academic stress research proposal

• Research article
• Open access
• Published: 26 October 2019

Stress among university students: factorial structure and measurement invariance of the Italian version of the Effort-Reward Imbalance student questionnaire

• Igor Portoghese 1 ,
• Maura Galletta   ORCID: orcid.org/0000-0002-0124-4248 1 ,
• Fabio Porru 2 ,
• Alex Burdorf 2 ,
• Salvatore Sardo 1 ,
• Ernesto D’Aloja 1 ,
• Gabriele Finco 1 &
• Marcello Campagna 1  

BMC Psychology volume  7 , Article number:  68 ( 2019 ) Cite this article

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In the last decade academic stress and its mental health implications amongst university students has become a global topic. The use of valid and theoretically-grounded measures of academic stress in university settings is crucial. The aim of this study was to examine the factorial structure, reliability and measurement invariance of the short student version of the effort-reward imbalance questionnaire (ERI-SQ).

A total of 6448 Italian university students participated in an online cross-sectional survey. The factorial structure was investigated using exploratory factor analysis and confirmatory factor analysis. Finally, the measurement invariance of the ERI-SQ was investigated.

Results from explorative and confirmatory factor analyses showed acceptable fits for the Italian version of the ERI-SQ. A modified version of 12 items showed the best fit to the data confirming the 3-factor model. Moreover, multigroup analyses showed metric invariance across gender and university course (health vs other courses).

Conclusions

In sum, our results suggest that the ERI-SQ is a valid, reliable and robust instrument for the measurement of stress among Italian university students.

Peer Review reports

In the last decade, there has been a growing attention in investigating stress risk factors and well-being consequences among university student’s population [ 1 , 2 ]. Stress and mental health of university students is a crucial public health subject as healthy students will be the healthier workers of the future. Attending university has the potential to become a positive and satisfying experience for students’ life. However, there is empirical evidence that being a student may become a stressful experience [ 1 , 3 , 4 , 5 , 6 ]. Stallman and Hurst [ 2 ] distinguished between eustress, important for student motivation and success at university, and distress, harmful for student’s well-being, as it exposes to a higher risk of psychological (for example, anxiety and burnout), behavioral (for example eating disorders), physical health problems (for example, ulcers, high blood pressure, and headaches), and suicidal ideation [ 7 , 8 , 9 , 10 ]. Furthermore, many scholars found that high stress was linked to reduced academic performance, low grade averages, and low rates of graduation and higher dropout [ 11 , 12 , 13 , 14 , 15 ].

Academic stressors have been identified as including high workload, attending lessons, respecting deadlines, balancing university and private life, and economic issues. Those stressors are linked to a greater risk of distress and reduced academic achievement [ 1 , 16 , 17 , 18 , 19 ].

Many authors adopted and extended original measures of stress, for example, by adapting work related stress measures to the university context [ 20 , 21 ]. Most of these measures were designed for medical students [ 22 ] or employed measures of stress not specifically developed for the academic context [ 20 , 21 , 22 ].

According to Hilger-Kolb, Diehl, Herr, and Loerbroks [ 23 ], the vast majority of these measures lack a stress theoretical model. It may represent an important limitation as, meausers based on a common tested stress model may be better help researchers to capture the links between stress and health among university students and to develop theory-based interventions [ 21 ]. Effort-Reward Imbalance (ERI) [ 24 ] is among the most common tested and valid models of stress. According to this model, when high efforts are balanced by low rewards, the resulting imbalance may generate negative emotions and sustained stress experiences. Originally developed to investigate stress risks among workers, this model has been the theorethical root of many studies investigating stress in non-working contexts.

Recently, Wege, Muth, Angerer, and Siegrist [ 25 ] extended the original ERI model to the context of university and adapted the ERI short questionnaire to the university setting, showing good psychometric properties. Thus, according to this theoretical approach, students’ stress was defined as the result of an imbalance between effort, such as high study load, and reward, such as being respected from supervisors.

A vast number of empirical studies measuring effort–reward imbalance in workplace context confirmed good psychometric qualities of the ERI short questionnaire [ 26 , 27 ]. Furthermore, psychometrically validated versions have been tested in 9 languages and in large European cohort studies, confirming the good psychometric qualities of the short ERI [ 28 , 29 ].

