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The Gender Pay Gap in Medical Physics: A 21-Year Analysis of Salaries (2003-2023)
Emily Hirata1, Angélica Pérez-Andújar2, Judith N Rivera3
1Department of Radiation Oncology, University of California, San Francisco, California.
Purpose:
To investigate the existence of a gender pay gap (GPG) in medical physics over a 21-year period (2003 to 2023), quantify the GPG, evaluate trends over time, and model the compounding impact of the GPG on lifetime earnings.
Methods And Materials:
The binary gender-stratified income data from the annual American Association of Physicists in Medicine (AAPM) Professional Survey reports from 2003 to 2023 were reviewed. Reported income was converted to real 2023-dollars using the Consumer Price Index (CPI) for historical comparison. To evaluate the statistical significance of the longitudinal gap despite the lack of individual-level raw data, an inverse-variance weighted longitudinal aggregation utilizing quantile-based variance estimation was performed for the board-certified medical physics cohorts. The accumulated income loss was modeled over a 35-year career span.
Results:
A persistent GPG was demonstrated, with men consistently earning more than women across all qualifications. The gap is significantly pronounced for certified physicists with longitudinal aggregation revealing a statistically significant, pooled 21-year income gap favoring men: +$19,420, P<0.0001 for certified Masters, and +$25,161, P<0.0001 for certified PhD physicists. Critically, the cumulative financial impact is substantial: an initial GPG of $15,000 results in an estimated income loss of $716,923 in lifetime earnings. While statistically significant, the aggregated data does not adjust for confounding variables such as years of experience or geographic cost of living.
Conclusion:
The GPG is a systemic issue in medical physics, requiring targeted intervention. To facilitate evidence-based corrective action, greater transparency in data reporting is vital. We recommend the AAPM explicitly expand its reports to include gender-stratified data on years of experience, leadership roles, and geographic cost of living.
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