Mental Health Literacy and Its Relation to Sexual and Gender Minority Identity in a Diverse Sample of Undergraduate College Students

Abstract

Research indicates that mental health literacy (MHL) can promote adaptive health behaviors and reduce stigma toward mental health problems. However, few studies have examined MHL among sexual and gender minority (SGM) individuals, a population that is disproportionately affected by negative mental health outcomes due to experiences with minority stress. This study aimed to fill this gap in the literature by investigating the association between MHL and SGM identity in a sample of demographically diverse college students in New York City. In addition to using a comprehensive measure of MHL, we recorded participants’ self-reported history of a psychological disorder. Results indicated that SGM identity was associated with higher MHL than non-SGM identity over and above other sociodemographic characteristics. This association was fully driven by participants’ self-reported history of a psychological disorder, which was more frequently reported by SGM participants as compared to non-SGM participants. These findings suggest that SGM college students may have higher MHL than non-SGM college students due to their relatively greater likelihood of having personally experienced a psychological disorder. Early MHL intervention with SGM individuals may be warranted to increase MHL prior to a potential onset of psychopathology, with the larger goal of facilitating more positive mental health outcomes. Implications for interventions in school-based settings and future research initiatives are also discussed.

Keywords

mental health literacy LGBTQ+college students sexual and gender minority mental health promotion

An extensive review of literature indicates that lesbian, gay, bisexual, transgender, and other sexual and gender minority (SGM) individuals are disproportionately affected by negative mental health outcomes as compared to people who identify as cisgender (i.e., people whose gender identity is the same as their sex assigned at birth) and heterosexual. Researchers have argued that these disparities can be explained by unique and chronic forms of stigma-related stress, known as minority stress, that are specific to SGM identity (Brooks, 1981; Hendricks & Testa, 2012; Meyer, 2003). Despite these well-documented mental health disparities, few studies examine mental health literacy (MHL) among SGM populations. This gap in the literature is concerning, as MHL is associated with positive attitudes and health behaviors that may improve mental health outcomes for at-risk groups (Bjørnsen et al., 2019; Bonabi et al., 2016; Griffiths et al., 2008; Jorm, 2012; Kutcher et al., 2016; Wright et al., 2007). Research on the MHL of SGM individuals could enhance understanding on the associations between MHL, psychopathology, and relevant attitudes and behaviors within this population. Understanding these critical relationships may subsequently inform the development of interventions that are tailored to meet the needs of SGM individuals. Thus, the purpose of this study was to investigate the association between MHL and SGM identity in a sample of demographically diverse undergraduate students.

Mental Health Literacy

The term mental health literacy was first defined by Jorm et al. (1997) as one’s “knowledge and beliefs about mental disorders, which aid their recognition, management, or prevention” (p. 182). While no studies have shown that MHL can prevent the onset of later psychological disorders altogether, findings from a growing body of research have identified several positive implications of MHL. For example, one large study found that an increase in depression literacy was related to more positive attitudes toward formal sources of support (e.g., social workers, psychologists, and psychiatrists), informal sources of support (e.g., friends and family), and psychopharmacological treatments (e.g., antidepressants; Goldney et al., 2005). Other studies have similarly found that MHL is related to greater help-seeking attitudes and intentions (Cheng et al., 2018; Smith & Shochet, 2011; Wright et al., 2007), as well as lower stigma toward mental health problems (Griffiths et al., 2008; Milin et al., 2016; Wang & Lai, 2008). Of note, a longitudinal study using data of people experiencing psychotic symptoms found that MHL predicted actual help-seeking behavior, as higher baseline MHL predicted later use of psychotherapy and psychiatric medication (Bonabi et al., 2016). Taken together, MHL may promote more positive mental health outcomes by facilitating adaptive health behaviors and attitudes (Bjørnsen et al., 2019; Jorm, 2012; Kutcher et al., 2016). Unfortunately, however, MHL among the general population is quite poor (Furnham & Swami, 2018; Jorm, 2000; Lam, 2014), prompting greater efforts to develop and test the effectiveness of MHL interventions.

