Educational Debt and Subspecialty Fellowship Type

This cross-sectional study used data from the American Board of Pediatrics (ABP) Subspecialty In-training Examination Postexamination Survey, administered annually to subspecialty fellows enrolled in 1 of 15 subspecialty ABP certifications. The final analytical sample included first-year subspecialty fellows who completed the Subspecialty In-training Examination during 2018 to 2019 and 2021 (no data were available for 2020, given temporary survey question changes). Data collection was approved by the ABP’s institutional review board of record; analyses were approved by the University of North Carolina at Chapel Hill’s institutional review board.

The exposure of interest was self-reported educational debt, categorized for these analyses as no educational debt, <$100 000, $100 000 to <$200 000, $200 000 to <$300 000, ≥$300 000, and “Prefer not to answer.” The outcome of interest was current subspecialty fellowship type, dichotomized into subspecialties with positive or negative lifetime earnings potential relative to private practice GP on the basis of Catenaccio et al's classification of lifetime relative net present value.²  Covariates in the multivariable model included: Sex, international versus American medical graduate, self-reported race and ethnicity, and fellowship geographic location. Race and ethnicity were included because of previous studies demonstrating that chosen area of subspecialty training and educational debt are associated with self-reported race and ethnicity.^4,5  Unadjusted and adjusted ordinal logistic regression factor analysis models examined the association between debt and subspecialty type. Analyses were performed using R Version 4.0. Statistical significance was established as a 2-sided P < .05.

A total of 3264 fellows (95.3% response rate) participated; sample characteristics are provided in Table 1. In unadjusted analyses, individuals with self-reported educational debt between $200 000 to <$300 000 and ≥$300 000 had 1.43 odds ratio (95% confidence interval [CI] 1.17–1.74) and 1.48 odds ratio (95% CI 1.21–1.80) of training in a positive lifetime earnings potential subspecialty (Table 2). No association was observed among individuals with self-reported educational debt of <$200 000. A similar pattern was observed in adjusted models with individuals with self-reported debt of $200 000 to <$300 000 and ≥$300 000 having 1.39 adjusted odds ratio (aOR) (95% CI 1.13–1.72) and 1.46 aOR (95% CI 1.19–1.79), respectively, of training in a positive lifetime earnings potential subspecialty (Table 2). For covariates, male sex, American medical graduate status, and fellowship location were associated with training in a positive lifetime earnings potential fellowship in unadjusted analyses (Table 1); only male sex remained in the adjusted analyses (aOR = 1.21, 95% CI 1.04–1.14).

Our study found that high self-reported educational debt was positively associated with training in a positive lifetime earnings potential subspecialty. Individuals with $200 000 to <$300 000 of educational debt were 1.39 more likely than those with no educational debt to be in a positive lifetime earnings potential subspecialty.

Although an Association of American Medical Colleges’ 2020 report has suggested no association between debt and specialty selection, a recent systematic review concluded that educational debt among medical students does positively influence selection of specialties with higher salaries.^1,6  Future research should focus on understanding how pediatric residents’ educational debt influences subspecialty selection, given that 44% of pediatric interns report >$200 000 in educational debt with notable disparities by race and ethnicity.⁷  Future studies should continue to examine the association of educational debt and chosen subspecialty using different measurements of lifetime earnings potential³  and the impact of educational debt reduction on workforce decisions. Interestingly, we did not find differences by race and ethnicity. This may reflect earlier decision-making regarding career choices before or during residency or other factors.⁸ 

Limitations include:

1. inability to comment on causation of association;

2. sample limited to those currently in subspecialty training and not at a decision-making point during residency who choose another subspecialty or remain in GP, potentially because of debt burden, possibly biasing us toward individuals with less debt⁹ ; and

3. lack of inclusion of other factors that influence debt, such as public or private medical school attendance or generational/family wealth.

Nevertheless, the large sample size of fellows participating allows for improved generalizability. Critical workforce issues, including potential shortages in smaller subspecialties and diversification, could be exacerbated by residents with high debt preferentially choosing subspecialties with positive lifetime earning potential. Our findings may inform current discussions around pediatric subspecialty workforce policy.

ABP

American Board of Pediatrics

aOR

adjusted odds ratio

CI

confidence interval

GP

general pediatrics