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. Author manuscript; available in PMC: 2025 Jun 1.
Published in final edited form as: Fam Process. 2023 Sep 15;63(2):983–1000. doi: 10.1111/famp.12941

Relationship Risk Factors for Intimate Partner Violence among Sexual and Gender Minorities: A Multilevel Analysis

Elissa L Sarno 1,2, Gregory Swann 1,2, Michael E Newcomb 1,2, Sarah W Whitton 3
PMCID: PMC10940214  NIHMSID: NIHMS1936871  PMID: 37715359

Abstract

Intimate partner violence (IPV) is alarmingly prevalent among sexual and gender minority youth assigned female at birth (SGM-AFAB), making it important to identify risk factors that can be targeted in prevention efforts for this population. Though several relationship-level risk factors for IPV have been identified in different-sex couples, research on SGM-AFAB is sparse and predominantly cross-sectional. The present study used seven waves of data from a longitudinal cohort study of SGM-AFAB youth (n = 463) to explore relationship factors (relationship quality, destructive conflict, and self- and partner-jealousy) as risk factors for perpetration and victimization of three types of IPV (physical, psychological, and coercive control). At each wave, participants reported on relationship factors and IPV for up to three romantic partners in the past 6 months. Multilevel models tested for associations between the relationship factors and IPV at three levels: between-persons, within-persons across time (wave), and within-persons across relationships. Relationship quality was associated with IPV mostly at the between-persons and within-persons (wave) levels. Couple conflict was associated with all IPV outcomes at all levels. Partner jealousy was more consistently associated with IPV victimization; participant jealousy was more consistently linked with IPV perpetration. These novel findings suggest that, within SGM individuals, IPV may be influenced by relationship quality, destructive conflict, and jealousy as they fluctuate within individuals from relationship to relationship and within individuals over time. As such, these relationship factors represent promising potential targets for interventions to reduce IPV among SGM-AFAB youth.

Keywords: intimate partner violence, sexual and gender minority, relationship quality, conflict, jealousy

Intimate partner violence (IPV), which includes physical violence, psychological aggression, and coercive tactics by an intimate partner, is very common among adolescent and young adult women. Recent data from the WHO Global Database on Prevalence of Violence Against Women indicates that approximately 24% of women aged 15–19 years and 26% of women aged 19–24 years have experienced IPV at least once (Sardinha et al., 2022). Rates of IPV among sexual and gender minority (SGM) adolescents and young adults have been shown to be at least as high, if not higher, than those of heterosexual populations (Edwards et al., 2015). This disparity appears to be particularly pronounced for sexual and gender minorities assigned female at birth (SGM-AFAB; i.e., cisgender women, transgender men, and gender nonbinary individuals assigned female at birth), who were found in one longitudinal study to have 75% greater odds of experiencing IPV compared to SGM assigned male at birth (Whitton et al., 2019). Research has also shown that SGM youth who are IPV victims experience more negative outcomes than heterosexual IPV victims, including poorer psychological, academic, and behavioral functioning (Dank et al., 2014; Walters et al., 2013). Identifying risk factors that represent targets for intervention to reduce IPV among SGM-AFAB is crucial to mitigating this growing health disparity (Kimmes et al., 2019).

Etiological models of IPV emphasize the presence of risk factors across multiple levels of the social ecology (Bell & Naugle, 2008; O’Leary et al., 2007). According to the dynamic developmental systems perspective (DDS; Capaldi et al., 2004; Capaldi et al., 2005) risk for IPV is influenced by developmental characteristics and behaviors of each partner (e.g., experience of childhood abuse, substance misuse), contextual factors (e.g., socioeconomic status, neighborhood factors), and characteristics of the relationship (e.g., relationship satisfaction, couple interaction patterns, jealousy). Relationship-level risk factors have been relatively neglected in the IPV literature (Capaldi et al., 2012), despite that they are the most proximal to IPV events and, in contrast to many well-studied risk factors (e.g., age, gender, childhood abuse), are modifiable. A large body of research suggests that couple interactions and relationship quality can be improved through relationship interventions, including healthy relationship education (Hawkins et al., 2008) and couple therapy (Doss et al., 2022). Further, culturally tailored versions of relationship education (Newcomb et al., 2017; Whitton et al., 2017) and couple therapy (Pentel et al., 2021) for SGM couples have shown high acceptability and efficacy in improving couple processes. Therefore, with the goal of contributing to tailored IPV risk reduction interventions for this population, we explored relationship characteristics that may act as risk or protective factors for IPV among SGM-AFAB.

