INTRODUCTION
Medical training is a long (8 to 11 years) and expensive process. The undergraduate program alone has an estimated direct cost of US $ 125,000 to US $ 310,000 depending on the country1-3. In addition, it is a considerable investment of time and money for students and their families. In many countries, there is also a major investment of the government’s money through partial or total subsidies to cover the cost of the program3,4.
Admission processes for medical programs are highly competitive all over the world, possibly due to the prospects of a satisfying and rewarding career, social recognition, and a solid upper-middle-class lifestyle2. However, being accepted to medical school is no guarantee of academic success. Medical programs are demanding and stressful for students. Most students manage this new situation and achieve academic success. However, some are less able to successfully cope with the transition and experience difficulties in adapting to the program routine3-5. Yates and James observed that 10% to 15% of Nottingham University Medical School students experienced some form of adjustment difficulty3,6.
The literature describes several predictive factors of academic success in medical programs, such as prior academic performance; performance in the admission process; and psychological, behavioral, demographic, social and economic factors3,7-10. Most studies evaluate predictive factors of success. The identification of reliable features of students at risk of failure has not been widely studied, and one cannot simply assume that the factors predicting failure are the inverse of those predicting success5.
Predictive factors of academic performance are usually divided into three groups: pre-program, admission process and program factors. Academic performance achieved prior to the admission process is one of the main predictive factors of medical program success4,5,11,12. Some studies have observed an association between worse performance during medical studies and sociodemographic factors such as male gender3,7, non-white ethnicity3,7, age over 24 years7,11 and low socioeconomic background11. Pudey and Mercer also observed an association between a background in humanities in the pre-medical years and academic failure11. High performance in the admission process has also been observed to be an independent factor of success in several studies3,4,7,8,11,12.
Problems related to low academic performance during an educational program can be classified into three types: (1) academic, (2) intrapersonal, and (3) interpersonal problems8. The first group refers to students who achieve low grades, fail courses, and have poor attendance, especially in the first two years3,6,8,13. The second group refers to students who experience personal conflicts or exhibit inappropriate academic behavior or psychiatric disorders, such as excessive anxiety, hypochondria and depression3,8,10. Students classified in the third group experience difficulties in interacting with teachers, colleagues, supervisors or patients8.
A study carried out by Hendren shows that 43% of students who experience academic problems and 29% of students with intrapersonal problems drop out of the program. The dropout rate was found to be much higher among students with interpersonal problems, with only 8% of them completing the program8.
Determining the predictive factors of academic success or failure is beneficial for students and their families, society and educational institutions, because it provides for the creation of mechanisms to identify and support students experiencing difficulties and for the onset of early intervention before students drop out for avoidable reasons3,4.
No study was identified in the literature review on predictive factors of academic performance among medical students in Brazil. The aim of this study is to identify predictive factors of academic failure among students from a Brazilian medical program.
METHOD
Population
The medical program of Universidade José do Rosário Vellano (UNIFENAS) on the Campus of Belo Horizonte, Minas Gerais, Brazil, was founded 17 years ago. It is a 6-year full-time program with pre-clinical years integrated into clinical years and involves a single admission process, occurring at the beginning of the program. Eighty students are admitted each semester, with a total of 160 per year. The university itself conducts the admission process. Low-income students are also admitted through the federal government’s full scholarship program (PROUNI). The government selects these students. The curriculum of the first 4 years is based on problem-based learning approaches and is organized into thematic modules (courses). Due to the curriculum structure, failure in any course during the program delays the student’s graduation.
This study involved four cohorts of students who started the program in 2010 and 2011 with the intention of graduating in 2015 and 2016, respectively. The inclusion criteria were as follows: students entering the program through the institution’s admission process or through PROUNI in 2010 or 2011 and whose academic information was available in the institution’s system. Students admitted through transfers from other institutions or who transferred to other institutions during the study period were excluded.
