Intentions to use PrEP among a national sample of transgender and gender-expansive youth and emerging adults: Examining gender minority stress, substance use, and gender affirmation.

doi:10.21203/rs.3.rs-5205877/v1

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Intentions to use PrEP among a national sample of transgender and gender-expansive youth and emerging adults: Examining gender minority stress, substance use, and gender affirmation.

https://doi.org/10.21203/rs.3.rs-5205877/v1

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Transgender and gender-expansive youth/emerging adults ages 13–24 years, experience disproportionate HIV risk, yet have among the lowest US PrEP uptake rates (< 10%). Still, factors that promote or impede PrEP outcomes for this population are poorly understood. This study examines the effects of gender minority stressors, gender affirmation, and heavy substance use on their PrEP outcomes.

Data were drawn from the CDC’s 2018 START study, which included transgender and gender-expansive youth/emerging adults indicated for PrEP (N = 972). We developed a conceptual model integrating the gender minority stress and gender affirmation models. We mapped START items onto it, including distal (family rejection, medical discrimination) and proximal (internalized transphobia, perceived TGE-stigma) gender minority stressors, heavy substance use, background factors, and gender affirmation across five domains. Structural equation modeling (Mplus-8.9) was used to examine factors related to PrEP intentions.

Most participants were 18–24 (68%), trans-female (46%) and White (45%). Additionally, 40% reported heavy substance use behaviors. Medical discrimination increased internalized transphobia (b = 0.097, SE = 0.034, p = 0.005) and perceived stigma (b = 0.087, SE = 0.034, p = 0.010). Family rejection also increased perceived stigma (b = 0.181, SE = 0.032, p < 0.001) and heavy substance use (b = 0.260, SE = 0.053, p < 0.001), and perceived stigma (b = 0.106, SE = 0.037, p = 0.004) increased heavy substance use. Notably, perceived stigma (b = -0.085, SE = 0.027, p = 0.002) and heavy substance use (b = -0.161, SE = 0.031, p < 0.001) decreased intentions to take PrEP, while gender affirmation increased PrEP intentions (b = 0.045, SE = 0.019, p = 0.020). Moreover, a 1-point increase in gender affirmation reduced the risk of heavy substance use by -0.179 (SE = 0.030; p < 0.001) in the presence of family rejection, and by -0.074 (SE = 0.041; p = 0.074) when perceived TGE stigma was present.

This study underscores the importance of addressing heavy substance use among transgender/gender-expansive young people as a potential barrier to PrEP uptake. Future research could explore how gender affirmation acts as a protective factor against the negative impact of family rejection and perceived stigma on heavy substance behaviors among these populations.

gender minority stress

youth and emerging adults

preexposure prophylaxis

substance use

gender affirmation

structural equation modeling

This paper examines intentions to use pre-exposure prophylaxis (PrEP) to prevent contracting HIV among transgender and gender-expansive youth and emerging adults ages 13–24 years (i.e., nonbinary, genderqueer, gender fluid). We refer to this population as TGE-YEA. TGE-YEA experience disproportionate risk for HIV, yet their rates of PrEP uptake are the lowest of any key risk group in the United States (U.S.; <10%) [1, 2]. According to the most recent Centers for Disease Control and Prevention (CDC) HIV surveillance report (2021), all youth and emerging adults in this age range account for 19% of the roughly 32,000 annual new HIV diagnoses in the US and comprise the largest percentage of those with undiagnosed HIV infection (44%) [3]. Within these youth populations, TGE-YEA experience a disproportionate risk for HIV.

TGE individuals across all age groups are diagnosed with HIV at rates considerably higher than the national average, with HIV prevalence estimates as high as 28% across all TGE identities, compared to 0.4% of the US population [4–8]. While most national HIV data do not disaggregate youth by gender identity, the CDC reports that for all TGE individuals, rates of HIV infection are increasing, rather than stabilizing or decreasing, as with most other populations [9, 10].

While HIV prevention tools exist for young people, including TGE-YEA [11], these programs and interventions have yet to sufficiently reduce or eliminate HIV incidence among TGE-YEA [12, 13]. In 2012, PrEP was approved by the US Food and Drug Administration (FDA) as an effective HIV prevention medication [14]. This approval marked a significant advancement in HIV prevention strategies, setting the stage for future initiatives aimed at combating the HIV epidemic. Indeed, PrEP has tremendous potential to stop the spread of HIV; it can prevent HIV infection up to 99% of the time when taken as prescribed [15].

Building on this advancement, the Ending the HIV Epidemic (EHE) initiative was launched in 2019, in conjunction with the National HIV/AIDS Strategy. Together they have a shared goal to end the HIV epidemic in the US by 2023 [16, 17]. To track progress towards this goal, the EHE initiative utilizes six national indicators, one of which is PrEP coverage. PrEP coverage measures the percentage of individuals at heightened risk for HIV who have been prescribed PrEP [18]. A key component of this effort is the national PrEP care continuum, a framework that tracks the progression of PrEP engagement through sequential stages [19]. The stages of the PrEP care continuum (see Fig. 1) begin with PrEP awareness and move through intentions, access, uptake, and persistent use [20]. Each step along the PrEP care continuum is critical to the success of the EHE initiative [21].

In 2018, the FDA approved PrEP for minor youth, creating an effective strategy to prevent HIV infection in this age group [22]. Yet, only 20% of all individuals 16–24 years of age in the U.S. who could benefit from PrEP were prescribed PrEP in 2021, representing the lowest PrEP uptake of all age groups [23]. While precise data on PrEP eligibility rates among TGE-YEA are scant, [24–28], PrEP uptake in these populations is estimated to be below 10%, the lowest PrEP uptake rate in the US [2, 10, 29]. However, the specific factors that promote or impede engagement along the PrEP care continuum among TGE-YEA and their causes and meanings are poorly understood [10, 30, 31].

While many studies report high PrEP awareness among TGE-YEA communities, they also indicate that intentions to take PrEP, as well as uptake and persistence, remain very low among TGE-YEA [1, 32–34]. The gap between PrEP awareness, intentions, and uptake underscores a critical need to understand the factors that influence their behaviors along the PrEP care continuum [35–38].

This population includes young transgender-identified individuals, as well as substantial and growing numbers of those who identify as gender nonbinary, gender non-conforming, or genderqueer, referred to here as "gender-expansive” individuals [39–41]. A recent report found that 1.2 million people in the US identify as gender-expansive and as such represent a substantial and growing population [40]. Gender-expansive can be defined as persons who expand beyond, actively resist, and/or do not subscribe to the idea of the gender binary (e.g., male or female/trans male or trans female) and wish to identify outside of the binary construct of gender [42]. Some gender-expansive individuals may identify as transgender, but some may not.

Historically, federal, state, and local-level data collected on HIV incidence and prevalence and PrEP behaviors, have only examined binary gender categories (i.e., men and women), ultimately neglecting to characterize those who are transgender and gender-expansive accurately [43]. When transgender people have been included in HIV surveillance and research, they are often categorized along binary gender lines, where transgender women are examined in conjunction with men who have sex with men, separately from transgender men and people with other gender-expansive identities, ultimately neglecting to capture gender identity accurately. Therefore, TGE persons are commonly mischaracterized in research [24–28]. The evolving nature of gender identity and the lack of precision in most research efforts in assessing gender identity means there are scant data on the TGE population [24–28, 44]. Therefore, there are significant gaps in the literature, which this study addresses.

