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Published in final edited form as: J Gay Lesbian Ment Health. 2022 Jun 20;28(1):132–145. doi: 10.1080/19359705.2022.2046973

Factor structure of the Outness Inventory in a sample of Black and White lesbian and bisexual young adult women

Alexis Sheffield 1, Irene Tung 2, Johnny Berona 4, Jessie B Northrup 2, Sierra Nannini 2, Alison E Hipwell 2,3, Kate Keenan 4
PMCID: PMC10977668  NIHMSID: NIHMS1803557  PMID: 38560510

Abstract

Introduction:

The Outness Inventory (OI; Mohr & Fassinger, 2000) is the most commonly used measure for assessing an individual’s level of outness, or openness about sexual identity. However, data on the validity of the OI factor structure across diverse populations is limited. The present study aimed to test the factor structure of the OI in a population-based sample of Black and White young adult women.

Method:

Participants included 319 lesbian and bisexual women drawn from the Pittsburgh Girls Study (PGS), a large longitudinal study of 5- to 8-year-old girls (53% Black) oversampled from low-income neighborhoods and followed through adulthood. Participants completed the 11-item OI at ages 20–23 years. Confirmatory factor analyses evaluated measurement invariance of the OI across race and suggested significant differences in factor structure between Black and White sexual minority women. Exploratory factor analyses were conducted separately by race.

Results:

An EFA revealed three factors for the Black subsample: Family, Straight Friends, and Work/Strangers. Three factors also emerged for the White subsample, representing Familiar Acquaintances, Less Familiar Acquaintances, and Work.

Conclusion:

Additional research is needed to investigate potential culturally-based differences in domains of disclosure, which may help to better understand how specific contexts of outness relate to mental health.

Keywords: outness, lesbian, bisexual, sexual minority

Introduction

Sexual minority individuals experience higher rates of adverse health outcomes across physical and mental health domains than heterosexual individuals (Frost, Lehavot, & Meyer, 2015; Lick, Durso, & Johnson, 2013; Plöderl & Tremblay, 2015). According to the minority stress model (Meyer, 2003), these health disparities are driven by higher levels of stress exposure experienced due to sexual minority status, effects magnified for individuals who experience multiple intersecting minority status identities related to their gender or race/ethnicity. For example, studies suggest that approximately 3.4% of women in the United States identify as lesbian, gay, or bisexual (Gates, 2001), and sexual minority women (SMW) may experience higher levels of discrimination due to their multiple marginalized identities as women and sexual minorities (Hagen, Hoover, & Morrow, 2018). Interpersonal stress may be particularly elevated for SMW who have disclosed their sexual identity to others. Indeed, outness (i.e., disclosing sexual identity) has been shown to significantly influence interpersonal interactions, including daily stressful experiences (e.g., microaggressions) and receipt of social support (Pachankis, 2007; Tabaac, Perrin, & Trujillo, 2015). Importantly, there is a growing body of evidence that suggests SMW may experience and express their sexuality differently from sexual minority men (Diamond, 2014; Diamond, 2016). For example, prior studies comparing SMW and sexual minority men have shown that SMW reach milestones of sexual development later than sexual minority men (i.e., same-gender attraction, same-gender sexual experience, and sexual minority identity; Katz-Wise et al., 2016). Additionally, within a sample of sexual minorities and individuals who endorse a history of same-gender sexual behavior, women were more likely to report same-gender attraction, other-gender attraction, and other-gender sexual experience (Katz-Wise et al., 2016). SMW may also show greater responsivity to relationship contexts; thus, changes in the sex of their partner from one relationship to another and changes in attraction across time can affect choices to “come out” and/or change how they self-identify (e.g., women are more likely than men to identify as bisexual or gay/lesbian after engaging in a romantic and/or sexual relationship with a same-gender partner; Everett et al., 2016). Indeed, individuals with bisexual identities are less likely to be “out” across contexts than their gay or lesbian counterparts (Legate, Ryan, & Weinstein, 2012). Together, these findings support the need for additional studies that investigate the complex ways in which SMW conceptualize and experience outness.

Prior research has demonstrated that an individual’s level of outness can vary significantly depending on their social context (e.g., family vs. friends or strangers) (Belmonte & Holmes, 2016), highlighting the need for measures that consider contextual differences in outness. As Aranda et al. noted (2016), every interaction involving a SMW has the potential for disclosure. Indeed, different approaches to understanding how outness interacts with environmental context may be one reason why prior studies have reported inconsistent associations between outness and health outcomes (Riggle et al., 2017; Operario et al., 2015; Legate, Ryan, & Weinstein, 2012; Frost, Lehavot, & Meyer, 2015). Differentiating contexts of outness may be particularly important during the transitional phase of early adulthood when individuals experience shifts to new settings as they enter the workforce or higher education institutions. However, there is not a 1:1 correspondence between behavior and identity, which further complicates individuals’ decisions to “come out.” For example, a woman may be dating another woman and identify as heterosexual (e.g., not consider herself as lesbian or bisexual), despite engaging in same-gender sexual activity. Thus, same-gender sexual activity and sexual minority identity are related but distinct constructs with identity as a prerequisite for outness.

