Cross-cultural adaptation and evidence of validity of the Gender Minority Stress Measure

Adaptação transcultural e evidências de validade da Medida de Estresse e Resiliência de Minorias de Gênero

Adaptación transcultural y evidencias de validez de la Escala de Estrés en Minorías de Género

Abstract

This study adapted and validated the GMSR for the Brazilian transgender and gender non-conforming (TGNC) population. Based on Meyer’s minority stress model, the GMSR assesses stress and resilience across nine dimensions. The adaptation process included expert review and pilot testing. The Brazilian version (GMSR-Br) was tested with 301 TGNC participants, aged 18 to 60 years (M = 27.21; SD = 9.97). Psychometric analyses included confirmatory factor analysis and internal consistency, showing good model fit (CFI = 0.942, TLI = 0.967) and reliability (α > 0.6). RMSEA (0.136) suggested areas for improvement. Internalized transphobia predicted negative outcomes, while community connection and pride acted as protective factors. The GMSR-Br is a valid tool for assessing minority stress and resilience in Brazilian TGNC populations.

Keywords:
Gender Minority; Stress; Resilience; Transgender Population; Validation Study

Resumo

Este estudo adaptou e validou a GMSR para a população transgênero e não conforme ao gênero (TGNC) no Brasil. Baseada no modelo de estresse de minoria de Meyer, a escala avalia estresse e resiliência em nove dimensões. O processo incluiu revisão de especialistas e estudo-piloto. A versão brasileira (GMSR-Br) foi aplicada a 301 participantes TGNC, com idades entre 18 e 60 anos (M = 27,21; DP = 9,97). As análises psicométricas incluíram análise fatorial confirmatória e consistência interna, com bons índices de ajuste (CFI = 0,942; TLI = 0,967) e confiabilidade (α > 0,6). O RMSEA (0,136) indicou pontos a melhorar. A transfobia internalizada foi preditora de desfechos negativos, enquanto conexão comunitária e orgulho mostraram-se fatores protetivos. A GMSR-Br mostrou-se válida para avaliar estresse e resiliência em minorias de gênero no Brasil.

Palavras-chave:
Minoria de Gênero; Estresse; Resiliência; População Transgênero; Estudo de Validação

Resumen

Este estudio adaptó y validó la GMSR para la población transgénero y de género no conforme (TGNC) en Brasil. Basada en el modelo de estrés de minorías de Meyer, la escala evalúa el estrés y la resiliencia en nueve dimensiones. El proceso incluyó revisión de expertos y prueba piloto. La versión brasileña (GMSR-Br) se aplicó a 301 participantes TGNC, con edades entre 18 y 60 años (M = 27,21; DE = 9,97). Los análisis psicométricos incluyeron análisis factorial confirmatorio y consistencia interna, con buenos índices de ajuste (CFI = 0,942; TLI = 0,967) y fiabilidad (α > 0.6). El RMSEA (0,136) indicó aspectos a mejorar. La transfobia internalizada predijo resultados negativos, mientras que la conexión comunitaria y el orgullo fueron factores protectores. La GMSR-Br demostró ser una herramienta válida para evaluar el estrés y la resiliencia en minorías de género en Brasil.

Palabras clave:
Minoría de Género; Estrés; Resiliencia; Población Transgénero; Estudio de Validación

Introduction

The stress experienced by gender minorities can result from a combination of individual, social and structural factors, which often include discrimination, violence, marginalization and social exclusion (Meyer, 2003; Scheim et al., 2022). People who identify outside traditional gender norms, such as transgender people, are often associated with experiences of prejudice and stigma in both public and private contexts, which can have a profound impact on their mental and emotional health (Hughto et al., 2020; Scandurra et al., 2019).

This stress is often chronic and can manifest itself in high levels of anxiety, depression and other psychological disorders (Chinazzo et al., 2021). In this sense, the minority stress model has proven to be an important and valid tool in explaining mental health disparities in minority populations, especially when applied to lesbian, gay and bisexual individuals, according to the model proposed by Meyer (2003).

Recent studies focused on transgender and non-binary people have revealed that this model is useful for understanding the specific stressors of these minorities, associated with resilience factors and inequalities observed in mental health (Testa et al., 2015). With regard to the aspect related to resilience, such as the ability to face and overcome adversity through coping strategies, social support and strengthening of gender identity (Meyer, 2015), it reflects notoriously on trans people. Resilience, in this context, not only minimizes the negative effects of stress, but also promotes the well-being, empowerment and quality of life of this population.

