Many aspiring medical students apply to medical school more than once before they are accepted. Little is known, however, about the characteristics of repeat applicants. By investigating factors that may discourage some medical school aspirants from reapplying, such as indebtedness,1,2 researchers can gain a better understanding of the social diversity of the applicant pool.3,4 Exploring gender differences in the factors that help explain the likelihood of reapplying is also important in light of the gradual decline in the percentage of medical school applicants who are female, from a peak of 50.8% in 2003 to 47.3% in 2010.5 Women have also been less likely than men to become repeat applicants in recent years: The percentage of women among repeat applicants decreased from 47.8% in 2004 to 43.7% in 2010.6 Unless the proportion of women among first-time and repeat applicants increases, this trend will continue to adversely affect the applicant pool's social diversity.
In this study, we therefore sought to identify factors that predict the likelihood of an unsuccessful first-time medical school applicant becoming a repeat applicant the following year. Specifically, we explored how the likelihood of becoming a repeat applicant is associated with self-reported career and educational alternatives and with total indebtedness. In addition, we examined how these associations differ between men and women.
Factors That May Influence the Decision to Reapply to Medical School
Two recent studies7,8 that used nationally representative data to examine college students' decisions to enroll in graduate and professional education programs helped focus our analyses. Perna,7 who focused on the sources of the underrepresentation of women and racial/ethnic minorities in such programs, found that relative to not enrolling in any postgraduate program, female college graduates were less likely than their male counterparts to enroll in a first-professional-degree program but were more likely to enroll in a master's level program. Millet,8 investigating the effects of educational indebtedness, reported findings suggesting that college students who have collected substantial amounts of debt are significantly less likely to apply to graduate programs. Together, these studies suggest that men and women make different postgraduate education decisions and that one significant factor in their decision-making process is indebtedness.
Research also suggests that some college students who consider applying to unrelated professional degree programs, such as medicine and law, focus more on achieving a professional class status than on choosing a professional degree.9 We, therefore, predicted that considering graduate study in a field unrelated to medicine (e.g., law, business, a social science) would be associated with a lower likelihood of reapplying to medical school. Although committed to pursuing medicine, applicants considering other fields of study may differ from other aspirants in their evaluation of the relative future benefits of professional education programs. After applying without being accepted, these applicants may perceive that the benefits of pursuing a degree in medicine no longer outweigh the benefits of pursuing an alternative professional degree. On the other hand, research has not yet shown how considering graduate study in a science, technology, engineering, or mathematics (STEM) field or in another health-related field may affect the likelihood of becoming a repeat applicant. How patterns of self-reported career and educational alternatives differ between male and female medical school applicants is also unknown.
Because research has shown that having a higher level of student indebtedness reduces an individual's likelihood of applying to a professional degree program, we predicted that indebtedness also would decrease the likelihood of becoming a repeat medical school applicant. Medical school aspirants who have already accumulated substantial debt and who are aware of the high levels of debt that must be absorbed during medical school may perceive the benefits of an alternative career or educational path as outweighing the benefits of a career in medicine. Whether there are gender differences in the association between indebtedness and the likelihood of becoming a repeat applicant is unknown.
In addition to indebtedness and the consideration of alternative career and educational paths, we suspected that other factors would also be associated with the likelihood of becoming a repeat applicant. First, aspirants who achieved high Medical College Admission Test (MCAT) scores but did not receive an acceptance may decide to reapply, perhaps after correcting nonacademic deficiencies to increase their chances of being accepted during the following application cycle. Second, aspirants who decided to pursue a career in medicine at an earlier phase of their formal education may be more likely to reapply than those who made the decision later. Third, because a continued commitment to pursue medicine depends in part on the availability of educational opportunities and financial resources, aspirants from higher socioeconomic status (SES) backgrounds may be more likely than those from lower SES backgrounds to reapply. Fourth, aspirants who have a parent who is a physician may be more likely to reapply than those without a physician parent, because familial influences can have a significant impact on career choice.10 Fifth, applicants who delayed their decision to apply to graduate or professional programs until after they graduated from college may be more likely than those who apply as college students to view applying to medical school as a one-time opportunity because of the rigors of the application process and possible economic and family commitments. Finally, independent of age, aspirants with dependents may have a similar view of applying to medical school. Thus, older applicants and those with dependents may be less likely to reapply.
