Discusiones generales
Center for Research in Economics and Entrepreneurial Sciences, Universidad Privada Boliviana, Cochabamba, BoliviaCorrespondencepcordova@upb.edu
Abstract
Identifying the relationship between academic stress and mental health of undergraduate university students is crucial for reducing and understanding its negative effects, enhancing students’ ability to cope with stressful situations, and thereby reducing the harm it causes on academic performance and overall well-being. This study aims to examine the correlation and predictive value of academic stress on mental health in undergraduate university students. A representative sample of 1,265 undergraduate university students from a private university in Bolivia was assessed using Pearson’s correlation analysis to determine the predictive value of academic stress on mental health. To validate the measurements obtained, a stepwise Hierarchical Multiple Linear Regression analysis was applied. A probability model was estimated to identify academic stressors that contribute to the probability of students experiencing Languishing Mental Health. The study revealed that Self-inflicted Stress was the most significant stressor among undergraduate students. This indicates that students’ self-demands and self-efficacy perceptions are essential factors in the development of high academic stress levels. There is a clear correlation between high levels of academic stress and the probability of experiencing Languishing Mental Health.
Keywords:
• academic stress
• mental health
• Languishing Mental Health
• Self-inflicted Stress
Previous articleView issue table of contentsNext article
PUBLIC INTEREST STATEMENT
This study examines the correlation between academic stress and mental health in university students. Through analysis of a sample of 1,265 students, the study reveals that high levels of academic stress, particularly self-inflicted stress, increase the probability of experiencing Languishing Mental Health. The findings underline the significance of identifying stressors and implementing educational programs to prevent the negative impact of stress on mental health. Additionally, students need to develop coping mechanisms to manage stressful situations in academic environments. The research has significant implications for universities and policymakers as it provides insight into the specific stressors that affect students and the measures that can be taken to mitigate their effects. Ultimately, the study aims to enhance mental health and academic performance among university students.
1. Introduction
Stress is a ubiquitous phenomenon in daily life that results from a natural physiological and psychological response of the body to situations perceived as challenging or threatening, acting as a catalyst to confront and resolve problems. However, excessive exposure to it can have detrimental long-term physical and mental effects (Flórez & Sánchez, Citation2020).
In recent years, numerous studies have demonstrated that chronic stress, when sustained for extended periods, can trigger anxiety disorders, depression, and other mental health issues. O’Connor et al. (Citation2021) found that chronic stress can have adverse effects on cognitive functioning, emotional regulation, and overall quality of life. Furthermore, emerging research, such as that conducted by Mariotti (Citation2015) suggested that chronic stress can increase the likelihood of developing psychiatric disorders among susceptible individuals.
The findings of stress studies emphasize the importance of addressing stress as a critical factor in promoting mental health by comprehending the biological mechanisms underlying stress. Dai et al. (Citation2020) conducted research revealing that chronic stress can activate a sequence of neurobiological responses, including the hypothalamic-pituitary-adrenal axis and cortisol release. Prolonged exposure to cortisol, a hormone released in response to stress, can negatively impact the hippocampus, a crucial brain structure involved in emotional regulation and memory processing. These findings provide a biological foundation for understanding the connection between chronic stress and mental health disorders.
There are several classifications of stress, each based on distinct aspects associated with it. The academic stress is distinguished as a type of situational stress that arises in the educational context and is related to the demands and requirements of the academic environment, among others. Barbayannis et al. (Citation2022) note that academic stress can manifest in the form of anxiety, depression, and emotional exhaustion, which can negatively affect students’ psychological well-being. Additionally, recent studies such as Espinosa et al. (Citation2020), showed that academic stress can have harmful consequences on students’ performance, motivation, and self-esteem.
The context of higher education represents a stressful scenario for students who, in addition to academic aspects, must face the transition from high school to university, which entails additional challenges such as adapting to new lifestyles, high competitiveness, changes in the environment, and the initiation of new relationships in an unfamiliar context. High social expectations about the future can contribute to increased academic stress. Authors such as Bashir et al. (Citation2019), Wang et al. (Citation2023) and Guzmán et al. (Citation2023) addressed this topic in recent publications, mentioning that the university environment involves a series of changes that students must adapt to, including an accelerated pace of study, deadlines for assignments and projects, and more in-depth coverage of topics, which can significantly impact students’ mental health.
When students begin university, they are faced with a multitude of scheduled tasks, the need to familiarize themselves and interact with new people in their academic environment, and a much higher level of demand compared to their previous years of education, including different work rhythms, schedules, and academic processes. All these factors create considerable pressure for students, who must balance their academic and personal responsibilities while adapting and growing in this new educational environment. A study by Bashir et al. (Citation2019) examined academic stress in university students and found that high expectations from professors and competition among peers can increase stress in the university environment. The study points out that stress can have negative effects on overall well-being, affecting students’ mental and physical health.
In addition, university students often face the pressure of making important decisions for their future, such as choosing a career or planning their professional path, and this uncertainty can generate additional anxiety and stress (Guzmán et al., Citation2023). Another stress-generating aspect is the pressure to excel academically and stand out in a highly competitive environment, which creates a constant sense of comparison and self-criticism. Students may experience the so-called “imposter syndrome,” where they doubt their abilities and feel that they do not deserve to be in university. This can generate emotional stress and affect their self-confidence (Cokley et al., Citation2017).