MHL intervention prior to early adulthood may be particularly critical to mental health promotion efforts. Indeed, the onset of most psychological disorders occurs before age 24 (Kessler et al., 2005). Some researchers also suggest that young people who experience mental health problems may be unlikely to seek professional help, with one systematic review finding that adolescents and young adults report self-stigma, preferences for self-reliance, and poor MHL as major barriers to help-seeking (Gulliver et al., 2010). Encouragingly, the implementation of school-based MHL interventions have yielded promising results, with participants demonstrating increased MHL, greater intentions to seek help for mental health problems, and decreased stigma toward psychological disorders post-intervention (Lindow et al., 2020; Milin et al., 2016; Skre et al., 2013). Although findings from these studies have established a good foundation for understanding the implications of MHL intervention among young people in general, research on how MHL may vary as a function of sociodemographic characteristics can be crucial in identifying specific groups in need of more targeted interventions.

Researchers have identified specific sociodemographic patterns of MHL. For example, rates of MHL vary as a function of gender, with men demonstrating poorer MHL, less adaptive help-seeking attitudes, and greater stigma toward mental health problems than women (Kim et al., 2015; Klineberg et al., 2011; Swami, 2012). Some evidence also suggests that MHL is relatively lower among racial and ethnic minority populations (Benuto et al., 2019; Cheng et al., 2018; Crisanti et al., 2016; Kim et al., 2015). In addition, racial and ethnic minority college students are less likely than White students to seek professional help for mental health problems (Masuda et al., 2009). Although these findings generate important avenues for both research and the development of targeted interventions for these at-risk populations, an important group has been largely absent from the MHL literature: SGM populations.

Mental Health and Minority Stress Among SGM Populations

Findings from a large body of research indicate that mental health problems are more prevalent among SGM populations relative to their cisgender, heterosexual counterparts. With respect to sexual minority populations, several studies have shown that sexual minority individuals are at higher risk of experiencing a range of mental health problems as compared to heterosexual people, including mood and anxiety disorders, suicidal ideation and behaviors, substance use problems and disorders, and disordered eating behaviors and eating disorders (Borgogna et al., 2019; Bostwick et al., 2010; Bränström & Pachankis, 2018; Cochran et al., 2003; Haas et al., 2010; Hazzard et al., 2020; King et al., 2008; Marshal et al., 2011; Miller & Luk, 2019). Of note, a recent study used nationally representative data of noninstitutionalized people in the general United States population to examine sexual orientation-related disparities in the prevalence of psychiatric disorders (Kerridge et al., 2017). In addition to finding higher risk of mood disorders, anxiety disorders, and substance use disorders, Kerridge et al. (2017) also found that sexual minority people were more likely to report post-traumatic stress disorder and personality disorders than heterosexual people. With respect to disparities related to gender identity, researchers have similarly found that transgender and gender diverse (TGD) people (i.e., people whose gender identity does not match their sex assigned at birth) face elevated risk for the development of mental health problems as compared to cisgender people (Bockting et al., 2013; Borgogna et al., 2019; Haas et al., 2010; Hanna et al., 2019; Reisner, Katz-Wise, et al., 2016; Su et al., 2016; Veale et al., 2017). It is important to note, however, that researchers have suggested that SGM identity in and of itself is not a risk factor for poor mental health outcomes, nor is it indicative of internal pathology (Meyer et al., 2021). Rather, the increased risk for psychopathology is thought to result from stress associated with societal oppression, which manifests in stigma, prejudice, discrimination, and violence enacted against SGM individuals (Brooks, 1981; Hendricks & Testa, 2012; Meyer, 2003).

Minority stress theory is a framework that aims to explain the mental health disparities between SGM and cisgender, heterosexual (herein referred to as “non-SGM”) populations that have been identified in the literature (Brooks, 1981; Hendricks & Testa, 2012; Meyer, 2003). This framework posits that minority stress results from unique and chronic stressors that impact members of marginalized populations. Examples of minority stress include both external forms, such as discrimination and victimization, as well as internal forms, such as internalized stigma and heightened rejection sensitivity (Feinstein, 2020; Meyer, 2003). This stress is centered on one’s stigmatized identity and is independent from the general stress that people experience in everyday life (e.g., relationship stress, vocational stress, etc.). Thus, minority stress is thought to exacerbate the effect of general life stress on health outcomes, resulting in higher prevalence of mental health problems among SGM populations as compared to non-SGM populations. Indeed, minority stress has been linked to poorer mental health outcomes in SGM populations, including substance use problems and suicidal ideation, as well as symptoms of depression, anxiety, and post-traumatic stress, in both sexual minority samples (Baams et al., 2015; Eldahan et al., 2016; Goldbach et al., 2014; Lehavot & Simoni, 2011; Mereish et al., 2019; Puckett et al., 2015; Straub et al., 2018) as well as TGD samples (Barr et al., 2021; Chodzen et al., 2019; Reisner, White Hughto, et al., 2016; Scandurra et al., 2018; Testa et al., 2017). Given that SGM individuals are at heightened risk of experiencing mental health problems as a result of experiences with minority stress, an understanding of MHL in SGM individuals can be critical to informing intervention efforts with this at-risk population.

