Help-Seeking for Severe Intimate Partner Violence Among Sexual and Gender Minority Adolescents and Young Adults Assigned Female at birth: A Latent Class Analysis

Abstract

Sexual and gender minority adolescents and young adults assigned female at birth (SGM-AFAB) report high rates of intimate partner violence (IPV) victimization. Despite adverse health outcomes of IPV, many survivors, particularly SGM-AFAB, do not seek help. This study (1) examined the proportion of SGM-AFAB who reported severe IPV victimization who sought help; (2) elucidated patterns of help-seeking facilitators and barriers; and (3) identified associations between sociodemographic characteristics, IPV victimization types, and minority stressors and latent classes of help-seeking facilitators and barriers. Participants included 193 SGM-AFAB (Mage = 20.6, SD = 3.4; 65.8% non-monosexual; 73.1% cisgender; 72.5% racial/ethnic minority; 16.6% annual household income $20,000 or less). Most participants who experienced severe IPV did not seek help (62.2%). Having a person or provider who was aware of the participant’s abusive relationship was the most common reason for seeking help (50; 68.5%). Minimizing IPV was the most common reason for not seeking help (103; 87.3%). Fewer than 5% of SGM-AFAB who experienced severe IPV and who did not seek help reported SGM-specific help-seeking barriers, including not wanting to contribute to negative perceptions of the LGBTQ community, not disclosing their SGM status, and perceiving a lack of tailored services. Help-seeking facilitators and barriers varied by sociodemographic characteristics. Three classes of help-seeking facilitators and two classes of help-seeking barriers emerged. SGM-AFAB subgroups based on sexual and gender identity, recent coercive control, and identity as IPV victims differed in latent classes. This study’s findings confirm SGM-AFAB IPV survivors’ low likelihood of seeking help. Our results also underscore the importance of continuing to bolster SGM-AFAB survivors’ access to trauma-informed, culturally sensitive, and affirming support. Further, multilevel prevention and intervention efforts are needed to reduce minimization of abuse and anticipatory judgment and blame among SGM-AFAB who hold multiple marginalized identities, experience coercive control, and identify as IPV victims.

Keywords

youth violence violence exposure sexuality domestic violence LGBTQ disclosure of domestic violence

Sexual and gender minority adolescents and young adults assigned female at birth (SGM-AFAB), including those who identify as cisgender women, transgender men, non-binary, or genderqueer (Dyar et al., 2020), are at increased risk for intimate partner violence (IPV) compared to cisgender heterosexual adolescents and young adults across sex assigned at birth (for a review, see Whitton et al., 2019). For instance, nationally representative studies found that IPV rates were higher among cisgender sexual minority female youth compared to cisgender heterosexual female youth (Scheer et al., 2021; Schwab-Reese et al., 2021). A recent meta-analysis highlighted that transgender and nonbinary individuals assigned female at birth (AFAB) were more likely than cisgender men and women to experience IPV (Peitzmeier et al., 2020). Compared to sexual and gender minority (SGM) youth assigned male at birth, SGM-AFAB are at heightened risk of IPV (Scheer, Edwards, et al., 2021; Schwab-Reese et al., 2021; Whitton et al., 2016). From an intersectionality framework (Crenshaw, 1989), multiple forms of stigma (e.g., heterosexism, sexism, cissexism) might synergistically drive IPV risk among SGM-AFAB (Whitton et al., 2019).

Consistent evidence demonstrates health consequences of IPV among SGM-AFAB (Decker et al., 2018; Scheer et al., 2021; Whitton et al., 2016). However, seeking help for IPV can improve health and even reduce risk of revictimization (Ameral et al., 2020). Further, most IPV research has focused on cisgender (heterosexual and sexual minority) women (Goldenberg et al., 2018) and most SGM research has focused on those assigned male at birth or treated SGM people monolithically (Calton et al., 2016; Dyar et al., 2020; Smalley et al., 2016). Given that SGM people face group-specific health risks and barriers to care (Smalley et al., 2016), research has called for more attention to disaggregated help-seeking patterns by SGM subpopulations (e.g., sexual minority women AFAB, transgender people AFAB, nonbinary people AFAB; Scheer et al., 2020). This study aims to address these limitations by examining help-seeking behavior, facilitators, and barriers among SGM-AFAB.

While social support networks and formal services are critical to improving the mental health and safety of those experiencing IPV, most IPV-exposed SGM youth, including SGM-AFAB, do not seek help. For instance, one study showed that while almost a third of SGM youth experienced IPV, most did not seek services (Scheer & Baams, 2021). Other findings suggest that only 18% to 35% of IPV-exposed SGM youth seek help (Sylaska & Edwards, 2015).

In the general population, IPV severity, including physical violence with a high probability of injuries, forced sexual intercourse, and coercive control, predicts help-seeking (Ansara & Hindin, 2010; Lysova & Dim, 2022). IPV severity also confers risk for domestic homicide (Sabri et al., 2014). Recent research has called for studies to examine IPV severity among vulnerable populations (Hardesty & Ogolsky, 2020; Stark & Hester, 2019). Yet, no studies have examined help-seeking rates among SGM-AFAB who report severe IPV. Further, most help-seeking research has focused on sources of help (e.g., formal vs. informal support) without assessing reasons that individuals exposed to severe IPV seek help from a particular source (i.e., facilitators) or do not seek help (i.e., barriers).

Help-Seeking Facilitators and Barriers

According to the health belief model (Rosenstock, 1974), help-seeking behavior is driven in part by individuals’ perceived benefits of seeking support (Skinner et al., 2015). In addition, the network-episode model (Pescosolido & Boyer, 2010) conceptualizes help-seeking facilitators as involving social networks, including social context and support systems. For instance, studies among IPV-exposed individuals in the general population have demonstrated that social network characteristics (e.g., being affirmed, trusting others not to take legal action) can facilitate help-seeking (Mapes & Cavell, 2021; Ravi et al., 2022). Knowing about SGM-specific forms of IPV (e.g., identity abuse; Dyar et al., 2021; Woulfe & Goodman, 2021) and providing affirmative support can promote help-seeking among SGM people (Ollen et al., 2017; Ravi et al., 2022).

