Associations Between Latent Classes of Trauma Exposure and Minority Stressors and Substance Use Among Cisgender Sexual Minority Women

Abstract

Psychosocial stressors (e.g., minority stressors, trauma exposure) profoundly impact sexual minority women’s (SMW’s) risk of alcohol and other drug (AOD) use. However, research has not examined whether there are distinct typologies (i.e., patterns) of psychosocial stressors and whether these vary based on sociodemographic characteristics or are differentially associated with AOD outcomes (e.g., alcohol dependence) among SMW. This study aimed to identify latent classes of SMW reporting distinct typologies of psychosocial stressors and examine predictors and outcomes of latent classes of psychosocial stressors among SMW. Participants included a community sample of 602 SMW (M_age = 39.9, SD = 14.0; 74.0% lesbian; 37.4% White, 36.6% Black, 22.3% Latinx; 26.6% annual income ≤$14,999). Latent class analysis was used to identify typologies of psychosocial stressors. Regression analyses were employed to examine sociodemographic predictors and AOD outcomes of class membership. Three classes of psychosocial stressors emerged. Participants in Class 1 were likely to report relatively low adversity. SMW in Class 2, who reported childhood physical abuse (CPA), severe childhood sexual abuse, and adult physical assault, were vulnerable to discrimination and stigma consciousness. A distinct subgroup of SMW (Class 3) was at heightened risk of CPA, adult sexual assault (ASA), and stigma consciousness. Older SMW, Black SMW, and SMW with lower social support were more likely to be in classes characterized by higher adversity. Older SMW were at disproportionate risk of CPA and ASA. Different combinations of psychosocial stressors were uniquely associated with AOD outcomes. Findings underscore the importance of considering within-group heterogeneity in SMW’s differential risk of psychosocial stressors and AOD outcomes. Routine screening of psychosocial stressors across several dimensions, brief interventions targeting AOD outcomes, and policies mitigating structural drivers of SMW’s increased risk of trauma and minority stressors may be especially important for older SMW, Black SMW, and SMW who lack social support.

Keywords

sexual minority women alcohol and other drug use latent class analysis minority stressors trauma exposure

Cisgender sexual minority women (SMW; e.g., lesbian, bisexual) are at heightened risk of negative alcohol and other drug (AOD) outcomes, such as alcohol use disorder, cannabis use, and illicit polydrug use (use of at least two illicit substances) (Evans-Polce et al., 2020; Hughes et al., 2020; McCabe, Engstrom, et al., 2022; Schuler & Collins, 2020). For instance, studies using data from national surveys have shown that SMW are more likely than heterosexual women to report heavy episodic drinking (HED), and cannabis, illicit polydrug, and heroin use (Evans-Polce et al., 2020; McCabe, Engstrom, et al., 2022). These risks vary across sociodemographic characteristics (Hughes et al., 2020; Schuler & Collins, 2020). For example, bisexual women have elevated rates of negative AOD outcomes compared to lesbian/gay women (Schuler & Collins, 2020). Within-group differences in AOD outcomes may result from SMW’s differential exposure to psychosocial stressors, such as trauma and minority stressors (Cerezo & Ramirez, 2020; Dyar et al., 2021; McCabe et al., 2022). Psychosocial stressor exposure varies in severity, timing, context, and type (Keyes et al., 2011). To date, no research has examined whether patterns—or typologies—of psychosocial stressors across these stress-exposure dimensions emerge among SMW and whether typologies are differentially associated with SMW’s sociodemographic characteristics and AOD outcomes.

Research findings highlight that SMW are at heightened risk of trauma across the lifespan, including childhood sexual abuse (CSA), childhood physical abuse (CPA), and intimate partner violence (IPV) (McCabe, Hughes, et al., 2022; Porsch et al., 2022; Scheer et al., 2022). For instance, one study using population-based data demonstrated that SMW were 8 to 14 times more likely than heterosexual women to experience recent IPV (Scheer et al., 2022). Another recent study using nationally representative data found that 30.6% of bisexual and 17.8% of lesbian women reported at least two types of CSA compared to 9.8% of heterosexual women (McCabe, Hughes, et al., 2022). Societal stigma toward same-sex sexuality may help explain SMW’s disproportionate risk of trauma relative to heterosexual women (McCabe, Hughes, et al., 2022; McLaughlin et al., 2012; Scheer et al., 2022). That is, in addition to general stressors, sexual minority individuals experience unique and chronic sexual minority-related stressors (i.e., minority stress; Brooks, 1981; Meyer, 2003). Minority stressors range from the interpersonal to the structural and are associated with subjective processes (e.g., internalized stigma beliefs) and AOD outcomes (Brooks, 1981; Hughes et al., 2020; Meyer, 2003). There is a strong need to develop integrative models that examine the confluence of trauma and minority stressors (i.e., psychosocial stressors; Evans-Polce et al., 2020; Fitzpatrick et al., 2020) as it remains unknown how stressors intersect to create typologies and may be differentially associated with AOD use among SMW.

Psychosocial stressors may synergistically erode SMW’s health by spiking SMW’s stress response systems and overwhelming coping resources (i.e., allostatic load; Juster et al., 2019). Persistent and chronic activation of the stress response system leads to cumulative “wear and tear” that can become maladaptive and increase risk of negative AOD outcomes (Koob & Le Moal, 2001). The association between psychosocial stressors and negative AOD outcomes among SMW is well established (Dyar et al., 2021; McCabe, Hughes, et al., 2022; Scheer et al., 2021). Repeated exposure to psychosocial stressors can have lasting effects on stress reactivity by sensitizing victimized individuals to future stressors (Nurius et al., 2013). Yet, research has yet to examine simultaneously the overlapping effects of multiple stressors among SMW.

Modeling Psychosocial Stressors With Latent Class Analysis

Most extant research investigating psychosocial stressors and health outcomes among SMW have relied on variable-centered approaches (Cerezo & Ramirez, 2020; McCabe, Hughes, et al., 2022; McCabe et al., 2019; Sutter et al., 2019). These approaches have typically been used to assess the presence of each stressor separately, to differentiate the impact of minority stressors and trauma among SMW by controlling for a particular stressor, or to categorize sources of psychosocial stressors (e.g., anti-gay vs. non-identity-based assault; Cerezo & Ramirez, 2020; McCabe, Hughes, et al., 2022; Sutter et al., 2019). Examining the behavioral health impact of psychosocial stressors using this sort of methodological approach may fail to capture complex, multivariate patterns of stressors across various dimensions, and resultant risk for AOD use.

Compared to variable-centered approaches, person-centered approaches (e.g., latent class analysis [LCA]) can provide a broader understanding of how psychosocial stressors cluster among SMW. Person-centered approaches assume heterogeneity in psychosocial stressors (Lanza & Rhoades, 2013) and thus are well suited for studying how SMW group into homogenous, mutually exclusive subsets of shared psychosocial stressor classes (Lanza & Rhoades, 2013). Previous research has used LCA to understand victimization and perpetration typologies among sexual and gender minority populations (Kassing et al., 2021; Layland et al., 2022; Scheer et al., 2021; Sutter et al., 2019; Talley et al., 2022). Fewer studies have used person-centered methods to uncover homogenous subgroups of sexual minority people characterized by shared minority stressors (Layland et al., 2022; Puckett et al., 2017; Shramko et al., 2018; Talley et al., 2022). No studies have used LCA to examine complexity of trauma and minority stressors across different dimensions or associations between classes of stressors and AOD use among SMW.

Prevention scholars have called for intersectional approaches (Bowleg et al., 2003) to identify disparities in psychosocial stressors among sexual and gender minority people, including SMW (Calabrese et al., 2015; Cerezo & Ramirez, 2020). Yet, information about underlying subgroups of SMW across sociodemographic characteristics who have a high probability of endorsing multiple psychosocial stressors is lacking. Prior studies using variable-centered approaches have documented that younger age, bisexual identity, racial/ethnic minority identity, lower income, and lower social support are associated with SMW’s elevated exposure to minority stressors and trauma (Calabrese et al., 2015; Feinstein & Dyar, 2017; Puckett et al., 2017). Identifying social determinants of latent classes of psychosocial stressors can help determine specific clinical and public health efforts to reach vulnerable subgroups of SMW.

This study’s aims were to: (a) uncover classes of SMW reporting distinct patterns of psychosocial stressors, (b) examine associations between sociodemographic characteristics and classes of psychosocial stressors, and (c) identify associations between class membership and SMW’s AOD outcomes. Findings may advance disparity-focused, within-group research seeking to assess unique configurations of psychosocial stressors and associated behavioral health outcomes.

Methods

Sample and Procedures

Data are from Wave 3 of the Chicago Health and Life Experiences of Women (CHLEW) study (see Hughes et al., 2021 for more details), a community-based, 22-year, five-wave study of cisgender SMW aged 18 and older. Wave 3 data were collected from 2010 to 2012 (N = 353 women from the original cohort were retained [response rate = 79%]). In Wave 3 a supplemental sample of younger (18–25 years) SMW, bisexual women, and additional Black and Latinx SMW (N = 373) was recruited using a modified version of respondent-driven sampling (Martin et al., 2015). We focused on Wave 3 data for these analyses because it includes a larger (N = 726) and more diverse sample than other waves. Four SMW who were believed to have misrepresented their sexual identity were excluded (Scheer et al., 2022). Participants who identified as mostly heterosexual, only heterosexual, or other sexual identity were also excluded from analyses (n = 26; Scheer et al., 2022). Those with missing data for psychosocial stressors (n = 4, 0.6% for physical IPV to n = 44, 6.1% for sexual IPV) were also excluded from analyses, leaving an analytic sample of 602. The Institutional Review Board of the University of Illinois at Chicago approved all study procedures.

