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Journal of Interpersonal Violence 1 –27
© The Author(s) 2017 Reprints and permissions:
sagepub.com/journalsPermissions.nav DOI: 10.1177/0886260517710486
Social Learning Theory, Gender, and Intimate Partner Violent Victimization: A Structural Equations Approach
Ráchael A. Powers, PhD,1 John K. Cochran, PhD,1 Jon Maskaly, PhD,2 and Christine S. Sellers, PhD3
Abstract The purpose of this study is to examine the applicability of Akers’s Social Learning Theory (SLT) to explain intimate partner violence (IPV) victimization. In doing so, we draw on the Intergenerational Transmission of Violence Theory (IGT) to extend the scope of SLT to the explanation of victimization and for a consideration of uniquely gendered pathways in its causal structure. Using a structural equation modeling approach with self- report data from a sample of college students, the present study tests the extent to which SLT can effectively explain and predict IPV victimization and the degree, if any, to which the social learning model is gender invariant. Although our findings are largely supportive of SLT and, thus, affirm its extension to victimization as well as perpetration, the findings are also somewhat mixed. More significantly, in line with IGT literature, we find that the social learning process is not gender invariant. The implications of the latter are discussed.
1University of South Florida, Tampa, USA 2The University of Texas at Dallas, USA 3Texas State University, San Marcos, USA
Corresponding Author: Ráchael A. Powers, Department of Criminology, University of South Florida, 4202 E. Fowler Ave., SOC 107, Tampa, FL 33620, USA. Email: firstname.lastname@example.org
710486 JIVXXX10.1177/0886260517710486Journal of Interpersonal ViolencePowers et al. research-article2017
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Keywords social learning, intimate partner violence, victimization, gender, intergenerational transmission of violence
A longstanding theoretical perspective on intimate partner violence (IPV) is the Intergenerational Transmission of Violence Theory (IGT; Straus, Gelles, & Steinmetz, 1980). This theory argues that experiencing household violence (direct victimization) and/or witnessing it (indirect/vicarious victimization), particularly during childhood, leads to subsequent IPV, either perpetration or victimization. The causal process involved in IGT is most often attributed to a learning process (e.g., Alexander, Moore, & Alexander, 1991). In this way, IGT shares much in common with Akers’s Social Learning Theory (SLT; see Fox, Nobles, & Akers, 2011; Sellers, Cochran, & Branch, 2005; Sellers, Cochran, & Winfree, 2003; Wareham, Boots, & Chavez, 2009a, 2009b). For instance, IGT and SLT stress exposure to influential role models (parents) who perpetrate or experience interpersonal violence within the household that children witness and later imitate. IGT and SLT also articulate the impor- tance of the transmission of beliefs, values, and norms conducive to IPV. However, SLT can also explicitly accommodate other common explanations for IPV including extrafamilial socialization, gender roles and violent mascu- linity, and the role of differential reinforcement.
On the contrary, Akers’s SLT is explicitly a theory of perpetration, and makes no claim to account for victimization. Conversely, IGT can account for both IPV perpetration and victimization. Given the high level of concep- tual and propositional congruity between the theories, it is our contention that IGT can offer a theoretical basis for expanding the scope of SLT to include victimization as well as perpetration. In addition, some of the literature on IGT has suggested that the causal processes are highly gendered, whereas SLT is ostensibly gender invariant. Although the results are not conclusive, previous research has found that men and women react differently to violence in the family of origin, and therefore, a gendered application of IGT may be warranted (see Stith et al., 2000). Extending this rationale to SLT, an other- wise gender invariant theory, it is possible that its causal processes do not operate identically for men and women with regard to IPV victimization.
To that end, the primary purpose of the present study, and one of its more significant contributions to the literature, is to examine the applicability of SLT to explain IPV victimization. In so doing, we are able to provide a further test of its theoretical scope, which, as a “general” theory of
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behavior, it should be able to accommodate. Moreover, we also examine the degree to which SLT as an explanation for IPV victimization is gender invariant, another important contribution and purpose of the present study. To the extent that SLT cannot account for IPV victimization, or to the extent that it is not gender invariant, it may not be as “general” a theory as some may claim it to be. Finally, this studycontributes to the literature testing SLT by employing a full structural equation model of the theory with com- plete representation and strong measurement properties for all four of the key SLT constructs while also accounting for the feedback/reciprocal influ- ence of IPV victimization.
Intergenerational Transmission of Violence
Experiencing physical violence in childhood has been associated with a sub- stantial increase in the odds of IPV perpetration (e.g., Gómez, 2011) and victimization (e.g., Hamby, Finkelhor, & Turner, 2012). The most common explanation for this relationship focuses on learning processes. Children learn behavior from their experiences and observations of social interactions. These observations are particularly salient when the modelers are of high status, such as parents and caregivers (Bandura, 1973). Therefore, when chil- dren experience violence or hostile parenting practices, they learn that vio- lence is an acceptable means of conflict resolution and will later model that behavior in their relationships (Akers & Sellers, 2009).
Although the direct link between childhood exposure to or experiences of interparental violence and later life involvement in IPV is presumably well established, it is far from conclusive. Recent studies using prospective meth- ods or advanced statistical procedures (e.g., propensity score matching) sug- gest that this relationship may not be causal; once other adverse childhood experiences or selection bias has been taken into account, the direct impact of childhood abuse and childhood exposure to domestic violence on later IPV perpetration and victimization disappears (Jennings et al., 2014; Widom, Czaja, & DuMont, 2015). In a meta-analysis of 39 studies of IGT conducted by Stith and colleagues (2000), they suggest that support for the theory is weak to moderate. With regard to victimization, they suggest that child abuse and witnessing interparental aggression have weak to moderate effects on later intimate partner victimization. They point to the need for more “com- plex studies” that are able to move beyond the examination of the direct rela- tionship between violence in the family of origin and later IPV. For example, Messing and colleagues (2012) suggested that posttraumatic stress disorder (PTSD) may partially mediate the relationship between some forms of child- hood trauma and later adult victimization.
