Ancuţa Elena Pǎduraru
Camelia Soponaru
Cǎtǎlin Dîrţu1†
Ovidiu Gavrilovici
Mihaela Dana Bucuţǎ- 1Department of Psychology, “Alexandru Ioan Cuza” University of Iaşi, Iaşi, Romania
- 2Department of Psychology, “Lucian Blaga University” of Sibiu, Sibiu, Romania
Introduction: The literature emphasizes the link between academic stress and academic performance and the fact that the most vulnerable students are first-year students, but we still need to understand the underlying mechanism for forming targeted intervention strategies and the protective factors. The main objective of the present study was to test the mediating effect of self-efficacy and social support on the relationship between academic stress and academic performance. We also aimed to identify the main sources of stress and their significant sources of support.
Methods: Data were collected via an online survey platform in January 2024, with 436 students, with a mean age of 19.99 ± 3.72, responding affirmatively to our invitation. Thus, in this cross-sectional study, the sample was a convenience sample.
Results: The highest source of stress was the pressure to perform, followed by time restraints, perceptions of workload and examinations, and self-perceptions. The highest level of support is obtained from significant others, followed by family support and, last, friends' support. Both self-efficacy and social support partially mediate the effect of academic stress on academic performance.
Conclusions: Our results suggest that one way to improve students' performance, even when they experience academic stress, is to increase their levels of social support, especially from family, as well as their self-efficacy. These results can be used by services that provide psychological support to students in order to design and implement intervention programs.
1 Introduction
Higher education accomplishment and academic performance have a positive long-term impact both on the individual's career development and on society at large, and a better understanding of the factors influencing them is imperative (Stajkovic et al., 2018). Higher education institutions are an essential pillar of society, and their performance is largely based on student performance (Abbas et al., 2021; Maajida Aafreen et al., 2018). However, dropout is still a significant problem (Ibáñez-Cubillas et al., 2023). As such, international policies are being considered for implementation with the aim of increasing the number of those who attend and complete tertiary education and have skills that enable them to enter the labor market (UN-ODS-UN, 2020). Often, an indicator of academic success is academic performance, also found among the categories of factors explaining school dropout (Mellizo-Soto, 2022). Students who perform poorly academically are more likely to drop out or to change college or university (Belloc et al., 2011), and it is important to identify the factors that favor good and very good results.
The most vulnerable to dropping out of school and academic stress are first-year students (Casanova et al., 2021; Chemers et al., 2001). Most of them move away from home to pursue university studies, thus diminishing parental support and supervision (Casanova et al., 2021; Gonzalez, 2021) and are challenged in their autonomy and personal maturity (Holdsworth et al., 2018). With the achieving of new status, young people have to cope with a higher level of educational demands, which comes with higher levels of academic stress (Hitches et al., 2022) and the need to create new personal relationships (Lamis et al., 2016). The extent to which these young people believe in their ability to cope, manage their abilities to successfully accomplish goals, and tend to relate to challenges as tasks to be faced rather than avoided. All these influence their performance (Doménech-Betoret et al., 2017). In other words, the level of self-efficacy has a significant effect on academic performance.
The best-known definition of stress is that by Lazarus and Folkman (1986), which states that stress arises in a person's relationship with his or her environment when he or she appraises the environment as threatening and exceeding the resources needed to cope with it, thus putting his or her well-being at risk. During higher education students often experience high, or at least moderate, levels of stress (Khan, 2023; Alkhawaldeh et al., 2023), which further has significant effects on health, quality of life, and academic performance (Hitches et al., 2023; Deng et al., 2022; Pascoe et al., 2020). The link between negative stress, self-efficacy, and low academic achievement is well-known in literature, but the underlying mechanisms are not yet fully understood and known (Grøtan et al., 2019), and is a part of the literature that needs to be further explored. A range of internal factors such as self-efficacy and external factors such as support from friends, family, or significant others are important protective factors (Sharififard et al., 2020; Arnett, 2013; León Hernández et al., 2019), especially in the first year of studies, which is a transitional period (Krypel and King, 2010; García and Velazquez, 2020).
Bandura (1994, 1997) defines self-efficacy as a person's view of his or her ability to achieve high levels of performance for events that significantly influence his or her life, further impacting on how he or she feels, thinks, behaves, and sets goals. Self-efficacy theory is a segment of social cognitive learning theory which argues that individuals will attempt to accomplish goals for which they feel capable of accomplishing and avoid those for which they foresee failure (Bandura, 1994, 1997). Self-efficacy is a motivational product, the level of which is closely related to a person's incentive to successfully accomplish goals and cope with academic stress (Capri et al., 2012).
Bearing in mind that a person's opinions can influence the outcomes of a task to a greater extent than the skills themselves, it becomes self-evident why it is important to study this variable in relation to academic performance. Without a healthy attitude toward academic tasks, inherent to university life, students may be overwhelmed by stress (Beiter et al., 2015), and their performance will be profoundly affected (García and Velazquez, 2020).
The link between self-efficacy and academic performance is supported by both earlier studies (Multon et al., 1991) and recent studies (Khan, 2023; Farid and Ashrafzade, 2020; León Hernández et al., 2019; Wilson et al., 2019; Talsma et al., 2018). Among factors that might influence academic performance, self-efficacy ranks first (Richardson et al., 2012), or second (Schneider and Preckel, 2017). Also, the mediating effect of self-efficacy has been demonstrated in the relationship between Big Five traits and academic performance (Stajkovic et al., 2018). And the need to study self-efficacy and academic performance of first-year students has been pointed out by authors such as García and Velazquez (2020), and is still a gap in the literature.