In addition to its inclusion of gender-expansive individuals, this study aims to advance the literature on engagement along the PrEP care continuum among TGE-YEA by focusing both on risk and resilience and by including domains the literature suggests play a vital role in PrEP outcomes in this population (e.g., heavy substance use and gender affirmation) but which are understudied to date [45, 46]. By examining the specific effects of gender minority stressors and heavy substance use behaviors, along with experiences of gender affirmation, and their impacts on PrEP intentions within this population, we aim to shed light on potential intervention points and inform efforts to improve the health and well-being of TGE-YEA.

The current study

For this study, we developed a conceptual model that integrates the gender minority stress and resilience [47, 48] and the gender affirmation models [49] and includes other factors salient for TGE-YEA (see Fig. 2). Using this model, we investigate factors that promote or impede PrEP intentions among a national sample of TGE-YEA. PrEP intentions signify the readiness and motivation to use PrEP as an HIV prevention method [50]. Exploring the factors influencing PrEP intentions among TGE-YEA can provide valuable insights into their potential PrEP uptake and persistence behaviors.

Gender Minority Stress

TGE-YEA experience high levels of gender minority stress, and these experiences have been found to impede engagement along the PrEP care continuum [31, 51, 52]. Minority stress was first conceptualized to understand the specific experiences of sexual minorities and how those experiences can contribute to health disparities [53, 54]. Hendricks and Testa [47] expanded on the minority stress model by developing the gender minority stress and resilience model, to incorporate the unique experiences of gender minorities. While everyone experiences general life stressors, TGE populations experience unique gender minority stressors, including external, contextual, and distal stressors, as well as internal, psychological, and proximal stressors. Indeed, individuals within the TGE community encounter elevated levels of violence, rejection, stigma, and discrimination in multiple domains [47]. These challenges are compounded for TGE-YEA who may experience a lack of family support, social networks, and limited access to resources [48]. All young people experience vulnerability to societal pressures, however, these experiences are heightened for TGE-YEA, which makes navigating these unique gender minority stressors even more daunting [55].

In our study, we explore how TGE-YEA experience gender minority stress in distal domains; namely, discrimination in medical settings and family rejection. TGE-YEA experience high rates of discrimination in medical settings, resulting in fear of medical providers and significant medical mistrust [56]. Medical discrimination has contributed to a series of health inequities in these populations, including the postponement of or not seeking medical care when needed, including for preventative care, such as HIV and STI testing [57, 58]. Additionally, many TGE-YEA report that their experiences with family rejection significantly shape their health outcomes and further have impacts on HIV prevalence for this population. Experiences of family rejection among TGE-YEA are understood to contribute to a range of negative psychosocial and physical health outcomes, as well as socioeconomic struggles which further contribute to a range of risk factors, including engagement in survival sex work and an associated risk for HIV [59–61].

We also consider how TGE-YEA experience gender minority stress in proximal domains; namely, internalized transphobia and perceived community stigma. Internalized transphobia is understood to be internalized shame, self-blame, and low self-esteem. Feelings of internalized transphobia result from experiencing gender minority distal stressors, such as victimization, rejection, and discrimination, affecting both the mental and physical health of TGE-YEA. These effects include intense loneliness, fear of rejection, TGE identity concealment, and low self-esteem [62, 63]. Additionally, the perception of community stigma (i.e., the expectation of rejection) is a known predictor of psychological distress among TGE-YEA. Perceived TGE stigma can also contribute to negative public health outcomes, including HIV risk, substance use behaviors, and isolation [46, 64, 65]. In particular, ongoing and mounting anti-trans legislation has increased the perception of stigma in recent years and represents a growing public health concern among TGE-YEA [66]. The perception of stigma combined with actual stigma compounds to create lasting effects on health outcomes among TGE-YEA and as such, effective interventions are needed to support these populations.

Substance Use Behaviors

Experiences of these gender minority stressors contribute to negative health outcomes among TGE-YEA, including substance use behaviors [6, 67–69]. Indeed, the prevalence of substance use is 2.5-4 times higher for TGE-YEA than their cisgender peers, and TGE-YEA experience a higher risk for early age onset of substance use behaviors [70]. Overall, the role of substance use in engagement along the PrEP care continuum for TGE-YEA is understudied to date, and findings are mixed [71]. The literature suggests those with substance use behaviors may be more aware of their HIV risk and potentially evidence more favorable PrEP intentions and awareness [72]. On the other hand, substance use may impede PrEP persistence [73–75]. We attend to substance use in the present study, given its high prevalence among TGE-YEA and its association with gender minority stress.

Heavy substance Use. We specifically focus on heavy substance use as an important domain in our model. Indeed, combined distal and proximal gender minority stressors may contribute to heavy substance use [70], which in turn has the potential to reduce PrEP intentions, uptake, and persistence, resulting in negative health outcomes, including HIV infection [68, 76–78]. A deeper understanding of relationships among various types and patterns of substances used and engagement along the PrEP care continuum for diverse TGE-YEA is needed.

Gender Affirmation

Gender affirmation across various domains has been identified as a buffer against the effects of gender minority stressors [49, 79, 80]. Indeed, an emerging literature suggests that gender affirmation acts as a vital protective factor against gender minority stressors and heavy substance use behaviors among TGE-YEA [81–84], including with respect to engagement along the PrEP care continuum [73, 85]. Gender affirmation can be understood as a range of actions and possibilities related to being able to access and affirm one’s TGE identity in psychological (e.g., resistance to internalized transphobia), social (e.g., using chosen name and pronouns), legal (e.g., name change), and medical (e.g., hormone therapy) domains [86].

We focus on gender affirmation as an important domain in our model. We explore if higher levels of gender affirmation in these domains buffer the adverse effects of gender minority stressors on heavy substance use behaviors and on intentions to use PrEP. Indeed, gender affirmation has the potential to mitigate negative health outcomes among TGE-YEA, yet the multi-dimensional nature of gender affirmation remains understudied to date, particularly in relation to engagement along the PrEP care continuum for TGE populations at risk for HIV [44, 87].

PrEP Intentions

Gender minority stressors and substance use behaviors have the potential to impact PrEP intentions among TGE-YEA [52, 75]. The willingness or readiness of individuals to initiate and persist on PrEP, represents a critical aspect of HIV prevention research along the PrEP Care Continuum, particularly among TGE-YEA, given their low PrEP uptake rates (< 10%; [1]. These low uptake rates underscore the need to understand the underlying factors influencing their intentions to take PrEP. Thus, we explore the relationships among gender minority stressors, heavy substance use, gender affirmation, and PrEP intentions to develop a deeper understanding of the factors that promote or impede intentions to take PrEP among these populations and how they operate [31].

The present study drew on data from a subset of participants included in a study carried out by the CDC’s Division of Adolescent and School Health (DASH) in 2018 called the Survey of Today’s Adolescent Relationships and Transitions (START). START was a one-time, cross-sectional online survey of 3,108 youth and young adults from two populations at elevated risk for HIV: sexual minority cisgender males ages 13–18 years (N = 1541) and TGE-YEA ages 13–24 years (N = 1567). START assessed sexual and gender minority (SGM) experiences of acceptance and rejection, substance use behaviors, and sexual risk behaviors, including HIV status, as well as PrEP outcomes (awareness, intentions, uptake, and current use), and HIV care experiences. A description of START, including the design, recruitment, implementation, and data management plans, can be found elsewhere [88]. This study’s primary outcome is PrEP intentions.