General population (i.e., not SGM-specific) research has identified several relationship factors with robust links to IPV. Recent meta-analyses indicate that global relationship quality (often labeled satisfaction) is a protective factor, demonstrating negative associations with physical IPV victimization (Spencer et al, 2019) and perpetration (Spencer et al, 2022). Couple conflict, including destructive or ineffective conflict management behaviors, is a robust proximal risk factor for IPV in different-sex relationships (Capaldi et al., 2012; Spencer et al., 2019, 2022). Jealousy within the relationship represents another risk factor for IPV; partner jealousy has been associated with IPV victimization (Spencer et al., 2019) and one’s own jealousy with physical IPV perpetration (Spencer et al., 2022). Unfortunately, there is very little research exploring these associations within SGM relationships. Although previous research has indicated that some risk factors for IPV in heterosexual couples may be relevant to SGM couples (Edwards et al., 2015), we cannot assume that associations of relationship-level risk factors and IPV perpetration and victimization will generalize to SGM couples without additional empirical evidence, particularly given the broader context of societal stigma in which SGM relationships exist, which can impact the quality of relationships and the health of those within them (LeBlanc, Frost, & Wight, 2015; Newcomb, 2020). A recent meta-analysis of risk factors for IPV in same-gender couples (Kimmes et al., 2019) included no relationship-level risk factors other than fusion in female couples (excepting other forms of IPV). Nevertheless, a handful of studies have found that female same-gender relationships characterized by higher, versus lower, relationship quality tend to be at lower risk for physical and psychological IPV (Balsam & Szymanski, 2005; Do et al., 2021; Lewis et al., 2017). Do et al. (2021) also found that destructive couple conflict was associated with psychological IPV perpetration. Lastly, in studies of SGM women, one found that experiencing jealousy in the relationship was associated with perpetration of abusive behavior (Telesco, 2004), and two found that those who perceived their partners as jealous were at higher risk for IPV victimization (Dyar et al., 2020; McClennen et al., 2002). In sum, general population studies and the nascent SGM literature on relationship risk factors for IPV suggest that conflict, relationship quality, and jealousy may predict IPV in this population; however, more research is clearly needed.

Another key limitation of the literature on IPV risk and protective factors is that the vast majority of studies are cross-sectional, prohibiting conclusions about the direction of effects or within-person associations (Capaldi et al., 2012; Stith et al., 2008). Scholars have called for longitudinal research that can speak more directly to whether relationship processes raise risk for IPV or are consequences of IPV, and that can assess for within-person associations over time, exploring whether changes in relationship processes are associated with changes in IPV risk within individuals. Further, extremely little is known about the effects of changing romantic partners on IPV risk. Following participants across multiple relationships is an underused but important study design that can build understanding of how differences in relationship characteristics (e.g., quality, conflict, and jealousy) between an individual’s different romantic partnerships may affect IPV risk (Capaldi et al., 2012). The presence of associations between relationship factors and IPV within-individuals across time would suggest that efforts to improve a couple’s relationship functioning (i.e., improving quality; reducing destructive conflict and jealousy) is likely to reduce risk for IPV within that partnership. The presence of within-person associations across relationships, in contrast, would suggest that exiting a relationship characterized by conflict or jealousy and entering a different partnership might reduce an individual’s risk for IPV.

Present Study

The present study used multiwave data to investigate associations of relationship factors (i.e., relationship quality, couple conflict, and self and partner jealousy) with IPV victimization and perpetration among SGM-AFAB youth (late adolescents and young adults) in relationships. Although experiences of minority stress (e.g., internalized heterosexism, sexual orientation microaggressions) have been identified as risk factors for IPV that are unique to SGM and which may help explain increased rates of IPV relative to heterosexual individuals (Longobardi & Badenes-Ribera, 2017), the goal of the present study was to identify within-group risk factors that represent intervention targets for this high risk population, rather than to explain disparities (on which we have focused in our prior work; see Sarno et al., 2023). Data were collected every six months (except for the final wave, which was collected one year after the previous wave); at each wave, participants reported on relationship factors and IPV for up to three partnerships in the last 6 months.

The goal of the present study was to add to the existing literature on SGM-AFAB IPV in several ways. First, in addition to assessing physical and psychological IPV, we also included coercive control (e.g., monitoring partner’s time, controlling access to partner’s money, making it difficult for partner to see friends or family) as an outcome, which has been shown to be distinct from psychological IPV and prevalent among same-sex couples (Frankland & Brown, 2014). Second, by collecting data across multiple study waves and for multiple partners for each participant, we were able to not only test associations of relationship factors and IPV at the between-persons level (similar to many previous cross-sectional studies), but also at the within-persons level in two different ways: Waves nested within individuals and relationships nested within individuals. Significant results at the between-persons level would indicate that, for example, participants who tend to have higher relationship quality on average across their partnerships experience less IPV than participants who tend to have lower relationship quality across partnerships. Significant results at the within-persons (relationship) level would indicate that, within individuals, IPV is less likely to be present in their relationships that are characterized by higher quality than in their relationships that are characterized by lower quality. Finally, significant results at the within-persons (wave) level would indicate that, within individuals, IPV is less likely to be present at time points when an individual’s relationship quality is higher than at time points when it is lower.

We hypothesized that at the between-persons level, higher relationship quality would be associated with lower likelihood of IPV victimization and perpetration, and that more conflict and (self and partner) jealousy would be associated with a higher likelihood of IPV victimization and perpetration. Based on theory and past evidence of within-person associations between other relationship processes, we hypothesized that these associations would be present at other levels as well. However, these hypotheses were tentative given the lack of previous studies exploring these effects at all levels of analysis.