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Likewise, several studies that are in line with the processes outlined in Akers’s SLT model have been employed to further disentangle this relation- ship between childhood experiences and adult IPV. The majority of these studies focus on the role of attitudes and beliefs surrounding violence and how they shape the risk for later perpetration and victimization. Several stud- ies have found that experiences of child abuse are related to later acceptance or condoning of violence against women, which may increase the likelihood of perpetration or risk of entering into a violent relationship (e.g., Markowitz, 2001). Indeed, this is often considered a crucial link in the learning process between childhood abuse and adult IPV.
Taken together, this research suggests that there is a complex relationship between childhood experiences of violence and adult IPV. However, the learning processes and mechanisms by which violence is transferred are not well understood. Akers’s SLT articulates some of these learning mechanisms and processes more explicitly.
SLT (Akers, 1998) proposes that crime and conformity are learned through interactions with other people that expose the individual to definitions and behaviors, reinforcements, and role models that either favor or oppose crime. Depending on the unique configuration of associates with whom one inter- acts, as well as the weight of each one’s influence on the individual, one may be exposed to attitudes, behaviors, reinforcements, and models that, on bal- ance, favor or oppose crime. In brief, SLT predicts that criminal behavior is likely to increase as association with criminal individuals outweighs associa- tion with noncriminal individuals; when this occurs, rewards for crime out- weigh the costs of crime, the number of criminal role models outweighs the number of conforming role models, and one’s positive or neutralizing defini- tions of crime outweigh one’s own negative definitions of crime.
SLT posits a processual model whereby differential association exerts both a direct effect on criminal behavior and a partially mediated or indirect effect via its influence on differential reinforcement, imitation, and defini- tions, which likewise exert direct effects on criminal behavior. Moreover, Akers (1998) argued that the model incorporates reciprocal and feedback effects, in which an increase in criminal behavior also amplifies association with others favorable to crime, which then continues one’s exposure to the other three elements of SLT.
Akers advanced SLT in a series of statements beginning with the differen- tial association-reinforcement theory (Burgess & Akers, 1966) and culminat- ing with the social structure-social learning model (Akers, 1998). Few
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empirical investigations of the theory were conducted until Akers himself published the first test of the full social learning model (Akers, Krohn, Lanza- Kaduce, & Radosevich, 1979), which demonstrated remarkable predictive accuracy of SLT in accounting for alcohol and drug use among adolescents. Tests of SLT flourished thereafter. Most of these studies were simple tests of the direct, linear, independent effects of one or more of the four social learn- ing variables on a dependent variable, the latter most frequently a form of substance use or common delinquency (for a review and meta-analysis, see Pratt et al., 2010). Far less common in the body of empirical research on SLT are tests of the causal sequencing of the full social learning model. Akers and Lee (1996) used structural equation modeling (SEM) to estimate both causal and reciprocal/feedback effects of social learning and teenage smoking (see also Cochran, Maskaly, Jones, & Sellers, 2017; Krohn, Skinner, Massey, & Akers, 1985), confirming (with the exception of the imitation variable) the hypothesized social learning effects. Lee, Akers, and Borg (2004) found sim- ilar results in their SEM analysis of the Social Structure Social Learning (SSSL) model of adolescent alcohol and marijuana use. Extending the social learning causal model to physical aggression rather than substance use, Cochran and colleagues (2017) demonstrated direct and indirect effects of all social learning variables on violence perpetrated against an intimate partner; moreover, IPV also exerted reciprocal/feedback effects on the four social learning variables.
Criminological theories like SLT are advanced explicitly to account for offending behavior. However, these theories in some instances are also pos- ited as viable explanations of criminal victimization (see, for instance, Schreck, 1999, regarding low self-control; Smith & Jarjoura, 1988, regarding social disorganization theory; or Zavala & Spohn, 2013, regarding general strain theory), in part because of the undeniable overlap between criminal offending and victimization (Lauritsen, Sampson, & Laub, 1991). There is at least some evidence of similar overlap in the victimization and perpetration of IPV (Graham-Kevan & Archer, 2003), especially in instances of what Johnson (1995) refers to as “common couple violence.” Prior research pro- vides some support of SLT as an explanation of IPV perpetration and less often, victimization (Cochran et al., 2017; Fox et al., 2011; Sellers et al., 2005, 2003; Wareham et al., 2009a, 2009b). Within the context of SLT, the likelihood of IPV victimization increases not only as exposure to a violent partner increases, but also as exposure to other victims of violence increases (differential association), especially when other victims express attitudes (neutralizing definitions) that excuse or rationalize the violence perpetrated against them (e.g., I was asking for it; he was drunk; that’s how a man shows he loves me). SLT acknowledges that these socialization processes can occur
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external to the family, including the cultural acceptance of violence as a means of conflict resolution (Krug, Mercy, Dahlberg, & Zwi, 2002) and the influence of traditional gender roles and violent masculinity. With regard to reinforcement, there is research to suggest that tenets of operant conditioning and reinforcement may explain the risk of IPV victimization or the stay– leave decision of victims. For example, Miller, Lund, and Weatherly (2012) applied operant learning principles to the examination of stay–leave deci- sions among women in violent relationships. The unpredictable pattern of offending behavior and subsequent reconciliation after abusive episodes pro- vides partial positive and negative reinforcements. Websdale (1998) sug- gested that the balance of reinforcements (e.g., the “honeymoon phase,” financial dependence) versus costs (e.g., physical injuries, emotional trauma, presence of children) of IPV victimization may at times tip toward repeated victimization. The response-cost of IPV may be quite high (Miller et al., 2012), and therefore, victimization, and repeated victimization, becomes more likely.
Gendered Learning Processes in IPV
IPV is a gendered phenomenon with regard to both perpetration and victim- ization (e.g., Johnson, 1995). As a general theory, SLT purports to account for the behavior of both men and women. In general, men are far more likely than women to be offenders and slightly more likely than women to be vic- tims of crime. SLT would explain that men are more likely than women to operate in learning environments that are more conducive to offending and victimization. However, some research on IPV finds that men and women are equally likely to be perpetrators as well as victims of aggression (Johnson & Ferraro, 2000). Furthermore, the social learning predictors of IPV differ by gender for both perpetration (Sellers et al., 2003) and victimization (Cochran, Sellers, Wiesbrock, & Palacios, 2011), but these tests were restricted to sim- ple regression-based approaches which do not allow for both direct and indi- rect/mediated social learning processes.