Social support acts as a buffer in the face of stress-generating events, in which other people provide resources to help coping (Cohen and Wills, 1985). According to the stress buffer theory (Kawachi and Berkman, 2001), social support has a protective role providing young people at the coping level with a positive attitude toward themselves and the situation they are facing. Among students, social support promotes psychological health by mediating hopelessness and depressive symptoms in predicting suicidal thoughts (Lamis et al., 2016). Maluenda-Albornoz et al. (2023) obtained results according to which perceived social support is a significant predictor of sense of belonging for first-year students, the relationship between the two variables being a strong one. In other words, a higher level of social support is associated with a greater sense of belonging, which in turn has an impact on academic performance (Antúnez et al., 2017). Also, Lopez-Angulo et al. (2021) indicate that a higher perception of social support is associated with a decrease in thoughts or intentions to drop out of academic studies among first-year students. The importance of social support and relationships with family, friends, and teachers in students' adjustment was also emphasized by a meta-analytic review of 44,668 students' responses (Credé and Niehorster, 2012). Students who experience a greater sense of social support will tend to feel connected to the learning environment, actively use adaptive cognitive strategies for learning, perform better on learning tasks, experience positive emotions in the classroom (Moreira and Lee, 2020), and have higher academic engagement (Chen et al., 2023) and achievement (Zhang et al., 2024). Although researchers agree on the beneficial role this variable has in students' lives (Bland et al., 2012), it is not yet known whether social support coming from different sources, e.g., from parents, friends, significant other, has an equivalent effect, still being an important gap in the literature (Gonzalez, 2021; Ouweneel et al., 2011). Among first-year students family support decreases, leading to feelings of loneliness (Dorrance Hall et al., 2017), and that of friends and family encourages positive attitudes toward university and decreases stress levels (Collings et al., 2014). In general, among students low levels of social support are associated with higher levels of stress (McLean et al., 2023).
Based on this information, along with other evidence from the literature, the main objective of the present study was to test the mediating effect of self-efficacy and social support on the relationship between academic stress and academic performance. We also aimed to identify first-year students' main sources of stress and their significant sources of support. Thus, the hypotheses of our study are (1) self-efficacy mediates the effect of academic stress on academic performance and (2) social support mediates the effect of academic stress on academic performance.
2 Materials and methods
Data were collected via an online survey platform (Google Forms) in January 2024. The study received ethical approval from the ethics committee of the Faculty of Psychology and Educational Sciences (number 595/12.05.2023). All participants were asked for consent to participate in the study, were assured of the confidentiality of their responses, and were treated in accordance with the Declaration of Helsinki.
2.1 Participants
First-year undergraduate students of Psychology and Educational Sciences, full-time undergraduate, from a faculty in the North-East region of Romania were invited to participate in the present study. We invited 559 students to participate in our survey, of which 436 (78%) students responded positively with an average age of 19.99 ± 3.72. Of these, 404 identified themselves as female and 32 as male. As can be seen in Table 1, more than half of the participants, 239 to be more precise, come from urban areas, while 197 are from rural areas. In terms of residence at the time of completing the instruments, 117 were living in a dormitory, 181 in rented accommodation, 90 with their parents, 11 in a host family, and 37 in a privately owned dwelling. Assessing marital status, we were able to identify that 12 subjects were married, 209 in a relationship and 215 single. Most of them, 423 to be exact, had no children.
Table 1. Socio-demographic characteristics of the sample.
2.2 Measures
2.2.1 Demographic questionnaire
Through this questionnaire, we collected the following information about the participants: faculty, year of study, age, gender, background, residence, marital status, and whether they have children or not.
The Academic Stress Scale (França and Dias, 2021) consists of 18 items that represent potential stress-generating situations for students. Responses are given on a 5-point Likert scale, ranging from 1 (Totally disagree) to 5 (Totally agree). The scale assesses four factors: pressure to perform made up of items that cause stress due to peer competition, parental expectations and teacher criticism of student performance, perceptions of workload and examinations made up of items that assess stress related to very high demands, high level of tasks and worry about failing tests, self-perceptions assesses academic self-confidence, confidence in making appropriate academic decisions and professional success, and the time restraints factor addresses stress due to time constraints in completing class assignments, catching up on missed assignments, and limited time for relaxation. For our study, we calculated the score for the four factors, as well as the total score for the 18 items. In terms of internal consistency, on our group of subjects, the pressures to perform scale obtained an α–Cronbach's α of 0.53, the perceptions of workload and examinations scale an α–Cronbach's α of 0.67, self-perceptions an α–Cronbach's α of 0.74, time restraints an α–Cronbach's α of 0.63, and the whole instrument registered an α–Cronbach's α of 0.85, demonstrating an internal consistency adequate for the research. The validity of this tool was recently demonstrated by França and Dias (2021).
The College Students' Academic Performance Scale (Li et al., 2022) was used to assess students' subjective perceptions of their academic performance through 19 items and the following four dimensions: learning efficiency (e.g., The extent to which I complete my work tasks as per teacher's requirements), interpersonal promotion (e.g., The extent to which I am considerate and caring to other students), learning dedication (e.g., The extent of my persistence in overcoming difficulties to complete learning tasks), and objective achievement (e.g., My overall performance compared to the class average). The answers are given on a 5-step Likert-type scale, with 1 representing not at all able or lowest and 5 representing fully able or highest. The higher the scores, the higher the academic performance. Cronbach's α for the 19 items was 0.90, for the learning efficiency dimension was 0.81, 0.84 for the interpersonal promotion dimension, 0.83 for the learning dedication dimension, and 0.79 for the objective achievement dimension. Li et al. (2022) demonstrated that the scale has a good validity, performing a confirmatory factor analysis which showed an SFL ranging from 0.73 to 0.88, being >0.5.