Method

Participants and Procedure

Participants were 463 SGM-AFAB youth from FAB 400, an ongoing longitudinal cohort study that began in November 2016. To achieve a multiple cohort, accelerated longitudinal design, FAB 400 includes SGM-AFAB from two cohorts: (1) a late adolescent cohort recruited for FAB 400 in 2016–2017 (N = 400; 16- to 20-years-old at baseline); and (2) a young adult cohort comprised of the AFAB participants from a previous cohort study of SGM youth recruited in 2007 (N = 88; 23- to 32-years old at the FAB 400 baseline). Eligibility criteria at original cohort enrollment were being ages 16–20 years old, assigned female at birth, and either identifying with a sexual or gender minority label or reporting same-sex attractions or sexual behavior. Both cohorts were recruited using venue-based recruitment, social media, and incentivized snowball sampling. Participants completed assessments at 6-month intervals (except for the interval between Wave 6 and 7, which was one year) and were compensated $50 for each visit. Retention was high across all waves (W2: 96.9%, W3: 95.5%, W4: 92.8%, W5: 93.4%, W6: 92.4%, W7: 90.8%). Older participants missed more waves (unstandardized beta = .10, p < .001) than younger participants and transgender youth missed more waves than cisgender participants (unstandardized beta = .43, p = .046). There were no significant differences in attrition based on race/ethnicity or sexual orientation. The study protocol was approved by the Institutional Review Board at Northwestern University with a waiver of parental permission for participants under 18 years of age under 45 CFR 46, 408(c). Participant demographics are displayed in Table 1.

Table 1.

Participant Demographics (N = 463)

M (SD)
Age 20.10 (3.72)
N (%)
Race/Ethnicity
 Black/African American 163 (35.2)
 White 119 (25.7)
 Hispanic or Latino/Latina/Latinx 114 (24.6)
 Multiracial 41 (8.9)
 Asian 21 (4.5)
 Other 5 (1.1)
Sexual Orientation
 Bisexual/Pansexual 254 (54.9)
 Lesbian/Gay 111 (24.0)
 Queer 57 (12.3)
 Unsure/Questioning 19 (4.1)
 Asexual 9 (1.9)
 Not Listed 7 (1.5)
 Straight/Heterosexual 6 (1.3)
Gender Identity
 Female 346 (74.7)
 Gender Non-Conforming/Gender Queer/Non-Binary 70 (15.1)
 Transgender/Male 41 (8.9)
 Not Listed 6 (1.3)
Relationship type (N = 1,414)
 Casually dating but not serious 621 (43.9)
 Serious relationship 702 (49.6)
 Engaged to be married 35 (2.5)
 Married/domestic partnership/civil union 39 (2.8)
 A lifelong committed relationship 17 (1.2)
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At each wave, participants reported on experiences of IPV with up to three sexual or romantic partners they had had in the previous six months. For each romantic relationship reported (i.e., excluding partnerships that were strictly sexual), data were collected on relationship quality, couple conflict, participant’s jealousy, and partner’s jealousy. For each partner, participants were asked to report the partner’s first name and the last initial (e.g., Sam W.), age, gender identity, sexual orientation, and race/ethnicity. Beginning at the second wave, participants were provided with the names of every partner they had previously reported and were asked if their partner matched any of the previous partners or was a new partner. At Wave 6, participants were provided a list of every partner they had reported over the course of the study and were once again asked to confirm which partners were the same. This last step was done to confirm participant’s previous reports and to account for partners who changed their name, gender identity, and/or sexual orientation over the course of the study. For data analysis, each partner was assigned a unique ID number (e.g., 1, 2, 3) that was combined with the participant’s ID number to create a partner ID, which was assigned to every report on the same relationship across all waves of the study.

To reduce participant burden, abbreviated versions of measures of all variables were administered for the second and third partners reported at each wave. For the present analyses, we used the abbreviated versions of all measures for all three partners, to ensure that scales were compatible across all partners. The final sample included 463 participants who reported on a total of 1,414 unique partnerships. Mean number of relationships reported on by participants was 3.05. Participants reported on each relationship for an average of 1.99 waves.

Measures

Relationship Quality.

Relationship quality was assessed using two items from the Relationship Quality subscale of the Relationship Assessment Scale (RAS; Vaughn & Matyastik Baier, 1999). Participants responded to each of the following items on a 5-point Likert-type scale: “In general, how satisfied are you with your relationship?” was rated from 1 (not satisfied) to 5 (very satisfied). “How many problems are there in your relationship?” was rated from 1 (no problems) to 5 (more problems than most relationships). The second item was reverse-scored and items were averaged into a single score, with higher scores indicating higher relationship quality (ρ = .65). The RAS showed evidence of convergent validity during development (e.g., high correlations with other established measures of relationship satisfaction; Vaughn & Matyastik Baier, 1999). Scores on the two-item version of the RAS showed high correlations with scores on the full scale (r = .87).

Couple Conflict.

Conflict was assessed using two items from the Couple Conflict: Danger Signs Scale, which measures key features of destructive couple communication (Stanley et al., 2002). Participants responded to each item on a 3-point Likert-type scale ranging from 1 (almost never) to 3 (frequently) to indicate how often each statement seemed true in their relationship. The statements were: “Little arguments escalate into ugly fights with accusations, criticisms, name-calling, or bringing up past hurts” and “When we argue, one of us withdraws, doesn’t want to talk about it anymore, or leaves the scene.” Items were averaged into a single score, with higher scores indicating more destructive couple conflict (ρ = .71). The Couple Conflict Scale showed evidence of convergent validity during development by demonstrating negative correlations with numerous measures of relationship quality and a positive correlation with divorce potential in a nationally representative sample of married adults (Stanley et al., 2002). Scores on the two-item version of the Couple Conflict Scale showed high correlations with scores on the full scale (r = .93).