What progress has been made to investigate the processual features of SLT has largely focused exclusively on offending or deviant behavior such as sub- stance use. However, SLT has begun to be found to be a viable explanation of victimization as well and less often, of gendered processes in IPV. Although research is scant, social learning variables have been associated with stalking (Fox et al., 2011) and IPV (Cochran et al., 2011; Sellers et al., 2003). Sellers and colleagues (2003) tested both the efficacy of SLT to explain IPV perpe- tration and the gender invariance of SLT. They found that SLT could account for IPV perpetration but that several of the SLT measures were not gender
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invariant. Similarly, Cochran and colleagues (2011) tested the efficacy of Akers’s SLT against self-report data on repetitive intimate partner victimiza- tion; they found that for both male and female victims, repetitive IPV victim- ization was associated with both differential association and differential reinforcement. However, they did not test for gender invariance. Moreover, neither the Sellers and colleagues (2003) study nor the Cochran and col- leagues (2011) study employed an SEM approach that would have permitted them to examine both the direct and indirect effects of SLT variables on IPV and the reciprocal effects of IPV on the SLT process.
The moderating effects of gender on IPV perpetration and victimization have been more fully articulated and explored in the IGT literature. Several studies have found that the conclusions regarding the influence of experienc- ing or witnessing violence in the home are contingent on the gender of the child or the parental aggressor, which suggests that there are gendered pro- cesses in the transmission of violence. Whereas many have found that both male and female children are adversely impacted by exposure to or experi- ences of violence in the home, some have found that this relationship holds only for men (Alexander et al., 1991) or women (Douglas & Straus, 2006). Marshall and Rose (1988) found that experiencing child abuse was correlated with both IPV perpetration and victimization for men, but only victimization for women.
Others have attempted to disentangle this relationship by focusing on the gender dynamics of the parental relationship. Jankowski, Leitenberg, Henning, and Coffey (1999) suggested that the gender of the child and the parental aggressor interact such that vicarious victimization increased the likelihood of later IPV perpetration only when the child and parent were of the same sex. Likewise, Laporte, Jiang, Pepler, and Chamberland (2011) found that although both male and female teens who experienced child abuse were more likely to perpetrate IPV, these effects were stronger for men in general and strongest for men who experienced abuse by their fathers.
In sum, SLT provides more causal mechanisms and perhaps more explic- itly articulated mechanisms for explaining how experiencing or witnessing violence in the home leads to later IPV perpetration. However, it has rarely been extended to examine IPV victimization. Furthermore, the theory assumes gender invariance. IGT, on the contrary, has been extended to vic- timization and provides compelling evidence that these learning processes may be gendered. The present study draws from the theoretical basis of IGT as well as the empirical literature to examine the utility of SLT; it tests the efficacy of SLT to explain IPV victimization; it tests for gender invariance in the SLT process; and it examines the direct, indirect, and reciprocal relation- ships between SLT constructs and IPV through an SEM analytic approach.
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The data for this study were gathered through a self-administered survey of students attending a large urban university in Florida. The students were surveyed in graduate and undergraduate classes randomly selected from the course offerings of five colleges (Arts and Sciences, Business Administration, Education, Engineering, and Fine Arts) during the first 4 weeks of the spring 1995 semester. Courses were sampled from each col- lege in proportion to the enrollments each college contributed to the uni- versity’s total enrollment. This sampling strategy targeted a total of 2,500 students; however, absenteeism on the day of the survey and enrollments of students in more than one sampled course produced an overall response rate of 73%. The current study is based on those students who completed the questionnaire, who report being currently involved in an intimate rela- tionship (i.e., married or dating), and who also report having had at least one previous serious relationship (n = 1,124). The sociodemographic pro- file of the sample was very similar to that of the total enrollment at the university. Importantly, these data, unlike most other self-reported data collections, were specifically designed to examine the efficacy of Akers’s SLT on IPV. Finally, while these self-report data are derived from a sample of college students, it is noteworthy that a substantial number of the respondents were married or cohabiting, and as we report below, the prev- alence and frequency of IPV among the students sampled was quite substantial.
Dependent variable: IPV. The dependent variables used in this study were latent constructs developed from a single set of measures of self-reported intimate partner violence victimization (IPV-V) by one’s current partner: a total scale composed of eight items and a subscale of the five more serious/ injurious items. All are drawn from the physical aggression items in Straus’s (1979) Conflict Tactics Scale (CTS)—The data were collected prior to the development of the CTS-II. Specifically, respondents were asked with regard to their current marital or dating relationship how many times their partner had done any of the following eight acts of IPV: (a) threw something; (b) pushed, grabbed, or shoved; (c) slapped; (d) kicked, bit, or hit with a fist; (e) hit with something; (f) beat up; (g) threatened with a knife or gun; and (h) used a knife or gun. Responses to these items were never, once or twice, 3 to 5 times, 6 to 10 times, 11 to 20 times, and 21 or more times, coded from 0 to
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7. Identical constructs were also constructed for victimization by a previous romantic partner. These were employed as exogenous variables and provide a method for assessing the reciprocal/feedback effects of prior victimization experience on the social learning process.
Independent variable: Social learning constructs. The independent variables in this study are first- or second-order latent constructs representing each of Akers’s four social learning concepts: differential association, imitation, defi- nitions, and differential reinforcement. We endeavored to measure the con- structs using items and scales derived near exactly as they were measured by Akers and colleagues (1979), though modified to reflect IPV rather than ado- lescent substance use.
Differential association is a second-order latent construct comprised of a single-item measure of the respondents’ estimation of the proportion of their best friends who had been physically victimized by a romantic partner (1 = none or almost none, 2 = less than half, 3 = more than half, and 4 = all or almost all), and two first-order latent constructs. The first of these first-order latent constructs is comprised of four items measuring mother’s, father’s, partner’s, and best friend’s attitudes toward IPV. For these items, respondents were asked to indicate to what degree each of these significant others would approve/disapprove of the use of physical violence against a partner (1 = strongly disapprove to 4 = strongly approve). The second of these two first- order latent constructs used to constitute differential association is composed of five indicators of physical violence used against significant others. Specifically, respondents were asked to indicate how often their mother, father, siblings, other family members, and best friends were victims of IPV (1 = never, 2 = seldom, 3 = usually, and 4 = always).