The General Self-Efficacy Scale (GSE; De las Cuevas and Peñate, 2015) was used to measure general self-efficacy using 10 items on a scale from 1 (not true at all) to 4 (completely true). We chose this scale due to the fact that this scale explicitly refers to personal agency, that is, the belief that our own actions are responsible for successful outcomes (e.g., I can solve most problems if I invest the necessary effort) and does not assess optimism as other scales do. The maximum score that can be obtained is 40 and the minimum 10, the higher the score the higher the self-efficacy. The internal consistency of the instrument is good, for our group of subjects Cronbach's α is equal to 0.91. The convergent validity of this scale was demonstrated by De las Cuevas and Peñate (2015).
The Multidimensional Scale of Perceived Social Support (MSPSS; Zimet et al., 1988) is a scale that assesses a person's perception of the support received from three sources: significant others (e.g., There is a special person who is around when I am in need), family (e.g., My family really tries to help me), and friends (e.g., I can count on my friends when things go wrong). Responses are recorded on a 7-step Likert-type scale ranging from 1 (very strongly disagree) to 7 (very strongly agree). Significant Other subscale obtained a Cronbach's α of 0.94, family subscale a Cronbach's α of 0.93, and friends subscale 0.94. Cronbach's α for all 12 items is 0.92. The scale demonstrated good validity in the study by Zimet et al. (1988).
2.3 Statistical analysis
All analyses were conducted using IBM SPSS 26 for Windows (IBM Corporation, Armonk, NY, USA). To test the two hypotheses we used the methodology proposed by Hayes (2013), using PROCESS (model 4, 2013). The mediation method is the approach proposed by Baron and Kenny (1986). The variables of the present research do not differ statistically significantly from a normal distribution, as the absolute value of the skewness coefficient is not >1 (Labăr, 2008). Extreme scores were identified and removed. The following extreme cases were identified: pressure to perform–1 extreme high case, self-perceptions–1 extreme high case, learning efficiency–1 extreme low case, learning dedication–5 extreme low cases, objective achievement–4 extreme low cases, total score performance–2 extreme low cases, significant others–77 extreme low cases, and social support total score–7 extreme low cases. Having performed analyses for the study variables with and without the extreme cases and observing that there are no significant changes in the results obtained, it was decided to ignore them and report the results with the extreme cases removed (Tabachnick and Fidell, 2013).
3 Results
In order to identify the factors that determine the highest level of stress, as well as the most important source of support, we calculated means and standard deviations. As can be seen in Table 2, the highest source of stress is the pressure to perform (M = 14.01 ± 3.52), followed by time restraints (M = 13.35 ± 3.57), perceptions of workload and examinations (M = 12.07 ± 3.31), and self-perceptions (M = 9.81 ± 2.98). The highest level of support is obtained from significant other (M = 25.59 ± 2.97), followed by family support (M = 21.57 ± 6.43), and, last, friends' support (M = 20.83 ± 6.48).
Table 2. Descriptive statistics for support and stress sources.
We further identified the correspondence between the study variables by calculating the correlation coefficient r Pearson. Most correlations are statistically significant (see Table 3), but we further present only medium and strong correlation:
Table 3. Bivariate correlations between study variables.
Pressure to perform correlates positively with perceived workload (r = 0.56, p < 0.001), self-perceptions (r = 0.47, p < 0.001), time restraints (r = 0.51, p < 0.001), p < 0.001), and negatively with general self-efficacy (r = –0.33, p < 0.001).
Perceived workload correlates positively with self-perceptions (r = 0.45, p < 0.001), time restraints (r = 0.66, p < 0.001), and negatively with general self-efficacy (r = −0.33, p < 0.001).
Self-perceptions correlate positively with time restraints (r = 0.51, p < 0.001), academic stress total score (r = 0.74, p < 0.001), and negatively with general self-efficacy (r = −0.58, p < 0.001), learning efficiency (r = −0.48, p < 0.001), interpersonal promotion (r = −0.35, p < 0.001), learning dedication (r = −0.46, p < 0.001), objective achievement (r = −0.48, p < 0.001), and academic performance total score (r = −0.53, p < 0.001).
Time restraints correlate negatively with general self-efficacy (r = −0.40, p < 0.001), learning efficiency (r = −0.42, p < 0.001), learning dedication (r = −0.35, p < 0.001), and academic performance total score (r = −0.38, p < 0.001).
Academic stress total score correlates negatively with general self-efficacy (r = −0.51, p < 0.001), learning efficiency (r = −0.44, p < 0.001), learning dedication (r = −0.40, p < 0.001), objective achievement (r = −0.36, p < 0.001), and academic performance total score (r = −0.44, p < 0.001).
Significant other support correlated positively with friends support (r = 0.35, p < 0.001), whereas family support correlates positively with friends support (r = 0.40, p < 0.001), social support total score (r = 0.76, p < 0.001), and learning efficiency (r = 0.30, p < 0.001).
General self-efficacy correlates positively with learning efficiency (r = 0.49, p < 0.001), interpersonal promotion (r = 0.37, p < 0.001), learning dedication (r = 0.48, p < 0.001), objective achievement (r = 0.44, p < 0.001), and academic performance total score (r = 0.52, p < 0.001). Learning efficiency positively correlates with interpersonal promotion (r = 0.53, p < 0.001), learning dedication (r = 0.60, p < 0.001), and objective achievement (r = 0.48, p < 0.001).
Interpersonal promotion positively correlated with learning dedication (r = 0.63, p < 0.001) and objective achievement (r = 0.39, p < 0.001), whereas learning dedication positively correlated with objective achievement (r = 0.48, p < 0.001).
Testing Hypothesis 1: self-efficacy mediates the effect of academic stress on academic performance (Figure 1). First we analyze the effect of the independent variable academic stress on the mediator variable self-efficacy. Thus, academic stress explains 24% of the variance of self-efficacy (R2 = 0.2466, p < 0.001), and the coefficient of the regression equation equals −0.2770 [t(432) = −11.8911, p < 0.001], with CI 95% [−0.3227– (−0.2312)]. High academic stress scores are associated with low self-efficacy scores.