The health belief model (Rosenstock, 1974) also hypothesizes that perceived barriers to seeking help impact people’s help-seeking behaviors (Henshaw & Freedman-Doan, 2009). Help-seeking barriers exist across individual (e.g., concerns about confidentiality), interpersonal (e.g., fears of retaliation), and structural levels (e.g., negative cultural beliefs about IPV victims) (Bundock et al., 2020; Overstreet & Quinn, 2013). Among SGM-AFAB, stigma-based minority stressors can create additional help-seeking barriers (Calton et al., 2016). For example, SGM survivors may anticipate rejection based on prior help-seeking experiences, or they may conceal their SGM status or IPV incident due to fears of being “outed” or perpetuating negative SGM stereotypes (Edwards et al., 2015; Ollen et al., 2017). Enacted stigma, including external sources of stress (e.g., providers’ biases, discriminatory shelter policies), also reduces SGM people’s likelihood of seeking help for IPV (Calton et al., 2016; Guadalupe-Diaz & Jasinski, 2016).

Variable- and Person-Centered Approaches to Modeling Help-Seeking

Prior studies examining help-seeking facilitators and barriers among IPV-exposed individuals have primarily relied on variable-centered approaches to examine the presence of each facilitator and barrier separately (Ameral et al., 2020; Ravi et al., 2022; Robinson et al., 2021). Other studies have dichotomized and grouped sources of help as either informal or formal (for a review, see Cheng et al., 2020). Compared to these variable-centered approaches, person-centered approaches, including latent class analysis (LCA), assume heterogeneity exists in help-seeking facilitators and barriers (Lanza & Rhoades, 2013). LCA can thus provide a broader understanding of how help-seeking facilitators and barriers cluster together among SGM-AFAB. LCA has been used in past research to understand help-seeking patterns across formal and informal supports and levels of service utilization (e.g., minimal use vs. substantial use) among IPV-exposed women in the general population (Ben-Porat, 2017; Cheng et al., 2020). Despite this promising line of inquiry, no studies have examined how help-seeking facilitators and barriers intersect to create typologies among SGM-AFAB who report severe IPV victimization.

Scholars have called for an intersectional understanding of IPV and related help-seeking among SGM populations, including SGM-AFAB (Decker et al., 2018; Edwards et al., 2015; Scheer et al., 2020; Whitton et al., 2019). Yet, there lacks information about whether SGM-AFAB’s probability of endorsing distinct combinations of help-seeking facilitators and barriers versus others varies across sociodemographic characteristics, IPV victimization type, and minority stressors (Ben-Porat, 2017; Cheng et al., 2020). Prior studies using variable-centered approaches have documented differences in help-seeking facilitators and barriers based on sociodemographic characteristics (e.g., race/ethnicity, immigration status) and IPV severity among women in general (Ben-Porat, 2017; Cheng et al., 2020; Wright et al., 2022) and among SGM populations broadly (Calton et al., 2016; Ravi et al., 2022; Robinson et al., 2021). No studies have examined whether latent classes of help-seeking barriers and facilitators vary based on identity as an IPV victim and exposure to minority stressors (e.g., internalized stigma, microaggressions, LGBTQ victimization) among SGM-AFAB who experienced severe IPV.

Aims of this study were to: (1) examine the proportion of SGM-AFAB with severe IPV victimization histories who sought help for IPV; (2) elucidate patterns of help-seeking facilitators and barriers; and (3) identify associations between sociodemographic characteristics, IPV victimization types, and minority stressors and latent classes of help-seeking facilitators and barriers. Findings may have important implications for improving access to high-quality support and reducing help-seeking barriers among SGM-AFAB who report severe IPV victimization.

Method

Participants and Procedures

Data are from FAB400, a study of 488 SGM-AFAB consisting of two cohorts: (1) a late adolescent cohort recruited in 2016 to 2017 (N = 400; 16–20 years old at baseline), and (2) a young adult cohort comprised of AFAB participants from a study of SGM youth that began in 2007 (N = 88; 23–32 years old at baseline in 2016–17). Participants were recruited using an incentivized snowball sampling approach. Eligibility criteria included being assigned female sex at birth; speaking English; and reporting same-gender sexual behavior, same-gender attractions, or sexual or gender minority identity (Swann et al., 2022). Potential participants were recruited via social media advertisements and directly through venues (e.g., SGM community organizations, health fairs). Advertisements contained information about the study’s purpose (e.g., to understand young LGBTQ people and their relationships) and specified that this study was recruiting those who were AFAB, an SGM person, and 16 to 20 years of age. From 2016 to 2017, all participants completed the baseline assessment and completed subsequent assessments every 6 months, totaling seven assessments across 3.5 years. Data were collected using computer-assisted self-interviews. The Institutional Review Board at Northwestern University approved study procedures, including a waiver of parental permission for those younger than 18 under 45 CFR 46, 408(c).

We used data from participants who endorsed any severe physical IPV, severe sexual IPV, severe coercive control, or physical injury by a partner across all assessments and who were asked whether they sought help for IPV (N = 193). Only participants who reported any severe physical IPV, severe sexual IPV, severe coercive control, or injury by a partner, including being physically injured, were asked whether they sought help (from any source) for IPV victimization. Data from the first timepoint were used if a participant both reported any severe IPV and answered help-seeking questions across multiple time points. Participants also indicated which partner was their “most significant partner.” Data from the most significant partner were used if more than one partner perpetrated IPV in a given assessment period.