Imitation is measured by a first-order latent construct comprising seven different admired role models the respondent had actually seen being physi- cally victimized (i.e., hit, slapped, kicked, or punched) by an intimate partner during a disagreement. These admired models included actors on television or in movies, mother, father, siblings, other family members, friends, and others.
Definitions is another second-order latent construct comprising a single- item measure of respondents’ own approval/disapproval of the use of physi- cal violence against a partner (1 = strongly disapprove to 4 = strongly approve), and three first-order latent constructs. The first of these three first- order latent constructs is a two-item measure of respondents’ attitudes favor- able toward the violation of the law in general and indicated by the extent to which respondents agreed/disagreed with the following Likert-type state- ments (1 = strongly agree to 5 = strongly disagree): “We all have a moral duty
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to abide by the law” (reverse coded) and “It is okay to break the law if we do not agree with it.” The next of these three second-order latent constructs rep- resents definitions approving of IPV indicated by three Likert-type state- ments (e.g., “It is against the law for a man to use violence against a woman even if they are in an intimate relationship”). Finally, the third of these first- order latent constructs measures neutralizing definitions and is composed of responses to three Likert-type statements (e.g., “Physical violence is a part of a normal dating/marital relationship”).
The last social learning construct, differential reinforcement, is a second- order latent construct comprised of two first-order constructs and two single- item measures. First, respondents reported the actual or anticipated reaction of three different sets of significant others (i.e., parents, other family mem- bers, and best friends) to the respondent’s physical victimization by their partner. Respondents indicated that these significant others would either 1 = disapprove and report to the authorities, 2 = disapprove and try to stop it, 3 = disapprove but do nothing, 4 = neither approve nor disapprove, and 5 = approve and encourage it. Second, a single 3-point, ordinal measure of the overall balance of reinforcement for partner violence was included. This item measured the respondent’s perception of the usual or anticipated net outcome from being victimized by their current partner (1 = mostly bad, 2 = about as much good as bad, and 3 = mostly good). Third, the net rewards-to-costs of being physically victimized by their partner was measured by asking respon- dents to indicate which, if any, of five social and nonsocial rewards and seven social and nonsocial costs they associated with IPV by their current partner. An example of a reward was “It showed me my partner really loved me,” and an example of a cost was “My friends criticized me.” To compute the net rewards-to-costs, the sum of the identified costs was subtracted from the sum of the identified rewards; this produced a measure with values ranging from −7 (all costs and no rewards) to 5 (no costs and all rewards). The results from the full confirmatory factor analysis (CFA) are included in the appendix.
Considering that the purpose of the current study is to examine the direct and indirect effects of various components of the social learning process on IPV victimization, the most appropriate analytical technique is SEM. Following the two-step process (see Kline, 1998), we first develop and test a measure- ment model using CFA. Following the recommendations of Hoyle and Panter (1995), we report several fit indices (i.e., χ2, standardized root mean square residual [SRMSR], root mean square error of approximation [RMSEA], and comparative fit index [CFI]). We follow the recommended general criterion
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values for fit statistics (e.g., Hu & Bentler, 1995). Following the measure- ment model, we test the structural model. Our structural models proceed in two phases, examining how SLT predicts (a) IPV victimization by one’s cur- rent partner and (b) the extent to which the social learning model of IPV victimization is gender invariant (measurement models available upon request).
Although no variable had more than 15% missing, using the standard list- wise deletion procedure would have resulted in approximately 30% attrition. Markov Chain Monte Carlo (MCMC) simulation was used to impute 10 data- sets to fill in missing values. All models were estimated in MPlus 7.4 using the weighted least squared Muthen version (WLSMV) estimator to account for the limited nature of the indicators (Rhemtulla, Brosseau-Liard, & Savalei, 2012).
The baseline social learning model is presented in Figure 1. It allows for an examination of both direct and indirect effects of the theoretically expected paths between the social learning constructs and IPV victimization. Importantly, it also controls for the anticipated feedback or reciprocal effects of IPV victimization on the social learning constructs as expressed by the effects of IPV victimization by one’s past partner on the social learning pro- cess that predicts IPV victimization by one’s current partner.
Overall, the model fit the data (χ2 = 660.94; SRMSR = .0120; RMSEA = .0009; CFI = .999). The results are somewhat mixed with regard to SLT’s ability to explain intimate partner victimization. First, the model accounts for only about 15% of the variance in IPV victimization by one’s current partner. While such a value is not uncommon in tests of many micro-social theories of criminal/deviant behavior, it is well below the R-square values typically observed in tests of Akers’s SLT. Second, we observe significant direct effects on victimization by one’s current partner in the theoretically expected direc- tion for only two of the four social learning constructs: differential associa- tion (b = .13; p < .05) and differential reinforcement (b = .12; p < .001). Conversely, we observed a nonsignificant effect for definitions (b = .04; ns) and an inverse effect for imitation (b = −.06; p < .05).
Differential association, as expected, also exerted direct effects on all three of the other social learning constructs (b = .30; p < .001 on differential reinforcement; b = .21; p < .001 on definitions; and b = .22; p < .001 on imita- tion). These effects support a partially mediated, indirect effect of differential association on intimate partner victimization through differential reinforce- ment (b = .04; p < .05), a small spurious component to its total effect via the
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definitions construct (b = .008; p < .05); and an unexpected diminution of its total effect due to imitation (b = −.01; p < .05) which, as noted above, is inversely associated with IPV victimization.