Measures

Alcohol Use Outcomes

HED was defined as consuming either ≥6 drinks/day in the past 12 months, or typically consuming ≥4 drinks on drinking days (1 = at least one episode of consuming ≥6 drinks on one or more days in the past year or consuming ≥4 drinks on drinking days, 0 = neither). Participants who endorsed three or more (out of five) DSM-IV alcohol dependence symptoms (e.g., continued use despite consequences) in the past 12 months were coded as meeting criteria for past-year DSM-IV alcohol dependence (Cronbach’s α = .74; Hasin et al., 2003). Consistent with prior research (Glass et al., 2015; Wilsnack et al., 2008), alcohol problem recognition was determined by asking participants whether they had ever wondered if they were developing a drinking problem (1 = yes, 0 = no).

Drug Use Outcomes

Cannabis use was assessed using questions about participants’ use of marijuana, pot, hashish, or tetrahydrocannabinol (THC) in the past 12 months (1 = any use, 0 = no use; Liautaud et al., 2021). Heroin or illegal methadone use was determined by participants’ responses to questions asking whether they had ever used heroin or illegal methadone (1 = any use, 0 = no use). Similar to prior research (Houang et al., 2023), illicit polydrug use was defined as lifetime use of two or more of the following substances: stimulants, cocaine/crack, heroin/illegal methadone, hallucinogens, or club drugs.

Psychosocial Stressors

Trauma was assessed using several measures of adversity during childhood and adult. CSA was assessed using Gail Wyatt’s CSA inventory (Wyatt, 1985) of eight types of sexual experiences occurring before age 18. Consistent with prior research (Hughes et al., 2014; Wilsnack et al., 2012; Wyatt, 1985), CSA in this study was defined as: (a) any unwanted intrafamilial sexual activity before age 18, or that involved a family member five or more years older than the participant; and/or (b) any unwanted extrafamilial sexual activity before age 18, or before age 13 and involved another person five or more years older. Given that dichotomizing CSA (any vs. no exposure) could evade the possibility of examining dose-response relationships between CSA severity and AOD outcomes (Dovran et al., 2019) and result in loss of statistical power (MacCallum et al., 2002), we assessed CSA severity using an ordered categorical approach. Although there is no gold standard for measuring CSA severity (Boroughs et al., 2015), it can be characterized across dimensions (e.g., chronicity, age at first abuse; Young et al., 2011). Similar to prior research (Boroughs et al., 2015), we used intrusion level (i.e., penetration) to demarcate CSA severity: 3 = high-risk contact (e.g., having vaginal/anal penetration), 2 = low-risk contact (e.g., fondling), 1 = noncontact (e.g., being asked or forced to expose private parts), 0 = no CSA.

Childhood neglect was determined by asking participants whether their basic needs (food, clothing, shelter, love) were neglected as a usual discipline method; 1 = yes, 0 = no. CPA was assessed with the question, “Do you feel that you were physically abused by your parents or other family members when you were growing up?”; 1 = yes, 0 = no.

Adult sexual assault (ASA) was assessed by asking participants, “Since you were 18 years old was there a time when someone forced you to have intercourse that you really did not want? This might have happened with partners, lovers, or friends, as well as with more distant persons and strangers.”; 1 = yes, 0 = no (Caceres et al., 2019; López et al., 2023; Veldhuis et al., 2023; Wilsnack et al., 2012). Adult sexual IPV was assessed by asking, “Since you were 18 years old was there a time when someone you were dating, an ex-partner, a recent partner, or a current partner forced you to have intercourse that you really did not want?” and whether they had “experienced any other kind of sexual assault” by someone they were dating, an ex-partner, a recent partner, or a current partner; 1 = any adult sexual IPV, 0 = no (Caceres et al., 2019; Veldhuis et al., 2023). Adult physical assault was determined by asking, “Not counting unwanted sexual experiences, has anyone other than your partner attacked you with a gun, knife or some other weapon, whether you reported it or not?” and whether they had been attacked by someone other than a partner “without a weapon but with the intent to kill or seriously injure you?”; 1 = any adult physical assault, 0 = no (Caceres et al., 2019; Veldhuis et al., 2023). Similar to prior research (Decker et al., 2015), participants were also asked two questions from the Conflict Tactics Scale (Straus et al., 1996) including whether a partner ever “threw something at you, pushed you, or hit you?” or “threatened to kill you, with a weapon or in some other way?”; 1 = any adult physical IPV, 0 = no (Caceres et al., 2019; Veldhuis et al., 2023).

Minority stressors included discrimination, stigma consciousness, and internalized stigma. Similar to prior research (Kidd et al., 2022), past-year discrimination was assessed using the six-item Experiences of Discrimination Scale (Krieger et al., 2005) based on sex/gender, race/ethnicity, and/or sexual identity. This scale assessed frequency of experiencing discrimination in six different situations, including discrimination affecting access to health care treatment. Following prior studies (Glass et al., 2020; Krieger et al., 2005), we calculated the number of situations in which any discrimination was experienced based on sex/gender, race/ethnicity, and/or sexual identity. Items were summed (0–6). Cronbach’s alpha (α = .69). Given that discrimination was positively distributed in the current study, and as recommended in contemporary epidemiological research (Gillespie & Anderson, 2018), tertiles were calculated: “high” (3 = 2+ forms of discrimination), “medium” (2 = 1 form of discrimination), and “low” (1 = no discrimination).

Stigma consciousness (i.e., the extent to which participants are influenced by and perceive stereotypes) was assessed using the Stigma Consciousness Questionnaire (Pinel, 1999). Response options ranged from 0 (strongly disagree) to 6 (strongly agree). Standardized scores were used because the scale for bisexual women had one more item than the scale for lesbian women. Each participant was assigned the standardized mean scale score that corresponded with their reported sexual identity. Final scale scores ranged from −2.71 to 3.25; higher scores indicated greater stigma consciousness (Cronbach’s α = .81). Consistent with our scoring approach for discrimination, responses were divided into tertiles and labeled “high” (3 = ≥0.441), “medium” (2 = −0.552 to 0.440), and “low” (1 = ≤ −0.553).

Internalized stigma was assessed with 10 questions adapted from Herek et al. (1997). Responses ranged from 1 (strongly agree) to 5 (strongly disagree). Scores ranged from 10 to 38 (SD = 5.37); higher total scores indicated greater internalized stigma (Cronbach’s α = .81). Given that internalized stigma was positively distributed and had high dispersion in the current study, and consistent with our scoring approach for discrimination and stigma consciousness, responses were divided into tertiles and labeled “high” (3 = ≥15), “medium” (2 = 12–14), and “low” (1 = ≤11).

Sociodemographic Characteristics

Participants reported their sexual identity using the following response options: “only lesbian/gay,” “mostly lesbian/gay,” “bisexual,” “mostly heterosexual,” “only heterosexual/straight,” and “other.” Consistent with prior research (López et al., 2023) and because responses to key questions differed little between SMW who identified as mostly lesbian/gay versus only lesbian/gay (López et al., 2023), we created a dummy variable to represent those who identified as “only lesbian/gay” or “mostly lesbian/gay” (0; “lesbian”) or “bisexual” (1). We measured age continuously. Race/ethnicity was assessed using responses two questions assessing Hispanic or Latinx origin or descent and race. Participants who identified as both Latinx and any other group were categorized as Latinx (LaVeist-Ramos et al., 2012); participants who identified with more than one race or as a race other than White, Black, or Latinx were excluded from the current analyses. That is, given small cell sizes, SMW who identified as Asian/Pacific Islander (n = 10), Native American/Alaskan Native (n = 13), or who reported that they did not know their race/ethnicity (n = 2) were excluded. Income was assessed with the following question: “For the last tax year, which represents your total household income from all sources?” We dichotomized responses (0 = above lowest quartile [>$14,999]; 1 = under lowest quartile [≤$14,999]). Participants reported their relationship status (in a relationship vs. not in a relationship) and geographical location (medium city or larger vs. town, village, or small city). Social support was assessed using the 12-item Multidimensional Scale of Perceived Social Support (MSPSS; Zimet et al., 1988); we used total social support scores (Cronbach’s α = .91), consistent with other SMW-focused research (Caceres et al., 2019; Ehlke et al., 2020; Puckett et al., 2015). Prior research has shown MSPSS to have strong internal consistency for the overall scale (Cronbach’s α = .88; Zimet et al., 1988).

Statistical Analysis

We used descriptive statistics to describe the sample’s sociodemographic characteristics, psychosocial stressors, and AOD outcomes. We then used LCA to identify unique patterns of psychosocial stressors among participants. Specifically, we used the three-step latent class analytic approach (Bakk et al., 2013), which prevents measurement bias related to class membership by correcting for classification error (Bakk et al., 2013).

All psychosocial stressors were treated as ordered categorical variables in the LCA models. This included minority stressor continuous variables that were ordered into categorical tertiles to avoid making untenable normality assumptions that would otherwise be required for continuous measures in LCA. We fit 1- to 6-class models with the 10 psychosocial stressors as indicators and considered models with residual correlations. A central assumption of LCA is local or conditional independence, which specifies that conditional on the latent variable, observed indicators are independent. We evaluated the local independence assumption by examining residual correlations among all item pairs (Vermunt & Magidson, 2016). Residual correlations were included for LCA models that violated the local independence assumption. The choice of LCA model was based on specified a priori criteria to identify the most optimally fitting LCA model: relative fit, including low Log Likelihood, Akaike Information Criteria (AIC), Bayesian Information Criteria (BIC), sample-size-adjusted BIC (aBIC), entropy above 0.60; class size; and interpretability (Lanza & Rhoades, 2013). Average posterior probabilities were used to examine class homogeneity (Nylund et al., 2007).

After selecting the best-fitting LCA model, we employed multinomial logistic regression to examine sociodemographic factors as class predictors, while accounting for classification error in class assignment (Bakk et al., 2013). We used multinomial logistic regression models regressing AOD outcomes onto class membership. For all models, we used the bias-adjusted maximum likelihood approach. Regression models controlled for sociodemographic factors.

Sample sizes depended on the amount of missing data for each model. Missing data for sociodemographic characteristics ranged from 0% for age to 4.2% for income. By design of the analytic study sample, there were no missing data across our indicators of psychosocial stressors. Missing data across outcome variables ranged from 0% for illicit polydrug use to 0.3% for HED. Only SMW who reported lifetime cannabis use were included in the regression model examining past-year cannabis use. Missing data were handled using pairwise deletion.

