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Background The physician shortage in the United States (US) continues to become more apparent. We aimed to evaluate the relationship between the US physician distribution from 2012-2019 by specialty at the state/regional level relative to the corresponding population growth. Methods US matched residents and practicing physicians from 2012-2019 were extracted from the National Resident Matching Program and Association of American Medical College databases, respectively. Residents and practicing physicians were divided by geographic regions (West, Midwest, South, Northeast), states, and specialties (anesthesiology, emergency medicine, family medicine, general surgery (GS), internal medicine, obstetrics/gynecology and pediatrics). Results Entering residents and physicians increased across 7 specialties from 2012-2019 with the exception of GS, which showed .2% decrease in practicing physicians. GS experienced decreases in entering residents in all US regions except the South. All specialties showed a decrease in the people-per-physician (PPP) except GS and pediatrics, which had a 4.1% and 71.3% increase, respectively. EM showed the largest growth overall, both in entering residents and overall workforce. Conclusion GS experienced slow growth of residents, decreases in practicing physicians and workforce overall, and an increase in PPP from 2012-2019. Our findings suggest that current population growth rate is exceeding the rate of physicians entering the field of GS and highlights the need for interventions to promote the recruitment of GS residents and retainment of attending physicians, particularly for rural areas. Future research to measure surgeon distribution in relation to patient outcomes and the efficacy of recent policy to address shortages can help define additional interventions to address physician shortages moving forward.

The rise of large neuroimaging datasets and multi-dataset mega-analyses brings the power to study interindividual differences in brain structure and function on a heretofore unseen scale. However, unknown and poorly characterized intra-individual variability continues to undermine the detection of robust brain-behavior associations and, ultimately, our understanding of the brain on the whole. Women’s and reproductive health underlie variability in more than half of the population, but have long been overlooked in the study of both inter- and intra-individual differences in the brain. To this end, the Dense Investigation of Variability in Affect (DIVA) Study was designed to study intra-individual variability in the brain and behavior across the menstrual cycle in a small cohort of premenopausal female participants. The DIVA Study acquired weekly actigraphy, self-report, biospecimen, and both functional and structural magnetic resonance imaging data with concurrent peripheral physiological recordings. These data facilitate the study of several common sources of variability in the brain and behavior: the menstrual cycle and ovarian hormones, sleep, stress, exercise, and exogenous sources of hemodynamic variability.