Measures

Intimate partner violence

Coercive control was assessed with five items from the Coercive Behaviors Scale (CBS; Frankland & Brown, 2014) and three items from the 2010 National Intimate Partner and Sexual Violence Survey (NIPSVS; Black et al., 2011), adapted for SGM (Dyar et al., 2021). For all analyses, we created a binary variable indicating the presence of past-6-months coercive control (0 = no, 1 = yes). Participants who were considered to have experienced severe coercive control endorsed the presence of any two items from the coercive control scale from the NIPSVS (e.g., “[Partner name] threatened to hurt themselves or commit suicide when they were upset with me”) or who endorsed a frequency of at least three to five times in the past 6 months for any of the other six items on the coercive control victimization subscale of the CBS. LGBTQ-specific IPV was assessed with the five-item SGM-Specific IPV Tactics Scale (Dyar et al., 2021). A binary variable was created to indicate the presence of past-6-months LGBTQ-specific IPV (0 = no, 1 = yes). Physical, psychological, and sexual IPV were assessed with the Sexual and Gender Minority Conflict Tactics Scale (SGM-CTS2; Dyar et al., 2021). Response options ranged from 0 (never) to 7 (not in the past 6 months, but it did happen). We created three binary variables indicating the presence of past-6-months physical, psychological, and sexual IPV, respectively (0 = no, 1 = yes). Participants were considered to have experienced severe physical or sexual IPV (and thus were asked whether they sought help) if they endorsed at least one item from any severe physical IPV or sexual IPV subscales of the SGM-CTS2. Presence of injury by a partner was measured via any endorsement from the five-item injury subscale from the SGM-CTS2 (Dyar et al., 2021). IPV victim identity was assessed by asking participants, “Did you consider yourself a victim of intimate partner violence/dating violence/domestic violence or to have been abused in this relationship?” (0 = no, 1 = yes).

Help-seeking

Help-seeking was assessed by asking participants who reported severe IPV, “Did you try to get anyone to help you handle what your partner had done, keep them from doing it again, or get you away from your partner?” (0 = no, 1 = yes). Participants who sought help were asked, “Who did you go to for help first?” and “Who else did you go to for help?” Response options include therapist or counselor; police; hotline, school officials, or staff; doctor or health care provider; domestic violence assistance service or shelter; parents, LGBTQ friends, heterosexual/straight friends, or other family members or relatives. Participants who sought help were also asked, “What led you to select this person/service to help you?” and provided with nine help-seeking facilitators: “Person/service knew about my relationship,” “I am emotionally close to person/service/go to them for all my problems,” “I knew person/service would keep it confidential,” “Person/service was knowledgeable about relationship violence,” “Person/service knew I am LGBTQ,” “I could trust person/service not to judge me for my sexual orientation,” “I could trust person/service not to judge me for my gender identity,” “I knew I wouldn’t run into anyone I know,” and “other reasons” (0 = no, 1 = yes).

Participants who reported not seeking help were asked, “If you did not seek help, why not?” and could select all that applied from a list of 16 help-seeking barriers: “It wasn’t really ‘abuse’ so I didn’t need help,” “Because they might have judged me or blamed me for it,” “Because I didn’t think they could/would help,” “Because they might not have believed me or taken me seriously,” “If my partner found out, they would have been angry, hurt me, or hurt someone I love,” “I was worried they would not keep it confidential,” “I didn’t know who I could go to,” “I fought back so I might have gotten in trouble,” “I was worried I might lose housing,” “I didn’t want to contribute to negative perceptions of the LGBTQ community,” “Because I was not out,” “Because they may have disapproved of my sexuality,” “Those services were not for people my age,” “Those services were not meant for same-sex relationships,” “I was worried I might lose my child(ren),” and “other reasons” (0 = no, 1 = yes).

Minority stressors

Sexual orientation-related internalized stigma was assessed with the eight-item Desire to Be Heterosexual subscale (Puckett et al., 2017). Response options ranged from 1 (strongly disagree) to 4 (strongly agree). Items were averaged to create a mean score of past-6-months internalized stigma (Cronbach’s α = .88). Frequency of past-month sexual orientation-based microaggressions were assessed with 19 items from the Sexual Orientation Microaggression Inventory (Swann et al., 2016), along with four items that assessed AFAB-specific microaggressions. Response options ranged from 1 (not at all) to 5 (21–30 times [almost every day]). Items were averaged (Cronbach’s α = .92). Frequency of past-6-months LGBTQ victimization was assessed with the 10-item measure developed by Pilkington and D’Augelli (1995). Response options ranged from 0 (never) to 5 (more than ten times). Items were averaged (Cronbach’s α = .76). Higher scores indicated greater internalized stigma, a greater frequency of microaggressions, and a greater frequency of LGBTQ victimization, respectively.

Sociodemographic characteristics

Participants reported their age, sexual identity (gay, lesbian, bisexual, queer, unsure/questioning, straight/heterosexual, pansexual, asexual, not listed [please specify]), gender identity (male, female, transgender, gender non-conforming, genderqueer, non-binary, not listed [please specify]), race/ethnicity (American Indian or Alaskan Native, Asian, Black or African American, Native Hawaiian or Other Pacific Islander, White, other [please specify]), education (high school/equivalent degree or lower vs. greater than high school/equivalent degree), and income (annual income < $20,000 to > $80,000). Participants also reported if they identified as Hispanic or Latinx, regardless of race. Those who selected a Latinx ethnicity were classified as Latinx (National Institutes of Health, 2001).

Economic distress was assessed with the “Can’t make ends meet” subscale of the Economic Pressure Scale (Conger et al., 1999). Participants responded to three items (e.g., “I had difficulty paying my monthly bills”). Response options were 4- and 5-point Likert-type scales (e.g., 1 [Strongly disagree] to 5 [Strongly agree]. Responses were standardized and summed; a higher score indicates greater economic distress (Cronbach’s α = .78).

We recoded sexual identity as “monosexual (gay or lesbian)” (0), “non-monosexual (bisexual/pansexual)” (1), or “other” (2). SGM-AFAB who chose “female” were recoded as cisgender (0). SGM-AFAB who chose “male,” “transgender,” “gender non-conforming,” “genderqueer,” “non-binary,” or “not listed” were recoded as gender minority (1). We recoded participants as either White (0) or racial/ethnic minority (1).

Statistical Analysis

Descriptive statistics were used to characterize the analytic sample’s sociodemographic characteristics, presence of past-6-months IPV, and help-seeking. Bivariate analyses were used to examine associations between sociodemographic characteristics and help-seeking indicators.

Using the three-step latent class analytic approach (Bakk et al., 2013), we fit models for facilitators with 1 to 9 classes with our nine indicators of help-seeking facilitators and then fit models for barriers with 1 to 9 classes with our 16 indicators of help-seeking barriers. We specified a priori the following criteria to identify the most optimally fitting LCA models: relative fit, including low Log Likelihood, Akaike Information Criteria (AIC), Bayesian Information Criteria (BIC), and sample-size-adjusted BIC (aBIC); entropy > .80; class size; and interpretability (Lanza & Rhoades, 2013). Average posterior probabilities of class membership were used to examine class homogeneity (Nylund et al., 2007). Local independence assumption was assessed by examining bivariate residuals; direct effects were included to allow for dependent pairs of indicators with the highest residuals (Vermunt & Magidson, 2016).

