Integrative Literature Review

A Dyadic Perspective on Psychopathology and Young Adult Physical Dating Aggression

Ann Lantagne and Wyndol Furman Department of Psychology, University of Denver

Objective: Although psychopathology has been broadly implicated as a risk factor for dating aggression, very little work has examined the externalizing and internalizing symptoms of both romantic partners to more fully understand associations between psychopathology and physical dating aggression among young adult couples. The present study examined the effects of each partner’s psychopathology on physical dating aggression, the conjoint influence of both partners’ psychopathology, and whether the effects of psycho- pathology on aggression depended upon the nature of the relationship. Method: Actor Partner Interdepen- dence Models were used to examine associations between psychopathology and physical dating aggression among 127 young adult couples (M age = 22.04 years). Actor Partner Interdependence Moderation Models (APIMoMs) were then tested to determine whether negative relationship characteristics exacerbated the effects of psychopathology on aggression. Results: Both males’ and females’ externalizing and internaliz- ing symptoms were associated with dating aggression. Evidence of homophily was found, and actor partner interactions revealed that couples in which both partners had high externalizing symptoms were at greater risk, whereas when either partner had low symptoms, the risk was mitigated. Relationship risk factors interacted with externalizing symptoms to predict female physical dating aggression, and with internalizing symptoms to predict partner aggression. Conclusion: Findings lend support to the merits of using a dyadic approach to examine individual risk factors and combinations of individual and relationship risk factors in predicting young adult physical dating aggression. Results could potentially inform clinical work on patterns and combinations of risk factors characteristic of high-risk young adult couples.

Keywords: dating aggression, dating violence, intimate partner violence, romantic relationships, dating

Supplemental materials: https://doi.org/10.1037/vio0000386.supp

Rates of physical dating aggression peak among young adult couples; in fact, more than half of individuals ages 18–24 report that they have experienced violence in a relationship (Halpern et al., 2001; O’Leary, 1999). Psychopathology is a known risk factor for such aggression (Devries et al., 2013). Indeed, elevated externaliz- ing symptoms, such as conduct problems and delinquency, and internalizing symptoms, such as depression and anxiety, are associ- ated with dating aggression during young adulthood (Vezina & Hebert, 2007). Existing work, however, has primarily focused on only one individual’s psychopathology and links with aggression (Capaldi et al., 2012). Notably, each partner’s characteristics shape the relationship: among young adult couples, both partners’ antiso- cial behaviors and depressive symptoms are uniquely associated with male and female physical dating aggression (Kim & Capaldi, 2004). Young adults also tend to select partners with similar levels

of psychopathology, suggesting that certain combinations of part- ners may be at greater risk (Kim & Capaldi, 2004). By examining risk among couples, physical dating aggression can be predicted above and beyond a single individual’s risk, yet limited work has taken such a dyadic approach during young adulthood.

One of the primary purposes of the present study was to supple- ment the limited dyadic work examining both partners’ psychopa- thology and physical dating aggression during this time. By including both partners’ risk factors, the present study sought to further our understanding of whether individual risk factors for dating aggression can be conceptualized as a dyadic process; specifically, we examined whether partner psychopathology contributed above and beyond the association between an individual’s psychopathology and their own dating aggression. We also examined whether partner similarity (homophily) occurred for psychopathology and explored the conjoint influence of both romantic partners’ psychopathology on the risk for aggression. Finally, the present study extended existing research by testing a dyadic moderation model to investigate whether relationship risk factors exacerbated associations between psychopathology and aggression. Results have the potential to further our understanding of psychopathology as a risk factor for physical dating aggression among young adult couples.

A Dyadic Approach to Dating Aggression

The dynamic developmental systems perspective (DDS; Capaldi et al., 2005) provides a dyadic conceptualization of young adult physical dating aggression across multiple levels of risk factors.

This article was published Online First April 29, 2021.

Ann Lantagne https://orcid.org/0000-0002-9435-7080 Preparation of this manuscript was supported by Grant 050106 from the

National Institute of Mental Health (Wyndol Furman, P.I.) and Grant 049080 from the National Institute of Child Health and Human Development (Wyndol Furman, P.I.). Appreciation is expressed to the Project Star staff for their assistance in collecting the data, and to the Project Star participants and their partners, friends and families. Correspondence concerning this article should be addressed to Ann

Lantagne, Department of Psychology, University of Denver, Denver, CO 80209, United States. Email: [email protected]

Psychology of Violence

© 2021 American Psychological Association 2021, Vol. 11, No. 6, 569–579 ISSN: 2152-0828 https://doi.org/10.1037/vio0000386

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At the core level of the perspective are the individual characteristics and behaviors each partner brings to the relationship, such as psychopathology or personality traits. The next level incorporates the relationship risk factors associated with aggression, including characteristics such as conflict, jealousy, attachment styles, and satisfaction (Capaldi et al., 2012). The DDS perspective emphasizes that to understand the risk for dating aggression, the effect of both partners’ risk factors on their own and their partner’s aggression must be examined. The perspective also posits that interactions between the individual and relationship levels can occur (Capaldi et al., 2012; Kim & Capaldi, 2004; Whitaker et al., 2010). One statistical approach that allows researchers to examine both

partners’ risk factors and the associations with dating aggression is the Actor Partner Interdependence Model (APIM; Kenny, 1996). In APIM, actor effects determine how much each individual’s psycho- pathology influences their own physical dating aggression, and partner effects reflect associations between an individual’s psycho- pathology and the partner’s physical dating aggression. Actor effects are measured while controlling for partner effects, and vice versa. Actor partner interactions take into account the interplay between the two romantic partners’ risk and assess whether combi- nations of partners’ risk factors result in a greater risk (Figure 1). Finally, additional moderators can be incorporated into APIM as well (Garcia et al., 2015).

Psychopathology as a Risk Factor

Two domains of psychopathology associated with physical dating aggression are externalizing and internalizing symptoms. First, a number of externalizing symptoms, including delinquency, antiso- cial behaviors, conduct problems, and general aggression are known risk factors for young adult dating aggression (Andrews et al., 2000; Ehrensaft et al., 2003). Across dyadic studies, discrepant patterns have been found. Among adult cohabiting couples, male and female antisocial behaviors predict female physical aggression but not male aggression (Marshall et al., 2011). In contrast, among young adult

couples in which male partners were at high risk for delinquency, male and female antisocial behaviors predict male physical aggres- sion, whereas only female antisocial behaviors predict female aggression (Kim & Capaldi, 2004). Second, internalizing symptoms are associated with greater reactivity, irritability, withdrawal, nega- tivity, and perceived alienation, which may underlie an increased risk for aggression (McCabe & Gotlib, 1993). Dyadic studies including adult couples highlight significant partner effects, such that males’ depressive symptoms predict female aggression and females’ depressive symptoms predict male aggression (Marshall et al., 2011). Among young adult couples, only females’ depres- sive symptoms predict male and female aggression concurrently (Kim & Capaldi, 2004).

Moreover, young adults and their partners tend to have similar levels of psychopathology, a phenomenon known as homophily (Kim & Capaldi, 2004; Merikangas, 1982). Homophily can occur by either assortative mating, in which individuals select partners with similar levels of psychopathology, or socialization, in which part- ners exert an influence on one another. Such pairing can increase the number of couples composed of two individuals who each have a higher risk for dating aggression. Furthermore, interactions between the partners’ psychopathology can occur, resulting in higher risk for aggression. Existing work among young adults has found additive effects of each partner’s psychopathology on aggression but may have been underpowered to find interactions between partners (Kim & Capaldi, 2004).

