierarchical
fashion to assess the unique or independent variance accounted for by each cluster. Three different equations were created with one domain omitted from each equation. A log likelihood ratio
statistic was computed to compare the explanatory power of these reduced models with the complete model to assess the independent strength of
the omitted cluster. The null hypothesis is that the
omitted set of variables has no impact on violence
probabilities. Results of the Tobit analysis indicated that the physiological set of variables had a
significant effect on violence (log likelihood ratio
= 28.58, p < .0001), as did the social domain (log
likelihood ratio = 24.46, p < .0001). Interestingly,
as a group the psychological variables did not
have a statistically significant independent effect
on violence probability.
As noted above, previous research has suggested interactions between certain variables;
based on this research literature, several interaction terms were created, and the dependent variable was regressed on these: testosterone x alcohol use, prolactin x alcohol use, testosterone x
prolactin, hostility x alcohol use, hostility x prolactin, testosterone x hostility, and relationship
quality x alcohol use. These interaction terms
were tested individually and entered following
their corresponding main effects. However, none
1.23
3.81*
.94
154.15
24.43***
.07
*p< .05. **p<.01. ***p< .001. ****p< .0001.
Social
Maritalquality
Negative life events
Social support
Family income
Physiological
Alcohol
Prolactin
Testosterone
Psychological
Anxiety
Hostility
Paranoia
Log likelihood
Log likelihood ratio
Rho-square
Parameter
Estimate
Chi-Square
-.11
.14
.02
-.00
4.68**
.91
.34
12.40***
.05
-.01
.07
23.67***
.50
2.46*
-1.57
.82
1.55
1.14
.43
2.01
127.69
75.62****
.23
*p<.10. **p<.05. ***p<.01. ****pp<.0001.
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Journal of Marriage and the Family
316
of these interaction terms had a significant impact
on the level of male violence expressed toward
female partners.
DISCUSSION
The findings from these analyses provide some
support for a biopsychosocial approach to the understanding of domestic violence. When examined separately, each conceptual domain was significantly related to the dependent measure. In the
full model, however, only the biological and social domains were statistically significant. Further, no significant interactions were found between any of the biological, psychological, and
social context variables.
It is interesting to note the relative independence of measures representing the three conceptual domains in this study. The biological variables were not significantly related (Pearson's r)
to any of the social or psychological variables,
nor were any of the hypothesized interactions significant. Similarly, while the social and the psychological variables were interrelated within their
respective domains, there were few significant relationships between variables across their domains, and again no significant interaction terms.
These findings would suggest an independent effect of the various domains on male aggression
toward wives in this study. Also, such findings
would support a linear relationship between the
independent variables and domestic violence in
contrast to those preliminary studies that have
found interaction effects across conceptual domains. It should be noted here that the lack of interaction effects may have been due to a number
of factors, including the use of a relatively small
sample, as well as the appearance of restricted
variance in some of the measures utilized in this
study. Selectivity cannot be ruled out given that
causation cannot be determined.
The data indicate that the social cluster constituted the best set of predictors, providing support
for a life events perspective on domestic violence.
In particular, family income and relationship
quality were found to constitute a combined set of
stressors and resources that predicted a sizable effect on the dependent measure. Additionally, in
the zero-order correlations, the life events measure was significantly related to domestic violence. Given the strong relationship between family income and violence probability found in this
study, an alternative hypothesis was tested. This
hypothesis was based on research that suggests
that family income is highly related to domestic
violence and thus might overshadow other variables. Hence, a stepwise Tobit analysis controlling for family income was conducted. This analysis did not result in a change in the previously
identified significant predictors in the Tobit
model with all variables entered.
Additionally, the strong association between
relationship quality and violence probability
prompted further analysis based on research that
suggests an "extent of interaction" hypothesis (cf.
Murphy & Cascardi, 1993). Relationships that are
of longer duration and/or include more frequent
contact have been shown to contain higher rates
of aggressive interaction (Mason & Blankenship,
1987; Stets, 1991). However, Pearson's r correlations between length of marriage and both relationship quality and violent behaviors proved to
be nonsignificant (r = .16 and .06, respectively).
Based on the hierarchical ordering, the biological domain also constituted an independent effect,
primarily as a result of the strength of the alcohol
use variable. This finding is consistent with the
vast literature supporting the relationship between
alcohol and abuse. However, this study is unique
in its use of the CDTect, a measure only recently
introduced into this country and offering the most
reliable and valid means of testing for recent alcohol use available. Compared with the normative
data, the subjects in this study fell below the cutoff score of 20 for excessive use of alcohol in the
last 14 days for both violent males (M = 16.93, SD
= 8.92) and nonviolent males (M = 12.71, SD =
5.29).
Testosterone did approach significance and
might have been significant with greater variability within the measure. In general, the mean scores
were very low-a mean of 4.18 compared with
the normal range of 3.6 ng/ml to 9.9 ng/ml. Only
two men scored above the normal range. However, testosterone was significant when the physiological cluster was assessed separately. Prolactin,
as a measure of serotonin, was likewise not related to male violence, perhaps also due to its low
variability, well within normal range. In addition,
prolactin may not have been the best proxy for
serotonin because it does not vary as much among
males; however, far more intrusive measures are
required to obtain other indices of serotonin. The
hypothesized interactions between and among
these and other variables were also limited by the
prolactin and testosterone scores of this particular
sample, as noted above. Perhaps the hypothesized
interaction effects are dependent on acute inges-
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317
Biopsychosocial Model
tion of alcohol along with higher levels of testosterone and/or prolactin. It should be noted that the
subjects were also tested for marijuana and cocaine use. Urinalysis indicated that only negligible levels of marijuanawere present in two nonviolent subjects, and no marijuana or cocaine use
was indicated in the violent subjects. Prescription
drug use was minimal in each group. Reported
comorbidity rates regarding polydrug use and violent acts (Hayes & Emshoff, 1993) underscore
how the lack of illegal drug ingestion becomes a
further indication of the restricted range of individual and interpersonal functioning levels in the
present sample.