We employed separate multinomial logistic regressions to model associations between sociodemographic characteristics with latent classes identified by the best-fitting LCA model, accounting for classification error (Bakk et al., 2013). Then, we used multinomial logistic regression to model associations between past-6-months IPV victimization type with latent classes and associations between minority stressors and latent classes.

Missing data ranged from 0 for age to 14 (7.3%) for economic distress. Missing data were handled using pairwise deletion. Descriptive statistics were conducted in SPSS 27 (IBM Corp., Armonk, NY). LCA and the bias-adjusted three-step LCA approach (Bakk et al., 2013) were implemented in Latent GOLD 5.1 (Vermunt & Magidson, 2016). We performed a post-hoc adjustment of p values using Benjamini–Hochberg procedures (Benjamini & Hochberg, 1995).

Results

Sample Description

Participants in the analytic sample (N = 193) were, on average, 20.62 years of age (SD = 3.42; range = 16.02–32.29; see Table 1). The entire analytic sample reported severe IPV. Most participants reported recent psychological IPV (68.4%). Most participants who experienced severe IPV did not seek help (62.2%); fewer sought help (37.8%). Of those who sought help, most accessed support from informal sources (84.1%); fewer accessed formal support (15.9%).

Table 1.

Frequencies of Study Variables of Analytic Sample (N = 193).

	M (SD)
Sociodemographic Characteristics
Age (Range: 16.02–32.29)	20.62 (3.42)
	n	%
Sexual identity
Gay or lesbian	37	19.2
Non-monosexual^a	127	65.8
Other^b	15	7.8
Gender identity
Cisgender women	141	73.1
Gender minority	38	19.7
Race/ethnicity
White	39	20.2
Racial/ethnic minority	140	72.5
Highest education
High school/equivalent degree or lower	100	51.8
Greater than high school/equivalent degree	79	40.9
Household income
<$20,000	32	16.6
$20,000–$39,999	44	22.8
$40,000–$49,000	25	13.0
$50,000–$59,999	19	9.8
$60,000–$69,999	14	7.3
$70,000–$79,999	9	4.7
>$80,000	34	17.6
Partner gender identity
Cisgender men	106	54.9
Cisgender women	57	29.5
Gender minority	27	14.0
Presence of past-6-months IPV victimization
Coercive control	115	59.6
LGBTQ-specific IPV	49	25.4
Physical IPV	75	38.9
Psychological IPV	132	68.4
Sexual IPV	83	43.0
Help-seeking for IPV victimization
No help-seeking for IPV victimization	120	62.2
Help-seeking for IPV victimization	73	37.8
	n	%
Source of support
Formal support sources^c	23	15.9
Informal support sources^d	122	84.1

Note. IPV = intimate partner violence; LGBTQ = lesbian, gay, bisexual, transgender, and queer. Percentages may not equal 100 due to missing data. Those who identified as straight/heterosexual also identified as gender minority and so were retained in the analyses. Range, mean, and standard deviation for age are reported.

Non-monosexual includes sexual and gender minority individuals assigned female at birth who identified as bisexual, queer, or pansexual.

Other includes sexual and gender minority individuals assigned female at birth who identified as asexual, questioning, straight/heterosexual, or an unlisted identity.

Formal support sources include therapist or counselor; police; hotline, school officials or staff (teachers or school psychologist, etc.); doctor or health care provider; or domestic violence assistance service or shelter.

Informal support sources include parents; LGBTQ friends; heterosexual/straight friends; other family members or relatives; other partners; Facebook; or co-workers.

Frequencies of Help-Seeking Facilitators and Sociodemographic Correlates

Among those who sought help, having support of people who were aware of participants’ relationships (50; 68.5%) was the most frequently endorsed help-seeking facilitator (see Table 2). Fewer participants endorsed seeking help because they knew that they would not see familiar people (9; 12.3%) and other reasons (write-ins, such as “She had also been in a relationship with this person and would understand” and “His knowledge of relationships, [and] specifically BDSM [bondage, discipline, dominance and submission, sadomasochism]”; 3; 4.1%). Write-in responses were categorized as “other reasons” and not qualitatively analyzed in this study.

Table 2.

Frequencies of Help-Seeking Facilitators and Barriers.

Help-Seeking Facilitators	Total Sample n = 73^a		Help-Seeking Barriers	Total Sample n = 118^b
Help-Seeking Facilitators	n	%	Help-Seeking Barriers	n	%
Person/service knew about my relationship	50	68.5	It wasn’t really “abuse” so I didn’t need help	103	87.3
I am emotionally close to person/service/go to them for all my problems	49	67.1	Other reasons	20	16.9
I knew person/service would keep it confidential	46	63.0	Because they might have judged me or blamed me for it	16	13.6
Person/service knew I am LGBTQ	31	42.5	Because I didn’t think they could/would help	12	10.2
I could trust person/service not to judge me for my sexual orientation	29	39.7	Because they might not have believed me or taken me seriously	11	9.3
Person/service was knowledgeable about relationship violence	21	28.8	If my partner found out, they would have been angry, hurt me, or hurt someone I love	5	4.2
I could trust person/service not to judge me for my gender identity	19	26.0	I was worried they would not keep it confidential	9	4.7
I knew I wouldn’t run into anyone I know	9	12.3	I didn’t know who I could go to	7	5.9
Other reasons	3	4.1	I fought back so I might have gotten in trouble	2	1.7
			I was worried I might lose housing	3	2.5
			I didn’t want to contribute to negative perceptions of the LGBTQ community	2	1.7
			Because I was not out	2	1.7
			Because they may have disapproved of my sexuality	1	0.8
			Those services were not for people my age	2	1.7
			Those services were not meant for same-sex relationships	1	0.8
			I was worried I might lose my child(ren)	0	0.0

Note. ^aParticipants who sought help and who endorsed one or more help-seeking facilitators (i.e., reasons that led participants to seek help from a particular source).