Exposure to peers and other students can also create pressure, as entering university involves a process of social adaptation. Students find themselves in an environment where they must establish new relationships and social networks, which can generate social anxiety due to the need to be accepted into a new group of peers and participate in extracurricular activities. Wang et al. (Citation2023) explored social stress in university students and found that a lack of social coping skills and a sense of isolation can contribute to the social stress experienced during university life.
In addition to academic and social factors, other aspects outside of university life can also contribute to stress. For example, many university students must deal with financial pressure, both their own and their parents’, as well as the cost of studying, which can generate additional stress as they try to balance studying and finding income to cover tuition, housing, food, and other related expenses, especially among those who have migrated to study. McCloud and Bann (Citation2019) examined the impact of financial stress on the mental health of university students and found that stress related to finances can have negative effects on the mental well-being of the students, increasing anxiety and depression.
In this context, after COVID-19 pandemic was declared in 2020 added a new and unpredictable stressful situation that caused an unprecedented crisis, with education being one of the most affected areas since face-to-face educational activities were prohibited at all levels. According to the Economic Commission for Latin America and the Caribbean ECLAC (Citation2020), more than 190 countries closed their educational establishments during the first semester of 2020 to prevent the spread of the virus and mitigate its impact. As a result, over 1.2 billion students of all levels were without access to face-to-face education. Data from the United Nations Educational, Scientific and Cultural Organization, International Institute for Higher Education in Latin America and the Caribbean reports that by the end of March 2020, more than 98% of the students in Latin America and the Caribbean from International Standard Classification of Education 5 to 8 levels were affected (Giannini, Citation2020).
To address this situation, a radical turn towards virtual teaching and learning modality, which existed for more than ten years but was not widely applied, was taken. Both teachers and students had to adapt to new conditions such as online classes, papers, and tests to continue their learning process (Bautista et al., Citation2020). Strong changes were made in life habits, having to reorganize their daily routines to adjust themselves.
Universities that had to migrate to a completely virtual education in 2020 need to adapt their academic model to ensure the health and well-being of the students, provide timely administrative service to clients, and ensure and improve academic quality. The academic model presented in Figure 1 was institutionalized in various universities, taking different names depending on the institution: hybrid, multimodal, flexible, blended; but with many coincidences.
Figure 1. Academic model: Hybrid model.
Display full size
According to Agyeiwaah et al. (Citation2022), students were given the opportunity to attend classes either in one of the modalities or a mix of them. These new models required efforts at various levels: i) intensive training of teachers in the use of information and communication technology for education, such as video conferencing tools, Learning Management Systems, survey systems, gamification, active methodologies, etc.; ii) selection of academic subjects that required face-to-face interaction, such as specialized laboratories, taking into account the relationship between the modality of the subject and the teaching competence; and iii) equipment and infrastructure adapted to allow the functioning of the hybrid model.
Initially temporary changes lasted longer than planned, with measures forbidding face-to-face lectures remaining in place for almost two across various countries worldwide. During this time, the lack of social contact, changes in socialization routines, and deprivation of extra-academic activities, among other factors, affected the psycho-emotional state of university students. This is because their educational process is not solely based on the learning of theoretical and practical knowledge but also on professional social interaction and the development of group ties. The isolation inevitably associated with confinement will have effects in terms of socio-emotional balance that will leave a mark, as emergency distance education has been accompanied by other manifestations, which are not less important for the different actors, although probably not very visible and documented (ECLAC, Citation2020).
Under these circumstances, it is crucial to measure the academic stress experienced by university students and its influence on their mental health. Stress can be defined as the relationship between the individual and their environment, in which the person perceives environmental demands as a threat to their well-being if they exceed or equal their resources to cope with them (Lazarus & Folkman, Citation2013). Academic stress, according to Lin and Chen (Citation2009), is the product of perceptions, frustrations, or problems related to the academic environment that result in the inability to adjust to the university requirements, leading to conflicting physical and mental phenomena. The most common stressors in this area are Teachers’ Stress, Results Stress, Test Stress, Studying in Groups Stress, Peer Stress, Time Management Stress, and Self-inflicted Stress.
The effects of stress, regardless of the factor that generates it, can impact physiological, emotional, cognitive, and behavioral levels (Barraza & Silerio, Citation2007). Therefore, it is crucial to measure its impact on mental health. Mental health is a term that has been conceptualized, measured, and studied based on the concept of well-being (Ryff, Citation1989), which is defined as individuals’ perception and subjective assessment of their lives (Keyes et al., Citation2008). Mental health is understood as a series of subjective factors such as thoughts, emotions, and beliefs that, if positive, produce positive functioning and functional contextual adaptation capacity in individuals. In this sense, mental health does not only involve the measurement of a single factor, but rather of several dimensions that condition it, according to the Mental Health Continuum Short Form (MHC-SF) (Keyes et al., Citation2008) used in this study, mental health is based on three general dimensions or areas: emotional, psychological and social well-being, which together determine the individual’s mental health.
