Gender,Life Domains,and Intimate Partner Violence Perpetration: A Partial Test of Agnew’s General Theory of Crime and Delinquency

Abstract

Objectives

We assess the proposed mechanisms outlined in Agnew’s General Theory of Crime and Delinquency about gender differences in crime and deviance (gender differences are due to differences between males and females in their standing on the life domains or differences in the effect of the life domains on the phenomenon among males and females) in accounting for sex differences in intimate partner violence (IPV) among a sample of young adults.

Methods

Drawing data from the International Dating Violence Study (IDVS) and employing the negative binomial regression method, we examined the effects of six self-domains, four family domains, one school/work domain, and one peer domain measures on IPV.

Results

Although males reported a higher frequency across all five life domains compared to females, the number of life domain variables that were significantly related to IPV among females was greater than the number among males. Further, the effects of the life domain variables on IPV were different for males and females with the peer variable (criminal peers) exhibiting the greatest effect on IPV among males and the self-domain (anger issues) demonstrating the greatest effect on IPV among females.

Conclusions

Agnew’s theory is well suited to assess sex differences in IPV.

Keywords

Agnew’s integrated general theory life domains intimate partner violence sex (gender) differences

Introduction

Intimate partner violence (IPV), defined as physical, sexual, or psychological harm perpetrated by a current or former romantic partner, is a significant legal, social, and public health problem (Saltzman et al. 2002). In the United States (U.S.), it is estimated that one in three women and one in four men have experienced physical and/or sexual aggression, and nearly half of all women and men have experienced psychological and verbal aggression by an intimate partner at some point in their lifetime (Smith et al. 2017). The consequences of IPV are well documented in the literature. Notably, it has been suggested that even mild and infrequent forms of IPV have implications for the victim’s physical and mental well-being and his/her relationship functioning (McNeal and Amato 1998; Umberson et al. 1998; Lawrence and Bradbury 2001; Lawrence et al. 2009).

To understand IPV, several theoretical models and typologies of IPV perpetration have been articulated. However, the literature still lacks a theoretical framework that provides systematic connections among the vast assortment of risk factors. In their review of IPV theories, Langer and Lawrence (2010) noted that “a greater understanding of IPV and future investigations of IPV need to be guided by comprehensive theories that incorporate multiple theoretical perspectives, model the dynamic and interactional nature of IPV, and emphasize variables or processes that can be targeted in interventions” (p. 369). Currently, there is one theory that not only integrates the key insights from the dominant theoretical perspectives on crime and deviance that are pertinent to IPV—namely, biological, psychological, control, strain, and social learning—but also organizes known risk factors of IPV as identified in these major crime theories and prior research into an integrated perspective. The theory also posits direct, indirect, and reciprocal effects among risk factors and crime, and the nonlinear and/or contemporaneous effects of the risk factors on crime and one another. The theory is Agnew’s (2005) General Theory of Crime and Delinquency and to date, it has not been applied to examine IPV perpetration, a crime of serious human and policy significance, but we believe could offer important promise in this space—at least in a preliminary fashion.

In this paper, we examine the efficacy of Agnew’s theory in understanding gender differences in IPV perpetration. Agnew’s perspective is well suited for exploring this topic because the theory was developed to account for both within- and between-individual patterns of offending. According to Agnew, a range of individual and social variables within five life spheres or domains (e.g., self, family, school, work, and peer) affect crime and deviance, and group differences in crime rates, including sex differences, are either due to (1) differences in the standing on the life domains between the groups or (2) differences in the effects of the life domains on crime among the groups. Hence, a key inquiry the present study seeks to assess is the extent to which the above-proposed processes from Agnew’s theoretical framework may help illuminate our understanding of IPV perpetration among a sample of male and female young adults. In so doing, our analysis offers a preliminary application of Agnew’s theory to IPV in general, and then to gender differences in IPV perpetration in particular, that can be built upon, elaborated, and extended in future inquiry.

The remainder of our paper is organized as follows. First, we introduce Agnew’s theory and describe how IPV risk factors identified in prior research are categorized within Agnew’s framework. We also outline the propositions related to gender differences in crime and deviance posited in Agnew’s theory. Next, we introduce our data and methods. Finally, we present our results and discuss the implications of our findings.

Agnew’s General Theory of Crime and Delinquency

In the field of criminology, Agnew is best known for his efforts at revitalizing traditional strain perspectives (Cohen 1955; Cloward and Ohlin 1960; Merton 1968), and in particular, for his general strain theory (GST; 1992). In 2005, Agnew moved beyond the strain framework and developed a theoretical perspective that essentially integrates the core arguments from the major criminological perspectives with the risk factors and criminogenic characteristics that are known to directly influence crime and deviance. From the leading crime theories, i.e., control, strain, social learning, biopsychological, deterrence, social support, and labeling, Agnew theorizes that crime is more likely to occur when the constraints against it are low and the motivations for it are high. Agnew defines constraints as factors that prevent individuals from engaging in crime and motivations as forces that either “push” or “pull” individuals to commit a crime.

Agnew also stipulates that a host of individual and social variables affect the constraints against and motivations for crime. These variables represent the leading causes of crime identified from major criminological perspectives and empirical research. However, to keep the list of these variables manageable, he only focused on those variables that have moderate to large direct effects on crime. Additionally, to simplify the complex reality between these variables and crime (e.g., many variables affect more than one type of constraint or motivation), Agnew organizes them around five major life domains (or major spheres of life): self, family, school, peers, and work.

Self-Domain

The self-domain encompasses the major traits that comprise the human personality. Agnew proposes two super traits within the self-domain: low self-control and irritability. The super trait of low self-control characterizes individuals who are impulsive, risk-seeking, gravitate toward exciting and high-energy activities, lack ambition, motivation, or perseverance, are not bound by conventional rules and norms, and have little concern over the long-range consequences of their behavior (Gottfredson and Hirschi 1990). The super trait of irritability refers to individuals who tend to have an antagonistic or adversarial interactional style, respond to life events in an aggressive or antisocial manner, attribute adverse experiences to the malicious behavior of others, and show little concern for the feelings and rights of others (Moffitt 1990; Farrington 1994; Caspi 1998; Colder and Stice 1998; Miller and Lynam 2001).

Low self-control has been found to link to IPV perpetration in prior empirical studies. Drawing data from the Transitions into Adulthood and Romantic Relationships Study, Baker, Klipfel, and van Dulmen (2018) found males and females with high levels of self-control were significantly less likely to engage in emotional and verbal aggression directed at their partners relative to males and females with low levels of self-control. Similarly, using a sample of undergraduate students from two large southeastern universities, Gover, Kaukinen, and Fox (2008) found that among male students, low self-control was a significant predictor of both physical and psychological abuse perpetration while among female students, low self-control was significantly related to physical but not psychological abuse perpetration (see also Jennings et al. 2011).