However, there is a shortage of instruments capable of measuring the experience of trans people in the face of their gender discovery and transition. Thus, in Brazil, there is a pressing need for instruments that accurately capture the stress and resilience of gender minorities, given the context of discrimination and social exclusion faced by this population.

The Gender Minority Stress and Resilience Measure (GMSR), originally developed in a North American context by Testa et al. (2015), is a psychometric instrument designed to assess the levels and factors of stress (external and internal) and the resilience factors of gender minorities, specifically transgender, transvestite and non-binary people. The GMSR was developed and instrumentally validated with the participation of 844 trans and non-binary people from the United States and measures nine main dimensions: gender-related discrimination, gender-related rejection, gender-related victimization, non-affirmation of gender identity, internalized transphobia, negative expectations for future events, non-disclosure, community connection and pride. These nine dimensions are divided into three factors: distal stress, proximal stress, and resilience, all together have an impact on aspects related to physical and psychological health. It is understood as a conceptualization of the dimensions according to the instrument (Testa et al., 2015), e a Figure 1 shows the general layout of the instrument.

Figure 1
Gender minority stress model as proposed by Testa et al. (2015). Dashed lines indicating inverse relationships.

Gender-related discrimination, gender-related rejection, and gender-related victimization represent distal stressors, reflecting experiences externas de hostilidade ou adversidade enfrentadas por pessoas trans e não-binárias. Gender-related discrimination encompasses experiences of prejudice or unequal treatment due to gender identity, including social and institutional barriers; gender-related rejection involves social or interpersonal exclusion, such as being ostracized by family, friends, or social groups; and gender-related victimization captures instances of physical, verbal, or sexual violence directly related to one’s gender identity. These factors illustrate the external challenges that can contribute to minority stress and negatively impact mental health.

Non-affirmation of gender identity, internalized transphobia, negative expectations for future events, and non-disclosure reflect proximal stressors, representing internalized or anticipated experiences of stress. Non-affirmation refers to the lack of recognition or validation of one’s gender identity by others, such as the incorrect use of pronouns or names; internalized transphobia captures the internalization of social stigmas about trans identities, leading to feelings of shame or self-deprecation; negative expectations for future events involve concerns or fears regarding ongoing discrimination or barriers to opportunities; and non-disclosure represents the choice or necessity to conceal one’s gender identity to avoid negative repercussions. Together, these factors describe how external stressors are internalized and anticipated, influencing psychological vulnerability.

Community connection and pride correspond to resilience-related factors, reflecting processes that help individuals cope with and adapt to minority stress. Community connection measures the sense of belonging and support within the trans and non-binary community, including positive social and emotional ties; and pride captures feelings of acceptance and affirmation of one’s gender identity, functioning as a protective factor against the adverse effects of discrimination and internalized stigma. These factors highlight the multidimensional nature of resilience as a process influenced by both social and intrapersonal resources.

Although the GMSR includes factors that contribute to resilience, such as pride and community connectedness, it is important to recognize that resilience is a dynamic process rather than a single construct. The instrument does not measure resilience in its entirety but captures specific factors that may facilitate or constitute part of the resilience process in individuals or populations. Other aspects, including socioeconomic conditions, access to health care, employment, education, supportive adults throughout development, and emotional regulation skills, are also critical to the development of resilience.

This questionnaire can be used in clinical and research contexts, providing a more detailed understanding of the stress and resilience experiences faced by gender minority individuals (Hidalgo et al., 2019). A Turkish version of the instrument was also carried out, with a smaller sample of 48 trans individuals who were waiting in line for the gender transition procedure (Şahin et al., 2023). Even with few participants, the instrument was considered suitable and validated for the Turkish population, and was considered by the authors to be a useful instrument for researchers and a valid screening tool in counseling interviews with this population.

The scale was also translated and cross-culturally adapted in Italy in a study conducted by Scandurra et al. (2020). The methodology used by the authors included six phases, starting with translation, followed by evaluation by a focus group of trans people, reverse translation and evaluation by three expert judges. The instrument was then validated with a sample of 203 transgender people using an online application. Furthermore, the Italian version of the GMSR proved to be an adequate and good tool for clinical and scientific use, allowing the exploration of internal and external stress factors and resilience and the repercussions of these factors on the mental health of gender dissident people (Scandurra et al., 2020).

