Understanding Adolescent and Family Influences on Intimate
Partner Psychological Violence During Emerging Adulthood
Brenda J. Lohman•Tricia K. Neppl•
Jennifer M. Senia•Thomas J. Schofield
Received: 12 January 2013/Accepted: 24 January 2013/Published online: 21 February 2013
? Springer Science+Business Media New York 2013
past three decades. Overall, the literature shows that violence
in the family of origin leads to violence in the family of des-
tination. However, this predominately cross–sectional or ret-
and reporter biases as it has not been able to assess how
individual and family behaviors simultaneously experienced
during adolescence influence intimate partner violence
throughout adulthood. The present study used data from the
Iowa Youth and Families Project (IYFP; N = 392; 52 %
overcome this limitation. We focused on psychological inti-
mate partner violencein
(19–23 years) and adulthood (27–31 years), and include self
a host of individual risk factors as well as interparental psy-
chological violence from adolescence (14–15 years), the
results show that exposure to parent–to–child psychological
violence during adolescence is a key predictor of intimate
partner violence throughout adulthood. In addition, negative
predicted intimate partner violence in both emerging adult-
positively with intimatepartner violence in adulthood but not
in emerging adulthood, whereas academic difficulties were
previous research, results did not support a direct effect of
The intergenerational transmission of violence
both emerging adulthood
interparental psychological violence on psychological vio-
lence in the next generation. Gender differences were found
Multimethod ? Multitrait ? Parenting
Intimate partner violence ? Longitudinal ?
Recent empirical studies have turned to understanding
precursors and consequences of intimate partner violence
during the teen years. This is particularly important to
understand as rates of teen dating violence increase over
adolescence and remain high during emerging adulthood.
Approximately one in four adolescents report dating vio-
lence each year (Centers for Disease Control 2012); simi-
larly, 23–38 % of emerging adults report violence in their
intimate partner relationships (Straus 2004). During
adulthood, national surveys show rates of physical intimate
partner violence range from 17 to 39 % (Plichta 1996;
Schafer et al. 1998; Straus and Gelles 1990). A recent
review of the literature shows that the peak for intimate
partner violence occurs early—in late adolescence and
young adulthood (Capaldi et al. 2012). The National Inti-
mate Partner and Sexual Violence Survey shows an annual
estimate of 4.2 million intimate partner violence related
physical assaults, rapes, and stalking perpetrated against
women and 3.2 million against men (Black et al. 2011).
Given the prevalence rates and negative consequences
that intimate partner violence may have on an individual’s
well–being and future relationships, it is imperative to
explore factors that may increase or reduce its occurrence
during both the teen and early adulthood years when rates
B. J. Lohman (&) ? T. K. Neppl ? J. M. Senia ? T. J. Schofield
Department of Human Development and Family Studies,
Iowa State University, 4389 Palmer Suite 2356,
Ames, IA 50011, USA
J Youth Adolescence (2013) 42:500–517
are high. Indeed, research has argued that the period of
emerging adulthood, which extends from the late teens to
the mid-to-late 20s, is particularly salient as late teens and
young adults explore and develop romantic relationships.
During this life period, individuals are assessing what they
want in a long-term romantic partner including figuring out
acceptable and unacceptable traits and behaviors, such as
intimate partner violence (Arnett 2000; Fincham and Cui
2011; Halpern-Meekin et al. 2013).
However, little is known about the continuity of such
relationships across time. For example, while we know that
the mean rates of intimate partner violence tend to decrease
over time in the general population, we know less about the
continuity of violence across relationships. That is, the
literature has focused on changes in violent behaviors
occurring within a single romantic relationship over time
rather than patterns of intimate partner violence for indi-
viduals in sequential relationships (i.e., across different
partners). Such work can provide important insight into
intraindividual stability in intimate partner violence (Shortt
et al. 2012). It may be that individuals have continuity in
intimate partner violence due to self–selection; individual
factors that lead to assortative partnering. Adolescents and
adults tend to select partners who are similar to themselves
in terms of substance use and antisocial behavior, both of
which are predictive of intimate partner violence (Kim and
Capaldi 2004; Shortt et al. 2012). This assortative part-
nering, in turn, could serve to reinforce behavior patterns
conducive to intimate partner violence. Moreover, previous
experience with intimate partner violence may predict
violence in subsequent romantic relationships (Schumacher
and Leonard 2005). However, little work has addressed the
stability of intimate partner violence across relationships.
Therefore, the purpose of the current study is to understand
the influence of individual and family factors experienced
during adolescence on intimate partner violence across
emerging adulthood and adulthood, including both perpe-
tration and victimization simultaneously.
Intimate Partner Violence
A variety of definitions has been used to understand intimate
partner violence and many use only single item measures
(National Institute of Justice 2011; Capaldi et al. 2012). Inti-
physical, psychological, and sexualabuse bymen and women
toward romantic partners of the same or opposite gender.
Physical violence ranges from mild contact (i.e., gentle push-
ing) to the extreme (e.g., severe beatings, or even death).
Psychological abuse, often defined as psychological aggres-
sion, refers to severe sarcasm, acting in an offensive or
degrading manner toward another, ultimatums or threats, and
restrictions (e.g., social isolation, financial control; O’Leary
than physical violence in both community and high–risk
samples (Capaldi et al. 2007; Lawrence et al. 2009; O’ Leary
and Maiuro 2001; Shortt et al. 2012). Therefore, the current
study specifically examines adolescent predictors of psycho-
logical violence across emerging adulthood and adulthood.
Intergenerational Continuity in Psychological Violence
The current research is guided by the developmental–inter-
Capaldi and Gorman–Smith 2003), which proposes that
the development of an interpersonal style conducive to vio-
lence in intimate partner relationships. Adolescents may
learn to behave violently towards romantic partners by
watching their parents interact with each other. This social-
ization perspective is often referred to as the intergenera-
tional transmission of violence (Straus et al. 1980; Capaldi
and Clark 1998; Cui et al. 2010; Simons et al. 1995).
Furthermore, a key proposition of many models linking
family processes with developmental outcomes is that par-
ents’ behaviors toward children are a more proximal influ-
ence on children’s developmental outcomes relative to the
influence of the interparental interactions (i.e., Cui and
Conger 2008). Thus, according to the developmental–inter-
actional model of romantic–partner directed aggression,
other family processes such as hostile parenting or parent–
to–child psychological violence, will directly influence the
adolescent’s behaviors and development (Stith et al. 2000;
Conger et al. 2000; Neppl et al. 2009). The developmental–
interactional model states that ‘‘direct treatment of the child
by the parent is viewed as more central [than observational
learning]’’ (Capaldi and Gorman–Smith 2003, p. 248). For
example, work by Capaldi and Clark (1998) shows that
parents’ behavior toward their children is more influential
than simply witnessing violence between parents. In short,
the spillover hypothesis speculates that negativity and hos-
tility from parental relationship violence may spill over into
parenting behaviors and the parent–child relationship (e.g.,
yelling, threatening, spanking, hitting; see Krishnakumar
and Buehler 2000). Thus, in this article, we test not only the
influence of parental intimate partner violence but also the
intimate partner violence in romantic relationships experi-
enced in emerging adulthood and adulthood.