Descriptive statistics were conducted in SPSS version 27. All other analyses were conducted using Latent GOLD software, version 6.0 (Vermunt & Magidson, 2016). We performed a post hoc adjustment of p values using Benjamini–Hochberg procedures (Benjamini & Hochberg, 1995). We also conducted a post hoc sensitivity analysis comparing our LCA results to a variable-centered approach by regressing AOD outcomes on psychosocial stressors.

Results

Sample Characteristics

As shown in Table 1, participants were, on average, 39.9 years of age (SD = 14.0). Most (74%) identified as lesbian; 26.0% identified as bisexual. Relatively equal percentages identified as White (37.4%) and Black (36.6%); fewer (22.3%) identified as Latinx. Less than half (41.9%) reported past-year HED; fewer reported lifetime alcohol problem recognition (38.3%), past-year cannabis use (33.9%), lifetime heroin/illegal methadone use (11.8%), and illicit polydrug use (26.6%). About 10% met criteria for past-year DSM-IV alcohol dependence (10.8%).

Table 1.

Sociodemographic Characteristics and Presence of Alcohol and Other Drug Use and Negative Outcomes (Chicago Health and Life Experiences of Women [CHLEW]; N = 601).

	n (%)
Sociodemographic characteristics
Age, M [SD], (range: 18–82)	39.98 [14.04]
Sexual identity
Lesbian	445 (74.0)
Bisexual	156 (26.0)
Race/ethnicity
White	225 (37.4)
Black	220 (36.6)
Latinx	134 (22.3)
Income^a
Annual income over $14,999	416 (69.2)
Annual income $14,999 or less	160 (26.6)
Relationship status
Not in a relationship	231 (38.4)
In a relationship	367 (61.1)
Geographical location
Medium-sized city or larger	572 (95.2)
Town, village, or small city	28 (4.7)
Perceived social support, M [SD], (range: 12–84)	66.24 [12.50]
Presence of alcohol and other drug outcomes
Heavy episodic drinking^b	252 (41.9)
DSM-IV alcohol dependence^c	65 (10.8)
Alcohol problem recognition^d	230 (38.3)
Cannabis use^e	204 (33.9)
Heroin or illegal methadone use^f	71 (11.8)
Illicit polydrug use^g	214 (35.6)

Note. Percentages may not equal 100 due to missing data.

Lowest quartile was used to calculate low-income status (1 = ≤$14,999 annually).

Past-year heavy episodic drinking (1 = ≥6 drinks on one or more days in the past year or ≥4 drinks on a typical drinking day; 0 = <6 drinks on one or more days in the past year and <4 drinks on a typical drinking day).

Past-year DSM-IV alcohol dependence (1 = ≥3 DSM-IV symptoms of alcohol dependence; 0 = <3 DSM-IV symptoms of alcohol dependence; Hasin et al., 2003).

Lifetime alcohol problem recognition (1 = wondered if developing a drinking problem; 0 = never wondered if developing a drinking problem).

Past-year cannabis use among lifetime users only (1 = cannabis use; 0 = no cannabis use).

Lifetime heroin or illegal methadone use (1 = heroin or illegal methadone use; 0 = no heroin or illegal methadone use).

Lifetime illicit polydrug use (1 = ≥2 illicit substances [stimulants, cocaine/crack, heroin/illegal methadone, hallucinogens, club drugs]).

Latent Class Identification of Psychosocial Stressors

Allowing for local dependencies, the three-class model of psychosocial stressors (i.e., with the addition of residual associations) had the lowest AIC, BIC, and aBIC (see Supplemental Table 1). Entropy was relatively high in the two-class model allowing for local dependencies (Bakk et al., 2013). The three-class model of stressors allowing for local dependencies had adequate class separation (Nylund et al., 2007). Although the 2-class solution was the most parsimonious, the 3-class solution suggested a well-defined latent class characterized by high probability of ASA, which was not present in the 2-class solution. Some researchers have found that sexual abuse is a stronger predictor of substance use than physical abuse among women in the general population (Lown et al., 2011; Moustafa et al., 2021). Other studies have shown that CPA and childhood neglect have distinct effects on AOD outcomes among women (Wilsnack et al., 2018). As such, the 3-class solution was deemed optimal to distinguish variation in SMW’s AOD use.

Probabilities of psychosocial stressor indicators across latent classes are shown in Supplemental Figure 1 and in Table 2. Class 1 (Low Likelihood of Psychosocial Stressors) included slightly more than half of the sample (n = 336; 55.9%; see Table 2). SMW who belonged to Class 1 were likely to report low adversity given below-average probabilities of psychosocial stressors; many probabilities were close to zero (e.g., childhood neglect). Although lower than in Classes 2 and 3, SMW in Class 1 had a moderate probability of CPA. Class 1 was also characterized by the highest probability of low levels of minority stressors.

Table 2.

Descriptive Statistics and Probabilities of Indicators (N = 601).

10 Psychosocial Stressor Indicators	n (%)	Latent Classes of Psychosocial Stressors
		Class 1^b	Class 2^c	Class 3^d
		Conditional Item Probabilities
Childhood physical abuse	348 (57.8)	0.44	0.84	0.55
Childhood neglect	59 (9.8)	0.01	0.24	0.14
Childhood sexual abuse severity
No CSA	266 (44.2)	0.60	0.22	0.33
Noncontact childhood sexual abuse	70 (11.6)	0.13	0.10	0.12
Low-risk contact childhood sexual abuse	87 (14.5)	0.11	0.18	0.17
High-risk contact childhood sexual abuse	179 (29.7)	0.16	0.50	0.38
Adult sexual assault	180 (29.9)	0.08	0.30	0.99
Sexual intimate partner violence	76 (10.9)	0.01	0.01	0.62
Adult physical assault	201 (33.4)	0.14	0.59	0.48
Physical intimate partner violence	177 (29.4)	0.21	0.39	0.39
Discrimination^a
Low discrimination	349 (50.2)	0.55	0.41	0.50
Medium discrimination	157 (22.6)	0.23	0.25	0.24
High discrimination	184 (26.5)	0.22	0.34	0.26
Stigma consciousness^a
Low stigma consciousness	222 (31.9)	0.40	0.25	0.29
Medium stigma consciousness	208 (29.9)	0.31	0.30	0.31
High stigma consciousness	246 (35.4)	0.29	0.45	0.41
Internalized stigma^a
Low internalized stigma	274 (39.4)	0.41	0.38	0.34
Medium internalized stigma	157 (22.6)	0.23	0.23	0.23
High internalized stigma	256 (36.8)	0.36	0.39	0.43

Tertiles were used to calculate discrimination, stigma consciousness, and internalized stigma.

Class 1: “Low Likelihood of Psychosocial Stressors”; n = 336; 55.9%.

Class 2: “High Likelihood of Childhood Physical and Sexual Abuse and Adult Physical Abuse and Moderate Likelihood of Minority Stressors”; n = 175; 29.1%.

Class 3: “Moderate Likelihood of Childhood Physical Abuse, High Likelihood of Adult Sexual Assault and Sexual IPV, and Moderate Likelihood of Minority Stressors”; n = 90; 15.0%.

Class 2 (High Likelihood of CSA, CPA and Adult Physical Abuse, and Moderate Likelihood of Minority Stress) included 175 (29.1%) participants. It was characterized by higher adversity than Class 1, as demonstrated by elevated probabilities of experiencing some but not all types of trauma. Participants in this class were likely to report CPA, have high-risk CSA, and likely to report adult physical assault and physical IPV. This class was distinguished by moderate probabilities of high levels of discrimination, stigma consciousness, and internalized stigma.

Class 3 (Moderate Likelihood of CPA, High Likelihood of ASA and Sexual IPV, and Moderate Likelihood of Minority Stressors) included 90 (15.0%) of participants. This was the only class characterized by elevated probabilities of ASA. This class was marked by above-average probability of CPA, although lower than Class 2. SMW in Class 3 had lower probabilities of childhood neglect and sexual abuse and adult physical assault, and a similar probability of adult physical IPV compared to Class 2. SMW in Class 3 had low probabilities of discrimination but moderate probabilities of high stigma consciousness and internalized stigma.

Sociodemographic Characteristics and AOD Outcomes as Correlates of Class Membership

Older SMW were more likely than younger SMW to be in Class 3 than Class 1 (see Table 3). Black SMW were more than three times as likely as White SMW to be in Class 2 as in Class 1. SMW in Class 2 reported lower levels of social support than SMW in Class 1. Latent classes did not vary by sexual identity, income, relationship status, or geographical location.

Table 3.

Multinomial Logistic Regression Model Assessing Sociodemographic Characteristics Associated With Latent Classes of Psychosocial Stressors Among Sexual Minority Women.

	Class 2^a		Class 3^b
Sociodemographic characteristics	aOR [95% CI]	FDR-Adjusted p-Value	aOR [95% CI]	FDR-Adjusted p-Value
Age	1.02 [0.99, 1.05]	.135	1.04 [1.02, 1.06]	.002
Sexual identity
Lesbian	Ref		Ref
Bisexual	0.75 [0.35, 1.60]	.264	1.34 [0.61, 2.96]	.264
Race/ethnicity
White	Ref		Ref
Black	3.07 [1.32, 7.13]	.014	0.81 [0.36, 1.79]	.319
Latinx	1.24 [0.51, 3.06]	.183	0.79 [0.38, 1.67]	.343
Income
Annual income over $14,999	Ref		Ref
Annual income $14,999 or less	0.60 [0.29, 1.27]	.225	1.18 [0.53, 2.60]	.224
Relationship status
Not in a relationship	Ref		Ref
In a relationship	0.71 [0.37, 1.37]	.224	0.70 [0.36, 1.34]	.237
Geographical location
Medium-sized city or larger	Ref		Ref
Town, village, or small city	1.97 [0.61, 6.33]	.127	0.35 [0.04, 3.28]	.177
Social support	0.95 [0.92, 0.98]	<.001	0.98 [0.95, 1.01]	.135

Note. All models used the bias-adjusted maximum likelihood approach and 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 (“Low Likelihood of Psychosocial Stressors”; n = 336; 55.9%). aOR = adjusted odds ratio; CI = confidence interval; Ref = reference group.