Prior research has also revealed a linkage between elements of the super trait of irritability (i.e., antisocial beliefs, antisocial personality, negative emotionality, and hostility) and perpetration of IPV. Employing data from the Dunedin Multidisciplinary Health and Development Study, Moffitt et al. (2000) found that for both male and female participants, high levels of negative emotionality (i.e., the enjoyment of frightening others and irrational suspiciousness) were significantly related to partner abuse (i.e., physical violence and psychological abuse). Similarly, using a sample of individuals with documented childhood abuse and matched controls, White and Widom (2003) uncovered a positive association between hostility (i.e., having urges to break or smash things and having urges to beat, injure or harm someone) and IPV perpetration (see also Simons et al. 1995; Jankowski et al. 1999; Andrews et al. 2000; Capaldi et al. 2001; White, Merrill, and Koss 2001; Heyman and Slep 2002; Woodward, Fergusson, and Horwood 2002; Ehrensaft et al. 2003, 2004; Brownridge et al. 2008; Lussier, Farrington, and Moffitt 2009; Connolly et al. 2010; Grych and Kinsfogel 2010; Eriksson and Mazerolle 2013).

Family Domain

The family domain emphasizes family life experiences and the interaction between parents and children. According to Agnew, the family variables affecting delinquency include poor parental supervision/discipline, negative parent/juvenile bonding, family conflict, child abuse, the absence of positive parenting, and criminal parents/siblings (Catalano and Hawkins 1986; Loeber and Stouthamer-Loeber 1986; Patterson, Crosby, and Vuchinich 1992; Sampson and Laub 1993; Agnew et al. 2000). Among adults, Agnew suggests that individuals who are not married, negatively bonded to their spouses, or have criminal spouses/partners have a heightened risk of engaging in crime and deviance (Sampson and Laub 1993; Farrington and West 1995; Horney, Osgood, and Marshall 1995; Giordano, Cernkovich and Rudolph 2002; Piquero et al. 2002).

Findings from prior research indicate that poor parent–child relationships and childhood abuse and neglect increase the risk of IPV perpetration. Drawing data from the Toledo Adolescent Relationship Study, Swinford et al. (2000) found child abuse (i.e., harsh physical discipline) predicted dating violence. Similarly, using data from a sample of individuals with documented childhood abuse and matched controls, White and Widom (2003) uncovered that childhood abuse and neglect were significant predictors of IPV for both men and women. Parental monitoring and support have also been linked to IPV. Using data from a sample of students (8th through 10th grades) from three counties in North Carolina, Foshee et al. (2011) found family aggression (i.e., fighting among family members) and parental monitoring (i.e., curfew time implemented by parents) were significantly related to dating violence perpetration (see also Lavoie et al. 2002; Ehrensaft et al. 2003; Lackey 2003; Herrenkohl et al. 2004; Linder and Collins 2005; Renner and Slack 2006; Herrera, Wiersma, and Cleveland 2008; Leadbeater et al. 2008; Miller et al. 2009; Schnurr and Lohman 2008).

School Domain

The school domain focuses on school experiences and the interaction between teachers and students. The school variables affecting delinquency are negative bonding to teachers/school, poor academic performance, little time on homework, low educational and occupational goals, poor supervision/discipline, negative treatment by teachers, and the absence of positive teaching (Colvin 2000; Gottfredson 2000; Thornberry et al. 2003; Agnew 2005). Among adults, Agnew posits that crime will be high among individuals with limited education (Thornberry and Farnworth 1982; Wright et al. 1999).

Whereas the linkage between individual and familial characteristics and IPV has received a considerable amount of empirical attention, the number of research studies assessing the influence of school context on IPV is limited. Nevertheless, factors such as school attachment/bonding and perceived school safety have emerged as risk factors for IPV perpetration, but it is important to bear in mind that the evidence is inconsistent. For example, using a sample of students from three counties in North Carolina, Foshee et al. (2011) found school bonding (i.e., adolescents’ endorsement of the statement, “my school is like my family”) was negatively related to dating violence among girls but positively related to dating violence among boys. Similarly, drawing data from the Three Cities Study, Schnurr and Lohman (2008) uncovered that perception of an unsafe school together with family violence experience were significantly related to dating violence perpetration among African-American male students, while high levels of school involvement together with family violence exposure were significant predictors of dating violence perpetration among Hispanic female students. In a longitudinal study involving a sample of adolescents, Spriggs and colleagues (2009) found that after controlling for race/ethnicity and age, school economic disadvantage (measured as the socioeconomic status (SES) levels of family participants at the school) did not predict dating violence victimization among male students. For female students, those from disadvantaged families attending more economically advantaged schools had a heightened risk of experiencing psychological and physical victimization.

Peer Domain

The peer domain concerns individuals’ relations with their peers and the context of the interaction between individuals and peers. The peer variables posited by Agnew to increase the likelihood of criminal offending are associations with criminal/deviant peers and unstructured and unsupervised time youth spent with their peers (Akers 1998; Colvin 2000; Cernkovich and Giordano 2001; Haynie 2001; Warr 2002; Huizinga et al. 2003; Agnew 2005). Agnew also postulates that while adults are less influenced by peers given the centrality of their work and relationship commitment, peers may occupy a central role in the lives of adults who are not married, unemployed, or employed in “bad” jobs (Crutchfield and Pitchford 1997; Cernkovich and Giordano 2001; Warr 2002).

There is evidence that associating with deviant peers is related to IPV perpetration. Drawing data from the Safe Dates Study, Arriaga and Foshee (2004) found adolescents with friends who were perpetrators of dating violence were significantly more likely to engage in dating violence relative to adolescents without such friends. Similarly, relying on data from the Three Cities Study, Schnurr and Lohman (2008) found increased involvement with antisocial peers was linked to dating violence perpetration for both male and female adolescents. Miller et al. (2009) also employed a sample of students (6th grade) and uncovered that dating violence perpetration was positively related to peer deviance (see also Kinsfogel and Grych 2004; Gagné, Lavoie, and Hébert 2005; Linder and Collins 2005; Schad et al. 2008; Williams, Ghandour, and Kub 2008; Foshee et al. 2011).

Work Domain

The work domain underscores individuals’ employment experiences and their interactions with supervisors and coworkers. According to Agnew, work-related factors that affect crime and deviance include unemployment, poor bonding to work, poor work performance, poor working condition, poor supervision, and criminal coworkers (Crutchfield and Pitchford 1997; Rutter et al. 1998; Colvin 2000; Laub and Sampson 2001; Giordano, Cernkovich, and Rudolph 2002; Piquero et al. 2002). It is noteworthy that the work domain only applies to adults since children and most adolescents typically do not work.