A study evaluated the application and responses of the GMSR in 258 young transgender Americans aged between 12 and 17 (Hidalgo et al., 2019). In the study, some items of the instrument were adapted to suit the experiences of the target audience, and the order of the sections was changed. However, it was concluded that the instrument, despite being designed for the adult population, was a suitable tool for measuring stress and resilience in adolescents as well. Thus, the GMSR can be recognized for its ability to capture the complexity of the experiences of gender minorities, offering a robust tool for investigating mental and physical health disparities within this population.

With its application, researchers and practitioners can gain valuable insights into how minority stress affects these communities, while identifying resilience factors that can be strengthened to promote well-being (Testa et al., 2015). Given the above, this study aims to assess the internal structure of the GMSR-Br and the relationships of its scores with psychological distress and self-esteem, to evaluate the hypothesized validity and reliability evidences.

Method

Design and participants

This study was a psychometric investigation about the validity and reliability evidences of the GMSR measure in a sample of Brazilian transgender and gender non-conforming (TGNC) people. This way, 301 Brazilian TGNC people were recruited by convenience to participate in the study. Participants’ ages varied from 18 to 60 years (M = 27.21; SD = 9.97), sample’s demographics are presented in Table 1. There were participants from each of the five Brazilian regions and races commonly identified in the country, which increases sample representativeness. Most of the participants attained high-school or undergraduate degree educational level, and an important percentage did not have any monthly income.

Table 1
Sample’s demographic characteristics

Characteristics	%	n
Brazilian region
North	5.3	16
Northeast	16.6	50
Midwest	10.9	33
Southeast	40.5	122
South	26.6	80
Race
White	51.2	154
Black	12.0	36
Latino/Hispanic	29.6	89
Asian	5.6	17
Indigenous	1.7	5
Education
Elementary school	10.3	31
High school	52.0	156
Undergraduate degree	30.7	92
Graduate degree	7.0	21
Monthly income a
No income	33.9	102
US$ 227,59	22.6	68
US$ 455,18 - 682,77	24.6	74
US$ 910,36 - 1.365,54	10.3	31
≥ US$ 1.365,54	8.6	26

• Note.^a salary values were converted from BRL to US$ based on a minimum wage of R$ 1.320.00 and an exchange rate of R$ 5.80/ US$ 1.00 (until December 2024).

Participants’ ages varied from 18 to 60 years (M = 27.21; SD = 9.97). Sample’s sex/gender characteristics are shown in Table 2. There was an equal distribution of trans woman and men in the sample. Regarding sexual orientation, the majority identified themselves as heterosexual or bisexual.

Table 2
Sample’s sexual/gender characteristics

Characteristics	%	n
Identification
Trans woman	46.0	131
Trans men	47.4	145
Cross-dresser	6.6	19
Sexual orientation
Heterosexual	31.8	95
Gay	13.7	41
Lesbian	13.4	40
Bisexual	23.4	70
Pansexual	13.0	39
Asexual	4.3	13
Demisexual	0.3	1

Instruments

Gender Minority Stress and Resilience Measure (GSMR)

Originally published and adapted for the American population by Testa et al. (2015), this measure was developed based on Meyer’s minority stress model and adjusted to reflect the experiences of transgender and non-binary people. The GMSR is the first and only psychometrically valid self-report measure known to assess stress and resilience of gender minorities, and is comprised of 3 factors and 9 subscales. The factors assessed are proximal stress, distal stress, and resilience, distributed across the following subscales: discrimination (α = 0.61), rejection (α = 0.71), and victimization (α = 0.77), which are scored dichotomously as yes or no and, the factors non-affirmation (α = 0.93), internalized transphobia (α = 0.91), pride (α = 0.90), negative expectations for future events (α = 0.89), non-disclosure (α = 0.80), and community connection (α = 0.86) are answered using a 5-point Likert scale, with 1 being strongly disagree and 5 being strongly agree. The psychometric properties of the instrument show it to be a reliable and valid tool for measuring stress and resilience factors in transgender and gender non-conforming populations, with correlations between the subscales below 0.60, suggesting good discrimination between the factors, and confirmatory factor analysis indicating good fit to the model (χ² (1559) = 5922.04, p < 0.001; CFI = 0.93; RMSEA = 0.058).

Depression, Anxiety, and Stress Scale (DASS-21)

The DASS-21 (Lovibond & Lovibond, 2004) assessed psychological distress via 21 items distributed across three factors (depression, anxiety, stress) and a second-order factor. In the Brazilian version (Vignola & Tucci, 2014), α = 0.92 (depression), α = 0.90 (stress) and α = 0.86 (anxiety). Responses used a 4-point Likert scale. CFA using Robust Maximum Likelihood showed adequate fit: χ² (186) = 838.194, RMSEA = .108, CFI = .924, TLI = .915. The general score was reliable (ω = .961), with higher scores indicating greater distress.