Figure 1. Effect of academic stress on academic performance as mediated by self-efficacy. ***p < 0.001.
The predictors academic stress (p < 0.001) and self-efficacy (p < 0.001) have a significant effect on academic performance, explaining 32% of its variance (R2 = 0.3241). For path b the coefficient is equal to 0.7678 [t(431) = 8.9579, p < 0.001], and the standardized value is 0.4087, with 95% CI [0.5993–0.9363]. Thus, high self-efficacy scores are associated with high academic performance scores. As for the direct effect, it is equal to −0.2539 [t(432) = −5.3104, p < 0.001], with CI 95% [−0.3478– (−0.1599)]. The standardized direct effect size is −0.2423. As the direct effect is statistically significant, the mediation is partial.
In terms of the total effect, stress explains 19% of the variance of academic performance (R2 = 0.1982, p < 0.001). The coefficient of the regression equation is −0.4665 [t(432) = −10.3349, p < 0.001], with a standardized value equal to −0.4452. For the total effect CI 95% [−0.5552– (−0.3778)]. Information on the indirect effect is recorded in Table 4.
Table 4. Total, direct, and indirect effect of academic stress on academic performance.
Hypothesis 2 claims that social support mediates the effect of academic stress on academic performance (Figure 2). We tested this hypothesis with both the total score of social support as a mediator and the three dimensions of social support as mediators. We first present the results obtained for the total score of social support as mediator in the relationship between academic stress and academic performance.
Figure 2. Effect of academic stress on academic performance mediated by social support. **p = 0.001, ***p < 0.001.
Analyzing the effect of academic stress on the mediator social support, we observe that the independent variable explains 4% of its variance (R2 = 0.0493, p < 0.001), and the coefficient of the regression equation is −0.2966 [t(425) = −4.6966, p < 0.001], having CI 95% [−0.4207– (−0.1725)].
The predictors academic stress and social support explain 22% of the variance of academic performance, having a statistically significant effect (R2 = 0.2223, p < 0.001). For path b the coefficient is equal to 0.1388 [t(424) = 4.0867, p = 0.001], the standardized value is 0.1795, with CI 95% [0.0720–0.2056]. As for the direct effect (c') it is equal to −0.4108 [t(424) = −9.0585, p < 0.001], with a standardized value of −0.3979, with CI 95% [−0.5000– (−0.3217)]. The mediation is partial, due to the fact that the direct effect is statistically significant.
When considering the total effect, stress explains 19% of the variance of academic performance (R2 = 0.1916, p < 0.001). The coefficient of the regression equation is −0.4520 [t(425) = −10.0379, p < 0.001], with a standardized value of −0.4378 and 95% CI [−0.5405– (−0.3635)]. Information on the indirect effect is recorded in Table 5.
Table 5. Total, direct, and indirect effect of academic stress on academic performance, with social support as a mediator.
Further, in order to analyze the impact of the mediator, we considered the social support factors, namely significant other support, family support, and friends' support, then introduced them into the model (Figure 3). To begin with, we obtained that stress explains 1% of the variance of the significant other support variable (R2 = 0.0192, p = 0.0085), the coefficient of the regression equation is −0.0389 [t(357) = −2.6446, p = 0.0085], and the CI 95% [−0.0679– (−0.0100)]. As for the second mediator, academic stress explains 5% of family support (R2 = 0.0543, p < 0.001) with the coefficient of the regression equation being −0.1286 [t(357) = −4.5293, p < 0.001] and CI 95% [−0.1844– (−0.0728)]. For the third mediator, stress is a significant predictor explaining 1% of the variance of friends' support (R2 = 0.0145, p = 0.0225), with the coefficient of the regression equation equal to −0.0666 [t(357) = −2.2923, p = 0.0225], and CI 95% [−0.1238– (−0.0095)].
Figure 3. Effect of academic stress on academic performance mediated by social support. *p < 0.05, ***p < 0.001.
Stress together with the three mediators explains 23% of the variance in academic performance, the model being statistically significant (R2 = 0.2312, p < 0.001). Of the three mediators, only the effect of family support is statistically significant [b = 0.2313, t(354) = 2.4242, p = 0.0158], with CI 95% [0.0437–0.4188]. Significant other support does not statistically significantly predict academic performance [b = 0.1929, t(354) = 1.0184, p = 0.3092], for which CI 95% [−0.1796 to 0.5655]. Friend support also does not statistically significantly predict academic performance [b = 0.1339, t(354) = 1.3927, p = 0.1646], for which CI 95% [−0.0552 to 0.3230].
Path c', of the direct effect is statistically significant, the regression coefficient b = −0.4215, t(354) = −8.3742, p < 0.001, the standardized coefficient equals −0.4029, and the CI 95% [−0.5204– (−0.3225)]. Analyzing the total effect, academic stress explains 19% of the variance of academic performance, the effect is statistically significant (R2 = 0.1999, p < 0.001). The coefficient of the regression equation is −0.4676 [t(357) = −9.4438, p < 0.001], with a standardized value equal to −0.4471, with CI 95% [−0.5650– (−0.3702)]. Again, the averaging is partial, and information on the indirect effect is given in Table 6.
Table 6. Total, direct, and indirect effect of academic stress on academic performance, with the 3 dimensions of support as mediators.
4 Discussion
In this study, we set out to identify the factor that determines the highest level of stress among first-year students and the source from which they rate receiving the highest level of support. Next, we analyzed the relationship between academic stress and academic performance, as well as the mediating effect in this relationship of variables such as self-efficacy and social support. Our hypotheses assume that the relationship between academic stress and academic performance is mediated by (1) self-efficacy and (2) social support.
