Abstract
Longitudinal research has provided systematic empirical data on the short- and long-term outcomes of admissions policies, curricular innovations, and complex decisions on students’ academic progress. This study aimed to investigate the academic performance of medical students and related factors using cohort database collected from a medical school. The study participants included 134 medical students who graduated from Chonnam National University Medical School in 2022. The medical school’s cohort database was used to collect data on demographics, admission, academic performance, extracurricular activities, and performance on the National Korean Medical Licensing Examination (KMLE). Participating in club activities had a significant association with medical students’ academic advancement delay or leave of absence during the entire course of medical school (P = 0.007). Logistic regression analysis indicated that the nationwide clinical knowledge mock examination during the fourth year of medical school was significantly associated with passing the KMLE (adjusted odds ratio 1.12, 95% confidence interval 1.02–1.22; P = 0.014). Extracurricular school activities (a non-cognitive student attribute) and a wide range of cognitive student attributes captured from the cohort database were associated with medical students’ academic performance. In conclusion, this study can reinforce a strong emphasis on the inclusion of cognitive and non-cognitive information in medical school curricula and assessments in order to improve medical education programs and future postgraduate performance.
Introduction
The goal of medical education is to produce competent physicians with cognitive and critical thinking skills as well as interpersonal skills in response to scientific advances and societal needs [1, 2]. To accomplish the desired outcome of producing well-rounded physicians, the paradigm of medical education has shifted to competency-based education and outcome evaluation [2]. Existing outcomes of medical school activities relevant to individual student competencies from admission to graduation can be useful to better understand how to develop competent, compassionate physicians [3]. Longitudinal databases in medical education are essential to understand how behavioral competence develop in order to set appropriate standards, and this requires following students over the full course of their educational activities [4].
Despite the importance of non-cognitive factors—defined as soft skills related to motivation, attitude, and temperament—in shaping the development of empathetic and compassionate physicians, medical curricula often lack strategies to cultivate these essential qualities [5, 6]. Medical schools often conduct longitudinal research on specific cohorts of medical students to gain a comprehensive understanding of their academic and clinical performance, as well as professional behavior, throughout the medical educational journey [7]. Most related longitudinal studies have found academic abilities (such as preclinical and clerkship grade point average [GPA], written and clinical examination scores) in medical school could predict future professional performance [8–11]. Non-cognitive factors, such as personality and behavioral qualities, have also been as significant contributors to postgraduate clinical competence [7, 12]. However, the findings were inconsistent regarding the associations between non-cognitive factors and academic outcomes [5]. Perceived stress, conscientiousness, and academic resilience were not associated with academic performance [5, 13–15]. Farrington et al. emphasized academic performance was a complex phenomenon in which cognitive and non-cognitive factors continuously interacted to create learning [6]. Therefore, it is necessary to determine association between predictor variables (including cognitive and non-cognitive student attribute) and criterion variables measured during or at the end of the course reflecting academic and clinical performance. While existing cohort studies have investigated cognitive and non-cognitive factors as predictors of academic performance in medical school [7, 16], there remains insufficient literature on this topic to draw comprehensive conclusions.
This study aimed to investigate the academic achievement of medical students and related factors using cohort database collected from a medical school. The research questions were as follows:
1) Which factors are associated with academic achievement indicators, such as academic advancement delay and leave of absence during the entire course of medical school?
2) Which factors affect final outcomes at the time of medical school graduation in terms of passing or failing the Korean Medical Licensing Examination (KMLE)?
Methods
Study design
A retrospective cohort study was conducted on 134 graduates who consented to have their academic performance and related factors investigated from admission to graduation. This study used data from the cohort database at Chonnam National University Medical School, which is a collection of routinely captured educational data spanning the continuum from undergraduate medical education (UME, medical school leading up to the Medical Doctor degree) to graduate medical education (GME, residency training, also known as postgraduate education, leading to eligibility for specialty board certification).
Study participants
The study participants were a total of 134 medical students who graduated from Chonnam National University Medical School in 2022. The study was approved by the Chonnam National University Institutional Review Board (IRB No. CNUH-2022-404). All participants received a detailed explanation about their participation in the study and provided written consent to the use of their data.
Data collection
Available UME-enrollee data included demographics (e.g., age, gender, residential area), admissions data (e.g., admission type, College Scholastic Ability Test [CSAT] grades), extracurricular activity data (e.g., club activities, student research program), academic performance data (e.g., GPA, academic advancement delay or leave of absence, nationwide medical knowledge mock examination score, regional clinical skills assessment score).
