Gender Minority Stress and Resilience Measure: A Meta-Analysis of the Associations with Mental Health in Transgender and Gender Diverse Individuals

Abstract

Transgender and gender diverse (TGD) individuals are more likely to experience mental health difficulties than cisgender individuals due to unique stressors related to their stigmatized gender identity and/or expression. This meta-analysis examined the associations between gender minority stressors and resilience factors, as measured by the Gender Minority Stress and Resilience Measure (GMSR; Testa et al., 2015), and two types of mental health symptoms (i.e., depression and anxiety). A comprehensive literature search and study inclusion process following PRISMA guidelines identified 69 sources, representing 47 unique samples. Mean effect sizes revealed significant positive associations between all GMSR minority stress subscales and anxiety and depression symptoms ( rs = .22 to .40) with larger correlations for proximal stressors compared to distal stressors. The GMSR resilience subscales were significantly negatively correlated with anxiety and depression symptoms ( rs = −.07 to −.16). These findings highlight the robust relationship between gender minority stressors and mental health symptoms among TGD individuals and indicate a need for addressing these stressors both by reducing exposure to external stressors and by addressing the internalization of those stressors in clinical settings. The small effects for the resilience subscales suggest a need to examine additional resilience factors that may be more pertinent to mental health among TGD individuals.

Minority stress and structural stigma predict well-being in European LGBTQ+ parents

“…Individual-level minority stress, assessed as a predictor group, emerged as one of the top-ranking predictors across all models. This aligns with theory (Brooks, 1981;Eaton et al, 2021;Meyer, 2003;Rivas-Koehl et al, 2023) and empirical findings (de Lange et al, 2022;Dürrbaum & Sattler, 2020;Newcomb & Mustanski, 2010;Pachankis et al, 2020;Pellicane & Ciesla, 2022;Wilson et al, 2023) that highlight the crucial role of minority stress in causing and perpetuating mental health burdens and reduced well-being within LGBTQ+ populations (irrespective of parental status). Limited quantitative research has focused on minority stress exposure in LGBTQ+ parents as compared to non-parents (e.g., Goldberg & Smith, 2011, 2014Mosovsky et al, 2016) due to different research priorities within this field (Farr et al, 2022).…”

“…A vast body of empirical research supports the tenets of minority stress theory across many populations, settings, and stressors (de Lange et al, 2022;Dürrbaum & Sattler, 2020;Newcomb & Mustanski, 2010;Pachankis et al, 2020;Pellicane & Ciesla, 2022;Wilson et al, 2023) and progress has been made in integrating intersectionality within these works (Dyar et al, 2023;Shangani et al, 2020). Within the field of LGBTQ+ parent research, however, research through a minority stress lens (irrespective of considerations of intersectionality) has been limited (van Eeden-Moorefield et al, 2018).…”

“…Identity concealment (i.e., hiding one's LGBTQ+ identity) emerged as a particularly important predictor across models, with higher levels of concealment being associated with predictions of lower well-being. This is notable, because associations between concealment and well-being in (non-parenting) LGBTQ+ populations are typically small and mixed (Pachankis et al, 2020;Wilson et al, 2023), in part because hiding one's identity can shield from further distal minority stress in unsafe environments and thus also be protective for well-being (Frost & Meyer, 2023;Pachankis et al, 2020). We offer two explanations for our finding that concealment is a particularly important predictor for LGBTQ+ parents' wellbeing: First, our non-linear, machine learning-based approach (Ke et al, 2017) is capable of inherently modeling variable interactions and might have enabled us to model this stressor's context-dependency better than approaches based on (generalized) linear models, as done in previous studies on (non-parenting) LGBTQ+ populations (Pachankis et al, 2020).…”