In addition to the social learning constructs, it is worth noting that IPV with a past partner (included in the model as a proxy for the expected recipro- cal/feedback effects of behavior on the social learning process) is a signifi- cant predictor of current partner victimization (b = .16; p < .001) and all of the other social learning constructs with the exception of definitions (b = .17; p < .001 on differential association; b = .25; p < .001 on differential reinforce- ment; b = .04; p < .001 on imitation; and b = −.00; ns on definitions). The results suggest that being the victim of IPV perpetrated by a prior partner seems to influence a person’s differential association and differential rein- forcement. Hence, being the victim of prior IPV also significantly, though
Figure 1. Baseline social learning model of IPV victimization by one’s current partner. Note. Model fit: χ2(1,015) = 660.94; SRMSR = .0120; RMSEA = .0009; CFI = .9987. Total variance explained by model = 15.4%. IPV = intimate partner violence; SRMSR = standardized root mean square residual; RMSEA = root mean square error of approximation; CFI = comparative fit index. *p < .05. **p < .01. ***p < .001.
Powers et al. 13
indirectly through differential association and differential reinforcement, increases the likelihood of also being the victim of IPV in their current rela- tionship (b = .02; p < .05 and b = .03, p < .001, respectively). In addition, there are more distal indirect effects of past partner intimate partner victim- ization that are transmitted through differential association to all of the other social learning constructs onto current partner IPV victimization. These distal indirect effects are theoretically consistent for both differential reinforcement (b = .006; p < .05) and definitions (b = .001; p < .05), but theoretically incon- sistent for imitation (b = −.002; p < .05).
To determine whether the social learning model operates differently for men and women, we conduct a series of tests to examine model invariance across gender. This process involves estimating a series of separate models for each group with progressively fewer restrictions between the group models. While it is desirable to modify the measurement model and the structural model simultaneously, this was not possible in the present study due to the complex measurement structure of these data (i.e., single-item constructs, first-order latent variables, and second-order latent variables). Therefore, we first test for measurement model invariance between men and women independently and then turn our attention to the invariance of the structural model. Testing model invariance is done by comparing the Δχ2 and the ΔCFI between the less restrictive model and the more restric- tive model (Byrne, 2010).
The test of invariance in the measurement model looks specifically at whether items measure the same construct in the same manner for members of both groups—here women and men. Starting with the most restrictive model, assuming the items measure the latent traits the same in both men and women, we see the model fits the data well (χ2 = 2,400.76; SRMSR = .0549; RMSEA = .0547; CFI = .9843). Only the model in which all parameters were allowed to freely vary between groups fit the data almost as well as the fully constrained model (χ2 = 2,281.93; SRMSR = .0531; RMSEA = .0515; CFI = .9863); however, this effect was not a significant improvement in model fit. When examining the factor loadings, the results suggest that the magnitudes of certain intimate partner victimization experiences vary for men and women. Therefore, we elect to use the more parsimonious measurement model for two reasons. First, there is no significant improvement in model fit based on the change. Second, the substantive meaning of the measures does not change between the two groups—rather the magnitudes of a small num- ber of factor loadings vary between genders.
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Next, we examine the potential for model invariance between men and women in the structural component of the model. Again, we start with the most restrictive model that assumes the causal process and the magnitudes of the effects are the same across gender. This model fits the data poorly (χ2 = 9,149.20; SRMSR = .0918; RMSEA = .122; CFI = .503), which suggests there are likely substantial differences in the social learning processes of inti- mate partner victimization between men and women. Working through the iteration of model constraints, we find the best fitting model to be the one where all values are allowed to vary freely between genders (χ2 = 2,768.19; SRMSR = .0462; RMSEA = .035; CFI = .994). Hence, Akers’s SLT is not gender invariant with regard to its ability to predict and explain intimate part- ner victimization.
The results of this model are presented in Figure 2. This figure depicts the same pooled model estimated previously, but now independently presenting the
Figure 2. Gendered social learning model of IPV victimization by one’s current partner. Note. Model fit: χ2(1,273) = 2768.19; SRMSR = .0462; RMSEA = .035; CFI = .994. Total variance explained by model = 24.5%. IPV = intimate partner violence; SRMSR = standardized root mean square residual; RMSEA = root mean square error of approximation; CFI = comparative fit index. *p < .05. **p < .01. ***p < .001.
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parameter estimates for men and women. Unlike the results from the pooled model, we see varying degrees of support for the social learning constructs’ abil- ity to directly explain intimate partner victimization with a current partner. The only direct effect of a social learning construct on current partner victimization that is significant for both men (b = .15; p < .05) and women (b = .11; p < .05) is differential reinforcement. Interestingly enough, there are different predictors of intimate partner victimization between the genders. Differential association, which tends to be one of the most robust of the social learning constructs, is significant for women (b = .17; p < .05), but not for men (b = .14; ns). Furthermore, we note theoretically inconsistent effects for imitation for both genders. The direct effect of imitation for men is significant and negative (b = −.31; p < .05), whereas the effect for women is nonsignificant (b = −.03; ns). Additional evidence of gendered social learning effects is seen in the direct effect of definitions, which exerts a theoretically expected effect for women (b = .06; p < .05) and an inconsistent effect for men (b = −.06; ns).
Although there are inconsistent findings in the direct effects between the social learning constructs and intimate partner victimization with a current part- ner, there are more theoretically consistent indirect effects of differential asso- ciation through the other social learning constructs across gender. Specifically, for men, we see the expected indirect effects of differential association through differential reinforcement (b = .066; p < .05) and imitation (b = .078; p < .05), although the effect through definitions, while significant, is theoretically unex- pected (b = −.025; p < .05). For women, we see theoretically expected indirect effects of differential association through both differential reinforcement (b = .02; p < .05) and definitions (b = .008; p < .05); conversely, we see a theoreti- cally unexpected yet significant indirect effect for imitation (b = −.006; p < .05).
The feedback effect of victimization by a past intimate partner on victimiza- tion by one’s current partner is substantially stronger for men (b = .48; p < .05) than for women (b = .06; p < .05). Furthermore, we again see there are more distal indirect effects of being the victim of prior IPV through differential association and then through other social learning constructs. Again, these patterns are con- sistent with the prior results. Specifically, the distal indirect effect through dif- ferential reinforcement is theoretically anticipated for both men (b = .01; p < .05) and women (b = .003; p < .05). However, the nature of this distal indirect effect through imitation (bMen = −.01; p < .05; bWomen = −.001; p < .05) and definitions (bMen = −.004; p < .05; bWomen = .001; p < .05) are inconsistent between genders.