The Outness Inventory (OI; Mohr & Fassinger, 2000) is the most commonly used measure for assessing an individual’s level of outness across multiple social spheres. The OI was developed 20 years ago using a convenience sample. Participants were predominantly (86%) White, college-educated lesbian women and gay men ranging in age from 18 to 69 years old (M = 36.62, SD= 9.47), who had maintained a same-sex relationship for 3 months or longer. Participants were recruited based on their response to fliers posted in several East Coast cities, advertisements placed in a gay newspaper in the DC area, or emails which had been sent to lesbian and gay organizations. Based on responses from this sample, three factors of outness were identified: “Out to World,” “Out to Family,” and “Out to Religion.” However, since this initial study, no further tests of measurement validity, including the replication of the factor structure of the OI, have been conducted.

Thus, although the OI and its subscales have been used across diverse settings and samples (e.g., Moradi et al., 2010; Balsam et al., 2011; Zimmerman et al., 2015; Brewster et al., 2013), it is unclear whether the measure captures relevant domains for current populations of sexual minority young adult women. For example, because the inclusion criteria for the initial study required participants to have been in a same-sex relationship for 3 months or longer, this sampling method effectively excluded “closeted,” “newly out,” or single participants, which may be particularly relevant for individuals in the young adult age group. Bisexual participants were also excluded from the initial analysis, an important limitation given that bisexual women constitute a large proportion of SMW but have been relatively understudied. Bisexual-identified individuals report unfair treatment by both heterosexuals and lesbians/gays, invalidation and erasure of their sexual identity, and higher levels of sexual victimization (Van et al., 2019). Thus, “coming out” may result in higher costs for women who identify as bisexual, including worse physical and mental health outcomes than heterosexual or lesbian/gay women (Feinstein et al., 2019; Dilley et al., 2010; Plöderl & Tremblay, 2015). This subgroup may further differ from the original sample in that they may have had same-sex and/or heterosexual relationships, further complicating their choice to “come out.”

Similarly, because the measure was developed in a predominantly White and college-educated convenience sample, it is unclear if the original factor structure of the OI generalizes to women of color, such as Black women who identify as lesbian, bisexual, or gay. Black women in the US who identify as sexual minorities are vulnerable to stressors associated with both racism and heterosexism, which may explain higher rates of depression for Black SMW (Mays, Cochran, & Roeder, 2004) and affect how they negotiate outness (Casey et al., 2019; Balsam et al., 2011; Malebranche et al., 2009). Additionally, some evidence suggests that compared to White SMW, Black SMW may have additional cultural barriers to disclosure within their family context which can influence rates of outness. For example, one study found that the greatest cultural barriers in coming out to parents are reported by Asian/Pacific Islander men, followed by Black and Latinx women and men, with White individuals endorsing the fewest cultural barriers to coming out (Riley, 2010). Thus, Black women may be more likely to conceal their sexual identity to prioritize family harmony (Bowleg et al., 2003; Balsam et al., 2015). An additional factor related to disclosure is whether an individual’s race or ethnicity is perceived to be of equal or greater weight than sexual identity in their self-concept (Greene, 1996). Supporting this view, Bowleg and colleagues (2003) found that Black lesbians often considered race to be the most important factor in their sense of self. Accordingly, studies suggest that on average, Black lesbian women disclose their sexual identity less frequently to individuals outside of the family compared to White women (Aranda et al., 2016; Rosario, Schrimshaw, & Hunter, 2004; Parks et al., 2004).

To advance research on outness, it is crucial to establish that the factors commonly used to study outness are capturing valid and meaningful constructs across racial/ethnic groups, such as between White and Black SMW. Given that the original factor structure of the OI was validated among predominantly White individuals, it may not accurately capture how the items cluster for Black SMW. For example, relative to White families, Black families may be more likely to have members of their extended family living in the household, which could lead to closer affective ties between non-nuclear relatives (Cross, 2018). Researchers have also illustrated the importance of “fictive kin” within the Black social structure and its similarity to the concept of “chosen families” as experienced by sexual minorities (Stewart, 2007; Mays, Chatters, Cochran, & Mackness, 1998). Because of racial differences in the family social structure, Black SMW may be more likely to self-disclose to extended family members and fictive kin at similar rates of disclosure as to immediate family members. Thus, racial differences in how the social environment is structured could lead to differences in the factor structure of the OI between Black and White SMW.

