"I Owe No One Any Gender Performance"
Transgender and Nonbinary Individuals' Experiences of Gender Dysphoria in Bodily, Social, and Systemic Contexts During the COVID-19 Pandemic
Chloe Goldbach , Douglas Knutson , Satveer Kler , Dannie Klooster , Savannah LeForce , David Cole Milton
Conceptualizations of gender dysphoria have primarily centered only on bodily contexts, but researchers have recently identified the importance of also considering the roles of social and systemic contexts when conceptualizing experiences of gender dysphoria. The present study aimed to expand the understanding of transgender and nonbinary (TNB) individuals’ experiences of gender dysphoria within bodily, social, and systemic contexts, including experiences at two points during and prior to the COVID-19 pandemic. Data were collected from 364 TNB participants at two time points: before (May 2019 to January 2020) and during (May to December 2020) the COVID-19 pandemic. Consensual Qualitative Research-Modified (CQR-M) was used to analyze participant responses. Using CQR-M, 12 domains were identified that captured participant descriptions of factors that contribute to their experiences of gender dysphoria: (a) binary gender norms, (b) language, (c) systems and structural issues, (d) gender congruence, (e) safety, (f) community exclusion, (g) transition care, (h) close relationships, (i) multiple marginalization, (j) pandemic detriments, (k) pandemic benefits, and (l) buffers against experiencing gender dysphoria. The results of the present study suggest that social and systemic factors, in addition to bodily factors, play a significant role in the experiences of gender dysphoria reported by TNB individuals. These findings demonstrate a complex, far reaching, and relatively stable impact of social and systemic factors on the development and maintenance of gender dysphoria that needs to be integrated into the process of conceptualization, assessment, and treatment.
- Volume (Issue)
- June 30, 2023
- © 2023. The Authors. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0)
- Preferred Citation
- Goldbach, Chloe, Knutson, Douglas, Kler, Satveer, Klooster, Dannie, LeForce, Savannah, Milton, David Cole. 2023. ""I Owe No One Any Gender Performance": Transgender and Nonbinary Individuals' Experiences of Gender Dysphoria in Bodily, Social, and Systemic Contexts During the COVID-19 Pandemic." Bulletin of Applied Transgender Studies 2 (1-2): 27-46. https://doi.org/10.57814/cchg-zz61
At present, there are significant gaps in health research literature and clinical practice scholarship that describe the complexity of transgender and nonbinary (TNB) peoples’ experiences of gender dysphoria from their own perspectives (Austin, Holzworth, and Papciak 2022; Galupo and Pulice-Farrow 2020; Galupo, Pulice-Farrow, and Lindley 2020; Pulice-Farrow, Cusack, and Galupo 2020). So far, researchers and scholars have characterized TNB people as possessing an internal, personal incongruence between their sex assigned at birth and gender identity (Tompkins 2021). Gender dysphoria has been conceptualized as being a byproduct of that internal incongruence (Coleman et al. 2012). However, approaches to gender dysphoria that account for individual differences are limited (Goldbach and Knutson 2021). Research is needed to further expand conceptualizations of gender dysphoria from the perspectives of TNB people that form the current basis of health interventions and research, conceptualizations that include the ways in which social and systemic factors, in addition to internalized/bodily factors, may contribute to experiences of gender dysphoria. Furthermore, the potential effects of the COVID-19 pandemic on TNB people’s experiences of gender dysphoria are largely unknown in the current research literature.
From a systems perspective, TNB people experience a branching (Davy 2015; van Anders 2015) or difference between their gender identity and the sociocultural expectations held by others (e.g., family, friends, broader society, and so on) that are based on their sex assigned at birth (Tompkins 2021). In other words, a TNB person may be assigned male at birth and, therefore, may be expected to identify as a man, but may identify as a woman. The potential roles of social and systemic factors in contributing to many TNB people’s experiences of gender dysphoria have been largely absent in research literature and clinical practice considerations, but recent research has demonstrated that the branching between social and systemic expectations and internal identity can produce significant health concerns such as general distress and gender dysphoria (Austin, Holzworth, and Papciak 2022; Galupo and Pulice-Farrow 2020; Galupo, Pulice-Farrow, and Lindley 2020).