Eligibility criteria. The current study focuses on a subset of the START sample using the following eligibility criteria: 1) identifies as a different gender than their assigned sex at birth, 2) is between the ages of 13–24 years, 3) not diagnosed with HIV by self-report, and 4) sexually active by self-report (and thus would be eligible for PrEP). A total of 972 individuals met the eligibility criteria and were included in the study.

Measures

Medical discrimination. Medical discrimination was assessed by a single item (“In the past 6 months, have you had any problems getting health or medical services because of your TGE identity?”), with responses coded as a binary variable where 1 = Yes/0 = No.

Family rejection. Family rejection was assessed by a single item capturing actual or perceived experiences of family rejection (“How supportive is your family of you being TGE?”). The original item was assessed on a 5-point Likert scale (very supportive to not at all supportive). To create a binary variable that characterizes experiences of family rejection, we recoded those responding “not at all supportive” or “not very supportive” as a “yes” response. Those who were not asked this question because they had previously responded in START that they had not told anyone they were TGE (N = 342), were coded as not having family support. The family rejection variable was thus coded as 1 = family rejection/0 = no family rejection.

Internalized transphobia. Internalized transphobia was assessed by a single item (“I wish I were not TGE”). The item was assessed on a 5-point Likert scale (strongly agree to strongly disagree). A binary variable was created where "strongly agree" or "agree" responses were coded as the affirmative response where 1 = Yes, has internalized transphobia/0 = No, does not have.

Perceived community TGE stigma. Perceived community TGE stigma was assessed with a single item (“Most people who live near where I do are tolerant of transgender or gender-nonconforming individuals?”). The item was assessed on a 5-point Likert scale (strongly agree to strongly disagree). A binary variable was created where "strongly agree" or "agree" responses were coded as the affirmative response, where 1 = No, does perceive TGE stigma in the community/0 = Yes; does not perceive TGE stigma in the community.

Heavy Substance Use. We created a binary variable for heavy substance use. Based on research by Bruce and colleagues [89], we defined heavy substance as including the presence of any of the following: (1) alcohol use 10 times or more in the past 30 days, 2) alcohol binge drinking, 5 + drinks in a row, 10 days or more in past 30 days, 3) cannabis use 10 times or more in the past 30 days, and 4) or any "hard" (e.g., Rx, Methamphetamines, Cocaine, Ecstasy, Heroin, IDU) drug use 10 times or more in a lifetime. Heavy substance use was coded as 1 = Yes, heavy substance use/0 = No, heavy substance use.

Gender Affirmation across five domains. START assessed gender affirmation through a set of five questions using a 5-point Likert scale, ranging from 5) strongly agree to 1) strongly disagree. These five items captured individuals' perceptions of the importance and desirability of gender-affirming experiences across different contexts. The questions included psychological gender affirmation (“I feel that being transgender or gender nonconforming has allowed me to express a natural part of myself”), gender affirmation in social, home, school, and medical settings (“It is important to me that my preferred pronouns are always used” in each of these settings), and medical gender affirmation (“It is important to me that my health care provider asks me what words I use for my body parts and describes my body using those words”). The mean score of the five items was calculated. Thus, the overall summary of gender affirmation ranged from 1 (strongly disagree) to 5 (strongly agree), with higher scores indicating a greater level of desired gender affirmation in psychological, social, and/or medical domains.

Race and Ethnicity. START assessed race and ethnicity using binary single item measures, asking participants to select all that applied. Participants were asked if they identified as, White, Hispanic, Latino/a, or Spanish, Black or African American, American Indian, or Alaska Native, Native Hawaiian or Other Pacific Islander, and/or Asian. We created four observed binary variables to capture participants’ race and ethnicity as belonging to one of the following four groups, White (not Latine or any other race), Black and not Latine, Latine, or identifying as either American Indian, Alaska Native, Native Hawaiian, Other Pacific Islander, or Asian, where 1 = Yes/0 = No. We created these dummy codes for analytic purposes. The chosen reference category is non Latine/White, as it is not only the most sizable group but also represents the racial/ethnic demographic with the greatest privilege.

Age. START assessed age numerically by asking (“How old are you?”) with the option of selecting between 13–24 years of age. The age variable was coded as 1 = 18–24 years of age/0 = 13–17 years of age.

Gender Identity. Participants in START were asked (“How do you currently describe your gender?”) to assess gender identity. Response options included (male, female, genderqueer/gender non-conforming, transgender female-to-male, transgender male-to-female, something else, or don’t know). We created three binary variables to capture participant’s gender identity into only one category (trans female, trans male, or gender expansive) each coded as 1 = Yes/0 = No. The trans-female variable includes those assigned male at birth and identified as female with those who identify as male to female. The trans-male variable includes those who were assigned female at birth and identify as male combined with those who identify as female to male. The gender expansive variable includes those identifying as genderqueer/gender non-conforming or something else. We created these dummy codes for analytic purposes, and the chosen reference category is the trans female variable, which represents the most sizable group in this sample.

Region. Participant region was assessed by four single item measures (“What region of the US do you live in..?”, in each of these regions: Northeast, Southeast, Midwest, or West). All were assessed on a binary scale coded as 1 = Yes/0 = No. The chosen reference category for this variable is the Southeast region, which represents the largest group in this sample.

Socioeconomic Barriers. Socioeconomic barriers were assessed by a single item (“In the past 12 months, was there a time when there wasn’t enough money in your house or apartment for rent, food, or utilities, such as gas, electric, or phone?”) and coded as a binary variable where 1 = Yes/0 = No.

Gender identity disclosure. Disclosure of TGE identity was assessed by a single item (“Have you told another person about being transgender or gender nonconforming?”) and coded as a binary variable where 1 = Yes/0 = No.

Sexual Orientation. Sexual orientation was assessed by a single item (How would you describe yourself?”) with the following response options: Heterosexual, Lesbian, Gay, Bisexual, Queer, Pansexual, Asexual, Demisexual, Questioning/unsure, Something else. We created a binary variable coded as 1 = LGBTQIA+/0 = Heterosexual.

Substance Use Types. START assessed 11 types of substance use using single items for each. Lifetime or current use was assessed for each type of substance. Responses were on an ordinal scale and included times used or the number of days used. We then created a binary variable where 1 = any use/0 = no use.

Current use. Current substance use was measured by asking about daily use of alcohol ("During the past 30 days, on how many days, if any, did you have at least one drink of alcohol?"), binge drinking behaviors ("During the past 30 days, on how many days did you have 5 or more drinks of alcohol in a row, that is, within a couple of hours?"), and use of cannabis ("During the past 30 days, how many days did you use cannabis?").

Lifetime use. Lifetime substance use was measured by number of days used for alcohol (“During your life, on how many days have you had at least one drink of alcohol?”). Number of times used was measured for cannabis, cocaine, ecstasy, prescription drugs (without an Rx), methamphetamines, heroin, and injection drug use (e.g., “During your lifetime, how many times have you used…?”).

