Revising Gender Minority Stress Theory: A Network Psychometrics Perspective

Gender minority stress theory is the premier theoretical framework for understanding the health and well-being of transgender and non-binary people. However, a theoretical disconnect exists within this field: the Gender Minority Stress and Resilience Measure (GMSRM), widely used to assess gender minority stress, is rooted in latent variable theory, assuming that different stressors (represented as items on the GMSRM) are statistically unrelated, once their given latent variable is accounted for. However, gender minority stress theory proposes that these stressors cause one another, specifically, that distal stressors cause proximal stressors. To address this inconsistency between theory and measurement, we interrogated the assumptions of latent variable models and considered a relatively new measurement framework psychometric network analysis. Our analysis of GMSRM data from 1006 trans* individuals revealed that the GMSRM is better represented by a psychometric network, rather than multiple latent variables, uncovering complex, direct associations among items across its subscales. These findings highlight the need to align measurement approaches with theoretical assumptions to better understand how social stressors impact transgender and non-binary populations.