In this context, the present study aimed to understand the relationship between academic stress and the mental health of university students in the new social and learning environment resulting from the COVID-19 pandemic. The research sought to answer the question of how academic stress affects the mental health of university students. The main objective was to evaluate the correlation and predictive value between academic stress and its different stressors on the mental health of university students. The study had three specific objectives: i) to measure the level of academic stress and its associated stressors (as mentioned above) in university students; ii) to evaluate the level of mental health in university students; and iii) to determine the relationship between academic stress and mental health in university students. The study also proposed the following hypotheses: a) University students encountered high levels of academic stress; b) The mental health levels of the students were languishing or moderate; and c) Academic stress had a correlation with languishing and moderate levels of mental health. Among the academic stressors, Result Stress, Test Stress, and Time Management Stress were identified as having the strongest association with mental health.
A representative sample of 1,265 undergraduate university students from a private university in Bolivia was assessed. Correlational analysis, stepwise Hierarchical Multiple Linear Regression analysis, and estimation of a probabilistic model of Languishing Mental Health were performed.
2. Materials and methods
2.1. Research design
The study adopted an ex post facto design as data on the level of academic stress and mental health of the students were collected after they had experienced these situations. Therefore, participants were not randomly assigned to experimental or control groups, but their condition was observed and measured using appropriate instruments for this study. The objective was to analyze the relationship between academic stressors and mental health of undergraduate university students.
2.2. Population and sampling
A cross-sectional, descriptive, relational, and analytical study was conducted during the second semester of 2021, with undergraduate students from all programs and faculties of a private university in Bolivia. The total number of enrolled students was 3,309, with 55.7% men, 44.3% women, and a mean age of 21 years. The sample size was calculated by considering the three university campuses as strata and faculties as clusters. The resulting total was a required sample of 1,060 students, with a 95% confidence level and an initial sampling error of 5%.
The study managed to obtain voluntary responses from 1,265 undergraduate university students (38% of total student population), surpassing the established sample size calculation. An invitation with a link to the questionnaires was sent to all students enrolled to conduct a full coverage study (census). Previous studies showed that not everyone responded to the invitation. Therefore, it was considered that those who responded to the questionnaires did so spontaneously, and the choice to respond or not was considered a random factor.
The response rate to the questionnaires was representative of the university’s overall student population, as well as segmented by campus, gender, faculty, and semester. At a general level throughout the university, the sampling error was calculated to be 3%. Additionally, it was possible to calculate the sampling error at the campus, gender, faculty, and semester levels, which did not exceed 7%.
2.3. Procedures
The questionnaires selected to determine academic stress and mental health were translated into Spanish and incorporated as components in a digital survey form for this study. A platform developed by the university in 2017, was utilized for this purpose. This platform is fully integrated with the university academic system database and aimed to enable teachers to generate surveys in their assigned subjects so that students could access them, thereby achieving better interaction between teachers and students.
The digital survey form was prepared in October 2021 and was validated for content, length, and language translation through a pilot test with university students. This test allowed for corrections, especially in the Spanish language translation of questions, to make them clearer. This resulted in the final version of the survey form being ready for implementation.
With the data collection tools ready, support was requested from university authorities to distribute the questionnaires to all students at each its campuses. The academic authorities reviewed the questionnaires and requested approval from the Ethics in Research Committee of the University to administer them to the students.
The university’s ethics committee reviewed the survey and concluded that the research did not incorporate an experimental approach at any of its stages. The purpose was simply to observe and measure specific characteristics of the study subjects without implicitly or explicitly seeking to modify their behavior, actions, or interpretation of reality. Furthermore, since the questionnaires were completely anonymous and students could voluntarily respond to them, the ethics committee approved the work, as the identity of respondents was guaranteed.
Once the ethics committee approval was obtained, university authorities approved the questionnaires to be shared with students throughout the university via a link in an official email, requesting voluntary support from students. The data collection officially started on 27 October 2021, and lasted until the end of the second semester of 2021, before the students’ vacation.
The survey responses were downloaded into an Excel format database, which was then reviewed and transformed into STATA 17 format for econometric analysis.
2.4. Measurements
The instrument used in this study to measure mental health were the Mental Health Continuum-Short Form (MHC-SF). This 14-item questionnaire (Keyes, Citation2002, Citation2005, Citation2006; Keyes et al., Citation2008) assesses mental health across three dimensions: a) Emotional Well-being (positive affect and life satisfaction); b) Social Well-being (including acceptance, actualization, social contribution, coherence, and social integration); and c) Psychological Well-being (autonomy, control, personal growth, positive relationships, self-acceptance, and purpose) (Ryff, Citation1989). The MHC-SF has demonstrated strong internal consistency with a Cronbach’s alpha above 0.70 (Keyes et al., Citation2008), and its three-factor structure (emotional, psychological, and social) has been confirmed in several studies (Gallagher et al., Citation2009; Góngora & Castro, Citation2018; Joshanloo et al., Citation2013; Lamers et al., Citation2010).
