The Big Five model that represents the five dimensions of individual behaviors includes extraversion, agreeableness, conscientiousness, emotional stability (neuroticism), and openness to experience (intellect of personality) have attracted the attention of researchers. A literature review showed that personality traits are important in that they define an individual’s tendencies toward certain behaviors in a wide range of functioning (Hoyle, 2006). Also, according to previous research (Poropat, 2009) there was proven that conscientiousness and openness can show stable associations with academic achievement in comparison to other personality traits (Poropat, 2014). Conscientiousness is determined by personal qualities such as responsibility, the ability to plan, organize, and achieve. Additionally, conscientiousness is associated with methodical and analytical learning (Miller et al., 1999; Eisenberg et al., 2014; Roberts et al., 2014). Meanwhile, it was proved that the openness to experience personality trait may reflect an individual’s positive attitude toward the complex learning process and experience (Matz, 2021), and the pursuit of knowledge that is the result of consistent learning (Komarraju et al., 2009; DeYoung, 2015).

According to the theoretical background, academic performance refers to the level of achievement or success that cadets attain in their academic pursuits, such as coursework, exams, projects, and overall grades. It reflects their ability to grasp and apply knowledge, meet academic requirements, and demonstrate their understanding of the subjects they are studying. Achieving academic success can boost students’ self-confidence and belief in their abilities. When students perform well academically, they develop a sense of competence and a belief that they can tackle new challenges, experience a sense of accomplishment, and reduced anxiety about their future prospects (Pascarella and Terenzini, 2005). It is important to note that academic success should not be the sole measure of a student’s worth or potential. Each student is unique, and success can be defined in various ways beyond academic achievements (Ransdell, 2001). Various studies have explored the relationship between personality traits and academic performance, and some consistent findings have emerged. The results of the Hakimi et al. (2011) study agreed that conscientiousness was the most significant predictor variable, which enlightened 39 percent of variance in academic achievement, but gender differences in personality characteristics and academic achievement were insignificant; Mateus et al. (2021) identified a correlation between personality traits related to cognitive functioning and academic performance; Mammadov (2022) found that academic performance could be explained by 27.8 percent of the effects of cognitive ability and personality traits, and conscientiousness appeared as a strong and robust predictor of academic performance.

A literature review specified that performance in the military context and personality traits may also be linked. But only certain traits have been found to be particularly relevant and can impact an individual’s effectiveness in military roles. Bobdey et al. (2021) explored the correlation between personality traits of cadets undergoing training at an Armed Forces Training Academy and their performance in terms of their military and academic pursuits. Bobdey et al. (2021) results showed that cadets with high personality traits scores in neuroticism and low scores in conscientiousness had performed poorly in all domains for performance evaluation. Additionally, the conscientiousness facet was found to be positively correlated with performance in academic and military tasks (Fosse et al., 2015).

Similarly, individual’s performance was found in close association with person’s self-efficacy. Self-efficacious individuals tend to approach tasks with confidence and a belief in their ability to succeed (Schunk and Pajares, 2009). This mindset positively influences their performance, as they are more likely to set challenging goals and exert the necessary effort to achieve them. The concept of self-efficacy originated from social cognitive theory, developed by the psychologist Albert Bandura (1997). According to Bandura (1997), self-efficacy plays a central role in motivation, behavior, and personal development. Bandura’s social cognitive theory emphasizes the role of cognitive processes, observational learning, and social interaction in shaping human behavior (Bandura, 2003). Self-efficacy is a key component of this theory as it influences how individuals approach and engage in various activities (Bandura, 2001). Bandura proposed that people with high self-efficacy are more likely to set challenging goals, persevere in the face of obstacles, and exhibit greater effort and resilience compared to those with low self-efficacy. Self-efficacy beliefs are developed from a variety of sources, including personal experiences, social persuasion, vicarious learning (observing others), and physiological and emotional states. These beliefs influence individuals’ choices, efforts, and resilience in the face of difficulties (Kanapeckaitė et al., 2022; Bekesiene et al., 2023). Recent research on occupational self-efficacy showed that self-efficacy increases persons’ belief and confidence in performing the tasks, challenges, and stresses associated with their profession (Li et al., 2022; Mei et al., 2022). Additionally, according to the Guo et al. (2017) study, higher occupational self-efficacy can motivate more people to solve work-related problems. Furthermore, researchers have shown that students with lower academic self-efficacy are at increased risk of academic burnout (Yu et al., 2016).