Rosenberg Self-Esteem Scale (RSE)

The RSE (Rosenberg, 1989) measured global self-esteem with 10 items on a single factor, rated on a 4-point Likert scale. The Brazilian version (Hutz & Zanon, 2011) presented α = 0.90 and evidence of construct validity. Fit indices (MLR): χ²(35) = 385.125, RMSEA = .182, CFI = .884, TLI = .851. Reliability was strong (ω = .958). Scores were summed, with higher scores reflecting greater self-esteem.

Procedures

This study is part of a broader research project, the doctoral thesis of one of the authors, which aimed to investigate the risk and protective factors associated with the mental health of Brazilian transgender people. Given the scarcity of empirical instruments, the need arose to adapt and validate the scale to the reality of Brazil in order to contribute as a tool for future research.

Cross-Cultural Adaptation of the GMSR

For the cross-cultural adaptation of the GMSR into Brazilian Portuguese, one of the authors of the instrument was initially contacted and, after his acceptance to translate the instrument, the following steps were followed: the adaptation involved four independent translations (two by psychologists, two by laypersons), synthesis and expert review, testing with the target population, back-translation by a native speaker, feedback from the original author, and finalization of the scale. Data were then collected for validity testing.

Independent Translation and Synthesis

First, four independent translators independently translated the GMSR. One of the researchers then synthesized the translations to create a draft version of the translation. This version was then discussed by a committee consisting of one of the researchers and three external consultants, all trained in psychology, one of whom was a researcher in the field of gender studies and one of whom was a trans person, in order to assess the adequacy of the synthesis of the translations.

Testing Phase and Content Validity Index (CVI)

Thirty-one participants were invited via social media to participate in the testing phase of the draft version of the instrument. They answered a questionnaire made available on the Microsoft Forms platform, which contained the 58 items of the GMSR followed by the following questions: 1) Is the language clear enough? 2) Is the language appropriate for trans people? 3) Did you understand the question? and 4) This item needs to be modified (yes/no, with a blank space for participants to write their suggestions). The content validity index (CVI) of each item was calculated after this data collection. All items were considered adequate, with CVIs ranging from 0.910 to 0.916. Some minor suggestions made by participants were incorporated to increase the clarity, appropriateness and comprehensibility of the instrument.

Back-Translation and Author Feedback

After this phase of the research, a version of the translation containing the participants’ feedback was sent for back-translation by a native English speaker with experience in English grammar. This back-translation was then sent to one of the authors of the original GMSR for evaluation. Based on their feedback, part of one of the items (TI Subscale, item 6) was modified to maintain the original English meaning and adapted to the context of the question, and a final version of the Brazilian Portuguese GMSR-Br was produced.

Final Version and Data Collection

This final version was made available together with the sociodemographic questionnaire and other instruments related to the main research project in an online questionnaire on the Microsoft Forms platform. The content was publicized on social media, namely on Instagram, using paid traffic sources to reach more participants. We explicitly stated that only adults aged 18 or over could participate. Advertisements on social media were made on profiles followed by the LGBT+ population and indicated the exclusive participation of people who identified as transgender or non-binary. When accessing the questionnaire content and after reading the TCLE, participants who agreed to take part in the study were sent directly to the questionnaire. Data collection was carried out between September 2023 and August 2024.

Data Analysis

The GSMR measure psychometric properties’ assessment was based on the Standards framework (American Educational Research Association et al., 2014). This way, validity evidence based on the internal structure were evaluated through confirmatory factor analysis (CFA). The Robust Weighted Least Squares (WLSMVS) estimator was used (DiStefano & Morgan, 2014; Li, 2016) to compute a unidimensional baseline model and a theorized nine-factor model (Testa et al., 2015). Cases with missing values were listwise deleted (6 participants excluded), resulting in the sample of 301 TGNC people.

Model fit was considered good when c²/df < 5.00, RMSEA (Root Mean Square Error of Approximation) values < 0.08, CFI (Confirmatory Fit Index) and TLI (Tucker-Lewis Index) > 0.90 (Brown, 2015; Byrne, 2016; Hoyle, 1995; McDonald & Ho, 2002). Factor loadings were considered good when its standardized values were l ≥ 0,40. This cutoff value was adopted based on recommendations in the literature, which suggest different thresholds for factor retention (Costello & Osborne, 2005; Hair et al., 2019). Factor scores were considered reliable when Omega (w) and Alfa (a) were > 0,60 (Cronbach, 1951; Raykov, 1997).