MHL Among SGM Populations

Despite the increased risk of poor mental health outcomes among SGM people relative to non-SGM people, studies assessing MHL in SGM populations remains scarce. We are aware of only two studies that have specifically examined MHL in samples of SGM individuals (Ferlatte et al., 2020; Wang et al., 2014). In a study of MHL among gay men in Switzerland, Wang et al. (2014) found that participants who met diagnostic criteria for depression within the previous 12 months demonstrated higher depression literacy than those who did not. These individuals were also more likely to correctly believe that gay men are at greater risk of experiencing depression than heterosexual men. A second study found that SGM participants in Canada had higher depression literacy and suicide literacy relative to the general Canadian population (Ferlatte et al., 2020). On average, these individuals were also aware of the heightened risk of suicide among SGM people compared to non-SGM people.

Although findings of the aforementioned studies have made notable contributions to the literature given their consideration of MHL among SGM populations, important questions remain unanswered. For example, neither study directly compared SGM and non-SGM participants, which prevented researchers from determining whether SGM identity was differentially associated with MHL within the same sample. Of note, however, Ferlatte et al. (2020) suggested that MHL is relatively higher in SGM populations than in non-SGM populations by comparing their results to the existing literature. Nevertheless, it remains unclear whether these potentially elevated rates of MHL are directly associated with SGM identity, or whether a third factor, such as one’s personal history of a psychological disorder, better explains this association. Indeed, Wang et al. (2014) found that depression literacy was higher among gay men who met diagnostic criteria for depression, suggesting that personal history of a psychological disorder may contribute to higher MHL in this population. Moreover, the previous studies only examined depression literacy and suicide literacy, limiting generalizability to the vast array of psychological problems that people can experience. Researchers that use more comprehensive measures of MHL can determine whether MHL among SGM people extends beyond depression and suicide. Finally, a study of MHL among SGM college students may be especially informative due to the importance of early adulthood as a developmental stage where people are particularly vulnerable to psychopathology (Kessler et al., 2005).

The Present Study

The present study aimed to address the aforementioned gaps in the literature by examining MHL in a sample of undergraduate students in New York City. Using a comprehensive measure of MHL, we tested the following research questions:

RQ1: Is SGM identity differentially associated with MHL among college students?

RQ2: Are differences in MHL between SGM and non-SGM college students explained by differences in self-reported history of a psychological disorder?

Based on the findings of previous research, we hypothesized that:

H1: SGM identity would be associated with higher MHL as compared to non-SGM identity.

H2: The association between SGM identity and higher MHL would be explained by self-reported history of a psychological disorder, such that self-reported history of a psychological disorder would be more frequently reported by SGM college students as compared to non-SGM college students.

Materials and Methods

Participants and Procedure

The present study conducted secondary analyses on data collected from a parent study of MHL among 683 undergraduate students (Miles et al., 2020; Rabin et al., 2021). The parent study used a convenience sampling method to recruit students from a large public university system in New York City. All aspects of the outlined procedure were approved by The City University of New York Institutional Review Board prior to data collection.

Members of the research team contacted course instructors across various academic departments (e.g., psychology, mathematics, business, and chemistry) to request permission to administer a paper-and-pencil questionnaire to students during classroom sessions. Other recruitment efforts included in-person recruitment of students at heavily populated campus locations (e.g., student lounges, libraries, and outdoor campus quads), online recruitment through campus subject pool listings, and through distribution of flyers that directed students to open administration sessions. The use of a diverse range of recruitment strategies was warranted given the aims of the parent study, which sought to recruit undergraduate students across different academic majors. To be eligible for the parent study, participants had to be actively enrolled at the undergraduate level and at least 18 years of age.

Students who met eligibility criteria and expressed interest in participating were given an overview of the study from an IRB-approved script, which outlined the general study aims, steps to ensure confidentiality, voluntary participation information, and rights to withdraw. If students agreed to participate, researchers administered the 30- to 40-minute questionnaire. Upon completion, participants were compensated with subject pool research credit, extra credit in a course, or a $5 cash incentive. Data collection commenced in March 2019 and concluded in January 2020.

