A psychometric evaluation of the Gender Bias in Medical Education Scale

Background: Gender bias in medical education is an increasing area of research and policy concern. However, to adequately address and monitor this issue, valid and reliable measures are needed. This research aimed to develop and test a short multidimensional measure of gender bias in medical education to assess student awareness of gender bias, beliefs about the degree to which gender bias should be addressed, and experience of gender bias.

Methods: Using students from the School of Medicine at the University of Wollongong, one pilot study and two empirical studies were conducted. The pilot study was used to scope the domain space (n = 28). This initial measure was extended to develop the Gender Bias in Medical Education Scale (GBMES). For study 1 (n = 172), confirmatory factor analysis assessed the construct validity of the three-factor structure (awareness, beliefs, experience) and enabled deletion of redundant items. Study 2 (n = 457) tested the generalizability of the refined scale to a new sample. Combining study 1 and 2, invariance testing for program of study and gender was explored. The relationship of the GBMES to demographic and gender politics variables was tested. The results were analyzed using confirmatory factor analysis and Multiple-Indicator-Multiple-Indicator-Cause models in order to determine construct validity and whether the scale generalized to other samples.

Results: After analysis of the responses from the original 16-item GBMES (Study 1), a shortened measure of 10 items fitted the data well and was found to generalize to a new sample in Study 2. The GBMES was found to be invariant across studies, gender, and program of study. Female students and those who reported greater agreement with gender equality responded with greater agreement for each of the factors in relation to gender bias. Likewise, postgraduate students reported higher scores on experience of gender bias than undergraduate students.

Conclusion: The GBMES provides a validated short multidimensional measure for use in research and policy. The factors are distinct and are related to background variables and covariates in expected patterns.