A handful of studies have explored the impact of IPV on employment status and productivity. Employing a sample of 512 predominantly Asian American and Pacific Islander young women living in Hawaii, Crowne et al. (2011) report both concurrent and longitudinal negative associations between IPV and employment stability (see also McFarlane et al. 2000; Alexander 2011). Howell and Pugliesi (1988) also found blue-collar occupation predicted IPV after controlling for age, exposure to parental aggression, low SES, and occupational and employment status while Pan, Neidig, and O'Leary (1994) uncovered a negative relationship between employment income and IPV.¹

Gender Differences in IPV Perpetration

Contrary to conventional findings that males tend to engage in crime and delinquency at a disproportionate rate relative to females, some researchers have found that women are just as likely as men to engage in IPV (i.e., the gender symmetry thesis; Straus 2009). Further, there is no clear consensus in the literature about whether men and women share the same risk factors for perpetrating IPV (Spencer, Cafferky, and Stith 2016). Agnew’s (2005) integrated theory is well suited for exploring the seemingly contradictory evidence on IPV perpetration among males and females because it is designed to explain why certain groups have higher crime rates than others. Agnew proposes two mechanisms to account for group differences in crime rates: (1) the groups differ in their standing on the life domains and (2) the life domains have larger effects on crime among some groups than others. Concerning the first mechanism, Agnew attributes group differences in crime rates to the fact that members of some groups are more likely than members of other groups to have traits conducive to crime, experience family problems, have negative school experience, associate with criminal peers, and/or have work problems. For instance, Agnew would attribute the evidence that men are primarily the perpetrators and women are primarily the victims of IPV (i.e., the gender asymmetry thesis) to the fact that males are more likely than females to be high in irritability and low in self-control, to be poorly supervised and harshly disciplined by parents, to have weaker family ties as adults, and to associate more with criminal peers.

Concerning the second mechanism, Agnew suggests that group differences in crime rates are due to differences in the effects of the life domain on crime among males and females. It is noteworthy that Agnew contends that family factors will have a larger effect on crime among females while work-related factors will have a larger effect on crime among males (Giordano, Cernkovich, and Rudolph 2002; Simons et al. 2002). Agnew premised the above suppositions on the fact that despite substantial changes in the relationship between sex, work roles, and family roles over the last few decades, women are still more committed to and affected by their family life than men, and men are still more committed to and affected by their work-life than women. To date, no study has sought to apply the above insights from Agnew’s perspective to examine gender differences in IPV perpetration.

Current Study

The focus of the current study is on assessing the proposed mechanisms outlined in Agnew’s theory about gender differences in crime and deviance (i.e., gender differences in crime are either due to differences between males and females in their standing on the life domains or differences in the effect of the life domains on the phenomenon among males and females) concerning IPV perpetration. We seek to investigate which mechanism(s) accounts for the phenomenon among male and female participants in our study.

Study Hypotheses

Since there is evidence indicating that males perpetrate IPV at a higher rate relative to females (i.e., the gender asymmetry thesis) as well as evidence that males and females perpetrate IPV at equal rates (i.e., the gender symmetry thesis), we do not have any prior assumptions or expectations regarding the level of IPV perpetration between males and females in our sample. Concerning group differences in crime and deviance, Agnew’s first proposition is that the differences are due to differences in the standing on the life domains between the groups. Hence, we propose the following hypothesis:

H1: There will be significant differences in the level standing of the life domains between males and females.

Agnew’s second proposition posits that group differences are due to differences in the effects of the life domains on crime among the groups. Thus, we propose the following hypothesis:

H2: The effects of the life domain variables on IPV perpetration will be different for males and females.

Agnew also asserts that work-related risk factors will have a greater effect on crime among adult males while family risk factors will exhibit a larger effect on crime among adult females. Accordingly, we propose the following hypotheses:

H3: The work domain variable will exhibit the largest effect on IPV perpetration relative to the other life domain variables among males.

H4: The family domain variables will exhibit the largest effect on IPV perpetration relative to the other life domain variables among females.

Methods

Data

Data for the current study came from the International Dating Violence Study (IDVS) that involves researchers from 68 universities in 32 nations (Straus 2011). After obtaining approval from each university internal review board (IRB), the researchers administered the survey to college students enrolled in mostly criminal justice, sociology, and psychology courses between the years 2001 and 2006.² The response rates of the study ranged from a low of 20 percent to as high as 100 percent, with 80 percent of researchers reporting a response rate of 65 percent or above. Participating students were given information about the nature and purpose of the study (i.e., to gather data on IPV perpetration and victimization) and assured that no identifying information will be collected. Before starting the survey, respondents were instructed to think about their current partner, or, if they were single at the time of the survey, to think about their last relationship that lasted a month or more when answering items contained in the survey.

For the current study, only the sample from the U.S. (N = 4,162) is used to focus on one single cultural context, which is consistent with other studies that have used these data to examine the prevalence, correlates, and consequences of IPV among young adults (Sabina and Straus 2008; Paat and Markham 2016; Meade et al. 2017; Sabina, Schally, and Marciniec 2017; Graham et al. 2019) but not doing so within the context of Agnew’s integrated theory and specifically with respect to gender differences in IPV and its correlates. The demographic characteristics for the full, male, and female samples are presented in Table 1. As shown, the majority of the sample was female (68 percent) and the mean age of the sample was 22 years. Similarly, the mean age for both male and female samples was also 22 years. Besides gender and age, the IDVS does not include other demographic information such as race or ethnicity.

Table 1.

Descriptive Statistics for all of the Variables in the Study.

	Males (N = 1,288)		Females (N = 2,874)		Full Sample (N= 4,162)				Collinearity	VIF
Variable	Mean (%)	SD	Mean (%)	SD	Mean(%)	SD	Min	Max	Tolerance
Sex
Male	—	—	—	—	32.00	—	—	—	—	—
Female	—	—	—	—	68.00	—	—	—	—	—
Dependent Variable
IPV perpetration	2.13	5.09	2.95*	6.08	2.69	5.80	0	58	—	—
Control Variables
Age	21.55	4.17	21.71	5.25	21.66	4.93	18	45	.92	1.08
Drug abuse	5.47*	2.16	4.78	1.57	5.01	1.81	4	16	.68	1.47
Prior violence	7.44*	2.72	5.68	2.12	6.25	2.47	4	16	.56	1.78
IPV victimization	2.77	6.03	2.55	6.06	2.62	6.06	0	68	.86	1.17
Self-Domain
Low self-control	13.53*	3.31	11.41	3.12	12.09	3.33	7	28	.44	2.26
Authoritarian personality	5.66*	1.58	5.35	1.51	5.45	1.54	3	12	.69	1.46
Negative attribution	7.93*	2.18	7.64	2.30	7.73	2.27	4	16	.49	2.05
Anger issues	10.62	2.33	11.06*	2.27	10.92	2.30	5	20	.80	1.25
Hostility toward men	10.34	2.35	10.53**	2.47	10.47	2.43	5	20	.74	1.36
Hostility toward women	9.92*	2.70	9.18	2.60	9.42	2.66	5	20	.65	1.55
Family Domain
Conflict with partner	16.78*	3.88	16.08	4.25	16.30	4.15	8	32	.51	2.00
Child neglect	12.99*	1.80	12.74	1.81	12.82	1.81	6	21	.84	1.19
Child abuse	8.67*	2.80	7.91	2.53	8.15	2.57	5	20	.62	1.61
Child sexual abuse	5.05	1.88	5.12	2.06	5.10	2.00	4	16	.80	1.26
Work/school domain
Discontent with work/school	3.82*	1.09	3.53	1.05	3.62	1.07	2	8	.76	1.32
Peer domain
Criminal peers	2.80*	.89	2.42	.96	2.54	.95	1	4	.85	1.18

Note: *p < .001, **p < .01; IPV = Intimate Partner Violence; Min = Minimum; Max = Maximum; VIF = variance inflation factor.