The pressure to perform is the factor that generates the highest level of stress for the students included in the study, followed by stress caused by time restraints and, in thirdly, perceptions of workload and examinations and self-perceptions. In terms of social support, students feel that they receive the highest level of support from significant others, followed in the same place by support from family and friends.
The first hypothesis of our study was partially confirmed, with self-efficacy partially mediating the relationship between academic stress and academic performance. In the model we tested, stress is a negative predictor of self-efficacy and self-efficacy is a positive predictor of academic performance. What is very important is that self-efficacy changes the sign of the influence of stress on academic performance, acting as a protective factor. The negative relationship between stress and self-efficacy has also been identified by other studies (Galindo-Domínguez and Bezanilla, 2021; Posada and Liu, 2017; Siddiqui, 2018). The fact that higher levels of self-efficacy are associated with higher levels of academic performance has also been identified by León Hernández et al. (2019), who argue that when students have a high perception of their effectiveness in accomplishing an academic task, they are more engaged and persist longer in accomplishing it, even when faced with challenges, including academic stress. The same results were also obtained by Khan (2023) in his pilot study, in which he emphasized the need for further research on the relationship between these two variables. Moreover, the two variables have often been linked, with their positive correlation demonstrated in several studies (Alyami et al., 2017). Also, self-efficacy reduces the risk of burnout in students (Capri et al., 2012) and helps them controlling unpleasant emotions and changes deriving from their emerging adult status more effectively (León Hernández et al., 2019). García and Velazquez (2020) obtained results showing that low levels of self-efficacy are related to low student performance and high levels of anxiety among students.
With respect to the second hypothesis, the results are similar, in the sense that social support partially mediates the effect of academic stress on academic performance. Our proposed second mediator has the same protective effect, changing the sign of the relationship. If academic stress is a negative predictor for social support, the mediator instead has a positive effect on academic performance. Because we wanted to see whether all three factors of social support mediate the relationship between academic stress and academic performance, we tested a model in which the three factors were included as mediators for the above-mentioned relationship. The results revealed that only family support is a significant mediator, although mediation is only partial. This outcome, in the context of the above result on the hierarchy of sources of support, is surprising and extremely important. Basically, students rate that they receive the highest level of support from their significant other, but the significant other is not a significant mediator, family support is.
It is possible that they perceive support from their significant other at a higher level because they spend more time together, see each other more often, especially if they are in the same city, or university campus, while the family remained in the hometown, interactions are more infrequent and predominantly via telephone. We know about our participants that only about 20% still live with their parents, which may explain the level of perceived support from their parents. Future studies looking at the way in which contact with the family is maintained and its possible effect on the relationship we tested may provide further and clarifying information.
Basically, social support, particularly through the dimension of family support, generates positive emotional and behavioral attitudes (Li et al., 2023), which further encourage high academic performance despite the presence of academic stress. Our results being in agreement with existing evidence in the literature that perceived social support has a crucial role in shaping students' academic achievement (Nair et al., 2024). Students who experience social support, especially family support, are embedded in a supportive network and are thus in a more advantageous position to cope with stress and achieve academic performance (Li et al., 2018). In addition to the positive link with academic performance, family support has been identified as an important factor in students' psychological, financial, and academic health (Nair et al., 2024). The fact that social support has a buffering effect against stress is a known fact in the literature (Rueger et al., 2016), and our results also support this effect in the relationship of stress with academic performance.
The practical conclusions of the present findings have implications not only for students, but also for parents, teachers and specialists providing counseling and personal development services for students. Counseling services for students can consider the implementation of programs to develop students' self-efficacy and to increase social support, especially the family support dimension. Basically, by increasing the strength of self-efficacy, students can achieve better academic outcomes, thus tempering some of the impact of encountered stressors (Stajkovic et al., 2018). Along with evidence that self-efficacy can be improved (Bartimote-Aufflick et al., 2016), our results provide intervention suggestions that can make a real difference for students' academic progress. These strategies to increase self-efficacy are absolutely necessary, especially in the first year of studies, a difficult period that can confront students with a range of difficulties (García and Velazquez, 2020).
5 Limits and future research directions
Data were collected from a single university and faculty. Data from a representative sample are absolutely necessary, otherwise they cannot be generalized. Another limitation is the cross-sectional nature of the study, a limitation that can be overcome, as we know, by longitudinal studies. The fact that self-efficacy in general and not academic self-efficacy was assessed may also be a limitation. Studies clarifying whether different results are obtained for academic self-efficacy are needed. Our data were collected at the end of the first semester, with some authors suggesting that different results might be obtained if data were collected at the beginning of the semester (García and Velazquez, 2020). Galyon et al. (2012) identified that self-efficacy correlates with academic performance in the middle of the semester, but not in the earlier stages of the term. As a result, studies examining the relationship between self-efficacy and academic performance at both the beginning and end of the semester are needed. Accounting for other mediators, such as mental health (Barbayannis et al., 2022), is another future research direction. Also, conducting longitudinal studies in testing the impact of psychosocial interventions applied in student counseling services may be another direction. Another limitation may be the mode of data collection, which was through online forms. This did not allow us to control the environmental conditions in which the data were collected.
6 Conclusion
Despite the limitations mentioned above, these results extend our knowledge about the role that self-efficacy and social support play in students' lives, particularly in relation to their academic performance. They suggest that one way to improve students' performance, even when they experience academic stress, is to increase the level of social support, especially from family, as well as self-efficacy.
Data availability statement
Raw data supporting the conclusions of this article will be made available by the authors upon request without unjustified reservation.
Ethics statement
The study received ethical approval from the Ethics Committee of the Faculty of Psychology and Educational Sciences (number 595/12.05.2023). The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their informed consent to participate in this study.
Author contributions
AP: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing. CS: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing. CD: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing. OG: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing. MB: Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing, Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources.