Data collection
Data were directly collected from the institution’s Academic System using Microsoft Excel® worksheets. The students’ names were removed to keep the study data confidential. The spreadsheets were then integrated into a single database based on each student’s registration number. Data were collected until July 2017.
The following variables were collected: gender, age at admission, marital status, admission type (institution’s process or PROUNI), type of high school (private or public), grade achieved during the admission process (although not for PROUNI students), time interval between finishing high school and admission to the medical program, and grades during and passing grades of first-semester courses. The overall performance during the first semester was calculated from the arithmetic mean of course grades. Students with grades ≥ 60% and frequency ≥ 75% passed each course according to the institution’s criteria. Four courses are offered in the first semester. The first is entitled Introduction to the Study of Medicine, which describes the program, trains the students for problem-based learning tutorial groups, and addresses basic concepts related to homeostasis, physiology, cytohistology, and anatomy. The second course, Hemorrhage and Shock, addresses the physiology, histology, and anatomy of the cardiovascular system. The third course, Oliguria, and the fourth, Dyspnea, address the same aspects regarding the genitourinary and respiratory tracts, respectively.
The study outcome was academic performance. Academic failure was defined as graduation delay (> 6 years) or dropping out of the program (Group 1). Academic success was defined as achieving graduation 6 years after program admission (Group 2).
Statistical analysis
Two separate statistical analyses were performed, because a failure in any course implies graduation delay. The first analysis involved all students entering the program (freshman students), and all variables were considered, except for grades and achieving passing grades at the first-semester courses. For the second analysis, only students who passed the first-semester courses were considered (students with passing grades), and all variables were included, with the exception of course approval.
A descriptive analysis was performed for each variable, based on the frequency distribution of categorical variables and using means and standard deviations for continuous variables. A chi-square test was performed to compare the categorical variables, and Student’s t test was applied to measure the continuous variables. Logistic regression was performed using the stepwise technique for variables with p <0.20. For continuous variables related to academic failure, according to the logistic regression, a ROC curve analysis was performed. The level of significance was set at 0.05. The software SPSS 19 (IBM, USA) and Stata 12.1 (StataCorp, USA) were used for our statistical analysis.
RESULTS
Three hundred and twelve students were admitted in 2010 and 2011, but seven were excluded because they transferred to other programs during the study period. Three other students were removed from the study due to conflicting academic information. The final sample consisted of 302 students (freshman students). Group 1 (academic failure) included 105 students, and Group 2 (academic success) included 197 students (Figure 1). The following causes of academic failure were identified: dropped out of the program (27 students - 25.7%) and graduation delay (78 students - 74.3%). Of these, 58 graduated late, and 20 were still completing the program as of July 2017. Of the 302 students, 32 students failed at least one course in the first semester. The second analysis covered 270 participants (students with passing grades), of whom 73 were in Group 1 and 197 were in Group 2 (Figure 1).
Table 1 shows sociodemographic and academic data for the freshman students. The majority was young (20.3 years old), female (193 - 63.9%) and single (295 - 97.7%). Most of them (85.5%) had attended high school at private institutions and had finished high school less than 4 years prior to the medical program admission. Most were admitted through the program’s process (274 - 90.7%), with a mean grade of 80.6 points. Only admission grades showed a statistically significant association with academic failure.