Concerning the student version of the ERI, there is limited psychometric information available. Given the importance of academic stress for understanding students’ mental health risk, the aim of this study was to investigate the psychometric properties of the Italian version of the ERI-student questionnaire [ 25 ]. To address this goal, we examined the factor structure of the Italian version of the ERI-SQ, assessed internal consistency for the dimensions of effort, reward, and over-commitment, and test the measurement invariance of the ERI-SQ.

Participants and procedure

The study population (convenience sample) was recruited through a public announcement at electronic learning platforms for students and university students’ associations’ network that contained an invitation for participating in a “Health Promoting University” survey. The online survey was implemented with Limesurvey from October 16th, 2017 to November 27th, 2017 and was restricted to enrolled university students (bachelor level and master level). The survey’s homepage reported the online informed consent form with specific information about study purpose, general description of the questionnaire, including information about risks and benefits of participation. Also, the time necessary to complete the survey (less than 10 min) and privacy policy information were reported. Specifically, to ensure anonimity, we did not register ip address neither requested any another sensitive data. The investigators and research team did not employ any active advertising to increase recruitment rates neither played any active role in selecting and/or targeting specific subpopulations of respondents. A total of 9883 students agreed to participate in the survey with 6448 (65.24%) completing the survey (target population: 1.654.680 Italian university students in 2017). The Italian version of the ERI-SQ (see Table 4 in Appendix ) was translated following the back-translation procedure [ 30 ].

Demographics

The sample for this research consisted of 75.5% females ( n  = 4869). Participants in this study ranged from 19 to 56 years of age, M = 22.97, SD = 3.01. 56.2% (3624) were enrolled in bachelor prrogrammes and 43.8% (2824) in master programmes. 39.6% (2551) were enrolled in health related courses (such as medicine, nursing, psychology, and biomedical science).

Stress was assessed with the ERI-SQ [ 25 ] that was developed for use in student samples. The version adopted in this study consists of 14 items that constitute three scales: Effort (EFF; 3 items; example: “I have constant time pressure due to a heavy study load”), Rewards (REW; 6 items; example: “I receive the respect I deserve from my supervisors/teachers”), and over-commitment (OC; 6 items; example: “As soon as I get up in the morning I start thinking about study problems”). All items are scored on a 4-point rating scale ranging from 1 (strongly disagree) to 4 (strongly agree). Average scores of items ratings for each subscale were calculated following appropriate recoding.

Statistical analyses

Statistical analyses were performed with R [ 31 ] and Rstudio [ 32 ]. The factorial structure was investigated using exploratory factor analysis (EFA; psych package) [ 33 ] and confirmatory factor analysis (CFA; lavaan package) [ 34 ]. The dataset was randomly split in half to allow for independent EFA (training set) and CFA (test set). A robust ML estimator was used for correcting violations of multivariate normality.

The analyses were conducted in two stages. Firstly, an EFA with principal axis factor (PAF) analysis was performed. Using Horn’s Parallel Analysis for factor retention. Internal consistency was assessed via Cronbach’s alpha coefficient.

The second stage of analysis involved investigating the factor structure of the Italian version of the ERI-SQ, a series of CFA were performed. As Mardia’s test of multivariate kurtosis (28.78, p  < .0001) showed multivariate non-normality, we investigated model fit with robust maximum likelihood (MLM) [ 35 ]. We compared alternative models: a 1-factor model, in which all 14 items were assessed as one common factor, a 3-factor model where items reflected the three subscales of the ERI-SQ, and a three-factor model with adjustments made according to error theory. We considered several fit indices: χ2(S-B χ2) [ 36 ], the robust root mean square error of approximation (RMSEA); the standardized root mean square residual (SRMR) and the robust comparative fit index (CFI). For CFI, score > .90 indicated acceptable model fit. For both RMSEA and SRMR, score ≤ .05 was considered a good fit, and ≥ .08 a fair fit [ 37 , 38 ].

