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Effect of medical student debt on mental health, academic performance and specialty choice: a systematic review.

ABSTRACT: OBJECTIVES:With the high and rising total cost of medical school, medical student debt is an increasing concern for medical students and graduates, with significant potential to impact the well-being of physicians and their patients. We hypothesised that medical student debt levels would be negatively correlated with mental health and academic performance, and would influence career direction (ie, medical specialty choice). DESIGN:We performed a systematic literature review to identify articles that assessed associations between medical student mental health, academic performance, specialty choice and debt. The databases PubMed, Medline, Embase, Scopus and PsycINFO were searched on 12 April 2017, for combinations of the medical subject headings Medical Student and Debt as search terms. Updates were incorporated on 24 April 2019. RESULTS:678 articles were identified, of which 52 met the inclusion criteria after being reviewed in full text. The majority of studies were conducted in the USA with some from Canada, New Zealand, Scotland and Australia. The most heavily researched aspect was the association between medical student debt and specialty choice, with the majority of studies finding that medical student debt was associated with pursuit of higher paying specialties. In addition, reported levels of financial stress were high among medical students, and correlated with debt. Finally, debt was also shown to be associated with poorer academic performance. CONCLUSIONS:Medical student debt levels are negatively associated with mental well-being and academic outcomes, and high debt is likely to drive students towards choosing higher paying specialties. Additional prospective studies may be warranted, to better understand how educational debt loads are affecting the well-being, career preparation and career choices of physicians-in-training, which may in turn impact the quality of care provided to their current and future patients.

SUBMITTER: Pisaniello MS

PROVIDER: S-EPMC6609129 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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Effect of medical student debt on mental health, academic performance and specialty choice: a systematic review.

Pisaniello Monique Simone MS Asahina Adon Toru AT Bacchi Stephen S Wagner Morganne M Perry Seth W SW Wong Ma-Li ML Licinio Julio J

BMJ open 20190702 7

<h4>Objectives</h4>With the high and rising total cost of medical school, medical student debt is an increasing concern for medical students and graduates, with significant potential to impact the well-being of physicians and their patients. We hypothesised that medical student debt levels would be negatively correlated with mental health and academic performance, and would influence career direction (ie, medical specialty choice).<h4>Design</h4>We performed a systematic literature review to ide ...[more]

PMID: 31270123

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Project description:Although medical school programs oriented toward postgraduate specialty training have the potential to reduce the duration and cost of medical school for US medical students, success depends on the ability of students to predict their postgraduate specialties. It is clear that first-year choices are poorly predictive, but it is not known when predictions become sufficiently reliable to support specialty-oriented learning programs. We therefore examined the predictive value of specialty preferences expressed at the ends of the first, second and third years of medical school and asked whether concurrent expressions of confidence in choices improved predictive ability. We also investigated the possibility that discrepancies between predicted and actual postgraduate specialty training were related to scores on an examination of knowledge in basic biomedical sciences required for US medical school graduation (the United States Medical Licensing Examination (USLME) Step 1 examination).We calculated positive and negative predictive values (PPV and NPV, respectively) for specialty choices and the sensitivity and specificity of asking for choices for 634 University of Colorado School of Medicine students who trained in 23 accredited residencies from 2011 through 2015. We examined the effect of confidence in first choices in 609 students, and in 334 students, sought an association between USMLE Step 1 scores and switching from postgraduate training specialties predicted at the end of year 2.The PPV of first choices improved from years 1 through 3. NPV was high throughout. PPVs of year 3 first choices ranged from 79% in Anesthesiology to 95% in Psychiatry. Expressions of confidence in first choices did not improve PPV. Sensitivity of asking for first choices increased with time; specificity was consistently high. USLME Step 1 scores were higher for students who ultimately trained in specialties more competitive than first-choice specialties at the end of year 2.Specialty-oriented learning programs during medical school must accommodate students who change career plans. The PPV of specialty first choices improves each year, but even year 3 predictions can be inaccurate with potential loss of students from specialty-specific programs. USMLE Step 1 scores appeared to affect career plans expressed at the end of year 2.

Project description:The acceptance of students to a medical school places a considerable emphasis on performance in standardized tests and undergraduate grade point average (uGPA). Traditionally, applicants may be judged as a homogeneous population according to simple quantitative thresholds that implicitly assume a linear relationship between scores and academic success. This 'one-size-fits-all' approach ignores the notion that individuals may show distinct patterns of achievement and follow diverse paths to success. In this study, we examined a dataset composed of 53 variables extracted from the admissions application records of 1,088 students matriculating to NYU School of Medicine between the years 2006-2014. We defined training and test groups and applied K-means clustering to search for distinct groups of applicants. Building an optimized logistic regression model, we then tested the predictive value of this clustering for estimating the success of applicants in medical school, aggregating eight performance measures during the subsequent medical school training as a success factor. We found evidence for four distinct clusters of students-we termed 'signatures'-which differ most substantially according to the absolute level of the applicant's uGPA and its trajectory over the course of undergraduate education. The 'risers' signature showed a relatively higher uGPA and also steeper trajectory; the other signatures showed each remaining combination of these two main factors: 'improvers' relatively lower uGPA, steeper trajectory; 'solids' higher uGPA, flatter trajectory; 'statics' both lower uGPA and flatter trajectory. Examining the success index across signatures, we found that the risers and the statics have significantly higher and lower likelihood of quantifiable success in medical school, respectively. We also found that each signature has a unique set of features that correlate with its success in medical school. The big data approach presented here can more sensitively uncover success potential since it takes into account the inherent heterogeneity within the student population.

Project description:BackgroundChoosing a medical specialty is an important, complex, and not fully understood process. The present study investigated the factors that are related to choosing and rejecting medical specialties in a group of students and recent medical doctors.Methodology and findingsA cross-sectional survey of 1,223 medical students and doctors was performed in Brazil in 2012. A standardized literature-based questionnaire was applied that gathered preferable or rejected specialties, and asked questions about extracurricular experiences and the influence of 14 factors on a Likert-type scale from 0 to 4. Specialties were grouped according to lifestyle categories: controllable and uncontrollable, which were subdivided into primary care, internal medicine, and surgical specialties. Notably, the time period of rejection was usually earlier than the time period of intended choice (p < 0.0001, χ(2) = 107.2). The choice mainly occurred during the internship period in medical school (n = 466; 38.7%). An overall large frequency of participation in extracurricular activities was observed (n = 1,184; 95.8%), which were highly associated with the respective medical area. Orthopedic surgery had the highest correlation with participation in specialty-specific organized groups (OR = 59.9, 95% CI = 21.6-166.3) and psychiatry was correlated with participation in research groups (OR = 18.0, 95% CI = 9.0-36.2). With regard to influential factors in controllable lifestyle specialties, "financial reason" (mean score ± standard deviation: 2.8 ± 1.0; median = 3) and "personal time" (3.1 ± 1.3; median = 4) were important factors. In primary care, these factors were less important (1.7 ± 1.3 and 1.7 ± 1.5, respectively; median = 2 for both), and higher scores were observed for "curricular internship" (3.2 ± 1.1, median = 4) and "social commitment" (2.6 ± 1.3, median = 3).ConclusionThe present findings provide important insights into developing strategies to stimulate interest in specialties based on the needs of the Brazilian healthcare system.

Dataset Information

Effect of medical student debt on mental health, academic performance and specialty choice: a systematic review.

Publications

Effect of medical student debt on mental health, academic performance and specialty choice: a systematic review.

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