Participants who did not report seeking help and who endorsed one or more help-seeking barriers.

Frequencies of Help-Seeking Barriers and Sociodemographic Correlates

Among those who did not seek help, minimizing IPV (i.e., believing that their experiences were not abuse; 103; 87.3%) was the most frequently endorsed help-seeking barrier (see Table 2). Fewer participants endorsed not seeking help because specific services were not meant for same-sex relationships (1; 0.8%) and because they feared losing their children (0; 0%).

Model Fit Assessment and Model Comparisons of Help-Seeking Facilitators Classes

For SGM-AFAB who sought help, the two-class model of help-seeking facilitators allowing for local dependencies had the lowest AIC and BIC while the seven-class solution had the lowest aBIC (see Table 3). Overall, the AIC and aBIC decreased in the one- through two-class solutions, increased in the two- through three-class solutions, and decreased again in the three-class solution allowing for local dependencies. Entropy was relatively high in the three-class model of help-seeking facilitators allowing for local dependencies (0.86; Bakk et al., 2013). Based on these criteria and class interpretability, the three-class model of help-seeking facilitators allowing for local dependencies was deemed optimal (Nylund et al., 2007).

Table 3.

Model Fit Indices and Model Comparison Statistics for Mixture Modeling of Help-Seeking Facilitators and Barriers.

	Log Likelihood	Akaike Information Criterion	Bayesian Information Criterion	Sample-Size Adjusted Bayesian Information Criterion	Entropy	Number of Free Parameters
Number of facilitators classes^a
1	−364.06	746.12	766.73	738.37	N/A	9
2	−319.15	676.30	719.82	659.95	0.90	19
2DE	−308.74	661.48	711.87	642.55	0.89	22
3	−306.52	671.05	737.47	646.09	0.85	29
3DE^c	−302.24	664.48	733.20	638.67	0.86	30
4	−298.64	675.28	764.61	641.72	0.85	39
5	−290.82	679.65	791.88	637.48	0.87	49
6	−284.51	687.02	822.16	636.24	0.89	59
7	−278.75	695.51	853.55	636.13	0.91	69
8	−273.81	705.62	886.57	637.64	0.91	79
9	−270.95	719.90	923.75	643.31	0.91	89
Number of barriers classes^b
1	−365.97	763.94	808.28	757.70	N/A	16
2^c	−323.71	713.43	804.86	700.54	0.83	33
2DE	−293.08	662.16	767.44	647.32	0.83	38
3	−300.37	700.75	839.28	681.22	0.83	50
3DE	−282.93	677.87	833.03	656.00	0.86	56
4	−289.89	713.79	899.42	687.62	0.91	67
5	−283.89	735.78	968.52	702.98	0.91	84
6	−275.54	753.08	1032.92	713.63	0.79	101
7	−269.94	775.89	1102.83	729.80	0.91	118
8	−261.89	793.78	1167.82	741.05	0.94	135
9	−266.45	836.90	1258.04	777.53	0.71	152

Note. DE = direct effects (i.e., addition of residual associations). Each criterion is based upon the Log-Likelihood.

Sexual and gender minorities assigned female at birth who reported severe intimate partner violence and who sought help.

Sexual and gender minorities assigned female at birth who reported severe intimate partner violence and who did not report seeking help.

Model selected as providing the best fit, as demonstrated by the relatively small Akaike Information Criterion, Bayesian Information Criterion, relatively high entropy, relatively few numbers of free parameters, and interpretability.

For the help-seeking facilitators LCA, Class 1 was characterized by low probabilities across help-seeking facilitators (“No Specified Facilitator Class”; n = 26; 35.6%). Class 2 was characterized by high probabilities of SGM-AFAB seeking help because the person or service provider was aware of their abusive relationship, had pre-existing supportive relationships with participants, and would keep confidentiality (“Interpersonal Closeness and Confidentiality Class”; n = 25; 34.2%). Finally, Class 3 was characterized by high probabilities of SGM-AFAB seeking help because the person or service provider was aware of their abusive relationship, had pre-existing supportive relationships with participants, would keep confidentiality, and was aware and affirming of participants’ sexual identity or gender identity (“Interpersonal Closeness, Confidentiality, and LGBTQ-Affirmative Class”; n = 22; 30.1%).

Predictors of Help-Seeking Facilitators Classes

Multinomial regression models revealed that compared to SGM-AFAB who identified as gay or lesbian, SGM-AFAB who reported another sexual identity (e.g., questioning) were four to five times more likely to be in the “Interpersonal Closeness and Confidentiality Class” and the “Interpersonal Closeness, Confidentiality, and LGBTQ-Affirmative Class” relative to the “No Specified Facilitator Class” (see Table 4). Gender minority AFAB were 15 times more likely than cisgender SGM-AFAB to be in the “Interpersonal Closeness, Confidentiality, and LGBTQ-Affirmative Class” relative to the “No Specified Facilitator Class.”

Table 4.

Multinomial Logistic Regression Models of Sociodemographic Correlates of Help-Seeking Latent Classes Among Sexual and Gender Minority Individuals Assigned Female at Birth.

	Help-Seeking Facilitators Latent Classes (n = 71)						Help-Seeking Barriers Latent Classes (n = 108)
	Class 2 (“Interpersonal Closeness and Confidentiality Class”; n = 25; 34.2%)			Class 3 (“Interpersonal Closeness, Confidentiality, and LGBTQ-Affirmative Class”; n = 22; 30.1%)			Class 2 (“Minimization of Abuse and Anticipatory Judgment or Blame Class”; n = 17; 14.4%)
	aOR (95% CI)	FDR-adjusted p-value	SE	aOR (95% CI)	FDR-adjusted p-value	SE	aOR (95% CI)	FDR-adjusted p-value	SE
Sociodemographic characteristics
Age	0.84 (0.63, 1.12)	0.220	0.15	0.86 (0.65, 1.14)	0.175	0.14	0.99 (0.82, 1.20)	0.467	0.09
Sexual identity
Gay or lesbian	ref			ref			ref
Non-monosexual	1.48 (0.31, 6.97)	0.374	0.79	2.21 (0.41, 11.81)	0.176	0.85	2.22 (0.39, 12.75)	0.151	0.89
Other	4.25 (1.56, 6.94)	0.006	1.37	5.21 (1.59, 8.82)	0.033	1.72	1.37 (0.11, 17.06)	0.467	1.29
Gender identity
Cisgender women	ref			ref			ref
Gender minority	2.04 (0.16, 26.38)	0.374	1.31	15.75 (2.01, 123.59)	0.024	1.05	0.58 (0.15, 2.31)	0.351	0.70
Race/ethnicity
White	ref			ref			ref
Racial/ethnic minority	0.99 (0.18, 5.54)	0.499	0.87	0.43 (0.09, 2.06)	0.175	0.80	0.53 (0.13, 2.21)	0.351	0.72
Economic distress	0.55 (0.23, 1.30)	0.220	0.44	0.48 (0.21, 1.11)	0.082	0.43	1.25 (0.69, 2.26)	0.351	0.38