Dependent Variable

The dependent variable, IPV Perpetration (α = 0.79) was measured using 12 items asking respondents if they have committed violent and aggressive acts toward their intimate partners in the past 12 months (e.g., twisted their arm or hair, pushed or shoved them, used a knife or gun on them; see Appendix A for the items that were employed to construct IPV Perpetration).³ The original response categories for this variable consisted of an 8-point Likert-type scale: 1 = Once in the past year, 2 = Twice in the past year, 3 = 3–5 times in the past year, 4 = 6–10 times in the past year, 5 = 11–20 times in the past year, 6 = More than 20 times in the past year, 7 = Not in the past year but it did happen before, and 8 = This has never happened. For this study, the responses were recoded to 0 = This has never happened, 1 = Not in the past year but it did happen before, 2 = Once in the past year, 3 = Twice in the past year, 4 = 3–5 times in the past year, 5 = 6–10 times in the past year, 6 = 11–20 times in the past year, and 7 = More than 20 times in the past year.⁴ The above items were summed together with higher scores indicating higher levels of IPV perpetration.

Life Domain Variables

To identify the life domain measures for our study, we employ the list of variables assigned to the five life domains included in Agnew’s theory. Hence, our life domain measures reflect the life domain variables posited by Agnew to directly affect crime and deviance. Our life domain measures also represent several risk factors of IPV identified in prior research. The items employed to construct the life domain scales in this study, as well as all other factor scales, are provided in Appendix A.

Self-Domain Measures

Our self-domain encompasses six variables: Low Self-Control, Authoritarian Personality, Negative Attribution, Anger Issues, Hostility toward Men, and Hostility toward Women. These variables have been linked to IPV perpetration (see, e.g., Moffitt et al. 2000; Swinford et al. 2000; White and Widom 2003; Kim and Capaldi 2004; Gover, Kaukinen, and Fox 2008; Jennings et al. 2011; Baker, Klipfel, and van Dulmen 2018) as well as align with the individual characteristics of irritability and low self-control proposed by Agnew (2005:42–45). Low Self-Control (α = 0.75) was measured using seven items (e.g., I often do things that other people think are dangerous, I don’t think about what I do will affect other people), Authoritarian Personality (α = 0.62) was measured using three items (e.g., sometimes I have to remind my partner of who’s boss, I generally have the final say when my partner and I disagree), and Negative Attribution (α = 0.70) was measured using four items (e.g., it is usually my partner’s fault when I get mad, my partner does things just to annoy me).

On the other hand, Anger Issues (α = .63) was created using six items (e.g., when I’m mad at my partner I say what I think without thinking about the consequences, there is nothing I can do to control my feelings when my partner hassles me), Hostility toward Men (α = 0.69) was created using five items (e.g., men are rude, men irritate me a lot), and Hostility toward Women (α = 0.77) was also created using five items (e.g., women are rude, women treat men badly). The response categories for all the items used to measure the self-domain variables include a 4-point Likert-type scale that ranges from 1 = Strongly Disagree to 4 = Strongly Agree and the responses were summed together with a higher score indicating a higher level of a particular self-domain measure (i.e., higher levels of Low Self-Control, higher levels of Authoritarian Personality,).

Family Domain Measures

Our family domain consists of four variables: Conflicts with Partner, Child Neglect, Child Abuse, and Child Sexual Abuse. Similar to the self-domain variables, our family domain measures have been linked to IPV in prior research (Gelles and Straus 1988; Swinford et al. 2000; White and Widom 2003) as well as align with the key family domain variables encompassed in Agnew’s (2005:45–49) perspective. Conflicts with Partner (α = 0.76) was captured with nine questions (e.g., my partner and I disagree about how much money to spend when we go places, my partner and I disagree about telling other people about things that happened between us) while Child Neglect (α = 0.74) was measured using eight statements (e.g., my parents did not care if I got into trouble in school, my parents did not comfort me when I was upset). Similarly, Child Abuse (α = 0.64) was captured using five statements (e.g., when I was less than 12 years old I was spanked or hit a lot by my mother/father, when I was a teenager I was hit a lot by my mother/father,) and Child Sexual Abuse (α = 0.74) was created using four items (e.g., before I was 18 an adult in my family made me look at or touch their private parts or looked at or touched mine, before I was 18 an adult in my family had sex with me). The response categories for all the items used to create the family domain variables include a 4-point Likert-type scale that ranges from 1 = Strongly Disagree to 4 = Strongly Agree and the responses were summed together with a higher score denoting a higher level of a particular family domain measure (i.e., higher levels of Conflicts with Partner, higher levels of Child Neglect,).

School/Work Domain Measure

The IDVS does not include separate measures for the school and work domains, a limitation we return to later in the manuscript. Hence, the variable Discontent with School/Work (α = 0.33)⁵ was created to represent both domains. This variable was measured using two statements: “People at work or school don’t get along with me” and “I don’t like my work or classes.” Respondents marked their answers using a 4-point Likert-type scale (1 = Strongly Disagree to 4 = Strongly Agree) and the responses were summed together, with higher scores indicating higher levels of discontent with school/work. It is noteworthy that our school/work domain variable has been linked to IPV in prior research (Schnurr and Lohman 2008; Spriggs et al. 2009; Foshee et al. 2011) and aligns with the key school and work domain variables outlined in Agnew’s (2005:49–55) theory.

Peer Domain Measure

The peer domain variable, Criminal Peers, was captured using the following statement: “I have friends who have committed crimes.” Respondents marked their answers using a 4-point Likert-type scale (1 = Strongly Disagree to 4 = Strongly Agree) with higher scores denoting higher levels of association with criminal peers. Similar to the school/work domain measure, our peer domain variable has been found to be related to IPV in prior research (Arriaga and Foshee 2004; Schnurr and Lohman 2008; Miller et al. 2009) and aligns with the key peer domain variables suggested by Agnew (2005:51–53).