To date, dyadic studies have focused on psychopathology and physical dating aggression exclusively among adult couples that were cohabiting or among high-risk young adult couples that had lasting relationships (Kim & Capaldi, 2004; Marshall et al., 2011). During young adulthood, dating aggression often culminates in breakups, on-again-off-again dynamics, and relationship instability (Halpern-Meekin et al., 2013; Rhoades et al., 2011). It will there- fore be informative to supplement existing work by examining patterns across a range of young adult relationships. Additionally, by testing the conjoint influence of both partners’ psychopathology in an adequately powered sample, the field will have a better understanding of whether certain young adult couples may be at greater risk.

Relationship Characteristics as Moderators

Although psychopathology is a relatively stable characteristic (Ferdinand et al., 1995), aggression fluctuates within relationships. Fifteen percent of individuals who did not initially engage in physical dating aggression became aggressive a year and a half later within that relationship, whereas around half of individuals who were aggressive remained aggressive over time (O’Leary et al., 1989). As such, psychopathology’s associations with dating aggres- sion may be exacerbated by the presence of contextual variables such as relationship characteristics, which vary in young adult relationships (Ferdinand et al., 1995; Karney & Bradbury, 1995).

Notably, the Vulnerability Stress Adaptation model posits that individuals with vulnerabilities such as psychopathology who also experience stressful relationships are most likely to have poor relationship outcomes (Karney & Bradbury, 1995; Marshall et al., 2011). The intersection of multiple risk factors could cause a tipping point in which aggression becomes more likely (Foran & O’Leary, 2008). To the best of our knowledge, only one study has examined

Figure 1 The Actor-Partner Interdependence Model (APIM)

Note. Paths labeled a indicate actor effects and paths labeled p indicate partner effects. Paths label axp reflect actor partner interactions. Double- headed arrows represented correlated variables. e1 and e2 represent residual (explained) portion of perpetration score.

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both individual and relationship risk factors. Woodin et al. (2013) found that lower perceived relationship bond interacted with depres- sion to predict dating aggression among college couples; however, existing work has not examined additional relationship risk factors, explored the interaction with both internalizing and externalizing symptoms, or used a dyadic approach. By examining the moderating effect of relationship characteristics, the field can obtain a better understanding of the roles of both individual and relationship risk factors and identify potential targets for prevention and intervention.

The Present Study

Existing work has typically examined risk factors for physical dating aggression by focusing on only one partner; about 5% of studies have examined risk factors among couples (Capaldi et al., 2012). In a prior study (Lantagne & Furman, 2020), we used a dyadic approach to examine the relationship level risk factors from the Dynamic Developmental Systems theory and found that rela- tionship characteristics had main effects on dating aggression. Specifically, our findings demonstrated that both partners’ anxious relational styles and jealousy predicted male and female aggression; female satisfaction and female negative interactions predicted male and female aggression, and each individual’s avoidant style pre- dicted their partner’s aggression. The present study used this same dyadic sample as our prior study

to further contribute to the limited dyadic work on risk factors for dating aggression by first examining a separate level of risk factors from the Dynamic Developmental Systems theory—the individual level. We used APIMs to determine associations between each romantic partner’s externalizing and internalizing symptoms, as well as interactions between partners’ psychopathology, in predict- ing young adult physical dating aggression. We then applied an innovative statistical technique, the Actor Partner Interdependence Moderation Model (APIMoM) to determine whether interactions can occur across levels of risk factors. Specifically, we examined the moderating effect of relationship characteristics on the links between psychopathology and aggression within couples. The present study extends our prior work and other existing work

in several important directions. First, a dyadic approach furthers our understanding of a known risk factor by determining the unique and conjoint influence of both partners’ psychopathology on young adult dating aggression. The present study also extends existing work on psychopathology by examining whether homophily occurs and whether there are interactions between both partners’ psycho- pathology, which could place some couples at particularly high risk. Additionally, by using a dyadic approach to examine individual risk factors for dating aggression, we determine the utility, and therefore the generalizability, of such an approach across a variety of risk factors and multiple levels of risk. Finally, the present study extends existing dyadic models by incorporating additional variables as moderators for risk factors for dating aggression. An examination of such moderation enables us to obtain a more nuanced conceptu- alization of the role of psychopathology as a risk factor by helping us to understand whether the effects of psychopathology on dating aggression have a differing association depending upon the presence of relationship risk factors. This could lend support to existing theories that posit that there can be an interplay between levels of risk factors for aggression.

Hypotheses

Hypotheses included that homophily would occur, such that individuals would pair with partners who had similar levels of psychopathology (Hypothesis 1). We hypothesized that higher physical dating aggression would be associated with higher levels of an individual’s externalizing symptoms (Hypothesis 2; “a” or actor path in Figure 1) and their partner’s externalizing symptoms Hypothesis 3; “p”or partner path in Figure 1). Parallel hypotheses were posited for internalizing symptoms (Hypothesis 4 & Hypoth- esis 5). We anticipated female and male psychopathology would interact to predict physical dating aggression above and beyond the main effects of each individual’s psychopathology (Hypothesis 6; “axp” or actor partner interaction path in Figure 1). Moderation effects were also expected, such that associations between psycho- pathology and aggression would be strongest when partners expe- rienced both elevated psychopathology and stressful relationship characteristics (Hypothesis 7, high psychopathology × high nega- tive interactions; Hypothesis 8, high psychopathology × high jealousy; Hypothesis 9, high psychopathology × high anxious styles; Hypothesis 10, high psychopathology × high avoidant styles; Hypothesis 11, high psychopathology × low satisfaction, “X1M1” and “X2M2” paths in Figure 2).

Method

Participants

The participants included in this study and our prior dyadic study (Lantagne & Furman, 2020) were a dyadic subsample drawn from a larger longitudinal study examining the role of adolescent and young adult interpersonal relationships on psychosocial adjustment (Project STAR; see Furman et al., 2009). Two hundred 10th graders (100 females) were recruited from a Western metropolitan area in the United States. To obtain a diverse sample, letters were sent to families across 36 zip codes of ethnically diverse neighborhoods and brochures were distributed to students enrolled in three high schools Interested families were contacted and compensated $25 to hear a description of the project, with the goal of selecting a quota sample with a distribution of racial and ethnic groups that approximated that of the U.S. and had equal rates of males and females. As many families were contacted who did not have a 10th grader, an ascertainment rate could not be determined. 85.5% of the families that heard a description of the project expressed interest and participated in the Wave 1 assessment. In Wave 1, scores for the overall sample were compared to comparable national norms of representative samples for eleven measures of adjustment. Our sample was more likely to have tried marijuana (54% vs. 40%); otherwise, sample scores did not differ from national scores on the other 11 measures, including frequency of marijuana usage (see Furman et al., 2009).