Predictors of Intimate Partner Violence
In addition to the above social learning perspectives, eco-
logical and developmental theories argue for the inclusion
J Youth Adolescence (2013) 42:500–517 501
of ontogenetic or individual risks that may lead to intimate
partner violence. Thus, we include both individual and
family risk factors that have been shown to predict intimate
partner violence (see Fig. 1). Below we discuss the litera-
ture related to these risk factors in greater detail, beginning
with individual–level factors and then turning to family–
Two classes of individual characteristics have been linked
to intimate partner violence: risky behaviors and disposi-
tional factors. First, a common predictor is substance use
including drug and alcohol use; however, these associations
may not be as strong or consistent as once thought (Caetano
et al. 2005; Eaton et al. 2007; Feingold et al. 2008;
Herrenkohl et al. 2007; Schluter et al. 2008; Schnurr and
Lohman 2008; Temple and Freeman 2011). Second, early
sexual activity including the number of partners has been
linked to intimate partner violence (Cleveland et al. 2003;
Halpern et al. 2001; Maxwell et al. 2003; Roberts and Klein
2003). Third, a multiplicity of research has shown a link
between intimate partner violence and antisocial behaviors
including hostility, delinquency, externalizing behaviors,
and conduct problems (Andrews et al. 2000; Capaldi et al.
2001; Ehrensaft et al. 2004; Herrenkohl et al. 2007;
Huesmann et al. 2009; Kim and Capaldi 2004; Lussier et al.
2009; O’Donnell et al. 2006; White and Widom 2003).
Fourth, self–esteem has been linked cross–sectionally to
intimate partner violence with mixed results (Capaldi and
Crosby 1997; Hazen et al. 2008; Whiting et al. 2009). Fifth,
a very strong predictor of intimate partner violence is
association with deviant peers (Arriaga and Foshee 2004;
Dishionet al. in press; Foshee et al. 2011; Gagne ´ et al. 2005;
Schnurr and Lohman 2008; Miller et al. 2009; Williams
et al. 2008). Sixth, disparate findings have been found
between intimate partner violence and academic difficulties
during adolescence (Cleveland et al. 2003; Herrenkohl et al.
2000; Schnurr and Lohman 2008). Seventh, a link between
personality types such as negative emotionality and intimate
partner violence has been explored but the results do not
lend consistent evidence (Hellmuth and MuNulty 2008).
Finally, the cadre of literature has shown disparate find-
misperception that males perpetrate intimate partner vio-
lence more than females (Foo and Margolin 1995; Schwartz
et al. 1997); however, in more recent years, females have
been shown to perpetrate intimate partner violence more
often than males (Archer 2000; Feiring et al. 2002; Schluter
et al. 2008; Kaura and Allen 2004; Lichter and McCloskey
2004; Schnurr and Lohman 2008). In fact, recent studies
show that men and women are equally likely to perpetrate
while women tend to perpetrate intimate partner violence
(Ages 14 - 15)
Family Risk Factor:
Intimate Partner Violence
Family Risk Factor:
(Ages 19 - 23)
(Ages 27 - 31)
Family Risk Factor:
Fig. 1 Conceptual model. Note Individual risk factors assessed
include substance use, sexual activity, antisocial behaviors, self–
esteem problems, association with deviant peers, academic difficul-
ties, negative emotionality, andgender. The intergeneration
transmission of intimate partner violence is shown by the bold
dashed lines while the influence of parent–to–adolescent psycholog-
ical violence is shown by the bold lines. The effects of family stress
are shown by the non–bolded dashed lines
502 J Youth Adolescence (2013) 42:500–517
more than men, women are still more likely to be seriously
injured or murdered by their partners than are men (Archer
shown conflicting indications as to whether the intergener-
ational transmission of violence differs by gender (Kalmuss
1984; Kwong et al. 2003), with some studies finding an
association for females, but not for males (e.g., Mihalic and
Elliot 1997), whereas others have found the association for
males, but not females (e.g., O’Keefe 1997).
the intergenerational transmission of partner violence or
exposure to intimate partner violence in the family of origin.
In particular, it is common for adolescents to both witness
intimate partner violence and be victims of parental abuse
with co–occurrence rates as high as 80 % (Saunders 2003).
Indeed, early intimate partner violence exposure during
childhood increases teen intimate partner violence and adult
intimate partner violence (Markowitz 2001; McCloskey and
Lichter 2003; Moretti et al. 2006; Renner and Slack 2006;
Roberts et al. 2010; Rosenbaum and Leisring 2003; Whit-
field et al. 2003; Williams et al. 2001; Wolf and Foshee
2003). However, nearly all findings are retrospective and
only a handful of studies has been able to establish inter-
generational transmission of intimate partner violence pro-
spectively (Capaldi and Clark 1998; Ehrensaft et al. 2003;
position to assess the intergenerational transmission of
partner violence prospectively across two generations of
Another family risk factor is parenting, specifically
parent–to–adolescent psychological violence or psycho-
logically abusive parenting. Mother–adolescent hostility
(Allen et al. 1994; Nix et al. 1999) and father–adolescent
hostility (Coley 2003; Shek 2005; Vazsonyi 2003) have
been associated positively with intimate partner violence.
Specific to the data used for this article, Neppl et al. (2009)
found that hostile parenting predicted adolescent exter-
nalizing behaviors which, in turn, led to hostile parenting
during adulthood. In addition, Schnurr and Lohman (2008)
found that mother–child hostility was predictive of perpe-
tration for Hispanic females, whereas father–child hostility
was protective for Hispanic females.
Finally, exposure to stress, particularly family and
interparental stress, has been explored as a predictor of
intimate partner violence. For example, cross–sectional
work has shown that financial stress was predictive of
perpetration (Neff et al. 1995; Slep et al. 2010). In addition,
life stressors such as work, stress, and parenting stress have
all been associated with marital conflict and higher rates of
intimate partner violence (Caetano et al. 2007; Probst et al.
2008; Jasinski and Kantor 2001; Jasinski et al. 1997). Thus,
the literature supports the notion that exposure to stress is
predictive of intimate partner violence. Beyond these
family risk factors, the current study controls for family
income as previous work shows that limited resources
associated with higher rates of violence (Cunradi et al.