The Medical Model
Gender dysphoria has historically been conceptualized from a medical lens with a primary focus on dissatisfaction, distress, and incongruence associated with the physical body, and without an acknowledgement of the impact of sociocultural expectations (Pulice-Farrow, Cusack, and Galupo 2020). Many TNB people experience gender dysphoria, formally defined as distress that an individual experiences when their gender identity does not conform to sociocultural gender expectations based on their sex assigned at birth (Byne et al. 2018). Many, but not all, TNB people experience gender dysphoria.1 Of course, there is ample evidence that, for many TNB people, gender dysphoria is a significantly distressing, internal and body-centered experience, but other factors have been implicated as well (Austin, Holzworth, and Papciak 2022; Byne et al. 2018; Cooper et al. 2020).
Beyond Body Dysphoria
Transgender and nonbinary people report experiencing significantly high rates of prejudice, discrimination, and even violence (James et al. 2016). Researchers continue to document the extensive physical and mental health disparities experienced by TNB people (James et al. 2016; Su et al. 2016), and how these disparities can be connected to oppressive social environments using the minority stress model (Hendricks and Testa 2012; Testa et al. 2015). Furthermore, recent research indicates that distress related to the COVID-19 pandemic has further increased minority stress (Goldbach et al. In press; Kidd et al. 2021; van der Miesen, Raaijmakers, and van de Grift 2020). Many TNB people have encountered additional difficulties accessing gender-affirming care (van der Miesen, Raaijmakers, and van de Grift 2020) and increased psychological distress (Kidd et al. 2021) due to the COVID-19 pandemic. The ability to and methods of accessing support systems and chosen families has been significantly affected by the pandemic as result of social distancing, masking mandates, and stay-at-home orders (Goldbach et al. In press). Decreased access to social support and affirming care has led researchers to call on health providers, educational service providers, and LGBTQ+ organizations to find ways to directly provide support services to TNB people (Gato et al. 2021). Transgender and nonbinary people have also developed resilience strategies, such as maintaining forms of community connectedness, to cope with stressors induced by the pandemic (Abreu et al. 2021).
Social and systemic contexts, such as oppressive social environments and living during a global pandemic, can play a significant role in experiences of gender dysphoria (Galupo, Pulice-Farrow, and Lindley 2020), and gender dysphoria can be conceptualized as a proximal or internalized minority stressor (Lindley and Galupo 2020), highlighting a disconnect between clinical characterizations and actual experiences of TNB people. Unfortunately, focusing solely on current clinical characterizations of gender dysphoria produces assessment tools and treatment frameworks (Cohen-Ketteinis and van Goozen 1997; Deogracias 2007) that omit consideration of how factors external to the individual (i.e., living in a cisnormative world that is often oppressive and violent to TNB people) may also contribute to some TNB people’s experiences of gender dysphoria.
Despite the many connections between social and systemic environments, minority stressors, and the physical and mental well-being of TNB people, there is a paucity of research exploring ways oppressive social and systemic contexts may relate to gender dysphoria. The present study therefore investigates the multiple contexts (bodily, social, systemic) in which TNB individuals described their experiences of gender dysphoria using Consensual Qualitative Research-Modified (CQR-M) method (Hill and Knox 2021; Spangler, Liu, and Hill 2012) with an emphasis on associations between gender dysphoria and social and systemic contexts. Data were collected at two time points that happened to fall before onset (May 2019 to January 2020) and after onset (May 2020 to December 2020) of the COVID-19 pandemic. Building on past research about the stability of qualitative findings (Spangler, Liu, and Hill 2012), the researchers sought to investigate whether patterns in experiences of personal and environmental gender dysphoria persisted after the onset of the COVID-19 pandemic. The study included three main research questions: 1) How do TNB people qualitatively report their experiences of gender dysphoria? 2) How do social and systemic interactions, in addition to experiences of the physical body, affect experiences of gender dysphoria? and 3) How has the COVID-19 pandemic shown up, if at all, in reported experiences of gender dysphoria?
The data for this study were collected using a free response question about self-reported contributors to gender dysphoria that was included in a larger research project on experiences of gender dysphoria. CQR-M was used for this study because the method is sensitive to emotionally loaded data and because it provides a clear, reliable, consensus-based approach to coding brief qualitative data (Spangler, Liu, and Hill 2012). The study was approved by the human subjects committee at Southern Illinois University Carbondale and informed consent was obtained from all participants.
Data were collected at two different time points from two separate samples. Participants recruited prior to the onset of the pandemic (N = 138) were 18 years old or older (M = 28.12) and identified as transgender and/or nonbinary. Most pre-onset participants reported being white (81.2%, n = 116), nonbinary (51.4%, n = 71), assigned female at birth (73.9%, n =102), and college-educated (91.4%, n = 126). Post-onset participants (N = 226) were also 18 years old or older (M = 27.76) and identified as transgender and/or nonbinary. Most post-onset participants reported being white (84.5%, n = 191), nonbinary (61.9%, N =140), assigned female at birth (61.5%, n = 139), and college-educated (85.4%, n = 193). For more detailed demographic information, see Table 1.