Funding
The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
References
Abbas, J., Alturki, U., Habib, M., Aldraiweesh, A., and Al-Rahmi, W. M. (2021). Factors affecting students in the selection of country for higher education: a comparative analysis of international students in Germany and the UK. Sustainability 13:10065. doi: 10.3390/su131810065
Alkhawaldeh, A., Al Omari, O., Al Aldawi, S., Al Hashmi, I., Ann Ballad, C., Ibrahim, A., et al. (2023). Stress factors, stress levels, and coping mechanisms among university students. Sci. World J. 2023:2026971. doi: 10.1155/2023/2026971
Alyami, M., Melyani, S., Al Johani, A., Ullah, E., Alyami, H., Sundram, F., et al. (2017). The impact of self-esteem, academic self-efficacy and perceived stress on academic performance: a cross-sectional study of Saudi psychology students. Eur. J. Educ. Sci. 4, 51–63. doi: 10.19044/ejes.v4no3a5
Antúnez, Á., Cervero, A., Solano, P., Bernardo, I., and Carbajal, R. (2017). “Engagement: a new perspective for reducing dropout through self-regulation,” in Factors Affecting Academic Performance, eds. J. A. González-Pienda, A. Bernardo, J. C. Núñez, and C. Rodríguez (New York, NY: Nova Science Publishers), 25–46.
Arnett, J. J. (2013). Adolescence and Emerging Adulthood: A Cultural Approach, 5th Edn. Boston, MA: Pearson.
Bandura, A. (1994). “Self-efficacy,” in Encyclopedia of Human Behavior, Vol. 4, ed. V. S. Ramachaudran (San Diego, CA: Academic Press), 71–81 (Reprinted in H. Friedman [Ed.], Encyclopedia of mental health, 1998).
Barbayannis, G., Bandari, M., Zheng, X., Baquerizo, H., Pecor, K. W., and Ming, X. (2022). Academic stress and mental well-being in college students: correlates, affected groups, and COVID-19. Front. Psychol. 13:886344. doi: 10.3389/fpsyg.2022.886344
Baron, R. M., and Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J. Pers. Soc. Psychol. 51, 1173–1182. doi: 10.1037/0022-3514.51.6.1173
Bartimote-Aufflick, K., Bridgeman, A., Walker, R., Sharma, M., and Smith, L. (2016). The study, evaluation, and improvement of university student self-efficacy. Stud. High. Educ. 41, 1918–1942. doi: 10.1080/03075079.2014.999319
Beiter, R., Nash, R., McCrady, M., Rhoades, D., Linscomb, M., Clarahan, M., et al. (2015). The prevalence and correlates of depression, anxiety, and stress in a sample of college students. J. Affect. Disord. 173, 90–96. doi: 10.1016/j.jad.2014.10.054
Belloc, F., Maruotti, A., and Petrella, L. (2011). How individual characteristics affect university students drop-out: a semiparametric mixed-effects model for an Italian case study. J. Appl. Stat. 38, 2225–2239. doi: 10.1080/02664763.2010.545373
Bland, H. W., Melton, B. F., Welle, P., and Bigham, L. (2012). Stress tolerance: new challenges for millennial college students. Coll. Stud. J. 46, 362–375.
Capri, B., Ozkendir, O. M., Ozkurt, B., and Karakus, F. (2012). General self-efficacy beliefs, life satisfaction and burnout of university students. Proc. Soc. Behav. Sci. 47, 968–973. doi: 10.1016/j.sbspro.2012.06.765
Casanova, J. R., Gomes, C. M. A., Bernardo, A. B., Núñez, J. C., and Almeida, L. S. (2021). Dimensionality and reliability of a screening instrument for students at-risk of dropping out from higher education. Stud. Educ. Eval. 68:100957. doi: 10.1016/j.stueduc.2020.100957
Chemers, M. M., Hu, L., and Garcia, B. F. (2001). Academic self-efficacy and first year college student performance and adjustment. J. Educ. Psychol. 93:55. doi: 10.1037//0022-0663.93.1.55
Chen, C., Bian, F., and Zhu, Y. (2023). The relationship between social support and academic engagement among university students: the chain mediating effects of life satisfaction and academic motivation. BMC Public Health 23:2368. doi: 10.1186/s12889-023-17301-3
Cohen, S., and Wills, T. A. (1985). Stress, social support, and the buffering hypothesis. Psychol. Bull. 98, 310–357. doi: 10.1037/0033-2909.98.2.310
Collings, R., Swanson, V., and Watkins, R. (2014). The impact of peer mentoring on levels of student wellbeing, integration and retention: a controlled comparative evaluation of residential students in UK higher education. High. Educ. 68, 927–942. doi: 10.1007/s10734-014-9752-y
Credé, M., and Niehorster, S. (2012). Adjustment to college as measured by the student adaptation to college questionnaire: a quantitative review of its structure and relationships with correlates and consequences. Educ. Psychol. Rev. 24, 133–165. doi: 10.1007/s10648-011-9184-5
De las Cuevas, C., and Peñate, W. (2015). Validation of the General Self-Efficacy Scale in psychiatric outpatient care. Psicothema 27, 410–415. doi: 10.7334/psicothema2015.56
Deng, Y., Cherian, J., Khan, N. U. N., Kumari, K., Sial, M. S., Comite, U., et al. (2022). Family and academic stress and their impact on students' depression level and academic performance. Front. Psychiatry 13:869337. doi: 10.3389/fpsyt.2022.869337
Doménech-Betoret, F., Abellán-Roselló, L., and Gómez-Artiga, A. (2017). Self-efficacy, satisfaction, and academic achievement: the mediator role of students' expectancy-value beliefs. Front. Psychol. 8:277668. doi: 10.3389/fpsyg.2017.01193
Dorrance Hall, E., McNallie, J., Custers, K., Timmermans, E., Wilson, S. R., and Van den Bulck, J. (2017). A cross-cultural examination of the mediating role of family support and parental advice quality on the relationship between family communication patterns and first-year college student adjustment in the United States and Belgium. Commun. Res. 44, 638–667. doi: 10.1177/0093650216657755
Farid, A., and Ashrafzade, T. (2020). A meta-analysis of the relationship self-efficacy and academic performance. J. Educ. Sci. 27, 69–90. doi: 10.22055/edus.2020.35466.3130
França, F. D. P., and Dias, T. L. (2021). Validity and reliability of the perceptions of academic stress scale. Psychol. Theory Pract. 23, 1–21. doi: 10.5935/1980-6906/ePTPPA13041
Galindo-Domínguez, H., and Bezanilla, M. J. (2021). Promoting time management and self-efficacy through digital competence in university students: a mediational model. Contemp. Educ. Technol. 13:ep294. doi: 10.30935/cedtech/9607
Galyon, C. E., Blondin, C. A., Yaw, J. S., Nalls, M. L., and Williams, R. L. (2012). The relationship of academic self-efficacy to class participation and exam performance. Soc. Psychol. Educ. 15:233e249. doi: 10.1007/s11218-011-9175-x
García, A. G., and Velazquez, M. L. (2020). Relationship between academic self-efficacy, performance and anxious and depressive symptoms in emerging adult college students. Educación 29, 87–109. doi: 10.18800/educacion.202002.005
Gonzalez, J. B. (2021). Examining the differences of perceived family support, self-esteem, self-efficacy, academic performance, and academic help-seeking on college adjustment among Hispanic first-year college students. (doctoral dissertation). Texas A&M University-Corpus Christi, Corpus Christi, TX, United States.
