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A study of MD-PhD pre-health advising identifies challenges to building a robust MD-PhD applicant pool
Amara L. Plaza-Jennings, Christie B. Ryba, Jessica Tan, Jennifer E.L. Diaz, Grace E. Mosley, Talia H. Swartz, Margaret H. Baron, Robert Fallar, Valerie Parkas
Amara L. Plaza-Jennings, Christie B. Ryba, Jessica Tan, Jennifer E.L. Diaz, Grace E. Mosley, Talia H. Swartz, Margaret H. Baron, Robert Fallar, Valerie Parkas
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Physician-Scientist Development

A study of MD-PhD pre-health advising identifies challenges to building a robust MD-PhD applicant pool

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Abstract

MD-PhD programs provide interdisciplinary training in medicine and research. Undergraduate pre-health advisors (PHAs) play a critical role in counseling prospective applicants, yet there have been no studies to our knowledge of MD-PhD pre-health advising. Here we surveyed 280 PHAs from US colleges and universities using both qualitative and quantitative measures that assessed their real-world advising behaviors as well as standardized evaluation of 1 of 2 fictional MD-PhD applicants, identical except for gender. We identified 3 factors that influenced advising behaviors: experience advising MD-PhD applicants, attitudes toward MD-PhD programs, and gender bias. Those PHAs with less experience and who held negative attitudes toward MD-PhD programs were less likely to initiate discussions about MD-PhD programs with qualified applicants and less likely to recommend the fictional applicants apply to MD-PhD programs. Finally, there was subtle gender bias that favored the male applicant. PHAs face challenges in advising MD-PhD applicants because there are relatively few MD-PHD applicants overall and there is a lack of resources to guide them. Addressing these challenges by strengthening collaborations with PHAs and providing comprehensive information about the value of and applicant qualifications for MD-PhD programs is crucial to enhancing MD-PhD advising, mitigating effects of bias, and expanding the pool of qualified applicants.

Authors

Amara L. Plaza-Jennings, Christie B. Ryba, Jessica Tan, Jennifer E.L. Diaz, Grace E. Mosley, Talia H. Swartz, Margaret H. Baron, Robert Fallar, Valerie Parkas

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Figure 4

Gender bias impacts applicant evaluation.

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Gender bias impacts applicant evaluation.
(A) Scatterplots of the MD-PhD...
(A) Scatterplots of the MD-PhD recommendation score as a function of the total score on the Modern Sexism Scale, with the linear regression line for the male and the female applicants. Spearman’s correlation: statistics shown in figure. (B) The percentage of PHAs who checked each application category as a strength or weakness grouped by whether they evaluated the male or the female applicant. Research as a weakness: Student’s t test (research as a weakness, P = 0.05; motivation essay as a weakness, P = 0.11). (C) Dot plot with average and standard error of MD-PhD recommendation score grouped by PHAs who checked research or essay as a strength or a weakness of the applicant. Welch’s t test (research, P < 0.0001; essay, P < 0.0001). Data points have been jittered along the x- and y-axes for better visualization. *P < 0.05, ****P < 0.0001.

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