2002; O’Donnell et al. 2002).
Limitations of the Current Literature
As briefly noted above, previous work in the area of inti-
mate partner violence is limited (National Institute of
Justice 2011; for review see Capaldi et al. 2012). For
example, self–report measurement, with one to three items
among both adult and adolescent samples, is the most
common measurement strategy. Furthermore, no studies to
date have included multi–modal measurement encom-
passing observational data or multi–informant data of
intimate partner violence during adolescence, and only 5 %
of the adult studies included multi–modal intimate partner
violence measures (Capaldi et al. 2012). Moreover, the
majority of these studies do not separate measures of
psychological violence from physical violence. While the
majority of recent studies assesses both male–to–female
and female–to–male intimate partner violence, only a
handful include interviews from both members of the dyad
(see Schnurr et al. 2010), with 78 % of the adult studies
and 95 % of the adolescent studies interviewing only one
partner (Capaldi et al. 2012). Concerns associated with
self–reported behaviors include underreporting due to
between partner and self–reports (Szinovacz and Egley
1995), and the potential for inflating the associations
between constructs (e.g., parental violence and subsequent
partner violence) due to method biases (Lorenz et al. 1991).
Finally, the literature is limited in that 61 % of adult
studies and 55 % of adolescent studies were cross sectional
(Capaldi et al. 2012); thus, the vast majority of the literature
has failed to utilize prospective designs that are not able to
assess multiple risk factors of intimate partner violence
metaanalytic review, Stith et al. 2000) has relied on retro-
spective accounts of violence in the family of origin (with
notable exceptions such as work by Capaldi and her col-
leagues, e.g., Andrews et al. 2000; Capaldi and Clark 1998;
Capaldi and Crosby 1997). Given the prevalence rates and
negative consequences that intimate partner violence may
have on an individual’s well–being and future relationships,
imperative to explore factors experienced during adoles-
cence that may increase or reduce intimate partner violence
during emerging adulthood and adulthood.
J Youth Adolescence (2013) 42:500–517503
Research Innovation: The Current Study
The proposed study overcomes earlier limitations by using
multi-trait multi-method data from a two–decade study of a
cohort of adolescents now grown to adulthood. Across the
two decades of the study, all participants have been assessed
on multiple occasions using a measurement strategy that is
both extensive (i.e., covers multiple domains of personal
and social characteristics) and intensive (i.e., employs a
multi–informant approach that includes self–reports, other
family member reports, teacher reports, ratings by trained
observers, school records, public records, and a genome–
wide assessment of participants). Thus, we are uniquely
positioned to overcome limitations and are innovative in six
First, we used a multi–method, multi–agent approach to
assess intimate partner violence across two generations. Sec-
ond, both self–report and romantic partner report of partner
male–to–female and female–to–male intimate partner vio-
lence were employed. Thus, each variable of interest was
measures (Conger et al. 2000; Cui and Conger 2008). Third,
both perpetration and victimization at the couple level were
violence emerges and is manifested in couples can be con-
sidered. Fourth, to address measurement biases, the present
study used measures based on multiple informants (mother,
father, adolescent, and the romantic partner of the adolescent
behaviors (Cui et al. 2005). Details regarding these assess-
ments are found in our measures section. Fifth, we utilized
violence as well as variations in pathways or predictors of
intimate partner violence, we examined issues related to the
gender of the adolescent.
Based on the aforementioned literature, five key
hypotheses are addressed in this article. Our first hypoth-
esis is that individual risks during adolescence will be
linked positively to intimate partner psychological violence
during both emerging adulthood and adulthood for vic-
timization and perpetration (Hypothesis One). We also
expect that exposure to parental intimate partner violence
during adolescence will be related positively to intimate
partner psychological violence during adulthood (Hypoth-
esis Two). We further propose that exposure to parent–
child psychological violence during adolescence will lead
to intimate partner psychological violence, during emerg-
ing adulthood and adulthood (Hypothesis Three). Lastly,
we speculate that exposure to family stress during
adolescence will lead to intimate partner psychological
violence (Hypothesis Four) and hypothesize that there will
be continuity of intimate partner psychological violence
across time (Hypothesis Five).
In the IYFP, data from the family of origin (N = 451) were
collected annually from 1989 through 1992. Participants
included the target adolescent age 13, their parents, and a
sibling within 4 years of age of the target adolescent (217
451 fathers) were originally recruited for a study of family
economic stress in the rural Midwest. When interviewed in
1989,the target adolescent
(M age = 12.7 years; 236 females, 215 males). Participants
were recruited from both public and private schools in eight
rural Iowa counties. Due to the rural nature of the sample,
there were few minority families (approximately 1 % of the
population);therefore, all of the participants were Caucasian.
Seventy-eight percent of the eligible families agreed to par-
ticipate. The families were primarily lower middle–or mid-
had a median family income of $33, 700. Families ranged in
size from 4 to 13 members, with an average size of 4.94
members. Fathers’ average age was 40 years, while mothers’
average age was 38.
In 1994, the families from the IYFP continued in another
project, the Family Transitions Project (FTP). The same
target adolescents participated in the FTP to follow their
transition into adulthood. Beginning in 1995, the target
adolescent (1 year after completion of high school) partic-
ipated in the study with a romantic partner. The FTP has
followed the target youth from as early as 1989 through
2007 (M target age = 32 years), with a 90 % retention rate.
The present article includes targets who participated
from adolescence through adulthood. The data were ana-
lyzed at the three developmental timepoints. The first was
when the target adolescent was 14, 15, and 18 years old
(1990, 1991, and 1994). The second timepoint was during
emerging adulthood when the target was 19, 21, and
23 years old (1995, 1997, and 1999). Finally, the last
period occurred when the target was in adulthood at ages
27, 29, and 31 years (2003, 2005, and 2007). Throughout
adulthood, targets participated with a romantic partner at
the time of the visit. The romantic partner could include a
boy/girlfriend, cohabitating partner, or a married spouse.
Of the 451 original target adolescents, 392 (52 % female)
of them participated with a romantic partner at multiple
504 J Youth Adolescence (2013) 42:500–517
points throughout adulthood and are included in the present
analyses. Only 54 (14 %) of the adolescents remained with
the same romantic partner across all the assessments.