Taking into account the existing literature and theoretical assumptions, direct pathways were hypothesized from five personality traits to self-efficacy, academic, and military performance in the proposed model (see Figure 1):

Direct effect of five personality traits on self-efficacy:

Direct effect of five personality traits on academic performance:

Direct effect of five personality traits on military performance:

Bandura’s social cognitive theory and the concept of self-efficacy have been widely applied in various fields, including psychology, education, health, and organizational behavior, to understand and enhance human performance and well-being. The available literature suggests that personality factors and self-efficacy are consistently associated with each other (Ahmadi et al., 2023). Additionally, a recently conducted study confirmed that personality factors and self-efficacy can help improve student performance by manipulating their interest, goal line, and learning are predominantly considered predictors rather than consequences of academic performance (Wang et al., 2023). Previous research conducted has shown that the relationship between personality traits and student performance may be mediated by self-efficacy. Di Giunta et al. (2013) showed that self-efficacy can play an intermediate role in the relationship between conscientiousness and openness and academic achievement. Furthermore, Caprara et al. (2011) confirmed mediation of self-efficacy between conscientiousness and academic achievements in the longitudinal study. Additionally, the results of the Hayat et al. (2020) study showed that individual differences in personality traits directly and indirectly play an essential role, through self-efficacy, in contributing to student academic performance; the positive indirect effect of conscientiousness and openness, and the negative indirect effect of neuroticism on academic performance through self-efficacy was confirmed.

Building and maintaining self-efficacy in the military often involves a combination of training, experience, positive reinforcement, mentorship, and providing opportunities for individuals to demonstrate and develop their skills (McCrory et al., 2013). By fostering a sense of self-efficacy among service members, military organizations can improve individual and collective effectiveness, as well as promote the overall well-being and resilience of their personnel (Bekesiene et al., 2023). Considering meaning in military performance as a complex individual construct, indirect pathways linking it to personality dimensions become significant. Following Fosse et al. (2015) it is not enough to take into account only personality traits characteristics as representations to evaluate if the performance of the cadets is suitable, and self-efficacy must also be included. It is especially true in the context of military performance, which refers to an individual’s belief in their own abilities to successfully perform specific tasks or achieve specific goals. Having a strong sense of self-efficacy in the military can lead to improved decision-making, adaptability, and overall mission success (Bekesiene et al., 2022; Lucier-Greer et al., 2022; Qiu et al., 2023). It helps individuals to believe in their own abilities to perform their duties and contribute effectively to the team or unit. In contrast, low self-efficacy can lead to self-doubt, decreased motivation, and potentially impact performance and mission outcomes. Therefore, professional self-efficacy may play an important role in the academic and military achievements of the cadets. However, there is little evidence to support the relationship between professional self-efficacy and levels of academic and military burnout among military academy students.

Taking into account the aspects of studies in the military academy, it can be expected that the military performance of the cadets was strengthened by the individual’s belief in their own abilities to successfully perform specific tasks or achieve specific goals. Therefore, the indirect effect of five personality traits on the academic and military performance of cadets through self-efficacy was hypothesized:

Mediation effect of self-efficacy on academic performance:

Mediation effect of self-efficacy on academic performance:

This study employed a random sampling method. Data were collected through self-reported questionnaires applied digitally (Google Forms) in spring 2023 in Lithuanian Military Academy (LMA). Before filling out the questionnaire, the cadets were informed of the ethical principles of anonymity and confidentiality of the data to be collected. The participation was fully voluntary with no rewards. The sample included 120 cadets attending the 3rd and 4th courses of the LMA. This contained within 80 men (77,5%) and 27 women (22,5%). The average age of the cadets was 21.9 years (±SD = 1.18, range = 20–27 years). Most of the 112 (92,5%) cadets had secondary school education and confirmed they had no previous military experience. In relations of age and military skills, the cadets of Lithuanian Military Academy in general are comparable with those of other NATO nations. Each participant was provided with information about the study; informed consent was obtained from all students before starting the study; their voluntary participation and anonymity were ensured.

Before all statistical analyzes the sample size evaluation test was conducted by using well-known G∗Power v3.1.9.4 package. The F tests for Linear multiple regression was based on five predictors with a significance level of 0.05, power of 0.90, and effect size of 0.15. was defined that to reach statistical power is required a sample size of 116. Additionally, the post-hoc test was performed to compute achieved power with significance level of 0.05, the sample size of 120 (a valid data set was used), and effect size of 0.15; it helped to reveal that even with the sample size of 114 can be reached the statistical power equal to 0.9129. Statistical studies were performed using IBM SPSS Statistics 29v and SPSS AMOS 29v. The individual level of analysis was used for collected demographic data and study constructs: (i) extraversion of five personality traits (EXTR), conscientiousness (CONC), emotional stability (EMO), openness to experience (OPEN), and agreeableness (AGRE); (ii) self-efficacy (SFE); (iii) academic performance (ACP) and (iv) military performance (MLP). The descriptive statistic was used to evaluate the statistical means and standard deviations (M and ± SD) of the variables, and then the Pearson bivariate correlation procedure was used to evaluate the relationships. To reduce the influence of common method bias in the study were used two different methods: first approach focused on developing instruments that emphasized anonymity and confidentiality of responses; as second approach Harman’s single-factor test was used to investigate the potential variance of the common method (Tehseen et al., 2017). The convergence of variables constructs was evaluated by average variance extracted (AVE) and composite reliability (CR) (Fornell and Larcker, 1981). Also, the discriminant validity and confidence intervals were used to demonstrate discriminant validity between constructs (Tehseen et al., 2017). Structural Equation Modeling Analysis (SEMA) was used to assess the hypothesized model. Before modeling, there was performed a factor analysis to assess the latent constructs and variables. Only then was the modeling process continued with theoretical causal model path analysis (Byrne, 2013). Causal interactions between eight factors were recognized by SEMA. Theorized direct and indirect links among study constructs were tested in specified four models: Model 1 was conducted to test how five personality traits affect self-efficacy (hypotheses: H1a-H1e); using Model 2 were evaluated pathways among five personality traits and academic performance (hypotheses: H2a-H2e); using Model 3 were tested how five personality traits affect military performance (hypotheses: H3a-H3e); and using Model 4, which was extended by three control variables (course, gender, and age), the theorized indirect effects between all constructs were evaluated (hypotheses: H4a-H4e and H5a-H5e). According to the proposed Model 4 design, 11 variables were recognized: three observed endogenous variables (MLP, SFE, ACP); five observed exogenous variables (EXTR, EMO, AGRE, CONC, and OPEN); and three unobserved exogenous variables.