Admission data were collected from admission type and CSAT grades. Admission type was classified as regular, rolling, or transfer. In the regular admissions process, students were selected based on the results of the CSAT; for rolling admissions, students were selected based on high school grades and achieving the minimum academic ability standard on the CSAT; and for transfer admissions, students were selected based on the medical education eligibility test and university grades. Students in the area where the school is located are likely to apply for the rolling admissions or transfer programs, where school grades are more important than CSAT scores. The CSAT is divided into 9 grades. The top 4% of the standard scores are grade 1, 4–11% are grade 2, 11–23% are grade 3, 23–40% are grade 4, 40–60% are grade 5, 60–77% are grade 6, 77–89% are grade 7, 89–96% are grade 8, and 96–100% are grade 9.
Extracurricular activity data included club activities and participation in student research programs. There were a total of 30 clubs, including 15 for hobbies such as music, photography, literature, sports, and dance; 10 that promote friendship between seniors and juniors; and 5 for volunteer or religious activities. Students are free to join any number of clubs during the premedical course. Those who did not join a club during the premedical course or who stopped participating in clubs were classified as ‘no’. Student research programs allow students to participate in experimental research under the supervision of a professor in the department of basic or clinical medicine through our Medical Science Research Institute, or to be selected for an overseas basic clinical practice program and participate in experimental research under the guidance of an instructor from another medical institution during a vacation period.
Academic performance data were measured by GPA, academic advancement delay or leave of absence, and examination scores. GPA is calculated on a 4.5-point scale, and when converted to 100 points, 4.5 points (A+) equate to 95–100 points, and 1.0 point (D0) equates to 60–64 points. ‘Academic advancement delay’ refers to a student’s failure to advance to the next academic level according to the regulations—if he or she achieves either a GPA below 2.0 (C0) on the 4.5-point scale or any ‘F’ grades. The student will be withdrawn if he or she fails to meet academic advancement criteria on three occasions. ‘Leave of absence’ refers to a suspension of studies due to poor academic performance, illness, or other personal reasons. Many medical students take a leave of absence when they are unable to adapt to the high academic load or if they anticipate that they will not be able to meet the academic advancement criteria [17, 18].
Available GME-enrollee data included national exams (e.g., KMLE, Clinical Knowledge Assessment [CKA], Clinical Skills Assessment [CSA]). The national passing rate for graduates on the KMLE is approximately 94–95% per year.
We tried to obtain measurements for all variables used in this study to avoid information bias, and measurements of all variables were collected.
Statistical analysis
Only psychological tests with many missing values were excluded; all other variables were used in the analysis. We used Student’s t-tests and chi-square tests to determine factors associated with academic advancement delay or leave of absence, as well as factors associated with passing the KMLE. Logistic regression analysis was used to investigate factors associated with passing the KMLE. All analyses were performed using SPSS Statistics for Windows, version 26.0 (IBM Corp., Armonk, NY, USA).
Results
Descriptive statistics
Eighty-five (63.4%) male students and 49 (36.6%) female students were included in the analysis. There were 89 (66.4%) students who resided in the area in where the school is located. Regarding the college entrance process, 45 (39.1%) students qualified through point-based regular admission. Overall, the students received a high average grade of 1.1 in the CSAT. Most students (93.3%) were participating in club activities, and only ten (7.5%) students were in student research programs (Table 1).
Table 1. General characteristics of fourth year medical students (N = 134).
| Variable | Classification | Value, n (%) or mean ± SD |
|---|---|---|
| Gender | Male | 85 (63.4) |
| Female | 49 (36.6) | |
| Residential area | Area where the school is located | 89 (66.4) |
| Others | 45 (33.6) | |
| Admission type | Regular admission | 45 (39.1) |
| Rolling | 31 (27.0) | |
| Transfer | 39 (33.9) | |
| College Scholastic Ability Test gradesa (Language Arts, Mathematics, English) | 1.1 ± 0.2 | |
| Club activities | Yes | 125 (93.3) |
| No | 9 (6.7) | |
| Student research program | Yes | 10 (7.5) |
| No | 124 (92.5) | |
aPresented on a scale from 1 to 9. The top 4% of the standard scores are grade 1, 4%-11% are grade 2, 11%-23% are grade 3, 23%-40% are grade 4, 40%-60% are grade 5, 60%-77% are grade 6, 77%-89% are grade 7, 89%-96% are grade 8, and 96%-100% are grade 9. SD, standard deviation
Academic achievement during medical school
The medical students achieved mean GPA of 3.1 ± 0.7 in the 2-year premedical course and a mean GPA of 3.3 ± 0.5 in the 4-year medical course. Overall, 19 (14.2%) students experienced academic advancement delay or leave of absence during the medical school program. The students achieved a mean T-score of 114 ± 18.1 on the nationwide basic medicine mock examination during the first year of medical school and a mean T-score of 100 ± 16.0 on the nationwide clinical knowledge mock examination during the fourth year of medical school. Additionally, the students achieved a mean T-score of 50 ± 10.0 on the regional clinical skills assessment. Of the 133 students, 122 (91.7%) passed the KMLE CKA and KMLE CSA. There were seven (5.3%) and five (3.8%) students who failed the KMLE CKA and KMLE CSA, respectively (Table 2).