Because missing cases on all variables were largely due to
the unavailability of data for a specific wave rather than
families no longer participating in the study, the present
analyses used Full Information Maximum Likelihood
(FIML) estimation processes to test predicted relationships
(Allison 2003) rather than deleting cases with any missing
When the target was an adolescent, all of the families of
origin were visited twice in their homes each year by a
trained interviewer. Each visit lasted approximately
2 hours, with the second visit occurring within 2 weeks of
the first visit. During the first visit, each family member
(mother, father, target adolescent, and sibling closest in age
to the target) completed questionnaires pertaining to sub-
jects such as parenting, individual characteristics, and the
quality of family interactions. During the second visit,
family members participated in four structured interaction
tasks that were videotaped. In the present analyses, we used
observer ratings from three of those tasks. Task 1 (parent–
child discussion) involved the parent and adolescent
engaging in a conversation about family rules, events, and
problems and lasted 30 min. Task 2 (problem solving
interaction) lasted 15 min and involved all family members
discussing and solving an issue they identified as prob-
lematic such as conflict over money or discipline. Task 3
(sibling discussion) was not part of the scope for this report
and therefore not considered here. Task 4 (marital inter-
action) involved the parents (mothers and fathers) of the
target adolescent engaging in a discussion of topics such as
childrearing, employment, and other life events. Trained
observers coded the quality of these interactions using the
Iowa Family Interaction Rating Scales (Melby et al. 1998).
These scales have been shown to demonstrate adequate
reliability and validity (Melby and Conger 2001).
From 1995 through 2007 the target adolescents, now
adults, and their romantic partner participated in data col-
lection. Each target adult and his or her romantic partner
were visited biennially in their home by trained inter-
viewers. During that visit, these adults completed a series
of questionnaires, some of which addressed their romantic
relationship. In addition to questionnaires, the target adult
and his or her romantic partner participated in a videotaped
25 minutes discussion task (Task 5) that was essentially the
same as that used for their parents during adolescence. The
means, standard deviations, and minimum and maximum
scores for the interaction tasks as well as for all study
variables are provided in Table 1.
Intimate Partner Psychological Violence
Victimization: Partner Psychological Violence to Adolescent
(Target) in Emerging Adulthood (Age 19–23) and Adulthood
Partner psychological violence to adolescent
(target) was measured with information from two reporters:
target report of partner’s behavior to the target and observer
her partner’s psychological violence included items such as
asking how often during the past month his/her partner got
or yelled at him/her because he/she was mad, or argued with
him/her whenever he/she disagreed about something (Con-
ger 1988). Responses ranged from 1 = never to 7 = always
forthe24items(a = .89foremergingadulthoodand.93for
Trained observers coded the degree to which the partner
engaged in verbal attacks to the target adult during a
videotaped discussion task (Task 5 described earlier).
Verbal attack was defined as personalized and unqualified
disapproval of another’s personal characteristics and crit-
icism of a global and enduring nature. Observer ratings
were on a nine–point scale, but were recoded to seven
point scales so as to have possible ranges equal to the
target report. The percentage of agreement for the
observed scales across the two timepoints were .82 and .81
respectively. The target self–report and observer rating of
partner at each of the two timepoints were combined into
three parcels which served as indicators for a latent vari-
able; this process is explained further in the analysis sec-
tion. Latent variables were created to represent partner
psychological violence to target at both emerging adult-
hood and adulthood.
Perpetration: Adolescent (Target) Psychological Violence
to Partner in Emerging Adulthood (Age 19–23) and
Adulthood (Age 27–31)
Adolescent (target) psychologi-
cal violence to partner was also measured with information
from two reporters: partner report of target’s behavior to
the partner and observer report of target’s behavior to their
partner. Partner report of target’s psychological violence
included items such as asking how often during the past
month the target got angry at the partner, criticized the
partner for his/her ideas, shouted or yelled at the partner
because he/she was mad, or argued with the partner
whenever he/she disagreed about something (Conger
1988). Responses ranged from 1 = never to 7 = always
for the 24 items (a = .88 for emerging adulthood and .93
Trained observers coded the degree to which the target
engaged in verbal attacks to their romantic partner during a
J Youth Adolescence (2013) 42:500–517505
videotaped discussion task (Task 5 described earlier).
Verbal attack was defined in the same way as it was for
victimization. Observer ratings were on a nine–point scale,
but were recoded to seven point scales so as to have pos-
sible ranges equal to the partner report. The percentage of
agreement for the observed scales across the two time-
points were .83 and .80 respectively. The partner self–
report and observer rating of target at each of the two
timepoints were combined into three parcels, which served
as indicators for a latent variable. Latent variables were
created to represent target psychological violence to part-
ner at both emerging adulthood and adulthood.
Individual Risk Factors Experienced During
reported how often problem behaviors occurred as a result
of consuming alcohol or drugs during the past year. The
measure was developed from diverse sources for the
1 = never to 4 = four or more times. Examples of prob-
lem behaviors included, ‘‘In the past year, how often did
you get drunk?’’ and ‘‘In the past year, when drinking or
using drugs, how often did you get into a fight?’’ A total of
Use Problems(Age 14–15)
Table 1 Descriptive statistics for study variables (N = 392)
Intimate partner psychological violence
Emerging adulthood victimizationa(1995, 1997, 1999)
Observer report1.42 0.701.00 5.00
Target report of partner
Adulthood victimizationb(2003, 2005, 2007)
2.49 0.83 1.006.75
Observer report1.54 0.831.00 5.33
Target report of partner
Emerging adulthood perpetrationa(1995, 1997, 1999)
Observer report1.49 0.781.00 7.00
Partner report of target
Adulthood perpetrationb(2003, 2005, 2007)
Observer report1.670.891.00 5.00
Partner report of target
Individual risk factors from adolescencec
Substance use problems1.06 0.16 1.002.27
Sexual activity 0.160.70 0.0010.00
Antisocial behavior 2.680.741.00 4.86
Low self–esteem 1.970.56 1.003.80
Association with deviant Peers1.26 0.261.00 2.71
Family risk factors from adolescencec
3.48 2.08 0.009.50
Interparental psychological violence (1991, 1992)
Observer report 1.070.161.00 2.50
Father report of wife 2.600.891.00 6.00
Mother report of husband 2.421.001.006.75
Parent–to–adolescent psychological abuse (1991, 1992)
Observer report1.19 0.390.504.00
Target report of mother2.770.941.006.38
Target report of father2.620.98 1.00 6.50
Family income (1991, 1992)8.79 5.63-15.0841.30
Family stress0.580.94-1.10 3.30
PV psychological violence
aAges 19–23,bAges 27–31,cAges 14–15,dAge 18
506J Youth Adolescence (2013) 42:500–517
11 items were combined and averaged across the two
assessments into a scale (a = .87) which served as the sole
indicator for a latent variable.
Sexual Activity (Age 14–15)
of sexual partners they had in the past 12 months.
Responses ranged from zero sex partners to more than 6
partners at both age 14 and age 15. The reports were
summed to reflect the total number of sexual partners
across the two timepoints into a scale (a = .63) which
served as the sole indicator for a latent variable.
