Personality traits and emotional status affecting academic achievements of medical students: testifying mediating effect of learning strategies

1. Background

Almost all medical students feel pressed to gain success in the academic program. Medical students are expected to complete academic requirements of class attendance, clinical practice, written and clinical performance exams, and seminars during the program. Students employ various learning strategies such as critical thinking and pre-testing to perform successfully, and personality traits and emotional status work in this context. It is essential to identify how these variables interrelatedly affect the academic achievements of medical students to get positive outcomes both for learners and educators in medical schools. However, studies in Korea have not much explored the causal relationships among these variables.

2. Learning strategies and academic achievements

Self-regulated learning is one of the main ways of education in various academic fields. Learning strategies mean the clusters of related learning activities that students have at their disposal in reaction to a specific learning goal [1]. Medical students use a variety of learning strategies not only to cope with program requirements but also to gain academic success. Medical students control their thoughts and cognition and concentrate their minds to achieve academic success. Hence, using efficient learning strategies is essential for the successful academic achievement of medical students [2]. Strategic learning is also a prerequisite for academic success and high-quality patient care in the future [1].

Medical students generally employ multi-dimensional learning strategies. They mostly use three learning strategies among various learning strategies cognitive, meta-cognitive, and resource-oriented [1]. Cognitive strategies include organization, critical thinking, development, and rehearsal of learning material and serve as information collection at lectures and seminars. Metacognitive strategies consist of planning (setting goals), regulating, and monitoring the learning processes and help students to control and regulate their cognition. Resource-oriented strategies are effort regulation and time management (intrinsic) and managing the study environment, peer-learning, and the use of additional literature (extrinsic) [1].

Various learning strategies were significantly correlated with the academic success of the medical students [2,3]. Self-regulated learning directly correlates with academic achievement among undergraduate premedical students [2]. Self-regulated learning and meta-cognitive learning strategies positively affect medical students’ academic performance [3]. Self-regulated learners independently plan to learn goals, control the study environment, and monitor their progress with an internal motivation to learn. Students’ self-regulated learning leads to more successful academic achievements [2].

3. Personality traits and emotional status

While students employ learning strategies to gain academic achievements, personality and emotional traits work in this context. Personality traits and emotional status often impact the learning strategies and academic achievements of medical students.

Self-efficacy is a person’s belief in their capability to carry out specific tasks with success [2]. Self-efficacy is the principal capacity to organize study activities and mobilize the study environment. Self-efficacy motivates the students’ capabilities to fulfill academic goals and tasks [3]. Self-efficacy is a crucial determinant of students’ learning strategies because self-efficacy affects self-regulatory processes, including goal setting, self-surveillance, and self-assessment [4]. Further, self-efficacy affects academic emotions [5-7]. Thus, self-efficacy is the most distinguished personality trait affecting students’ academic performance. High-level self-efficacy predicted a high academic performance of medical students [8,9].

Medical students commonly report negative emotions such as anxiety and depression with stress during the academic program. Anxiety is an emotional state consisting of feeling, tension, and apprehension which affects an individual’s nervous system [10]. There are negative relationships between anxiety and academic achievements among medical students [10] and between negative emotions and academic achievement among medical students [5]. Contrarily, positive emotions are positively associated with the academic performance of medical students [11]. Further, positive emotions such as enjoyment, hope, and pride motivate self-regulated learning strategies of medical students [12] and, consequently, high-level academic achievements of medical students [3].

4. Causal relationships among variables

The relationship between learning strategies, academic achievements, personality traits, and emotional status is complex. However, researchers in Korea have not recognized the interrelated relationships among these variables [13-18]. Prior studies on the academic achievements of medical students in Korea have mainly examined the relationships between the variables [13-18]. The prior studies found that resilience [13], motivation and neuroticism [14,15], integrity and extroversion [16], and self-regulation [18] of personality traits, test anxiety and academic burnout [13] among emotional status, and rehearsal strategy [16], organization, elaboration, critical thinking, and time management [17] as learning strategies were significantly related with academic achievements of medical students.

Therefore, most studies in Korea have neglected to explore the direct and indirect effects of these variables on the academic achievements of medical students. One study abroad highlighted that students’ efficacy significantly impacted their learning-related emotions and meta-cognitive learning strategies, and meta-cognitive strategies significantly mediated the effect of the feelings on academic performance [3].

Based on the above discussions, we hypothesized as follows.

H1. Competent personality traits will reduce the negative emotional status, but encourage efficient learning strategies and improve academic achievements.