Measures

Mental Health Literacy

MHL was assessed with the Mental Health Literacy Assessment for college students (MHLA-c; Rabin et al., 2021). The MHLA-c is an 18-item multiple-choice measure validated within a sample of demographically diverse U.S. college students that is available in three forms. The three forms of the MHLA-c each measure the construct of MHL with slightly differing content; however, forms are equivalent with respect to number of items, format of items, and range and level of item difficulty. Items focus on (a) knowledge of more than 20 psychological disorders, including their etiology, risk factors, diagnosis, symptoms, treatment, course, and outcome and (b) application of this knowledge to real world situations, including level of insight/awareness, manifestation of symptoms in real life, responding to others, accessing help from professionals, and likelihood of experiencing or preventing negative outcomes. Rabin et al. (2021) found psychometric support for the measure including internal consistency reliability (Kuder–Richardson formula 20 values 0.74–0.75 for all forms), evidence of content and construct validity, and unidimensionality (based on an exploratory factor analysis). Participants’ scores were averaged across forms to create a percent correct score, with a minimum possible score of 0 and a maximum possible score of 100. Given issues with participant burden, participants were randomly assigned to complete either all three forms of the MHLA-c or just two forms. Of note, the percent correct scores did not vary as a function of the number of forms administered.

Sociodemographic Characteristics

Age

Age was assessed using a single self-report item.

Race/ethnicity

Race/ethnicity was assessed using a multiple-choice question with the options “Black,” “White,” “Hispanic/Latino,” “Asian American,” Native American,” and “Multiracial.” Participants were able to select as many options as applied to them, as well as to self-report their race/ethnicity via an open-ended response if it was not listed. If participants selected more than one race/ethnicity without selecting “Multiracial,” they were classified as “Multiracial” for analyses.

Gender

Gender was assessed using a multiple-choice question with the options “male,” “female,” “gender nonbinary,” “gender nonconforming,” “genderqueer,” and “prefer not to answer.” Participants were able to select as many options as applied to them, as well as to self-report their gender via an open-ended response if it was not listed. Although our demographic form used the terms “male” and “female” to assess gender, we acknowledge that these terms are typically indicative of biological sex and not gender. It is important to note that using “male” and “female” rather than “man” and “woman” to assess gender can be stigmatizing, as it erroneously conflates sex and gender. These distinctions are critical, as biological sex and gender are not interchangeable constructs. While we would prefer to use the terms “man” and “woman” as opposed to “male” and “female,” doing so would misrepresent what participants were presented with and reported on.

Transgender Identity

Transgender identity was assessed using a single item (i.e., “Do you identify as transgender?”) with the options “yes,” “no,” “unsure,” and “prefer not to answer.”

Sexual Orientation

Sexual orientation was assessed using a multiple-choice question with the options “straight,” “gay/lesbian,” “bisexual,” “pansexual,” “asexual,” and “prefer not to answer.” Participants were able to select as many options as applied to them, as well as to self-report their sexual orientation via an open-ended response if it was not listed.

SGM Identity

To determine SGM identity, participants who reported either a sexual or gender minority identity were coded as “SGM,” while participants who identified as both cisgender and heterosexual were coded as “non-SGM.”

Self-Reported History of a Psychological Disorder

To assess self-reported history of a psychological disorder, we created a dichotomized variable based on participants’ response to an item that captured possible ways that participants could have gained knowledge and/or experience with psychological disorders, which was answered via a “check all that apply” prompt. Specifically, participants were presented with the item “Do you have knowledge/experience with psychological disorders as a result of: personal history of psychological disorder(s); family history of psychological disorder(s) (e.g., parents, siblings, and child); close friend with a history of psychological disorder(s); other (open-ended response).” Participants who checked “personal history with psychological disorder(s)” were coded as having a self-reported history of a psychological disorder. Participants’ responses to other components of the item were not considered in creating this dichotomized variable.

Data Analysis

First, we used hierarchical linear regression to identify the unique contribution of SGM identity in predicting MHL. Specifically, the sociodemographic control variables of age, gender, and race/ethnicity were entered at step 1, followed by SGM identity at step 2. This allowed us to identify whether SGM identity was associated with MHL above and beyond other sociodemographic characteristics. We then entered self-reported history of a psychological disorder at step 3 to examine whether a potential association between SGM identity and MHL remained robust. Categorical variables were recoded into separate dichotomous variables to allow for meaningful interpretation of the results, with “White” as the reference category for race/ethnicity and “female” as the reference category for gender. These reference categories were selected due to previous research that suggested that White and female individuals have relatively higher MHL than their respective counterparts (Benuto et al., 2019; Crisanti et al., 2016; Kim et al., 2015; Klineberg et al., 2011; Swami, 2012), making them suitable benchmarks for comparison.