Targets reported the number
Antisocial Behaviors (Age 14–15)
their own antisocial behaviors using items from the Buss
and Durkee (1957) hostility scale. Responses ranged from
1 = not at all to 5 = exactly, and included, ‘‘If someone
hits me first, I let him have it’’ and ‘‘When I get mad, I say
nasty things.’’ A total of seven items were averaged across
the two timepoints into a scale (a = .90) which served as
the sole indicator for a latent variable.
Low Self–Esteem (Age 14–15)
esteem was measured as a manifest variable using
self–report. Adolescents completed Rosenberg’s (1965)
self–esteem scale. Responses ranged from 1 = strongly
agree to 5 = strongly disagree. A total of 10 items were
combined and averaged across the two assessments into a
scale (a = .91) which served as the sole indicator for a
Target adolescent self–
Association with Deviant Peers (Age 14–15)
rated how many of their friends engaged in deviant
behaviors such as run away from home, purposely damage
or destroy property that did not belong to them, or use
alcohol and drugs (Elliott et al. 1985). Responses ranged
from 1 = none of them to 5 = all of them. A total of 17
items were combined and averaged across the two assess-
ments into a scale (a = .89) which served as the sole
indicator for a latent variable.
Academic Difficulties (Age 14–15)
(GPA) was measured as a manifest variable using target
adolescent self–report. The adolescents reported their GPA
on a scale from 00 = F to 10 = A, and the reports were
averaged across timepoints into a scale (a = .89) which
served as the sole indicator for a latent variable.
Grade point average
Negative Emotionality (Age 18)
was assessed using the Multidimensional Personality
The target’s personality
Harkness et al. 1995). An abbreviated 33–item informant
report for the MPQ was used to obtain reports of adoles-
cent personality from the parents. Mothers and fathers
independently rated the adolescent on a 5–point scale by
comparing their adolescent on a particular trait to other
individuals of the same age and gender (1 = Lowest 5 %;
2 = Lower 30 %; 3 = Middle 30 %; 4 = Higher 30 %;
5 = Highest 5 %). The correlations between mother and
father reports ranged from .40 for alienation to .47 for
stress reaction, which indicated a reasonable amount of
agreement, a result broadly consistent with existing per-
sonality research (e.g., Funder 1999). Reports were com-
bined into the negative emotionality superfactor for each
parent, then averaged across mother and father responses
(a = .80).
(MPQ)developed by Tellegen(e.g.,
2 = female) was assessed at age 14.
Self–report of gender where (1 = male,
Family Risk Factors Experienced During Adolescence
Interparental Psychological Violence (Age 14–15)
parental psychological violence was measured with three
indicators: father report of his wife’s behavior to him,
mother report of her husband’s behavior to her, and
observer report of mother and father behavior to each
other. Spouse reports of psychological violence included
items such as how often during the past month the spouse
got angry at them, criticized them for their ideas, shouted
or yelled at them because they were mad, or argued with
them whenever they disagreed about something (Conger
1988). Responses ranged from 1 = never to 7 = always.
Internal consistency reliability was acceptable for father
report of his wife (mean a = .91) and mother report of her
husband (mean a = .93).
Observer report of interparental psychological violence
was measured using task 2 (family problem solving
interaction) and task 4 (marital interaction) as described
above. Trained observers coded the degree to which the
father and mother engaged in verbal attacks toward each
other. Verbal attack was defined in the same manner as
victimization and perpetration. Observer ratings were on
a nine–point scale, but were recoded to seven point
scales so as to have possible ranges equal to mother and
father self– report. The percentage of agreement for the
observed scales for father behavior to mother and mother
behavior to father are .96 and .97 respectively. The
father self–report, mother report, and observer rating of
parent across the two interaction tasks were combined
into three parcels, which served as indicators for a latent
J Youth Adolescence (2013) 42:500–517 507
Parent psychological violence to the adolescent
was measured with three indicators: Target adolescent
report of father behavior to him/her, target adolescent
report of mother behavior to him/her, and observer report
of mother and father behavior to the adolescent. Adolescent
report of father and mother psychological violence inclu-
ded asking the adolescent how often during the past month
their father and mother got angry at him/her, criticized him/
her for his/her ideas, shouted or yelled at him/her because
she was mad, or argued with him/her whenever she dis-
agreed about something (Conger 1988). Responses ranged
from 1 = never to 7 = always. Internal consistency reli-
ability was acceptable for adolescent report of father (mean
a = .87) and mother (mean a = .86).
Observer report of parental psychological violence to
the adolescent was measured using Task 1 (parent–child
discussion interaction). Trained observers coded the
degree to which the father and mother engaged in verbal
attacks with the adolescent. Verbal attack was defined
and coded in the same manner as the previous obser-
vational tasks. Observer ratings were on a nine–point
scale, but were recoded to seven point scales so as to
have possible ranges equal to adolescent self– report.
The percentage of agreement for the observed scales for
father behavior to adolescent and mother behavior to
adolescent are .92 and .95 respectively. The adolescent
self–report of father, adolescent self–report of mother,
and observer rating of parent behavior were combined
into three parcels, which served as indicators for a latent
Family Income (Age 14)
family per capita income was assessed in 1990 and 1991.
The mean family per capita income across waves was
divided by 1,000 for the ease of analysis and interpretation
in this study. It should be noted that family per capita
income included negative values because some families
had negative net farm income.
Mother and father self–report of
Family Stress (Age 15)
stress, we took an approach similar to Sameroff (1998;
Sameroff et al. 1987) and Furstenburg (Furstenberg et al.
1999) and used 1991 measures of economic pressure,
parental psychological distress, and parent trait hostility to
construct an index of family stress. To create the family
stress index score for each family, we first created five
continuous scales of family stress (cannot make ends
depression, and parental hostility). Then each of the five
scales was dichotomized so that the quarter of the sample
To assess dimensions of family
reporting the most family stress on that scale was
assigned to the high family stress category for that scale
(coded 1) and the remaining 75 % of the sample was
assigned to the low family stress category for that scale
(coded 0). Most scales, however, did not allow for an
exact 25 and 75 % split, which resulted in 22.5–27.7 % of
the sample being assigned to the high stress category
across all five scales. The five dichotomized scales were
then averaged to make the family stress index, which
ranged from zero to one. The family stress index had a
mean of .27 and a standard deviation of .31. Approxi-
mately 44 % of the sample fell into the low family stress
category on all five items, while about 6 % of the sample
was in the high family stress category for all items. A
brief description of each of the six scales, the percentage
of the sample in the high and low family stress groups for
each of the six components, and the mean score for the
high and low family stress groups for each component is
provided in the Appendix.