Control Variables

Given the evidence that IPV declines with age (Kim et al. 2008), substance use is related to IPV perpetration (Feingold, Kerr, and Capaldi 2008), and the association between non-relationship aggression and IPV (Herrera, Wiersma, and Cleveland 2008), Age, Drug Abuse, and Prior Violence were included as control variables in the study. Age is a continuous variable and measured in years. Drug Abuse (α = 0.69) was captured using four statements (e.g., In the past I used coke, crack, or harder drugs more than once or twice, I worry I have a drug problem,) and Prior Violence (α = 0.73) was created using four statements, (e.g., Before the age of 15, I physically attacked someone with the idea of seriously hurting them, before the age of 15, I hit or threatened to hit my parents).

Relatedly, given the evidence on the association between IPV perpetration and victimization (Jennings et al. 2011), IPV Victimization (α = 0.82) was also included as a control variable. The same items that were used to measure IPV Perpetration were alternatively presented in the context of the respondent being victimized by these acts to create IPV Victimization (e.g., your partner twisted your arm or hair, your partner pushed or shoved you, your partner used a knife or gun on you). Respondents marked their answers using an 8-point Likert-type scale (i.e., 1 = Once in the past year, 2 = Twice in the past year, 3 = 3–5 times in the past year, 4 = 6–10 times in the past year, 5 = 11–20 times in the past year, 6 = More than 20 times in the past year, 7 = Not in the past year but it did happen before, and 8 = This has never happened). The original responses were recoded to 0 = This has never happened, 1 = Not in the past year but it did happen before, 2 = Once in the past year, 3 = Twice in the past year, 4 = 3–5 times in the past year, 5 = 6–10 times in the past year, 6 = 11–20 times in the past year, and 7 = More than 20 times in the past year. All the items were summed together with higher scores indicating higher levels of IPV victimization. The descriptive statistics for the life domain and control variables for the full, male, and female samples are provided in Table 1.

Analytical Plan

To assess the hypothesis that males and females differ in their standing on the life domain variables (Hypothesis 1), we perform a series of mean difference tests on the reported frequencies for all the life domain variables across gender. To examine the hypotheses that the effects of the life domain variables on IPV perpetration are different for males and females (Hypothesis 2), the work domain variable exhibits the greatest effect on IPV perpetration relative to the other life domain variables among males (Hypothesis 3), the family domain variables exhibit the largest effect on IPV perpetration relative to the other life domain variables among females (Hypothesis 4), and given that our dependent variable is a count variable with a mean-variance inequality in favor of over-dispersion (Mean = 2.69; SD = 5.80), we estimate two negative binomial regression models (one for the male sample and the other for the female sample) in which IPV Perpetration was regressed on the life domain variables (e.g., Low Self-Control, Authoritarian Personality, Negative Attribution, Anger Issues, Hostility toward Men, Hostility toward Women, Conflicts with Partner, Child Neglect, Child Abuse, Child Sexual Abuse, Discontent with School/Work, and Criminal Peers) while controlling for Age, Drug Abuse, Prior Violence, and IPV Victimization. We also conduct a series of coefficient comparison tests (Paternoster et al. 1998) to determine whether the effects of the life domain measures on IPV perpetration are significantly different between males and females (i.e., to provide a formal test for Hypothesis 2). The negative binomial regression models were estimated using SPSS Version 27.

Results

Table 1 shows the reported frequencies for IPV perpetration by males and females. According to the results, the mean level of reported IPV perpetration for females (Mean = 2.95) was significantly higher than the mean level reported for males (Mean = 2.13). To assess differences in the standing on the life domains between males and females (Hypothesis 1), we performed a series of mean difference tests on the reported frequencies for the life domain variables. Within the self-domain, relative to females, males reported significantly higher levels of low self-control, authoritarian personality, negative attribution, and hostility toward women. Conversely, relative to males, females exhibited a significantly higher level of anger issues and hostility toward men (Table 1).

Similarly, within the family domain, males reported a significantly higher level of conflict with partner, child neglect, and child abuse relative to females. No significant sex differences were found for child sexual abuse. With regard to the school/work and peer domains, males reported significantly greater negative experiences at school/work (discontent with school/work) and higher levels of association with criminal peers (criminal peers) than females. Accordingly, our results suggest some evidence of sex differences in the standing on the life domains with males in our sample appearing to possess more risk factors—as well as higher levels for some risk factors—for IPV relative to females.

To determine whether the effects of the life domain variables on IPV perpetration are different for males and females (Hypothesis 2), the work domain variable exhibits the greatest effect on IPV perpetration relative to the other life domain variables among males (Hypothesis 3), and the family domain variables exhibit the largest effect on IPV perpetration relative to the other life domain variables among females (Hypothesis 4), we estimated two negative binomial regression models (one for males and the other for females) in which IPV perpetration was regressed on the life domain variables while holding age, drug abuse, prior violence, and IPV victimization constant. The results for the male sample are shown in Table 2 and the results for the female sample are shown in Table 3.

Table 2.

Negative Binomial Regressions of Life Domains on IPV Perpetration among Males (N = 1,288).

Variables	IRR^a	SE	95% CI
Control
Age	.997	.010	.977–1.016
Drug abuse	.973	.022	.932–1.017
Prior violence	1.028	.020	.989–1.068
IPV victimization	1.231*	.009	1.210–1.252
Self-domain
Low self-control	1.002	.019	.950–1.023
Authoritarian personality	1.001	.032	.940–1.066
Negative attribution	1.039	.027	.985–1.095
Anger issues	1.083*	.020	1.041–1.126
Hostility toward men	1.043***	.019	1.004–1.083
Hostility toward women	1.016	.020	.977–1.056
Family domain
Conflict with partner	1.028	.014	.999–1.057
Child neglect	.962	.026	.913–1.013
Child abuse	.983	.021	.944–1.024
Child sexual abuse	1.079*	.028	1.033–1.126
School/work domain
Discontent with work/school	.894	.069	.821–0.973
Peer domain
Criminal peers	1.101***	.054	.990–1.224
Constant	.093*	.465	.037–0.230
Model χ²²	1681.60*

Incidence rate ratios.

*p < .001; ***p < .05.

Table 3.

Negative Binomial Regressions of Life Domains on IPV Perpetration among Females (N = 2,874).

Variables	IRR^a	SE	95% CI
Control
Age	.985**	.005	.975–0.995
Drug abuse	.956**	.017	.924–0.989
Prior violence	1.075*	.014	1.047–1.105
IPV victimization	1.188*	.006	1.174–1.202
Self-domain
Low self-control	1.015	.011	.993–1.037
Authoritarian personality	1.061**	.019	1.022–1.101
Negative attribution	1.031***	.015	1.002–1.062
Anger issues	1.160*	.012	1.133–1.189
Hostility toward men	1.025	.013	1.000–1.051
Hostility toward women	.964**	.012	.943–0.987
Family domain
Conflict with partner	1.028*	.008	1.012–1.044
Child neglect	0.954**	.015	.926–0.982
Child abuse	1.041**	.012	1.017–1.066
Child sexual abuse	1.004	.013	.978–1.031
School/work domain
Discontent with work/school	.989	.027	.937–1.043
Peer domain
Criminal peers	1.051	.028	.996–1.110
Constant	.080*	.257	.048–0.132
Model χ²²	3113.47*

Incidence rate ratios.