Finally, the measurement invariance of the ERI-SQ was investigated. We performed a series of multi-group CFAs. We tested 5 nested models with progressive constrained parameters: Model 0 tested for configural invariance; Model 1 tested for metric invariance (constrained factor loadings); Model 2 tested for scalar invariance (constrained factor loadings and item intercepts); Model 3 tested for uniqueness invariance (constrained factor loadings, item intercepts, and residual item variances/covariances); Model 4 tested for structural invariance (constrained factor loadings, item intercepts, and factor variances/covariances). Models were compared by using the chi-square (χ2) [ 39 ]. In comparing nested models, we considered changes in CFI, RMSEA, and SRMR indices as follows: ΔCFI ≤ − 0.02 [ 40 , 41 ], ΔRMSEA ≤0.015, and ΔSRMR ≤0.03 for tests of factor loading invariance [ 40 , 42 ] and ΔCFI ≤-0.01, RMSEA ≤0.015, and SRMR ≤0.01 for test of scalar invariance [ 42 ].

Exploratory factor analysis

We split the dataset ( n  = 6448) into random training and test samples. EFA was performed on the training sample ( n  = 3879). Results from parallel analysis with 5000 parallel data sets using 95th percentile random eigenvalue showed that the eigenvalues for the first three factors exceeded those generated by the random data sets. Subsequently, a three-factor solution was inspected in a principal axis factor analysis with varimax rotation on the 14 items of the ERI-SQ (Table 1 ).

The EFA revealed that two items (EFF2 “I have many interruptions and disturbances while preparing for my exams” and REW4r “ I am not sure whether I can successfully accomplish my university trainings”) loaded on the same factor. An item analysis revealed that, probably, both items have a general and ambiguous formulation among student population. These items were therefore deleted from all analyses, as subsequent analyses were conducted with the remaining 12 items. We then re-conducted a principle axis factor analysis with varimax rotation. The three factors collectively explained 40.0% of the variance in the three facets. After rotation, the factors were interpreted as effort, reward and over-commitment.

Confirmatory factor analysis

Based on the results from the EFA, three models were tested on the test sample ( n  = 3879; Table  2 ).

Fit indices for the unidimensional model S-Bχ2(54) = 1833.95, rCFI = .78, rTLI = .73, RMSEA = .109, SRMR = .084 suggested that the model did not provide a good fit to the data. We next considered the three-factor model [ 21 ]. Fit indices suggested this model fits the data well, S-Bχ2(51) = 384.17, rCFI = .96, rTLI = .95, rRMSEA = .048, SRMR = .033. The χ2 difference test was significant, ΔS-Bχ2(3) = 1449.79, p  < .001. All standardized factor loadings were significant.

Internal consistency was .66 for reward, and .78 for overcommitment. Correlations between the three latent factors were as follows: −.30 between effort and reward, .52 between effort and over-commitment, −.33 between reward and over-commitment. Mean scores were: effort = 3.04 (SD = 0.59), reward = 2.67 (SD = 0.48) and over-commitment = 2.65 (SD = 0.63). The mean value of the effort-reward ratio was 1.20 (SD = 0.41).

Measurement invariance

Next, for testing measurement invariance, we conducted a series of multi-group CFAs across different groups: health (medicine, nursing, etc.) vs other courses (engineering, economy, etc.) and gender (male vs female).

First, a series of multi-group CFA (MGCFA) was conducted on the health and other university courses. Table  3 shows that configural invariance was supported (Model 0) as fit the data well across health courses ( n  = 2551) and other courses ( n  = 3897): S-Bχ2(102) = 398.06, CFI = .962, RMSEA = .045, SRMR = .032. All loadings were significant ( p  < .01). We found support for metric invariance (Model 1): ΔCFI = −.001, ΔRMSEA = −.001, and ΔSRMR = −.002. Next, we did not find support for scalar invariance (Model 2; ΔCFI = − .043; ΔRMSEA = .019, and ΔSRMR = .017). As full scalar invariance was not supported, we tested for partial invariance. Inspecting modification indices, we found that three items from the reward subscale (REW2 “I receive the respect I deserve from my fellow students”; REW3 “I am treated unfairly at university”; and REW6 “Considering all my efforts and achievements, my job promotion prospects are adequate”) and all items from the over-commitment subscale lacked invariance. However, as showed on Table 3 , partial scalar invariance (Model 2b) was not supported (ΔCF = −.021, ΔRMSEA = −.012, and ΔSRMR = .011).