Because our measure of intimate partner victimization includes several items that could be deemed less serious or less injurious, we replicated the baseline
16 Journal of Interpersonal Violence 00(0)
and gendered models present with models in which the latent variable for IPV victimization is restricted to the five more serious forms of IPV (i.e., slapped; kicked, bit, or hit with a fist; hit with something; beat up; threatened with a knife or gun; used a knife or gun). By and large, the findings from these supplementary analyses mirror those reported above (results available upon request). That is, we observed somewhat mixed support for SLT’s ability to effectively predict IPV victimization, and, more importantly, we also observed that the social learning process of IPV victimization is, again, not gender invariant.
Also, because IGT stresses the unique effects of early childhood expo- sure to violence in the family of orientation on subsequent perpetration and/or victimization in one’s family of procreation, we also elected to test a pure IGT model on IPV victimization (see Wareham et al., 2009a, 2009b). This model (available upon request) restricted the components of the latent variables to only those associated with mother’s and father’s use of IPV witnessed by our subjects, mother’s and father’s supportive definitions of IPV, role modeling of IPV, and rewards and punishments for subject’s IPV on subjects’ definitions of IPV and their IPV victimiza- tion. Several findings are especially noteworthy. First, the model restrict- ing attention to parental influences on IPV victimization did not fit the data nearly as well as the full social learning models presented herein (e.g., R2 of .08 for the IGT model vs. .15 for the SLT model). Second, the parameter estimates for the effects of these latent constructs were con- siderably weaker and less likely to attain statistical significance than were their parallel effects from the more complete SLT model. Notable among these was the very weak, inverse, and nonsignificant effect of witnessing parents’ use and role modeling of IPV in childhood (b = −.02; p > .05).
The findings are rather mixed with regard to SLT’s ability to explain and predict IPV victimization. On one hand, the theory does seem to work as expected. There was empirical support for most of the pathways articulated in the theory. Likewise, the fully explicated social learning model fit the data considerably better than the IGT model assessed in our supplementary analy- ses. As a test of the scope of Akers’s SLT, these results do establish that the theory can be extended to effectively explain and predict IPV victimization as well as perpetration. With regard to whether these relationships are gender invariant, in both of the gendered models examined for the effects of social learning variables on IPV victimization, we found more support for fully
Powers et al. 17
gendered pathways for the social learning processes of male and female IPV victimization.
These results ultimately underscore the importance of consideration of gendered pathways for IPV and challenge traditional criminological theories to address how and why processes that lead to perpetration and victimization may differ for men and women. For example, Schwartz and Pitts (1995) inte- grated feminist theory into routine activities theory (RAT) to explain how college campuses are criminogenic for violence against women perpetrated by men. By focusing on the motivation for violence among college men, they challenge traditional criminological theory while elucidating specific pro- cesses that lead to violence against women. For SLT as applied to IPV in particular, SLT may benefit from the explicit acknowledgment of how these same macro-level cultural values in a patriarchal society influence individual learning processes. For example, drawing from DeKeseredy and Schwartz’s (1993) modified male peer support theory, differential association with men who support values that condone violence against women likely impart these values, which leads to an increase in the likelihood of perpetration. Likewise, abuse and toxic masculinity is reinforced by these same peer groups. More broadly, as men and women both live in a patriarchal society, these cultural values excuse or legitimize the use of violence in intimate partnerships. Therefore, although SLT is aptly suited to more fully articulate the learning processes of IPV victimization, given the unique nature of IPV, SLT would be strengthened by the integration of feminist theories that situate offending and victimization experiences in a larger cultural context.
Implications for Future Research
These analyses provide new avenues for research in this area. For example, in the current study, differential association was only directly related to vic- timization for women and imitation was negatively related to victimization for men. This finding is at first counterintuitive; however, as Bandura (1973) suggested, high status role models may influence the social learning process more, and some research on IGT suggests that the gender of the parental aggressor matters in that a same-sex parent exerts a more meaningful influ- ence on the child’s later adult behavior (e.g., Jankowski et al., 1999). These same dynamics may also influence social learning processes for victimiza- tion. For example, in the current study, it is not known what proportion of their friends who are victims are of the same gender as the respondent. Likewise, although our ancillary models isolated more severe forms of IPV in terms of the likelihood of injury as the outcome, we were not able to explore the severity of violence among the respondents’ family, friends, and
18 Journal of Interpersonal Violence 00(0)
role models. Therefore, future research should disentangle which role models are most salient in shaping risk as well as how the type of violence experi- enced in one’s social network shapes IPV experiences for victims.
Future research should also explore how the processes and mecha- nisms of SLT differ among those who co-share the role of victim and offender, as the victim–offender overlap with regard to IPV has been observed in several studies (e.g., Lauritsen et al., 1991). It is possible that some of these processes, particularly those related to neutralizing defini- tions, operate differently for those who are in mutually combative rela- tionships. It is important to examine not only whether those who are victims may also be considered perpetrators, but also the context of the perpetration, as some have suggested that women often use violence in self-defense or in anticipation of victimization (Allen, Swan, & Raghavan, 2009).
Another distinction in the type of domestic violence is more difficult to disentangle, but equally important. Johnson (1995) suggested that although there may be relative gender symmetry with regard to overall likelihood of domestic violence, there are different types of domestic vio- lence: common couple violence (CCV), intimate terrorism (IT), violent resistance (VR), and mutual violent control (MVR) (Johnson & Ferraro, 2000). These distinctions are important for a number of reasons. First, women are more likely than men to be victims of IT, which often involves not only physical aggression but also psychological abuse. Therefore, the reinforcement process and the definitions that condone or neutralize these behaviors may operate differently on the aggregate between men and women. Although research has explored these ideas with regard to perpe- tration and has found that IT and CCV perpetrators differ in their attitudes toward women (see Johnson, 2006; Johnson & Ferraro, 2000), research has not thoroughly explored the role of these factors for victims. Second, the processes that tap into observed violence or knowledge of violence between parents, friends, and role models may differ contingent on whether that violence featured coercive control.