The present study

The primary goal of the present study was to validate the factor structure of the OI in a sample of Black and White young adult bisexual and lesbian women using confirmatory factor analysis. Furthermore, we additionally examined whether the factor structure of the OI differed by race by testing for measurement invariance between Black and White SMW.

Methods

Sample

Participants were drawn from the Pittsburgh Girls Study (PGS, n=2450), an ongoing longitudinal study focused on investigating the development of mental health and behavioral outcomes in girls and young women. Following a city-wide enumeration, low-income neighborhoods were oversampled to identify families with girls between the ages of 5–8 years in 1999–2000 (see details in Hipwell et al., 2002; Keenan et al., 2010). Children living in poverty experience increased vulnerability for later mental health problems due to exposure to chronic stressors associated with economic inequities in the US (Dodge, Pettit, & Bates, 1994). To increase power to elucidate the mechanisms whereby poverty confers risk for mental health and behavioral outcomes, the original PGS oversampled families from low-income neighborhoods. Of the 2450 participants, close to half of the participants’ caregivers had completed a high school education or less, and 39% of the households received public assistance (e.g., WIC, Medicaid) in the first PGS assessment wave. Approximately 53% of the PGS sample identified as Black/African American, 41% White/European American, 1% Asian American, and 5% multiracial. Thus, relative to the 2000 US Census report for the city of Pittsburgh, in which 67.6% of residents identified as White/European American and 27.1% identified as Black/African American, the PGS sample included a larger proportion of Black/African American families and a smaller proportion of White/European American families. Participants have been assessed annually in the home since their recruitment at ages 5–8, and high retention rates have been maintained throughout the study: 86% in assessment wave 16 (ages 20–23) when the OI was first introduced. Approval for all study procedures was obtained from the University of Pittsburgh Institutional Review Board, and written informed consent was obtained from the young women.

The current analysis focused on a subset of SMW (N=319; 15%) from the larger PGS who self-identified as lesbian/gay (N=86) or bisexual (N=233) when assessed in PGS wave 16. Participants ranged between the ages of 20–23 (M = 21.40). Other participants were excluded because they were unsure of their sexuality (n=11; 0.4%) or refused to answer the sexual orientation item (n=3; 0.1%). The sexual minority subsample did not differ from the rest of the PGS in terms of race (53% Black in both groups; X2(1) = .009, p = .923). Participants in the sexual minority subsample reported fewer years of education (47% with 12 years or less of education vs. 36% of the heterosexual participants; X2(1) = 14.944, p < .001) and were more likely to live in a household receiving public assistance than the heterosexual participants (48% vs. 42%; X2(1) = 3.859, p = .049).

Measures

Demographic variables (including race, highest level of education received, and employment status) were based on self-report. Household poverty was defined by familial receipt of public assistance (e.g., Women, Infants, and Children; Medicaid).

Sexual identity was assessed at ages 20–23 via self-report on a single item that asked, “Do you consider yourself to be…?” with response choices of lesbian/gay, bisexual, or heterosexual/straight.

Outness was measured using the Outness Inventory (OI; Mohr & Fassinger, 2000), which is a widely used self-report measure of a sexual minority individual’s level of outness with coworkers, employers, family, friends, members of their religious community (if applicable), and strangers. The measure includes 11 items that are scored on a 7-point Likert scale (ranging from 1 = “person does not know about your sexual orientation” to 7 = “person definitely knows about your sexual orientation, and it is openly talked about”). The items are grouped according to the three subscales: “Out to World,” “Out to Family,” and “Out to Religion.” Higher scores indicate greater openness about the participant’s sexual orientation. Of note, the two OI items assessing outness to participants’ religious community and leaders of the religious community were not relevant for the majority of the sample: 169 of 319 (53%) participants selected the response, “there is no such person or group of people in my life.” To maintain a sufficiently sized sample for stability of factor structure (Guadagnoli & Velicer, 1988; Costello & Osborne, 2005), these two items were excluded from analyses.