Procedure and Selection of Dyadic Sample

The dyadic sample from Lantagne & Furman (2020) was used in the present study. Participants were eligible to invite their romantic partners to participate in our study if the romantic relationship was currently three months or longer. 75.7% of the eligible partners participated (N = 293 of 387). Independent samples t tests were used to assess for differences between the participants whose partner

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participated and those whose partner did not. Those whose partner participated reported more committed relationships, t(387) = 4.37, p = .01 and more dating aggression perpetration and victimization, t(387) = 2.14, p = .01 & t(387) = 2.90, p = .01, respectively. There were no differences in internalizing and externalizing symptoms. The dyadic sample was drawn from the first wave during young

adulthood (Waves 5–8) in which the participant had a romantic partner complete questionnaires. Data were reorganized into scores for males and females and only heterosexual dating couples were included to allow APIM analyses of distinguishable dyads. Ten LGBQ couples were excluded; additionally, seven married couples were excluded. The resulting sample consisted of 127 couples (participants’ M age = 22.04 yrs., range = 19.54—26.87 yrs; average relationship length = 17.77 months, SD = 16.42); 31.5% of the dyads were cohabiting/engaged. 74% were White, non- Hispanic, 7.7% African American, 1.85% Asian American, 12.1% Hispanic,0.7% Native American, and 3.65% biracial. The local Institutional Review Board approved the study. U.S. Department of Health and Human Services Certificates of Confidentiality pro- tected the confidentiality of the data.

Measure

Psychopathology

Each partner completed 35 externalizing and 39 internalizing items from the Adult Self-Report (Achenbach, 1997); the external- izing scale included items about aggressive behavior, rule-breaking, and intrusiveness, whereas the internalizing scale included items about anxiety/depression, withdrawal, and somatic complaints.

Participants rated how descriptive each item was on a 3-point scale ranging from 0 = not true of me to 2 = very true or often true of me. Higher scores indicated greater symptomatology. The ASR has acceptable internal reliability and construct validity (mean Cron- bach’s α= .82 for externalizing & α = .88 for internalizing).

Relationship Characteristics

The following relationship characteristics were included in the present study as moderators. These characteristics were selected from the prior dyadic study by Lantagne & Furman (2020) because they were the theoretically driven measures in our data set that allowed us to examine the constructs of interest and to permit comparisons across the two studies.

Negative Interactions. Each partner completed the Network of Relationships Inventory: Behavioral Systems Version (NRI; Furman & Buhrmester, 2009). Six items assessed negative inter- actions in the romantic relationship, including conflict, criticism, and antagonism (e.g., “How much do you and this person get on each other’s nerves?”). Ratings were made on a 5-point Likert scale ranging from 1 = Strongly Disagree to 5 = Strongly Agree. Items were averaged to create a total score; higher scores represented greater negative interactions; M Cronbach’s α = .91. Validational evidence is presented in Furman & Buhrmester (2009).

Relationship Satisfaction. A version of Norton’s (1983) Qual- ity of Marriage Index was adapted to assess young adult relationship satisfaction. A sample item was “My romantic partner and I have a good relationship.” The measure consists of five 7-point Likert items (1 = Strongly Disagree/Not at all true to 7 = Strongly Agree/Very true), and one 10-point Likert item that assessed overall satisfaction

Figure 2 Actor Partner Interdependence Moderation Model (APIMoMs) for Interaction Between Externalizing Symptoms and Relationship Satisfaction on Dating Aggression

Male Physical Dating Aggression (Y1)

Female Physical Dating Aggression (Y2)

Male Externalizing Symptoms (X1)

Female Externalizing Symptoms (X2)

Male Relationship Satisfaction (M1)

Female Relationship Satisfaction (M2)

Female Externalizing x Female Satisfaction (X2M2)

Male Externalizing x Male Satisfaction (X1M1)

e1

e2

Note. Double-headed arrows represent correlations; e1 and e2 represent residual portion of dating aggression.

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with relationship (1 = Extremely Unhappy, 10 = Extremely Happy). Scores were transformed to a 5-point scale so all items had the same range and averaged to derive a total score, with higher scores indicating greater satisfaction; M Cronbach’s α = .95. The measure has acceptable internal reliability and construct validity (Baxter & Bullis, 1986). Jealousy. Pfeiffer and Wong’s (1989) Multidimensional Jeal-

ousy Scale assessed emotional, cognitive, and behavioral jealousy. Each partner used a 5-point Likert scale (1 = Never to 5 = All the time) to rate 24 items; a sample item was “I suspect my romantic partner may be attracted to someone else”; M Cronbach’s α = .89. The scale has good convergent and discriminant validity (Pfeiffer & Wong, 1989). Relational Styles. The Behavioral Systems Questionnaire as-

sessed romantic relational styles (BSQ; Furman & Wehner, 1999). Each partner used a 5-point Likert scale to rate agreement with 27 statements ranging from 1 = Strongly Disagree to 5 = Strongly Agree. Two scores were calculated based on previous factor analy- ses (see Jones & Furman, 2011): (a) an avoidant score, consisting of the average of 9 dismissing items (e.g., I do not ask my romantic partner to comfort me) and 9 secure items (reverse scored) and (b) an anxious score, consisting of the average of 9 preoccupied items (e.g., I am afraid that my romantic partner thinks I am too dependent). The scales have acceptable internal reliability (M Cronbach’s α = .89 for avoidant & .84 for anxious styles) and validity (Furman et al., 2002).

Physical Dating Aggression

Participants reported on their own and their partner’s use of physical aggression using Simon and Furman’s (2010) adaptation of Kurdeck’s Conflict Resolution Style Inventory (Kurdeck, 1994). Four items assessed physical aggression (Forcefully pushing or shoving, Slapping or hitting, Throwing items that could hurt, and Kicking, biting or hair pulling). The items were similar in content to items on the Conflict Tactics Scale (Straus et al., 1996), but used the CRSI’s 7-point format (ranging from 1=never; 7= always) to assess how often each partner engaged in such aggression in arguments during the past year (M α = .82 for perpetration & .91 for victimi- zation). Higher scores indicated greater frequency of dating aggres- sion. Both partners’ reports were used to yield male physical dating aggression (male self-report & partner report of females, r = .56, p = .001) and female aggression (female self-report & partner report of males, r = .35, p = .001). This measure has demonstrated construct validity over several studies (Collibee et al., 2018; Collibee & Furman, 2016; Novak & Furman, 2016; Simon & Furman, 2010) and finds similar rates of dating aggression as other measures (e.g., 46% of adolescents experienced victimization and 52% perpetration; see Novak & Furman, 2016).

Data Analysis Plan

All variables were examined to ensure acceptable skew and kurtosis (Behrens, 1997), and outliers were Winsorized. Hypotheses were tested using MPlus 8.0 (Muthén & Muthén, 2012). Per guidelines around standardizing dyadic data in SEM (Kenny et al., 2006), predictor and outcome variables were standardized by grand mean centering across the entire sample and dividing by the standard deviation across entire sample. APIMoMs were

conducted to determine whether the effects of an individual’s psychopathology on their own and their partner’s physical dating aggression is stronger depending on the nature of the relationship.

Power was assessed using APIM Power R (Ackerman & Kenny, 2016). Given medium-size effects (β = .30) and an alpha of .05, the power for internalizing and externalizing with 127 dyads is .95 and .96. Power exceeded .80 for β’s of .25 or greater. APIM Power R does not assess interaction effects, but Kenny & Cook (1999) noted that the sample size requirements for multiple regression analyses apply to APIMs estimated via SEM. Thus, we examined the power of interaction effects using Cohen’s (1988) calculations for multiple regression. The estimates of power for the interactions were virtually identical to those for the main effects.

