Usage Information
Abstract
The 2014 NIH Physician-Scientist Workforce Working Group predicted a future shortage of physician-scientists. Subsequent studies have highlighted disparities in MD-PhD admissions based on race, income, and education. Our analysis of data from the Association of American Medical Colleges covering 2014–2021 (15,156 applicants and 6,840 acceptees) revealed that acceptance into US MD-PhD programs correlates with research experience, family income, and research publications. The number of research experiences associated with parental education and family income. Applicants were more likely to be accepted with a family income greater than $50,000 or with one or more publications or presentations. Applicants were less likely to be accepted if they had parents without a graduate degree, were Black/African American, were first-generation college students, or were reapplicants, irrespective of the number of research experiences, publications, or presentations. These findings underscore an admissions bias that favors candidates from affluent and highly educated families, while disadvantaging underrepresented minorities.
Authors
Darnell K. Adrian Williams, Briana Christophers, Timothy Keyes, Rachit Kumar, Michael C. Granovetter, Alexandria Adigun, Justin Olivera, Jehron Pura-Bryant, Chynna Smith, Chiemeka Okafor, Mahlet Shibre, Dania Daye, Myles H. Akabas
Usage data is cumulative from January 2025 through January 2026.
| Usage | JCI | PMC |
|---|---|---|
| Text version | 2,096 | 569 |
| 350 | 22 | |
| Figure | 593 | 0 |
| Table | 246 | 0 |
| Citation downloads | 207 | 0 |
| Totals | 3,492 | 591 |
| Total Views | 4,083 | |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.