Table 1 Comparative analysis of sociodemographic and academic variables of freshman students according to academic failure (Group 1) or success (Group 2)
Categorical variables | Group 1 (n=105) | Group 2 (n = 197) | Total (n = 302) | p | ||||
---|---|---|---|---|---|---|---|---|
n | % | n | % | n | % | |||
Gender | Female | 60 | 57.1 | 133 | 67.5 | 193 | 63.9 | 0.079 |
Male | 45 | 42.9 | 64 | 32.5 | 109 | 36.1 | ||
Marital status | Single | 103 | 98.1 | 192 | 97.5 | 295 | 97.7 | 0.763 |
Married | 2 | 1.9 | 4 | 2.0 | 6 | 2.0 | ||
Divorced | 0 | 0 | 1 | 5.0 | 1 | 3 | ||
High school type* | Private | 73 | 84.9 | 169 | 85.8 | 242 | 85.5 | 0.843 |
Public | 13 | 15.1 | 28 | 14.2 | 41 | 14.5 | ||
Admission type | Institutional process | 99 | 94.3 | 175 | 88.8 | 274 | 90.7 | 0.120 |
PROUNI | 6 | 5.7 | 22 | 11.2 | 28 | 9.3 | ||
Continuous variables | Mean | SD | Mean | SD | Mean | SD | p | |
Age | 20.2 | 2.8 | 20.3 | 3.6 | 20.3 | 3.3 | 0.636 | |
Time since high school graduation (years)** | 3.4 | 2.7 | 3.7 | 3.5 | 3.6 | 3.2 | 0.346 | |
Admission grades*** | 78.8 | 8.4 | 81.7 | 9.2 | 80.6 | 9.0 | 0.008 |
SD = standard deviation; * no information = 19; ** no information = 3; *** - PROUNI students were not subject to institutional selection.
Table 2 shows sociodemographic and academic data for students who achieved passing grades in the first-semester courses. As for freshman students, admission grades showed a statistically significant association with academic failure. A significant association was also observed between academic failure and first-semester course grades and overall performance.
Table 2 Comparative analysis of sociodemographic and academic variables of the students with passing grades according to academic failure (Group 1) or success (Group 2)
Categorical variables | Group 1 (n=73) | Group 2 (n = 197) | Total (n = 270) | p | |||||
---|---|---|---|---|---|---|---|---|---|
n | % | n | % | n | % | ||||
Gender | Female | 44 | 60.2 | 133 | 67.5 | 177 | 65.6 | 0.266 | |
Male | 29 | 39.7 | 64 | 32.5 | 93 | 34.4 | |||
Marital status | Single | 71 | 97.2 | 192 | 97.5 | 263 | 97.4 | 0.266 | |
Married | 2 | 2.7 | 4 | 2.0 | 6 | 2.2 | |||
Divorced | 0 | 0.0 | 1 | 0.5 | 1 | 0.4 | |||
High school type* | Private | 50 | 68.5 | 169 | 85.6 | 219 | 81.1 | 0.467 | |
Public | 11 | 15.0 | 28 | 14.2 | 39 | 14.4 | |||
Admission type | Institutional process | 67 | 91.8 | 175 | 88.8 | 242 | 89.6 | 0.481 | |
PROUNI | 6 | 8.2 | 22 | 11.2 | 28 | 10.4 | |||
Continuous variables | Mean | SD | Mean | SD | Mean | SD | p | ||
Age | 20.3 | 2.9 | 20.3 | 3.6 | 20.3 | 3.3 | 0.902 | ||
Time since high school graduation (years)** | 3.5 | 2.7 | 3.7 | 3.5 | 3.7 | 3.3 | 0.599 | ||
Admission grades*** | 79.0 | 9.0 | 81.7 | 9.2 | 81.0 | 9.2 | 0.043 | ||
Course | Mean | SD | Mean | SD | Mean | SD | p | ||
Introduction to the Study of Medicine | 77.4 | 6.4 | 82.5 | 5.8 | 81.1 | 6.4 | <0.001 | ||
Hemorrhage and Shock | 76.1 | 6.1 | 81.0 | 5.5 | 79.6 | 6.1 | <0.001 | ||
Oliguria | 77.0 | 7.1 | 82.8 | 5.7 | 81.3 | 6.6 | <0.001 | ||
Dyspnea | 78.4 | 7.1 | 83.5 | 5.9 | 82.1 | 6.6 | <0.001 | ||
Overall performance | 77.2 | 6.1 | 82.4 | 5.2 | 81.0 | 5.9 | <0.001 |
SD = standard deviation; * no information = 19; ** no information = 3; *** - PROUNI students were not subject to institutional selection.