Results

Descriptive statistics and bivariate correlations are presented in Table 1. 24.4% of couples endorsed male physical perpetration and 34.6% endorsed female perpetration. Rates of female and male physical dating aggression were highly correlated, r = .75, p < .001. Regarding clinical cutoffs, 11.8% of our sample were in the clinical range for internalizing symptoms and 9.3% were in the clinical range for externalizing symptoms. Males reported higher levels of externalizing symptoms than females, t(123) = 1.99, p = .04; females reported higher levels of internalizing symptoms than males, t(123) = −3.05, p = .003. Evidence of homophily was found (Hypothesis 1): male and female externalizing symptoms were correlated (r = .28, p < .01) and male and female internaliz- ing symptoms were also correlated (r = .23, p = .02).

Psychopathology

Overall, higher psychopathology was associated with higher physical dating aggression. Female externalizing symptoms had an actor effect on female aggression, and male externalizing symp- toms had an actor effect on male aggression (Hypothesis 2; β = .25, p < .01 & β = .33, p = .001, respectively). Male externalizing symptoms had a partner effect on female aggression as well (Hypothesis 3; β = .40, p < .001). Additionally, male internalizing symptoms had an actor effect on male aggression, and female internalizing symptoms had an actor effect on female aggression (Hypothesis 4; β = .28, p = .001 & β = .21, p = .03, respectively). Both male and female internalizing symptoms had partner effects (Hypothesis 5; β = .39, p < .001 & β = .16, p = .05, respectively).

Regarding actor partner interactions, the product terms of male by female externalizing or internalizing symptoms were then exam- ined. Significant interactions were interpreted using Preacher et al.’s (2006) computational tools. The estimated effect of one individual’s psychopathology on their dating aggression was plotted at three levels of their partner’s psychopathology: low levels (one standard deviation below the mean), average levels (at the mean), and high levels (one standard deviation above the mean). Consistent with our hypothesis (Hypothesis 6), male and female externalizing symptoms interacted to predict both male (β = .14, p = .04) and female aggression (β = .25, p < .001; Figure 3). For couples in which females had average or high externalizing symptoms, male aggres- sion increased as male externalizing symptoms increased, t(121) = 2.94, p < .01 for average female externalizing; t(121) = 3.81, p < .001 for high). Similarly, for couples in which males had average

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or high externalizing symptoms, female aggression increased as female externalizing symptoms increased, t(121) = 3.21, p = .002 for aver- age male externalizing; t(121) = 4.46, p < .001 for high male exter- nalizing). Contrary to hypotheses, there were no interactions between male and female internalizing symptoms.

Relationship Characteristics as Moderators

Relationship characteristics were then examined as moderators of associations between psychopathology and dating aggression.

Product interaction terms were created as follows: (1) female externalizing (or internalizing) symptoms by female relationship characteristic and (2) male externalizing (or internalizing) symp- toms by male relationship characteristic (Figure 2). All product interaction terms were entered after main effects to avoid the limitations of interpreting conditional main effects (Cohen et al., 2003; Little, 2013). Main effects of relationship characteristics were reported in Lantagne and Furman (2020) and thus not presented here. Due to the number of interaction effects found, only significant simple slopes are reported in the text; however, nonsignificant simple slopes are presented as supplemental material.

Female Externalizing Symptoms

Female satisfaction interacted with female externalizing symp- toms to predict female aggression (see Figure 2, β = −.18, p = .02; Hypothesis 11), and female jealousy interacted with female exter- nalizing symptoms to predict female aggression (β = .22, p = .01; Hypothesis 8). As female externalizing symptoms increased, female aggression increased for females with low satisfaction, t(115) = 2.76, p = .01. As female externalizing symptoms increased, female aggression increased for females with high jealousy, t(115) = 2.69, p = .01.

Male Externalizing Symptoms

Male satisfaction interacted with male externalizing symptoms to predict female aggression (see Figure 2, β = −.22, p = .002; Hypothesis 11), and male jealousy interacted with male externaliz- ing symptoms to predict female aggression (β = .18, p = .003; Hypothesis 8). Male anxious styles and negative interactions inter- acted with male externalizing symptoms to predict female and male aggression (β = .16, p = .03 for male anxious styles to male aggression; β = .26, p = .001 for male anxious styles to female aggression; β = .17, p = .007 for male negative interactions

Table 1 Means and Standard Deviations of Psychopathology, and Bivariate Correlations of Psychopathology With Relationship Characteristics and Dating Aggression

Variables 1 2 3 4

Male internalizing symptoms (1) — Female internalizing symptoms (2) .23* — Male externalizing symptoms (3) .63** .24** — Female externalizing symptoms (4) .25** .72** .28** — Male negative interactions (5) .29** .25** .37** .40** Female negative interactions (6) .25** .51** .31** .58** Male satisfaction (7) −.33** −.30** −.27** −.35** Female satisfaction (8) −.29** −.38** −.21* −.40** Male jealousy (9) .37** .11 .31** .21* Female jealousy (10) .18* .44** .26** .49** Male anxious styles (11) .46** .23* .50** .32** Female anxious styles (12) .26** .52** .23* .41** Male avoidant styles (13) .23** .18* .28** .14 Female avoidant styles (14) .11 .15 .14 .15 Male dating aggression (15) .34** .25** .33** .22* Female dating aggression (16) .38** .27** .46** .37** Mean (SD in parentheses) 0.28 (0.24) 0.38 (0.26) 0.33 (0.22) 0.28 (0.22)

Note. The correlations were conducted on the measures prior to standardizing them for the APIM analyses. Please see Lantagne and Furman (2020) for correlations among relationship characteristics and dating aggression. † p < .10. * p < .05. ** p < .01. *** p < .001.

Figure 3 Actor by Partner Interactions Between Male and Female External- izing Symptoms on Male Physical Dating Aggression

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to male aggression; β = .25, p < .001 for male negative inter- actions to female aggression; Hypothesis 9 & Hypothesis 7, respectively). First, as male externalizing symptoms increased, female aggres-

sion increased for males with low or average satisfaction (low t(115) = 5.25, p < .0001 & average t(115) = 4.24, p < .0001). Next, as male externalizing symptoms increased, female aggression increased for males with high or average levels of jealousy (high t(115) = 5.28, p = .0001 & average t(115) = 4.14, p < .0001). For anxious styles, as male externalizing symptoms increased,

female aggression increased for males with high or average anxious styles, t(115) = 4.21, p = .0001 for high & t(115) = 2.58, p = .01 for average. Similar patterns were found for predicting male aggres- sion: as male externalizing symptoms increased, male aggression increased for males with high anxious styles, t(115) = 2.63, p = .01. Finally, as males’ externalizing symptoms increased, female aggression also increased for males with high or average negative interactions, t(115) = 4.95, p <.001 for high & t(115) = 3.30, p < .001 for average. Regarding male physical dating aggres- sion, as males’ externalizing symptoms increased, male aggression increased for males with high negative interactions, t(115) = 2.92, p = .004.

Female Internalizing Symptoms

Female satisfaction and avoidant relational styles interacted with female internalizing symptoms to predict male dating aggression (β = −0.17, p = .008 for satisfaction & β = .23, p = .004 for avoidant styles; Hypothesis 11 & Hypothesis 10 respectively). As female internalizing symptoms increased, male aggression increased for females with low satisfaction, t(115) = 2.47, p = .02. Next, as female internalizing symptoms increased, male aggression increased for females with high or average avoidant styles, t(115) = 4.20, p < .001 for high & t(115) = 2.33, p =.02 for average.