PrEP Behaviors

Intentions to use PrEP (primary outcome). PrEP intentions were measured in START with a single item (“Would you be likely to use PrEP, that is, to take an anti-HIV medicine every day to lower your chances of getting HIV?”) assessed on a 5-point Likert scale with responses ranging from very unlikely to very likely. Responses were dichotomized to a binary variable. Those who selected “very likely" and "somewhat likely" to use PrEP were coded as 1, and those who were, “unsure” “somewhat unlikely”, or “very unlikely” to use PrEP were coded as 0. Those who were not asked this question because they had previously responded in START that they were not aware of PrEP (N = 656) were coded as 0, unlikely to use PrEP. We created a binary variable where 1 = has intentions to use PrEP/0 = no intentions to use PrEP.

PrEP awareness. PrEP awareness was assessed by a single item (“Before today, have you heard of PrEP or Truvada?”). PrEP uptake. PrEP uptake was assessed by a single item (“Have you ever used PrEP before?”). Current PrEP Use. PrEP use was assessed by a single item (“Are you currently taking PrEP?”). All were coded as 1 = Yes/0 = No.

Missing data strategy

The START study included some branching logic that resulted in key items not being asked of participants based on their prior responses. This resulted in data not missing at random. The following variables were affected: family rejection and PrEP intentions. These variables were coded for analysis to reduce missingness, as described in the Measures section.

Then, a complete case analysis was conducted to exclude cases with any missing data across all study variables. This process resulted in a final analytic sample of N = 972 participants, with N = 229 participants eliminated due to incomplete data. These exclusions specifically comprised individuals who selected responses such as 'doesn't apply to me,' 'don't know,' or 'prefer not to answer,' reflecting varying levels of missingness across the dataset. As a result of these systematic strategies, the analysis was conducted with no missing data.

Data Analysis

Descriptive statistics (frequencies, means) were computed using R [90] to characterize the sample, including the following background measures (described above) not included in the analysis (PrEP awareness, uptake, current PrEP use, sexual orientation, gender identity disclosure, and types and frequencies of substance use behaviors), as well as the analytic measures described below.

Measures. Measures included in the model (described above) were gender minority distal (medical discrimination, family rejection) and proximal stressors (internalized transphobia, perceived community TGE stigma), heavy substance use, intentions to take PrEP, and gender affirmation. Background factors (covariates) were integrated to address potential confounding effects and enhance the robustness of our findings. These include sociodemographic and background variables collected in START, including race/ethnicity, age, gender identity, US region, and socioeconomic factors. Their selection is grounded in prior research findings and theoretical frameworks, supporting their relevance in our study context [80, 91, 92]. Gender identity disclosure, substance use types, and sexual orientation were used for descriptive purposes.

First, we examined the effects of gender minority stress, including proximal and distal stressors, and behavioral responses to stress (heavy substance use) on PrEP intentions among TGE-YEA who evidence HIV risk and would be eligible for PrEP. This first step of our analysis tests Hypothesis 1: Gender minority stressors will increase the risk for heavy substance use, which will, in turn, reduce PrEP intentions. The goal is to understand if gender minority stress undermines PrEP intentions, by means of its effects on heavy substance use. To investigate this first step in our analysis and H1 we estimated direct effects using Mplus [93]. The model included regression equations for the following variables: 1) proximal stress (internalized transphobia, perceived TGE stigma); 2) heavy substance use, and 3) PrEP intentions. Proximal stressors (internalized transphobia, perceived TGE stigma) will be regressed on distal stressors (medical discrimination and family rejection) and background variables (race/ethnicity, age, gender identity, US region, and socioeconomic factors). Heavy substance use will be regressed on distal stress (medical discrimination, family rejection), proximal stress (internalized transphobia, perceived TGE stigma), gender affirmation, and background variables. The PrEP intentions outcome will be regressed on distal stress (medical discrimination, family rejection), proximal stress (internalized transphobia, perceived TGE stigma), gender affirmation, heavy substance use, and background factors.

Next, we expand our analysis to consider the possibility of gender affirmation as an important moderator of specific direct effects of stress on heavy substance use and on PrEP intentions through heavy substance. This next step tested Hypothesis 2: When gender affirmation levels are high, the negative impact of stressors, including on heavy substance use, is diminished and PrEP intentions will increase. To investigate this, interaction effects between gender affirmation and both distal and proximal stressors will be added to the regression equation for heavy substance use. This will make estimates of effects of gender minority stress on heavy substance conditional on the level of gender affirmation. If these interaction effects are significant, effects of gender minority stress on heavy substance use and on PrEP intentions will be estimated at low, average, and high levels of gender affirmation.

Structural Equation Model

A Structural Equation Modeling (SEM) framework was used to conduct our analyses. With a relatively large sample size (N = 972), our study was determined to have adequate statistical power (80%) to detect medium effect sizes in the hypothesized relationships among variables. All variables included in this analysis were directly observed.

We used the robust maximum likelihood estimator with robust standard errors (ESTIMATOR = MLR) in Mplus (v. 8.9) [93], which is well-suited for data exhibiting non-normality, as is characteristic of our primarily binary variables with one continuous moderator [94]. The MLR approach in Mplus applies a numerical integration algorithm ensuring the robustness of our findings [95]. By computing standard errors using a sandwich estimator, the MLR framework enhances the stability of results against violations of standard statistical assumptions [93]. Given our need to test interactions with a continuous moderator (gender affirmation) and binary variables, and to model the correlation structure within our binary data accurately, MLR is the preferred method of analysis within Mplus [96].

In our analysis, we did not declare our four binary outcome variables as categorical. This decision was informed by methodological considerations given the nature of our model and variables. Utilizing MLR enabled us to maintain continuous treatment of our binary variables, preserving the integrity and precision of our parameter estimates without introducing unnecessary complexity [97]. This approach provided clearer and more intuitive estimates while ensuring statistical robustness. By treating the binary outcomes as continuous, we avoided potential misinterpretations that can arise from categorization, such as artificial threshold effects [94]. This approach is particularly beneficial for integrating our continuous moderating variable (gender affirmation) into our interaction terms without the non-linear transformation complications presented by logistic regression [98]. Therefore, in the context of our analysis, a linear regression model is used and the coefficients can be interpreted as risk differences expected for a one-unit change in the explanatory variable [94, 97].

Prior to testing direct effects (i.e., the structural portion of the model), the degree to which the baseline model fits the data will first be assessed. For model fit, we assess four indices, the chi-square level of significance, the comparative fit index (CFI), the root mean square error of approximation (RMSEA), and the standardized root mean square residual (SRMR) using their standard cutoff scores (Chi-square p value > .05, CFI ≥ 0.90, RMSEA < 0.06, and SRMR ≤ 0.08; see (Kline, 2023). Our analysis included an examination of both direct and moderated effects, utilizing 95% bias-corrected confidence intervals. Our results will be presented in unstandardized form, reflecting the raw parameter estimates obtained from the analysis. Modification indices may be used to improve the fit of the baseline model. All variables are mean-centered to reduce collinearity when estimating interaction effects. Results are interpreted by evaluating both hypotheses, with an examination of barriers to and facilitators of PrEP intentions for TGE-YEA.