Next, we used binary logistic regression to determine whether self-reported history of a psychological disorder would be an appropriate mediator to explain an indirect effect of SGM identity on MHL. Specifically, we tested whether SGM identity was associated with a greater likelihood of reporting a personal history of a psychological disorder after controlling for the sociodemographic variables of age, gender, and race/ethnicity.

Finally, we conducted a mediation analysis with 10,000 bootstrap samples using the Latent Variable Analysis (lavaan) package in R to test the indirect effect of SGM identity on MHL through self-reported history of a psychological disorder (Hayes, 2009; Rosseel, 2012). Because the independent variable (i.e., SGM identity) and mediator (i.e., self-reported history of a psychological disorder) were each dichotomous, the lavaan package was ideal for this analysis given its ability to utilize binary exogenous and endogenous categorical variables (Rosseel, 2012). All other statistical analyses were performed using SPSS Statistics Version 27.

Results

Participant Characteristics

Sociodemographic characteristics of participants in the analytic sample are presented in Table 1. Data were collected from 683 participants. Twenty-two participants were removed from further analyses because they had missing data for both the sexual orientation and transgender identity items, which prevented the assessment of SGM identity. This resulted in a final analytic sample of 661 participants. Ninety-four participants reported an SGM identity (14.2%), with nine of these participants identifying with both sexual minority and gender minority identities. Given inadequate cell sizes, gender nonbinary, gender nonconforming, genderqueer, and multiple gender identities were not included in the “gender” control variable. However, these identities are reflected in the “SGM identity” variable. Of note, the majority of participants recruited for the present study reported that they majored in fields of study other than psychology. Furthermore, SGM identity was not associated with a greater likelihood of majoring in psychology as compared to other majors, and SGM college students were equally represented among psychology and non-psychology majors.

Table 1

Sociodemographic Characteristics of the Analytic Sample of (N = 661) Undergraduate Students

Age	M = 22.1	SD = 4.82
Variables	n	%
Race/ethnicity
White/Caucasian	206	31.3
Black/African American	134	20.4
Hispanic/Latino	113	17.2
Asian American	145	22.1
Native American	3	0.5
Multiracial	56	8.5
Gender^a
Male	231	34.9
Female	420	63.5
Gender nonbinary	3	0.4
Gender nonconforming	2	0.3
Genderqueer	1	0.2
Multiple gender identities	—	—
Male and genderqueer	1	0.2
Female and gender nonbinary	2	0.3
Gender nonbinary, gender nonconforming, and genderqueer	1	0.2
Transgender identity
Yes	4	0.6
No	652	98.6
Unsure	5	0.8
Sexual orientation
Heterosexual	573	86.9
Gay/Lesbian	23	3.4
Bisexual	52	7.9
Pansexual	7	1.0
Asexual	1	0.2
Demisexual^b	1	0.2
Queer^b	1	0.2
Multiple orientations	—	—
Gay and pansexual	1	0.2
SGM identity
Yes (i.e., sexual and/or gender minority)	94	14.2
No (i.e., cisgender and heterosexual)	567	85.8
Self-reported history of a psychological disorder
Yes	173	26.2
No	488	73.8

Note. Data was missing for age (n = 3), race/ethnicity (n = 4), and sexual orientation (n = 2). SGM = sexual and gender minority.

Given inadequate cell sizes, gender nonbinary, gender nonconforming, genderqueer, and multiple gender identities were not included in the “gender” control variable in the following analyses.

Denotes an open-ended response.

Hierarchical Linear Regression Predicting MHL

The results of the hierarchical linear regression model are presented in Table 2. The sociodemographic control variables were associated with MHL at step 1. The addition of SGM identity at step 2 was associated with a significant change in the variance accounted for in the model. Consistent with H1, reporting an SGM identity was associated with higher MHL than reporting a non-SGM identity. This association remained statistically significant after entering self-reported history of a psychological disorder at step three.