Class 2: “High Likelihood of Childhood Physical and Sexual Abuse and Adult Physical Abuse and Moderate Likelihood of Minority Stressors”; n = 175; 29.1%.

Class 3: “Moderate Likelihood of Childhood Physical Abuse, High Likelihood of Adult Sexual Assault and Sexual IPV, and Moderate Likelihood of Minority Stressors”; n = 90; 15.0%.

After adjusting for sociodemographic characteristics, SMW in Classes 2 and 3 were more likely than SMW in Class 1 to recognize problematic drinking and to report heroin or illegal methadone use and illicit polydrug use (see Table 4). SMW in Class 3 were more likely to meet criteria for DSM-IV alcohol dependence. SMW’s HED or cannabis use did not vary by classes.

Table 4.

Multinomial Logistic Regression Models Assessing Psychosocial Stressors Latent Classes as Predictors of Alcohol and Other Drug Use and Negative Outcomes Among Sexual Minority Women.

	Heavy Episodic Drinking^a		DSM-IV Alcohol Dependence^b		Alcohol Problem Recognition^c		Cannabis Use^d		Heroin or Illegal Methadone Use^e		Illicit Polydrug Use^f
	aOR [95% CI]	FDR-Adjusted p-Value	aOR [95% CI]	FDR-Adjusted p-Value	aOR [95% CI]	FDR-Adjusted p-Value	aOR [95% CI]	FDR-Adjusted p-Value	aOR [95% CI]	FDR-Adjusted p-Value	aOR [95% CI]	FDR-Adjusted p-Value
Sample size	n = 545		n = 545		n = 545		n = 446^g		n = 546		n = 546
Psychosocial stressors class
Class 1^g	Ref		Ref		Ref		Ref		Ref		Ref
Class 2^h	1.00 [0.45, 2.24]	.999	3.13 [0.82, 11.89]	.132	3.49 [1.49, 8.19]	.020	0.66 [0.26, 1.71]	.600	15.14 [7.09, 32.34]	<.001	6.23 [2.30, 16.88]	<.001
Class 3ⁱ	1.76 [0.39, 1.76]	.950	4.72 [1.29, 15.00]	.028	3.27 [1.60, 6.67]	.011	1.72 [0.73, 4.05]	.600	4.59 [1.93, 10.93]	<.001	2.69 [1.13, 6.41]	.063
Sociodemographic characteristics
Age	0.94 [0.93, 0.96]	<.001	0.96 [0.94, 0.99]	<.001	1.01 [0.99, 1.02]	.286	0.93 [0.91, 0.95]	<.001	1.07 [1.05, 1.10]	<.001	1.01 [0.99, 1.02]	.425
Sexual identity
Lesbian	Ref		Ref		Ref		Ref		Ref		Ref
Bisexual	1.068 [0.70, 1.66]	.950	1.23 [0.65, 2.32]	.578	1.19 [0.76, 1.88]	.563	0.86 [0.53, 1.41]	.630	2.22 [1.10, 4.51]	.045	1.38 [0.81, 2.33]	.329
Race/ethnicity
White	Ref		Ref		Ref		Ref		Ref		Ref
Black	1.04 [0.66, 1.62]	.967	3.14 [1.43, 6.91]	.027	0.62 [0.39, 0.98]	.100	1.23 [0.74, 2.02]	.540	0.94 [0.46, 1.93]	.860	0.42 [0.24, 0.73]	.011
Latinx	1.28 [0.79, 2.07]	.950	2.26 [0.94, 5.45]	.115	0.58 [0.34, 0.97]	.100	0.85 [0.49, 1.48]	.590	2.14 [0.97, 4.75]	.087	0.48 [0.26, 0.88]	.060
Income
Annual income over $14,999	Ref		Ref		Ref		Ref		Ref		Ref
Annual income $14,999 or less	0.94 [0.60, 1.45]	.950	1.38 [0.74, 2.56]	.387	0.89 [0.56, 1.39]	.667	1.35 [0.82, 2.23]	.600	4.60 [2.31, 9.15]	<.001	0.90 [0.53, 1.53]	.700
Relationship status
Not in a relationship	Ref		Ref		Ref		Ref		Ref		Ref
In a relationship	0.70 [0.47, 1.03]	.345	0.53 [0.29, 0.96]	.087	1.06 [0.71, 1.60]	.750	0.89 [0.57, 1.39]	.630	1.23 [0.66, 2.28]	.567	0.68 [0.42, 1.08]	.200
Geographical location
Medium-sized city or larger	Ref		Ref		Ref		Ref		Ref		Ref
Town, village, or small city	0.71 [0.29, 1.75]	.950	1.19 [0.30, 4.68]	.800	1.73 [0.75, 4.02]	.286	0.62 [0.20, 2.02]	.600	0.27 [0.06, 1.21]	.110	0.48 [0.15, 1.44]	.317
Social support	0.99 [0.98, 1.01]	.950	0.98 [0.96, 1.00]	.115	0.99 [0.97, 1.00]	.220	0.62 [0.20, 2.02]	.600	1.07 [1.04, 1.09]	<.001	1.00 [0.99, 1.02]	.700

Note. FDR-adjusted refers to the Benjamini–Hochberg procedure used to correct for the false discovery rate. aOR = adjusted odds ratio; CI = confidence interval; Ref = reference group. Boldface type indicates a significant aOR.

Past-year DSM-IV alcohol dependence (1 = ≥3 DSM-IV symptoms of alcohol dependence; 0 = <3 DSM-IV symptoms of alcohol dependence; Hasin et al., 2003).

Lifetime alcohol problem recognition (1 = wondered if developing a drinking problem; 0 = never wondered if developing a drinking problem).

Past-year cannabis use (1 = cannabis use; 0 = no cannabis use). Sexual minority women who reported no lifetime cannabis use were excluded in model examining psychosocial stressors latent classes as predictors of past-year cannabis use.

Lifetime heroin or illegal methadone use (1 = heroin or illegal methadone use; 0 = no heroin or illegal methadone use).

Lifetime illicit polydrug use (1 = ≥2 illicit substances; 0 = <2 illicit substances).

Class 1: “Low Likelihood of Psychosocial Stressors”; n = 336; 55.9%.

Class 2: “High Likelihood of Childhood Physical and Sexual Abuse and Adult Physical Abuse and Moderate Likelihood of Minority Stressors”; n = 175; 29.1%.

Class 3: “Moderate Likelihood of Childhood Physical Abuse, High Likelihood of Adult Sexual Assault and Sexual IPV, and Moderate Likelihood of Minority Stressors”; n = 90; 15.0%.

Our post hoc sensitivity analysis comparing LCA results to a variable-centered approach while adjusting for sociodemographic characteristics indicated that SMW who experienced various forms of trauma, compared to those who did not, were more likely to report alcohol problem recognition, heroin or illegal methadone use, and illicit polydrug use (see Supplemental Table 2). SMW who experienced adult physical assault in general and in dating relationships as well as ASA in dating relationships and elevated levels of discrimination were uniquely at risk for DSM-IV alcohol dependence. SMW who reported sexual IPV compared to those who did not were more likely to report past-year cannabis use.

Discussion

The current study extends prior research (Feinstein & Dyar, 2017; McCabe, Hughes, et al., 2022; Puckett et al., 2017; Shramko et al., 2018) by documenting unique patterns of psychosocial stressors among SMW and heterogeneity in SMW’s risk of endorsing psychosocial stressors. In addition, building on prior findings (Kassing et al., 2021; Keyes et al., 2011; Layland et al., 2022; Talley et al., 2022), these results are among the first to show that exposure to multiple types of psychosocial stressors is associated with AOD outcomes among SMW.

We examined 10 distinct experiences of trauma exposure and minority stressors. Two latent classes (Classes 2 and 3) exhibited higher adversity relative to Class 1, which was characterized by low (but not zero) probabilities of experiencing psychosocial stressors (i.e., lower adversity). Even though SMW in Class 1 were less likely to report psychosocial stressors than SMW in other classes, they had a moderate probability of reporting CPA, reinforcing evidence that SMW are vulnerable to this form of childhood maltreatment (McCabe, Hughes, et al., 2022).

SMW in Class 2, who reported CPA, severe CSA, and ASA, were distinctively vulnerable to discrimination and stigma consciousness (Pinel, 1999). Additional research is needed to examine mechanisms underlying this co-occurrence, such as exteroception (e.g., perception of threat; Adhia et al., 2021). Our findings also noted a distinct subgroup of SMW (Class 3) at heightened risk of CPA, ASA, and stigma consciousness. Classes 2 and 3 build on prior research in a sample of sexual minority Latinx youth that revealed two latent profiles characterized by discrimination and victimization and related to poor mental health (Shramko et al., 2018).

This study’s post hoc results expand variable-centered research that has primarily focused on sexual revictimization among CSA-exposed SMW (Sutton et al., 2021). Our person-centered results support and add to prior research (Layland et al., 2022) by showing the combined burden of multiple types of adversity on SMW’s AOD outcomes. Our findings also highlight the importance of addressing the intersection of childhood and adult trauma, discrimination, and stigma consciousness, rather than focusing on separate, additive experiences across type.

Latent classes of psychosocial stressors varied among SMW by age, race/ethnicity, and social support. Aligned with prior findings (Calabrese et al., 2015; Ehlke et al., 2020), older SMW, Black SMW, and SMW with lower social support were more likely than younger SMW, White SMW, and SMW with higher social support, respectively, to be in classes characterized by high probabilities of childhood and adult maltreatment and minority stressors. Older SMW may be uniquely burdened by CPA, ASA, and stigma consciousness. Furthermore, Black SMW appear to be especially vulnerable to poly-victimization and minority stressors, potentially rooted in intersectional oppression (e.g., racism, heterosexism, sexism; Bowleg et al., 2003; Calabrese et al., 2015). Our findings are consistent with prior research noting that SMW who lack strong social support networks may be at heightened risk of psychosocial stressors (Ehlke et al., 2020).