Table 1

Sociodemographic factors & health behaviors (N = 972)
Variable		N
Age in years	19.1 (2.67)	-
13–17 years	31.4	305/972
18–24 years	68.6	667/972
Gender Identity		-
Gender Expansive (genderqueer, nonbinary, genderfluid)	25.2	245/972
Transfemale	47.5	462/972
Transmale	27.3	265/972
Gender Identity Disclosure	72.8	708/972
Race/Ethnicity		-
Black, non-Latine	16.0	156/972
White, non-Latine	45.3	440/972
Latine	27.5	267/972
Asian, AAIN, or NHOPI, non-Latine	11.2	109/972
Sexual Orientation		-
Heterosexual	1.6	16/972
LGBTQIA+	98.4	956/972
Socioeconomic Barriers		-
Not enough money for basic needs in the past 12 months	37.2	362/972
Region		-
Northeast	16.3	158/972
Southeast	31.8	309/972
Midwest	22.4	218/972
West	29.5	287/972
PrEP behaviors		-
PrEP Awareness	48.4	470/972
PrEP Intentions	24.6	239/972
PrEP Uptake (ever)	7.1	69/972
Current PrEP Use	4.2	41/972
Substance Use Behaviors		-
Heavy Substance Use	40.7	396/972
Types of Substances Use (1 + times used)		-
Alcohol (lifetime)	84.9	825/972
Alcohol (past 30 days)	65.9	641/972
Alcohol Binge (past 30 days, 5 + drinks in one sitting)	50.6	492/972
Cannabis (lifetime)	63.8	620/972
Cannabis (past 30 days)	47.5	463/972
Non-prescribed Rx Drugs (lifetime)	41.0	399/972
Methamphetamines (lifetime)	25.8	251/972
Cocaine (lifetime)	29.4	286/972
Ecstasy (lifetime)	30.9	300/972
Heroin (lifetime)	24.9	242/972
Injection Drug Use (lifetime)	27.0	262/972

The sociodemographic factors and health behaviors of the sample are represented in Table 1. The majority (68.6%) fell in the 18–24 years of age range. Gender identities ranged across gender expansive (25.2%), trans female (47.5%), and trans male (27.3%). Additionally, 72.8% reported they had disclosed their gender identity to at least one person. A majority reported their sexual orientation as LGBTQIA+ (98.4%). Approximately half (54.7%) identified their race/ethnicity as non-white, and (43.5%) of those respondents identified as Black and/or Latine. The sample was regionally diverse, with approximately a third residing in the Southeast region of the US (31.8%). Additionally, 37.2% did not have enough money for basic needs in the past 12 months.

Substance use behaviors were prevalent, with 40.7% of the sample reporting a history of heavy substance use. Across substance types, the lowest rate of lifetime use reported was for heroin (24.9%), while the highest reported was for alcohol (84.9%). Additionally, slightly more than half of the sample (50.6%) reported alcohol binge drinking (5 + drinks in one sitting) in the past 30 days. Less than half of the sample (48.4%) reported being aware of PrEP, while a smaller proportion expressed intentions to use PrEP (24.6%). A minority of participants reported having ever used PrEP (7.1%), with an even smaller portion (4.2%) currently using it.

Model

The baseline model showed a marginal fit to the data (Chi-Square (3) = 9.214, p = .0266, RMSEA = 0.046, CFI = 0.987, SRMR = 0.011), and had 3 degrees of freedom and 63 free parameters. There were no standardized residuals whose absolute value was greater than 2. For modification indices exceeding 4.0 (the highest such index was 7.87), we estimated two additional parameters. First, we modeled the covariance between gender affirmation and internalized transphobia. Additionally, we accounted for covariance among all independent variables to capture nuanced relationships beyond direct effects. These decisions were consistent with our theoretical models [48, 49, 80], which suggested their interdependence [99].

Next, we examined interaction effects between gender minority stressors (medical discrimination, family rejection, internalized transphobia, perceived TGE stigma) and gender affirmation to understand their combined impact on heavy substance use behaviors and intentions to use PrEP. As detailed in Table 2, and further described below, three significant interaction effects were found between family rejection, internalized transphobia, and perceived TGE stigma and gender affirmation on heavy substance use behaviors. These three significant interactions, along with the covariances described above, were incorporated into our final model.

Our final structural equation model (see Fig. 3) had satisfactory overall global fit (Chi-Square (7) = 6.922, p = .0437, RMSEA = 0.000, 90% CI [0.000, 0.039, p-value for close fit = 0.992, CFI = 1.000, standardized RMR = 0.006; see [99], for a description of these indices). The final model fit indicates it is a reasonable representation of the underlying relationships among the variables. The final model had 7 degrees of freedom and 223 free parameters.

Main Effects

Table 2

Unstandardized estimates (B), standard errors (SE), and two-tailed p-values for structural equation model of experiences of gender minority stress (distal and proximal), gender affirmation, heavy substance use behaviors, and PrEP uptake intentions (N = 972).
Path	B	S.E.	p-value
Structural Coefficients- Main Effects
Family Rejection → Internalized Transphobia	0.040	0.032	0.220
Medical Discrimination → Internalized Transphobia	0.097	0.034	0.005
Family Rejection → Perceived TGE Stigma	0.181	0.032	< 0.001*
Medical Discrimination → Perceived TGE Stigma	0.087	0.034	0.010
Family Rejection → Heavy Substance Use	0.260	0.053	< 0.001*
Medical Discrimination → Heavy Substance Use	0.016	0.032	0.629
Internalized Transphobia → Heavy Substance Use	-0.057	0.039	0.145
Perceived TGE Stigma → Heavy Substance Use	0.106	0.037	0.004
Family Rejection → PrEP Intentions	-0.013	0.031	0.681
Medical Discrimination → PrEP Intentions	0.026	0.029	0.368
Internalized Transphobia → PrEP Intentions	0.052	0.028	0.059
Perceived TGE Stigma → PrEP Intentions	-0.085	0.027	0.002
Heavy Substance Use → PrEP Intentions	-0.161	0.031	< 0.001*
Gender Affirmation → Heavy Substance Use	-0.010	0.039	0.796
Gender Affirmation → PrEP Intentions	0.045	0.019	0.020
Structural Coefficients- Interaction Effects
Gender Affirmation * Family Rejection → Heavy Substance Use	-0.168	0.040	< 0.001*
Gender Affirmation * Medical Discrimination → Heavy Substance Use	-0.032	0.033	0.335
Gender Affirmation * Internalized Transphobia → Heavy Substance Use	0.082	0.035	0.018
Gender Affirmation * Perceived TGE Stigma→ Heavy Substance Use	-0.063	0.031	0.039
Gender Affirmation * Family Rejection → PrEP Intentions	-0.008	0.039	0.838
Gender Affirmation * Medical Discrimination → PrEP Intentions	0.042	0.032	0.185
Gender Affirmation * Internalized Transphobia → PrEP Intentions	-0.045	0.033	0.162
Gender Affirmation * Perceived TGE Stigma → PrEP Intentions	-0.013	0.030	0.657
Estimates and associated statistics were generated in Mplus 8.10 (estimator = MLR), *p < 0.001

The main effects of our model (Table 2 & Fig. 3) represent the unstandardized estimates (B), standard errors (SE), and two-tailed p-values for our modified model of experiences of gender minority stress (distal and proximal), gender affirmation (at an average level), heavy substance use behaviors, and PrEP intentions (N = 972). We do not present results for covariates, which were included to control for potential confounding effects.