Table 1. Demographic Information
|Study 1 (N=138)||Study 2 (N=219)|
|Sex Assigned at Birth|
|American Indian or Alaskan Native||1||0.70%||4||1.80%|
|Black or African American||3||2.20%||8||3.50%|
|Middle Eastern or North African American||2||1.40%||0||0.00%|
|Native Hawaiian or Other Pacific Islander||0||0.00%||0||0.00%|
|Some high school||2||1.40%||6||2.70%|
|High school diploma or GED||10||7.20%||27||11.90%|
|2-year college degree||11||8.00%||15||6.60%|
|4-year college degree||37||26.80%||59||26.10%|
|Less than $20,000||72||52.20%||115||50.90%|
|$20,000 to $34,999||25||18.10%||42||18.60%|
|$35,000 to $49,999||18||13.00%||16||7.10%|
|$50,000 to $74,999||11||8.00%||25||11.10%|
|$75,000 to $99,999||9||6.50%||7||3.10%|
|Greater than $100,000||3||2.20%||12||5.30%|
|Specific Transition Steps Taken|
|Came out as transgender to family||100||72.50%||170||75.20%|
|Came out as transgender to friends||134||97.10%||203||89.80%|
|Came out as transgender to coworkers and/or classmates||96||69.60%||143||63.30%|
|Adopted a name that is different from the one given at birth||99||71.70%||162||71.70%|
|Legally changed name to adopted name||56||40.60%||72||31.90%|
|Use different pronouns from the ones aligned with your sex assigned at birth||127||92.00%||207||91.60%|
|Legally changed gender marker on any documentation||44||31.90%||61||27.00%|
|Change in clothing/accessories/appearance to match gender identity in social situations||114||82.60%||191||84.50%|
|Change in clothing/accessories/appearance to match gender identity at work and/or school||99||71.70%||153||67.70%|
|Started hormone replacement therapy (HRT)||67||48.60%||111||49.10%|
|Undergone any gender-affirming surgical procedure (sex reassignment surgery, breast removal, breast augmentation, facial feminization surgery, etc.)||39||28.30%||34||15.00%|
Note: Percentages may add to more than 100% for several demographic variables because participants were allowed to select more than one option for several demographic variables.
Consistent with CQR-M, our judges met to generate and apply codes through a collaborative, consensus-based process (Hill and Knox 2021). The coding team sizes were variable at time one and two, but both teams worked to establish consensus regarding final domain labels and frequencies (Spangler, Liu, and Hill 2012). The primary investigator and an assistant professor in counseling psychology served on both coding teams. Other team members changed from time one to time two based on their availability and interest in participating in the rigorous, time-consuming coding process. The fact that the research teams for the pre-onset and post-onset coding projects were different indicated that the codes were well defined and stable across samples. The diversity of identities and experiences of team members further contributed to the accuracy of the domains that were formulated and applied. For details about the teams, see Table 2.
Table 2. Pre- and Post-Onset Research Team Characteristics
|Primary Investigator||white, lesbian transgender woman, doctoral student in counseling psychology||pre- and post-onset|
|Co-Primary Investigator||white, gay cisgender man, assistant professor in counseling psychology||pre- and post-onset|
|Coder||South Asian, queer nonbinary doctoral student in counseling psychology||pre-onset|
|Coder||white, queer transgender man, undergraduate psychology student||pre-onset|
|Coder||white, lesbian cisgender woman, undergraduate psychology student||pre-onset|
|Coder||white, queer cisgender woman doctoral student in counseling psychology||pre-onset|
|Coder||Native American and white, lesbian cisgender woman, master’s student in community counseling||post-onset|
|Coder||white, queer nonbinary doctoral student in counseling psychology||post-onset|
|Auditor||white, gay cisgender man, doctoral student in counseling psychology||pre- and post-onset|
Participants were recruited for two time points: before (May 2019 to January 2020) and during (May to December 2020) the COVID-19 pandemic. Data were collected the same way at both time points. Participants were recruited via social media and email lists obtained at LGBTQ+ events (e.g., Pride festivals). When participants clicked on the link, they were directed to a survey in Qualtrics. They were first presented with an informed consent form, followed by a series of quantitative measures, after which they were prompted to respond to an open-ended question. Upon survey completion, participants were redirected to separate survey that allowed them to select one of 12 transgender-focused non-profit organizations to which $1 would be donated.