Male Internalizing Symptoms

Male satisfaction and anxious relational styles interacted with male internalizing symptoms to predict female aggression (β = −.30, p = .001 for satisfaction & β = .20, p = .01 for anxious relational styles; Hypothesis 11 & Hypothesis 9 respectively). Male negative interactions interacted with male internalizing symp- toms to predict female and male aggression (β = .30, p < .001 for female aggression & β = .16, p = .01 for male aggression; Hypothesis 7). First, as female internalizing symptoms increased, female

aggression increased for males with low or average satisfaction, t(115) = 3.86, p = .001 for low & t(115) = 2.25, p = .03 for average. Next, as male internalizing symptoms increased, female aggression increased for males with high anxious styles, t(115) = 2.34, p = .02. Finally, as male internalizing symptoms increased, female aggression increased for males with high or average negative interactions, t(115) = 4.71, p = .001 for high & t(115) = 2.29, p < .02 for average. Similarly, as male internalizing symptoms increased, male aggression increased for males with high reports of negative interactions, t(115) = 3.12, p = .002.

Discussion

The present study contributes to the limited work examining associations between psychopathology and dating aggression in young adult couples. Each partner’s psychopathology was associ- ated with their own and their partner’s aggression. Males and females externalizing symptoms interacted to predict both partners’ aggression, placing certain couples at greater risk. Additionally, relationship characteristics interacted with externalizing symptoms to predict female aggression, and with internalizing symptoms to predict partner aggression. Present findings add merit to conceptu- alizing the risk for young adult dating aggression as dyadic, depending on both partners’ psychopathology and the nature of the relationship.

Main Effects of Psychopathology and Actor by Partner Interactions

One goal of the present study was to extend the limited dyadic work examining young adult psychopathology and physical dating aggression. Present findings are largely consistent with existing work on externalizing symptoms (Kim & Capaldi, 2004) and with our second and third hypotheses: males’ externalizing symptoms predicted male aggression and both partners’ externalizing symp- toms predicted female aggression. Whereas existing work has shown that only females’ depressive symptoms predict male aggres- sion (Kim & Capaldi, 2004), present findings were also consistent with our fourth and fifth hypotheses and indicated that both partners’ internalizing symptoms are associated with male and female aggres- sion. Prior research has focused on relationships of high-risk young adult males; the present study may have found different patterns due to greater variability in psychopathology within our community sample. Despite differences, overall findings demonstrate that both partners’ psychopathology are risk factors for male and female physical dating aggression.

Regarding gender, past work has also found that male internaliz- ing symptoms are less influential in predicting dating aggression (Kim & Capaldi, 2004). Notably, the present study demonstrated that both male and female internalizing symptoms predict each partner’s aggression. In fact, both partners’ externalizing symptoms also uniquely predicted male and female aggression, highlighting the importance of a dyadic approach. The present study may have uncovered effects for both males’ and females’ psychopathology because we examined each individual’s risk factor on aggression while controlling for the partner’s effect.

Moreover, consistent with our sixth hypothesis regarding actor partner interactions, rates of aggression were highest when homo- phily occurred and both partners had high levels of externalizing symptoms. Hostile and aggressive patterns of interacting may be more prevalent and prolonged for these couples, as both partners could have lower impulse control and emotion regulation abilities (Capaldi & Kim, 2007; Keenan-Miller et al., 2007). In contrast, when one partner had low levels of externalizing symptoms, the other partner’s level of symptoms was not predictive of aggression. For such couples, the effects of the partner’s externalizing symp- toms on aggression were mitigated. Findings are consistent with existing work, which has found that if an individual pair with a normative partner, adaptive functioning improves, whereas if an

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individual couple with a deviant partner, maladaptive functioning continues (Pickles & Rutter, 1991; Quinton et al., 1993).

Interactions Between Psychopathology and Relationship Characteristics

The present study then examined relationship characteristics as moderators. Male satisfaction and negative interactions interacted with externalizing symptoms to predict male aggression. Female satisfaction and jealousy interacted with externalizing symptoms to predict female aggression. The risk for aggression is high for those with externalizing symptoms; when combined with low satisfaction, high conflict, or high jealousy, it may reach a tipping point where the impulse exceeds inhibition (Reyes et al., 2015). Additionally, con- sistent with our hypotheses on the moderating role of relationship characteristics, male negative interactions, jealousy, anxious styles, and satisfaction interacted with externalizing symptoms to predict female aggression (Hypothesis 7, Hypothesis 8, Hypothesis 9, & Hypothesis 1, respectively). As discussed in our prior dyadic study of this sample (Lantagne & Furman, 2020), such characteristics may be indices of relationship insecurity. Relationships in which males experience both higher insecurity and externalizing behaviors may cultivate a particularly taxing interpersonal context. Such relation- ship dynamics may also challenge the use of effective communica- tion strategies within the dyad (Capaldi et al., 2005). Females have reported that one of the most pervasive explanations for their own aggression is to show anger, which may be salient in such relation- ships (O’Keefe, 1997). Findings for internalizing symptoms were consistent with exist-

ing literature (Longmore et al., 2014), and showed that internalizing symptoms predicted partner aggression, an association that was most pronounced in the presence of negative relationship character- istics. Female avoidant styles and low satisfaction interacted with internalizing symptoms to predict male aggression (Hypothesis 10 & Hypothesis 11, respectively). Male negative interactions, jealousy, anxious styles, and low levels of satisfaction interacted with internalizing symptoms to predict female aggression (Hypothesis 7, Hypothesis 8, Hypothesis 9, & Hypothesis 11, respectively). Inter- nalizing symptoms may impede an individual’s sense of self- efficacy and self-worth, increasing the odds of entering or remaining in an unhealthy relationship (Cleveland et al., 2003; Vezina & Hebert, 2007). Studies suggest that individuals who feel depressed often stay in poor relationships to avoid losing an interpersonal connection (Vicary et al., 1995). Additionally, internalizing symp- toms can impair interpersonal competence (Longmore et al., 2014; Stroud et al., 2008). Indeed, individuals with high internalizing symptoms often demonstrate poor problem-solving in romantic relationships (Vujeva & Furman, 2011). Individuals with poor communication skills or problem-solving abilities, who are also in a romantic relationship with negative characteristics may also experience greater escalation in conflict, resulting in dating aggres- sion (Riggs & O’Leary, 1989). Globally, for couples in which one partner has high internalizing symptoms, romantic interactions are rated by objective outsiders as displaying greater hostility, irritabil- ity, negative affect, and negative communication (McCabe & Gotlib, 1993). Thus, the impact of psychopathology on relationship interactions, when combined with the presence of a negative relationship may result in greater risk.

Across internalizing and externalizing symptoms, seven signifi- cant interactions between relationship characteristics and psycho- pathology were found for males and four for females. Disinhibitory psychopathology has been found to be a unique risk factor for males (Ehrensaft et al., 2003), whereas other factors were uniquely pre- dictive for females. It may be that for males, the combination of psychopathology and relationship characteristics culminates in dis- inhibition, whereas other processes are at play for females. Notably, across genders, the interplay between characteristics and psychopa- thology suggests that not all individuals who experience psychopa- thology are involved in aggressive relationships. Rather, consistent with a theory of multifinality (Cicchetti & Rogosch, 1996), complex combinations of male and female psychopathology and relationship characteristics culminate in both partners’ aggression.