Table 2

Characteristics Associated With Mental Health Literacy

Variables	Step 1			Step 2			Step 3
Variables	B	SE	β	B	SE	β	B	SE	β
Age	0.36*	0.15	.09	0.37*	0.15	.10	0.36*	0.14	.09
Gender
Female	Referent			Referent			Referent
Male	−6.25***	1.45	−.17	−5.92***	1.44	−.16	−5.67***	1.42	−.15
Race/ethnicity
White	Referent			Referent			Referent
Black	−7.97***	1.95	−.18	−8.56***	1.94	−.19	−7.85***	1.91	−.17
Hispanic/Latino	−2.29	2.06	−.05	−3.34	2.06	−.07	−3.53	2.02	−.07
Asian American	−9.02***	1.93	−.21	−9.11***	1.91	−.21	−8.15***	1.89	−.19
Native American	−9.65	10.17	−.04	−9.23	10.08	−.03	−7.38	9.91	−.03
Multiracial	−1.96	2.71	−.03	−3.44	2.72	−.05	−3.81	2.67	−.06
SGM identity
Non-SGM	—	—	—	Referent			Referent
SGM	—	—	—	7.37***	2.08	.14	4.84*	2.11	.09
Self-reported history of a psychological disorder
No	—	—	—	—	—	—		Referent
Yes	—	—	—	—	—	—	7.83***	1.61	.19
Adjusted R²		0.081			0.098			0.128
R ² _change		—			0.017***			0.030***

Note. SGM = sexual and gender minority; SE = standard error.

p < .05; ***p < .001.

Binary Logistic Regression Predicting the Relative Likelihood of Self-Reported History of a Psychological Disorder

The results of the binary logistic regression are presented in Table 3. SGM identity emerged as a statistically significant predictor of self-reported history of a psychological disorder. Specifically, SGM participants were more likely than non-SGM participants to self-report a personal history of a psychological disorder. This relationship remained statistically significant after entering age, gender, and race/ethnicity into the model.

Table 3

Characteristics Associated With Self-Reported History of a Psychological Disorder

Factors	Adjusted odds ratio [95% CI]
Age	1.01 [0.97, 1.05]
Gender
Female	1
Male	0.80 [0.53, 1.20]
Race/ethnicity
White	1
Black	0.58 [0.34, 1.00]
Hispanic/Latino	1.09 [0.65, 1.85]
Asian American	0.45** [0.25, 0.80]
Native American	—
Multiracial	1.22 [0.62, 2.41]
SGM identity
Non-SGM	1
SGM	4.52*** [2.74, 7.47]

Note. SGM = sexual and gender minority; CI = confidence interval.

**p < .01. ***p < .001.

Test of the Indirect Effect of SGM Identity on MHL Through Self-Reported History of a Psychological Disorder

The results of the mediation analysis are depicted with standardized regression coefficients in Figure 1. Consistent with H2, the effect of SGM identity on MHL was fully explained by self-reported history of a psychological disorder. Specifically, SGM identity was associated with greater self-reported history of a psychological disorder than non-SGM identity, and self-reported history of a psychological disorder was associated with higher MHL. The direct effect of SGM identity on MHL was not statistically significant in this model. However, the indirect effect of SGM identity on MHL through self-reported history of a psychological disorder was statistically significant. Unstandardized indirect effects were computed for each of the 10,000 bootstrap samples and the 95% confidence interval was computed by determining the indirect effects at the 2.5th and 97.5th percentiles. The point-estimate of the unstandardized indirect effect was 5.69 (p < .001) and the 95% confidence interval did not include 0 [3.59, 8.60]. The model explained 12% of the variance in MHL.

Figure 1.

Test of the indirect effect of sexual and gender minority (SGM) identity on mental health literacy (MHL) through self-reported history of a psychological disorder.

Discussion

The present study is among the first to examine the association between MHL and SGM identity, building on previous research in several important ways. First, we used a sample that included both SGM and non-SGM participants, which allowed us to determine whether SGM identity was differentially associated with MHL relative to cisgender, heterosexual identity. Second, we measured participants’ self-reported history of a psychological disorder to explore how such history may contribute to potential associations between SGM identity and MHL. Third, we administered a comprehensive measure of MHL that assessed both conceptual knowledge of over 20 psychological disorders and the application of this knowledge to everyday life. Finally, we examined these associations in a diverse sample of undergraduate college students, an at-risk population for psychopathology.

Based on the findings of previous research, we hypothesized that (a) SGM identity would be associated with higher MHL and this relationship would be driven by self-reported history of a psychological disorder. Our findings supported each of these hypotheses. Specifically, results of hierarchical linear regression indicated that SGM identity was associated with higher MHL above and beyond other sociodemographic characteristics. A subsequent mediation analysis additionally revealed that this association was fully explained by one’s self-reported history of a psychological disorder. Indeed, SGM participants were over four times more likely than non-SGM participants to self-report a personal history of a psychological disorder, which, in turn, was associated with higher MHL. Thus, our findings suggest that SGM individuals may have higher MHL than non-SGM individuals due to their relatively greater likelihood of having reported a personal history with mental health problems.