To measure academic stress and its stressors, this research employed the Lin and Chen (Citation2009) scale, which comprises seven academic stressors: Teachers’ Stress (TES), Results Stress (RS), Test Stress (TS), Stress of Studying in a Group (SGS), Peer Stress (PS), Time Management Stress (TMS), and Self-inflicted Stress (SIS). The questionnaire consisted of 34 five-point Likert scale statements, with responses ranging from 5 (completely agree) to 1 (completely disagree). The Cronbach reliability test and alpha values for each of the questionnaire’s components or factors ranged from 0.85–0.92, and the alpha value of the academic stress questionnaire was 0.90 (Lin & Chen, Citation2009). The K Pearson’s correlation analysis indicated a significant level of related coefficients between the components and the total score, ranging from 0.63–0.86.
2.5. Data analysis
The quantitative analysis of the data generated in this study required the application of three statistical and econometric techniques: Pearson correlation, Hierarchical Multiple Linear Regression (HMLR) analysis, and a probability model—Probit. These techniques provided a comprehensive understanding of the relationship between academic stressors and mental health.
Pearson correlation is a statistical measure that evaluates the linear relationship, strength, and direction between two quantitative variables. It is an important tool in research and descriptive statistics, as it can help to understand the relationships between variables and identify patterns of behavior in data. This measure varies from −1 to 1, where −1 indicates a perfect negative relationship, 0 indicates no correlation, and 1 indicates a perfect positive relationship (Bolshakova, Citation2021). Pearson correlation was used to determine the strength and direction of the relationship between academic stressors and the mental health in university students. However, as correlation does not necessarily indicate causality, we also conducted an HMLR analysis.
HMLR is a statistical technique that allows for the examination of the relationship between a dependent variable and multiple independent variables while controlling for other factors that could influence the relationship (Petrocelli, Citation2003). In this study, the dependent variable was mental health, while the independent variables were different academic stressors. The HMLR analysis was conducted by introducing the measurement equation with a significance level of p < 0.05. The independent variables (academic stressors) were organized in the equation based on the percentage of explained variance. This allowed us to identify the unique contributions of each academic stressor to mental health outcomes while controlling for other factors that could influence the relationship.
Probability model—Probit is a technique used to examine the relationship between the levels of academic stressors and languishing mental health. The Probit model allowed us to determine the coefficients of the levels of academic stressors and predict the probability that a student would experience Languishing Mental Health, treated as a binary variable that took the value of 1 when an individual had Languishing Mental Health, and 0 otherwise (Greene, Citation1996). This enabled us to identify the academic stressors and their levels that contribute to Languishing Mental Health, which could be used to develop interventions aimed at addressing these factors and improving mental health outcomes.
In summary, the combination of techniques provided a comprehensive understanding of the relationship between academic stress and mental health.
3. Results
3.1. Descriptive statistics and correlations
To conduct this study, a total of 1,265 students from a private university in Bolivia completed the questionnaires developed specifically for this purpose. Of these, 615 (48.6%) were female and 650 (51.4%) were male, with an age range of 17 to 31 years and a mean age of 21.68 (±2.04) years. Table 1 presents the means and standard deviations of the variables analyzed in this study. Academic stress, with its seven analyzed stressors (TES—Teachers’ Stress, RS—Results Stress, TS—Test Stress, SGS—Studying in Groups Stress, PS—Peer Stress, TMS—Time Management Stress, and SIS—Self-inflicted Stress), had a mean of 2.67 points with a standard deviation of 0.69 points, and no outliers were detected. The mental health variable had a mean of 2.14 points with a standard deviation of 0.69 points, and no significant presence of outliers was detected.
Table 1. Mean and standard deviations for mental health and stressors of academic stress
Download CSVDisplay Table
The descriptive analysis of mental health, based on the present levels, showed that 18.1% (229) of the students presented Languishing Mental Health, 49.8% (630) presented moderate levels (Moderate Mental Health), and 32.1% (406) presented high levels of mental health (Flourishing Mental Health). After analyzing the stressors of academic stress, 14.3% (181) exhibited high levels of TES, 15.7% (198) experienced RS, 44.7% (565) underwent TS, 13.8% (174) experienced SGS, 8.3% (105) experienced PS, 26.7% (338) experienced TMS, and 22.4% (283) experienced SIS. The breakdown and description of this data are displayed in Table 2.
Table 2. Distribution of mental health levels according to stressors of academic stress in undergraduate students from a private university in Bolivia, 2021
Download CSVDisplay Table
As observed in the distribution table, among university students, mental health showed a predominantly moderate trend (49.8%), and the primary academic stressors were related to TS (44.7%), TMS (26.7%), and SIS (22.4%). The latter was defined as the self-demands resulting from contextual elements concerning one’s expectations. This factor was associated with students’ belief in successfully coping with academic demands, which was an eminently subjective factor influenced by their beliefs, perceptions, and feelings regarding their abilities to handle the context.