H2. Negative emotional status will discourage efficient learning strategies and reduce academic achievements.

H3. Efficient learning strategies will increase academic achievement, thus will mediate the relationships among personality traits, emotional status, and academic achievements.

1. Study sample and measurement

We recruited the study sample using a cross-sectional research design. The sample was composed of 424 medical students in the academic year of 2020 at the Gyeongsang National University College of Medicine. The school program is a 6-year program consisting of a 2-year premedical course and a 4-year medical course.

All the 424 students participated in the survey and assessed their academic achievements with personality traits, emotional status, and learning strategies using the Multi-dimensional Learning Strategy Test-Ⅱ (MLST-Ⅱ). The MLST-Ⅱ is the instrument developed by professor DH Park (the Insight of Psychology, Seoul, Korea), made up of items assessing the students’ traits and academic-related achievements.

Personality traits were assessed as percentiles of self-efficacy, expectation, and integrity. Emotional status was evaluated as percentiles of depression, anxiety, and petulance. Self-regulated learning strategies were evaluated as percentiles of four strategies concentrating, reading, memorizing, and testing. Self-assessed performance and percentiles of satisfaction degree of performance assessed the academic achievements. Self-assessed performance was assessed as high (5), mid-high (4), middle (3), mid-low (2), and low (1).

This study analyzed the internal consistency for each scale in the questionnaire. A Cronbach’s α value of at least 0.6 indicates acceptable. Reliability analyses resulted in 0.729 for personality traits, 0.870 for emotional status, and 0.792 for learning strategies.

2. Statistics

This study used t-test and analysis of variance to compare the levels of academic achievements of medical students according to gender and schooling year. A p-value of <0.05 was accepted to be statistically significant. This study used structural equation modeling (SEM) to identify the causal relationships among personality traits, emotional status, learning strategies, and academic achievements and to testify mediating effect of learning strategies in the relationships. The SEM is a valid and reliable statistical tool to construct causal relationships of the data collected on a cross-sectional design. The normality test found that all the variables are within the recommended criteria of skewness (<3.00) and kurtosis (<10.00).

Goodness-of-fit indexes of the path model used the absolute fit measures such as chi-square (χ²) and root mean squared error of approximation (RMSEA), and incremental fit measures such as normal fit index (NFI), Tucker-Lewis index (TLI), and comparative fit index (CFI) to show a good fit between the path model and the data. A Q (χ²/pdf) below 2 is considered good, between 3–5 to be the reasonable cutoff criterion. RMSEA below 0.05 indicates a good fit, but below 0.08 shows a reasonable fit. NFI, TLI, and CFI greater than 0.90 indicate a good fit [19,20]. IBM SPSS Statistics ver. 25.00 (IBM Corp., Armonk, USA) was used to conduct statistical analyses.

3. Ethical approval

The Institutional Review Board of Gyeongsang National University Hospital approved our study (GNUH-IRB 2022-06-017). The survey was conducted with the informed consent of the students when they were enrolled.

1. Mean differences in personality traits, emotional status, learning strategies, and academic achievements of medical students by gender and schooling year

Of the 424 students, male students comprised 63.4% and female students 36.6%. The first-year and second-year students of the premedical course consisted of 13.0% and 12.3%, and the first-year, second-year, third-year, and fourth-year students of the medical course consisted of 19.6%, 17.9%, 19.6%, and 17.7%, respectively.

Medical students showed higher integrity (mean=66.79) than self-efficacy (mean=65.41) and expectation (mean=49.32). Personality traits of medical students were not significantly different by gender but significantly different by schooling year. All the self-efficacy, expectation, and integrity reached the highest level in the first year of the premedical course but reduced to the lowest level in the first year of the medical course. The level rebounded in the second year of the medical course but decreased again in the third year (Table 1).

Table 1.

Mean Values of Personality Traits, Emotional Status, Learning Strategies, and Academic Achievements of Medical Students by Gender and Schooling Year (N = 424)

Medical students showed higher anxiety (mean=46.75) than depression (mean=44.43) and petulance (mean=36.15). The emotional status of medical students was not significantly different by gender but significantly different by schooling year. All the depression, anxiety, and petulance were at the lowest level in the first year of the premedical course but increased to the highest level in the first year of the medical course. The level reduced in the second year but increased again in the third year of the medical course (Table 1).