Data analytic plan

Analyses proceeded in three steps. First, a confirmatory factor analysis (CFA) was conducted with the overall sample to assess whether the previously identified factors of “Out to Family” and “Out to World” adequately fit the data for the present study. Standard indices were examined, including the comparative fit index (CFI), Tucker Lewis Index (TLI), root mean square error of approximation (RMSEA), and standardized root mean square residual (SRMR). We assessed whether indices were within recommended ranges for good model fit (CFI, TLI ≥ 0.90; RMSEA < 0.08; SRMR < 0.08; Hooper, 2008). Second, we used multigroup CFA to test for measurement invariance between Black and White women. Specifically, chi-square tests examined whether differences were present when groups were constrained to have the same factor structure (configural invariance), factor loadings (scalar invariance), and item thresholds (metric invariance). Third, we used exploratory factor analysis (EFA) to identify factor structures that may differ by race. All analyses were conducted in Mplus 8.5 using weighted least squares means and variance adjusted estimator (WLSMV) for ordinal variables.

Results

Descriptive analyses

Table 1 shows the demographic characteristics of the N=319 SMW. Significant differences in socioeconomic status were observed by race, with 30% of White participants having 12 years of schooling or less compared to 70% of Black participants (X2(1)=35.361, p<.001). Additionally, 33% of the White subsample received public aid compared to 67% of the Black subsample (X2(1)=25.434, p<.001). Bisexual and lesbian participants reported similar levels of education, with 45.3% of lesbian participants completing 12 years of school or less compared to 48% of bisexual participants (X2(1) = .186, p = .666), and 42% of the lesbian subsample receiving public aid compared to 50% of their bisexual counterparts (X2(1) = 1.458, p = .23).

Table 1.

Descriptive Statistics of Sociodemographic Characteristics in the full sample of SMW (N = 319)

Demographic Variable N %
Race Black 168 52.7%
White 131 41.1%
Education ≤12 years of school 151 47.3%
>12 years of school 168 52.7%
Income Public assistance 152 47.6%
No public assistance 165 51.7%
Sexual orientation Bisexual 233 73.0%
Lesbian 86 27.0%
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Confirmatory factor analyses

The factor structure of the CFA model demonstrated good fit for the overall sample (CFI=.99, TLI=.98, RMSEA=.08, SRMR=.04). However, the chi-square test for configural invariance indicated that CFA model fit differed significantly between the Black and White groups (χ2 (9) = 21.86, p = .009). Model fit began to decline further when groups were constrained to have equivalent factor loadings (χ2 (7) = 13.2, p = .07) and item thresholds (χ2 (50) = 86.0, p = .001), suggesting that the structure of factors may differ between Black and White women.

Exploratory factor analyses

As the OI did not display robust invariance by race, separate EFA models were conducted for the subsamples and allowed up to 3 factors to be extracted. For both subgroups, the 3-factor solutions displayed the best fit across all indices. For the Black subsample, the first factor included items indicating outness to family (see Table 2). The second factor included items indicating outness to peers at work, supervisor at work, strangers, and new straight friends. The third factor included being out to old and new straight friends. For the White subsample, the first factor indicated outness to familiar acquaintances (family and old straight friends; see Table 3). Being out to new straight friends and strangers loaded onto the second factor. The third factor included being out to peers and supervisor out work.

Table 2.

Exploratory factor analysis of the Outness Inventory in the subsample of Black SMW (N = 168)

Item Factor 1 Factor 2 Factor 3
Out to:
 Mother 1.21
 Father .80
 Siblings .92
 Extended family .84
 Old straight friends .65
 New straight friends 43 .52
 Peers at work .76
 Supervisor at work 1.22
 Strangers .60
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Note. Table displays geomin rotated factor loadings above .35 significant at p < .05.

Table 3.

Exploratory factor analysis of the Outness Inventory in the subsample of White SMW (N = 130)

Item Factor 1 Factor 2 Factor 3
Out to:
 Mother .94
 Father .98
 Siblings .56
 Extended family .77
 Old straight friends .45
 New straight friends 1.05
 Peers at work .71
 Supervisor at work .77
 Strangers .58
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Note. Table displays geomin rotated factor loadings above .35 significant at p < .05.

Discussion

The present study examined the OI factor structure in a young adult sample of Black and White SMW. As previously described, the initial principal components analysis (PCA) of the OI was conducted 20 years ago with a mixed gender sample of predominantly White adults aged 18–69 years and identified three components of outness: “Out to Family,” “Out to World,” and “Out to Religion.” Several key differences emerged when examining the factor structure of the OI in this more recent sample of Black and White sexual minority women. First, because over half of the participants in our sample reported no religious affiliation (i.e., items regarding religious contexts were marked as not applicable), these two items could not be included in analysis. Our results suggest that the two remaining factors of the OI did not demonstrate measurement invariance across race, such that the contextual patterns of outness differed when comparing Black and White participants. As we discuss further below, the difference in the configural models may reflect differences in young adult social relationship domains, with variability in the degree to which friends overlap across the “work peers” and “straight friends” categories.