Gender Minority Stressors. We tested the direct effects of distal stress (family rejection, medical discrimination) on proximal stress variables (internalized transphobia, perceived stigma). Family rejection increased perceived TGE stigma (b = 0.181, SE = 0.032, p < 0.001), but did not have a significant relationship with internalized transphobia (b = 0.040, SE = 0.032, p = 0.220). Additionally, medical discrimination increased both internalized transphobia (b = 0.097, SE = 0.034, p = 0.005) and perceived TGE stigma (b = 0.087, SE = 0.034, p = 0.010).

Heavy Substance Use. We also tested the effects of distal (family rejection, medical discrimination) and proximal (internalized transphobia, perceived stigma) gender minority stressors on heavy substance use behaviors. Family rejection (b = 0.260, SE = 0.053, p < 0.001) and perceived TGE stigma (b = 0.106, SE = 0.037, p = 0.004) increased heavy substance use behaviors. However, medical discrimination (b = 0.018, SE = 0.032, p = 0.582) and internalized transphobia (b = -0.057, SE = 0.039, p = 0.145) did not have a significant effect on heavy substance use behaviors.

PrEP Intentions. Next, we tested the effects of distal (family rejection, medical discrimination) and proximal (internalized transphobia, perceived stigma) stressors and heavy substance use behaviors on PrEP intentions. Perceived TGE stigma (b = -0.085, SE = 0.027, p = 0.002) and heavy substance use (b = -0.161, SE = 0.031, p < 0.001) decreased intentions to take PrEP intentions. Also, internalized transphobia (b = 0.052, SE = 0.028, p = 0.059) may reduce PrEP intentions. However, family rejection (b = -0.013, SE = 0.031, p = 0.681) and medical discrimination (b = 0.026, SE = 0.029, p = 0.368) did not have significant direct effects on PrEP intentions.

Gender Affirmation. Lastly, we tested the effects of gender affirmation on heavy substance use behaviors and PrEP intentions. Gender affirmation increased PrEP intentions (b = 0.045, SE = 0.019, p = 0.020), although gender affirmation did not have a direct effect on heavy substance use behaviors (b = -0.010, SE = 0.039, p = 0.796).

Interaction Effects

Next, in Table 2, we examined the potential interaction effects between gender affirmation and various measures of gender minority stress to understand their combined impact on heavy substance use and PrEP intentions. We found that the interaction between gender affirmation and family rejection (b = -0.168, SE = 0.040, p < 0.001), internalized transphobia (b = 0.082, SE = 0.035, p = 0.018), and perceived TGE stigma (b= -0.063, SE = 0.031, p = 0.039) were significantly associated with heavy substance use behaviors. However, the interaction between gender affirmation and medical discrimination (b = 0.032, SE = 0.033, p = 0.335) did not significantly predict heavy substance use.

None of the potential interaction effects between gender affirmation and family rejection (b = -0.008, SE = 0.039, p = 0.838), medical discrimination (b = 0.042, SE = 0.032, p = 0.185), internalized transphobia (b = -0.045, SE = 0.033, p = 0.162), or perceived TGE stigma (b = -0.013, SE = 0.030, p = 0.657) significantly predicted PrEP intentions.

Conditional Effects

While Table 2 detailed the main effects and interaction effects, it does not explain how the effects of gender minority stress on heavy substance use differ across various levels of gender affirmation. Considering the significant interaction effect found between gender affirmation and family rejection, internalized transphobia, and perceived TGE stigma for heavy substance use behaviors, we estimated conditional (i.e., simple) effects of each of these gender minority stress variables (family rejection, internalized transphobia, perceived TGE stigma) to understand how their impact depends on affirmation. These conditional effects are presented in Table 3.

Table 3. Conditional Effects of Family Rejection, Internalized Transphobia, and Perceived TGE Stigma on Heavy Substance Use at Varying Levels of Gender Affirmation (GA), *p < 0.05
		GA = 1			GA = 2		GA = 3		GA = 4			GA = 5
Family Rejection
Yes		0.809			0.630		0.452		0.273			0.094
No		0.212			0.202		0.192		0.182			0.171
Risk Difference (SE)		0.597* (0.128)			0.428* (0.089)		0.260* (0.053)		0.091* (0.032)			-0.077 (0.049)
When family rejection is present, for each 1-point increase in GA, the risk of heavy substance use is reduced by -0.179 (SE = 0.030; p < 0.001)
Internalized Transphobia
Yes			-0.010	0.062		0.134		0.206			0.278
No			0.212	0.202		0.192		0.182			0.171
Risk Difference (SE)			-0.222* (0.100)	-0.139* (0.067)		-0.057 (0.039)		0.025 (0.031)			0.107 (0.052)
When internalized transphobia is present, for each 1-point increase in GA, the risk of heavy substance use is increased by 0.072 (SE = 0.048; p = 0.136)
Perceived TGE Stigma
Yes	0.445			0.371		0.298				0.224			0.150
No	0.212			0.202		0.192				0.182			0.171
Risk Difference (SE)	0.233* (0.089)			0.169* (0.061)		0.106* (0.037)				0.042 (0.029)			-0.021 (0.048)
When perceived TGE stigma is present, for each 1-point increase in GA, the risk of heavy substance use is reduced by -0.074 (SE = 0.041, p = 0.074)

In our sample, gender affirmation scores, measured on a 5-point Likert scale, primarily clustered around the midpoint, with a score of 3 being the most common. To assess the potential moderating effect of gender affirmation, we estimated effects of family rejection, internalized transphobia, and perceived TGE stigma when gender affirmation scores were 1, 2, 3, 4, or 5. We mean-centered gender affirmation, setting zero to represent the average score of 3, to enhance the interpretability of its moderating effects. Our results revealed that gender affirmation emerges as a significant moderator, weakening the association of family rejection, internalized transphobia, and perceived TGE stigma on heavy substance use behaviors, which consequently influences effects of family rejection, internalized transphobia, and perceived TGE stigma on PrEP intentions.

Family Rejection. The effects of family rejection on heavy substance use behaviors remained significant across gender affirmation levels 1 (b = 0.597, SE = 0.128), 2 (b = 0.428, SE = 0.089), 3 (b = 0.260, SE 0.053), 4, (b = 0.091, SE = 0.032), becoming nonsignificant at the highest level of gender affirmation 5 (b = -0.077, SE 0.049). These conditional effects illustrate that as gender affirmation increases, the influence of family rejection on heavy substance use behaviors decreases and becomes insignificant at the highest level of gender affirmation. Moreover, when family rejection is present, for each 1-point increase in gender affirmation, the risk of heavy substance use is reduced by -0.179 (SE = 0.030; p < 0.001). This suggests gender affirmation has a protective role in mitigating the impact of family rejection on heavy substance use behaviors, which can, in turn, change how family rejection affects PrEP intentions.