Table 2. Academic achievement during medical school.
| Variable | Classification | Value, n (%) or mean ± SD |
|---|---|---|
| GPA during the premedical course | 3.1 ± 0.7 | |
| GPA during the first year of medical school | 3.3 ± 0.7 | |
| GPA during the second year of medical school | 3.2 ± 0.6 | |
| GPA during the third year of medical school | 3.6 ± 0.5 | |
| GPA during the fourth year of medical school | 3.3 ± 0.6 | |
| GPA throughout medical course | 3.3 ± 0.5 | |
| Academic advancement delay or leave of absence in the medical course | Yes | 19 (14.2) |
| No | 115 (85.8) | |
| Nationwide basic medicine mock examination during the first year of medical schoola (T-score) | 114.0 ± 18.1 | |
| Nationwide clinical knowledge mock examination during the fourth year of medical schoola (T-score) | 100.0 ± 16.0 | |
| Regional clinical skills assessment during the fourth year of medical schoolb (T-score) | 50.0 ± 10.0 | |
| KMLE CKA and CSA | Pass | 122 (91.7) |
| Fail | 11 (8.3) | |
| KMLE CKA | Pass | 126 (94.7) |
| Fail | 7 (5.3) | |
| KMLE CSA | Pass | 128 (96.2) |
| Fail | 5 (3.8) | |
aNationwide basic medicine and clinical knowledge mock examinations are governed by the Medical Education Assessment Consortium of the Korean Association of Medical Colleges.
bRegional clinical knowledge mock examination is organised by a five-medical school consortium. The third- and fourth-year clinical skills mock assessments are organised by Jeolla Consortium for Standardized Patient Education. GPA, grade point average; KMLE, Korean Medical Licensing Examination; CKA, Clinical Knowledge Assessment; CSA, Clinical Skills Assessment; SD, standard deviation
Factors associated with medical students’ failure experiences
Participating in club activities had a significant association with medical students’ academic advancement delay or leave of absence (P = 0.007). Compared with 15(12.0%) of 125 students who participated in club activities, four (44.4%) of 9 students who did not participate in club activities experienced academic advancement delay or leave of absence. On the other hand, other variables, such as gender, residential area, and student research program participation, had no significant association with academic advancement delay or leave of absence (Table 3).
Table 3. Academic advancement delay or leave of absence according to the general characteristics of medical students.
| Variable | No (n = 115) | Yes (n = 19) | P-value |
|---|---|---|---|
| Gender | 0.979 | ||
| Male | 73 (85.9) | 12 (14.1) | |
| Female | 42 (85.7) | 7 (14.3) | |
| Residential area | 0.745 | ||
| Area where the school is located | 77 (86.5) | 12 (13.5) | |
| Others | 38 (84.4) | 7 (13.6) | |
| Club activities | 0.007 | ||
| Yes | 110 (88.0) | 15 (12.0) | |
| No | 5 (55.6) | 4 (44.4) | |
| Student research program | 0.181 | ||
| Yes | 10 (100.0) | 0 (0.0) | |
| No | 105 (84.7) | 19 (15.3) |
Data are presented as n (%).
Factors associated with passing the KMLE
Overall, high medical school GPA (P < 0.001), experience of academic advancement delay or leave of absence (P = 0.021), high nationwide basic medicine mock examination score (P = 0.028), high nationwide clinical knowledge mock examination score (P < 0.001), and high regional clinical skills assessment score (P < 0.001) were significantly associated with passing the KMLE. Students who passed the KMLE achieved higher GPA scores (mean 3.4 ± 0.5) than those who did not pass the KMLE (mean 2.8 ± 0.3). Of 115 students who did not experience academic advancement delay or leave of absence, 108 (93.9%) passed the KMLE, whereas 14 (77.8%) of 18 students who experienced academic advancement delay or leave of absence passed the final licensure examination. Students with higher scores on the nationwide basic medicine mock examination during the first year of medical school (mean 115 ± 18.1) were more likely to pass the KMLE than those with lower scores (mean 102.5 ± 14.9). Students who achieved higher scores on the nationwide clinical knowledge mock examination of the fourth year of medical school (mean 102.2 ± 14.6) were more likely to pass the KMLE than those who achieved lower scores (mean 77.4 ± 12.2). Finally, students who performed well on the regional clinical skills assessment of the fourth year of medical school (mean 115.0 ± 18.1) were more likely to pass the KMLE than those who did not perform well (mean 102.5 ± 14.9) (Table 4).