Jealousy.

Participant and partner jealousy were each assessed using a single item developed for FAB 400 based on a review of the Multidimensional Jealousy Scale (Elphinston et al., 2011) and the Psychological Maltreatment of Women Inventory (Tolman, 1999). Participants responded to each item, “I am jealous when [partner name] is around people they may be attracted to,” and “[Partner name] is jealous when I am around people I may be attracted to,” on a 7-point Likert-type scale ranging from 1 (strongly disagree) to 7 (strongly agree). Higher scores on each item were used to indicate higher participant jealousy and perceptions of partner jealousy, respectively.

Intimate Partner Violence.

At each visit, three types of IPV (described below) were assessed for up to three partners in the last six months. For each type of IPV, items were administered twice: once to assess victimization and once to assess perpetration. On each item, participants indicated how frequently each behavior or event occurred on a scale ranging from 0 (never) to 6 (more than 20 times). For each IPV type, responses were used to create a dichotomous variable indicating any occurrence (vs. absence) of that type of IPV victimization or perpetration. If participants reported a value greater than zero for any of the items on a subscale, they were coded as 1; those that reported zero for all items were coded as 0.

Physical and Psychological IPV.

To assess physical and psychological IPV, participants completed the Sexual and Gender Minorities Conflict Tactics Scale (SGM-CTS2), a newly developed version of the CTS2 (Straus et al., 1996) adapted to be culturally appropriate for SGM samples (Dyar et al., 2021). In the psychometric evaluation study of the SGM-CTS2, the measure showed the same factor structure of the CTS2 and evidence of validity and reliability (Dyar et al., 2021). For these analyses, we used a six-item version of the SGM-CTS2 assessing psychological (three items) and physical (three items) IPV. Scores on the three-item version of the psychological IPV subscale of SGM-CTS2 showed high correlations with scores on the full subscale for perpetration (r = .88) and victimization (r = .89); scores on the three-item version of the physical IPV subscale of SGM-CTS2 showed high correlations with scores on the full subscale for perpetration (r = .88) and victimization (r = .91).

Coercive Control.

Coercive control, or behaviors that are intended to monitor and control an intimate partner, was measured using a two item investigator-developed scale based on the Controlling Behaviors Scale (Frankland & Brown, 2014) and items from the National Intimate Partner and Sexual Violence Survey (NISVS; Walters et al., 2013). The items were: “[Partner name] monitored my time and made me account for my whereabouts” and “[Partner name] made it difficult for me to see friends or family.” In the psychometric evaluation study of the Coercive Control measure, the full eight item measure showed the expected unidimensional factor structure and evidence of convergent and divergent validity (Dyar et al., 2021). Scores on the two-item version of the Coercive Control scale showed high correlations with scores on the full scale for perpetration (r = .87) and victimization (r = .89).

Statistical Analyses

The associations of the four relationship characteristics (relationship quality, couple conflict, participant’s jealousy, and their partner’s jealousy) with the six IPV outcomes (victimization and perpetration of psychological, coercive control, and physical IPV, respectively) were tested in MPlus (Muthén & Muthén, 1998–2017) using multilevel logistic regression models. Missingness was accounted for using full information maximum likelihood estimation (FIML). Three levels were included in each model: one between-persons level, and two within-persons levels: waves nested within individuals, and relationships nested within individuals. For the between-persons level, predictors were grand-mean centered. For the within-persons (waves) and within-persons (relationships) levels, predictors were group-mean centered in two different ways. At the within-persons (waves) level, for those who reported on multiple relationships at a given wave, the value for the predictor at that wave was the average of that predictor across all relationships reported on at that wave. At the within-persons (relationships) level, for those who reported on the same relationship across multiple waves, the value of the predictor for that relationship was the average of that predictor across all waves reported for that relationship. For example: At Wave 1, Participant 1001 reported having been in a relationship with Partner 1, Partner 2, and Partner 3 (identified by concatenating the participant ID and partner ID numbers): 10011, 10012, and 10013. This participant therefore had data on each relationship factor and IPV variable for each of the three relationships at this wave. At Waves 2 and 3, Participant 1001 reported that they were in a relationship with Partner 3 (10013) and had no other partners. For this participant, the within-persons (waves) value for the relationship factors and IPV at Wave 1 would be an average of the scores for partners 10011, 10012, and 10013; for Waves 2 and 3, their within-persons (waves) values would be the scores for Partner 3 only. At the within-persons (relationships) level, for 10011 and 10012, the values for relationship factors and IPV would be scores from Wave 1; for 10013, the values would be the average of scores on measures from Waves 1, 2, and 3.