To test our predictions regarding factors that may influence unsuccessful applicants' decisions to reapply to medical school, we analyzed 2009 American Medical College Application Service (AMCAS) data, 2010 AMCAS data, and 2008 Pre-MCAT Questionnaire (PMQ) data. AMCAS is a centralized application processing service that most U.S. medical schools use as their primary application method. It is available to applicants entering their first year at participating schools.11 The PMQ is a survey that the Association of American Medical Colleges administers each year to individuals who have registered to take the MCAT.12
We obtained deidentified AMCAS and PMQ data, and we did not have access to identifiable data. Applicants' records were linked across datasets through a unique identification variable. We used logistic regression models to examine the likelihood that a first-time medical school applicant who does not successfully matriculate will reapply the following year. We performed all analyses using Stata 12 (Stata Corp, College Station, Texas).
Using 2009 AMCAS data, we first identified all 2009 applicants who had the potential to become repeat applicants in 2010. Of the 40,646 total applicants using AMCAS in 2009, 38,402 (95%) were U.S. citizens or permanent residents with an MCAT score. Of these applicants, 20,415 (53%) were not accepted by a medical school. Among this population, 14,389 (70%) were first-time applicants, and 6,026 (30%) had applied in a previous year. For this analysis, we focused on the 14,389 first-time applicants who were not accepted. Using 2010 AMCAS data, we determined that 5,282 (37%) of the 14,389 first-time nonaccepted applicants became repeat applicants in 2010, and 40% (2,121) of the repeat applicants were accepted to medical school.
The opportunity to participate in the 2008 PMQ was offered to 46,192 (70%) of all 2008 MCAT registrants (n = 65,589). The overall 2008 PMQ response rate among registrants who took the MCAT was 37%. Among the 14,389 potential 2010 repeat applicants we identified, 7,078 (49%) had the opportunity to respond to the 2008 PMQ. Their response rate was 47% (n = 3,326). Therefore, a total of 3,326 (23% of the 14,389) potential 2010 repeat applicants had valid PMQ data and comprise the sample for our analyses. For logistic regression analyses, we therefore used population-level demographic data from AMCAS to weight all results so that our sample would more accurately represent the population of potential repeat applicants. To create the weight variable, we first regressed respondents' sociodemographic characteristics—sex, age, and race/ethnicity—and their actual 2010 repeat applicant status to predict the likelihood that a potential repeat applicant would have responded (1) or not responded (0) to the 2008 PMQ. We then took the inverse of the predicted probabilities from the logistic regression model—that is, we divided 1 by the selection probability of a potential repeat applicant having answered the PMQ, or 1/p(pmq).
The 2008 PMQ asked respondents to identify their potential career and educational alternatives, indicate when they decided to pursue a career in medicine, and report their educational debt. The PMQ question about alternative plans stated: “What is on your ‘Plan B’ list? If you apply to one or more medical schools in an upcoming application year but are not accepted into medical school that year, which options will you most likely consider?” Respondents were instructed to select up to 3 of the following 10 response options: “reapply to medical school the following application year”; “business school/MBA”; “getting a job”; “graduate program in science, technology, engineering, or math (STEM)”; “graduate program in the social sciences”; “graduate program in the humanities”; “law school/JD”; “other kind of medical training or health profession”; “postbaccalaureate, internship, or research program”; and “other”. In our analyses, because of the small number of responses (for both men and women), we added responses for “graduate program in the humanities” to the “other” responses, and we combined “law school/JD” and “business school/MBA” responses as “business or law school.”
For analyses involving indebtedness, we used the data that PMQ respondents provided regarding the total amount of their outstanding educational loans from their college or premedical education.