Findings also highlight that SMW in classes marked by moderate to high probabilities of trauma exposure and minority stressors were between 2 and 15 times as likely to report AOD use and negative AOD outcomes as SMW in the class marked by lower probabilities of trauma and minority stressors AOD use. Even after accounting for sociodemographic differences, SMW who reported high adversity were more likely than those with low adversity to meet criteria for DSM-IV alcohol dependence, recognize problematic drinking, and to report heroin or illegal methadone use and illicit polydrug use. These findings provide preliminary evidence of the stress-sensitizing effects of early and cumulative adversity and benefits of utilizing LCA to formulate a life course, context-sensitive, and cumulative-effect approach to conceptualizing SMW’s vulnerability (Nurius et al., 2013). Notably, SMW’s likelihood of reporting HED and cannabis use did not vary across latent classes.

Our variable-centered findings demonstrated links between various psychosocial stressors and AOD outcomes and are consistent with our heterogeneous stressor latent classes that predicted within-group variation in AOD outcomes among SMW. Unlike our LCA results, this variable-centered approach identified past-year cannabis use among SMW who reported ASA in dating relationships. However, differentiating AOD outcomes based on isolated psychosocial stressors, rather than considering multiple stressors simultaneously, ignores the potential synergistic effect of trauma exposure and minority stressors on SMW’s AOD use.

Implications and Future Directions

An integrated public health approach is also needed to prevent structural drivers of SMW’s repeated exposure to trauma and minority stressors (Cardona et al., 2021; Decker et al., 2018). For instance, policies that reduce inequity, address structural disadvantage, and establish norms that address attitudes toward violence against SMW should be implemented (Decker et al., 2018; Flentje et al., 2022; Scheer et al., 2022). Social marketing approaches that challenge heterosexist norms, increase public awareness of SMW’s increased risk of trauma exposure and minority stressors, and mobilize the broader sexual and gender minority community as important safety nets, supports, and allies in violence prevention represent other important structural initiatives to reducing rates of psychosocial stressors facing SMW (Decker et al., 2018; Orchowski et al., 2020; Woodford et al., 2018). Prior research has also highlighted the importance of addressing SMW’s repeated exposure to trauma, minority stressors, and insufficient social safety by developing and implementing macro-level interventions, including increasing anti-discrimination protections via statewide and federal policies (Diamond & Alley, 2022; Puckett et al., 2020).

Results from this study highlight the need for universal screening for lifetime adversity, including trauma and minority stressors, and AOD use and related problems among SMW. In addition, clinicians might consider employing functional analysis to identify proximal antecedents (e.g., negative emotionality, impulsivity, emotion dysregulation, dissociation, posttraumatic stress disorder symptoms) to negative AOD outcomes among SMW who report multiple psychosocial stressors (Boness & Witkiewitz, 2022; Dworkin et al., 2021; Fitzpatrick et al., 2020). Clinicians should also assess distress resulting from these psychosocial stressors to advance personalized delivery of substance use treatment for SMW. Depending on the source of SMW’s distress, clinicians might prioritize: (1) cognitive restructuring skills to help SMW modify AOD outcome expectancies related to internalized stigma; or (2) distress tolerance skills to help SMW cope with AOD craving following exposure to trauma-related stimuli (Boness & Witkiewitz, 2022). This modularized approach could increase the effectiveness of AOD treatment for SMW (Boness & Witkiewitz, 2022). Moreover, given that intimate relationships and social support protect against SMW’s negative health behaviors and outcomes (Caceres et al., 2019; Veldhuis et al., 2019, 2020), clinicians and intervention researchers should consider bolstering SMW’s access to strong support networks and enhance skills among those supporting SMW. For instance, trauma-informed social environments, including romantic or dating partners, SMW community members, caregivers, and mentors, may support SMW in coping with psychosocial stressors in ways that promote recovery and resilience (Matlin et al., 2019).

Future studies can build on these results by identifying risk pathways, such as neurobiological mechanisms and affective states, to inform etiology and maintenance models of AOD outcomes among SMW. For example, recent research using a sample of college drinkers found that drinking-to-cope motives increase drinking urges immediately following exposure to trauma cues (Zaso & Read, 2020), highlighting the need for future research to examine momentary affective processes driving trauma- and minority stress-related AOD use among SMW. Future studies should examine whether substance use motives or mental health needs influence SMW’s likelihood of engaging in HED and using cannabis following psychosocial stressors. Additional research is also needed to examine the connections between SMW’s risk of psychosocial stressors and broader sociopolitical context (Veldhuis et al., 2018).

Limitations

It is unknown whether our results generalize to SMW who identify as other than lesbian or bisexual or who live outside of Chicago Metropolitan Area in Illinois. Furthermore, data were collected in 2010 to 2012. Newer studies should determine whether findings can be replicated perhaps particularly due to narrowing gender differences in alcohol use (White, 2020) and given the shifting landscape of both supports for sexual and gender minority people (e.g., Obergefell, improved societal attitudes toward sexual and gender minority individuals; Aksoy et al., 2020; Drabble et al., 2020, 2021) and heightened structural stigma against sexual and gender minority people (e.g., anti-LGBT legislation, rise in hate crimes; Coston, 2020; Fredrick et al., 2022; Horne et al., 2022). Data were cross-sectional, and not all measures used consistent timeframes. However, findings advance foundational knowledge that can be replicated in longitudinal research. We used retrospective self-report measures and several measures were single-item indicators. In addition, this study did not include measures of motives for alcohol or other drug use. LCA results are limited by the latent class indicators included in the parent study. Future studies should consider including other factors, such as resilience, among SMW (Layland et al., 2022). Furthermore, gender-diverse SMW report unique AOD-related risks. Future research is needed to examine whether our findings generalize to SMW across gender identity and expression (Batchelder et al., 2023).

Conclusions

Three distinct classes of psychosocial stressors emerged among SMW and these varied by age, race/ethnicity, and social support. SMW who were in the higher adversity classes had heightened risks for negative AOD outcomes, such as alcohol dependence, heroin or illegal methadone use, and illicit polydrug use. Results highlight the need for universal screening for lifetime trauma exposure, minority stressors, and AOD use and related problems among SMW. Future studies should test modifiable mechanisms (e.g., coping strategies) underlying these associations to inform brief screening protocols and evidence-based adapted interventions for at-risk SMW. Moreover, public health prevention and intervention efforts are needed to mitigate structural drivers of trauma exposure and minority stressors, which are disproportionately shouldered by SMW and contribute to AOD use and negative outcomes in this population.

Supplemental Material

sj-docx-1-jiv-10.1177_08862605231153886 – Supplemental material for Associations Between Latent Classes of Trauma Exposure and Minority Stressors and Substance Use Among Cisgender Sexual Minority Women

Supplemental material, sj-docx-1-jiv-10.1177_08862605231153886 for Associations Between Latent Classes of Trauma Exposure and Minority Stressors and Substance Use Among Cisgender Sexual Minority Women by Jillian R. Scheer, Melanie M. Wall, Cindy B. Veldhuis, Jessie V. Ford, Cory J. Cascalheira, Emily C. Helminen, Thomas J. Shaw, Virinca Jaipuriyar, Michelle J. Zaso and Tonda L. Hughes in Journal of Interpersonal Violence

Supplemental Material

sj-docx-2-jiv-10.1177_08862605231153886 – Supplemental material for Associations Between Latent Classes of Trauma Exposure and Minority Stressors and Substance Use Among Cisgender Sexual Minority Women

Supplemental material, sj-docx-2-jiv-10.1177_08862605231153886 for Associations Between Latent Classes of Trauma Exposure and Minority Stressors and Substance Use Among Cisgender Sexual Minority Women by Jillian R. Scheer, Melanie M. Wall, Cindy B. Veldhuis, Jessie V. Ford, Cory J. Cascalheira, Emily C. Helminen, Thomas J. Shaw, Virinca Jaipuriyar, Michelle J. Zaso and Tonda L. Hughes in Journal of Interpersonal Violence

Footnotes

Declaration of Conflicting Interests

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

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The Chicago Health and Life Experiences of Women (CHLEW) study is supported by the National Institute on Alcohol Abuse and Alcoholism (NIAAA; R01AA013328-16; PI: Hughes). Jillian R. Scheer acknowledges support from NIAAA (K01AA028239-01A1). Cindy B. Veldhuis acknowledges support from NIAAA (K99AA028049). Jessie Ford acknowledges support from NIAAA (K01AA028532-01A1). Cory J. Cascalheira acknowledges support as a National Institutes of Health RISE Fellow (R25GM061222). Michelle J. Zaso acknowledges support from NIAAA (T32AA007583, K99AA029728). Information in this report is the authors’ own and does not represent the views of the funders, including the National Institutes of Health. We would like to express our gratitude to the project manager of CHLEW, Kelly Martin, MPH, MA and to the CHLEW participants.

ORCID iDs

Jillian R. Scheer

Emily C. Helminen

Virinca Jaipuriyar

Michelle J. Zaso

Supplemental Material

Supplemental material for this article is available online.

Author Biographies

Jillian R. Scheer, PhD, is a licensed counseling psychologist, the Cobb-Jones Professor of Clinical Psychology, and an Assistant Professor in the Department of Psychology at Syracuse University. Dr. Scheer’s research focuses on understanding the synergistic effect of violence exposure and minority stressors on sexual minority women’s hazardous drinking and co-occurring mental health outcomes and developing tailored interventions for this population.

Melanie M. Wall, PhD, is the director of Mental Health Data Science in the Psychiatry Department of the New York State Psychiatric Institute (NYSPI)/Columbia University Irving Medical Center (CUIMC), where she oversees a team of biostatisticians collaborating on predominately National Institutes of Health (NIH)-funded research projects related to psychiatry. She has worked extensively with modeling complex multilevel and multimodal data on a wide array of psychosocial public health and psychiatric research questions in both clinical studies and large epidemiologic studies.