In sum, the interactions between individual and relationship risk factors highlight the interplay across multiple levels of the dynamic developmental systems theory (Capaldi et al., 2012). In a previous study of this same sample (Lantagne & Furman, 2020), we identified a number of relationship characteristics that were dyadic risk factors; here we found internalizing and externalizing symptoms were additional dyadic risk factors. However, the risk for dating aggres- sion is not simply a linear or additive risk: relationship character- istics appear to work synergistically with psychopathology (Moffitt et al., 2001) such that individuals who have high levels of psycho- pathology and who are in stressful relationships are at greater risk for aggression. Present findings are consistent with theories on multiple risk factors, which posit that the presence of any single risk factor for dating aggression can be exacerbated by the presence of additional risk factors (Kim & Capaldi, 2004). Finally, our findings also add merit to conceptualizing risk for dating aggression as dynamic (Collibee & Furman, 2016). The majority of existing studies have examined the risk for dating aggression as an invariant and static factor rather than as a risk that changes over time and across partners. Notably, the degree of current psychopathology and relationship characteristics can vary between and within young adult relationships, underscoring the dynamic nature of risk.

Limitations

The present study had several limitations. First, it was cross- sectional; longitudinal research examining dyadic models of dating aggression over time is needed to test the temporal order of the associations between psychopathology and aggression. Externaliz- ing and internalizing symptoms also tend to co-occur, and indivi- duals who experience both often have the poorest overall adjustment (Capaldi & Stoolmiller, 1999). While participant and partner reports of dating aggression were included, we only incorporated self- reports of predictors. Additionally, our measure of dating aggression assesses a range of conflict tactics but has been used less often in studies of dating aggression. It will be important to replicate the actor and partner effects with other measures such as the Conflict Tactics Scale 2 (Straus et al., 1996).

We conducted a number of statistical analyses and thus, it is likely that some Type I errors may have occurred. Statisticians have persuasively argued that corrections for Type I error do not solve the problem and, in fact, present other problems (Garamszegi, 2006; Nakagawa, 2004; Rothman, 1990; Saville, 1990). Thomas (1998) argues that simply describing which tests of significance have been performed and why is the best way to manage multiple comparisons.

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In that respect, 24 of our 52 tests of actor, partner, and interaction effects were significant. Finally, because the present study drew from a community

sample, there is greater generalizability of our findings than much existing work. However, our sample consisted of early adult couples, and it will be important to replicate findings across adolescence and adulthood to determine developmental differences in associations. Additionally, our study exclusively included het- erosexual couples. Dating aggression is also prevalent among LGBQ couples and it will be imperative to extend dyadic ap- proaches to LGBQ couples.

Research Implications

Findings from the present study lend additional support to the utility of using a dyadic approach to more fully understand the complex relationship among risk factors and dating aggression in young adult couples. Not only were actor and partner effects found, but actor partner interactions were found. The effects of high levels of externalizing symptoms were mitigated when the partner had low levels. Results also demonstrated that the combination of psycho- pathology and poor relationship characteristics substantially increased the likelihood of dating aggression. Our findings under- score that dating aggression should be conceptualized as a multi- determined behavior (Capaldi et al., 2012; Foran & O’Leary, 2008); future studies should expand analyses to include an array of pre- dictors for both male and female dating aggression, as well as the interplay among variables, to further our understanding of this complex phenomenon.

Clinical Implications

Present findings imply that there are several critical points of intervention. One point would be to focus on decreasing psychopa- thology; studies indicate that individuals with lower levels of depression are less likely to be victimized (Halpern et al., 2009). Alternatively, as different patterns of relationship characteristics moderated internalizing and externalizing symptoms, relationship prevention programs that target multiple risk factors may be most effective (Longmore et al., 2014). Finally, findings could shift the focus of existing prevention programs from individuals to young couples (Capaldi & Kim, 2007). Programs may be most effective if targeting both partners’ externalizing symptoms, as present findings indicate risk for dating aggression is higher for couples in which both partners have elevated symptoms.

Conclusion

Taken together, the current study makes several notable con- tributions to the field on young adult physical dating aggression. Findings highlight that both partners’ psychopathology is risk factor. The interplay between partners’ externalizing symptoms underscores that when couples consist of two individuals with high externalizing symptoms, the risk for dating aggression in- creases. Results also demonstrate that psychopathology does not inevitably lead to dating aggression; rather, the co-occurrence of individual and relationship characteristics shapes risk. In sum, by considering combinations of risk factors among couples, researchers may be better able to predict who is at greatest risk for physical

dating aggression, with which partners, and in which relationships (Collibee & Furman, 2016; Reese-Weber & Johnson, 2013).

References

Achenbach, T. M. (1997). Manual for the Young Adult Self-Report & Young Adult Behavior Checklist. University of Vermont Department of Psychiatry.

Ackerman, R. A., & Kenny, D. A. (2016, December). APIMPower: An interactive tool for Actor-Partner Interdependence Model power analysis [Computer software]. https://robert-a-ackerman.shinyapps.io/apimpower/

Andrews, J. A., Foster, S. L., Capaldi, D., & Hops, H. (2000). Adolescent and family predictors of physical aggression, communication, and satis- faction in young adult couples: A prospective analysis. Journal of Consulting and Clinical Psychology, 68(2), 195–208. https://doi.org/10 .1037/0022-006X.68.2.195

Baxter, L. A., & Bullis, C. (1986). Turning points in developing romantic relationships. Human Communication Research, 12(4), 469–493. https:// doi.org/10.1111/j.1468-2958.1986.tb00088.x

Behrens, J. T. (1997). Principles and procedures of exploratory data analysis. Psychological Methods, 2(2), 131–160. https://doi.org/10.1037/1082- 989X.2.2.131

Capaldi, D. M., & Kim, H. K. (2007). Typological approaches to violence in couples: A critique and alternative conceptual approach. Clinical Psychol- ogy Review, 27(3), 253–265. https://doi.org/10.1016/j.cpr.2006.09.001

Capaldi, D. M., Knoble, N. B., Shortt, J. W., & Kim, H. K. (2012). A systematic review of risk factors for intimate partner violence. Partner Abuse, 3(2), 231–280. https://doi.org/10.1891/1946-6560.3.2.231

Capaldi, D. M., Shortt, J. W., & Kim, H. K. (2005). A lifespan developmental systems perspective on aggression toward a partner. In W. M. Pinsof & J. L. Lebow (Eds.), Family psychology: Art of the science (pp. 141–167). Oxford University Press.

Capaldi, D. M., & Stoolmiller, M. (1999). Co-occurrence of conduct problems and depressive symptoms in early adolescent boys: III. Predic- tion to young-adult adjustment. Development and Psychopathology, 11(1), 59–84. https://doi.org/10.1017/S0954579499001959

Cicchetti, D., & Rogosch, F. A. (1996). Equifinality and multifinality in developmental psychopathology. Development and Psychopathology, 8(4), 596–600. https://doi.org/10.1017/S0954579400007318

Cleveland, H. H., Herrera, V. M., & Stuewig, J. (2003). Abusive males and abused females in adolescent relationships: Risk factor similarity and dissimilarity and the role of relationship seriousness. Journal of Family Violence, 18, 325–339. https://doi.org/10.1023/A:1026297515314

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum.

Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). Lawrence Erlbaum.

Collibee, C., & Furman, W. (2016). Chronic and acute relational risk factors for dating aggression in adolescence and young adulthood. Journal of Youth and Adolescence, 45, 763–776. https://doi.org/10.1007/s10964- 016-0427-0

Collibee, C., Furman, W., & Shoop, J. (2018). Risky interactions: Relational and developmental moderators of substance use and dating aggression. Journal of Youth and Adolescence, 48, 102–113. https://doi.org/10.1007/ s10964-018-0950-2

Devries, K. M., Mak, J. Y., Bacchus, L. J., Child, J. C., Falder, G., Petzold, M., Astbury, J., & Watts, C. (2013). Intimate partner violence and incident depressive symptoms and suicide attempts: A systematic review longitu- dinal studies. PLoS Medicine, 10(5), Article e1001439. https://doi.org/10 .1371/journal.pmed.1001439

Ehrensaft, M. K., Cohen, P., Brown, J., Smailes, E., Chen, H., & Johnson, J. G. (2003). Intergenerational transmission of partner violence: A 20 year

PSYCHOPATHOLOGY AND AGGRESSION 577

T h is d o cu m en t is co p y ri g ht ed

b y th e A m er ic an

P sy ch o lo g ic al

A ss o ci at io n o r o n e o f it s al li ed

p u b li sh er s.

T h is ar ti cl e is in te nd ed

so le ly

fo r th e p er so n al

u se

o f th e in di v id u al

u se r an d is n o t to

b e d is se m in at ed

b ro ad ly .

prospective study. Journal of Consulting and Clinical Psychology, 71(4), 741–753. https://doi.org/10.1037/0022-006X.71.4.741

Ferdinand, R. F., Verhulst, F. C., & Wiznitzer, M. (1995). Continuity and change of self-reported problem behaviors from adolescence into young adulthood. Journal of the American Academy of Child & Adolescent Psychiatry, 34(5), 680–690. https://doi.org/10.1097/00004583-199505000- 00020

Foran, H. M., & O’Leary, K. D. (2008). Alcohol and intimate partner violence: A meta-analytic review. Clinical Psychology Review, 28(7), 1222–1234. https://doi.org/10.1016/j.cpr.2008.05.001

Furman, W., & Buhrmester, D. (2009). Methods and measures: The network of relationships inventory: Behavioral systems version. International Journal of Behavioral Development, 33(5), 470–478. https://doi.org/10 .1177/0165025409342634

Furman, W., Low, S., & Ho, M. (2009). Romantic experience and psycho- social adjustment in middle adolescence. Journal of Clinical Child and Adolescent Psychology, 38(1), 75–90. https://doi.org/10.1080/ 15374410802575347

Furman, W., Simon, V. A., Shaffer, L., & Bouchey, H. A. (2002). Adoles- cents’ working models and styles for relationships with parents, friends, and romantic partners. Child Development, 73(1), 241–255. https:// doi.org/10.1111/1467-8624.00403

Furman, W., & Wehner, E. A. (1999). The behavioral systems questionnaire- revised [Unpublished measure]. University of Denver.

Garamszegi, L. Z. (2006). Comparing effect sizes across variables: Gener- alization without the need for Bonferroni correction. Behavioral Ecology, 17(4), 682–687. https://doi.org/10.1093/beheco/ark005

Garcia, R. L., Kenny, D. A., & Ledermann, T. (2015). Moderation in the actor-partner interdependence model. Personal Relationships, 22(1), 8– 29. https://doi.org/10.1111/pere.12060

Halpern, C. T., Oslak, S. G., Young, M. L., Martin, S. L., & Kupper, L. L. (2001). Partner violence among adolescents in opposite-sex romantic relationships: Findings from the National Longitudinal Study of Adoles- cent Health. American Journal of Public Health, 91(10), 1679–1685. https://doi.org/10.2105/AJPH.91.10.1679

Halpern, C. T., Spriggs, A. L., Martin, S. L., & Kupper, L. L. (2009). Patterns of intimate partner violence victimization from adolescence to young adulthood in a nationally representative sample. Journal of Adolescent Health, 45(5), 508–516. https://doi.org/10.1016/j.jadohealth.2009.03.011

Halpern-Meekin, S., Manning, W. D., Giordano, P. C., & Longmore, M. A. (2013). Relationship churning, physical violence, and verbal abuse in young adult relationships. Journal of Marriage and Family, 75(1), 2–12. https://doi.org/10.1111/j.1741-3737.2012.01029.x

Jones, M. C., & Furman, W. (2011). Representations of romantic relation- ships, romantic experience and sexual behavior in adolescence. Personal Relationships, 18(1), 144–164. https://doi.org/10.1111/j.1475-6811.2010 .01291.x

Karney, B. R., & Bradbury, T. N. (1995). The longitudinal course of marital quality and stability: A review of theory, methods, and research. Psycho- logical Bulletin, 118(1), 3–34. https://doi.org/10.1037/0033-2909.118.1.3

Keenan-Miller, D., Hammen, C., & Brennan, P. (2007). Adolescent psycho- social risk factors for severe intimate partner violence in young adulthood. Journal of Consulting and Clinical Psychology, 75(3), 456–463. https:// doi.org/10.1037/0022-006X.75.3.456

Kenny, D. A. (1996). Models of non-interdependence in dyadic research. Journal of Social and Personal Relationships, 13(2), 279–294. https:// doi.org/10.1177/0265407596132007

Kenny, D. A., & Cook, W. (1999). Partner effects in relationship research: Conceptual issues, analytic difficulties, and illustrations. Personal Relationships, 6(4), 433–448. https://doi.org/10.1111/j.1475-6811.1999 .tb00202.x

Kenny, D. A., Kashy, D. A., & Cook, W. L. (2006). Dyadic data analysis. Guilford Press.

Kim, H. K., & Capaldi, D. M. (2004). The association of antisocial behavior and depressive symptoms between partners and risk for aggression in romantic relationships. Journal of Family Psychology, 18(1), 82–96. https://doi.org/10.1037/0893-3200.18.1.82

Kurdeck, L. A. (1994). Conflict resolution styles in gay, lesbian, heterosex- ual nonparent, and heterosexual parent couples. Journal of Marriage and the Family, 56(3), 705–722. https://doi.org/10.2307/352880

Lantagne, A., & Furman, W. (2020). More than the sum of two partners: A dyadic perspective on young adult physical dating aggression. Psychology of Violence, 10(4), 379–389. https://doi.org/10.1037/vio0000267

Little, T. D. (2013). Longitudinal structural equation modeling. Guilford Press.