Next, we performed a series of MGCFAs to test the invariance of the ERI-SQ between female and male students (Table 3 ). We found support for configural invariance (Model 0) across female ( n  = 4869) and male ( n  = 1579) groups: S-Bχ2(102) = 445.20, CFI = .956, RMSEA = .049, SRMR = .033. All loadings were significant ( p  < .01). Next, we found support for metric invariance (Model 1): ΔCFI = − .001, ΔRMSEA = −.002, and ΔSRMR = .003. Next we found support for scalar invariance (Model 2): ΔCFI = −.009, ΔRMSEA = .003, and ΔSRMR = .002. Next uniqueness invariance (Model 3) was supported: ΔCFI = −.005, ΔRMSEA = −.001, and ΔSRMR = .002. Finally, we found support for structural invariance (Model 4): ΔCFI = −.010, ΔRMSEA = .004, and ΔSRMR = .012.

The main objective of this study was to examine the factorial validity and invariance of the Italian version of the ERI-SQ among Italian university students. Overall, our results confirmed the factorial structure underlying the ERI-SQ, as theorized by Siegrist [ 25 ] and reported by Wege and colleagues [ 25 ] in the student version of the ERI. However, in light of the conclusions drawn from the EFA, to enhance the fit of the model, we had to delete two items with high cross loadings. The deleted items were problematic in the Wege and colleagues [ 25 ] study too. Specifically, both items (EFF2 and REW4) showed a low factor loading in the CFA.

In the Italian sample, using a modified and shortened version (12 items) of the ERI-SQ, we confirmed the three factors structure components of the model, showing a satisfactory fit of the data structure with the theoretical concept. In sum, the current findings show that the ERI-SQ is as a reliable instrument for measuring academic stress among students.

Finally, as expected, we found support for metric invariance across gender and university course, health (medicine, nursing, etc.) vs other courses (engineering, economy, etc.). Mainly, MCFAs confirmed that the three-factor structure of the ERI-QS is (mostly) invariant across different groups. More specifically, we found support for parameter equivalence across gender (structural invariance), but the ERI-SQ was significantly different in health vs other courses. In fact, we were not able to find scalar invariance, suggesting that items REW2, REW3, REW6 and all the over-commitment items vary by academic courses. However, the lack of scalar invariance is a negligible issue for the Italian version of the ERI-SQ.

Implications and limitations

Results from our study showed that the Italian version of the ERI-SQ-10 provides a psychometrically sound measure of stress as defined in the ERI theoretical framework. The ERI-SQ is a brief and easy to administer university student stress measure. In this sense, using valid and reliable measures of stress is crucial for Italian university counselling services to advance in monitoring and understanding the levels of stress affecting students and how to support them. In this manner it would be possible to offer appropriate mental health support [ 43 ] when students are exposed to lack of reciprocity between spending high efforts and receiving low rewards during their student career.

The present study has several limitations. First, data were obtained from a convenience sample offering reduced generalizability of our results. However, for the purpose of the study this sample was deemed appropriate. Second, the Effort dimension was composed of only two items. A factor with only two items leads to a CFA that cannot be estimated unless constraining the model. Future research would overcome this limitation by reevaluating a wider version of the ERI and adapting other items from the Effort factor as defined in the ERI questionnaire [ 24 ]. Third, further research is also recommended concerning construct and criterion validity [ 44 ]. Specifically, we are not able to provide evidence of convergent validity (how closely the ERI-SQ is related to other variables and other measures of the same construct), and discriminant (ERI-SQ does not correlate with other variables that are theoretically not related). Future research would consider to analyse it by employing a multitrait-multimethod [ 45 ]. Finally, as one of the anonymous reviewers correctly pointed out, our study does not offer any evidence of criterion validity, mainly concurrent validity (the degree to which a measure correlates concurrently to an external criterion in the same domain [ 44 ]. However, according to Wege and colleagues [ 25 ], no studies have provided estimates of these validities for the ERI-SQ. Future research would provide evidence of it by analyzing the correlation between the ERI-SQ and a theoretically similar measure of student stress. In this sense, concurrent validity is an important area of future research. Fourth, we did not test for test–retest reliability. Future research should address these issues. Despite these important limitations, the Italian version of the ERI-SQ showed satisfactory psychometric properties.