The demographic questionnaire collected basic information that included age, race, sexual orientation, gender identity, and social and medical transition steps taken.
Free Response Question
Participants were asked to respond to the prompt, “Please specify any other important factors that contribute to your level of gender dysphoria.” The prompt was presented immediately after a new measure of gender dysphoria that asked participants to think about contributors to gender dysphoria related to social and systemic variables (Goldbach and Knutson 2021).
One criticism of qualitative methods is that researchers may project their own biases and expectations on the data they analyze (Hill and Knox 2012). CQR-M addresses the potential for bias by asking researchers to identify their biases and expectations, to bracket those expectations, and to hold fellow researchers accountable for bracketing their expectations as well (Spangler, Liu, and Hill 2012). The method also makes use of a consensus-building process that allows for in vivo inter-rater reliability checks, and it includes an auditor who checks the accuracy and consistency of the coding process (Hill and Knox 2021). Both pre- and post-onset teams identified possible biases that could impact their work as a team, and they agreed to work together to reduce the impact of those factors (Table 3).
Table 3. Biases and Expectations
|Team||Biases and Expectations|
|Pre-Onset||Noted that the process of coding and organizing words and experiences of others is inherently privileged. Identified that all team members are students and educators. Acknowledged that research has colonial origins and committed to try to decolonize the process to the furthest extent possible.|
|Post-Onset||Noted that experiences as LGBTQ+ people and privileged status as middle-class people associated with graduate programs might shape perspectives. Identified that cisgender members of team lack shared experience with participants around gender dysphoria and lack of access to transition-related care. Acknowledge a shared expectation that participants would report distressing experiences with health care professionals and additional gender dysphoria due to COVID-19 pandemic impact.|
CQR-M allowed each coding team to utilize a qualitative coding and analysis process that was clear, structured, and consensus-based (Hill and Knox 2021; Spangler, Liu, and Hill 2012). Each participant response was treated as a unit of data. Similar procedures were followed by both coding teams with the following exceptions: (a) the pre-onset team worked to consensus in person whereas the post-onset team met online and (b) the pre-onset team used Google Documents with comment bubbles to track codes whereas the post-onset team used Google Sheets.
Using CQR-M, 12 domains were identified in the final code list that captured participant descriptions of factors that contribute to their experiences of gender dysphoria. Each of the domains that follow are accompanied by brief examples. Please refer to Table 4 for a summary of domain definitions and frequencies.
Multiple marginalization is a domain that captures experiences of oppression related to marginalized identities other than gender. Participants’ experiences included, but were not limited to, fatphobia, racism, and ageism that intersect with gender identity. One participant, a multiracial transgender man, shared unique stressors they experience as someone who is transgender, a man, and a person of color: “Being a person of colour, people expect me to be a lot… larger. Taller. Stronger. Deeper voice. I pass as a guy, but I fear they don’t see me as a real man.”
The domain of safety captures participant experiences of feeling unsafe or threatened in various contexts. Participants spoke to threats/feelings of unsafety that have occurred and fears of a lack of safety in future situations. A white nonbinary trans masculine participant emphasized negotiating whether correcting someone who has invalidated them feels safe or worth it: “It is very stressful for me because it never seems worth correcting the person but then I have to subject myself to misgendering during the interaction and the guilt over not seizing the ’teaching moment’ to educate someone.”
Feeling excluded from gendered spaces was captured in the community exclusion domain. Participant experiences within this domain included being excluded from community spaces aligned with identities they hold (e.g., identity erasure in a trans community space, being excluded from gendered facilities). Experiences of feeling othered or feeling “out of place” were captured by one participant who identifies as a white transgender woman: “As an AMAB individual who is transitioning and presenting female, I find that the gender stereotypes expected of me due to bone structure and facial features cause me to feel out of place in spaces that are traditionally women-only spaces.”
Buffers against experiencing gender dysphoria captured instances where participants shared protective factors that reduce or eliminate experiences of gender dysphoria for them. Limiting contacted with unsupportive people, feeling congruence between gender identity and appearance, and having their gender affirmed by others were some of the protective factors shared by participants. One participant, a multiracial South Asian and white nonbinary person, highlights how medical transition has significantly reduced their gender dysphoria and increased their happiness and comfort in their own body: “Being post-transition (hormones and surgery) I rarely feel physical dysphoria with myself—I’m happy with and feel comfortable in my body, and I’m gender correctly by my family, friends and co-workers.”