Convergent validity evidence was defined as the strength of items’ convergence on their respective factors. Average Variance Extracted (AVE) was used to measure such a strength, considering AVE ≥ 0.5 as suggesting good convergent evidence (Fornell & Larcker, 1981; Marôco, 2021). Discriminant validity evidence was defined as the degree factors are independent of each other. Heterotrait-Monotrait (HTMT) ratio of correlations was analyzed, and bivariate correlations > 0.90 indicates a lack of discriminant validity (Henseler et al., 2015).

Validity evidence based on relationships with other variables were assessed through a set of linear regression models where the nine GSMR factor were used as predictors and four outcomes were used in four different models: psychological distress (DASS-21) and self-esteem (RSE). Model fit was considered good when the F statistic was significant at p < .05, adjusted R² values were maximized, and RMSE (Root Mean Square Error) were minimized. The impact of the predictors on the outcomes was considered significant when the t statistic was significant (p < .05). The magnitude of the effect was measured by the standardized coefficient (b). All analysis were performed in the Jamovi v. 2.6.17 statistical software (The Jamovi Project, 2024), which implements the R Lavaan package (Rosseel, 2012).

Results

Validity evidence based on internal structure

The assessment of GMSR’s validity evidence based on internal structure was conducted in three steps: (a) general model fit; (b) factor loadings, item characteristics (M, SD), and score’s internal consistency; (c) convergent and discriminant evidence in the factor structure. Findings are presented in the following.

Model fit

Model fit results are presented in Table 3. A one-factor model was tested as a baseline comparison for the nine-factor theorized solution. Second-order models (three and two higher-order factors) were tested, but failed to converge as the matrix was singular. As may be seen in the table, the nine-factor model substantially improves the fit over the one-factor solution. However, RMSEA values in the nine-factor model remained off the proper threshold (< .080).

Table 3
Model fit indices for one and nine factor solutions

Model	c2	c2/df	RMSEA	CFI	TLI
			[LB; UB]
one-factor	46637*	29,24	.357	.713	.776
			[.354; .359]
nine-factors	6211*	3,98	.136	.942	.967
			[.133; .140]

• Note. The model fit was considered good when the c ² / df ratio was < 5, the CFI (Confirmatory Fit Index) and TLI (Tucker-Lewis Index) was ≥ .90, and the RMSEA (Root Mean Square Error of Approximation) was < 0.008. LB = Lower-Bound, UB = Upper-Bound. * p ≤ 0.001

Modification indices and factor loading were inspected to identify ways of improving the nine-factor model fit. Modification indices pointed out a residual correlation between two items (CC_4 ~~ CC_5) and four cross-loadings with one item CC_5. After excluding this item, RMSEA values did not reduce much (DRMSEA = -.012). Five items’ factor loadings were weak (l < .040), but removing these items did not improve substantially the RMSEA values (DRMSEA = -.009).

The best fit regarding RMSEA values was obtained by removing the six items mentioned above, RMSEA = .127 [.123; .131], however this remained an unsatisfactory result. The unsatisfactory RMSEA value may be due to an ambiguous factor structure, an explanation supported by several cross-loadings pointed by the modification indices.

Nonetheless, as this study sample was relatively small compared to the model complexity, definitive judgements about it should be suspended. What can be asserted is that the nine-factor model, on an overall account of all fit indices, presented a good fit.

Factor loadings, item characteristics, and internal consistency

Item’s characteristics (M, SD) and factor loadings are shown in Table 4. Items from the discrimination (D), rejection (R), and victimization (V) factors were binary and their means represented the proportion of “yes” responses. Factor loadings for items D_1, D_3, R_1, and R_3 were below the threshold of adequacy (l > 0.40). The factor loadings of other items, however, were quite high, near 1.