Note. aOR = adjusted odds ratio; CI = confidence interval; ref = reference group, SE = standard error. All models controlled for cohort and used pairwise deletion. FDR-adjusted refers to the Benjamini–Hochberg procedure used to correct for the false discovery rate. Boldface type indicates a significant aOR. Omitted (reference) category is Class 1 (“No Specified Facilitator Class”) for latent classes of help-seeking facilitators (n = 26; 35.6%) and Class 1 (“Minimization of Abuse Class”) for latent classes of help-seeking barriers (n = 101; 85.6%).

SGM-AFAB who reported past-6-months coercive control were 19 times more likely than those who did not report recent coercive control past-6-months coercive control to be in the “Interpersonal Closeness and Confidentiality Class” relative to the “No Specified Facilitator Class” (see Table 5). SGM-AFAB who identified as victims of IPV were less likely than those who did not identify as victims of IPV to be in the “Interpersonal Closeness and Confidentiality Class” relative to the “No Specified Facilitator Class.” Latent classes of help-seeking facilitators did not vary by past-6-months psychological, physical, sexual, or LGBTQ-specific IPV, or minority stressors.

Table 5.

Multinomial Logistic Regression Models of Intimate Partner Violence and Minority Stressors Correlates of Help-Seeking Latent Classes Among Sexual and Gender Minority Individuals Assigned Female at Birth.

	Help-Seeking Facilitators Latent Classes						Help-Seeking Barriers Latent Classes
	Class 2 (“Interpersonal Closeness and Confidentiality Class”; n = 25; 34.2%)			Class 3 (“Interpersonal Closeness, Confidentiality, and LGBTQ-Affirmative Class”; n = 22; 30.1%)			Class 2 (“Minimization of Abuse and Anticipatory Judgment or Blame Class”; n = 17; 14.4%)
	aOR (95% CI)	FDR-adjusted p-value	SE	aOR (95% CI)	FDR-adjusted p-value	SE	aOR (95% CI)	FDR-adjusted p-value	SE
Model 1: Past-6-months IPV victimization
Sample size	n = 71						n = 108
Psychological IPV
No psychological IPV	ref			ref			ref
Psychological IPV	0.27 (0.03, 2.11)	.159	1.04	0.48 (0.06, 3.76)	.244	1.05	0.01 (0.01, 1.27)	.058	1.22
Physical IPV
No physical IPV	ref			ref			ref
Physical IPV	0.09 (0.01, 2.08)	.132	1.62	0.29 (0.05, 1.77)	.171	0.92	1.29 (0.23, 7.13)	.387	0.87
Sexual IPV
No sexual IPV	ref			ref			ref
Sexual IPV	1.92 (0.23, 15.74)	.272	1.07	0.15 (0.02, 1.45)	.171	1.16	5.91 (0.84, 41.31)	.058	0.99
Coercive control
No coercive control	ref			ref			ref
Coercive control	19.55 (1.18, 325.10)	.030	1.43	0.39 (0.04, 3.92)	.244	1.18	8.64 (1.19, 62.57)	.048	1.01
LGBTQ-specific IPV
No LGBTQ-specific IPV	ref			ref			ref
LGBTQ-specific IPV	2.48 (0.29, 21.38)	.244	1.09	4.12 (0.41, 41.45)	.171	1.18	0.22 (0.02, 2.04)	.116	1.13
IPV victim identity
Does not identify as an IPV victim	ref			ref			ref
Identifies as an IPV victim	0.11 (0.02, 0.84)	.030	1.02	3.49 (0.53, 23.03)	.171	0.96	12.51 (2.03, 76.87)	.018	0.93
Model 2: Minority stressors
Sample size	n = 70						n = 107
Internalized stigma	0.97 (0.23, 4.14)	.481	0.74	0.68 (0.17, 2.68)	.293	0.70	1.11 (0.43, 2.88)	.441	0.48
Microaggressions	0.31 (0.09, 1.15)	.120	0.68	0.67 (0.21, 2.13)	.249	0.59	0.19 (0.02, 2.55)	.161	1.31
LGBTQ victimization	2.39 (0.45, 4.18)	.211	1.43	2.10 (0.15, 30.41)	.293	0.74	3.75 (0.75, 6.74)	.021	1.53

Note. IPV = intimate partner violence; aOR = adjusted odds ratio; CI = confidence interval; ref = reference group. All models controlled for sexual identity, gender identity, and cohort, and used pairwise deletion. FDR-adjusted refers to the Benjamini–Hochberg procedure used to correct for the false discovery rate. Boldface type indicates a significant aOR. Omitted (reference) category is Class 1 (“No Specified Facilitator Class”) for latent classes of help-seeking facilitators (n = 26; 35.6%) and Class 1 (“Minimization of Abuse Class”) for latent classes of help-seeking barriers (n = 101; 85.6%).

Model Fit Assessment and Model Comparisons of Help-Seeking Barriers Classes

For SGM-AFAB who did not report seeking help, the two-class solution allowing for local dependencies had the lowest AIC, BIC, and aBIC (see Table 3). Further, the AIC and aBIC decreased in the one- through two-class solutions. Entropy was relatively high in the two-class solution (0.83; Bakk et al., 2013). As such, the two-class model of help-seeking barriers was deemed optimal based on these criteria and class interpretability.