3.2. Predictive value of academic stress about mental health
The study analyzed the predictive value of academic stress on mental health, and the results are presented in Table 3. The analysis showed significant negative correlations between all academic stressors and mental health levels, with (r) larger than 0.20 as an absolute value. Among the academic stressors, TES (r=−0.24,p < 0.01) and PS (r=−0.24,p < 0.01) showed weak negative correlations, followed by TS (r=−0.27,p < 0.01), RS (r=−0.33,p < 0.01), SGS (r=−0.33,p < 0.01), and TMS (r=−0.37,p < 0.01). The SIS had a moderate negative correlation (r=−0.42,p < 0.01).
Table 3. Matrix of correlation coefficients (r) between the mental health levels and stressors of academic stress in undergraduate students from a private university in Bolivia, 2021
Download CSVDisplay Table
Additionally, a HMLR analysis was performed, and the results are presented in Table 4. The analysis showed that the stressors of SIS, TMS, SGS, and RS met the predictive criteria with a significant value (R2=0.304,F=116.96,p<0.01). SIS had the strongest correlation according to the adjusted R2 (R2=0.238,F=342.62,p<0.01). The introduction of TMS, SGS, and RS stressors increased the prediction by 6.60%, while the other stressors were excluded due to their insignificant correlation. The analysis revealed a significant increase in the explanation of the academic stress and mental health among university students. The additional predictive value, when entered the SIS equation, was related to the TMS, SGS, and RS (p<0.01) stressors.
Table 4. Hierarchical multiple linear regression analysis of mental health on each stressor of academic stress
Download CSVDisplay Table
The estimated models did not present any problems of heteroscedasticity in the residuals (Ho: Constant variance, chi−square=0.00,p=0.96), high collinearity between regressors (variance enlargement factor -VIF- not greater than 1.85), and no omitted relevant variables at 95% confidence (Ramsey test—RESET, Ho: the model has not omitted variables, F=0.63,p=0.60). In conclusion, the final model was well-adjusted.
Three dimensions of mental health were analyzed: psychological, emotional, and social well-being. The results showed that 26% of the variance in the Emotional Well-being dimension was explained by five academic stressors, with SIS, TMS, RS, SGS, and PS being the most significant in that order. In addition, 14.5% of the variance in the Social Well-being dimension was explained by SIS, TMS, and SGS, while 30% of the variance in the Psychological Well-being dimension was explained by SIS, TMS, SGS, and RS. The study findings suggest that the mental health of the student population is related to subjective, psychological, emotional, and perceptual factors regarding their ability to cope with academic and economic realities. Academic stressors for these students are primarily psycho-emotional rather than operational, and subjective perceptions play a crucial role in how students react to the academic environment.
3.3. Probability model for Languishing Mental Health
A probability model (probit) was estimated to analyze the probability of having Languishing Mental Health, which was treated as a binary variable taking the value of 1 when an individual had Languishing Mental Health and 0 otherwise (Moderate or Flourishing Mental Health). The Kruskal Wallis Test showed statistically significant differences in the mean scores of each stressor of academic stress, including TES (Teachers’ Stress), RS (Results Stress), TS (Test Stress), SGS (Studying in Groups Stress), PS (Peer Stress), TMS (Time Management Stress), and SIS (Self-inflicted Stress) based on the level of mental health (Languishing, Moderate, and Flourishing Mental Health). The pairwise comparisons for the Sidak, Bonferroni, and Scheffe post hoc tests supported the results of the Kruskal Wallis Test and showed statistically significant differences in the mean scores of each stressor of academic stress based on mental health level at a 99% confidence level, favoring Flourishing Mental Health compared to Moderate Mental Health (p<0.01), Flourishing Mental Health compared to Languishing Mental Health (p<0.01), and Moderate Mental Health compared to Languishing Mental Health (p<0.01). Figure 2 displayed the Kernel density functions estimated for TES, RS, TS, SGS, PS, TMS, and SIS by mental health levels (Languishing, Moderate, and Flourishing Mental Health), which confirmed the results of the Kruskal Wallis Test, Sidak, Bonferroni, and Scheffe post hoc tests.
Figure 2. Kernel density functions estimated for academic stressors by mental health levels.
Display full size
Considering the statistically significant differences found in each mental health level according to each stressor of academic stress, a probability model was estimated for Languishing Mental Health to approximate the differences in the effects that the different stressors of academic stress have on explaining the variance of mental health in the HMLR model, on the most worrying (sensitive) level of mental health.
The model presented a pseudo R2 of 0.15; however, other measures were used to check the fit of the predicted values to the observed values, as the pseudo-McFadden R2 does not have a direct interpretation. Among these measures were the Hosmer and Lemeshow test and the classification table. The first indicated a p-value of 0.11, allowing us not to reject the null hypothesis that the model is well-adjusted (Ho: The data are consistent with a specified distribution). The second measure is the global classification rate, which measured the percentage of observations for which the modeling was correctly predicted, showing a value of 82.92%.