Our findings not only align with Ferlatte et al.’s (2020) claim that SGM individuals have higher MHL than non-SGM individuals, but also add meaningful nuance by suggesting that this association may be explained by SGM individuals’ greater relative experience with psychopathology, which is likely driven by minority stress (Brooks, 1981; Hendricks & Testa, 2012; Meyer, 2003). This echoes previous research findings, which suggested that depressed gay men had higher depression literacy than non-depressed gay men (Wang et al., 2014). Taken together, this suggests that higher MHL among SGM individuals may be a product of mental health problems as opposed to a previously-obtained skill to aid in their prevention or management.

Implications for Research and Practice

Our results have important implications for MHL interventions with SGM populations. For instance, our finding that the association between SGM identity and MHL was driven by self-reported history of a psychological disorder suggests that early intervention may be warranted in this population in order to build MHL prior to a potential onset of psychopathology. As MHL is intended to promote positive mental health, aid in the prevention of poor mental health outcomes, and enhance engagement in adaptive health behaviors (Bjørnsen et al., 2019; Jorm, 2012; Jorm et al., 1997; Kutcher et al., 2016), this literacy may be particularly critical for prevention efforts with SGM individuals. However, if higher MHL among SGM individuals is explained by their relatively greater experience with mental health problems, one could argue that, under such conditions, MHL is not serving a preventative purpose. Conversely, if school-based MHL interventions are implemented for SGM individuals at younger ages (e.g., early adolescence), it is more likely that enhanced literacy will precede a potential onset of psychopathology. This early enhanced literacy may then facilitate attitudes and behaviors that can aid in promoting more positive mental health outcomes.

There are several ways that schools may attempt to disseminate MHL interventions and resources to support SGM students. Gender and sexuality alliances (also known as gay straight alliances; GSAs) are one such avenue for early intervention. Indeed, GSA-based programs have been developed to promote mental health, resilience, and well-being among SGM youth and have yielded encouraging results (Craig et al., 2014; Heck, 2015; Lapointe & Crooks, 2018). In addition, the development of GSA-based MHL programs is particularly favorable given their ability to intervene at early ages in a supportive environment. While intervention at younger ages is ideal, colleges and universities can take specific measures to promote MHL among SGM students as well. For example, college counseling centers can develop workshops and information sessions that are specifically targeted for SGM students. Upon developing such interventions, counseling centers could then coordinate with other campus resources, such as lesbian, gay, bisexual, and transgender (LGBTQ+) student centers, to aid in dissemination efforts.

With respect to research initiatives, future studies should explore whether certain identity-specific factors, such as awareness of minority stress, are related to MHL among SGM populations. Given that minority stress is associated with poorer mental health outcomes among SGM populations (Baams et al., 2015; Barr et al., 2021; Chodzen et al., 2019; Lehavot & Simoni, 2011; Puckett et al., 2015; Reisner, White Hughto, et al., 2016), determining whether awareness of minority stress is associated with higher MHL is a logical next step for research with SGM individuals. Although previous studies have shown that SGM individuals with high MHL reported that SGM people are at greater risk of depression (Wang et al., 2014) and suicide (Ferlatte et al., 2020) than non-SGM people, it is unclear whether these participants would have attributed this increased risk to minority stress. Furthermore, perhaps greater knowledge of minority stress and its impact on the mental health of SGM individuals should be conceptualized as a form of MHL in and of itself. Indeed, psychoeducation techniques centered on building awareness of minority stress have been integrated into psychotherapy interventions (Budge et al., 2020; Pachankis et al., 2019) and mental health promotion programs (Heck, 2015) with SGM individuals. These interventions have demonstrated positive outcomes, suggesting that awareness of minority stress is associated with better mental health outcomes for SGM populations. Thus, researchers may consider developing MHL assessment tools that integrate knowledge of minority stress and its impact on marginalized populations into the measurement of its construct.

Limitations and Future Directions

While this research makes notable contributions to the literature, there are several limitations that provide important avenues for future research. First, we used a cross-sectional design, which prevented us from establishing causation or temporal relationships between variables. Nevertheless, we believe that our mediation analysis provides an important theoretical contribution to enhance understanding of the association between SGM identity and MHL. While future studies should prioritize longitudinal designs to build support for temporal associations between psychopathology and MHL among SGM individuals, our findings underscore the potential importance of early intervention in this vulnerable population, which could bear meaningful implications for mental health outcomes.