For the help-seeking barriers LCA, Class 1 was characterized by a high probability of SGM-AFAB not seeking help because they minimized IPV (“Minimization of Abuse Class”; n = 101; 85.6%). Class 2 was characterized by a high probability of SGM-AFAB not seeking help because they minimized IPV and anticipated being judged or blamed for their IPV victimization (“Minimization of Abuse and Anticipatory Judgment or Blame Class”; n = 17; 14.4%).

Predictors of Help-Seeking Barriers Classes

In multinomial regression models, sociodemographic characteristics did not predict latent classes of help-seeking barriers (see Table 4). SGM-AFAB who reported recent coercive control were eight times more likely than those who did not report to be in the “Minimization of Abuse and Anticipatory Judgment or Blame Class” relative to the “Minimization of Abuse Class” (see Table 5). SGM-AFAB who identified as victims of IPV were 12 times more likely than those who did not identify as victims of IPV to be in the “Minimization of Abuse and Anticipatory Judgment or Blame Class” relative to the “Minimization of Abuse Class.” Latent classes of help-seeking barriers did not vary by other IPV forms (e.g., physical IPV) or minority stressors.

Discussion

Extending previous research (Calton et al., 2016; Robinson et al., 2021; Scheer et al., 2020), the current study documented that the majority of SGM-AFAB who experienced severe IPV victimization did not seek help. Having a person or provider who was aware of the participant’s abusive relationship was the most common reason for seeking help while minimizing IPV was the most common reason for not seeking help among SGM-AFAB. Findings also revealed three distinct combinations of help-seeking facilitators and barriers among SGM-AFAB, indicating a novel contribution to the literature. SGM-AFAB differed in their likelihood of being in classes characterized by help-seeking facilitators and barriers based on sociodemographic characteristics and IPV victimization type but not minority stressors.

Our findings build on extant research by showing that more than half of SGM-AFAB who reported seeking help did so because they could identify specific people—mostly informal support sources—with whom participants were close, who were aware of participants’ abusive relationship, and who would keep IPV disclosure confidential. Indeed, IPV interventions involving people with whom SGM-AFAB have a close relationship (i.e., a “network oriented” approach) can promote help-seeking behavior (Goodman & Smyth, 2011; Ogbe et al., 2020).

Notably, among SGM-AFAB who sought help, only 30% of participants reported awareness and affirmation of their sexual or gender identity as help-seeking facilitators. Some SGM-AFAB survivors who experience severe IPV might prioritize seeking help from people who could provide participants with crisis management support or help to create a safety plan as opposed to those who are SGM-affirmative. Still, awareness and affirmation of SGM identities are critical to engaging SGM people in care (Klein & Golub, 2020; Robinson et al., 2021). Thus, it is critical that support sources affirm SGM-AFAB participants’ SGM status while also addressing immediate safety concerns to effectively meet the needs of SGM-AFAB survivors.

Findings also suggest some demographic differences in factors that facilitate IPV help-seeking among SGM-AFAB. Specifically, SGM-AFAB with nontraditional sexual identities (e.g., questioning, an unlisted identity) were more likely than gay or lesbian AFAB to seek help from a source with whom they had a pre-existing relationship, who was aware of their abusive relationship, and who would keep confidentiality. SGM-AFAB who are uncertain about or who question their identities may face unique stereotypes (e.g., that their identities are not legitimate or stable) and discrimination from both heterosexual and SGM youth, which may increase identity concealment and overall health burden in this population (Borders et al., 2014). As such, confidentiality and interpersonal closeness might be important when considering seeking help following instances of IPV particularly among SGM-AFAB with nontraditional sexual identities.

Similarly, interpersonal closeness, confidentiality, and affirmation/awareness of their SGM identity were salient facilitators for gender minority but not for cisgender SGM-AFAB. Identity affirmation/awareness might be especially important facilitators of help-seeking among gender minority AFAB given their increased risk of IPV and stigma-based stressors compared to cisgender sexual minority AFAB (Scheer, Edwards, et al., 2021). Further, our study is the first to show that interpersonal closeness and confidentiality were particularly important help-seeking facilitators among SGM-AFAB who reported recent coercive control and who identified as IPV victims.

Strikingly, among SGM-AFAB who experienced severe IPV victimization and who did not seek help, over 87% reported not seeking help because they minimized their experiences of abuse. Minimizing IPV deters survivors from attaining effective help (Kennedy et al., 2018) and is a common coping strategy employed in response to IPV and reinforced by disclosure recipients who discredit survivors (Overstreet et al., 2019). Among SGM people, minimizing IPV is largely shaped by heteronormative depictions of IPV (e.g., “battered women”; Donovan & Barnes, 2019; Kurdyla et al., 2019). Such messages may be internalized by SGM-AFAB, contributing to SGM-AFAB idealizing abusive relationships, making it difficult to recognize their experiences as abuse, and hindering help-seeking (Calton et al., 2016; Kurdyla et al., 2019). Formal and informal support sources might help SGM-AFAB to adapt more empowering self-schemas and reduce self-invalidation (Pachankis et al., 2022). Tailored violence prevention programming (e.g., campaigns) is needed to raise awareness about public health burdens of SGM IPV and to change norms condoning violence against SGM-AFAB (McCauley et al., 2018).

Conversely, fewer than 5% of SGM-AFAB who experienced severe IPV victimization but who did not seek help reported SGM-specific help-seeking barriers, including not wanting to contribute to negative perceptions of the LGBTQ community, not disclosing their SGM status, fearing support sources disapproving their sexuality, and perceiving a lack of tailored and affirming services. Studies have shown that IPV-exposed SGM individuals do not seek help because of experiences of stigma, anticipation of rejection, and fears of perpetuating negative stereotypes about SGM people (Calton et al., 2016; Edwards et al., 2015; Ollen et al., 2017). Moreover, the low endorsement across SGM-specific barriers in this study could be because nearly two-thirds of the sample who sought help were in classes demarcated by interpersonal closeness, suggesting that SGM-AFAB are likely to seek help from affirming informal supports.

In addition to minimizing abuse, SGM-AFAB who experienced coercive control and who identified as IPV victims did not seek help because of anticipated judgment/blame. Less visible IPV forms, such as coercive control, compared to those that may be more visible, may influence perceived severity of IPV and thus lower help-seeking behavior (Frankland & Brown, 2014). Moreover, studies have demonstrated that individual and social attitudes toward IPV survivors (e.g., victim-blaming, deservingness beliefs) influences help-seeking (Overstreet et al., 2019).