To test our overall conceptual model (Fig. 1), we utilized
structural equation models. When evaluating the fit of
structural models to the data, we used several types of
indicators. We used the standard chi–square index of sta-
tistical fit that is routinely provided under maximum like-
lihood estimation of parameters. We also used two indices
of practical fit, the root mean square error of approximation
(RMSEA; Browne and Cudeck 1993) and the Tucker—
Lewis index (TLI; Tucker and Lewis 1973). RMSEA val-
ues under .05 indicate close fit to the data, values between
.05 and .08 represent reasonable fit (Hu and Bentler 1999).
For the TLI, fit index values should be greater than .90, and
preferably greater than .95, to consider the fit of a model to
data to be acceptable.
Our hypotheses related to the structural model, and prior
work suggests that use of multi–item parcels as indicators
for latent variables is defensible in such situations
(Bandalos and Finney 2001; Marsh and O’Neill 1984). Use
of parcels in these circumstances addresses rater effects
and reduces the number of estimated paths in the model. A
domain–representative approach to parcel construction
treats information from each reporter as equally valid and
unit–weights the raters by distributing their information
across the parcels. Following the procedures outlined by
Kishton and Widaman (1994), domain representative par-
cels were created, which allowed rater–specific variance
and variance common across raters to contribute to the
For purposes of illustration, we created the three mani-
fest variables that served as indicators for the latent factor
508J Youth Adolescence (2013) 42:500–517
‘perpetration of psychological violence during emerging
adulthood’ in the following way. We began with 15 items
romantic partner during emerging adulthood (12 items
from the romantic partner, and three observer ratings). We
randomly selected four romantic partner items and one
observer rating. We first averaged the four romantic partner
items so that the parcel would contain equal proportions of
variance from both reporters, then we averaged the
romantic partner items with the observer rating to create
our first parcel. From the remaining 10 items, we randomly
selected four items from romantic partner, and one obser-
ver rating, which we averaged in like manner to create the
second parcel. The remaining five items were similarly
averaged into a third parcel. Each of these parcels, as well
as all other parcels, had an aggregate reliability of .65 or
Correlations and Descriptive Statistics
Descriptive statistics for all study variables are presented
in Table 1, and correlations are presented in Table 2.
Consistent with Hypothesis 1, there was considerable sta-
bility from emerging adulthood to adulthood for victim-
ization(r = .34for males,
perpetration (r = .17 for males, .53 for females). Victim-
ization and perpetration were significantly correlated at
both emerging adulthood (r = .78 for males, .70 for
females) and adulthood (r = .68 for males, .69 for
females). The patterns of associations were generally
supportive of the theoretical model, and justified the for-
mal model testing that follows.
We used Mplus Version 7 (Muthe ´n and Muthe ´n 2006) to
estimate the model using full information maximum like-
lihood estimation, first focusing on the measurement
model, then turning to the structural paths predicted by our
theoretical model. We ran analyses testing for measure-
ment invariance across males and females, in order to test
whether the latent variables could be considered equivalent
across the two groups. A series of analyses demonstrated
weak factorial invariance across gender for the latent
variables (see Meredith 1993). In addition, in the following
model tests we evaluated gender differences in findings for
targets and their romantic partners. There were no signifi-
cant differences by gender; therefore we report the results
for the combined sample.
Our attempts to fit a model with target perpetration and
victimization by target separately were unsuccessful due to
the high correlations between perpetration and victimiza-
tion at each timepoint. One of the principal reasons we
used different reporters of victimization and perpetration
was to eliminate shared–method variance and thereby
decrease the association between the two constructs.
Nevertheless, the data suggested that even in the absence of
shared–method variance, both victimization by target and
target perpetration of psychological violence were most
appropriately conceptualized in this sample as indicators of
the same variable. Consequently, we modeled higher–order
latent variables of target psychological violence using the
latent constructs for victimization and perpetration as
indicators.This model showed
v2= 137.58, df = 48, p\.001, TLI = .941, RMSEA =
.055, and was the model used for our primary analyses. All
covariates were added to this model, and then chi–square
difference tests were used to trim the model. Nonsignificant
paths were set to zero (which did not significantly worsen
model fit), resulting in a final model fit of: v2= 317.37,
df = 174, p\.001, TLI = .949, RMSEA = .046. All
manifest loadings had standardized loadings of k = .40 or
higher. The coefficients for this model are presented in
Standardized coefficients from the final model that
reached statistical significance are presented in Fig. 2.
Regarding Hypothesis One, negative emotionality and
sexual activity during adolescence both predicted higher
levels of psychological violence during emerging adult-
hood as well as adulthood. Academic difficulties and
gender positively predicted violence in emerging adult-
hood only. However, the individual risk factors of sub-
stance use, antisocial behaviors, low self–esteem, and
associations with deviant peers were not statistically
We did not find support for Hypothesis Two, in that
exposure to parental intimate partner violence during
adolescence did not predict later intimate partner psycho-
logical violence in either emerging adulthood or adulthood.
However, Hypothesis Three was supported; parent–child
psychological violence during adolescence predicted inti-
mate partner psychological violence, during emerging
adulthood and adulthood. Consistent with Hypothesis Four,
exposure to family stress during adolescence predicted
intimate partner psychological violence. Family stress was
the only predictor to show a lagged or ‘sleeper’ effect,
predicting psychological violence only in adulthood, but
not in emerging adulthood. And finally, we found support
for Hypothesis Five that psychological violence between
romantic partners (defined as both victimization and per-
petration) showed stability from emerging adulthood to
adulthood (b = .28, SE = .06).
J Youth Adolescence (2013) 42:500–517509
Table 2 Correlations among variables used in analyses
Intimate partner violence in emerging adulthood
Intimate partner violence in adulthood
Individual risk factors from adolescencec
5. Substance use
6. Sexual activity
7. Antisocial behaviors
8. Low self–esteem
9. Assoc. dev. peers
10. Academic difficulties
11. Neg. emotionalityd
Family risk factors from adolescencec
12. Interparental PV
13. Parent–to–adolescent PV
14. Family income
15. Family stress
Coefficients for males are above diagonal
PV psychological violence
aAges 19–23,bAges 27–31,cAges 14–15,dAge 18
510 J Youth Adolescence (2013) 42:500–517
The intergenerational transmission of violence directed
toward intimate partners is well documented (e.g., Kalmuss
1984; Kwong et al. 2003; Straus et al. 1980). However, this
predominately cross–sectional and retrospective literature
is limited with self–selection, endogeneity, and reporter
biases as it has not been able to assess how individual and
family behaviors simultaneously experienced during ado-
lescence influence intimate partner violence across time.