Medical students employed concentrating strategy (mean=63.93) more than reading (mean=61.16), memorizing (mean=58.27), and testing (mean=60.81) strategies. Learning strategies of medical students were not significantly different by gender but significantly different by schooling year (concentrating, p<0.01; reading, p<0.001; memorizing, p<0.001; and testing, p<0.001). All the strategies reached the highest level in the first year of the premedical course but reduced to the lowest in the first year of the medical course. The level rebounded in the second year but decreased again in the third year of the medical course (Table 1).

Self-assessed performance of medical students was significantly different by gender, with female students assessing their performance higher (mean=3.27) than male students (mean=2.94). However, the satisfaction degree of performance did not show any group difference (female, 53.42 and male, 52.12; t=-1.200). Schooling year did not show any significant group difference for self-assessed performance (1st premed, 3.45; 2nd premed, 3.00; 1st med, 2.86; 2nd med, 3.13; 3rd med, 2.95; and 4th med, 3.08; F=2.033 and p>0.5). Still, the first-year students of the premedical course responded with the highest satisfaction degree of performance (mean=59.14) than any other students (2nd-year premedical course, 54.19; 1st medical course, 51.25; 2nd medical course, 51.41; 3rd medical course, 51.11; and 4th medical course, 50.04), which gradually decreased along with schooling years (F=5.660 and p<0.001) (Table 1).

2. Correlation analyses between variables

Correlation analyses showed that personality traits were negatively associated with emotional status (r=-0.275, p<0.01, and personality traits were positively associated with learning strategies (r=0.631, p<0.01). Personality traits were also positively related to self-assessed performance (r=0.367, p<0.01) and satisfaction degree of performance (r=0.347, p<0.01) of medical students. The emotional status was negatively associated with learning strategies (r=-0.467, p<0.01), self-assessed performance (r=-0.187, p<0.01), and satisfaction degree of performance (r=-0.330, p<0.01) of medical students. Learning strategies were positively associated with self-assessed performance (r=0.385, p<0.01) and satisfaction degree of performance (r=0.372, p<0.01) of medical students (Table 2).

Table 2.

Pearson’s Correlation Coefficients between Variables

3. Causal relationships among latent variables

This study created a conceptual path model to identify the causal relationships among personality traits, emotional status, learning strategies, and academic achievements of medical students and to testify mediating effect of learning strategies on academic achievements of medical students using the SEM. This study constructed possible paths based on the discussion above. Goodness-of-fit indexes within the recommended criteria show a good fit between the path model and the data (χ²=122.834, degrees of freedom [df]=44, χ²/df=2.769, NFI=0.946, TLI=0.946, CFI=0.964, RMSEA=0.065) (Table 3).

Table 3.

Goodness-of-Fit Indexes of the Path Model

The path model’s coefficients (standardized regression weights) were statistically significant at the 0.05, 0.01, or 0.001 levels. The first path in the model demonstrates that personality traits directly affect academic achievements (β=0.299, p=0.010). The second path in the model demonstrates that personality traits affect emotional status (β=-0.321, p<0.001)) which in turn affect academic achievements (β=-0.184, p=0.008). Thus, personality traits indirectly affect academic achievements via emotional status, which partially mediates this relationship (β=0.059). The third path in the model demonstrates that personality traits affect learning strategies (β=0.723, p<0.001), which in turn affect academic achievements (β=0.302, p=0.021). Thus, personality traits indirectly affect academic achievements via learning strategies which partially mediates this relationship (β=0.218). The fourth path in the model demonstrates that personality traits first affect emotional status (β=-0.321, p<0.001), following emotional status affecting learning strategies (β=-0.213, p<0.001), and further, learning strategies involving academic achievements (β=0.302, p=0.021). Thus, personality traits indirectly affect academic achievements via emotional status and learning strategies which partially mediate this relationship (β=0.021).

All together, personality traits indirectly affect academic achievements through three multiple paths in the model, where learning strategies mediate the relationship between personality traits and academic achievements and the relationship between emotional status and academic achievements of medical students. Indirect effect (β=0.298) is calculated with [(-0.321×-0.184)+(0.723×0.302)+(-0.321×-0.213×0.302)] (Table 4). Therefore, it could explain that the more competent personality traits are, the less negative emotional status is, the more efficient learning strategies are, and the higher academic achievements are. All these findings support our hypotheses. Fig. 1 illustrates the path model integrating three multiple paths with all latent variables.

Table 4.

Estimates of the Latent Variables in the Path Model

Fig. 1.

Path Model of Latent Variables