Internalized transphobia. The conditional effects of internalized transphobia on heavy substance use behaviors vary at different levels of gender affirmation. The impact was significant at gender affirmation levels 1 (b = 0.222, SE = 0.100) and level 2 (b = 0.139, SE = 0.067). However, the effect became nonsignificant at level 3 (b = 0.057, SE = 0.039) and level 4 (b = 0.025, SE = 0.031), and shifted to a nonsignificant negative impact at level 5 (b = -0.107, SE = 0.052). These findings indicate that increasing levels of gender affirmation reduce the influence of internalized transphobia on heavy substance use, with the effects becoming minimal and nonsignificant at the highest affirmation level. Moreover, when internalized transphobia is present, for each 1-point increase in gender affirmation, the risk of heavy substance use is marginally increased by 0.072 (SE = 0.048; p = 0.136), highlighting a complex relationship. This suggests that while gender affirmation has a protective role in mitigating the detrimental effects of internalized transphobia, it does so in nuanced ways that could significantly alter related behaviors, including intentions to use PrEP.

Perceived TGE stigma. The impact of perceived TGE stigma on heavy substance use behaviors was significant at gender affirmation levels 1 (b = 0.233, SE = 0.089), 2 (b = 0.169, SE = 0.061), and 3 (b = 0.106, SE = 0.037). However, the effects became nonsignificant at level 4 (b = 0.042, SE = 0.029) and level 5 (b = -0.021, SE = 0.048). These conditional effects illustrate that as gender affirmation increases, the influence of perceived TGE stigma on heavy substance use behaviors decreases and becomes insignificant at higher levels of gender affirmation. Moreover, when perceived TGE stigma is present, for each 1-point increase in gender affirmation, the risk of heavy substance use is reduced by -0.074 (SE = 0.041; p = 0.074). This suggests gender affirmation has a protective role in mitigating the impact of perceived stigma on heavy substance use behaviors, which can, in turn, change how perceived stigma affects PrEP intentions.

These conditional effects underscore the nuanced moderating role of gender affirmation highlighting its differential impact on various gender minority stressors and their effects on heavy substance use behaviors. Importantly, our findings uncovered that gender affirmation emerges as a significant moderator, weakening the influence of family rejection, internalized transphobia, and perceived stigma on heavy substance use behaviors, which, in turn, affects intentions to take PrEP.

These findings offer insights into the gender minority stress and gender affirmation experiences of TGE-YEA and their subsequent impact on heavy substance use behaviors, as well as their intentions to adopt PrEP for HIV prevention. These domains are important for the health and well-being of TGE-YEA. Overall, these results illuminate the dynamics among gender affirmation, family rejection, perceived stigma, heavy substance use behaviors, and PrEP intentions, providing valuable insights into potential pathways for targeted interventions. Similar to experiences of stigma and discrimination, gender affirmation can be directly influenced by acceptance from others. This means, that when TGE-YEA experience acceptance, they feel a stronger sense of affirmation in their gender identity, which significantly promotes their well-being and resilience [100, 101].

Engagement along the PrEP Care Continuum

Despite concerted efforts to promote PrEP among sexual and gender minority populations [1], our findings indicate that slightly more than half of the TGE-YEA in our sample were unaware of PrEP, aligning with existing research demonstrating variation in PrEP awareness among different gender minority identities [102]. This suggests that PrEP promotion efforts may not be uniformly reaching or engaging all segments of the TGE-YEA community. The reasons behind this lack of awareness are multifaceted. Research suggests barriers at the healthcare provider level, such as biases or a lack of training in gender-affirming care practices, may impede the delivery of effective PrEP education during clinical encounters [36, 82, 83]. The stigma associated with HIV and PrEP usage may further restrict TGE-YEA's access to or engagement with PrEP information [5, 103]. Given the pivotal role of awareness in the pathway to PrEP uptake, understanding the underlying factors contributing to low PrEP awareness among TGE-YEA is critical. The persistence of low awareness levels within these populations necessitates further investigation into the effectiveness of current PrEP promotion strategies and the potential need for tailored approaches to reach this specific community [31].

Our findings also indicate a significant gap between PrEP awareness, intentions to take PrEP, and PrEP uptake. While slightly more than half of our sample reported being aware of PrEP, less than a quarter of the sample reported intentions to take PrEP, and even smaller amount of the TGE-YEA in our sample have taken PrEP. The disconnect between awareness, intentions and uptake may be attributed to a variety of factors. Many TGE-YEA have not disclosed their gender identity or sexual orientation to their families, which can be a barrier to PrEP uptake [31, 104]. Also, TGE-YEA may fear disclosing their sexual orientation to their medical providers [51, 105], and if they experience discrimination in medical settings, they are unlikely to stay engaged in care [41, 56, 106]. Additionally, TGE-YEA report concerns about potential PrEP interactions with hormone replacement (HRT) therapy [107, 108]. Developing an understanding of these complex dynamics is essential for developing effective interventions to promote the engagement of TGE-YEA along the PrEP care continuum (i.e., awareness, intentions, uptake, and persistence) [34].

Heavy Substance Use and PrEP

Our findings revealed significant relationships among the gender minority distal (medical discrimination, family rejection) and proximal (internalized transphobia and perceived TGE stigma) stress factors measured in this study highlighting their impacts on heavy substance use behaviors and intentions to take PrEP to prevent HIV. Historically, there have been mixed findings regarding of the role substance use on the PrEP care continuum. In past studies, substance use has been found to contribute to PrEP awareness and uptake and in other studies to contribute to the discontinuation of HIV prevention measures and disrupt PrEP persistence [71]. The effects of substance use on the different stages of the PrEP care continuum, therefore, remain ambiguous [109].

In the present study, we discovered that heavy substance use behaviors significantly reduced the PrEP intentions among TGE-YEA in our sample. This finding underscores the influence of broader systemic factors, as heavy substance use may serve as a coping mechanism that detracts from engagement with long-term health goals, including PrEP adoption [110, 111]. Heavy substance use can lead to a focus on immediate needs rather than future health goals, a situation worsened by feelings of hopelessness [112]. For TGE-YEA, this hopelessness can stem from constant experiences of rejection and discrimination, as well as the stress of living in a hostile socio-political environment [113]. These factors together add to the already significant challenges that TGE-YEA encounter. Such a climate exacerbates the gender minority stressors inherent in their daily lives and may discourage the pursuit of preventive health measures [76, 91]. This suggests a vital link between the immediate coping strategies adopted by TGE-YEA facing systemic adversity and their diminished proactive health behaviors. A nuanced understanding of how substance use influences each stage of the PrEP care continuum is needed to develop interventions that are specifically designed for these populations.

Gender Affirmation, Gender Minority Stressors, and Heavy Substance Use

Our findings revealed that gender affirmation has the potential to lessen the effects of family rejection on heavy substance use behaviors. These conditional effects imply a potential intervention strategy: which is to consider ways to strengthen gender-affirming experiences in non-family settings, such as in school, community agencies and medical provider spaces to potentially mitigate the impact of family rejection on heavy substance use behaviors, in turn, increasing intentions to take PrEP. We know from past research that when TGE-YEA experience family acceptance, they generally have better psychosocial, physical, and sexual health outcomes [114–117]. However, past studies have also shown that family relationships are not always modifiable in the lives of TGE-YEA, and therefore it is important to understand ways to improve their health outcomes that do not involve families [118, 119]. These findings suggest that if TGE-YEA are accepted for who they are and affirmed in their gender identity in settings outside of their families, such as in school, medical, and legal settings, we have the [105] opportunity to mitigate experiences of family rejection. This means they may be less likely to engage in heavy substance use behaviors, more likely to uptake PrEP to prevent HIV, and potentially experience an entire host of other health benefits [57, 85, 120–122].