For the purposes of our logistic regression analyses, we categorized responses to the PMQ question “When did you definitely decide you wanted to study medicine?” into “decided before college” (1) and “decided after entering college” (0).
Career and educational alternatives and indebtedness
The self-reported alternative career and educational options and debt that our sample of potential 2010 repeat applicants (n = 3,326) indicated on the 2008 PMQ are reported in Table 1 by repeat applicant status and gender. In this section, we report unweighted percentages for the sample of PMQ respondents; Table 1 also reports weighted percentages that would more accurately reflect the actual population of repeat applicants. The “Plan B” option that potential repeat applicants selected most frequently was “reapply to medical school the following application year” (87.9%, n = 2,925). The next three most common responses were “getting a job” (33.9%, n = 1,129), “graduate program in STEM” (29.6%, n = 984), and “other kind of medical training or health profession” (25.1%, n = 834).
Aspirants who did not reapply in 2010 were more likely to choose the “other kind of medical training or health profession” option (27.0%, 563 of 2,085) compared with repeat applicants (21.8%, 271 of 1,241). This difference is largely accounted for by men. Relative to women, a greater percentage of men (25.4%, 217 of 854) who did not reapply reported that they were considering other medical training or health professions compared with men who reapplied (17.9%, 113 of 633; z = 3.32, P < .001).
Regarding level of educational debt, the largest share of the 3,326 potential repeat applicants (39.7%, n = 1,320) reported having no debt, whereas 17.0% (n = 564) reported having less than $20,000, 15.8% (n = 527) reported having $20,000–$49,999, and 11.3% (n = 375) reported having $50,000 or more; 16.2% (n = 540) did not respond to the debt question. Our analyses showed that those who became repeat applicants had lower levels of debt than did those who chose not to reapply (χ2 = 19.14, P < .001), suggesting that aspirants who have accumulated substantial levels of educational debt and could potentially reapply to medical school are less likely to do so than are those with lower levels of debt. We tested this assumption using a multivariate model, and we present the results below.
Factors predicting the likelihood of becoming a repeat applicant
Table 2 presents the results of our multivariate logistic regression analysis of factors predicting the likelihood that unsuccessful 2009 applicants would become repeat applicants in 2010. Model 1 (all potential applicants) shows that, controlling for all other factors, women had 19% lower odds of reapplying. Potential repeat applicants who selected “reapply to medical school the following application year” as one of their Plan B options were 1.7 times more likely to reapply. On the other hand, potential repeat applicants who considered pursuing graduate study in a STEM field, another kind of medical training or health profession, or a graduate degree in a social science were less likely to reapply to medical school. These findings are largely consistent with the descriptive results shown in Table 1.
MCAT score was a strong predictor of becoming a repeat applicant to medical school: Compared with aspirants with scores ≤23, the odds of reapplying gradually increased from 1.5 for those with scores of 24–26, to 5.1 for those with scores ≥33. Educational debt also had a significant association with the likelihood of reapplying to medical school: Aspirants with ≥$20,000 in debt were less likely to reapply compared with those with no debt.
Net of all other factors, a longtime commitment to the pursuit of a career in medicine increased the likelihood of reapplying to medical school. Aspirants who reported they had decided on a career in medicine before entering college were roughly 1.1 times more likely to reapply than were those who decided after entering college. As we predicted, being older than 23 years of age reduced the likelihood of becoming a repeat applicant. Having at least one dependent, on the other hand, had no significant association with the likelihood of reapplying. Finally, black/African American and Hispanic aspirants were more likely than white aspirants to become repeat applicants.
Models 2 and 3 present the results of our separate analyses for men and women. To test whether coefficients for men (βmj) and women (βfj) were statistically different, we calculated the Wald statistic (Table 2). The Wald statistic is a test of the equality of logit coefficients (βfj = βmj) from models of multiple groups.13 Comparing logit coefficients from the separate models for men and women, a statistically significant Wald statistic (3.84, P < .05) for a particular variable (e.g., age) would indicate that the variable has a significantly different association by gender on the likelihood of reapplying. We found that a number of coefficients were indeed statistically distinguishable—notably, five of the eight Plan B options, educational debt, and socioeconomic background.