Table 4
Item means (M), standard deviations (SD), and factor loadings (l)

Item	M	SD	l		Item	M	SD	l
D_1	0.44	0.50	0.234**		IT_7	2.11	1.16	0.886***
D_2	0.78	0.42	0.967***		IT_8	2.53	1.23	0.852***
D_3	0.38	0.49	0.201*		P_1	3.07	1.18	0.740***
D_4	0.37	0.48	0.602***		P_2	3.30	1.27	0.891***
D_5	0.64	0.48	0.909***		P_3	3.21	1.31	0.868***
R_1	0.78	0.41	0.292**		P_4	3.04	1.23	0.846***
R_2	0.65	0.48	0.600***		P_5	3.00	1.20	0.885***
R_3	0.40	0.49	0.189*		P_6	3.13	1.24	0.817***
R_4	0.69	0.46	0.866***		P_7	2.95	1.30	0.803***
R_5	0.62	0.49	0.953***		P_8	3.32	1.27	0.855***
R_6	0.71	0.45	0.564***		NE_1	3.74	1.30	0.875***
V_1	0.84	0.37	0.821***		NE_2	3.93	1.20	0.881***
V_2	0.64	0.48	0.824***		NE_3	3.65	1.53	0.972***
V_3	0.25	0.44	0.754***		NE_4	3.74	1.56	0.977***
V_4	0.59	0.49	1.027***		NE_5	3.94	1.37	0.972***
V_5	0.45	0.50	0.879***		NE_6	3.88	1.40	0.975***
V_6	0.30	0.46	0.632***		NE_7	4.09	1.30	0.936***
NA_1	4.15	1.19	0.887***		NE_8	3.67	1.42	0.898***
NA_2	4.10	1.23	0.904***		NE_9	3.83	1.34	0.914***
NA_3	3.97	1.35	0.888***		ND_1	3.62	1.41	0.869***
NA_4	4.03	1.26	0.900***		ND_2	3.59	1.37	0.915***
NA_5	4.01	1.24	0.931***		ND_3	3.77	1.38	0.933***
NA_6	4.17	1.17	0.930***		ND_4	3.80	1.37	0.921***
IT_1	2.26	1.19	0.874***		ND_5	3.66	1.43	0.931***
IT_2	2.03	1.16	0.870***		CC_1	3.26	1.19	0.856***
IT_3	2.30	1.24	0.965***		CC_2	3.47	1.13	0.874***
IT_4	2.20	1.20	0.927***		CC_3	3.86	1.01	0.591***
IT_5	3.00	1.20	0.676***		CC_4	3.05	1.16	0.584***
IT_6	3.44	1.02	0.487***		CC_5	2.81	1.28	0.499***

• Note. D = discrimination, R = rejection, V = victimization, NA = non-affirmation, IT = internalized transphobia, P = pride, NE = negative expectations, ND = non-disclosure, CC = community connectedness. Items CC_4 and CC_5 were reverse scored. *p < .05, **p < .01, ***p < .001

Factor scores descriptive statistics and internal consistency indices are presented in Table 5. It is possible to observe in the table that all scores present adequate internal consistency reliability (> .60) by both Alpha (a) and Omega (w) indices.

Table 5
Factor scores descriptive statistics (Min, Q¹, M, SD, Q³, Max) and internal consistency Alfa (a) and Omega (w) indices

Score	Min	Q 1	M (SD)	Q 3	Max	a	w
Discrimination	0	2	2.60 (1.51)	4	5	.789	.599
Rejection	0	3	3.86 (1.74)	5	6	.816	.655
Victimization	0	1	3.07 (1.95)	5	6	.928	.845
Non-affirmation	6	19	24.42 (6.54)	30	30	.964	.944
Internalized transphobia	8	14	19.87 (7.22)	26	32	.933	.924
Pride	8	20	25.02 (7.88)	30	40	.929	.936
Negative expectations	9	28	34.46 (11.09)	45	45	.981	.976
Non-disclosure	5	15	18.46 (6.15)	25	25	.958	.943
Community connectedness	5	15	16.44 (3.71)	18	25	.680	.788

• Note. Min = minimum score, Q ₁ = 25^th percentile, M = mean, SD = standard-deviation, Q ³ = 75^th percentile, Max = maximum score, a = ordinal alpha, w = omega 1. Scores were calculated by the sum.

Convergent and discriminant validity evidence

Convergent and discriminant analysis’ results are shown in Table 6. Factors discrimination (D), rejection (R), and community connectedness (CC) showed a lack of convergent validity evidence, but the values are relatively close to the threshold. This is due to items that showed weak factor loadings on these factors. According to the HTMT correlations, all the factors showed discriminant validity evidence (< .90).