Overall, our results drawn from this more recent sample of young adult women emphasize the need to consider contextual differences in outness among young adult SMW. Whereas the original OI study found that old and new friends, co-workers, and strangers loaded onto a single “Out to World” component, our findings suggest that there are additional separations among SMW that need to be considered. Using the present sample to examine factor structure, a more nuanced picture of outness unfolded that differentiated between friends, co-workers, and strangers. This suggests that levels of self-disclosure shift across these environments and SMW may manage their identities through “strategic outness” (Orne, 2012). For example, our findings suggest that it is important to consider variability in overlap between work peers and friends, given that the frequency of outness may differ across these contexts. Particularly in the transitional period of early adulthood, participants may self-disclose to their work community at a lower frequency, in specific contexts, or at a later timepoint than they disclose to family or friends.

Our results also suggest that the patterns in which outness may vary across contexts may differ between Black and White SMW. Specifically, a distinct “Out to Work” factor (separated from friends and strangers) emerged for the White subsample, whereas items related to co-workers, new straight friends, and strangers loaded onto the same factor for the Black subsample. In interpreting these findings, it is important to consider other sociodemographic factors that may be intersecting with the differences observed between Black and White young adult women in our sample. In early adulthood, the level of exposure to new social circles and the amount of work experience may differ based on income-level and post-high school education. Because Black SMW in our sample were more likely to be experiencing financial stressors (i.e., higher rates of receiving public assistance in Wave 16) than White SMW, race differences observed in the factor structure of outness could partially reflect racial disparities in earlier age of entry into the workforce or differences in the industry of work. For example, young adults who grew up in low-resourced households may enter the workforce earlier and have more established relationships with coworkers, resulting in new friendships (explaining the loading of new straight friends onto both “Out to Work/Strangers” and “Out to Straight Friends” factors). Additionally, the development of an “Out to Familiar Acquaintances” factor for the White subsample may suggest that participants endorse “chosen families,” consisting of family members and close friends (Lee & Quam, 2013). Follow-up studies are needed to directly investigate how differences in work settings and friendship dynamics can influence the way in which patterns of outness may differ between Black and White sexual minority women, particularly during the transitional period of early adulthood.

Several limitations of the present study are noted. First, the sample was drawn from an urban environment in Pittsburgh and focused exclusively on Black and White SMW; thus, results may not generalize to rural populations of SMW or SMW from other racial and ethnic groups. Second, the modest sample size of participants who endorsed a religious community did not allow us to test the factor structure of the OI measure with these items or assess racial differences in outness to religious community. This may reflect a cohort effect, general disengagement with religion during this developmental period, or could be specific to young adult SMW living in an urban setting. Third, the relatively small sample of lesbian/gay women prevented us from examining measurement invariance across sexual identity and thereby assessing whether the factor structure differed for participants who identified as bisexual versus lesbian/gay. It is therefore possible that combining the lesbian/gay and bisexual participants into a single sexual minority category obscured differences between these subgroups. Finally, it should be noted that the language used to assess participants’ sexual identity did not provide options beyond heterosexual, lesbian, or bisexual. Queer individuals who would describe themselves using different language if given the opportunity may conceptualize their identity and outness differently than those who use the terms “lesbian” or “bisexual” when self-describing sexual orientation.

Despite the limitations, this is the first study to examine the validity of the OI subscales in a Black and White sample of young adult SMW. Our findings emphasize the need to consider a more nuanced approach to investigating outness outside of the family context. The original “Out to World” factor may not be useful because it obscures differences in outness to work communities with outness to friends and strangers. Our study also expanded on prior studies by establishing differences in the factor structure of the OI for Black and White SMW. Group differences in the contexts of outness may signify a difference in the experience of self-disclosure, the decision-making process involved, or how individuals structure their social environment. Future research could assess whether the timing of outness, quality of relationships, and the type of work environment affect participants’ conceptualizations of their social structure in the context of outness. Outness is a salient construct in the context of health, minority stress, and psychological wellbeing, and it is critical to measure outness in a rigorous manner to understand its connection to physical and mental health outcomes. The present analysis reflects an opportunity to improve our framework for assessing outness by highlighting ways in which patterns of outness may vary between Black and White lesbian and bisexual young adult women.

Acknowledgements

This work was supported by funding from the National Institutes of Health under grants R01 MH0506630 and R01 HL137246. Special thanks to families and staff of the Pittsburgh Girls Study (PGS) and the Health, Environment Adapted over Time (HEArT) substudy.

Footnotes

Declaration of interest

No competing financial interests exist.

