Difficulties in Measurement: Gender Nonconformity and Implications for Policy

Objectives: Gender nonconformity is increasingly acknowledged as a predictor of stress beyond sexual minority and gender minority identities, yet no clear consensus exists regarding how to measure this construct. The current study examines how five gender measures relate to each other and to common correlates.

Methods: Participants were 681 cisgender women and men, including 63 LGB-identified individuals, who took part in an online study examining correlates among different dimensions of identities, stigma, and mental health. Pearson’s product-moment correlation coefficients were computed to assess the relationships between the five gender nonconformity measures, as well as the relationships between gender nonconformity scores and trauma, victimization, and psychopathology scores.

Results: Statistically significant correlations (p < .01) were found between each of five gender nonconformity measures, ranging between r = .124 and r = .413, n = 601 to 651, for each analysis. Cronbach’s alpha ranged between .61 and .71 for the three measures containing multiple items. Statistically significant (p < .05) correlations were also found between each of five gender nonconformity measures and childhood trauma scores, school-based victimization, and psychopathology scores, ranging between r = .086 and r = .421, n = 529 to 681.

Conclusion: Different commonly used gender nonconformity measures in research produce substantially disparate findings. Depending on which measure is used, different conclusions about the relationships between gender nonconformity, victimization, and psychopathology may be drawn, which has important implications for applying research findings to anti-discrimination policies.