Longmore, M. A., Manning, W. D., Giordano, P. C., & Copp, J. E. (2014). Intimate partner victimization, poor relationship quality, and depressive symptoms during young adulthood. Social Science Research, 48, 77–89. https://doi.org/10.1016/j.ssresearch.2014.05.006

Marshall, A. D., Jones, D. E., & Feinburg, M. (2011). Enduring vulner- abilities, relationship attributions, and couple conflict: An integrative model of the occurrence and frequency of intimate partner violence. Journal of Family Psychology, 25(5), 709–718. https://doi.org/10.1037/ a0025279

McCabe, S. B., & Gotlib, I. H. (1993). Interactions of couples with and without a depressed spouse: Self-reported and observations of problem- solving situations. Journal of Social and Personal Relationships, 10(4), 589–599. https://doi.org/10.1177/0265407593104007

Merikangas, K. R. (1982). Assortative mating for psychiatric disorders and psychological traits. Archives of General Psychiatry, 39(10), 1173–1180. https://doi.org/10.1001/archpsyc.1982.04290100043007

Moffitt, T. E., Robins, R. W., & Caspi, A. (2001). A couples analysis of partner abuse with implications for abuse-prevention policy. Criminology & Public Policy, 1(1), 5–36. https://doi.org/10.1111/j.1745-9133.2001 .tb00075.x

Muthén, L. K., & Muthén, B. O. (2012). Mplus. Nakagawa, S. (2004). A farewell to Bonferroni: The problems of low statistical power and publication bias. Behavioral Ecology, 15(6), 1044–1045. https://doi.org/10.1093/beheco/arh107

Norton, R. (1983). Measuring marital quality: A critical look at the depen- dent variable. Journal of Marriage and the Family, 45(1), 141–151. https://doi.org/10.2307/351302

Novak, J., & Furman, W. (2016). Partner violence during adolescence and young adulthood: Individual and relationship level risk factors. Journal of Youth and Adolescence, 45, 1849–1861. https://doi.org/10.1007/s10964- 016-0484-4

O’Keefe, M. (1997). Predictors of dating violence among high school students. Journal of Interpersonal Violence, 12(4), 546–568. https:// doi.org/10.1177/088626097012004005

O’Leary, K. D. (1999). Developmental and affective issues in assessing and treating partner aggression. Clinical Psychology: Science and Practice, 6(4), 400–414. https://doi.org/10.1093/clipsy.6.4.400

O’Leary, K. D., Barling, J., Arias, I., Rosenbaum, A., Malone, J., & Tyree, A. (1989). Prevalence and stability of physical aggression between spouses: A longitudinal analysis. Journal of Consulting and Clinical Psychology, 57(2), 263–268. https://doi.org/10.1037/0022-006X.57.2.263

Pfeiffer, S. M., & Wong, P. T. P. (1989). Multidimensional jealousy. Journal of Social and Personal Relationships, 6(2), 181–196. https://doi.org/10 .1177/026540758900600203

Pickles, A., & Rutter, M. (1991). Statistical and conceptual models of “turning points” in developmental processes. In D. Magnusson, L. Bergman, G. Rudinger, & B. Torestad (Eds.), Problems and methods in longitudinal research: Stability and change (pp. 131–165). Cambridge University Press.

Preacher, K. J., Curran, P. J., & Bauer, D. J. (2006). Computational tools for probing interactions in multiple linear regression, multilevel modeling,

578 LANTAGNE AND FURMAN

T h is d o cu m en t is co p y ri g ht ed

b y th e A m er ic an

P sy ch o lo g ic al

A ss o ci at io n o r o n e o f it s al li ed

p u b li sh er s.

T h is ar ti cl e is in te nd ed

so le ly

fo r th e p er so n al

u se

o f th e in di v id u al

u se r an d is n o t to

b e d is se m in at ed

b ro ad ly .

and latent curve analysis. Journal of Educational and Behavioral Statis- tics, 31(4), 437–448. https://doi.org/10.3102/10769986031004437

Quinton, D., Pickles, A., Maughan, B., & Rutter, M. (1993). Partners, peers, and pathways: Assortative pairing and continuities in conduct disorder. Development and Psychopathology, 5(4), 763–783. https://doi.org/10 .1017/S0954579400006271

Reese-Weber, M., & Johnson, A. I. (2013). Examining dating violence from the relational context. In H. R. Cunningham & W. F. Berry (Eds.), Handbook on the psychology of violence (pp. 53–76). Nova Publishing.

Reyes, H. L., Foshee, V. A., Tharp, A. T., Ennett, S. T., & Bauer, D. J. (2015). Substance use and physical dating violence: The role of contextual moderators. American Journal of Preventive Medicine, 49(3), 467–475. https://doi.org/10.1016/j.amepre.2015.05.018

Rhoades, G. K., Kamp-Dush, C. M., Atkins, D. C., Stanley, S. M., & Markman, H. J. (2011). Breaking up is hard to do: The impact of unmarried relationship dissolution on mental health and life satisfaction. Journal of Family Psychology, 25(3), 366–374. https://doi.org/10.1037/ a0023627

Riggs, D. S., & O’Leary, K. D. (1989). The development of a model of courtship aggression. In M. A. Pirog-Good & J. E. Stets (Eds.), Violence in dating relationships: Emerging social issues (pp. 53–71). Praeger.

Rothman, K. (1990). No adjustments are needed for multiple comparisons. Epidemiology (Cambridge, Mass.), 1(1), 43–46.

Saville, R. (1990). Multiple comparison procedures: The practical solution. The American Statistician, 40(2), 174–180.

Simon, V. A., & Furman, W. (2010). Interparental conflict and adolescents’ romantic relationships. Journal of Research on Adolescence, 20(1), 188– 209. https://doi.org/10.1111/j.1532-7795.2009.00635.x

Straus, M. A., Hamby, S. L., Boney-McCoy, S., & Sugarman, D. B. (1996). The revised conflict tactics scale (CTS2): Development and preliminary psychometric data. Journal of Family Issues, 17(3), 283–316. https:// doi.org/10.1177/019251396017003001

Stroud, C. B., Davila, J., & Moyer, A. (2008). The relationship between stress and depression in first onsets versus recurrences: A meta analytic review. Journal of Abnormal Psychology, 117(1), 206–213. https:// doi.org/10.1037/0021-843X.117.1.206

Thomas, V. P. (1998). What’s wrong with Bonferroni adjustments. British Medical Journal, 316(1236), 1236–1238. https://doi.org/10.1136/bmj.316 .7139.1236

Vezina, J., & Hebert, M. (2007). Risk factors for victimization in romantic relationships of young women: A review of empirical studies and im- plications for prevention. Trauma, Violence & Abuse, 8(1), 33–66. https:// doi.org/10.1177/1524838006297029

Vicary, J. R., Klingaman, L. R., & Harkness, W. L. (1995). Risk factors associated with date rape and sexual assault of adolescent girls. Journal of Adolescence, 18(3), 289–306. https://doi.org/10.1006/jado .1995.1020

Vujeva, H. M., & Furman, W. (2011). Depressive symptoms and romantic relationship qualities from adolescence through emerging adulthood: A longitudinal examination of influences. Journal of Clinical Child and Adolescent Psychology, 40(1), 123–135.

Whitaker, D. J., Le, B., & Niolon, P. H. (2010). Persistence and desistance of the perpetration of physical aggression across relationships: Findings from a national study of adolescents. Journal of Interpersonal Violence, 25(4), 591–609. https://doi.org/10.1177/0886260509334402

Woodin, E. M., Caldeira, V., & O’Leary, K. D. (2013). Dating aggression in emerging adulthood: Interactions between relationship processes and individual vulnerabilities. Journal of Social and Clinical Psychology, 32(6), 619–650. https://doi.org/10.1521/jscp.2013.32.6.619

Received October 27, 2019 Revision received February 20, 2021

Accepted March 8, 2021 ▪

PSYCHOPATHOLOGY AND AGGRESSION 579

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