References

  1. Alexander M (2010). The new Jim Crow: Mass incarceration in the age of colorblindness. The New Press. [Google Scholar]
  2. Angel R, & Tienda M (1982). Determinants of extended household structure: Cultural pattern or economic need?. American journal of Sociology, 87(6), 1360–1383. [Google Scholar]
  3. Aranda F, Matthews AK, Hughes TL, Muramatsu N, Wilsnack SC, Johnson TP, & Riley BB (2015). Coming out in color: Racial/ethnic differences in the relationship between level of sexual identity disclosure and depression among lesbians. Cultural Diversity and Ethnic Minority Psychology, 21(2), 247. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Balsam KF, Lehavot K, Beadnell B, & Circo E (2010). Childhood abuse and mental health indicators among ethnically diverse lesbian, gay, and bisexual adults. Journal of Consulting and Clinical Psychology, 78(4), 459. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Balsam KF, Molina Y, Beadnell B, Simoni J, & Walters K (2011). Measuring multiple minority stress: the LGBT People of Color Microaggressions Scale. Cultural Diversity and Ethnic Minority Psychology, 17(2), 163. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Balsam KF, Molina Y, Blayney JA, Dillworth T, Zimmerman L, & Kaysen D (2015). Racial/ethnic differences in identity and mental health outcomes among young sexual minority women. Cultural Diversity and Ethnic Minority Psychology, 21(3), 380. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Belmonte K, & Holmes TR (2016). Outside the LGBTQ “safety zone”: Lesbian and bisexual women negotiate sexual identity across multiple ecological contexts. Journal of Bisexuality, 16(2), 233–269. [Google Scholar]
  8. Bowleg L, Huang J, Brooks K, Black A, & Burkholder G (2003). Triple jeopardy and beyond: Multiple minority stress and resilience among Black lesbians. Journal of lesbian studies, 7(4), 87–108. [DOI] [PubMed] [Google Scholar]
  9. Brewster ME, Moradi B, DeBlaere C, & Velez BL (2013). Navigating the borderlands: The roles of minority stressors, bicultural self-efficacy, and cognitive flexibility in the mental health of bisexual individuals. Journal of Counseling Psychology, 60(4), 543. [DOI] [PubMed] [Google Scholar]
  10. Casey LS, Reisner SL, Findling MG, Blendon RJ, Benson JM, Sayde JM, & Miller C (2019). Discrimination in the United States: Experiences of lesbian, gay, bisexual, transgender, and queer Americans. Health Services Research, 54, 1454–1466. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Costello AB, & Osborne JW (2005). Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis. Practical assessment, research & evaluation, 10(7), 1–9. [Google Scholar]
  12. Cross CJ (2018). Extended family households among children in the United States: Differences by race/ethnicity and socio-economic status. Population Studies, 72(2), 235–251. [DOI] [PubMed] [Google Scholar]
  13. Diamond LM (2014). Gender and same-sex sexuality. In APA handbook of sexuality and psychology, Vol. 1: Person-based approaches. (pp. 629–652). American Psychological Association. [Google Scholar]
  14. Diamond LM (2016). Sexual fluidity in male and females. Current Sexual Health Reports, 8(4), 249–256. [Google Scholar]
  15. Dilley JA, Simmons KW, Boysun MJ, Pizacani BA, & Stark MJ (2010). Demonstrating the importance and feasibility of including sexual orientation in public health surveys: health disparities in the Pacific Northwest. American journal of public health, 100(3), 460–467. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Dodge KA, Pettit GS, & Bates JE (1994). Socialization mediators of the relation between socioeconomic status and child conduct problems. Child Development, 65, 649–665. [PubMed] [Google Scholar]
  17. Dubé EM, & Savin-Williams RC (1999). Sexual identity development among ethnic sexual-minority male youths. Developmental Psychology, 35(6), 1389. [DOI] [PubMed] [Google Scholar]
  18. Everett BG, Talley AE, Hughes TL, Wilsnack SC, & Johnson TP (2016). Sexual identity mobility and depressive symptoms: A longitudinal analysis of moderating factors among sexual minority women. Archives of sexual behavior, 45(7), 1731–1744. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Feinstein BA, Dyar C, Li DH, Whitton SW, Newcomb ME, & Mustanski B (2019). The longitudinal associations between outness and health outcomes among gay/lesbian versus bisexual emerging adults. Archives of sexual behavior, 48(4), 1111–1126. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Floyd FJ, & Bakeman R (2006). Coming-out across the life course: Implications of age and historical context. Archives of sexual behavior, 35(3), 287–296. [DOI] [PubMed] [Google Scholar]
