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.