Table 4. Factors associated with passing the Korean Medical Licensing Examination.
| Variable | Pass (n = 122) | Fail (n = 11) | P-value |
|---|---|---|---|
| Gender | 0.046 | ||
| Male | 74 (88.1) | 10 (11.9) | |
| Female | 48 (98.0) | 1 (2.0) | |
| Residential area | 0.669 | ||
| Area where the school is located | 81 (91.0) | 8 (9.0) | |
| Others | 41 (93.2) | 3 (6.8) | |
| Club activities | 0.076 | ||
| Yes | 116 (92.8) | 9 (7.2) | |
| No | 6 (75.0) | 2 (25.0) | |
| Student research program | 0.323 | ||
| Yes | 10 (100.0) | 0 (0.0) | |
| No | 112 (91.1) | 11 (8.9) | |
| GPA of the medical course | 3.4 ± 0.5 | 2.8 ± 0.3 | <0.001 |
| Academic advancement delay or leave of absence in the medical course | 0.021 | ||
| Yes | 14 (77.8) | 4 (22.2) | |
| No | 108 (93.9) | 7 (6.1) | |
| Nationwide basic medicine mock examination during first year of medical school (T-score) | 115.0 ± 18.1 | 102.5 ± 14.9 | 0.028 |
| Nationwide clinical knowledge mock examination during the fourth year of medical school (T-score) | 102.2 ± 14.6 | 77.4 ± 12.2 | <0.001 |
| Regional clinical skills assessment during the fourth year of medical school (T-score) | 51.0 ± 9.4 | 39.4 ± 11.2 | <0.001 |
Data are presented as n (%) or mean ± standard deviation. GPA, grade point average
Logistic regression analysis indicated that the nationwide clinical knowledge mock examination during the fourth year of medical school was significantly associated with passing the KMLE (adjusted odds ratio 1.12, 95% confidence interval 1.02–1.22; P = 0.014; Table 5).
Table 5. Logistic regression analysis of the factors associated with passing the Korean Medical Licensing Examination.
| Variable | Adjusted OR (95% CI) | P-value |
|---|---|---|
| Gender (ref. Male) | ||
| Female | 1.44 (0.11–19.28) | 0.784 |
| Residential area (ref. Others) | ||
| Area where the school is located | 0.95 (0.16–5.61) | 0.952 |
| Club activities (ref. No) | ||
| Yes | 2.89 (0.14–61.34) | 0.496 |
| GPA throughout medical course | 13.33 (0.34–517.54) | 0.165 |
| Academic advancement delay or leave of absence in the medical course (ref. No) | ||
| Yes | 0.89 (0.14–5.64) | 0.900 |
| Nationwide basic medicine mock examination during first year of medical school (T-score) | 0.98 (0.92–1.05) | 0.635 |
| Nationwide clinical knowledge mock examination during the fourth year of medical school (T-score) | 1.12 (1.02–1.22) | 0.014 |
| Regional clinical skills assessment during the fourth year of medical school (T-score) | 1.07 (0.98–1.18) | 0.144 |
OR, odds ratio; CI, confidence interval; GPA, grade point average
Discussion
This study investigated the academic achievement of medical students and associated factors using cohort data collected from a medical school database.
The contribution of the current study is twofold. First, we found that students’ participation in extracurricular school activities (a non-cognitive student attribute) is significantly associated with academic advancement delay or a leave of absence from the medical school. Specifically, this study extends insight into the importance of persistent participation in extracurricular activities during medical school, which is essential for preventing detrimental academic consequences, such as academic advancement delay or a leave of absence and promoting positive academic outcomes, such as high GPAs [19, 20]. Second, this study revealed that a wide range of assessment measures (cognitive student attributes, e.g., GPA, academic advancement delay, and nationwide medical examination scores) obtained from the existing cohort database within our institution were strongly associated with performance on the KMLE. The findings from this study demonstrate that, to deepen our understandings of students’ performance and the effectiveness of medical education, medical educators and researchers can benefit from using a combination of measures from existing sources [3, 7].