  21. Frost DM, Lehavot K, & Meyer IH (2015). Minority stress and physical health among sexual minority individuals. Journal of behavioral medicine, 38(1), 1–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Gates GJ (2001, April). How many people are lesbian, gay, bisexual, and transgender? The Williams Institute at UCLA School of Law. https://williamsinstitute.law.ucla.edu/publications/how-many-people-lgbt/.
  23. Greene B (1996). Lesbian women of color: Triple jeopardy. Journal of lesbian studies, 1(1), 109–147. [DOI] [PubMed] [Google Scholar]
  24. Guadagnoli E, & Velicer WF (1988). Relation of sample size to the stability of component patterns. Psychological bulletin, 103(2), 265. [DOI] [PubMed] [Google Scholar]
  25. Hagen WB, Hoover SM, & Morrow SL (2018). A grounded theory of sexual minority women and transgender individuals’ social justice activism. Journal of homosexuality, 65(7), 833–859. [DOI] [PubMed] [Google Scholar]
  26. Hipwell AE, Loeber R, Stouthamer‐Loeber M, Keenan K, White HR, & Kroneman L (2002). Characteristics of girls with early onset disruptive and antisocial behaviour. Criminal Behaviour and Mental Health, 12(1), 99–118. [DOI] [PubMed] [Google Scholar]
  27. Hooper D, Coughlan J, & Mullen M (2008, September). Evaluating model fit: a synthesis of the structural equation modelling literature. In 7th European Conference on research methodology for business and management studies (pp. 195–200). [Google Scholar]
  28. Hsieh N, & Ruther M (2016). Sexual minority health and health risk factors: intersection effects of gender, race, and sexual identity. American Journal of Preventive Medicine, 50(6), 746–755. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Keenan K, Hipwell A, Chung T, Stepp S, Stouthamer-Loeber M, Loeber R, & McTigue K (2010). The Pittsburgh Girls Study: overview and initial findings. Journal of Clinical Child & Adolescent Psychology, 39(4), 506–521. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Kennamer JD, Honnold J, Bradford J, & Hendricks M (2000). Differences in disclosure of sexuality among African American and White gay/bisexual men: Implications for HIV/AIDS prevention. AIDS Education and Prevention, 12(6), 519. [PubMed] [Google Scholar]
  31. Lee MG, & Quam JK (2013). Comparing supports for LGBT aging in rural versus urban areas. Journal of Gerontological Social Work, 56(2), 112–126. [DOI] [PubMed] [Google Scholar]
  32. Legate N, Ryan RM, & Weinstein N (2012). Is coming out always a “good thing”? Exploring the relations of autonomy support, outness, and wellness for lesbian, gay, and bisexual individuals. Social Psychological and Personality Science, 3(2), 145–152. [Google Scholar]
  33. Lick DJ, Durso LE, & Johnson KL (2013). Minority stress and physical health among sexual minorities. Perspectives on Psychological Science, 8(5), 521–548. [DOI] [PubMed] [Google Scholar]
  34. Malebranche DJ, Fields EL, Bryant LO, & Harper SR (2009). Masculine socialization and sexual risk behaviors among Black men who have sex with men: A qualitative exploration. Men and Masculinities, 12(1), 90–112. [Google Scholar]
  35. Martinez O, Lee JH, Bandiera F, Santamaria EK, Levine EC, & Operario D (2017). Sexual and behavioral health disparities among sexual minority Hispanics/Latinos: Findings from the National Health and Nutrition Examination Survey, 2001–2014. American journal of preventive medicine, 53(2), 225–231. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Mays VM, Chatters LM, Cochran SD, & Mackness J (1998). African American families in diversity: Gay men and lesbians as participants in family networks. Journal of Comparative Family Studies, 29, 73–87. [Google Scholar]
  37. Mays VM, Cochran SD, & Rhue S (1993). The impact of perceived discriminitation on the intimate relationships of black lesbians. Journal of homosexuality, 25(4), 1–14. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Mays VM, Cochran SD, & Roeder MR (2004). Depressive distress and prevalence of common problems among homosexually active African American women in the United States. Journal of Psychology & Human Sexuality, 15(2–3), 27–46. [Google Scholar]
  39. McGarrity LA, & Huebner DM (2014). Behavioral intentions to HIV test and subsequent testing: The moderating role of sociodemographic characteristics. Health Psychology, 33(4), 396. [DOI] [PubMed] [Google Scholar]
  40. Meyer IH (2003). Prejudice, social stress, and mental health in lesbian, gay, and bisexual populations: conceptual issues and research evidence. Psychological bulletin, 129(5), 674. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Mohr J, & Fassinger R (2000). Measuring dimensions of lesbian and gay male experience. Measurement and Evaluation in Counseling and Development, 33(2), 66–66. [Google Scholar]