Second, our coding decisions and analyses were limited by the number of participants who reported SGM identities. Although the proportion of SGM participants in our sample (14.2%) was relatively higher than what would be expected from population estimates (i.e., 4.5%; Conron & Goldberg, 2019), some identities were much more frequently reported than others (e.g., larger numbers of bisexual individuals and fewer numbers of TGD individuals). Thus, we combined all participants who reported a sexual and/or gender minority identity into a single SGM category to maximize statistical power. This amalgamation is not ideal, as the LGBTQ+ community is not a homogenous population. As such, future studies should aim to recruit larger samples of SGM participants to examine potential intersectional differences in MHL within SGM populations (e.g., differences based on gender identity, sexual orientation, and race/ethnicity).

Third, our assessment of participants’ personal history of a psychological disorder was a single self-reported item that did not capture specific diagnoses or symptomatology. Rather, the item reflected participants’ own perceptions as to whether they have personally experienced a psychological disorder. In effect, some participants may have endorsed this item due to having a mental health diagnosis, whereas others may have endorsed it due to their own subjective experience of psychological distress. Future research should use more detailed measures of psychopathology to determine whether symptom severity or specific diagnoses result in different associations with MHL among SGM individuals.

Fourth, the study relied on a non-probability sample of college students in New York City, suggesting that participants likely have important differences compared to samples of emerging adults more broadly. For example, even if participants were struggling with psychopathology, they were still functioning well enough to attend college. Thus, the association between self-reported history of a psychological disorder and higher MHL in the current study may be affected by systematically lower severity of mental health problems in college students relative to other populations. Furthermore, unlike emerging adults who do not attend college, students can benefit from support networks and mental health resources that are available on college campuses. With respect to SGM identity more specifically, stigma and mental health problems among SGM individuals vary as a function of geographic location, with SGM individuals reporting greater distress in rural compared to urban areas (Cohn & Leake, 2012; Horvath et al., 2014; Lee & Quam, 2013). This suggests that findings may not generalize to samples across areas with differing attitudes toward SGM populations. Finally, it is unclear whether the differences in MHL between SGM and non-SGM college students would extend to people across education levels. Despite the fact that most participants did not major in psychology, and that SGM participants were no more likely to major in psychology as compared to non-SGM participants, SGM college students are still likely to have greater exposure to information regarding mental health compared to SGM individuals who are not in college. While our focus on SGM college students is important given college students’ relative risk of psychopathology, as well as the potential to enact school-based interventions, future studies should examine whether our findings can replicate in other SGM populations.

Conclusion

MHL can promote adaptive health behaviors and more positive attitudes toward mental health problems, which may aid in intervention and health promotion efforts. Unfortunately, there is a paucity of research on MHL among SGM individuals, a population that disproportionately experiences negative mental health outcomes due to experiences with minority stress. We aimed to build on the limited extant literature by exploring the associations between SGM identity and MHL in a sample of demographically diverse undergraduate students. We found that SGM identity was associated with higher MHL than non-SGM identity, and that this relationship was driven by SGM participants’ greater relative likelihood of self-reporting history of a psychological disorder. This suggests that early intervention with SGM populations may be warranted in order to build MHL prior to a potential onset of mental health problems, which may promote more positive outcomes in turn. Future research should continue to address this gap in the literature by employing methods to replicate and build on these findings. Such work should aim to inform intervention efforts, which may aid in attenuating the mental health disparities between SGM individuals and their cisgender, heterosexual counterparts.

Footnotes

Acknowledgements

We wish to thank Rose Bergdoll, Franchesca Campbell, Milushka Elbulok-Charcape, Jessica Garrett, Yuliya Golubev, Nigora Jurabaeva, Sabrina Khakimova, Anastasiya Kharlamova, and Sade Thomas for assisting with data collection on this study. We would also like to thank Joanne Davila, Alexander Grieshaber, Riley McDanal, and the reviewers for their feedback, which was instrumental in helping us improve the quality of the manuscript. Finally, we thank all the participants for dedicating their time to participate in this study.

Declaration of Conflicting Interests

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

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by a grant from the John Cleaver Kelly (JCK) Foundation. The JCK Foundation had no role in the design of the study, the collection, analysis, and interpretation of the data, or the writing of the manuscript.

ORCID iD

Stephan A. Brandt

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