When examined separately, the psychological
domain also accounted for a significant effect on
the dependent measure, with hostility as the only
variable significantly related to domestic violence. Hostility could be perceived either as a direct effect or as a response to stressors (negative
life events, relationship quality, and family income) with which they were correlated. However,
none of the variables within the psychological domain were significant in the combined model.
Perhaps this domain would have been a stronger
predictor if the level of violence had been greater;
psychological factors have a greater impact on
males exhibiting higher levels of aggression (Hotaling & Sugarman, 1986; O'Leary 1993). The
low level of violence and the lack of variablity
within this measure might also have limited the
power of the other independent variables in predicting relationship violence. The scores of the
subjects on the three SCL-90/BSI subscales also
were well within the middle band of normative
scores, although in each case the violent men's
scores were greater. The means on each of the
three SCL-90/BSI subscales (anxiety, hostility,
paranoia) for the nonviolent men (.57, .68, .19, respectively) placed this group in the 64th, 61st,
and 50th percentiles of the normative group
scores, respectively, as reported by Derogatis
(1992). A similar comparison of the violent men's
scores (.68, 1.01, .32) placed this group in the
64th, 65th, and 53rd percentiles of the normative
group scores, respectively.
Although only exploratory, the findings of this
study indicate the potential of a biopsychosocial
approach to the understanding of domestic violence. It is probable that the strength of many of
the predictors, and thus the power of the model,
could have been enhanced by the inclusion of
males with scores beyond the normal range on
such variables as alcohol use, testosterone, pro-
lactin, paranoia, and anxiety. Although clinical
samples have been overused in family violence
research, such a sample, including more pathological and/or severely distressed subjects, may have
been more appropriate in developing the biopsychosocial model specified in this study. Also, a
larger number of violent males in general would
have lessened the risk of a Type II error.
For some researchers and practitioners alike,
there is often concern when biological factors are
examined in relation to dysfunctional behavior
that such findings might be used to absolve individual responsibility. Similarly, the examination
of psychopathology as an underlying mechanism
of family violence has been criticized for conceptualizing violent behaviors within the family as
only extreme responses and abnormal behaviors.
It is hoped that such concern has been minimized
by the study's intent of integrating both psychological and biological perspectives with the more
thoroughly studied social factors.
Indeed, the findings of the study indicate that
the best estimates of violence probability are the
social variables, given a sample where scores on
the variables within both biological and psychological domains were largely within normal
range. These findings are consistent with many
other studies cited above that have generated evidence regarding the primacy of social context
variables, and in a sense they argue against the
necessity for a biopsychosocial approach to domestic violence. Also, the biopsychosocial perspective holds that it is not simply the summative
relationships but also the interactive relationships
among biological, psychological, and social context variables that fully explain phenomena related to health and pathology (Engel, 1977; McDaniel et al., 1992). Hence, further disputation of
this approach is evidenced through the lack of
significant interactions found between variables
representing the three domains of the model. In
certain ways, then, the influence of biological and
psychological factors on violence probability estimates may be seen as secondary to and perhaps
dependent on social context variables.
Further advancements in empirical efforts will
also need to occur if researchers are to remain
consistent with the holistic biopsychosocial
model. For instance, it would have been preferable to have studied other members of the male's
family or community system. Data were available
from the wives on many measures and were indeed used in the compilation of the violence
score. However, due to sample size restrictions
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318
Journal of Marriage and the Family
and the interest in individual factors that previous
literature has related to domestic violence, a more
expansive analysis was not conducted.
This study was also limited by its cross-sectional design, which did not allow for causal inferences. Researchers have generally neglected to examine the temporal relationships between wife
abuse and characteristics correlated with it; thus it
cannot be established whether correlates are risk
factors or merely consequences of abuse (Sedlak,
1988). A longitudinal analysis also would have allowed for better detection of possible interactions
of study variables. For example, it was not possible to examine Lindman et al.'s (1992) conclusion
that high levels of testosterone are thought to precede alcohol abuse, with chronic alcohol use then
resulting in lower testosterone levels.
Self-report is always a limitation in studies of
sensitive topics. However, this study made some
attempts to compensate for this limitation by
using couple scores on the CTS and by using biological indicators, including the CDTect alcohol
screening device, which do not rely on self-report. It is hoped that the use of clinically trained
interviewers limited the influence of social desirability in the administration of the SCL-90/Brief
Symptom Inventory.
In some respects, the ability to translate this
study's findings into treatment and policy considerations is a difficult task. This is especially true
in light of the antagonism that has existed historically between domestic violence researchers and
victim advocates (Gelles, 1994). However, it is
believed that the biopsychosocial model offered
here may at the very least be a small but significant step toward the utilization of the "contextual
approach"advanced by Jacobson (1994a, 1994b),
a perspective that advances an inclusive and ecological viewpoint regarding the study of relationships that contain interactions of violence.
NOTE
Salaries and research support for this study were provided, in part, by state and federal funds appropriatedto
the Ohio Agricultural Research and Development Center, The Ohio State University (H-075).
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