The domain of language refers to written and/or verbal language or communication that contributes to invalidation, exclusion, or oppression of TNB people. Participants discussed gender dysphoria and distress associated with misgendering, deadnaming, and more. A white nonbinary participant shared multiple experiences of social invalidation that significantly contribute to their gender dysphoria: “Being perceived as a woman, being identified by strangers with ’that lady’, parents referring to me with she/her/daughter/etc., accessing healthcare that has very gendered ideas. I’m closeted except to friends so it’s not out of malice that I’m misgendered, but it gives me great social dysphoria.”
The binary gender norms domain refers to cultural norms that contribute to erasure of TNB people’s identities and experiences. One participant, who identifies as a Latinx, genderfluid nonbinary person, spoke to erasure they encounter in interpersonal interactions: “The fact that most people, both total strangers and my mother, cannot even conceptualize a nonbinary person, and therefore perceive me (and treat me) as my agab [assigned gender at birth] regardless of what I do to present differently.”
Systems and structural issues also contributed to participants self-reported experiences of gender dysphoria. This code refers to institutions (e.g., religion, politics, media, educational systems) that negatively impact the lives of TNB people. One participant, a white genderqueer person, shared how political debates over transgender rights contribute to their levels of distress and gender dysphoria: “The ’trans rights debate’ is extremely visible in my city and is often expressed through both pro- and anti-trans stickers and posters, which I see almost every day. It has more of an effect on my mental health than I like to admit.”
Participant descriptions of medical and social transition needs and interactions with systems (e.g., healthcare settings) that impact access to transition needs were captured in the transition care domain. Interactions with staff, providers, healthcare facilities, and health insurance companies were included in this domain. Participant experiences included lack of access to affirming care, financial barriers, and interacting with healthcare staff who had minimal knowledge on transgender issues. A Black nonbinary participant shared how negative interactions with healthcare staff contribute to their experiences of gender dysphoria: “I want to get top surgery, but have felt extreme levels of gender dysphoria from any medical professional I have seen because they 1) assume my sex assigned as birth equates my gender, 2) don’t ask for my pronouns, and 3) use conversational and medical language that does not correlate with my gender.”
Many participants shared experiences of body and social gender dysphoria, captured under the gender congruence domain. These experiences included gender dysphoria associated with the physical body (i.e., body dysphoria), invalidating social interactions, and gender dysphoria associated with voice/speaking (e.g., talking on the phone). One participant, a white transgender woman, expressed how feeling an incompatibility between their gender identity and physical body triggers gender dysphoria: “This body having developed reproductive morphology that is not compatible with what my brain expects to be plugged in to.”
Some participants shared how emotional distress in close relationships contributes to their gender dysphoria, which was captured under close relationships. Participants described experiences of invalidation and rejection from close friends, family, and/or significant others. A multiracial transgender man emphasized how living with an unsupportive family triggers experiences of gender dysphoria: “I am out to friends but am not out at home due to extreme transphobic parents. So while I do try to live as myself, I am unable to do much in my transition because of family situation.”
The final two domains, pandemic benefits and pandemic detriments, captured ways in which the pandemic reduced or increased the severity or frequency of experiences of gender dysphoria. One participant, an Asian nonbinary agender person, shared how lockdowns associated with the pandemic significantly reduced experiences of misgendering:
I was misgendered almost every day before lockdown and the ensuing dysphoria wore down my resilience and capacity. Being repeatedly misgendered in a short period of time was also exhausting and I over presented as masculine to try and compensate. Being in lockdown for COVID-19 has given me a lot of time and I’m more resilient to the occasional misgendering and I feel more comfortable dressing less masculine.
Several participants also shared how the pandemic created additional distress (e.g., healthcare access barriers, financial stress) that negatively impacted their gender transition and gender dysphoria. One participant, a white nonbinary person, expressed how moving home during pandemic lockdown prompted them to make difficult choices regarding their gender transition: “I am a college student living at home due to covid. This has forced me to put my transition on hold until it’s over. I cannot risk my living situation by coming out as trans to family.”
Throughout the qualitative responses, participants shared powerful examples of times that they feared for their safety and they highlighted difficulties accessing transition care. For the second sample, pandemic distress and benefits interacted with feelings of gender dysphoria in complex ways. The frequency with which participants referenced various domains fluctuated from the first to the second sample and were variable across the different domains. Some domains like binary gender norms and gender congruence were coded more frequently, indicating a greater focus among participants on those issues. Less frequently referenced domains like multiple marginalization were still included in the results because they were mentioned by multiple participants and they contribute to a more wholistic picture of participant experiences, but they should be approached with care and further examined in future studies. Throughout their stories and reflections, participants demonstrated determination and resilience as they discussed buffers against experiencing dysphoria. We provide further details for each code in Table 4, including definitions and frequencies.