Help-seeking facilitators and barriers classes did not vary across minority stressors measured in this study (i.e., internalized stigma, microaggressions, LGBTQ victimization). That is, regardless of levels of proximal or distal minority stressors, SGM-AFAB report similar reasons for deciding whether to seek help. Future research should consider investigating potential moderators of the association between minority stressors and help-seeking facilitators and barriers classes, including stigma-related stress reactions (e.g., social isolation, emotion dysregulation, avoidance) to help clarify for whom this association might be present. In addition, it is possible that structural minority stressors (e.g., anti-SGM structural stigma, gender-based structural stigma) could distinguish between latent classes of facilitators in this population.

Limitations and Future Directions

Limitations should be noted. Data were cross-sectional and measures used inconsistent timeframes, limiting our ability to detect temporal sequencing among variables. Data from the first timepoint assessing help-seeking behavior were used given that not all participants provided answers to the help-seeking question across time points. In addition, potential misclassification and under-reporting of IPV victimization and help-seeking might have biased results. The study used retrospective self-report measures and did not include measures of access to or satisfaction with help-seeking. This study did not distinguish latent classes by support source, which could have masked differences in facilitators and barriers by source of support. Whether these findings generalize to older SGM-AFAB, less significant relationships, and SGM assigned male at birth is unknown. Also, our measures did not include transgender-specific or intersectional stressors, or animal cruelty perpetrated by partners. Given that 19.7% of our sample identified as gender minority, we did not have enough power to test transgender-specific stress effects on classes. Our small sample size may have contributed to large standard errors and confidence intervals.

We also note future research directions. First, research should examine whether different mechanisms (e.g., endorsement of gender role norms, ambivalence in identifying as an IPV victim) influence help-seeking facilitators and barriers. Future studies could respond to calls for research to examine help-seeking patterns among SGM-AFAB among those who had witnessed animal cruelty (Riggs et al., 2021). Research should also assess associations between IPV victim identity centrality (i.e., perceiving identity as IPV victims as important to self-concept) or salience (i.e., perceiving identity as IPV victims as relevant; Overstreet et al., 2019) and help-seeking barriers classes among SGM-AFAB. Research is also needed to understand IPV-exposed SGM-AFAB participants’ goals for help-seeking (e.g., to reduce symptoms vs. leave abusive relationships) to develop tailored prevention and intervention efforts for this population. Time-series studies might consider assessing help-seeking facilitators and barriers over time and examining the timing of SGM-AFAB participants’ IPV exposure and help-seeking.

Conclusion

This study highlights the large proportion of SGM-AFAB who experience severe IPV but do not seek help; elucidates heterogeneity in factors that facilitate and represent barriers to IPV help-seeking among SGM-AFAB; and identifies sexual and gender identity, coercive control, and identity as an IPV victim as correlates of latent classes of help-seeking facilitators and barriers. Our findings underscore the need to improve IPV-related care engagement and access to affirming and nonjudgmental support among SGM-AFAB, particularly those who hold multiple marginalized identities, who experience coercive control, and who identify as IPV victims. Results also highlight research, clinical, and public health priorities, including promoting campaigns that raise awareness of SGM IPV rates and patterns, fostering a “network oriented” approach to providing services for SGM-AFAB, and reducing self-blame among SGM-AFAB.

Footnotes

Declaration of Conflicting Interests

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

Funding

The author(s) disclosed receipt of the following financial support for the research and/or authorship of this article: This study was supported by a grant from the National Institute of Child Health and Human Development (Grant No. R01HD086170; PI: Whitton). Dr. Jillian R. Scheer acknowledges support from the National Institute on Alcohol Abuse and Alcoholism grant under K01AA028239. Cory J. Cascalheira is supported as a RISE Fellow by the National Institutes of Health (R25GM061222). The content of this article is solely the responsibility of the authors and does not necessarily reflect the views of the National Institutes of Health or the National Institute of Child Health and Human Development. We thank Christina Dyar, Parks Dunlap, Jazz Stephens, Arielle Zimmerman, Kitty Beuhler, Greg Swann, Shariell Crosby, Kai Korpeck, Deborah Capaldi, and Brian Mustanski for their assistance with the larger study. We also thank the FAB400 participants for their invaluable contributions to understanding the health of the sexual and gender minority community.

ORCID iD

Jillian R. Scheer

Author Biographies

Jillian R. Scheer, PhD, is a licensed counseling psychologist, the Cobb-Jones Professor of Clinical Psychology, and an Assistant Professor of Clinical Psychology in the Department of Psychology at Syracuse University. Dr. Scheer’s research focuses on understanding and addressing co-occurring epidemics (e.g., violence exposure, minority stress, hazardous drinking, PTSD) surrounding sexual minority women and gender minority people.

Margaret Lawlace, MA, is a doctoral student in clinical psychology at the University of Cincinnati. Her research focuses on intimate partner violence in minoritized populations, its mental health consequences, and cultural sources of resilience

Cory J. Cascalheira, BA, is a doctoral student of counseling psychology at New Mexico State University and a research project coordinator at Syracuse University. Cascalheira’s research aims to (1) to examine stigma-based individual, interpersonal, and structural mechanisms conferring risk for SGM health disparities (e.g., substance misuse); and (2) to apply computational methods (i.e., artificial intelligence) to expand the scientific understanding of theory-driven constructs (e.g., minority stress) pertinent to SGM wellbeing.

Michael E. Newcomb, PhD, is an Associate Professor in the Department of Medical Social Sciences and the Institute for Sexual and Gender Minority Health and Wellbeing at Northwestern University. He is the Director of the THRIVE Center for Translational Science in Sexual and Gender Minority Health. His research focuses on health disparities impacting SGM youth, including HIV, substance use, and mental health, with an emphasis on the role of romantic relationships in ameliorating or exacerbating health problems.

Sarah W. Whitton, PhD, is a professor in the Department of Psychology at the University of Cincinnati and director of the Today’s Couples and Families Research Program. Her research is primarily focused on the mental health and close relationships of individuals in marginalized groups, particularly sexual and gender minorities.

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