In the present study, we found that the Italian version of the ERI-QS partially confirms the original version from Wege and colleagues [ 25 ]. We were able to show satisfactory psychometric properties of the ERI-SQ. Considering a high prevalence of academic distress among University students and the limited interventions aimed to reduce stress [ 46 ], universities should employ preventive interventions by measuring and controlling for potentially harmful psychosocial risk. In this sense, the Italian version of the ERI-QS presents a valid instrument for measuring academic stress on Italian-speaking university students.

Availability of data and materials

Raw data pertaining to analyses performed in this study are available available from the authors upon reasonable request.

Abbreviations

Confirmatory Factor Analysis

Comparative Fit Index

Exploratory Factor Analysis

Effort-Reward Imbalance

Effort-Reward Imbalance Students Questionnaire

Multi-Group Confirmatory Factor Analysis

Maximum Likelihood

Robust Maximum Likelihood

Over-commitment

Principal Axis Factor

Root Mean Square Error of Approximation

Standard Deviation

Standardized Root Mean Square Residual

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Acknowledgements

The authors gratefully acknowledge Prof. Johannes Siegrist and Prof. Nico Dragano for their careful reading and constructive feedbacks on the final draft of the manuscript.

This study was not funded.

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Contributions

IP, MG, FB and MC contributed to the conception and design of the study. IP, FB and AB contributed to the development procedure of the Italian version of ERI-SQ, including forward translation and back translation review. IP and FP contributed to the acquisition of data. IP analyzed the data and wrote the first draft of the manuscript. MG, and AB supervised the analysis. SS, ED, GF and MC helped to draft and revise the manuscript. All authors read and approved the final manuscript.

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Correspondence to Maura Galletta .

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We conducted this study in accordance with (a) ethic committee of the University of Cagliari, (b) the Declaration of Helsinki in 1995 (as revised in Edinburgh 2000), and (c) with Italian privacy law (Decree No. 196/2003). Participation to the study was totally voluntary and written online informed consent was obtained by clicking on “I accept”.

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Portoghese, I., Galletta, M., Porru, F. et al. Stress among university students: factorial structure and measurement invariance of the Italian version of the Effort-Reward Imbalance student questionnaire. BMC Psychol 7 , 68 (2019). https://doi.org/10.1186/s40359-019-0343-7

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Published : 26 October 2019

DOI : https://doi.org/10.1186/s40359-019-0343-7

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Students, who are trying to complete academic activities in an educational environment, are objected to academic stress. Research results indicated that this stress can be reduced by the individual and psychosocial resources of them. So, this study aimed to determine the mediating role of grit and academic self-efficacy in the relationship between students’ psychological need satisfaction and academic stress. The research was conducted on 967 college students who are studying at education, theology, and medical education faculty. We used serial mediation analysis to determine the mediator effect. Results demonstrated that there are statistically significant positive relationships between autonomy, competence, and relatedness, which are the components of psychological need satisfaction, grit, and academic self-efficacy, and negative relationships between academic stress. Mediation analysis results showed that the serial mediator effect of grit and academic self-efficacy was statistically significant in the relationship between autonomy, competence, relatedness, and academic stress. The research findings were interpreted according to the self-determination theory and positive psychology literature.

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Introduction

• Psychological need satisfaction

As claimed by the self-determination theory, psychological need satisfaction is considered a concept that focuses attention on three basic needs, autonomy, competence, and relatedness, which are necessary for human development and contribute to psychological functionality and growth when it is satisfied (Deci & Ryan, 2002 ). The first component of the psychological need satisfaction, autonomy, includes individuals deciding on their freedom when taking action, knowing that the power is theirs, and the freedom and responsibility of being able to choose without being influenced by others. Another constituent, competence, reflects how an individual perceives their potential when taking any action; in other words, it reflects the state of individuals perceiving themselves as self-sufficient. The third component, relatedness, is viewed as a dimension that deals with the positive social relations that the individual has established with others. The importance of fulfillment of these three main psychological needs is pointed in individuals having an active life, becoming their higher self and ability to deal with the obstacles coming their way, and stress-making stimulants (Deci & Ryan, 2002 ; Ryan & Deci, 2000 ).