Implications for Policy and Prevention/Intervention Strategies
Differential association (i.e., knowing others who are victimized, parents’ attitudes toward IPV) predicts differential reinforcement (i.e., perceptions of others’ reactions to IPV, cost/benefit analysis of IPV) for both men and women. Likewise, differential reinforcement impacts risk of victimiza- tion. Taken together, this suggests that the risk of entering and remaining in a violent relationship is shaped the experiences and perceived reactions
Powers et al. 19
of close family and friends. Research has long recognized the role of the attitudes of significant others in shaping risk of perpetration and the micro-level (e.g., peer groups) and macro-level (e.g., cultural norms) influences on those attitudes, albeit the focus has been predominately on violence against women (see Flood & Pease, 2009). In addition, research has pointed to the role of positive social support from family and friends on victims’ recovery (e.g., Coker et al., 2002) and in the decision-making process to leave a violent relationship (Miller et al., 2012). This suggests that prevention programs that focus on changing social norms surround- ing IPV and explicitly focusing on how informal social networks can sup- port healthy relationships and remove barriers to leaving violent relationships may be effective.
Likewise, the response-cost of staying in abusive relationships can be directly addressed through an increase in victim services and punishments for offending. Women who are victims of IPV do not lack agency, rather they make decisions based on the perceived costs and benefits of leaving. Choice and Lamke (1997) suggested that conceptually, these decisions fall under one or both domains: “Can I do it?” and “Will I be better off?” The role of the criminal justice system is to remove the structural and personal barriers to leaving (e.g., fear of retaliation, financial burden) so that women are able to leave abusive relationships.
Furthermore, there is psychological variation in the experiences of IPV victims, and this has implications for intervention strategies. For example, Lerner and Kennedy (2000) found that coping, trauma, and self-efficacy play a role in the decision-making processes of female IPV victims. These likely interact with learning processes, particularly in terms of perceptions of response-cost. This suggests that practitioners should acknowledge variation in women’s experiences and tailor intervention strategies accord- ingly. Likewise, intervention strategies should focus on not only removing tangible barriers to leaving an abusive relationship but also fostering cop- ing skills and self-efficacy to empower women who choose to leave.
The mixed results with regard to Akers’s SLT, particularly those most at odds with previous tests of the theory, suggest that the present study may be hampered by a number of possible limitations. For instance, both IGT and Akers’s SLT are processual theories that require longitudinal data for proper testing. The present study is restricted to cross-sectional data, as are
20 Journal of Interpersonal Violence 00(0)
most other tests of SLT. Although the investigation of both direct and indi- rect social learning effects through SEM and the inclusion of a measure of past partner IPV victimization as a surrogate measure for the feedback/ reciprocal effect of behavior on the social learning process mitigate this limitation somewhat, future research should explore these processes using panel data.
Another limitation of these data that needs to be addressed is the dated nature of these data; they are more than 20 years old. While the age of the data should not, in most cases, be a relevant concern for tests of a general theory, there has be to considerable social and technological changes that have taken place that have had an influence on both IPV and social learning processes. Over this passage of time, there has been considerable attention in research, policy, practice, and the media on the issue of IPV, raising social awareness about this problem. In turn, this greater awareness may have altered persons’ perceptions and attitudes toward IPV in ways much different than they were when the college students in these data were surveyed. Moreover, social media now play a much more prominent role in our daily lives. These social media permit new ways for violent partners to contact, surveil, stalk, threaten, and/or terrorize their victims. At the same time, social media also provides victims of IPV additional outlets for social support and assistance.
Finally, our measures of differential association and differential reinforce- ment rely heavily upon respondents’ perceptions on how significant others were victims of IPV, their perceptions of their significant others’ attitudes toward IPV, and their perceptions on their significant others’ reactions to respondent’s IPV victimization. Measurements that rely on such perceptual measures are prone to projection bias in measurement (see Rebellon & Modecki, 2014).
Whereas Akers’s SLT may be a more fully articulated theoretical frame- work that allows for a more thorough exploration of the causal processes in IPV victimization, these results suggest that these pathways are highly gen- dered. The current state of social learning research cannot fully explain why these processes are different for men and women. However, SLT, cou- pled with insights from the IPV literatures on IGT, cultural norms surround- ing gender, and typologies of domestic violence provide promising avenues of research to disentangle under what conditions these factors matter in shaping risk of intimate partner victimization.
Powers et al. 21
Appendix CFA Estimates.
Latent Variable/Sublatent Variable (When Applicable)/Item (Variable Name) Coefficient (SE)
Differential associations Number of friends experiencing IPV (NOFRPHYV) 0.36 (.03)***
Friends and families definitions 0.59 (.05)*** Mother’s definitions of IPV (momdef) 0.49 (.03)***
Father’s definitions of IPV (daddef) 0.83 (.04)*** Best friend’s definitions of IPV (bfdef) 0.47 (.05)***
Sexual partner’s definitions of IPV (spdef) 0.32 (.04)***
Victimization experiences of friends and family 0.91 (.05)*** Mother victim of physical IPV (damaphyv) 0.76 (.03)***
Father victim of physical IPV (dafaphyv) 0.52 (.03)*** Sibling(s) victim(s) of intimate partner IPV (dasbphyv) 0.56 (.03)***
Another family member victim of physical IPV (daofphyv) 0.55 (.03)*** Best friend victim of intimate partner IPV (dabfphyv) 0.52 (.03)***
Differential reinforcement Rewards minus costs for IPV victimization (R − C) 0.30 (.03)***
Usual result of IPV victimization (VOUTCOME) 0.62 (.06)*** Reactions to violence 0.52 (.05)***
Parents reactions to IPV victimization (PARREACP) 0.90 (.01)*** Friends reactions to IPV victimization (FRREACP) 0.80 (.01)***
Other relatives’ reactions to IPV victimization (ORREACP) 0.90 (.01)***
Imitation Ever seen someone you admire. . .