The current study attempts to overcome some of these
limitations by prospectively assessing a multitude of indi-
vidual and family risk factors for intimate partner violence
in both emerging adulthood and adulthood. We assessed
psychological intimate partner violence as it has been
shown to be highly prevalent, relatively stable, largely
bidirectional, and has a severe impact (e.g., Carney and
Barner 2012; Lawrence et al. 2009; O’ Leary and Maiuro
2001; Shortt et al. 2012; Taft et al. 2006). Furthermore, it
has been identified as a predictor of physical violence in
romantic relationships (e.g., Capaldi et al. 2007; Frye and
Karney 2006). Thus, understanding predictors of psycho-
logical intimate partner violence to be targeted in preven-
tion programs may in turn, reduce rates of subsequent
Fig. 2 Statistical model. Note
Table 3 Structural equation modeling coefficients
Direct paths from Fig. 2Emerging
Individual risk factors
Substance use0.25 (0.15)0.12 (0.14)
Sexual activity0.17 (0.06)*0.15 (0.05)*
Antisocial behavior0.03 (0.08)0.10 (0.08)
Low self–esteem–0.02 (0.08) –0.09 (0.07)
Association with deviant Peers–0.23 (0.14)–0.14 (0.15)
Academic difficulties 0.14 (0.07)* 0.07 (0.07)
Negative emotionality0.11 (0.04)* 0.10 (0.04)*
Female 0.28 (0.05)*0.14 (0.08)
Family risk factors
0.01(0.05) 0.07 (0.06)
0.17 (0.06)* 0.25 (0.06)*
Family income–0.02 (0.06)–0.03 (0.06)
Family stress–0.02 (0.06)0.18 (0.05)*
Standard errors appear in parentheses. * p\.05
J Youth Adolescence (2013) 42:500–517511
physical violence, and ultimately reduce the often damag-
ing and costly physical and psychological consequences of
physical intimate partner violence.
This article also overcomes limitations of the literature
in that victimization and perpetration often are assessed
independently rather than simultaneously. Past literature
that addresses these events separately obscures patterns
where partners both perpetrate violence towards a partner
and experience victimization. Thus, we tested models
where victimization and perpetration were assessed sepa-
rately using self–reports and models where we created a
dyadic couple variable of intimate partner violence using a
combination of self, partner, and observation reports.
Those that used a combination of reporters, including the
observational data, were the most robust models. We dis-
cuss the results of the models and the implications for
prevention and future research below.
Using a multi–method multi–trait prospective longitu-
dinal approach, the current study tested five hypotheses
related to the developmental–interactional model (i.e.,
Capaldi and Gorman–Smith 2003) of intimate partner
violence across time, romantic partners, and generations.
We found significant stability in intimate partner violence
from emerging adulthood to adulthood, even though over
80 % of the targets in this sample changed romantic
partners over this period. This suggests that intimate
partner violence is a behavioral pattern that is recreated
across subsequent relationships. After controlling for a
host of individual risk factors as well as interparental
psychological violence, the results show the continuity of
psychological violence across adulthood. We also find that
exposure to parent–to–child psychological violence during
adolescence is a key predictor of later intimate partner
violence. Because intimate partner violence was opera-
tionalized at the dyadic level, these findings hold for per-
petration as well as victimization.
We acknowledge that some might object to our decision
to combine victimization and perpetration into a single
variable. A possible objection would be that while corre-
lated, the two variables are functionally nonequivalent, and
have different antecedents. However, as can be seen in
Table 2, the pattern of correlations reflect how victimiza-
tion and perpetration were not consistently different in
terms of their correlation with other variables. Further-
more, the standardized loadings onto the second–order
latent factor were quite robust (ranging from .76 to .91)
suggesting that the variables were very highly correlated
after removing measurement error. The fact that there was
no shared method variance across the two variables further
strengthens the argument that these variables may be best
thought of as indicators of a variable operationalized at the
dyadic level. Although personal characteristics affect
which role a person assumes in a relationship characterized
by intimate partner violence (perpetrator or victim), and
likely contribute to intimate partner violence carrying
forward to later relationships, at its core, intimate partner
violence appears to be a characteristic of a relationship, not
Contrary to expectations, the results did not support the
intergenerational transmission of violence. Several studies
have suggested that parental behavior toward the youth
may be more predictive of youth violence than exposure to
parental intimate partner violence (Capaldi and Clark 1998;
Conger et al. 2000; Neppl et al. 2009; Krishnakumar and
Buehler 2000; Stith et al. 2000). Indeed, findings suggest
that parent–to–adolescent psychological violence, which
may be seen as a form of psychologically abusive parent-
ing, is particularly detrimental and is predictive of similar
forms of violence in their emerging adult and adult
romantic relationships. It may be true that, at the simple
correlation level, both witnessing and experiencing paren-
tal violence or abuse in the family of origin are associated
with later acts of intimate partner violence. However, when
a host of individual and family risk factors are simulta-
neously assessed, parenting is shown to have a very critical
role in the development of intimate partner violence. Other
studies have found that when a child experiences parent–
to–adolescent aggression, in comparison to witnessing in-
terparental aggression, being exposed to parental aggres-
sion is associated more directly with subsequent intimate
partner violence (see Ehrensaft et al. 2003; Marshall and
In addition, findings suggest that exposure to family
stress was a ‘‘sleeper effect’’ as it was associated with
intimate partner violence in adulthood but not in emerging
adulthood. That is, experiences (or dimensions) of family
stress such as economic pressure, parental psychological
distress, and parent trait hostility may not spillover to
intimate partnerships until later on in adulthood. In con-
trast, we found evidence that individual risk factors were
related more proximally with violence in intimate part-
nerships during emerging adulthood. While a multitude of
individual risk factors were assessed, negative emotion-
ality and the number of sexual partners in adolescence
were found to increase significantly intimate partner vio-
lence in emerging adulthood and adulthood. On the other
hand, academic difficulties were found to increase vio-
lence in emerging adulthood only. Together, these findings
suggest developmentally–specific causes of intimate part-
ner violence, which merit attention in future work in this
Finally, the present study found that females perpetrated
higher levels of intimate partner psychological violence
than males in emerging adulthood but not in adulthood.
This is consistent with previous work that suggests that
females are more aggressive than males in marriages and
512 J Youth Adolescence (2013) 42:500–517
relationships (e.g., Steinmetz 1977; Straus et al. 1980).