*p < .001; **p < .01; ***p < .05.

The results from Table 2 reveal that among males, two self-domain variables, anger issues and hostility toward men, were significant predictors of IPV perpetration. According to the results, for a one unit increase in anger issues, the incident rate of IPV perpetration increased by 8 percent (IRR = 1.083, p < .001) and for a one unit increase in hostility toward men, the incident rate of IPV perpetration increased by 4 percent (IRR = 1.043, p < .05). None of the other self-domain variables were related to the outcome variable. Among the family domain variables, only child sexual abuse was a significant predictor of IPV perpetration. For a one unit increase in child sexual abuse, the incident rate of IPV perpetration increased by 8 percent (IRR = 1.079, p < .001). The peer domain variable, criminal peers, also exhibited a significant association with the outcome variable in that for a one unit increase in criminal peers, the incident rate of IPV perpetration increased by 10 percent (IRR = 1.101, p < .05). On the other hand, the school/work domain variable (discontent with work/school) was not related to the outcome variable.

Concerning the magnitudes of the effects of the life domain variables on the outcome variable, the results from Table 2 indicate that the peer domain variable (criminal peers) exhibited the greatest effect (IRR = 1.101, p < .05) on IPV perpetration relative to the other life domain variables. Hence, we did not find support for Hypothesis 3 (the work domain variable will exhibit the greatest effect on IPV perpetration relative to the other life domain variables among males). Among the control variables, we found IPV victimization was significantly related to the outcome variable. For every unit increase in IPV victimization, the incident rate of IPV perpetration increased by 23 percent (IRR = 1.231, p < .001).

Shifting our attention to the female sample, the results from Table 3 reveal that four of the six self-domain variables (e.g., authoritarian personality, negative attribution, anger issues, and hostility toward women) were significantly related to IPV perpetration. For every unit increase in authoritarian personality, the incident rate of IPV perpetration increased by 6 percent (IRR = 1.061, p < .01) and for every unit increase in negative attribution, the incident rate increased by 3 percent (IRR = 1.031, p < .05). Similarly, a one unit increase in anger issues resulted in a 16 percent increase in the incident rate of IPV perpetration (IRR = 1.160, p < .001). Conversely, for every unit increase in hostility toward women, the incident rate of IPV perpetration decreased by 4 percent (IRR = 0.964, p < .01).

Concerning the family domain measures, three of the four variables (e.g., conflict with partner, child neglect, and child abuse) were significant predictors of IPV perpetration. For every unit increase in conflict with partner, the incident rate of IPV perpetration increased by 3 percent (IRR = 1.028, p < .001) and for every unit increase in child abuse, the incident rate of IPV perpetration increased by 4 percent (IRR = 1.041, p < .01). On the other hand, a one unit increase in child neglect was associated with a 5 percent decrease in the incident rate of IPV perpetration (IRR = 0.954, p < .01). The school/work and peer domain measures were not related to IPV perpetration.

Concerning the magnitudes of the effects of the life domain variables on IPV perpetration among females, the results from Table 3 reveal that the self-domain variable of anger issues exhibited the largest effect (IRR = 1.160, p < .001) on IPV perpetration relative to the other life domain variables. Accordingly, our results did not provide support for Hypothesis 4 (the family domain variables will exhibit the largest effect on IPV perpetration relative to the other life domain variables among females), but it is important to bear in mind that two of the four family domain variables did operate as Agnew expected. With respect to the control variables, the results from Table 3 also indicate that a one unit increase in age is associated with a 2 percent decrease in the incident rate of IPV perpetration (IRR = 0.985, p < .01) and a one unit increase in drug abuse resulted in a 4 percent decrease in the incident rate (IRR = 0.956, p < .01). On the other hand, a one unit increase in prior violence led to an 8 percent increase in the incident rate of IPV perpetration (IRR = 1.075, p < .001) and a one unit increase in IPV victimization is associated with a 19 percent increase in the incident rate (IRR = 1.188, p < .001).⁶

In addition to the above analyses, we also conducted a series of coefficient comparison tests to determine whether the effects of the life domain variables on IPV perpetration are different between males and females. The results for these tests are presented in Table 4 and indicate that 4 of the 12 life domain measures emerged as being significantly different across gender. As can be seen, the effects of two self-domain variables (e.g., anger issues and hostility toward women) and two family domain variables (e.g., child abuse and child sexual abuse) on IPV perpetration were significantly different between males and females. Among the self-domain variables, anger issues were a significant predictor of IPV for both males and females with its effect on the outcome variable being greater for females than for males (B = .149, p < .001 and B = .079, p < .001, respectively) but it bears repeating that the coefficients were positive and statistically significant for both groups. On the other hand, while the effect of hostility toward women on IPV perpetration was not significant among males, it exhibited a significant and negative effect on the outcome variable among females (B = .016, p > .05 and B = −.036, p < .01, respectively).

Table 4.

Z-Tests Comparing Male and Female Regression Coefficients.

Variables	Males (N = 1,288)	Females (N = 2,874)	z-score
Self-domain
Low self-control	.014 (.019)	.015 (.011)	.05
Authoritarian personality	.001 (.032)	.059 (.019)**	−1.55
Negative attribution	.038 (.027)	.031 (.015)***	.23
Anger issues	.079 (.020)*	.149 (.012)*	−3.04
Hostility toward men	.042 (.019)***	.025 (.013)	0.73
Hostility toward women	.016 (.020)	−.036 (.012)**	2.25
Family domain
Conflict with partner	.027 (.014)	.027 (.008)*	0.01
Child neglect	−.039 (.026)	−.048 (.015)*	.30
Child abuse	−.017 (.021)	.040 (.012)*	−2.37
Child sexual abuse	.076 (.022)*	.004 (.013)	2.82
School/work domain
Discontent with work/school	−.113 (.043)	−.011 (.027)	−1.09
Peer domain
Criminal peers	.096 (.054)***	.050 (.028)	.76
Constant	−2.380 (.465)*	−2.528 (.257)*
Model χ²	1,681.60*	3,113.47*

Note: Entries are standardized regression coefficients; standard errors are in parentheses; significant z-scores are bolded.

*p < .001; **p < .01; ***p < .05.

Within the family domain, two coefficient estimates were observed to be significantly different across gender and for each of these two z-tests, it was the case that one of the coefficient estimates was significant among one of the genders but not the other. First, whereas child abuse was not a significant predictor of IPV perpetration among males it exhibited a significant effect on the outcome variable among females (B = −.017, p > .05 and B = .040, p < .001, respectively). Similarly, although child sexual abuse was not related to IPV perpetration among females, it demonstrated a significant effect on the outcome variable among males (B = .004, p > .05 and B = .076, p < .001, respectively). In short, although we detected some coefficient differences, the majority of comparisons did not reveal significant differences across gender.