Table 4. Domains, Subdomains, Definitions and Representative Quotes
|Domain||Frequency (Study 1, N=138)||Frequency (Study 2, N=219)|
|Multiple Marginalization||The participant discusses experiences of oppression related to minority identities other than gender such as but not limited to size, race, and age. These experiences are in addition to oppression related to the person’s gender identity.||n = 5, 3.62%||n = 6, 2.74%|
|Safety||The participant talks about feeling unsafe or threatened. This threat may be an actual or perceived danger in a present or future situation. Examples include, being faced with the decision about (a) whether or not to correct others about their misperceptions, (b) in what contexts and whether or not to come out, (c) in which spaces the participant is more likely to be safe or unsafe.||n = 12, 8.70%||n = 28, 12.79%|
|Community Exclusion||The participant mentions feeling excluded in gendered spaces, especially spaces for individuals with whom the participant identifies and/or feels a communal tie. Examples include: (a) being ignored or treated as if the participant is not in the given community, (b) being excluded from spaces such as men’s or women’s bathrooms (c), having their identity disqualified, erased, and/or shunned in cis and/or transgender communal spaces (e.g., facilities, online groups, social gatherings, etc.).||n = 8, 5.80%||n = 9, 4.11%|
|Buffers against Experiencing Gender Dysphoria||The participant lists protective factors that mitigate the severity of dysphoria. Participants may discuss, for example, limited contact with biased people, satisfaction with congruent appearance, and/or experiences of affirmation from others.||n = 20, 14.49%||n = 21, 9.59%|
|Language||The participant talks about verbal and/or written language that serves to exclude or oppress TNB people such as documents, deadnaming, honorifics, and use of wrong pronouns.||n = 24, 17.39%||n = 48, 21.92%|
|Binary Gender Norms||The participant describes patterns of behavior and/or interaction patterns that erase trans experience. These cultural norms may include pressure to pass as cisgender, feeling unable to come out or transition, pressure to conform to a binary gender identity, nonbinary invisibility, and general cisnormative pressure.||n = 38, 27.54%||n = 45, 20.55%|
|Systems and Structural Issues||The participant mentions insidious norms that permeate every level of society. This category involves non-inclusive worldviews that impact the systems in which TNB people live. Impacted institutions may be physical and/or ideological and extend to religion, politics, media, education, and other spheres.||n = 28, 20.29%||n = 42, 19.18%|
|Transition Care (from Healthcare)||The participant describes interactions with the medical system. These interactions may be with providers, facilities, or health insurance companies. Participants report lack of access (because of distance and other factors), lack of inclusive services, cost prohibitiveness, lack of knowledge among health care providers, and lack of insurance coverage. Includes access and lack of access to social (includes clothing, makeup, hair, etc.) and medical transition needs.||n = 8, 5.80%||n = 34, 15.53%|
|Gender Congruence||Participants talk about experiences of body dysphoria and/or dysphoria that results from direct interactions with strangers and/or acquaintances. This may include talking (on the phone and elsewhere), low self-confidence in interactions, and body dysphoria. Can include emotional and sexual intimacy.||n = 53, 38.41%||n = 88, 40.18%|
|Close Relationships||Participants mention distress encountered in close relationships (e.g., family, friends, significant others) such as rejection, invalidation, etc.||n = 12, 8.70%||n = 22, 10.05%|
|Pandemic Benefits||Any positive experience related to lockdown, quarantine, etc.||N/A||n = 4, 1.83%|
|Pandemic Detriments||Any negative experience related to lockdown, quarantine, etc.||N/A||n = 3, 1.37%|
|Other:||Any content that did not fit into existing categories, but that was indexed for later consideration.||n = 22, 15.94%||n = 8, 3.65%|
Note: AMAB = assigned male at birth; GNC = gender nonconforming; TNB = transgender and nonbinary; HRT = hormone replacement therapy
The present study sought to examine external and internal contributors to gender dysphoria among two non-clinical samples of transgender and nonbinary individuals recruited before and during the COVID-19 pandemic. The CQRM analysis generated 12 domains that add depth and context to research suggesting that gender dysphoria is impacted by social, systemic, and bodily factors. Findings also add to growing evidence that social and systemic aspects of gender dysphoria are important foci for future research. Although the domains do not fit perfectly into specific categories (binary gender norms can have social, systemic, and bodily implications), the discussion addresses each of these broader themes and extends the research discussed in the introduction.