Internalized transphobia (i.e., internalized shame) resulting from experiences of transgender discrimination and rejection is linked to increased mental health concerns, substance use behaviors, loneliness, and low self-esteem [63, 123–125]. However, our findings demonstrate that higher levels of gender affirmation may buffer the harmful impact of internalized transphobia on heavy substance use behaviors among TGE-YEA. This aligns with research indicating that positive identity affirmation and supportive peer and community networks can mitigate the adverse effects of internalized transphobia on health outcomes among TGE-YEA [126–128]. Notably, as our study shows, when TGE-YEA experience greater affirmation of their gender identity across psychological, social, medical, and legal levels, including personal validation, peer and community support, or affirmation in health settings, the detrimental effects of internalized transphobia on substance use behaviors may decrease, and in some cases, become insignificant [125, 129–131]. This suggests that fostering environments that promote gender affirmation could be crucial in reducing the negative health impacts associated with internalized transphobia, thus potentially increase PrEP uptake [31, 105]

Our findings also suggest that gender affirmation experiences have the potential to dampen the effects of perceived stigma on TGE-YEA heavy substance use behaviors. Indeed, emerging research on the effects of school and community connectedness in TGE-YEA populations show these experiences lessen the effects of perceived stigma. When TGE-YEA feel affirmed in their gender identity, have supportive allies and connections to a large TGE community, the less the effects of perceived stigma has on heavy substance use behaviors and associated HIV risk [76, 132, 133].

Anti-Transgender Legislation

While our study focuses primarily on exploring the direct effects of specific gender minority stressors on heavy substance use behaviors and intentions to take PrEP, it is important to acknowledge the pervasive influence of policy and legislative environments on the lived experiences of TGE-YEA [134]. In the context of our findings on the significant impact of distal (medical discrimination, family rejection) and proximal (internalized transphobia, perceived TGE stigma) stressors on the heavy substance use behaviors and on PrEP intentions among TGE-YEA, it is essential to consider the broader societal context in which these stressors arise. Mounting and ongoing legislative attacks targeting TGE-YEA in the United States have been sweeping the country for the past several years [135], and the impacts of this onslaught are felt far and wide in this vulnerable population of young people.

Anti-transgender policies have detrimental effects on the health and mental health of TGE persons overall [134, 136, 137], including for TGE-YEA [138]. Indeed, consumption of news about anti-transgender legislation has been associated with increased rumination, depressive symptoms, physical health symptoms, fear of identity disclosure, and experiences of discrimination and maltreatment among TGE-YEA [113]. A recent national survey with queer and trans young people showed that nearly 1 in 3 respondents surveyed reported poor mental health due to anti-LGBTQ policies and legislation, whereas 79% of respondents reported that hearing about states trying to ban conversion therapy made them feel better [139]. Additionally, emerging research on state level stigma and gender affirming medical care shows that when TGE-YEA are able to access and experience gender affirming medical care, they experience less severe psychological distress and when they are in a state that has supportive transgender policies, they are less likely to exhibit health care avoidance behavior [140].

TGE-YEA face unique health challenges, compounded by anti-transgender policies such as those restricting access to gender-affirming care and participation in sports. These policies exacerbate marginalization and health risks [66]. Considering these challenges, understanding the potential consequences of restrictive policies on the health and well-being of TGE-YEA as they navigate their daily lives is essential [113].

Limitations

We recognize the limitations of this study. Firstly, the use of cross-sectional data is a fundamental limitation for conducting mediation analysis. However, this study aims to contribute to the small, but growing literature to date to understand the experiences of TGE-YEA. Further, this analysis aimed to examine whether the hypothesized relationships are plausible. Secondly, branching logic in START led to specific choices in this analysis to ensure we had participants who were not yet out as TGE and who were not aware of PrEP. Future research should consider ensuring all young people are given the chance to answer questions regarding their experiences with their families, whether they are out as TGE to their families or not, as well as the opportunity to be asked if they would take PrEP, given that they are now aware that it exists due to being asked the question.

Thirdly, START, while concise, lacks mental health indicators and relies on single item measures rather than validated scales. Identifying and using validated scales to measure these concepts is an important next step. Lastly, START lacks detailed data on the PrEP care continuum engagement. Future studies with TGE-YEA might consider including important confounders and structural factors along the PrEP care continuum, to understand the varying factors that impact PrEP uptake and persistence for these populations.

Implications

Given the high substance use rates in this sample and that close to half reported being unaware of PrEP and as having heavy substance use behaviors, it is clear that the unique experiences of TGE-YEA require a tailored HIV prevention strategy. The significant negative association between heavy substance use and PrEP intentions highlights the need for further research to investigate this relationship and identify effective strategies to improve PrEP outcomes among this population. Multi-level interventions are needed such as policy amendments to increase PrEP access, training for healthcare providers to better support TGE-YEA, community-based programs that provide peer support, and individual counseling that addresses both substance use and PrEP adherence [141]. Such a comprehensive approach could facilitate improved engagement at each stage of the PrEP care continuum.

Additionally, given the role gender affirmation has on buffering the experiences of family rejection, internalized transphobia, and perceived TGE stigma on heavy substance use behaviors, further research could explore how to implement gender-affirmative services. Gender-affirmative services across psychological, social, legal, and medical settings, have the potential to reduce heavy substance use behaviors and may increase PrEP uptake among TGE-YEA [75]. A deeper understanding of the underlying mechanisms of gender affirmation in varying settings is needed to develop targeted interventions that promote positive health outcomes among this population.

Also, given the impact of anti-transgender legislation on TGE-YEA health outcomes, future research should continue to investigate the interplay between policy impacts, societal attitudes, and the health outcomes of TGE-YEA populations, to inform targeted interventions and advocacy efforts aimed at advancing health equity and promoting their well-being. Indeed, informed policy and compassionate healthcare practices have the potential to address these challenges [66].

These findings provide initial insights into the role gender affirmation has in shaping substance use behaviors and HIV prevention intentions among TGE-YEA. This study underscores the importance of addressing heavy substance use among TGE-YEA as a potential barrier to PrEP uptake, a critical tool for HIV prevention. Additionally, the findings from this study advance the literature on understanding the role that gender affirmation plays in the lives of diverse TGE-YEA, particularly for those who are experiencing the greatest barriers to engagement along the PrEP care continuum.

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The authors declare no competing interests.

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Intentions to use PrEP among a national sample of transgender and gender-expansive youth and emerging adults: Examining gender minority stress, substance use, and gender affirmation.

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Abstract

Figures

Introduction

The current study

Gender Minority Stress

Substance Use Behaviors

Gender Affirmation

PrEP Intentions

Methods

Measures

PrEP Behaviors

Missing data strategy

Data Analysis

Structural Equation Model

Results

Model

Main Effects

Interaction Effects

Conditional Effects

Discussion

Engagement along the PrEP Care Continuum

Heavy Substance Use and PrEP

Gender Affirmation, Gender Minority Stressors, and Heavy Substance Use

Anti-Transgender Legislation

Limitations

Implications

Conclusion

References

Additional Declarations

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