Grøtan, K., Sund, E. R., and Bjerkeset, O. (2019). Mental health, academic self-efficacy and study progress among college students - the SHoT study, Norway. Front. Psychol. 10:408316. doi: 10.3389/fpsyg.2019.00045
Hayes, A. F. (2013). Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach. Guilford Press.
Hitches, E., Woodcock, S., and Ehrich, J. (2022). Building self-efficacy without letting stress knock it down: stress and academic self-efficacy of university students. Int. J. Educ. Res. Open 3:100124. doi: 10.1016/j.ijedro.2022.100124
Hitches, E., Woodcock, S., and Ehrich, J. (2023). Shedding light on students with support needs: comparisons of stress, self-efficacy, and disclosure. J. Divers. High. Educ. 16, 205–214. doi: 10.1037/dhe0000328
Holdsworth, S., Turner, M., and Scott-Young, C. M. (2018). Not drowning, waving. Resilience and university: a student perspective. Stud. High. Educ. 43, 1837–1853. doi: 10.1080/03075079.2017.1284193
Ibáñez-Cubillas, P., López-Rodríguez, S., Martínez-Sánchez, I., and Rodríguez, J. Á. (2023). Multicausal analysis of the dropout of university students from teacher training studies in Andalusia. Front. Educ. 8:1111620. doi: 10.3389/feduc.2023.1111620
Kawachi, I., and Berkman, L. F. (2001). Social ties and mental health. J. Urban Health 78, 458–467. doi: 10.1093/jurban/78.3.458
Khan, M. (2023). Academic self-efficacy, coping, and academic performance in college. Int. J. Undergrad. Res. Creat. Activ. 5:3. doi: 10.7710/2168-0620.1006
Krypel, M., and King, D. (2010). Stress, coping styles and optimism: are they related to meaning and education in students' lives? Soc. Psychol. Educ. 13, 409–424. doi: 10.1007/s11218-010-9132-0
Labăr, A. V. (2008). SPSS pentru stiintele educatiei. Metodologia analizei datelor in cercetarea pedagogica. Iaşi: Polirom.
Lamis, D. A., Ballard, E. D., May, A. M., and Dvorak, R. D. (2016). Depressive symptoms and suicidal ideation in college students: the mediating and moderating roles of hopelessness, alcohol problems, and social support: college student suicidal ideation. J. Clin. Psychol. 72, 919–932. doi: 10.1002/jclp.22295
Lazarus, R. S., and Folkman, S. (1986). “Cognitive theories of stress and the issue of circularity,” in DynaDlics of Stress Physiological, Psychological, and Social Perspectives, ed. M. H. Appley and R. Trumbull (New York, NY: Plenum), 63–80.
León Hernández, A., González Escobar, S., Arratia López Fuentes, N. I. G., and Barcelata Eguiarte, B. E. (2019). Stress, self-efficacy, academic achievement and resilience in emerging adults. Electr. J. Res. Educ. Psychol. 17, 129–148.
Li, J., Han, X., Wang, W., Sun, G., and Cheng, Z. (2018). How social support influences university students' academic achievement and emotional exhaustion: the mediating role of self-esteem. Learn. Individ. Differ. 61, 120–126. doi: 10.1016/j.lindif.2017.11.016
Li, J., Huang, J., Hu, Z., and Zhao, X. (2022). Parent-child relationships and academic performance of college students: chain-mediating roles of gratitude and psychological capital. Front. Psychol. 13:794201. doi: 10.3389/fpsyg.2022.794201
Li, N., Zhao, S., Liu, C., Dai, K., and Huang, W. (2023). Exploring the relationship between perceived social support and college students' autonomous fitness behavior: chain mediating effect test. Front. Psychol. 13:1036383. doi: 10.3389/fpsyg.2022.1036383
Lopez-Angulo, Y., Cobo-Rendon, B. C., Perez-Villalobos, M. V., and Diaz-Mujica, A. E. (2021). Social support, autonomy, academic commitment, and drop out intention in first year undergraduate students. Formación Universitaria 14:e00139. doi: 10.4067/S0718-50062021000300139
Maajida Aafreen, M., Vishnu Priya, V., and Gayathri, R. (2018). Effect of stress on academic performance of students in different streams. Drug Invent. Today 10, 1176–1780.