We treated our outcomes as dichotomous in our models and used a Bayes estimator because of its superior performance compared to other MPlus estimators at handling data that is non-normally distributed. For the Bayes estimator in MPlus, a one-tailed significance test is calculated with the statistical significance threshold at a p-value below .025. We ran separate models for each predictor with each of the six IPV outcomes (24 models in total). Covariates at the between-persons level included age, race/ethnicity, sexual orientation, and gender identity. At the within-persons (waves) level, we included whether the partner was current (i.e., they were still with that partner at the time of reporting) and whether the participant’s relationship was serious or casual (note: these variables were not included at the within-persons (relationships) level because these statuses could change over the course of the study for reoccurring relationships).

Results

Rates of IPV perpetration and victimization are displayed in Table 2. Rates were calculated as the percentage of participants who reported having experienced each type of IPV with at least one partner at one wave, the percentage of relationships in which participants reported experiencing IPV in at least one wave, and the percentage of waves in which participants reported experiencing IPV with at least one partner. Within each type of IPV, the proportions of participants, relationships, and waves in which victimization was present was roughly equal to the proportion in which perpetration was present, possibly a reflection that most IPV is bidirectional. The proportion of participants who ever experienced IPV is higher than the proportion of relationships or waves in which it was present, which was expected, since the latter two occurred within the subgroup of participants who ever experienced IPV. The most frequently reported type of IPV was psychological IPV, followed by coercive control and physical IPV.

Table 2.

Frequencies and Intraclass Correlation Coefficients of Intimate Partner Violence Variables

ICC % with at least one IPV experience
Within-Persons (Waves) Within-Persons (Relationships) Between-Persons Waves Relationships Participants
IPV Perpetration
 Psychological .501 .235 .264 42.9 42.9 72.8
 Coercive Control .697 .132 .171 13.1 16.5 36.9
 Physical .655 .145 .200 10.1 13.2 30.2
IPV Victimization
 Psychological .497 .283 .220 40.0 41.2 72.4
 Coercive Control .674 .212 .114 17.4 22.0 48.4
 Physical .622 .250 .128 9.8 12.8 30.0
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Note. ICC = Intraclass correlation coefficient. ICC for the Within-Persons (Waves), Within-Persons (Relationships), and Between-Persons levels indicates the proportion of variance that was due to differences between waves (within-persons), differences between relationships (within-persons), and differences between participants, respectively. In the % with at least one IPV experience columns, “participants” represents the percentage of participants who reported having experienced each type of IPV with at least one partner at one wave; “relationships” represents the percentage of relationships in which participants reported experiencing IPV in at least one wave; and “waves” represents the percentage of waves in which participants reported experiencing IPV with at least one partner.

Prior to testing associations of relationship factors with IPV, we calculated the intraclass correlation coefficient (ICC) for the six outcome variables to examine the proportions of variance that were due to differences between waves (within participants), differences between relationships (within participants), and differences between participants (see Table 2). The ICCs indicated that, in general, most of the variance in IPV outcomes was due to within-person differences across time points (i.e., within-persons [waves]; 50–70%), with the remaining variance roughly equally due to within-person differences across relationships (i.e., within-persons [relationships]; 13–28%) and differences between participants (11–26%).

Relationship Quality

Results for perpetration models can be found in Table 3 and victimization models in Table 4. There were statistically significant between-persons associations of relationship quality with psychological IPV perpetration, psychological IPV victimization, coercive control perpetration, coercive control victimization, physical IPV perpetration, and physical IPV victimization. Individuals who reported higher average relationship quality over the course of the study were less likely to be victims or perpetrators of all three forms of IPV compared to individuals who reported a lower average relationship quality across the study.

Table 3.

Multilevel Relationship Factors on Intimate Partner Violence Perpetration

Psychological IPV Coercive Control Physical IPV
Relationship Quality Estimate 95% CI p-value Estimate 95% CI p-value Estimate 95% CI p-value
 Between-Persons −0.75 −1.04: −.44 <.001 −0.57 −.89: −.27 <.001 −0.61 −.96: −.29 <.001
 Within-Persons (Relationships) 0.06 −.18: .22 0.265 −0.10 −.29: .08 0.123 −0.28 −.46: −.05 0.003
 Within-Persons (Waves) −0.46 −.59: −.33 <.001 −0.20 −.33: −.06 0.004 −0.30 −.46: −.15 <.001
Couple Conflict
 Between-Persons 1.73 1.28: 2.20 <.001 0.97 .53: 1.44 <.001 1.36 .87: 1.88 <.001
 Within-Persons (Relationships) 0.42 .13: .74 0.002 0.67 .39: .96 <.001 0.49 .22: .87 0.001
 Within-Persons (Waves) 0.93 .72: 1.14 <.001 0.41 .19: .62 <.001 0.56 .32: .77 <.001
Jealousy (Self)
 Between-Persons 0.11 −.03: .25 0.058 0.26 .12: .41 <.001 0.21 .04: .38 0.008
 Within-Persons (Relationships) 0.16 .07: .26 <.001 0.11 .00: .22 0.028 0.02 −.11: .15 0.398
 Within-Persons (Waves) 0.06 .00: .12 0.023 0.14 .08: .21 <.001 0.13 .05: .21 0.001
Jealousy (Partner)
 Between-Persons 0.17 .04: .29 0.004 0.38 .23: .54 <.001 0.28 .12: .45 <.001
 Within-Persons (Relationships) 0.16 .08: .24 <.001 0.07 −.05: .19 0.111 0.11 .00: .22 0.027
 Within-Persons (Waves) 0.09 .04: .15 <.001 0.15 .08: .23 <.001 0.16 .09: .24 <.001
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Note. CI = Credibility Interval. IPV = Intimate Partner Violence. Estimates are unstandardized regression coefficients. Statistically significant associations (p < .025) are in bold text. All models controlled for age, race/ethnicity, sexual orientation, gender identity, casual relationship status, and if relationship was still current at time of reporting.