The hypothesized relations between the model constructs were tested using SPSS AMOS 29v, and the coefficient weights were chosen to assess the causal relations by agreeing with suggestions of previous scholars (Bekesiene et al., 2017a,b, 2022; Smaliukienė et al., 2023) who propose a versatile methodology for assessing the suitability of a theoretical model. Therefore, the goodness of fit of the models was estimated by subsequent criteria: (1) the probability statistic of χ² likelihood ratio, (2) the Tucker and Lewis Index (TLI), (3) the Comparative Fit Index (CFI), and (4) the Root Mean Square Error of Approximation (RMSEA) with related confidence intervals (CI). Only values greater than 0.95 values of the TLI and CFI indices (Hu and Bentler, 1999) and values lower than 0.08 for the RMSEA measure (Browne and Cudek, 1993) were accepted. Data analysis was conducted, and model parameters were estimated using full information maximum likelihood (Maydeu-Olivares and García-Forero, 2010). The bootstrapping analysis of 5,000 was conducted and confidence acceptance was established at 95% bias-corrected confidence intervals (95% CI). The effects of indirect relationships were considered statistically significant if zero was not included in the 95% bias-corrected CI (Hayes and Scharkow, 2013; Hair, 2019).

As mentioned previously, descriptive statistical analysis was performed at the individual level and preliminary information on research variables was collected. Furthermore, the relationships between the study variables were evaluated by calculating Pearson’s bivariate correlation coefficients. In addition, the convergent and discriminant validity of the designed constructs were estimated. These results are presented in Table 1.

The correlation coefficients (see Table 1) indicated that academic performance is positive associated with military performance (ACP&MLP, r = 0.518, p < 0.01), and self-efficacy (ACP&SFE, r = 0.560, p < 0.01). Military performance also indicated positive and highly significant relationships with self-efficacy (MLP&SFE, r = 0.525, p < 0.01). The Big Five personality traits such as extraversion (EXTR), conscientiousness (CONC) and openness to experience (OPEN) had statistically significant relations with: (i) self-efficacy (EXTR&SFE, r = 0.227, p < 0.05; CONC&SFE, r = 0.302, p < 0.01; OPEN&SFE, r = 0.243, p < 0.01); (ii) academic performance (EXTR&ACP, r = 0.313, p < 0.01; CONC&ACP, r = 0.419, p < 0.01; OPEN&ACP, r = 0.171, p < 0.05); and (iii) military performance (EXTR&ACP, r = 0.313, p < 0.01; CONC&ACP, r = 0.419, p < 0.01; OPEN&ACP, r = 0.171, p < 0.05). Although personality traits such as emotional stability and agreeability did not show the relationships with self-efficacy, academic or military performance. Finally, age as one of the control variables was positively correlated with military performance (Age&MLP, r = 0.136, p < 0.05).

Harman’s single-factor test was conducted. The findings of exploratory factor analysis (EFA) accounted for 67.57% of the total variance for greater than one factor, and 30.54% of the covariance between the measures was indicated for a single factor. Furthermore, to demonstrate the reliability of the study constructs, composite reliability (CR) values were computed. The results of statistical analysis let us establish the adequacy of eight constructs, the CR values ranged from 0.903 to 0.932. Furthermore, by evaluating the average variance extracted (AVE) the discriminant validity of the study constructs was tested. The get results showed that AVE values of constructs ranged from 0.646 to 0.774 are in an acceptable interval and meet the requirements (Fornell and Larcker, 1981). The discussed values are presented in Table 1.

Modeling analysis was performed using IBM AMOS 29v software. Confirmatory factor analysis was used to test the theorized links among constructs in specified models. Model 1 tested how five personality traits affect self-efficacy (hypotheses: H1a-H1e); Model 2 evaluated pathways among five personality traits and academic performance (hypotheses: H2a-H2e); and Model 3 tested how five personality traits affect military performance (hypotheses: H3a-H3e). Finally, the control variables (course, gender and age) were included and indirect effects theorized (hypotheses: H4a-H4e and H5a-H5e) between all constructs were evaluated by Model 4. The goodness-of-fit of theorized models was assessed by SEMA results.