Table 5 presented the marginal effects of the different academic stressors on the probability model estimated for the level of Languishing Mental Health. The results showed that if students experienced medium levels of SIS, the probability of them experiencing Languishing Mental Health was higher by 8 percentage points (pp) compared to students who had low SIS. Moreover, if they experienced high SIS, the probability of them experiencing Languishing Mental Health was even greater by 20pp compared to students who had low SIS. Similarly, for students who had high levels of TMS, the probability of them experiencing Languishing Mental Health was greater by 11pp compared to students who had low TMS. If they suffered from high levels of SGS, the probability of them experiencing Languishing Mental Health was greater by 11pp compared to students who had low SGS. Finally, if they suffered from high levels of RS, the probability of them experiencing Languishing Mental Health was higher by 12pp compared to students who had low RS.
Table 5. Association between languishing mental health and levels of academic stressors
Download CSVDisplay Table
Therefore, it was concluded that moderate academic stress can result in Languishing Mental Health among university students, which is characterized by indicators of stress, depression, anxiety, and other psycho-emotional conditions that could potentially affect their performance, self-perception, and self-efficacy. The findings indicate that students who experience high levels of SIS and poor TMS are more likely to have Languishing Mental Health. Additionally, Languishing Mental Health can be associated with high levels of stress related to working in groups and obtaining negative results in assignments.
4. Discussion
The results of the academic stress and mental health scales applied to the population sample showed that academic stress in university students was predominantly linked to SIS. According to Naranjo (Citation2009), any situation that a person perceived as a demand or a threat requiring rapid change produced stress, but not all situations, nor all stressors, were negative or had to carry consequences. Thus, the impact of stress on mental health depended on how different situations were perceived, producing different impacts.
This study had several strengths, including the wide representation of students based on sex, age, semester, and faculty. In total, 38% of all enrolled students voluntarily completed the questionnaire, which is more than other studies on academic stress, such as those conducted by Restrepo et al. (Citation2020), Luque et al. (Citation2022), Micin and Bagladi (Citation2011), Denovan et al. (Citation2017), and Kennett et al. (Citation2020).
The results of this study indicated that situations of high academic stress predicted a higher probability of experiencing Languishing Mental Health, with stress generated by Self-inflicted Stress being the most relevant factor among the students. This suggests that the self-demands and perception of self-efficacy of the students are important factors in the appearance of high stress, highlighting the direct relationship between high levels of academic stress and the likelihood of having Languishing Mental Health.
In this way, the correlation results between stress factors and the mental health of university students showed that academic stress was linked to self-generated stress, with a moderate correlation, showing that self-demand in academic stressors, personal (and socio-family) expectations, regarding performance developed into the need to comply with what the student believed was expected of them (even when this was not the case), causing continuous pressure (momentary and prolonged in time) that would only be alleviated when it was considered that one’s own or the environment’s expectations had been met, which responded to subjective components, since they were not stated objectively, they did not generate a measurable data of scope or compliance. This need to respond to subjective, own, or environmental demands could lead to a constant feeling of dissatisfaction or failure since they were linked to self-perception of sufficiency, beliefs about oneself being able to respond to the situations of the environment, and to mental schemes about one’s abilities, such as being good, successful, unsuccessful, or useless (Álvarez et al., Citation2018).
According to Martínez and Díaz (Citation2007), stress is strongly influenced by individuals’ subjective beliefs about the demands placed on them and their capacity for understanding and control. If the evaluation of these beliefs is negative, it can generate stress and have a negative impact on mental health. Recent research supports this idea, highlighting that the way people interpret and evaluate stressful situations, as well as their beliefs about coping capacity, are important factors in the experience of stress and its impact on mental health (Rodríguez & Sánchez, Citation2022). Therefore, these subjective beliefs about the self and the potential response to environmental demands would generate stress if the evaluation is negative, consequently also leading to lower levels of mental health.
It is evident from the present study that stress variables generated by objective factors such as evaluations, academic results, teachers, and peers, as well as studying in groups, have only a weak correlation with mental health. This finding contrasts with other studies like Ramírez et al. (Citation2015) and Berrio and Mazo (Citation2011) that have identified task overload, evaluations, time management, group competitiveness, conflict between classmates, and evaluations as the main academic stressors in university populations. However, it is important to consider that the pandemic situation and the virtualization of classes may have influenced the results. In this regard, case studies conducted during 2021, such as Restrepo et al. (Citation2020) and Luque et al. (Citation2022), have also found that academic stress in students during the pandemic is linked to task overload, time management, evaluations, job type, and participation in virtual classes.
The study conducted by Silva et al. (Citation2020) revealed that the academic stressors of greatest concern during the pandemic were task overload, evaluations, assignments, and time constraints, which were not observed in the population studied in this research. The data from this study indicated that the mental health of the students is linked to academic stress, which can be predicted by Self-inflicted Stress associated with personal, family, and social expectations. These self-demands are related to the perception of sufficiency in the face of social and academic demands, which are subjective factors associated with beliefs about one’s capacity to respond to environmental demands (Chacón et al., Citation2019).
The difference in results could be attributed to contextual factors specific to the Bolivian environment or peculiarities of the study population. Our study was conducted in a private university, where the tuition fees are much higher than those of public universities, and during a pandemic when the economic crisis was at its peak. Furthermore, majority of the university students (57% of the total number of enrolled students) were beneficiaries of some form of scholarship before and during the pandemic.