Among the eight Plan B options, four career and educational alternatives distinguished men from women: business or law school, graduate program in a social science, graduate STEM program, and another type of medical training or health profession. For men, considering business or law school as an alternative to medicine decreased the odds of reapplying to medical school. Contrastingly, women considering business or law school were 1.3 times more likely to reapply to medical school. It should be noted, however, that no more than 8% of men and 5% of women reported business or law school as a possible Plan B option. Similarly, although considering a social science graduate program decreased women's odds of reapplying to medical school, less than 5% of women reported it as a Plan B option. Among men, considering a graduate STEM program decreased the odds of reapplying by 18%; however, the association was also negative for women (P < .10), and the difference between the coefficients for men and women was not statistically significant (Wald statistic = 1.61).
Consideration of pursuing another type of medical training or another health profession has a significant association with reapplying for men and for women. Men who reported this as a Plan B option had 42% lower odds of reapplying than other men. Women who reported this as a Plan B option had 13% lower odds of reapplying compared with other women.
Although greater levels of debt reduce all aspirants' likelihood of reapplying, we found that larger amounts of debt (≥$50,000) reduced the likelihood more for men than for women. Furthermore, SES background strongly distinguished men and women: Men from higher SES backgrounds were significantly less likely to reapply to medical school compared with men who were first-generation college graduates. Among women, on the other hand, those who had a parent with a graduate degree or a physician parent were roughly 1.3 times more likely to reapply.
We found no significant, gender-based differences in the association between MCAT score and the likelihood of reapplying: There was a strong, positive association for both men and women. Figures 1 and 2 summarize the results from Table 2 by presenting the predicted probabilities of becoming a repeat applicant by MCAT score, Plan B options, and educational debt level.
We explored the factors associated with the likelihood that a medical school applicant who is unsuccessful in his or her first attempt will become a repeat applicant the following year, to provide insight into how medical school aspirants make decisions about their careers and graduate-level education. We found noticeable differences between nonaccepted 2009 applicants who reapplied to medical school in 2010 and those who did not. Specifically, potential repeat applicants who expressed an interest in other medical training or another health profession, a graduate STEM program, or a graduate social science program as a potential Plan B option to a career in medicine were significantly less likely to reapply to medical school than were those who did not express such interests. Having greater amounts of debt (≥$20,000) also decreased the likelihood of reapplying. Black/African American and Hispanic aspirants were more likely than white aspirants to reapply, as were those who reported an early commitment to pursuing a career in medicine compared with those who made the decision later.
Women were less likely than men to reapply, and factors associated with the likelihood of reapplying differed by gender. These differences were explained by self-reported educational and career Plan B options, SES background, and, to a lesser extent, level of educational debt. Specifically, considering a career in business or law as an alternative to medicine increased the likelihood of reapplying for women but decreased the likelihood for men. Interest in a graduate social science program decreased the likelihood of reapplying among women but not among men; contrastingly, interest in a graduate STEM program decreased the likelihood of reapplying among men but not among women.
Our results suggest that medical school aspirants are being absorbed by other health professions and graduate STEM programs. In recent years, roughly one in seven applicants to MD-granting schools also applied to DO-granting schools.14 Further, different premedical educational experiences play an important role in shaping career and educational alternatives for men and women. For example, premedical sorting during college is more likely to dissuade women than men from pursuing a career in medicine.15,16 This process may not only affect academic preparedness, as measured by science grade point averages and MCAT scores, but may also deter female aspirants from continuing with the medical school application process.
Our finding that educational debt is negatively associated with the likelihood of reapplying for both men and women suggests that debt is also a significant dissuading factor for individuals who aspire to a career in medicine but ultimately choose never to apply. Future studies should examine the extent to which educational debt dissuades aspirants (i.e., those who register for the MCAT) from applying to medical school, and how this might differ by social group (e.g., race/ethnicity, SES, gender).