Cindy B. Veldhuis, PhD, is an Assistant Professor in the Department of Medical Social Sciences at Northwestern Feinberg School of Medicine and in the Institute for Sexual and Gender Minority Health and Wellbeing at Northwestern University. She is a K99/R00 Pathway to Independence awardee from the National Institutes of Health. Broadly, her research focuses on LGBTQIA+ women’s relationships, health, and health behaviors as well as violence, trauma, mental health, and the impacts of sociopolitical events on wellbeing.

Jessie V. Ford, PhD, is a Public Health Sociologist and Assistant Professor in the Department of Sociomedical Sciences at Columbia University’s Mailman School of Public Health. Dr. Ford’s research explores how expectations and inequalities around gender and sexuality shape sexual health, violence, and pleasure. At present, she is working on a series of research projects examining the high rates of sexual assault associated with hazardous drinking among bisexual women.

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) examine stigma-based individual, interpersonal, and structural mechanisms conferring risk for SGM health disparities (e.g., substance misuse); and (2) apply computational methods (i.e., artificial intelligence) to expand the scientific understanding of theory-driven constructs (e.g., minority stress) pertinent to SGM wellbeing.

Emily C. Helminen, MS, is a doctoral candidate in School Psychology at Syracuse University. Helminen’s research focuses on (1) examining how compassion-based interventions can improve mental and behavioral health among sexual and gender minority populations, and (2) understanding the physiological and cognitive mechanisms by which these interventions are effective.

Thomas J. Shaw, BA, is doctoral student at Virginia Polytechnic Institute and State University. Shaw’s research interests pertain to (1) better understanding the pathways and manifestation of bidirectional intimate partner violence (IPV) in young adult couples; and (2) creating a more nuanced understanding of how risky behaviors such as alcohol use, heavy episodic drinking, and heavy cannabis are associated with IPV perpetration and victimization.

Virinca Jaipuriyar, BA, is a Research Assistant at the Minority Stress & Trauma Lab. Jaipuriyar’s research interests concern intervention-focused research from a social, cognitive, and neurobiological and psychobiological perspective in psychological symptoms relating to interpersonal stressors, anxiety, and substance use.

Michelle J. Zaso, PhD, is a postdoctoral associate at the University at Buffalo—State University of New York. She received her doctorate in clinical psychology from Syracuse University. Dr. Zaso’s major research interests include etiologies of alcohol use across development, with particular attention to the role of alcohol-promoting stressful and traumatic experiences.

Tonda L. Hughes, PhD, RN, FAAN, is the Henrik H. Bendixen Professor of International Nursing, and Associate Dean for Global Health in the School of Nursing at Columbia University in New York City. She is also Executive Director of the Center for Sexual and Gender Minority Health Research in the School of Nursing and holds an interdisciplinary appointment as Professor in the College of Medicine, Department of Psychiatry at Columbia. She has a distinguished research career focusing on women’s mental health and substance use and is recognized internationally as a leading expert on sexual minority women’s health.

References

Adhia

Gordon

A. R.

Roberts

A. L.

Fitzmaurice

G. M.

Hemenway

Austin

S. B.

(2021). Childhood gender nonconformity and intimate partner violence in adolescence and young adulthood. Journal of Interpersonal Violence, 36(5–6), NP3130–NP3152. https://doi.org/10.1177/0886260518770643

Aksoy

C. G.

Carpenter

C. S.

De Haas

Tran

K. D.

(2020). Do laws shape attitudes? Evidence from same-sex relationship recognition policies in Europe. European Economic Review, 124, 103399. https://doi.org/10.1016/j.euroecorev.2020.103399

Bakk

Tekle

F. B.

Vermunt

J. K.

(2013). Estimating the association between latent class membership and external variables using bias-adjusted three-step approaches. Sociological Methodology, 43(1), 272–311. https://doi.org/10.1177/0081175012470644

Batchelder

A. W.

Foley

J. D.

Stanton

A. M.

Gorman

K. R.

Morris

J. C.

Scheer

J. R.

(2023). Facets of gender expression and discrimination in relation to alcohol and other drug use severity among sexual minority women and gender diverse individuals assigned female at birth. LGBT Health, 10(3), 191–201. https://doi.org/10.1089/lgbt.2022.0138

Benjamini

Hochberg

(1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society. Series B (Methodological), 57(1), 289–300.

Boness

C. L.

Witkiewitz

(2022). Precision medicine in alcohol use disorder: Mapping etiologic and maintenance mechanisms to mechanisms of behavior change to improve patient outcomes. Experimental and Clinical Psychopharmacology. Advance online publication. https://doi.org/10.1037/pha0000613

Boroughs

M. S.

Valentine

S. E.

Ironson

G. H.

Shipherd

J. C.

Safren

S. A.

Taylor

S. W.

Dale

S. K.

Baker

J. S.

Wilner

J. G.

O’Cleirigh

(2015). Complexity of childhood sexual abuse: Predictors of current PTSD, mood disorders, substance use, and sexual risk behavior among adult men who have sex with men. Archives of Sexual Behavior, 44(7), 1891–1902. https://doi.org/10.1007/s10508-015-0546-9

Bowleg

Huang

Brooks

Black

Burkholder

(2003). Triple jeopardy and beyond: Multiple minority stress and resilience among black lesbians. Journal of Lesbian Studies, 7(4), 87–108. https://doi.org/10.1300/J155v07n04_06

Brooks

(1981). Minority stress and lesbian women. Lexington Books.

10.

Caceres

B. A.

Veldhuis

C. B.

Hickey

K. T.

Hughes

T. L.

(2019). Lifetime trauma and cardiometabolic risk in sexual minority women. Journal of Women’s Health, 28(9), 1200–1217. https://doi.org/10.1089/jwh.2018.7381

11.

Calabrese

S. K.

Meyer

I. H.

Overstreet

N. M.

Haile

Hansen

N. B.

(2015). Exploring discrimination and mental health disparities faced by black sexual minority women using a minority stress framework. Psychology of Women Quarterly, 39(3), 287–304. https://doi.org/10.1177/0361684314560730

12.

Cardona

Madigan

Sauer

(2021). How minority stress becomes traumatic invalidation: An emotion-focused conceptualization of minority stress in sexual and gender minority people. Clinical Psychology Science and Practice, 29(2), 185–195. https://doi.org/10.1037/cps0000054

13.

Cerezo

Ramirez

(2020). Perceived discrimination, alcohol use disorder and alcohol-related problems in sexual minority women of color. Journal of Social Service Research, 47(1), 33–46. https://doi.org/10.1080/01488376.2019.1710657

14.

Coston

(2020). Hate crimes against LGBT people in the United States. Oxford Research Encyclopedia of Politics.

15.

Decker

M. R.

Latimore

A. D.

Yasutake

Haviland

Ahmed

Blum

R. W.

Sonenstein

Astone

N. M.

(2015). Gender-based violence against adolescent and young adult women in low-and middle-income countries. Journal of Adolescent Health, 56(2), 188–196. https://doi.org/10.1016/j.jadohealth.2014.09.003

16.

Decker

M. R.

Wilcox

H. C.

Holliday

C. N.

Webster

D. W.

(2018). An integrated public health approach to interpersonal violence and suicide prevention and response. Public Health Reports, 133(1_suppl), 65S–79S. https://doi.org/10.1177/0033354918800019

17.

Diamond

L. M.

Alley

(2022). Rethinking minority stress: A social safety perspective on the health effects of stigma in sexually-diverse and gender-diverse populations. Neuroscience & Biobehavioral Reviews, 138, 104720. https://doi.org/10.1016/j.neubiorev.2022.104720

18.

Dovran

Winje

Arefjord

Tobiassen

Stokke

Skogen

J. C.

Øverland

(2019). Associations between adverse childhood experiences and adversities later in life. Survey data from a high-risk Norwegian sample. Child Abuse & Neglect, 98, 104234. https://doi.org/10.1016/j.chiabu.2019.104234

19.

Drabble

L. A.

Mericle

A. A.

Wootton

A. R.

Munroe

Trocki

K. F.

Hughes

(2021). Measuring the impact of legal recognition of same-sex marriage among sexual minority women. Journal of GLBT Family Studies, 17(4), 371–392. https://doi.org/10.1080/1550428X.2021.1935382

20.

Drabble

L. A.

Wootton

A. R.

Veldhuis

C. B.

Perry

Riggle

E. D. B.

Trocki

K. F.

Hughes

T. L.

(2020). It’s complicated: The impact of marriage legalization among sexual minority women and gender diverse individuals in the United States. Psychology of Sexual Orientation and Gender Diversity, 7(4), 396–406. https://doi.org/10.1037/sgd0000375

21.

Dworkin

E. R.

Jaffe

A. E.

Fitzpatrick

Rhew

I. C.

Kaysen

(2021). Daily relationships between posttraumatic stress symptoms, drinking motives, and alcohol consumption in trauma-exposed sexual minority women. Psychology of Addictive Behaviors, 35(1), 3–15. https://doi.org/10.1037/adb0000680

22.

Dyar

Dworkin

E. R.

Pirog

Kaysen

(2021). Social interaction anxiety and perceived coping efficacy: Mechanisms of the association between minority stress and drinking consequences among sexual minority women. Addictive Behaviors, 114, 106718. https://doi.org/10.1016/j.addbeh.2020.106718

23.

Ehlke

S. J.

Braitman

A. L.

Dawson

C. A.

Heron

K. E.

Lewis

R. J.

(2020). Sexual minority stress and social support explain the association between sexual identity with physical and mental health problems among young lesbian and bisexual women. Sex Roles, 83(5), 370–381. https://doi.org/10.1007/s11199-019-01117-w

24.

Evans-Polce

R. J.

Kcomt

Veliz

P. T.

Boyd

C. J.

McCabe

S. E.

(2020). Alcohol, tobacco, and comorbid psychiatric disorders and associations with sexual identity and stress-related correlates. The American Journal of Psychiatry, 177(11), 1073–1081. https://doi.org/10.1176/appi.ajp.2020.20010005

25.