Our study found that consistent involvement in extracurricular activities during medical school was a significant facilitator of improved learning outcomes and academic performance among medical students. This finding aligns with prior studies that have demonstrated extracurricular activities to have a significant impact on quality of life as well as academic performance among medical students [20–22]. Extracurricular activities refer to non–credit-granting and voluntary activities that are carried out by students outside of the medical school curriculum; these can include research, teaching, community, cultural, social, religious, and sporting activities [23]. Medical educators have highly prioritized medical students’ quality of life because it may impact their academic performance and vice versa [21]. The fear of academic advancement delay is the major stressor during medical school, and it can negatively impact medical students’ quality of life [22]. Medical students participate in a variety of academic and extracurricular activities in order to improve their work-life balance [21]. On the other hand, some research has shown that medical institutions tend to heavily focus on extracurricular research programs to enhance research competency because medical students have strong interest in developing professionalism through extracurricular research participation [24]. Conversely, this may lead to negative outcomes, such as stress and burnout [25]. Redundant participation in extracurricular activities can also result in failure in academic examinations [26]. Hence, based on our findings, we contend that extracurricular activities should not only mitigate the stress associated with the fear of academic advancement delay but also improve the overall well-being of medical students. To encourage students to actively participate in extracurricular activities, medical schools should be aware of potential motives for further engagement and remove obstacles that disrupt participation; concurrently, the implementation of faculty mentorship, activity evaluation systems, and career association programs should take place for the further development of extracurricular activities [23, 27].
The evidence from this study suggests that cognitive student attributes related to academic performance during medical school may be predictors of performance on the KMLE and may reflect the strengths and weaknesses of medical education curricula. Specifically, the KMLE, with which prospective physicians are expected to demonstrate professional clinical knowledge and skills, is a profound assessment of the effectiveness of undergraduate medical education programs and a critical predictor of performance during their postgraduate training [8]. In this regard, this study supports the findings from previous studies that pre-clinical performance and exam preparation are significantly associated with performance on medical licensure examinations, such as USMLE (United States Medical Licensing Examination) Step 1 [28, 29]. Likewise, medical students with higher scores in academic and clinical examinations were more likely to demonstrate better outcomes in the KMLE in our study. We may subsequently develop a predictive assessment of clinical competence for physicians in postgraduate professional programs based on such cohort data [3, 28]. However, this research should look beyond relationships between exam performance and associated factors that can be derived from a cohort database. For example, relevant research noted that medical students’ exam-directed study behaviors are positively predictive of high-stakes examination performance [29], and institutional factors such as coaching and help-seeking can be feasible approaches for students at risk of exam failure [30].
This study had several limitations. First, the findings inherently cannot be generalized to other medical education contexts because this study used an existing cohort database from specific medical students at one medical school. Second, we recommend that future studies include a broad range of non-cognitive student attributes such as individual characteristics (e.g., personal traits, interpersonal skills, and self-appraisal), tutor evaluations, and socioeconomic factors, in order to gain a deeper understanding of predictors of academic advancement delay and performance on a medical licensure examination [7, 12]. Third, potential unmeasured confounding factors could affect the interpretation of academic performance and related factors in medical school. For instance, variations in academic ability may arise from different admission types. Reasons for a leave of absence may extend beyond poor academic performance, such as personal or health-related issues. Academic challenges may also impede participation in extracurricular activities. Furthermore, the COVID-19 pandemic could have impacted academic performance through factors like inadequate support, economic hardship, and individual health challenges. Finally, this study findings suggest that medical educators and researchers should have access to the data of individualized learners and use the predictive techniques of learning analytics (LA) to offer early interventions to at-risk medical students because we focused on assessing the relationships between predictors and academic performance in medical examinations [3, 31].
Conclusions
Undergraduate medical students’ participation in extracurricular activities was significantly associated with academic advancement delay or a leave of absence from the medical school. A variety of assessment measures obtained from our medical school’s existing cohort database were highly associated with student performance on the KMLE. In conclusion, this study can reinforce a strong emphasis on the inclusion of cognitive and non-cognitive information in medical school curricula and assessments in order to improve medical education programs and future postgraduate performance.
Data Availability
All relevant data are within the manuscript.
Funding Statement
This study was supported by a grant from the Chonnam National University Hospital Biomedical Research Institute (CRI16028-1). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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Data Availability Statement
All relevant data are within the manuscript.