Studies also prove that psychological need satisfaction has an aspect impacting students’ academic achievements in a positive way (Gutiérrez et al., 2018 ; Zhou et al., 2021 ), and increases their academic motivation (Gnambs & Hanfstingl, 2016 ), self-efficacy (Sun et al., 2020 ; Wang & Tsai, 2020 ), school performance, and school attachment (Liu & Flick, 2019 ). In this context, Gutiérrez et al. ( 2018 ) point out that perceived autonomy support is a factor that increases students’ success through academic self-efficacy and school participation. Another study demonstrates an intermediary effect of psychological need satisfaction between stress and well-being (Aldrup et al., 2017 ). It has also been revealed that psychological need satisfaction helps students go through less stress (Zhou et al., 2020 ), anxiety (Maralani et al., 2016 ), and depression (Emery et al., 2015 ). Zhou et al. ( 2021 ) emphasized that basic psychological need satisfaction increases positiveness and academic success in adolescents. In this sense, it can be stated that psychological need satisfaction affects a person’s academic and social life. Therefore, in this study, psychological need satisfaction was considered an independent variable and thought that the students’ academic stress would decrease as psychological need satisfaction increased.

Psychological need satisfaction and academic stress

Academic stress is regarded as a rubric that expresses unpleasant psychological situations caused by the repression of education and examination systems and the high academic expectations for students of teachers and families (Sarita, 2015 ). Academic stress negatively affects physical and psychological health and is considered a factor in lowering students’ academic achievements (Sedere, 2010 ). Research findings show that students may be exposed to academic stress during activities that require high academic performance (Yu et al., 2016 ). Academic stress may occur more in departments with heavier course content and evaluation systems. In the given context, in an inquisition examining the differentiation of academic stress according to departments, and in a cross-sectional study examining the perceived academic stress level among medical, dentistry, psychology, and sports students, it is demonstrated that sports and psychology students have lower perceived stress risk compared to medical students (Neveu et al., 2012 ). Furthermore, students’ stress levels may be less at the beginning of their university years and higher in their senior year. The growing expectations for education, homework, and examinations can cause stress for college students. Considering that the students in the final year have a higher workload and the number of theoretical and applied courses to be accomplished, they are more likely to be exposed to stress in their senior year. Research findings show that educational stress may increase in the later years of the education process and towards the last years. In this context, as a result of a study on medical students, it was seen that educational stress is lower in the first grade and higher in recent years (Neufeld et al., 2020). So, using psychological resources to meet the increasing educational demands in senior years may be effective in reducing their stress levels. On the contrary, it is possible for students to be exposed to stress during their first year of university. Trying to get used to a new environment, getting used to living away from their family, and being able to be accepted in the social environment can bring about intense stress in individuals. Therefore, it is thought that it is crucial to examine the determination of academic stress, which has the potential to negatively affect the academic success of college students and the factors that will reduce the stress. In the meantime, as the academic stress increases, depression and level of anxiety also increase (Kuo et al., 2018 ) and the students undergo much more disconfirming emotions. In this context, Polat and Özdemir ( 2018 ) state that academic stress and school burnout are significant predictors of students’ alienation from school (Gibbons, 2012 ). Accordingly, it is accepted that determining the causes of academic stress in students and revealing the variables that will reduce academic stress are also essential for increasing academic success and connecting students to school. In research regarding factors that reduce academic stress, studies concerning components of psychological need satisfaction are remarkable.