Table 6
Average Variance Extracted (AVE) values and Heterotrait-Monotrait (HTMT) ratio of correlations

Factor	D	R	V	NA	IT	P	NE	ND	CC
D	.444
R	.843	.410
V	.565	.807	.691
NA	.300	.320	.307	.823
IT	.241	.134	.109	.120	.690
P	.163	.142	.116	.158	.405	.704
NE	.317	.319	.435	.801	.114	.190	.873
ND	.303	.300	.403	.594	.097	.214	.690	.835
CC	.370	.320	.294	.278	.264	.375	.297	.277	.487

• Note. D = discrimination, R = rejection, V = victimization, NA = non-affirmation, IT = internalized transphobia, P = pride, NE = negative expectations, ND = non-disclosure, CC = community connectedness. AVE values (diagonal) > .50 suggests convergent validity. HTMT correlations < .90 suggest discriminant validity.

Validity evidence based on relationships with other variables

The GSMR factors are expected to predict outcomes like psychological distress and self-esteem. Therefore, linear models were adjusted to assess this expectancy. The linear regression models’ fit using the nine GSMR factors as predictors and the different outcome variables are presented in Table 7. All models showed a good fit and they were presented in their explanatory power order, indexed by the coefficient of determination (R²).

Table 7
Linear Models’ Fit with the GSMR nine factors as Predictors

Outcome	M (SD)	F	p	R2 adjusted	RMSE
Self-Esteem	28.63 (8.24)	17.714	<.001	.334	6.72
Distress	27.27 (21.93)	16.384	<.001	.316	18.14

• Note. M = Mean, SD = Standard Deviation, R² _adjusted = Adjusted Coefficient of Determination, RMSE = Root Mean Squared Error.

Models’ standardized coefficients are presented in Table 8. The results can be interpreted for each predictor as the following:

Table 8
Linear Models’ Standardized Coefficients (β) of the GSMR nine factors on Different Outcomes

Predictors	bself-esteem	bdistress
Discrimination	-.148*	.176**
Rejection	-.052	-.003
Victimization	.188**	-.143*
Non-affirmation	-.166*	.213**
Internalized transphobia	-.392***	.281***
Pride	.148**	-.101
Negative expectations	-.150*	.293***
Non-disclosure	.282***	-.266***
Community connectedness	.124*	-.175***

• Note. *p < .05, **p < .01, ***p < .001

• Discrimination: negatively affects self-esteem, positively impacts distress. As expected, more discrimination experiences lead to greater psychological vulnerability and distress.

• Rejection: does not have a statistically significant impact on any outcome assessed. Contrary to the expectations, rejection was a factor of lower importance for psychological positive and negative outcomes when in the presence of other stress and resilience variables.

• Victimization: positively affects self-esteem, negatively impacts distress. Contrary to what was expected, victimization experiences are associated to improved self-esteem, as well as diminished distress.

• Non-affirmation: negatively impacts self-esteem, positively affects distress. As expected, more non-affirmation experiences lead to greater distress and psychological vulnerability.

• Internalized transphobia: negatively impacts self-esteem; positively impacts distress. This predictor showed the greatest overall magnitude on the outcomes. More internalized transphobia leads to greater distress and psychological vulnerability.

• Pride: positively impacts self-esteem, as expected for a resilience factor. Its effects on distress were not statistically significant.

• Negative expectations: negatively impact self-esteem, while positively affects distress, as expected.

• Non-disclosure: positively affects self-esteem; negatively impacts distress. Contrary to what’s expected for a stress factor, more non-disclosure experiences lead to improved well-being and psychological health, as well as diminished distress.

• Community connectedness: positively affects self-esteem and negatively impacts distress, as expected.

Discussion

The present study aimed to adapt and validate the Gender Minority Stress and Resilience Measure (GMSR-Br) for the Brazilian population, investigating its psychometric properties and the relationships between its factors and indicators of psychological distress and self-esteem among transgender and non-binary individuals. The findings of this study underscore the overall adequacy of the GMSR’s adaptation for the Brazilian transgender and gender non-conforming (TGNC) population, with mixed results in model fit and variable impact. The nine-factor model demonstrated good fit across several indices (CFI = .942, TLI = .967), aligning with previous validations in other contexts (Şahin et al., 2023; Scandurra et al., 2020). However, the RMSEA value (.136) indicated room for improvement, potentially due to sample size constraints, as the complexity of the model demands larger and more representative samples to reduce error variability and improve fit indices (Brown, 2015; Li, 2016).