Feinstein

B. A.

Dyar

(2017). Bisexuality, minority stress, and health. Current Sexual Health Reports, 9(1), 42–49. https://doi.org/10.1007/s11930-017-0096-3

26.

Fitzpatrick

Dworkin

E. R.

Zimmerman

Javorka

Kaysen

(2020). Stressors and drinking in sexual minority women: The mediating role of emotion dysregulation. Psychology of Sexual Orientation and Gender Diversity, 7(1), 46–54. https://doi.org/10.1037/sgd0000351

27.

Flentje

Clark

K. D.

Cicero

Capriotti

M. R.

Lubensky

M. E.

Sauceda

Neilands

T. B.

Lunn

M. R.

Obedin-Maliver

(2022). Minority stress, structural stigma, and physical health among sexual and gender minority individuals: Examining the relative strength of the relationships. Annals of Behavioral Medicine, 56(6), 573–591. https://doi.org/10.1093/abm/kaab051

28.

Fredrick

E. G.

Mann

A. K.

Brooks

B. D.

Hirsch

J. K.

(2022). Anticipated to enacted: Structural stigma against sexual and gender minorities following the 2016 presidential election. Sexuality Research and Social Policy, 19(1), 345–354. https://doi.org/10.1007/s13178-021-00547-0

29.

Gillespie

S. L.

Anderson

C. M.

(2018). Racial discrimination and leukocyte glucocorticoid sensitivity: Implications for birth timing. Social Science & Medicine, 216, 114–123. https://doi.org/10.1016/j.socscimed.2018.08.010

30.

Glass

J. E.

Grant

J. D.

Yoon

H. Y.

Bucholz

K. K.

(2015). Alcohol problem recognition and help seeking in adolescents and young adults at varying genetic and environmental risk. Drug and Alcohol Dependence, 153, 250–257. https://doi.org/10.1016/j.drugalcdep.2015.05.006

31.

Glass

J. E.

Williams

E. C.

(2020). Racial/ethnic discrimination and alcohol use disorder severity among United States adults. Drug and Alcohol Dependence, 216, 108203. https://doi.org/10.1016/j.drugalcdep.2020.108203

32.

Hasin

D. S.

Schuckit

M. A.

Martin

C. S.

Grant

B. F.

Bucholz

K. K.

Helzer

J. E.

(2003). The validity of DSM-IV alcohol dependence: What do we know and what do we need to know? Alcoholism: Clinical and Experimental Research, 27(2), 244–252. https://doi.org/10.1097/01.ALC.0000060878.61384.ED

33.

Herek

G. M.

Cogan

J. C.

Gillis

J. R.

Glunt

E. K.

(1997). Correlates of internalized homophobia in a community sample of lesbians and gay men. Journal of the Gay and Lesbian Medical Association, 2, 17–25.

34.

Horne

S. G.

McGinley

Yel

Maroney

M. R.

(2022). The stench of bathroom bills and anti-transgender legislation: Anxiety and depression among transgender, nonbinary, and cisgender LGBQ people during a state referendum. Journal of Counseling Psychology, 69, 1–13. https://doi.org/10.1037/cou0000558

35.

Houang

S. T.

Kafka

J. M.

Choi

S. K.

Meanley

S. P.

Muessig

K. E.

Bauermeister

J. A.

Hightow-Weidman

L. B.

(2023). Co-occurring epidemic conditions among southern U.S. Black men who have sex with men in an online eHealth intervention. AIDS and Behavior, 27(2), 641–650. https://doi.org/10.1007/s10461-022-03799-y

36.

Hughes

T. L.

Johnson

T. P.

Steffen

A. D.

Wilsnack

S. C.

Everett

(2014). Lifetime victimization, hazardous drinking, and depression among heterosexual and sexual minority women. LGBT Health, 1(3), 192–203. https://doi.org/10.1089/lgbt.2014.0014

37.

Hughes

T. L.

Veldhuis

C. B.

Drabble

L. A.

Wilsnack

S. C.

(2020). Research on alcohol and other drug (AOD) use among sexual minority women: A global scoping review. PLOS ONE, 15(3), e0229869. https://doi.org/10.1371/journal.pone.0229869

38.

Hughes

Wilsnack

Martin

Matthews

Johnson

(2021). Alcohol use among sexual minority women: Methods used and lessons learned in the 20-Year Chicago Health and Life Experiences of Women Study. The International Journal of Alcohol and Drug Research, 9(1), 30–42. https://doi.org/10.7895/ijadr.289

39.

Juster

R. P.

de Torre

M. B.

Kerr

Kheloui

Rossi

Bourdon

(2019). Sex differences and gender diversity in stress responses and allostatic load among workers and LGBT people. Current Psychiatry Reports, 21(11), 110. https://doi.org/10.1007/s11920-019-1104-2

40.

Kassing

Casanova

Griffin

J. A.

Wood

Stepleman

L. M.

(2021). The effects of polyvictimization on mental and physical health outcomes in an LGBTQ sample. Journal of Traumatic Stress, 34(1), 161–171. https://doi.org/10.1002/jts.22579

41.

Keyes

K. M.

Hatzenbuehler

M. L.

Hasin

D. S.

(2011). Stressful life experiences, alcohol consumption, and alcohol use disorders: The epidemiologic evidence for four main types of stressors. Psychopharmacology, 218(1), 1–17. https://doi.org/10.1007/s00213-011-2236-1

42.

Kidd

J. D.

Everett

B. G.

Corbeil

Shea

Hughes

T. L.

(2022). Gender self-concept and hazardous drinking among sexual minority women: Results from the Chicago Health and Life Experiences of Women (CHLEW) study. Addictive Behaviors, 132, 107366.

43.

Koob

G. F.

Le Moal

(2001). Drug addiction, dysregulation of reward, and allostasis. Neuropsychopharmacology: Official Publication of the American College of Neuropsychopharmacology, 24(2), 97–129. https://doi.org/10.1016/S0893-133X(00)00195-0

44.

Krieger

Smith

Naishadham

Hartman

Barbeau

E. M.

(2005). Experiences of discrimination: Validity and reliability of a self-report measure for population health research on racism and health. Social Science & Medicine, 61(7), 1576–1596. https://doi.org/10.1016/j.socscimed.2005.03.006

45.

Lanza

S. T.

Rhoades

B. L.

(2013). Latent class analysis: An alternative perspective on subgroup analysis in prevention and yreatment. Prevention Science, 14(2), 157–168. https://doi.org/10.1007/s11121-011-0201-1

46.

LaVeist-Ramos

T. A.

Galarraga

Thorpe

R. J.

Bell

C. N.

Austin

C. J.

(2012). Are black Hispanics black or Hispanic? Exploring disparities at the intersection of race and ethnicity. Journal of Epidemiology and Community Health, 66(7), e21. https://doi.org/10.1136/jech.2009.103879

47.

Layland

E. K.

Maggs

J. L.

Kipke

M. D.

Bray

B. C.

(2022). Intersecting racism and homonegativism among sexual minority men of color: Latent class analysis of multidimensional stigma with subgroup differences in health and sociostructural burdens. Social Science & Medicine, 293, 114602. https://doi.org/10.1016/j.socscimed.2021.114602

48.

Liautaud

M. M.

Barrington-Trimis

J. L.

Liu

Stokes

Krueger

E. A.

McConnell

Pang

R. D.

(2021). E-cigarette, cigarette, and cannabis use patterns as a function of sexual identity in a sample of Southern California young adults. Addictive Behaviors Reports, 13, 100338.

49.

López

Yeater

E. A.

Veldhuis

C. B.

Venner

K. L.

Verney

S. P.

Hughes

T. L.

(2023). Sexual assault, psychological distress, and protective factors in a community sample of black, Latinx, and white lesbian and bisexual women. Journal of Interpersonal Violence, 38(1–2), NP1239–NP1260. https://doi.org/10.1177/08862605221090570

50.

Lown

A. E. E.

Nayak

M. B.

Korcha

R. A.

Greenfield

T. K.

(2011). Child physical and sexual abuse: A comprehensive look at alcohol consumption patterns, consequences, and dependence from the national alcohol survey. Alcoholism: Clinical and Experimental Research, 35(2), 317–325. https://doi.org/10.1111/j.1530-0277.2010.01347.x

51.

MacCallum

R. C.

Zhang

Preacher

K. J.

Rucker

D. D.

(2002). On the practice of dichotomization of quantitative variables. Psychological Methods, 7(1), 19–40. https://doi.org/10.1037/1082-989X.7.1.19

52.

Martin

Johnson

T. P.

Hughes

T. L.

(2015). Using respondent driven sampling to reruit sexual minority women. Survey Practice, 8(2), 273.

53.

Matlin

S. L.

Champine

R. B.

Strambler

M. J.

O’Brien

Hoffman

Whitson

Kolka

Tebes

J. K.

(2019). A community’s response to adverse childhood experiences: Building a resilient, trauma-informed community. American Journal of Community Psychology, 64(3–4), 451–466. https://doi.org/10.1002/ajcp.12386

54.

McCabe

S. E.

Engstrom

C. W.

Kcomt

Evans-Polce

West

B. T.

(2022). Trends in binge drinking, marijuana use, illicit drug use, and polysubstance use by sexual identity in the United States (2006–2017). Substance Abuse, 43(1), 194–203. https://doi.org/10.1080/08897077.2021.1913696

55.

McCabe

S. E.

Hughes

T. L.

Beal

Evans-Polce

Kcomt

Engstrom

West

Veliz

Leary

McCabe

Boyd

(2022). Sexual orientation differences in childhood sexual abuse, suicide attempts, and DSM-5 alcohol, tobacco, other drug use, and mental health disorders in the US. Child Abuse & Neglect, 123, 105377. https://doi.org/10.1016/j.chiabu.2021.105377

56.

McCabe

S. E.

Hughes

T. L.

West

B. T.

Veliz

Boyd

C. J.

(2019). DSM-5 alcohol use disorder severity as a function of sexual orientation discrimination: A national study. Alcoholism: Clinical and Experimental Research, 43(3), 497–508. https://doi.org/10.1111/acer.13960

57.