This particular context could lead students to perceive a need for extra effort and dedication to maintain a high academic level in order to keep their financial support through scholarships and to acknowledge their family’s efforts to cover the fees to study at a private university, which could result in Self-inflicted Stress affecting the mental health of this population. On the other hand, the study results also suggest that this Self-inflicted Stress is related to time management, the feeling of insufficiency to meet deadlines for assignment delivery, or the belief that it will not be possible to complete said assignments within the established period. These stressors could be related to the educational model of the institution, as the subjects are modular, meaning 24 continuous sessions (Monday to Friday) with assignments delivery and tests every eight days.
As evidenced by the results, one factor that was found to be correlated with mental health is group studying. The items evaluated in this indicator dealt with sharing group assignments and the challenge of finding suitable colleagues to work with. This may be since control over the time required to complete the work is distributed among the members of the group, and therefore, each member may feel anxious that their colleague will not deliver the work on time, resulting in poor academic results. Additionally, this indicator measures subjective variables such as fear of being mocked by peers, feeling hurt by it, feeling nervous when speaking in public, and the perception of hostility and distrust towards others, which may be exacerbated in a virtual learning environment. It is noteworthy that many of the students have been taking virtual classes for two years, never having met their classmates or teachers in person, with only a screen separating them. Various authors have also highlighted the significance of human relationships as a central cause of stress, given the human need for affection and a sense of belonging.
The study population’s academic stress factors were found to be associated with non-objective elements, specifically subjective beliefs about their abilities to cope with the demands of the context, and control over contingent elements. Within the studied university system, most assignments were group-based, and individual students did not always have control over the entire work process. This lack of control, coupled with a lack of trust in their classmates’ ways of working and the quality of their work, could be a major source of stress.
In this way, the mental health of the studied population is linked to subjective, psychological, emotional, and above all, perceptual variables regarding their abilities to react to academic reality and family economic reality. This means that academic stress for these students is more psychoemotional than operational, more subjective than linked to objective variables, and therefore, the impact it generates at a psychoemotional level is related to how the student perceives themselves in terms of their possibilities for action in the environment.
It is interesting to note that the study found the opposite of the results obtained in the study conducted by Restrepo et al. (Citation2020). While they assumed that academic stress was determined by objective conditions, our research provided evidence to the contrary, showing that stress is primarily influenced by the individual’s subjective perception of their ability to cope with academic demands (such as self-demand, beliefs of self-sufficiency, perception of self-efficacy, and personal expectations), as well as the need to depend on group study to achieve positive academic outcomes. This indicates that the process of academic stress in this context can be addressed from a cognitive-behavioral perspective, as opposed to other studies that point to external factors as stressors for students.
From an academic perspective, both teachers and students have had to adapt to virtual education, changing their habits, routines, and even the way in which teachers teach and students learn. This shift to virtual and subsequently hybrid learning has had an impact on the results presented in our research, as students have had to exert more effort to adapt to studying at home, in environments that are sometimes shared with their entire family, and in many cases where they have had to share technological resources with parents and siblings (Ariyo et al., Citation2022). All of this has required an additional self-learning effort on the part of the students, as noted by Pardeshi et al. (Citation2022), who found that self-learning was one of the factors that negatively affected learning during the COVID-19 pandemic, as students had to complete homework, tests, and group work to maintain and improve their grades.
The relationship between the incidence of academic stress and students’ mental health indicates the importance of the academic environment and related experiences on students’ psychological, emotional and social well-being. The dimensions that show a greater connection with mental health are psychological and emotional well-being, suggesting that the possibility of positive functioning is mediated by the way in which the person lives that stress experience, by the individual coping capacity and the perception of personal self-efficacy (Díaz et al., Citation2006). Considering that the greatest stressor is the one generated by oneself, it can be inferred that the negative perception of the students about their abilities to respond to the demands of the academic environment puts pressure on students who have high levels of self-demand, personal or socio-family expectations (real or imaginary) that condition their functionality. This can generate poor adaptation to the demands, dynamics, and academic processes.
Therefore, the need to respond to subjective demands from the environment, and particularly from oneself, can lead to a constant feeling of dissatisfaction or even failure based on equally subjective aspects of self-assessment. These are linked to the self-perception of sufficiency and mental schemas about one’s abilities, such as being good, successful, unsuccessful, or useless.
The stressors of time management and group work, in this research show an important relationship with the e-learning teaching model. Due to the lack of separation between home and university, many students were unable to manage their time as effectively as before, as noted by Heo et al. (Citation2021), where time management plays a crucial role in the success of online learning. In addition, effective communication plays a vital role in promoting positive virtual learning (Penrod et al., Citation2022), and the communication between teachers and students and among students themselves was not as smooth as it was in face-to-face classes. The quarantines during 2020 and 2021 made group sessions and coordination more challenging for students, as a result, the stressor related to group management is evident in our research.
5. Limitations
The study had certain limitations that needed to be considered when interpreting the results, primarily due to the presence of other factors that could have influenced mental health and academic stress at the time of questionnaire completion. For instance, social, economic, and cultural factors that were not assessed in this study could have had an impact.