Table 4.

Multilevel Relationship Factors on Intimate Partner Violence Victimization

Psychological IPV Coercive Control Physical IPV
Relationship Quality Estimate 95% CI p-value Estimate 95% CI p-value Estimate 95% CI p-value
 Between-Persons −0.73 −1.05: −.42 <.001 −0.41 −.71: −.11 0.004 −0.90 −1.27: −.54 <.001
 Within-Persons (Relationships) −0.05 −.25: .13 0.317 −0.22 −.42: −.02 0.016 −0.19 −.40: .09 0.071
 Within-Persons (Waves) −0.58 −.73: −.44 <.001 −0.44 −.58: −.30 <.001 −0.49 −.66: −.32 <.001
Couple Conflict
 Between-Persons 1.74 1.31: 2.19 <.001 0.77 .35: 1.23 <.001 1.55 1.06: 2.12 <.001
 Within-Persons (Relationships) 0.67 .37: .97 <.001 0.76 .46: 1.07 <.001 0.61 .24: 1.03 <.001
 Within-Persons (Waves) 0.93 .73: 1.14 <.001 0.66 .45: .87 <.001 0.77 .52: 1.04 <.001
Jealousy (Self)
 Between-Persons 0.11 −.03: .26 0.073 0.33 .20: .48 <.001 0.09 −.09: .26 0.159
 Within-Persons (Relationships) 0.15 .05: .25 0.001 −0.05 −.16: .05 0.145 0.20 .06: .33 0.002
 Within-Persons (Waves) 0.09 .03: .15 0.002 0.13 .06: .19 <.001 0.04 −.04: 12 0.155
Jealousy (Partner)
 Between-Persons 0.21 .08: .35 0.001 0.38 .25: .52 <.001 0.14 −.02: .31 0.046
 Within-Persons (Relationships) 0.18 .08: .27 <.001 0.12 .02: .23 0.012 0.30 .16: .43 <.001
 Within-Persons (Waves) 0.14 .08: .20 <.001 0.25 .18: .32 <.001 0.10 .03: .18 0.004
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Note. CI = Credibility Interval. IPV = Intimate Partner Violence. Estimates are unstandardized regression coefficients. Statistically significant associations (p < .025) are in bold text. All models controlled for age, race/ethnicity, sexual orientation, gender identity, casual relationship status, and if relationship was still current at time of reporting.

At the within-persons (relationships) level, relationship quality was significantly associated with coercive control victimization and physical IPV perpetration. However, associations with psychological perpetration, psychological victimization, coercive control perpetration, and physical IPV victimization were not significant. This indicates that individuals were less likely to be victims of coercive control or perpetrate physical IPV in their relationships characterized higher relationship quality than in their relationships characterized by lower relationship quality.

There were statistically significant within-person (waves) associations between relationship quality and both perpetration and victimization of all three types of IPV. That is, individuals were less likely to be victims or perpetrators of any type of IPV at waves when they reported higher relationship quality than at waves when they reported lower relationship quality.

Couple Conflict

Results indicated that couple conflict was associated with perpetration and victimization of all three types of IPV (psychological IPV, coercive control, and physical IPV) at all three levels of analysis. At the between-persons level, individuals with higher average couple conflict over the course of the study were more likely to be victims and perpetrators of all forms of IPV compared to individuals with lower average couple conflict. At the within-persons (relationships) level, within individuals, relationships were more likely to include all types of IPV perpetration and victimization if they included more couple conflict compared to relationships with less conflict. At the within-individuals (waves) level, associations between couple conflict and all IPV measures were also significant. This indicates that individuals were more likely to experience all types of IPV at waves when they reported experiencing more couple conflict compared to waves when they experienced less conflict.

Jealousy (Self)

Results revealed between-persons associations of jealousy with coercive control perpetration, coercive control victimization, and physical IPV perpetration, but no other IPV variables. That is, participants who were more jealous overall were more likely to be victims and perpetrators of coercive control and were more likely to perpetrate physical IPV than participants who were less jealous over the course of the study.

At the within-individuals (relationships) level, jealousy was associated with psychological IPV perpetration and physical IPV victimization, but no other IPV variables. This indicates that individuals were more likely to be perpetrators of psychological IPV and were more likely to be victims of physical IPV in their relationships where they experienced more jealousy than in their relationships where they experienced less jealousy.

At the within-individuals (waves) level, jealousy was significantly associated with psychological IPV perpetration, psychological IPV victimization, coercive control perpetration, coercive control victimization, and physical IPV perpetration, but not physical IPV victimization. That is, individuals were more likely experience all types of IPV except physical perpetration at waves when they experienced more jealousy than at waves when they were less jealous.