Interactions with healthcare systems and transition-related care were contributors to gender dysphoria among both the pre-onset (5.80%, n = 8) and post-onset samples (15.53%, n = 34). These findings are consistent with past qualitative research concerning sources of gender dysphoria. Pulice-Farrow and colleagues (2020) have documented that gender incongruence related to specific body parts plays a significant role in terms of how individuals conceptualize their gender dysphoria. Furthermore, a recent systematic review and ethnographic meta-analysis concerning 20 existing qualitative studies on gender dysphoria detailed that bodily sources of gender dysphoria and gender incongruence were amongst some of the most salient sources of gender dysphoria participants mentioned (Cooper et al. 2020).
Other Sources of Dysphoria
However, the answer to our first research question was nuanced. Beyond bodily factors, participants also named binary gender norms and exclusionary language as social contributors to gender dysphoria. Binary gender norms included responses related to a pressure to pass as cisgender, pressure to conform to a cisgender identity, and nonbinary invisibility. This domain included 38 (27.54%) responses in the pre-onset sample and 45 responses (20.55%) in the post-onset sample. The use of exclusionary language included misgendering, deadnaming, and using incorrect pronouns. Such exclusionary language was another large social contributor for both the pre-onset (17.39%, n = 24) and post-onset (21.92%, n = 48) samples. Interestingly, participants mentioned that in addition to the social pressures of binary gender norms and exclusionary language, other aspects of social worldviews and institutions were sources of gender dysphoria as well. Both pre-onset (20.29%, n = 28) and post-onset (19.18%, n = 42) participants reported that institutions such as the media, education, politics, and religion advanced hostile, anti-transgender ideologies and worldviews that contributed to experiences of gender dysphoria. Similar societal and systemic contributors of gender dysphoria were found to be present among transgender individuals in several other studies (Galupo, Pulice-Farrow, and Lindley 2020; Goldbach and Knutson 2021).
Social and Systemic Interactions
The current study’s findings related to the societal and systemic contributors to gender dysphoria, our second research question, are important because they suggest that the medical model of gender dysphoria (e.g., the DSM-5-TR diagnostic model) may be a flawed or incomplete conceptualization of how transgender and nonbinary individuals understand and experience gender dysphoria. Conceptualizations of gender dysphoria need to be updated to take social and systemic contributors, such as exclusionary language and binary gender norms, into account (Goldbach and Knutson 2021). For example, healthcare providers and systems can contribute to transgender and nonbinary people’s experiences of gender dysphoria if measures are not taken to account for exclusionary language and binary gender norms, such as having forms that allow individuals to share their pronouns and provide gender options that are inclusive of nonbinary individuals. Transgender and nonbinary individuals also appear to increasingly reject the medicalization of their experiences. Johnson (2019) conducted 158 hours of participatory field-observations of a transgender community organization in the southeastern US and surveyed 33 transgender and nonbinary individuals to analyze communal perceptions of the medical model of gender dysphoria. Participants rejected a medical model of their experiences and instead advocated for a social model of gender-affirming care. Furthermore, the medical model of gender dysphoria is often rooted in binary expectations for gender transition (e.g., expectation that transgender people will medically transition from “one gender to the other”), which in and of itself can contribute to gender dysphoria due to reinforcement of binary gender norms. Such findings mirrored participant responses from the current study, with many participants naming social and societal aspects of their gender dysphoria.
Indicative of their resilience, participants from both the pre-onset (14.49%, n = 20) and post-onset (9.59%, n = 21) samples named buffers and protective factors against experiencing gender dysphoria. Such buffers included affirmation from others and limited contact with bigoted individuals. Researchers have extensively documented that transgender individuals may draw upon various sources of resilience when coping with minority stress, depression, and anxiety (Bariola et al. 2015; Bockting et al. 2013; Bockting et al. 2020; Hendricks and Testa 2012; Puckett et al. 2019; Singh, Hays, and Watson 2011; Testa et al. 2015; Veale et al. 2017). Furthermore, access to gender transition needs for social and/or medical transition has been documented to alleviate, reduce, or “treat” gender dysphoria (Coleman et al. 2012; Davy and Toze 2018). Although researchers have recently found evidence to support conceptualizing gender dysphoria as a proximal minority stressor (Lindley and Galupo 2020) and researchers have explored various sources of resilience that TNB people access in the face of gender minority stress (Bockting et al. 2013; Bockting et al. 2020; Hendricks and Testa 2012; Testa et al. 2015; Veale et al. 2017), unique resilience and protective factors for experiences of gender dysphoria appear to be unexamined in the research literature.