However, when testing whether the overall model and the
processes or predictors of intimate partner violence varied
for males and females, we found no statistically significant
differences (Kalmuss 1984; Kwong et al. 2003. Thus, the
interpretation of these gender differences should not
overshadow that men, on average, are able to inflict more
Despite the above findings, this study is not without
limitations. For example, the sample was limited in terms
of ethnic and racial diversity, geographic location (rural
Iowa), and family structure (all adolescent children lived
with their biological parents). However, other findings
from this sample have been replicated in more diverse
samples (Conger and Conger 2002; see Conger and
Donnellan 2007). In addition, while intimate partner vio-
lence was generally low in this sample, the prevalence rates
are comparable to those in national surveys (e.g., Straus
and Gelles 1986). Therefore, our findings are fairly repre-
sentative of community samples but may not be general-
ized to high risk families (Capaldi and Clark 1998).
In terms of future research, the current study only
assessed psychological intimate partner violence. There-
fore, future studies should explore whether these relation-
ships hold for physical violence as well as sexual violence.
In addition, other relationship factors such as acceptability
of violence, relationship satisfaction, relationship type and
length as well as variations in relationship structures across
sexual orientations should also be explored. Finally, future
studies should assess rates of perpetration and victimiza-
tion for more than two timepoints. Person–oriented
approaches, such as growth curves, and latent class anal-
yses, should be utilized in future work to elucidate patterns
of co–occurring victimization and perpetration for indi-
viduals overtime. Person-oriented approaches also could
address variations in intimate partner violence across
relationships (i.e., stability and instability), including the
importance of churning (Halpern-Meekin et al. 2013).
Furthermore, understanding how the individual and family
risk factors assessed in the present study influence these
patterns of behaviors is also needed.
Despite these limitations, the present study contributes
to the literature by examining individual and family pre-
dictors of psychological violence using a prospective,
multi–informant design. The findings point to a robust
connection between parent–to–child psychological vio-
lence and intimate partner relationships in both emerging
adulthood and adulthood; thus supporting the notion that
experiences in the family of origin are linked to how
individuals approach subsequent romantic relationships.
These results can be used to assist in comprehensive
in violent intimate
empirically informed prevention programs that aim to
reduce intimate partner violence, which largely have been
underdeveloped (Ehrensaft et al. 2003; Shortt et al. 2012).
In particular, programs that reduce violent behaviors in the
family of origin, particularly parent–to–adolescent psy-
chological violence and family stress, ultimately may
reduce intimate partner violence in adulthood. Further-
more, programs that decrease risky sexual behaviors or
provide services to youth with negative emotionality
might serve as useful targets for preventing psychological
violence in future romantic relationships. In addition,
prevention programs that include school experiences that
enhance the academic achievement of students may lead
to more positive romantic relationships in emerging
adulthood, which is a key period for intimacy develop-
ment. Other work has shown the importance of school
factors in reducing the perpetration of emerging adult
intimate violence (Schnurr and Lohman 2008). Taken
together, these results argue that human service profes-
sionals working with victims or perpetrators of intimate
partner violence in adulthood need to think systematically
and comprehensively to understand the influences that
early experiences have on adult current behaviors in
from the Eunice Kennedy Shriver National Institute of Child Health
and Human Development, the National Institute of Mental Health,
and the American Recovery and Reinvestment Act (HD064687,
HD051746, MH051361, and HD047573). The content is solely the
responsibility of the authors and does not necessarily represent the
official views of the funding agencies. Support for earlier years of the
study also came from multiple sources, including the National Insti-
tute of Mental Health (MH00567, MH19734, MH43270, MH59355,
MH62989, and MH48165), the National Institute on Drug Abuse
(DA05347), the National Institute of Child Health and Human
Development (HD027724), the Bureau of Maternal and Child Health
(MCJ–109572), and the MacArthur Foundation Research Network on
Successful Adolescent Development Among Youth in High–Risk
Settings. Correspondence regarding this manuscript should be
addressed to Brenda Lohman. A special thank you is extended to the
children, caregivers, and families who have graciously participated in
this study and given us access to their lives for so many years.
This research is currently supported by grants
violence, she participated in the design, conceptualization, analytic
planning and the writing of this article. As an Investigator of FTP, TN
has been an integral part in the design and coordination of all phases
of this study as well as the development, conceptualization, and
writing of this article. JS and TS were primarily responsible for data
Given BL’s interests in intimate partner
See Table 4.
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Table 4 The family stress index
%High stress Normal stress
Measure of family stressHigh stress
M SDM SD
1. Can’t make ends meet24.8 2.501.06-0.461.03
2. Financial cutbacks 23.38.901.972.442.02
3. Parental anxiety 22.51.640.661.050.07
4. Parental depression25.41.970.511.210.16
5. Parental hostility27.7 1.800.53 1.150.11
6. Marital hostility24.7 2.190.610.740.40
Percent of the sample in the high family stress category on each
family stress item and mean scores for the high and low stress groups
on each of the six measures
1. Can’t make ends meet assessed families’ ability to pay monthly
bills, and is the average of two standardized items. Observed scores
range from—3.71 to 5.03, with higher scores indicating greater eco-
nomic pressure. Nearly 25 % of the sample fell into the high stress
category for this measure
2. Financial cutbacks assessed whether families made significant
cutbacks in daily expenditures because of limited resources. There is
a maximum of 15 possible financial cutbacks. Families in the high
stress category (23.3 %) reported making almost four times as many
cutbacks as families in the low stress category
3. Parental anxiety was assessed with the Anxiety subscale of the
Symptom Checklist-90-Revised (SCL-90-R; Derogatis 1983). Scores
in the sample ranged from 1 to 4.8. Families scoring 1.25 or more
were assigned to the high stress category (22.5 %)
4. Parental depression was assessed with the Depression subscale of
the SCL-90-R (Derogatis 1983). Observed scores ranged from 1 to
4.69. Families scoring more than 1.54 were assigned to the high stress
category (25.4 %)
5. Parental trait hostility was assessed with the Hostility subscale of
the SCL-90-R (Derogatis 1983). Scores in the sample ranged from 1
to 4.67. Families scoring 1.42 or more were assigned to the high stress
category (27.7 %)
514J Youth Adolescence (2013) 42:500–517
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Dr. Brenda J. Lohman is an Associate Professor and Director of
Graduate Education in Human Development and Family Studies at
Iowa State University. Her research interests focus on the successful
academic, physical, psychosocial and sexual adjustment of adoles-
cents especially those from economically disadvantaged families or
families of color.
Dr. Tricia K. Neppl is an Assistant Professor in Human Develop-
ment and Family Studies at Iowa State University. Her work
addresses the intergenerational transmission of parenting and child
Jennifer M. Senia is a Doctoral Candidate in Human Development
and Family Studies at Iowa State University. Her research assesses
how family stress influences family structure and individual well-
Dr. Thomas J. Schofield is an Assistant Professor in Human
Development and Family Studies at Iowa State University. His
research interests focus on understanding the mediating and moder-
ating factors associated with the stability of parenting.
J Youth Adolescence (2013) 42:500–517 517