Actor victim of IPV (imacphyv) 0.34 (.04)*** Father victim of IPV (imfaphyv) 0.31 (.04)***
Mother victim of IPV (immaphyv) 0.34 (.04)*** Siblings victim of IPV (imsbphyv) 0.51 (.05)***
Another relative victim of IPV (imorphyv) 0.35 (.04)*** Friends victim of IPV (imfrphyv) 0.42 (.04)***
Another admired person victim of IPV (imotphyv) 0.35 (.04)***
Definitions Index of participant’s own definitions of IPV (OWNDEF) 0.64 (.05)***
General definitions of law abiding 0.71 (.03)*** We all have a moral duty to abide by the law (lawabid1—
reversed) 0.41 (.05)***
It’s okay to break the law if we do not agree with it (okbrlaw) 0.42 (.02)***
22 Journal of Interpersonal Violence 00(0)
Latent Variable/Sublatent Variable (When Applicable)/Item (Variable Name) Coefficient (SE)
Laws controlling violence, even in relationships, should be obeyed (lawobey)
Neutralizing definitions 0.71 (.05)*** Physical violence is a normal part of a dating relationship
(violnorm—reverse) 0.50 (.02)***
I believe victims provoke physical violence (victprvk—reverse coded)
In dating relationships, physical abuse is never justified (abusnev) 0.61 (.02)*** Specific definitions 0.74 (.05)***
It’s illegal for a man to use violence against a woman, even in a relationship (mviolw)
It’s illegal for a woman to use violence against a man, even in a relationship (wviolm)
Past partner victimization How many of your partners in prior committed
relationships have. . .
Threw, smashed, hit, or kicked something (vppthrew) 0.85 (.01)*** Pushed, grabbed, or shoved you (vpppush) 0.78 (.01)***
Slapped you (vppslap) 0.83 (.01)*** Kicked, bit, or hit you with fist (vppkick) 0.89 (.01)***
Hit or tried to hit you with something (vpphit) 0.90 (.01)*** Beat you up (vppbeat) 0.53 (.02)***
Threatened you with a knife or gun (vppthrgun) 0.35 (.02)*** Used a knife or gun against you (vppgun) 0.28 (.02)***
Current partner victimization How many times has your current partner. . .
Threw, smashed, hit, or kicked something (vcpthrew) 0.67 (.02)*** Pushed, grabbed, or shoved you (vcppush) 0.70 (.01)***
Slapped you (vcpslap) 0.81 (.01)*** Kicked, bit, or hit you with fist (vcpkick) 0.81 (.01)***
Hit or tried to hit you with something (vcphit) 0.87 (.01)*** Beat you up (vcpbeat) 0.44 (.02)***
Threatened you with a knife or gun (vcpthrgun) 0.51 (.02)*** Used a knife or gun against you (vcpgun) 0.26 (.03)***
Covariance terms momdef, bfdef 0.07 (.03)*
daddef, bfdef −0.21 (.11)*
Powers et al. 23
Latent Variable/Sublatent Variable (When Applicable)/Item (Variable Name) Coefficient (SE)
daddef, spdef −0.19 (.08)* damaphyv, daofphyv −0.17 (.05)** damaphyv, dabfphyv −.034 (.06)*** dafaphyv, dabfphyv −.0.17 (.04)*** dasbphyv, daofphyv 0.08 (.03)* imacphyv, imorphyv 0.78 (.01)*** imfaphyv, immaphyv 0.28 (.03)***
OWNDEF, General Defs. 0.37 (.03)*** OWNDEF, Neutral Defs. 0.41 (.03)*** OWNDEF, Specific Defs. 0.23 (.03)***
General Defs., Neutral Defs. 0.95 (.03)*** General Defs., Specific Defs. 0.68 (.03)***
Neutral Defs., Specif Defs. 0.61 (.03)*** vcpthrew, vcppush 0.19 (.03)***
vcpthrew, vcphit 0.27 (.03)*** vcpslap, vcphit −0.29 (.05)***
vcpslap, vcpbeat 0.23 (.03)*** vcpbeat, vcpthrgun −0.20 (.03)***
vppslap, vppbeat 0.22 (.02)*** vpphit, vppbeat 0.13 (.03)*** vpphit, vppgun 0.06 (.02)***
vppbeat, vppthrgun 0.26 (.02)*** vppbeat, vppthrgun 0.36 (.02)***
vppbeat, vppgun 0.36 (.02)*** vppthrgun, vppgun 0.73 (.01)***
Cur. Part. Vic., Past Part. Vic. 0.30 (.02)***
Note. χ2(1,027) = 698.51; SRMSR = 0.009; RMSEA = 0.004; CFI = 0.9989. Items in bold and left justified are latent constructs; those in bold, italicized, and indented are sublatent constructs; and right justified items are observed variables. Text in parentheses are variable names with reversed = items that were reverse coded. All covariance terms refer to the error/disturbance term associated with the variable. CFA = confirmatory factor analysis; IPV = intimate partner violence; SRMSR = standardized root mean square residual; RMSEA = root mean square error of approximation; CFI = comparative fit index. *p < .05. **p < .01. ***p < .001.
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.
24 Journal of Interpersonal Violence 00(0)
The author(s) received no financial support for the research, authorship, and/or publi- cation of this article.
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Ráchael A. Powers, PhD, is an associate professor in the Department of Criminology at the University of South Florida. Her research interests surround violent victimiza- tion including intimate partner violence, sexual violence, and hate crime. She has been published in Justice Quarterly, Journal of Interpersonal Violence, and Child Abuse & Neglect, among other outlets.
John K. Cochran is a professor of criminology at the University of South Florida. He earned his PhD in sociology at the University of Florida (1987). He has more than 100 peer-reviewed manuscripts, most of which involve tests of micro-social theories of criminal behavior and macro-social theories of crime and crime control. His current research interests involve tests of micro-social theories of criminal behavior. He is also continuing his work on issues associated with the death penalty.
Jon Maskaly is an assistant professor in the Criminology Program at the University of Texas at Dallas. He received his doctorate from the University of South Florida. His research interests are in quantitative applications to test criminological theory, communities and crime, and law enforcement. His recent publications have appeared in Social Science Research, Crime & Delinquency, and the American Journal of Criminal Justice.
Christine S. Sellers is professor and director of the School of Criminal Justice at Texas State University. She is coauthor with Ronald Akers and Wesley Jennings on Criminological Theories: Introduction, Evaluation, and Application, now in its sev- enth edition. Her research interests include criminological theories and the role of gender in the explanation of criminal and delinquent behavior.
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