Jealousy (Partner)

There were significant between-persons associations between partner jealousy and all types of IPV except physical victimization, indicating that participations who reported more jealous partners over the course of the study were more likely to be victims and perpetrators of psychological IPV and coercive control and to perpetrate physical IPV than were those with less jealous partners overall.

At the within-persons (relationships) level, partner jealousy was associated with psychological IPV perpetration, psychological IPV victimization, coercive control victimization, and physical IPV victimization, but not perpetration of coercive control or physical IPV. This suggests that individuals were more likely to be victims and perpetrators of psychological IPV, and to be victims of coercive control and physical IPV, in their relationships with more jealous partners than in their relationships with less jealous partners.

At the within-individuals (waves) level, partner jealousy was significantly associated with all IPV measures. At waves when their partner was more jealous, individuals were more likely to be victims and perpetrators of all forms of IPV compared to waves when their partner was less jealous.

Discussion

The present study used multiwave data to investigate associations of relationship factors (i.e., relationship quality, couple conflict, and self and partner jealousy) with IPV (i.e., psychological, physical, and coercive control) victimization and perpetration among SGM-AFAB at three levels of analysis: between-persons, within-persons across relationships, and within-persons across time. As such, the findings significantly advance previous cross-sectional research conducted with SGM-AFAB samples showing that relationship quality, negative communication, and jealousy were associated with psychological and physical IPV victimization and perpetration (Balsam & Szymanski, 2005; Do et al., 2021; Dyar et al., 2020; Lewis et al., 2017; McClennen et al., 2002; Telesco, 2004). Because those studies only examined between-person associations at a single point in time within the context of one relationship, they left much unknown regarding whether and how these relationship factors covary with IPV within-persons, both from relationship to relationship and from timepoint to timepoint. The within-persons associations across relationships are particularly novel; we were unable to locate any other studies that used this approach. Importantly, these findings suggest that an individual can reduce their risk for IPV by leaving a jealous and conflictual partnership and working to build a healthier relationship with a new partner, refuting notions that propensity for IPV is a trait-like characteristic that individuals carry with them to all of their relationships. The observed within-persons associations across time, which are also novel among SGM samples, suggest that interventions that improve relationship functioning are likely to also reduce IPV risk. As such, they provide critical evidence to support healthy relationship education and couple therapy as part of efforts to address the high rates of IPV among SGM-AFAB people.

Destructive couple conflict was the most consistent predictor of IPV, with positive associations at the within-persons (waves), within-persons (relationships), and between-persons levels for all IPV types. These findings extend the literature in several ways. First, they indicate that destructive couple conflict is a robust risk factor for IPV among SGM-AFAB, as has been shown in the general population (Spencer et al., 2019, 2022). Contemporary views that IPV often arises from mismanaged conflict (i.e., situational couple violence; Johnson, 1995), rather than unidirectional attempts of an abuser to assert control over their partner (i.e., intimate terrorism; Johnson, 1995) appear to apply to SGM couples as well as different-sex couples. Second, this is the first study we know of to demonstrate that IPV risk differs across an individual’s romantic partnerships as a function of the given relationship’s level of destructive conflict. This reinforces understandings of IPV as a dyadic phenomenon that emerges from the particular context of a given relationship (e.g., Capaldi et al., 2004, 2005). It also supports efforts to provide healthy relationship education to youth that emphasizes the importance of selecting partners who can resolve issues constructively (e.g., Rhoades & Stanley, 2009). Third, by showing that, within-individuals, decreases in destructive conflict are associated with decreases in likelihood of all types of IPV, findings suggest that interventions that can reduce destructive conflict among SGM couples (e.g., Pentel et al., 2021; Whitton et al., 2017) hold promise for also reducing IPV within those partnerships. Conjoint treatment of IPV, which addresses situational couple violence that primarily occurs as part of escalated conflict (Stith & McCollum, 2011), may also be appropriate for SGM-AFAB youth’s relationships.

The present results also make important contributions regarding the role of jealousy as a risk factor for IPV. Among these SGM-AFAB youth, perceived partner jealousy had positive associations with all types of IPV victimization at all levels, replicating previous between-persons associations (Dyar et al., 2020; McClennen et al., 2002) and extending them by showing that within individuals, risk of IPV varied across time and across relationships as a function of partner jealousy. The present findings also extend previous research by showing that partner jealousy is associated not only with victimization, but also perpetration of physical and psychological IPV, both understudied among SGM-AFAB. Though it is less clear why partner jealousy might raise risk for perpetrating IPV, SGM youth may respond to partner jealousy with verbal or physical aggression. Alternately, as jealousy is one of the top argument-starters among young adult couples (Whitton et al., 2018), partner jealousy may lead to conflict that escalates into bidirectional IPV. In a parallel fashion, participant’s own feelings of jealousy were associated with most forms of IPV perpetration across levels of analysis, and less consistently associated with IPV victimization. This finding contradicts evidence that among different-sex couples, victims but not perpetrators tend to attribute the IPV to self- and partner-jealousy (Neal & Edwards, 2017) and suggest that SGM-specific IPV interventions might be able to capitalize on perpetrators’ willingness to acknowledge the role of their jealousy in couple violence. Finally, the present findings identify jealousy as a likely driver of coercive control, which is a vastly understudied type of IPV despite its relevance for SGM couples (Frankland & Brown, 2014). Among SGM-AFAB, feeling jealous of one’s partner may lead to controlling behaviors (e.g., monitoring partner’s time, controlling access to partner’s money, making it difficult for partner to see friends or family) that are associated with psychological and relationship distress.