Regression analyses highlighted the nuanced relationships between stressors, resilience factors, and psychological outcomes. Notably, internalized transphobia emerged as a significant predictor across all outcomes, amplifying psychological distress (β = .281, p < .001) and negatively impacting self-esteem (β = -.392, p < .001). This aligns with the minority stress model, where internalized stigma is a robust determinant of mental health disparities (Meyer, 2003; Testa et al., 2015). These findings highlight the urgency of targeted interventions addressing internalized transphobia within TGNC populations.

Interestingly, community connectedness and non-disclosure demonstrated unexpected trends. Community connectedness was positively associated with self-esteem (β = .124, p < .05) and negatively correlated with distress (β = -.175, p < .001), corroborating resilience literature that underscores the protective role of social support (Meyer, 2015). It should be emphasized that the GMSR assesses factors that contribute to resilience rather than resilience as a whole process. Pride and community connectedness emerged as relevant predictors for positive psychological outcomes, yet they represent only part of the broader resilience process. Resilience is shaped by multiple interconnected elements, including social and economic resources, access to health care and education, supportive relationships, and emotional regulation skills. Therefore, while these factors provide good data, they should be considered within the broader context of resilience development among TGNC individuals.

Conversely, non-disclosure, traditionally viewed as a stressor, positively impacted self-esteem (β = .282, p < .001), suggesting a nuanced role potentially linked to cultural and contextual factors within the Brazilian landscape. For instance, concealment may sometimes act as a protective mechanism in environments with heightened discrimination, aligning with findings in high-stigma settings (Hidalgo et al., 2019).

The relationship between victimization and improved self-esteem also deviates from traditional assumptions. This phenomenon possible may reflect a resilience-building process where overcoming adversity fosters a sense of pride and agency (Scandurra et al., 2020; Testa et al., 2015). Discrimination negatively affected self-esteem and positively impacted distress, in line with minority stress research emphasizing the psychological harm of social rejection. Rejection, despite not showing significant associations in the present models, may interact with other stress factors to influence mental health outcomes in larger or different samples. Non-affirmation experiences were associated with increased distress and decreased self-esteem, reinforcing the importance of social validation. Pride, as a resilience factor, positively contributed to self-esteem and well-being, whereas negative expectations for future events were related to poorer psychological outcomes across all measures, highlighting the anticipatory stress component of minority stress. However, this interpretation warrants caution, as the long-term psychological costs of victimization are well-documented (Chinazzo et al., 2021).

Although the discrimination and rejection factors showed relatively lower reliability indices, these were maintained due to the theoretical importance of their content for capturing essential aspects of minority stress in TGNC populations. Excluding items based solely on statistical criteria could risk omitting experiences that are culturally and clinically relevant (Hambleton et al., 2004). Furthermore, internal consistency is only one indicator of measurement quality, and scales with coefficients slightly below traditional thresholds can still provide valuable information for research, particularly in complex psychosocial constructs (Streiner, 2003).

Conclusion

This study demonstrated that the Brazilian adaptation of the Gender Minority Stress and Resilience Measure (GMSR) presents promising validity and reliability for assessing stress and resilience factors among transgender and gender non-conforming (TGNC) individuals. Overall, the nine-factor model showed adequate psychometric properties, and most factors were meaningfully associated with psychological distress and self-esteem, highlighting the relevance of both stress and resilience dimensions in understanding mental health outcomes within this population. Nuanced cultural factors appeared to influence the relationships between these factors and psychological outcomes, suggesting the importance of considering context-specific experiences in research and clinical practice.

The study’s methodological limitations, particularly the small sample size and uneven representation across demographic subgroups, constrain the generalizability of the findings. Future research should prioritize larger and more diverse samples to refine the GMSR’s psychometric properties, provide more accurate estimates of model error, and further explore the complex dynamics of stress and resilience in TGNC populations.

Overall, the GMSR-Br offers valuable insights for both research and clinical applications, emphasizing the need for culturally sensitive interventions that address the multifaceted experiences of TGNC individuals.

Ethical Statements

The research procedures were approved by the institutional ethics board. The sample was selected for convenience. When they agreed to take part in the research, the individuals signed a free and informed consent form, which defined their rights and described the risks and benefits of their participation. Confidentiality and anonymity were guaranteed, and the data was only accessed by the researchers, in accordance with ethical considerations on research involving human beings.

DATA AVAILABILITY STATEMENT:

The research data are not available.

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Edited by

• Editor:
  Karina da Silva Oliveira

Publication Dates

• Publication in this collection
  27 Apr 2026
• Date of issue
  2026

History

• Received
  19 May 2025
• Reviewed
  03 Oct 2025
• Accepted
  04 Dec 2025