  42. Moradi B, Wiseman MC, DeBlaere C, Goodman MB, Sarkees A, Brewster ME, & Huang YP (2010). LGB of color and white individuals’ perceptions of heterosexist stigma, internalized homophobia, and outness: Comparisons of levels and links. The Counseling Psychologist, 38(3), 397–424. [Google Scholar]
  43. Morales ES (1989). Ethnic minority families and minority gays and lesbians. Marriage & Family Review, 14(3–4), 217–239. [Google Scholar]
  44. Morris JF, & Rothblum ED (1999). Who fills out a “lesbian” questionnaire? The interrelationship of sexual orientation, years “out,” disclosure of sexual orientation, sexual experience with women, and participation in the lesbian community. Psychology of Women Quarterly, 23(3), 537–557. [Google Scholar]
  45. Newport F (2018, May 22). In U.S., Estimate of LGBT Population Rises to 4.5%. Gallup. https://news.gallup.com/poll/234863/estimate-lgbt-population-rises.aspx?version=print
  46. Pachankis JE (2007). The psychological implications of concealing a stigma: A cognitive-affective-behavioral model. Psychological bulletin, 133(2), 328. [DOI] [PubMed] [Google Scholar]
  47. Parks CA, Hughes TL, & Matthews AK (2004). Race/ethnicity and sexual orientation: Intersecting identities. Cultural diversity and ethnic minority psychology, 10(3), 241. [DOI] [PubMed] [Google Scholar]
  48. Plöderl M, & Tremblay P (2015). Mental health of sexual minorities. A systematic review. International review of psychiatry, 27(5), 367–385. [DOI] [PubMed] [Google Scholar]
  49. Riggle ED, Rostosky SS, Black WW, & Rosenkrantz DE (2017). Outness, concealment, and authenticity: Associations with LGB individuals’ psychological distress and well-being. Psychology of Sexual Orientation and Gender Diversity, 4(1), 54. [Google Scholar]
  50. Riley BH (2010). GLB adolescent’s “coming out.”. Journal of Child and Adolescent Psychiatric Nursing, 23(1), 3–10. [DOI] [PubMed] [Google Scholar]
  51. Rosario M, Schrimshaw EW, & Hunter J (2004). Ethnic/racial differences in the coming-out process of lesbian, gay, and bisexual youths: A comparison of sexual identity development over time. Cultural Diversity and Ethnic Minority Psychology, 10(3), 215. [DOI] [PubMed] [Google Scholar]
  52. Russell ST, & Fish JN (2016). Mental health in lesbian, gay, bisexual, and transgender (LGBT) youth. Annual review of clinical psychology, 12, 465–487. [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Sarno EL, Mohr JJ, Jackson SD, & Fassinger RE (2015). When identities collide: Conflicts in allegiances among LGB people of color. Cultural Diversity and Ethnic Minority Psychology, 21(4), 550. [DOI] [PubMed] [Google Scholar]
  54. Savin-Williams RC (1998). The disclosure to families of same-sex attractions by lesbian, gay, and bisexual youths. Journal of Research on Adolescence, 8(1), 49–68. [Google Scholar]
  55. Savin-Williams RC, & Diamond LM (2000). Sexual identity trajectories among sexual-minority youths: Gender comparisons. Archives of sexual behavior, 29(6), 607–627. [DOI] [PubMed] [Google Scholar]
  56. Stewart P (2007). Who is kin? Family definition and African American families. Journal of Human Behavior in the Social Environment, 15(2–3), 163–181. [Google Scholar]
  57. Tabaac AR, Perrin PB, & Trujillo MA (2015). Multiple mediational model of outness, social support, mental health, and wellness behavior in ethnically diverse lesbian, bisexual, and queer women. LGBT Health, 2(3), 243–249. [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. U.S. Census Bureau. (2000). State & County Quickfacts Pittsburgh, PA. Washington, DC: U.S. Bureau of the Census. [Google Scholar]
  59. Van EED, Mereish EH, Woulfe JM, & Katz-Wise SL (2019). Perceived discrimination, coping mechanisms, and effects on health in bisexual and other non-monosexual adults. Archives of sexual behavior, 48(1), 159–174. [DOI] [PMC free article] [PubMed] [Google Scholar]
  60. Wei M, Heppner PP, Ku TY, & Liao KYH (2010). Racial discrimination stress, coping, and depressive symptoms among Asian Americans: A moderation analysis. Asian American Journal of Psychology, 1(2), 136. [Google Scholar]
  61. Zimmerman L, Darnell DA, Rhew IC, Lee CM, & Kaysen D (2015). Resilience in community: A social ecological development model for young adult sexual minority women. American journal of community psychology, 55(1–2), 179–190. [DOI] [PMC free article] [PubMed] [Google Scholar]

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