Academic and non-academic predictors of academic performance in medical school: an exploratory cohort study

Abstract

Background Medical schools should also evaluate applicants’ non-academic characteristics in the search for successful students and future physicians, but ideal non-academic criteria have not yet been found. We followed two successive generations of medical students at the University of Split School of Medicine (USSM) to assess both academic and non-academic constructs as predictors of academic performance, defined as medical school grade point average (GPA). We also interviewed some of the participants to gain additional insight for future studies. Methods We measured study GPA in first and last year, as well as attitudes towards science, motivation, emotional intelligence, self-esteem, and perceived personal incompetence in first year. We also obtained their scores on existing medical school enrollment criteria, the State Graduation Exam (SGE) and high-school GPA. Regression models were constructed for predictors of GPA in the last year of medical school. Four structured pilot interviews were conducted to explore participants’ perceptions of necessary traits for medical school and later practice. Results Regression analysis showed that only SGE predicted final academic performance in medical school (β=0.35, 95% confidence interval (CI)=0.06-0.64), while none of the non-academic constructs we assessed predicted this outcome of education. The two generations did not significantly differ in any variable except that intrinsic motivation was higher in the generation that enrolled in 2011 (OR=1.47, 95%CI=1.12-1.93, P=0.005). Discussion None of the non-academic constructs predicted academic performance in medical school. Their use as selection criteria may not be warranted as they could impact the academic quality of enrolling medical students.

Using machine learning to identify key subject categories predicting the pre-clerkship and clerkship performance: 8-year cohort study

“…26 Regarding background characteristics, our findings were in line with previous studies, which found that nonacademic factors did not significantly predict academic performance in medical school. 21,27 Predictions in academic performance have recently drawn substantial attention in the medical education field, especially due to the potential of machine learning techniques that use advanced learning analytics. 15,28,29 For different machine learning techniques, natural language processing was the most commonly used machine learning technique to predict medical students' academic performance based on data extracted mostly from clinical notes with 75% positive prediction.…”

“…Some of the studies have investigated several predictors of medical students’ clerkship performance, including their summative scores such as the grade point average during pre-med and pre-clerkship, 14 scores on the medical school entrance exam, 20,21 and the United States Medical Licensing Examination. 20,22 Our findings demonstrated that many individual subjects in the pre-med and basic medical science stages could also be a significant predictor of clerkship performance.…”

Relationship between admission selection tools and student attrition in the early years of medical school

“… 6 , 7 The accepted applicant should be able to graduate from the medical school and be successful in his/her subsequent professional practice. 8 …”

Defining success in healthcare education: US dental student and faculty perspectives

“…Student success serves a critical role in professional educational institutions, as it not only correlates with a more capable professional workforce but is also often used as a metric for institutional performance 1 . A recent surge in investigations seeks to enhance professional student success and determine primary non‐cognitive skills associated with such success, often not easily measured by standardized examinations 2–4 . York et al.…”

“…1 A recent surge in investigations seeks to enhance professional student success and determine primary non-cognitive skills associated with such success, often not easily measured by standardized examinations. [2][3][4] York et al delineated six core components to define academic success: satisfaction, academic achievement, acquisition of skills and competencies, attainment of learning objectives, and career success. Growing evidence links such non-cognitive factors as critical for not only academic performance, 5 but physical and psychological wellness [6][7][8] alongside a degree of professional engagement.…”