A low level of satisfaction in autonomy, competence, and relatedness components of psychological needs both hampers human growth and causes negative emotions such as depression (Emery et al., 2015 ), burnout (Cho & Jeon, 2019), and stress (Naylor, 2020). By satisfying these three psychological needs, individuals’ level of achievement and coping with stress may boost, and accordingly, they may experience less stress. Academic stress typically occurs when educational requirements exceed an individual’s coping resources (Wilks, 2008). The satisfaction of three needs may help students to overcome these demands as an adaptive resource. Self-determination theory claims that satisfaction of three needs is associated with lower stress incursion (Ryan & Deci, 2000 ). Similarly, Weinstein and Hodgins (2008) claim that the basic psychological need satisfaction could act as a defensive response that assists in regulating and maintaining positive outcomes following stress exposure. A study conducted by Neufeld et al. (2020) showed a negative association between basic psychological need satisfaction and perceived stress, thus indicating a stress-protective role of basic psychological need satisfaction in medical students. Another case demonstrates that psychological need satisfaction mediates the relationship between exposure to stress and well-being (Aldrup et al., 2017 ). Travis and Bunde ( 2020 ) also found a significant negative relation between psychological need satisfaction and stress. Zhou et al. ( 2020 ) have shown that the relationship between autonomy, competence, relatedness need satisfaction, and stress is negatively paced. In this connection, in a study regarding the relationship between autonomy support and academic stress, the conclusion was that self-arranged learning and goal-oriented mediate this relationship (Zheng et al., 2020 ). Research findings suggest that psychological need satisfaction components are considered a factor in reducing students’ academic stress and increasing their achievements.

Psychological need satisfaction is a highly compatible and complementary motive that helps students to accomplish their developmental tasks. Given that college students are in the emerging adulthood period which has many social and psychological aspects that need to be accomplished, the satisfaction of autonomy, competence, and relatedness needs boosts adjustment and well-being. University students have different academic, social, and psychological development tasks and periods every year. The freshmens and the juniors have to adjust a new social environment, to make new friendships, and to succeed academic tasks. At this developmental process, the satisfaction of autonomy, competence, and relatedness and high level of satisfaction means for students have a high level of well-being and successful academic and social life. Neufeld et al. (2020) indicated that students’ autonomy and competence satisfaction and dissatisfaction were higher in senior years. So, in the current study, we choose a socio-demographically diverse sample including a different class, department, and faculty.

The mediating role of grit and academic self-efficacy

Grit is an individual’s determination and effort to achieve their long-term goals and be successful against the handicaps they face (Duckworth et al., 2007 ). It is stated that students with higher grit levels use more functional coping mechanisms for the obstacles they are facing and are more academically successful (Ivcevic & Brackett, 2014 ). According to the study results, we can say that grit has the potential to increase students’ academic success, and it has a protective and preventive effect in dealing with problems.

Gritty students go on relentlessly regardless of the handicaps they face (Duckworth et al., 2007 ). A study regarding this context highlights that psychological need satisfaction is a variable improving students’ grit levels (Jin & Kim, 2017 ). At the same time, it was stated that the predictive effects of fundamental psychological needs and grit were crucial in predicting well-being in adolescents (Akbag & Ümmet, 2017 ). As grit is the determination level of an individual in achieving goals, one can say a person with satisfying psychological needs can show more grit. With the increase in psychological need satisfaction, students feel more autonomous and competent and are more successful in their social relations. It can also help students to become more determined. Since individuals with a high level of psychological need satisfaction can act autonomously, they can be successful in determining their future goals themselves and become more willing to reach these goals in the future. At the same time, another component, competence, reveals the individual’s belief in their own capacity, so the individual who sees themselves as self-sufficient can also see themselves as sufficient to achieve their future goals. This, in turn, can increase the level of grit characterized by decisive action to achieve their goals. Thus, if the level of students’ basic psychological need satisfaction increases, their level of grit may also increases as well. Thus, the study by Yoon et al. ( 2020 ) defined that students with high autonomy support also have high grit levels. Pupils with exalted psychological need satisfaction can both see their competence higher and act more autonomously, which can help individuals show determination for achieving their goals. Also, if the students consider themselves sufficient to accomplish their dreams, their grit level can go up.

Numerous researches indicated that gritty students experience less depression (Datu et al., 2019 ), higher well-being (Jiang et al., 2020 ; Jin & Kim, 2017 ), more positive emotions, fewer negative emotions (Singh & Jha, 2008 ), and higher academic success (Ivcevic & Brackett, 2014 ). Furthermore, the more grit the students have, the less stress they experience. Students who work tirelessly on the path they set and in line with the goals they set can organize the learning process and have a high level of motivation. This may cause students to experience less stress in the learning process. In the same context, in a study by Lee ( 2017 ), it was stated that the students go through less stress with a rising grit level than before. Another research shows that grit is a preventive factor for dealing with stress (Mosanya, 2019 ). Therefore, increasing grit can be evaluated as a stress-reducing factor.