Discussion

The goal of this research was to apply Agnew’s (2005) theoretical propositions concerning group differences in crime and deviance to examine sex differences in IPV perpetration among a sample of young adults. Our focus was on determining which mechanism (i.e., the differences are due to differences in the standing on the life domains between the groups or the differences are due to differences in the effects of the life domains on crime rates among the groups) may potentially aid in illuminating any potential differences in the levels of IPV perpetration between male and female participants in our study. We uncovered several key findings worth further discussion.

First, we found support for Hypothesis 1 (there will be significant differences in the reported level of the life domains between males and females) in that, with two exceptions (e.g., anger issues and hostility toward men), the reported frequencies for the life domain variables among males in our sample were greater than the reported frequencies among females. Out of the 12 life domain measures, males exhibited a greater level of risk across 9 measures relative to females. Specifically, compared to females, males exhibited a higher level of low self-control, measures assessing irritability (i.e., authoritarian personality, negative attribution, and hostility toward women), relationship conflict, child neglect and maltreatment, negative experiences with work/school, and associations with antisocial peers (Table 1).

However, despite having a greater proportion of risk factors of IPV, males in the current study reported a significantly lower level of IPV perpetration relative to females (Table 1). While prior research has also reported similar findings (Moffitt et al. 2001), it does contradict some conventional assumptions about IPV perpetration thereby raising the possibility that our findings could be attributed to males in our sample possessing protective factors that serve to prevent or buffer the risk of engaging in IPV, that there may be some under-/overreporting differences between the genders on IPV perpetration, or that such conventional assumptions simply do not square away with empirical reality. It is noteworthy that prior research has identified several protective factors of IPV including help-seeking behavior, self-esteem, and life skills (Gerino et al. 2018). Yet, protective factors are generally studied less extensively when compared to risk factors. Given the above evidence and that our data do not include protective measures of IPV, we encourage future research to examine and identify the characteristics and actions that potentially decrease the likelihood of IPV victimization both within and across intimate relationships. This line of work is crucial and warranted in providing direction for IPV prevention and intervention programs.

Second, we uncovered that some of the effects of the life domain variables on IPV were different for males and females in our study. This finding provided support for Hypothesis 2 (the effects of the life domain variables on IPV perpetration will be different for males and females). Relative to the male sample, the number of life domain variables exhibiting a significant effect with the outcome variable (IPV perpetration) is greater in the female sample (Tables 2 and 3). Further, the results from our coefficient comparison tests indicate that the effects of four life domain variables (e.g., anger issues, hostility toward women, child abuse, and child sexual abuse) on IPV perpetration were significantly different between males and females (Table 4), but many more others were not different between the two groups. Although having high levels of hostility toward women and child abuse did not influence the likelihood of IPV perpetration among males, they significantly increased the risk of such behavior among females. Conversely, experiencing high levels of child sexual abuse did not seem to impact the likelihood of engaging in IPV among females but such experience heightened the risk of IPV among males. On the other hand, having high levels of anger issues was a risk factor for IPV for both males and females in our sample, its influence on the likelihood of IPV perpetration, though significant for both groups, was somewhat stronger for females relative to males. Taken together, our results suggest that males and females in our sample appear to share some of the same risk factors, but not all of them, and in several cases the risk factors operate to a different degree and in different ways (i.e., sign differences).

Third, among the life domain measures, we uncovered that the peer variable (criminal peers) exhibited the greatest effect on IPV perpetration in the male sample (Table 2). Hence, our results did not provide support for Hypothesis 3 (the work domain variable will exhibit the largest effect on IPV perpetration relative to the other life domain variables among males). It is plausible that our null finding between the work domain variable and IPV perpetration among males is due to how the variable was measured. As noted previously, our data do not include separate measures for the school and work domains, and hence, the variable discontent with school/work was created to represent both domains in our study. The above finding could also be attributed to the cross-sectional nature of our data. Given the evidence that IPV is negatively related to employment stability (Crowne et al. 2011), we were unable to longitudinally determine the time ordering of the relationship between the work domain variable and IPV perpetration (i.e., discontent with work could have preceded IPV perpetration). And it could also be the case that “work” for this sample is not considered in the sense as it would full-time work in the form of a career among older adults who are no longer in college. We encourage future research to utilize separate measures for the work domain as well as incorporate additional variables that we did not include in our study (e.g., commitment to school or work, attachment to a partner, etc.) to explore sex differences in IPV over time.⁷

Relatedly, it is instructive that while Agnew theorizes that the magnitude of the association between criminal peers and offending will decrease among male adults in light of the centrality of their employment and marital commitment, he also posits that deviant peers will have a major impact among adults who are not employed and adults who are not married. Since our data do not include information about marital and employment statuses, we advocate future research to explore the above proposition suggested by Agnew.

Fourth, among female participants, we discovered that the self-domain variable of anger issues exhibited the greatest effect on IPV perpetration relative to the other life domain variables (Table 3). Thus, we did not find support for Hypothesis 4 (the family domain variables will exhibit the largest effect on IPV perpetration relative to the other life domain variables among females). It is noteworthy that the measure of anger issues is a salient risk factor of IPV for both males and females in our sample, albeit it exhibited a greater effect on the outcome variable among females relative to males (Table 4). While negative emotions occupy a less central role in Agnew’s integrated theory than in GST (Agnew 1992), they are conceptualized as significant motivation sources in his integrated perspective. Given our finding that the inability to control one’s anger is a crucial risk factor for IPV for both males and females, we encourage future research to incorporate measures of negative emotions in their test of Agnew’s integrated theory. Taking account of negative emotions may hold the key to our understanding as to why some people are more likely than others to engage in crime as well as why crime is more likely in some situations than others.

Returning to Agnew’s propositions concerning group differences in crime and deviance, (i.e., group differences in crime and deviance could either be due to differences in the standing on the life domains between the groups or differences in the effects of the life domains on crime among the groups), the results from our study appear to provide support for the latter because although males in our sample possessed more risk factors of IPV than female participants, the effects of these factors on IPV were different between the sexes at the bivariate level (Table 1). Specifically, females in our sample reported a lower frequency across all five life domains compared to males yet, the number of life domain variables that were significantly related to IPV perpetration among females was greater than the number among males. Further, the effects of the life domain variables on IPV perpetration appeared to be different (and at times greater) for females than for females than for males, but for the most part, there were more similarities than differences across gender.

Policy Implications

One of the key findings that emerged in the current study is that having anger issues is a significant risk factor of IPV for both males and females. This finding aligns with the evidence from a systematic review on IPV (Norlander and Eckhardt 2005). Hence, targeting anger and offering anger management education is crucial for treating and preventing IPV. In anger management, violence is generally seen as a momentary outburst of anger and thus, the focus in treatment tends to be on managing emotions (Burton n.d.). There is evidence that the use of cognitive behavioral therapy (CBT) in conjunction with other therapies such as relaxation techniques, problem-solving strategies, etc., in anger management treatment is effective in helping participants feel more in control of their anger (Nesset et al. 2019).