This gap in the research literature may be due to, in part, researchers only recently connecting gender dysphoria to social contexts (Galupo, Pulice-Farrow, and Lindley 2020; Goldbach and Knutson 2021), the absence of gender dysphoria in current models gender minority stress and resilience (Hendricks and Testa 2012; Testa et al. 2015), the medicalization of TNB bodies and experiences of gender dysphoria (Dewey and Gesbeck 2017; Johnson 2015; Johnson 2019), and a lack of consistency in how gender dysphoria is described across the research literature (e.g., personal phenomenological experience, specific mental health diagnosis; Davy and Toze 2018). Researchers have specifically called for increased focus on gender dysphoria in affirmative practice (Austin, Holzworth, and Papciak 2022), which could include a focus on resilience and protective factors. The present study’s findings help elucidate buffers and protective factors specifically related to dysphoria and may be useful for developing future interventions to decrease gender dysphoria.
COVID-19 and Gender Dysphoria
Because the post-onset sample was recruited during the COVID-19 pandemic, participants listed such as a relevant factor related to their gender dysphoria or lack thereof and provided us with answers to our third research question. Some participants mentioned the pandemic was detrimental to their health and a contributor to dysphoria (1.37%, n = 3), but some participants mentioned the pandemic was beneficial for avoiding dysphoria (1.83%, n = 4). Goldbach and colleagues (2021) recently recruited a sample of 220 LGBTQ+ individuals and found that higher levels of resilience weakened the effects of the pandemic on mental health outcomes. These findings may suggest that participants from the current study are utilizing their resilience to address any negative impacts of the pandemic related to gender dysphoria. Further research is necessary to confirm the contextual relationship between the pandemic and gender dysphoria.
Gender dysphoria also appeared to be context-dependent for many of the current study participants. For example, participants from both the pre-onset (8.70%, n = 12) and post-onset (12.79%, n = 28) reported that their sense of safety determined in which contexts to come out, correct people about their misperceptions, or even what spaces to go to. Community exclusion from both gendered spaces and LGBTQ+ spaces (5.80%, n = 8; 4.11%, n = 9) as well as rejection or mistreatment in close relationships (8.70%, n = 12; 10.05%, n = 22) were contributors to gender dysphoria in both samples. Some participants contextualized their understandings of their gender dysphoria related to the oppression that they faced from having multiple marginalized identities (3.62%, n = 5; 2.74%, n = 6). This is in line with existing models of identity development among transgender people of color (de Vries 2015).
Strengths and Limitations
The strengths of this study include the use of the established CQR-M method of coding, which involves blind consensus-building among raters while keeping pre-identified expectations and biases in check at all points of the coding process. The difference in coding schemes utilized before and after the global outbreak of the COVID-19 pandemic can also be interpreted as a strength, as the second round of data interpretation was not limited to a pre-existing code list. This qualitative nature of this study also allowed for an in-depth examination of the factors impacting gender dysphoria, with the unique lens of pre- and post-pandemic cross-examination.
Limitations for the present study include potential for bias due to participant and researcher bias. As the majority of participants identified as white in study 1 (81.2%) and study 2 (84.5%), future research should further investigate the voices of TNB populations of color. Additionally, the majority of participants self-identified as assigned female at birth (AFAB) in study 1 (73.9%) and study 2 (61.5%). Other studies have indicated a similar bias towards white and AFAB participants (Lindley, Bauerband, and Galupo 2021; Morris and Galupo 2019), and therefore future researchers should take care to not generalize findings to all TNB individuals. Additionally, all study data were interpreted by a coding team that was majority graduate-educated and majority white. All coders self-identified as queer, gay, or lesbian, and half as TNB which can simultaneously be regarded a strength and limitation to the current study. Lastly, while the coding scheme was developed based on the data, oversimplification of participant responses is a limitation to the CQR-M method used (Hill and Knox 2021; Spangler, Liu, and Hill 2012).
Although previous research findings have already emphasized the importance of bodily factors in the treatment of gender dysphoria, the present study reveals that gender dysphoria is also deeply connected with societal and systemic factors. Future research should further investigate the role of additional factors beyond bodily experiences in gender dysphoria, including daily interactions with oppressive social and societal systems. Future health interventions in the treatment of gender dysphoria should highlight an individual’s sociocultural context, including their geographic setting, access to affirming care, and interactions with social systems.
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In this manuscript, gender dysphoria in lower case will be used to refer the experience of distress, whereas Gender Dysphoria in title case will be used to refer to the diagnosis in the Diagnostic and Statistical Manual of Mental Disorders (DSM), 5th Edition, Text Revision (American Psychiatric Association 2022). ↩︎