McLaughlin

K. A.

Hatzenbuehler

M. L.

Xuan

Conron

K. J.

(2012). Disproportionate exposure to early-life adversity and sexual orientation disparities in psychiatric morbidity. Child Abuse & Neglect, 36(9), 645–655. https://doi.org/10.1016/j.chiabu.2012.07.004

58.

Meyer

(2003). Prejudice, social stress, and mental health in lesbian, gay, and bisexual populations: Conceptual issues and research evidence. Psychological Bulletin, 129(5), 674–697. https://doi.org/10.1037/0033-2909.129.5.674

59.

Moustafa

A. A.

Parkes

Fitzgerald

Underhill

Garami

Levy-Gigi

Stramecki

Valikhani

Frydecka

Misiak

(2021). The relationship between childhood trauma, early-life stress, and alcohol and drug use, abuse, and addiction: An integrative review. Current Psychology, 40(2), 579–584. https://doi.org/10.1007/s12144-018-9973-9

60.

Nurius

P. S.

Uehara

Zatzick

D. F.

(2013). Intersection of stress, social disadvantage, and life course processes: Reframing trauma and mental health. American Journal of Psychiatric Rehabilitation, 16(2), 91–114. https://doi.org/10.1080/15487768.2013.789688

61.

Nylund

K. L.

Asparouhov

Muthén

B. O.

(2007). Deciding on the number of classes in latent class analysis and growth mixture modeling: A Monte Carlo simulation study. Structural Equation Modeling: A Multidisciplinary Journal, 14(4), 535–569. https://doi.org/10.1080/10705510701575396

62.

Orchowski

L. M.

Edwards

K. M.

Hollander

J. A.

Banyard

V. L.

Senn

C. Y.

Gidycz

C. A.

(2020). Integrating sexual assault resistance, bystander, and men’s social norms strategies to prevent sexual violence on college campuses: A call to action. Trauma, Violence, & Abuse, 21(4), 811–827. https://doi.org/10.1177/1524838018789153

63.

Pinel

E. C.

(1999). Stigma consciousness: The psychological legacy of social stereotypes. Journal of Personality and Social Psychology, 76(1), 114–128.

64.

Porsch

L. M.

Veldhuis

C. B.

Bochicchio

L. A.

Zollweg

S. S.

Hughes

T. L.

(2022). Intimate partner violence among sexual minority women: A scoping review. Trauma, Violence, & Abuse. Advance online publication. https://doi.org/10.1177/15248380221122815

65.

Puckett

J. A.

Horne

S. G.

Herbitter

Maroney

M. R.

Levitt

H. M.

(2017). Differences across contexts: Minority stress and interpersonal relationships for lesbian, gay, and bisexual women. Psychology of Women Quarterly, 41(1), 8–19. https://doi.org/10.1177/0361684316655964

66.

Puckett

J. A.

Maroney

M. R.

Wadsworth

L. P.

Mustanski

Newcomb

M. E.

(2020). Coping with discrimination: The insidious effects of gender minority stigma on depression and anxiety in transgender individuals. Journal of Clinical Psychology, 76(1), 176–194. https://doi.org/10.1002/jclp.22865

67.

Puckett

J. A.

Woodward

E. N.

Mereish

E. H.

Pantalone

D. W.

(2015). Parental rejection following sexual orientation disclosure: Impact on internalized homophobia, social support, and mental health. LGBT Health, 2(3), 265–269. https://doi.org/10.1089/lgbt.2013.0024

68.

Scheer

J. R.

Edwards

K. M.

Helminen

E. C.

Watson

R. J.

(2021). Victimization typologies among a large national sample of sexual and gender minority adolescents. LGBT Health, 8(8), 507–518. https://doi.org/10.1089/lgbt.2021.0024

69.

Scheer

J. R.

Pachankis

J. E.

Bränström

(2022). Gender-based structural stigma and intimate partner violence across 28 countries: A population-based study of women across sexual orientation, immigration status, and socioeconomic status. Journal of Interpersonal Violence, 37(11–12), NP8941–NP8964. https://doi.org/10.1177/0886260520976212

70.

Schuler

M. S.

Collins

R. L.

(2020). Sexual minority substance use disparities: Bisexual women at elevated risk relative to other sexual minority groups. Drug and Alcohol Dependence, 206, 107755. https://doi.org/10.1016/j.drugalcdep.2019.107755

71.

Shramko

Toomey

R. B.

Anhalt

(2018). Profiles of minority stressors and identity centrality among sexual minority Latinx youth. The American Journal of Orthopsychiatry, 88(4), 471–482. https://doi.org/10.1037/ort0000298

72.

Straus

M. A.

Hamby

S. L.

Boney-McCoy

Sugarman

D. B.

(1996). The revised conflict tactics scales (CTS2). Journal of Family Issues, 17(3), 283–316.

73.

Sutter

M. E.

Rabinovitch

A. E.

Trujillo

M. A.

Perrin

P. B.

Goldberg

L. D.

Coston

B. M.

Calton

J. M.

(2019). Patterns of intimate partner violence victimization and perpetration among sexual minority women: A latent class analysis. Violence Against Women, 25(5), 572–592. https://doi.org/10.1177/1077801218794307

74.

Sutton

T. E.

Edwards

K. M.

Siller

Shorey

R. C.

(2021). An exploration of factors that mediate the relationship between adverse childhood experiences and sexual assault victimization among LGBTQ+ college students. Child Maltreatment, 27(4), 539–549. https://doi.org/10.1177/10775595211041970

75.

Talley

A. E.

Veldhuis

Wall

M. M.

Wilsnack

S. C.

Everett

B. G.

Hughes

T. L.

(2022). Associations of adult roles and minority stressors with trajectories of alcohol dependence symptoms throughout adulthood among sexual minority women. Psychology of Addictive Behaviors. Advance online publication. https://doi.org/10.1037/adb0000869

76.

Veldhuis

C. B.

Drabble

Riggle

E. D. B.

Wootton

A. R.

Hughes

T. L.

(2018). “I fear for my safety, but want to show bravery for others”: Violence and discrimination concerns among transgender and gender-nonconforming individuals after the 2016 presidential election. Violence and Gender, 5(1), 26–36. https://doi.org/10.1089/vio.2017.0032

77.

Veldhuis

C. B.

Hughes

T. L.

Drabble

Wilsnack

S. C.

Matthews

(2020). Do relationships provide the same levels of protection against heavy drinking for lesbian and bisexual women? An intersectional approach. Psychology of Sexual Orientation and Gender Diversity, 7(3), 337–352. https://doi.org/10.1037/sgd0000383

78.

Veldhuis

C. B.

Hughes

T. L.

Drabble

Wilsnack

S. C.

Riggle

E. D. B.

Rostosky

S. S.

(2019). Relationship status and drinking-related outcomes in a community sample of lesbian and bisexual women. Journal of Social and Personal Relationships, 36(1), 244–268. https://doi.org/10.1177/0265407517726183

79.

Veldhuis

C. B.

Juster

R. P.

Corbeil

Wall

Poteat

Hughes

T. L.

(2023). Testing whether the combination of victimization and minority stressors exacerbate PTSD risks in a diverse community sample of sexual minority women. Psychology & Sexuality, 14(1), 252–278. https://doi.org/10.1080/19419899.2022.2106147

80.

Vermunt

J. K.

Magidson

(2016). Technical guide for Latent GOLD 5.1: Basic, advanced, and syntax. Statistical Innovations Inc.

81.

White

(2020). Gender differences in the epidemiology of alcohol use and related harms in the United States. Alcohol Research: Current Reviews, 40(2), 1–13. https://doi.org/10.35946/arcr.v40.2.01

82.

Wilsnack

R. W.

Wilsnack

S. C.

Gmel

Kantor

L. W.

(2018). Gender differences in binge drinking. Alcohol Research: Current Reviews, 39(1), 57–76.

83.

Wilsnack

S. C.

Hughes

T. L.

Johnson

T. P.

Bostwick

W. B.

Szalacha

L. A.

Benson

Aranda

Kinnison

K. E.

(2008). Drinking and drinking-related problems among heterosexual and sexual minority women. Journal of Studies on Alcohol and Drugs, 69(1), 129–139. https://doi.org/10.15288/jsad.2008.69.129

84.

Wilsnack

S. C.

Kristjanson

A. F.

Hughes

T. L.

Benson

P. W.

(2012). Characteristics of childhood sexual abuse in lesbians and heterosexual women. Child Abuse & Neglect, 36(3), 260–265. https://doi.org/10.1016/j.chiabu.2011.10.008

85.

Woodford

M. R.

Kulick

Garvey

J. C.

Sinco

B. R.

Hong

J. S.

(2018). LGBTQ policies and resources on campus and the experiences and psychological well-being of sexual minority college students: Advancing research on structural inclusion. Psychology of Sexual Orientation and Gender Diversity, 5, 445–456. https://doi.org/10.1037/sgd0000289

86.

Wyatt

G. E.

(1985). The sexual abuse of Afro-American and White-American women in childhood. Child Abuse & Neglect, 9(4), 507–519. https://doi.org/10.1016/0145-2134(85)90060-2

87.

Young

T. L.

Riggs

Robinson

J. L.

(2011). Childhood sexual abuse severity reconsidered: A factor structure of CSA characteristics. Journal of Child Sexual Abuse, 20(4), 373–395. https://doi.org/10.1080/10538712.2011.590124

88.

Zaso

M. J.

Read

J. P.

(2020). Drinking motives as moderators of in-the-moment drinking risks in response to trauma-related distress. Alcoholism, Clinical and Experimental Research, 44(12), 2561–2569. https://doi.org/10.1111/acer.14487

89.

Zimet

G. D.

Dahlem

N. W.

Zimet

S. G.

Farley

G. K.

(1988). The multidimensional scale of perceived social support. Journal of Personality Assessment, 52(1), 30–41. https://doi.org/10.1207/s15327752jpa5201_2

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.19 MB

0.30 MB