Interestingly, global relationship quality was associated with all IPV outcomes at the between-persons and within-persons (waves) levels, but only with two forms of IPV (physical perpetration and coercive control victimization) at the within-person (relationships) level. This pattern of findings highlights the importance of assessing associations between relationship factors at multiple levels, rather than assuming that between-persons associations will generalize into associations within individuals over time or across relationships. As shown in the general population for physical IPV (Spencer et al, 2019; Spencer et al, 2022), the present between-persons findings suggest that SGM youth who generally have higher quality relationships are less likely to experience physical, psychological, or coercive control IPV than those who tend to have lower quality relationships. The within-persons findings suggest that it may be less important to consider relationships with lower global relationship quality as being at risk for IPV, and more crucial to monitor decreases in quality across time as indicators of an individual’s current risk for IPV. Fluctuations in perceived quality of a given relationship over time have been associated with poor partner mental health (e.g., Whitton et al., 2014), low relationship commitment, and break-up (Arriaga, 2001); it is possible that they are also influential for IPV risk. However, due to the way the multilevel data were structured in this study, the within-persons (waves) associations did not differentiate between fluctuations in relationship quality over time that occurred within the same relationship or across different partnerships. Future longitudinal research using samples of SGM couples can more precisely assess the extent to which relationship quality and IPV covary over time within specific relationships.

Limitations and Future Directions

Results of the present study should be considered with its limitations. First, our recruitment methods may limit the generalizability of results to SGM-AFAB youth who are relatively out and connected to the SGM community. Second, to reduce participant burden for those reporting on multiple relationships at each wave, we used two- or three-item measures to assess relationship factors and IPV outcome variables, which can have an impact on reliability and validity of these measures, relative to the full scales. Additional evaluation of the psychometrics of these measures is needed. Third, IPV is a product of relationship dynamics that result from the interactions between partners and is often bidirectional. Thus, having data from only one relationship partner limits our ability to fully characterize the ways that these relationship factors may increase risk for IPV among SGM-AFAB youth. Future research using dyadic data (i.e., from both partners) is needed to fully explore the ways that each partners’ perception of relationship factors may contribute to their independent and interactive experiences of IPV perpetration and victimization.

Lastly, as discussed above, due to the way that data were centered at each level of analysis, there were cases in which we used scores for predictor variables that were averages across multiple waves within the same relationship (at the within-persons [relationships] level) and across multiple relationships at the same wave (at the within-persons [waves] level). This limited our ability to investigate fluctuations from wave to wave within specific relationships. Future longitudinal research conducted over longer periods of time with older adults to capture multiple, multi-wave relationships for each participant would be able address this limitation by including enough variability at all three levels of analysis to test models with waves nested within relationships nested within persons. Similarly, future research should consider trajectories over time, and in particular, how SGM-AFAB youth’s experiences of relationships and IPV change across development.

Clinical Implications

Results of the current study have important implications for clinical work with SGM-AFAB youth who may be at risk for IPV. The consistent within-persons associations across time between relationship factors and IPV indicate that, even after accounting for variability in IPV from participants’ average relationship factors, and from relationships’ average in these factors, fluctuations in relationship quality, conflict, and jealousy from wave to wave covaried with corresponding fluctuations in IPV victimization and perpetration. This could be an indication that interventions to improve quality and reduce conflict or jealousy might also help reduce IPV within a relationship, without necessarily needing to end the relationship. There is increasing recognition that healthy relationship education can play an important role in preventing and responding to IPV (McKay et al., 2020); couples who have attended evidence-based relationship education programs have shown reduced aggression and controlling relationship behaviors (Antle et al., 2011; Markman et al., 1993), likely due to positive program effects on relationship quality and conflict management. Similarly, despite long-standing reluctance to use couple therapy to treat IPV out of fear of violent retaliation between partners, there is growing evidence that conjoint couple therapy can reduce IPV and improve relationship quality among couples experiencing situational violence (Karakurt et al., 2016). Tailored, SGM-affirmative relationship interventions (Pentel et al., 2021; Whitton et al., 2017), which have shown significant positive effects on conflict resolution and relationship quality, may represent a particularly appropriate approach to addressing IPV in this stigmatized and vulnerable group.

Importantly, though, we also observed associations between the relationship factors and IPV between-persons and within-persons across relationships. This suggests that, among SGM-AFAB youth, certain individuals and relationships may consistently be at elevated risk for IPV as a function of the conflict, jealousy, and general relationship health that characterize them. Accordingly, broad IPV prevention efforts would benefit from including not only conjoint couple interventions, but also individually-focused programs for teens, such as Dating Matters™, which target multiple individual- and relationship-level risk factors (Tharp, 2012). Such interventions may reduce individual SGM-AFAB youth’s risk for future IPV by guiding them to select appropriate partners, building their relationship skills can be used in all their relationships, and teaching skills for exiting conflictual and jealous relationships.

Acknowledgments

This study was supported by a grant from the National Institute of Child Health and Human Development (R01HD086170; PI: Whitton).

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