Our finding that there was a significant gender difference in the likelihood of reapplying by SES was unexpected. Women from higher SES backgrounds were more likely to reapply compared with other women, whereas we found the opposite for men. We speculate this may be explained by the differential influence that mothers with higher levels of education (e.g., mothers who are physicians) have on their daughters' versus their sons' careers and educational aspirations. Similarly, our results showed that, compared with white aspirants, black/African American and Hispanic aspirants were more likely to persist in the application process. This is a positive finding in terms of fostering a diverse pool of applicants committed to careers in medicine. Further studies should examine whether this finding holds among the pool of aspirants who have registered for the MCAT but have not yet submitted a first application to medical school.
In this study, we focused on the individual-centered characteristics associated with the likelihood of reapplying to medical school. A more complete analysis would also consider occupation-oriented factors, such as perceived future work–family constraints, which may play a role in deterring aspirants from reapplying and may also differ between women and men. In addition, although our analysis will help researchers better understand how the applicant pool is being shaped and where diversity is being lost, the results would be strengthened by using multiple years of data to isolate any possible period effects. This is important, given that the recent economic recession may have had a greater effect on the career options of some social groups compared with others. Finally, our results may have been affected by who became part of the potential repeat applicant pool. The factors associated with the likelihood of reapplying to medical school in 2010 are dependent on which of the first-time applicants in the original 2009 pool were accepted into medical school. Specifically, a selection bias may occur if medical schools, both MD- and DO granting, differentially select men and women by certain characteristics, such as SES.
The authors would like to thank Laura Castillo-Page, Tim Liao, Christine Liu, and Emory Morrison for their comments and suggestions.
1. Kassebaum DG, Szenas PL, Schuchert MK. On rising medical student debt: In for a penny, in for a pound. Acad Med. 1996;74:1123–1134.
3. Association of American Medical Colleges, Diversity Policy and Programs. The Diversity Research Forum: Successfully Evaluating Diversity Efforts in Medical Education. Washington, DC: Association of American Medical Colleges; 2008.
4. Association of American Medical Colleges, Diversity Policy and Programs. The Diversity Research Forum: Getting to Institutional Excellence: Ensuring the Integration of Diversity in Academic Medicine. Washington, DC: Association of American Medical Colleges; 2010.
5. Association of American Medical Colleges. Application and Matriculation Data. Table 7: Applicants, first-time applicants, acceptees, and matriculants to U. S. medical schools by sex, 1999–2010. https://www.aamc.org/download/159590/data/table7
. Accessed January 18, 2012.
6. Association of American Medical Colleges Data Warehouse. Applicant biographic data research (APP_Bio_R) table. Washington, DC: AAMC.
7. Perna LW. Understanding the decision to enroll in graduate school: Sex and racial/ethnic group difference. J Higher Educ. 2004;75:487–527.
8. Millet C. How undergraduate loan debt affects application and enrollment in graduate or first professional school. J Higher Educ. 2003;74:386–427.
9. Schleef D. “That's a good question!” Exploring motivations for law and business school choice. Sociol Educ. 2000;73:155–174.
10. Xie Y, Shauman KA. Women in Science: Career Processes and Outcomes. Cambridge, Mass: Harvard University Press; 2003.
13. Liao TF. Comparing social groups: Wald statistics for testing equality among multiple logit models. Int J Comp Sociol. 2004;45:3–16.
14. Jolly P, Garrison G, Boulet JR, Levitan T, Cooper RA. Three pathways to a physician career: Applicants to U.S. MD and DO schools and U.S. citizen applicants to international medical schools. Acad Med. 2008;83:1125–1131.
15. Barr D. Questioning the Premedical Paradigm: Enhancing Diversity in the Medical Profession a Century After the Flexner Report. Baltimore, Md: Johns Hopkins University Press; 2010.
16. Hill C, Corbett C, St. Rose A. Why So Few? Women in Science, Technology, Engineering, and Mathematics. Washington, DC: American Association of University Women; 2010.
This article reflects the work of the authors and does not necessarily reflect the opinions or policies of the Association of American Medical Colleges.