The study acknowledged specific limitations that should be taken into consideration when interpreting the results. Firstly, it should be noted that the study focused on a private university, where students faced particular social, cultural, and economic conditions. These conditions may have significantly differed from those of the students at a public university, which could have influenced the results obtained and made it challenging to generalize the findings. Another limitation to consider was the virtual modality imposed by the Ministry of Education regulations. The shift to the virtual teaching-learning environment, inherent in the pandemic situation, introduced new conditions that may have added pressure on students. Finally, adapting to online teaching could have influenced active participation, interaction with teachers and classmates, and potentially affected the academic stress levels of students.
6. Conclusions and implications
This study found that Self-inflicted Stress, time management stress, group work stress, and performance stress were predictors of mental health, supporting the hypothesis that there is a negative relationship between academic stress and the mental health of university students. Identifying specific stressors can help reduce and understand the impact of stress on mental health, mitigate its damage, and lessen its negative impact on academic performance. Implementing educational programs to prevent stress and its negative effects can enhance students’ ability to cope with stressful situations.
Additionally, the results of the stepwise Hierarchical Multiple Linear Regression analysis showed a relationship between academic stressors and the level of mental health in university students. Some situations had a greater impact on the overall level of academic stress than others, with self-generated stress being the most relevant stressor among the students in this research. This suggests that students with lower self-efficacy and high demands and expectations regarding their academic results and performance tend to perceive the academic environment as threatening. This could be due to having less confidence in their abilities or not trusting the work of their classmates, particularly in group projects. The study also found a significant association between the level of Languishing Mental Health and academic stressors (SIS, TMS, SGS, and RS). Therefore, greater attention should be paid to this population of students, as high academic stressors predict a higher probability of experiencing Languishing Mental Health.
The findings of this study on academic stress in university students and its impact on mental health have relevant practical implications. First, it is important to focus on the virtual teaching/learning modality, which requires rethinking the model and implementing support strategies and intervention programs aimed at managing stress in the academic environment, particularly in the virtual modality. It is essential to foster healthy university environments that promote the mental well-being of the students, whether virtual or face-to-face. This could include initiatives such as better planning of activities and work presentations, creating rest intervals during classes, implementing relaxation spaces, sports or recreational activities, and promoting an adequate balance between academic work and other activities of student life. Workshops on stress management and coping techniques, time management, and self-perception of efficacy in relation to academic processes are also necessary. Finally, the study’s results emphasize the need to raise awareness among teachers and academic staff about the impact of stress on students’ mental health, train teachers to recognize the signs of stress, and adapt teaching methodologies to reduce the academic load.
Future studies can be developed based on the findings of this research, focused on comparative analysis in a post-pandemic context and complemented by measuring and identifying students’ emotions in the classroom.
Authors’ contributions
In the study, Pamela Córdova, Patricia Gasser, and Alberto Sanjinés contributed to its conception and design. Hernán Naranjo and Pamela Córdova oversaw the process of data collection, database development, and data processing and analysis. Patricia Gasser, Isabel La Fuente, and Alberto Grájeda contributed to data interpretation. The manuscript draft was written by Pamela Córdova, Patricia Gasser, and Isabel La Fuente, while Hernán Naranjo, Alberto Grájeda, and Alberto Sanjinés reviewed and revised the draft. All authors participated in reading the final manuscript and approved its submission.
Availability of data and materials
The datasets generated and analyzed during the current study are not publicly available due to privacy restrictions but are available from the corresponding author on reasonable request. The data that can be provided will be provided in a de-identified manner.
Ethical approval
The Ethics in Research Committee of the University approved this study, and an ethical exemption letter was issued. The identity of all participants has been anonymized.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Additional information
Notes on contributors
Pamela Córdova Olivera
Pamela Córdova Olivera, expert in Health Economics and Impact Evaluation, holds a PhD in Economics from UPB. She is a professor, researcher and Head of the Economics program at UPB.
Patricia Gasser Gordillo
Patricia Gasser Gordillo, in Social Psychology from Universidad Complutense de Madrid, Spain; directed the Organizational Psychology program at UPB and, currently, conducts research on mental health and emotional states.
Hernán Naranjo Mejía
Hernán Naranjo Mejía, professor and researcher in the Data Analysis Unit for Innovation and Academic Quality at UPB, is a doctoral candidate in the field of Agri-food Economics at the Universitat Politècnica de València, Spain.
Isabel La Fuente Taborga
Isabel La Fuente Taborga is a researcher, professor and Head of Organizational Psychology program at UPB. Expert in Organizational Psychology and Human Talent Management, she holds a PhD from Universidad Complutense de Madrid, Spain.
Alberto Grajeda Chacón
Alberto Grájeda Chacón, PhD in Business Innovation from the Universitat Politècnica de València, Spain; leads the Center for Innovation in Information Technology for Education at UPB. His expertise lies in the effective implementation of educational tools utilizing TIC.
Alberto Sanjinés Unzueta
Alberto Sanjinés Unzueta, expert in Business Ethics, Compliance, and Social Responsibility; holds a PhD in Business Administration from UPB, Bolivia. He is the Academic Vice President at UPB, leading the process of academic and tech-ed innovation.