Another key finding documented in the current study is that association with criminal peers heightened the risk of IPV perpetration among males. This finding is not surprising given the evidence that individuals tend to select friends with similar interests and behavior as well as dating partners is usually selected from the same peer group (Yamaguchi and Kandel 1993; Kim and Capaldi 2004). Relatedly, there is evidence that IPV typically starts in middle school (at the age of 12 years; O’Leary and Slep 2012) and appears to be somewhat stable (Fritz, O’Leary, and Foshee 2003). Hence, early prevention and intervention are key in combating IPV. In recent years, several effective prevention and intervention programs targeting perpetration and victimization of IPV among adolescents have been identified. For example, Safe Dates (Stith et al. 2004), a school-based prevention intervention program, offers a curriculum consisting of sessions on personal safety, communication strategies, sexuality, tips for safe dating, consequences of abusive behaviors, identification of abusive relationships, and related health problem-solving skills. The focus of the program is on fostering relationship skills (prevention) and addressing emotional/psychological abuse (intervention). Safe Dates also encompasses a community component that includes school project newsletters, an information session for parents, and a manual on how to prevent violence in the community. It is noteworthy that comprehensive IPV prevention interventions based in both school and community are effective in preventing IPV perpetration and victimization among adolescents (De Koker et al. 2014).

The results from our study also suggest that, although there is some overlap in the risk factors across gender (such as anger issues), males and females do not appear to share all the same—or same level of—risk factors of IPV. While there continues to be a debate on whether there is a need for gender-neutral or gender-specific theories of crime (see Smith and Paternoster 1987; Piquero et al. 2005), currently, the evidence on the effectiveness of gender-neutral and gender-specific prevention and intervention programs for IPV is inconclusive (see De Koker et al. 2014). While more research is needed to determine whether a gender-neutral approach works better than a focused approach targeting males and females separately in preventing and addressing IPV, it would be prudent to take into account the possibility that factors influencing IPV perpetration may be different for males and females when designing interventions.

In the end, we believe the pressing issue in combating and preventing IPV is to promote healthy, respectful, nonviolent relationships. Prevention strategies such as Teach Safe and Healthy Relationship Skills that focus on promoting social and emotional competency among youth and building healthy relationships among young couples and Disrupt the Developmental Pathways toward Partner Violence that emphasize parenting and interpersonal skills, preschool enrichment with family engagement, and home visitation are promising strategies in curbing IPV (Piquero, Farrington, Welsh, et al. 2009; Centers for Disease Control and Prevention 2020).

Study Limitations

To be sure, our study is not without limitations. First, our study involved cross-sectional, quantitative, and self-reported data, and hence, definitive causal relationships cannot be established and no information on contextual factors was available to aid with the interpretation of the results. Second, other measures of the life domains were not available in the IDVS. For instance, we did not have separate measures for the work and school domains. While we believe our combined measure of school/work domain represents a fair assessment of the participants’ school and work experiences since our sample consists of college students and there is evidence that many college students work (Amour 2019), however, having a separate school domain measure and work domain measure may provide additional insights into the impact of the life domains on IPV perpetration. Relatedly, although certainly within the spirit of Agnew’s theory, our peer domain variable was measured using a single (but critical) item. Hence, we encourage future research to incorporate additional life domain measures (e.g., employment status, marital status, etc.) and employ life domain scales to assess Agnew’s theory. Third, we employed a general measure of IPV in our study albeit there are subtypes of IPV perpetration including intimate terrorism, mutual violence control, violent resistance, and situational couple violence (Johnson 2006). Thus, we encourage future research to extend our work by applying Agnew’s theory and assess sex differences in the effects of the life domains on specific types of IPV perpetration as well as offending and violence more generally (see, e.g., Theobald et al. 2016). Lastly, Agnew posits that the variables in each domain increase crime by reducing the constraints against crime and increasing the motivations for crime, each life domain directly affects crime and indirectly affects crime through its effects on the other domains, the life domain interacts in affecting crime and one another, and the life domains have nonlinear and largely contemporaneous effects on crime and one another. Exploration of these issues is beyond the space available to us in this paper, but it is important to be considered in subsequent work to continue empirically investigating various relationships contained in Agnew’s theory, including mediation and moderation analyses, vis-à-vis IPV.

Conclusions

Our study represents a preliminary assessment of Agnew’s (2005) general theory of crime and delinquency in helping us understand IPV perpetration and the extent to which the life domains outlined in his theory operate in the same manner across gender in a sample of young adults. Overall, our results provide some support for Agnew’s conjectures about group differences in offending, but also some challenges to his expectations, at least within the context of IPV within the current data. Accordingly, we advocate future research to apply the above ideas for future work and examine gender differences in IPV using different populations (e.g., clinical samples, adolescent samples, senior samples, etc.), a more expansive list of life domain variables, and with additional types of violence not fully considered within these data. We hope our research will inspire future research to employ Agnew’s perspective to continue the quest of unpacking the relationship between gender and this type of violence.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

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

ORCID iD

Fawn T. Ngo

Notes

Author biographies

Fawn T. Ngo is an associate professor of Criminology at the University of South Florida. Her research interests include criminological theory, interpersonal violence, cybercrime, and predictive analytic applications in criminology and criminal justice. Her work has appeared in Justice Quarterly, Crime & Delinquency, Journal of Criminal Justice, American Journal of Criminal Justice, and Victims & Offenders: The International Journal of Evidence-based Research, Policy, and Practice.

Egbert Zavala is an associate professor in the Department of Criminal Justice at The University of Texas at El Paso, where he has been since receiving his PhD in sociology from Kansas State University. His area of research includes intimate partner violence, testing criminological theories, victimology/victimization, and deviance. His publications appear in Journal of Family Violence, Crime & Delinquency, Violence & Victims, Journal of Crime and Justice, and many others.

Alex R. Piquero is professor and chair of the Department of Sociology and Criminology and Arts & Sciences Distinguished Scholar at the University of Miami, and professor of Criminology at Monash University in Melbourne Australia. He is also editor of Justice Evaluation Journal. His research interests include criminal careers, criminological theory, crime policy, evidence-based crime prevention, and quantitative research methods. He has received several research, teaching, and service awards and is fellow of both the American Society of Criminology and the Academy of Criminal Justice Sciences. In 2014, he received the University of Texas System Regents' Outstanding Teaching Award and in 2018 he was inducted into the University of Texas System Academy of Distinguished Teachers. In 2019, he received the Academy of Criminal Justice Sciences Bruce Smith, Sr. Award for outstanding contributions to criminal justice In 2020 he was recipient of the Lifetime Achievement Award from the Division of Developmental & Life-Course Criminology of the American Society of Criminology..

Appendix A: Survey Scales and Items

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