Maluenda-Albornoz, J., Berríos-Riquelme, J., Infante-Villagrán, V., and Lobos-Peña, K. (2023). Perceived social support and engagement in first-year students: the mediating role of belonging during COVID-19. Sustainability 15:597. doi: 10.3390/su15010597
McLean, L., Gaul, D., and Penco, R. (2023). Perceived social support and stress: a study of 1st year students in Ireland. Int. J. Ment. Health Addict. 21, 2101–2121. doi: 10.1007/s11469-021-00710-z
Mellizo-Soto, M. F. (2022). Analysis of Undergraduate Dropout in Face-to-Face Universities in Spain. Ministry of Universities.
Moreira, P. A., and Lee, V. E. (2020). School social organization influences adolescents' cognitive engagement with school: the role of school support for learning and of autonomy support. Learn. Individ. Differ. 80:101885. doi: 10.1016/j.lindif.2020.101885
Multon, K. D., Brown, S. D., and Lent, R. W. (1991). Relation of self-efficacy beliefs to academic outcomes: a meta-analytic investigation. J. Counsel. Psychol. 38, 30–38. doi: 10.1037/0022-0167.38.1.30
Nair, A. A., Bhatia, A. K., Kumar, A. V. D., Pothakani, M. Y., and Benedict, S. M. (2024). Exploring the Perceived Social Support Among College Students. Available at: https://ssrn.com/abstract=4722943 (accessed January 15, 2024).
Ouweneel, E., Le Blanc, P. M., and Schaufeli, W. B. (2011). Flourishing students: a longitudinal study on positive emotions, personal resources, and study engagement. J. Posit. Psychol. 6, 142–153. doi: 10.1080/17439760.2011.558847
Pascoe, M. C., Hetrick, S. E., and Parker, A. G. (2020). The impact of stress on students in secondary school and higher education. Int. J. Adolesc. Youth 25, 104–112. doi: 10.1080/02673843.2019.1596823
Posada, A., and Liu, Y. (2017). The moderating effects of gender on the relationship between academic stress and academic self-efficacy. Int. J. Stress Manag. 25, 56–61. doi: 10.1037/str0000089
Richardson, M., Abraham, C., and Bond, R. (2012). Psychological correlates of university students' academic performance: a systematic review and meta-analysis. Psychol. Bull. 138, 353–387. doi: 10.1037/a0026838
Rueger, S. Y., Malecki, C. K., Pyun, Y., Aycock, C., and Coyle, S. (2016). A meta-analytic reviewof the association between perceived social support and depression in childhoodand adolescence. Psychol. Bull. 142, 1017–1067. doi: 10.1037/bul0000058
Schneider, M., and Preckel, F. (2017). Variables associated with achievement in higher education: a systematic review of meta-analyses. Psychol. Bull. 143, 565–600. doi: 10.1037/bul0000098
Sharififard, F., Asayesh, H., Hosseini, M. H. M., and Sepahvandi, M. (2020). Motivation, self-efficacy, self-efficacy, stress, and academic performance correlation with academic burnout among nursing students. J. Nurs. Midwif. Sci. 7, 88–93. doi: 10.4103/JNMS.JNMS_30_19
Siddiqui, A. F. (2018). Self-efficacy as a predictor of stress in medical students of King Khalid University, Saudi Arabia. Makara J. Health Res. 22, 1–7. doi: 10.7454/msk.v22i1.7742
Stajkovic, A. D., Bandura, A., Locke, E. A., Lee, D., and Sergent, K. (2018). Test of three conceptual models of influence of the big five personality traits and self-efficacy on academic performance: a meta-analytic path-analysis. Pers. Individ. Diff. 120, 238–245. doi: 10.1016/j.paid.2017.08.014
Tabachnick, B. G., and Fidell, L. S. (2013). Using Multivariate Statistics, 6th Edn. Boston, MA: Pearson.
Talsma, K., Schüz, B., Schwarzer, R., and Norris, K. (2018). I believe, therefore I achieve (and vice versa): a meta-analytic cross-lagged panel analysis of self-efficacy and academic performance. Learn. Individ. Diff. 61, 136–150. doi: 10.1016/j.lindif.2017.11.015
Wilson, C., Babcock, S., and Saklofske, D. (2019). Sinking or swimming in an academic pool: a study of resiliency and student success in first-year undergraduates. Can. J. High. Educ. 49, 60–84. doi: 10.47678/cjhe.v49i1.188220
Zhang, B., Yin, X., and Ren, Z. (2024). Can perceived social support influence academic achievement of master's students? Evidence from a university in China. Educ. Inform. Technol. 29, 21449–21475. doi: 10.1007/s10639-024-12693-0
Keywords: academic performance, self-efficacy, social support, academic stress, university students
Citation: Pǎduraru AE, Soponaru C, Dîrţu C, Gavrilovici O and Bucuţǎ MD (2025) What do I need from myself as a student but also from others to reduce the impact of stress on academic performance? Self-efficacy and social support. Front. Educ. 9:1469865. doi: 10.3389/feduc.2024.1469865
Received: 24 July 2024; Accepted: 10 December 2024;
Published: 24 January 2025.
Edited by:
Konrad Reschke, Leipzig University, GermanyReviewed by:
Stacie Craft DeFreitas, Prairie View A&M University, United StatesJorge Ignacio Maluenda-Albornoz, University of Concepcion, Chile
Copyright © 2025 Pǎduraru, Soponaru, Dîrţu, Gavrilovici and Bucuţǎ. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Ancuţa Elena Pǎduraru, YW5jYS5wYWR1cmFydUB1YWljLnJv; Mihaela Dana Bucuţǎ, bWloYWVsYS5idWN1dGFAdWxic2liaXUucm8=
†These authors have contributed equally to this work and share first authorship