The logistic regression results are shown in Table 3. The following variables were included in the regression model for freshman students: gender, admission type and admission grades. Collinearity was observed between the admission type and admission grades, and the admission type was excluded from the analysis because it did not show a statistically significant association with academic performance. After adjustments, admission grades continued to be statistically associated with academic failure among freshman students. For students with passing grades, the regression model included the following: admission grades, course grades and overall performance. Collinearity was observed between course grades and overall performance because overall performance is the arithmetic mean of course grades. Two logistic regression models were analyzed. Model 1 included admission and course grades, whereas model 2 included admission grades and overall performance. After analyzing the two models, model 2 was chosen, and only overall performance was maintained as a predictive factor of failure.
Table 3 Final logistic regression model for predictive factors of academic failure among freshman students and those with passing grades
Freshman students | Raw p | Adjusted p | |
---|---|---|---|
Gender | 0.079 | 0.084 | |
Admission type* | 0.120 | --- | |
Admission grades** | 0.008 | 0.012 | |
Passing students | Raw p | Adjusted p - Model 1 | Adjusted p - Model 2 |
Admission grades** | 0.043 | 0.857 | 0.729 |
Introduction to the Study of Medicine | <0.001 | 0.061 | --- |
Hemorrhage and Shock | <0.001 | 0.951 | --- |
Oliguria | <0.001 | 0.022 | --- |
Dyspnea | <0.001 | 0.583 | --- |
Overall performance*** | <0.001 | ---- | <0.001 |
*collinearity with admission grades; ** except for PROUNI students; *** collinearity with course grades
A ROC curve analysis was performed on the admission grades of the freshman students (Figure 2A) and on the overall performance of those with passing grades in the first semester (Figure 2B). In both cases, no cutoff point with good sensitivity (identifying students more likely to succeed) and specificity (identifying students more likely to fail) was identified, although the two analyses confirmed the statistical association indicated by the logistic regression.

Figure 2 ROC curve of variables statistically associated with academic failure among freshman students (2A)
Ethical approval
The study was approved by UNIFENAS’s Institutional Review Board (Reference Number 2.006.948) and was carried out in accordance with the current version of the Declaration of Helsinki and its amendments and with Resolution 466/2012 of the National Council of Ethics in Human Research of the Brazilian Health Ministry and its amendments.
DISCUSSION
The objective of this study was to identify predictive factors of academic failure during medical school. Based on a literature review, no similar studies carried out in Brazil were identified, making this study an innovative one.
Two factors were found to be statistically associated with academic failure throughout medical program: grades achieved during the admission process among freshman students and overall performance achieved during the first-semester courses among students with passing grades in that semester. These results corroborate the findings of other authors who observed an independent association between grades during the admission process and academic difficulties in the USA7, Australia11,12, the UK3, and Croatia4. An association between underperformance in the first year and academic failure has also been reported in the literature3,6,8,13.
This study showed no association between academic failure and age, as observed by Andriole and Jeffe7 and by Pudey and Mercer11. There was also no association between male gender and academic failure, as reported by Yates and James3 and by Andriole and Jeffe7. Considering that students from public high schools or students who were admitted through the federal government scholarship program may have low socioeconomic background, no association was observed between these variables and academic failure, as observed by Puddey and Mercer11.
The main limitation of this study lies in its retrospective design and in the use of a secondary database that did not have information on other variables associated with academic performance, such as ethnicity, academic performance prior to entering the medical program and behavioral changes or mental illness. It should be noted that the findings of this study might be specific to the evaluated program, although the study can serve as a model from which other institutions can identify predictive factors of program success or failure.
Despite these limitations, this study has a large sample and, to the best of our knowledge, is the first Brazilian study on academic performance in medical programs. The findings show that it is possible to identify students with a higher risk of experiencing academic failure early in the program. With this information, it is possible to develop intervention strategies to reduce failure and dropout rates throughout the program.
CONCLUSION
Low grades achieved during the admission process and low overall performance in first-semester courses were statistically associated to graduation delay at the UNIFENAS Belo Horizonte medical program. No association was observed between sociodemographic characteristics and academic failure.