Grit includes the individual’s determination to reach their goals, working tirelessly and striving resolutely to reach their goals (Duckworth et al., 2007 ). Therefore, the level of grit can be expected to be higher at the stage where the individual strives to achieve their future goals. The high level of determination of the individual, especially in the last class, in order to be successful in the vocational transition exams based on placement with a central score may be effective in making them successful. Therefore, the high level of grit of the students in the last year can be an effective source both in their success and in reducing their stress. At the same time, the high level of determination at the beginning of the university years is important for students to achieve a certain high grade point average. Students must have a certain level of grades in order to be able to take courses from the next year and not to repeat the semester. Therefore, being determined in the first and following years may have a function that increases success and helps transition to a higher class.

Another factor that helps students increase their academic success and experience less stress is academic self-efficacy. Academic self-efficacy consists of students perceiving their competencies equally with the skill level required by the activity while trying to achieve academic activities (Bong & Skaalvik, 2003 ). In other words, students with a high level of academic self-efficacy also have higher expectations about academic activities in school (Putwain et al., 2013 ). As academic self-efficacy expands, students’ commitment to school (Stubbs & Maynard, 2017 ), academic success (Putwain et al., 2013 ), and psychological well-being (Asghari et al., 2014 ) also increase, and stress levels decrease (Travis & Bunde, 2020 ; Zajacova et al., 2005 ). Hence, students who feel competent academically undergo less stress and become more successful. At the same time, the importance of satisfying psychological needs in the formation of students’ academic self-efficacy was highlighted (Travis & Bunde, 2020 ). Individuals become more competent, particularly with the satisfaction of autonomy competence needs, which are included in psychological need satisfaction. They perceive their competence at a level to perform the activity (Buch et al., 2015 ; Oriol-Granado et al., 2017 ). In other words, as psychological need satisfaction increases, academic self-efficacy also increases. Therefore, it can be said that academic self-efficacy has an aspect that reduces academic stress and an element that is affected by psychological need satisfaction. Thus, in this research, regarding whether grit and academic self-efficacy will play a mediating role in reducing students’ academic stress, these two variables were included in the research as mediator variables.

Academic self-efficacy may differ from student department and class levels. There were research results that indicate students’ academic self-efficacy beliefs vary in numerous sociodemographic variables. Turgut (2013) found a significant differentiation between grade level and academic self-efficacy which freshman, sophomore, and junior students’ academic self-efficacy is the highest level when their GPA is the maximum level. Satici and Can (2016) found that academic self-efficacy significantly differs according to grade level and the senior students’ academic self-efficacy was higher than freshmen, juniors, and sophomores respectively. This study also reveals that students’ academic self-efficacy differed from their fields of study which are tech & sci, social, health, and art respectively. The first year of university education students has to deal with many educational and social stimuli. The following years mean for students both educational and job-related exams, so senior students need to be more self-efficient with the help of growing academic knowledge and required intern education. So, academic self-efficacy may be different for each year of university students.

Purpose of the research and hypotheses

Turkish undergraduate university students are faced with many stress-related stimuli while trying to achieve academic activities. The students challenge many theoretical and practical courses in teaching activities, and after completing their undergraduate education, they try to get ready for central exams such as Public Personnel Selection Exam (PPSS) or Medical Specialization Exam (MSE) to meet the conditions for entry into the profession. They can experience academic stress both during their undergraduate studies and at the stage of preparation for the central exams after completing their undergraduate studies. For many students, university education means getting used to living in another city, developing positive and harmonious social relations with their surroundings, participating in theoretical and practical training, developing projects, and succeeding in academic and social activities such as preparing for exams. Positive resources of the individual in the realization of these activities can have a protective and preventive function in reducing stress levels. In this context, it can be said that individuals who become more autonomous, competent, and satisfied in their relationships by meeting their basic psychological needs will successfully organize their learning process. At the same time, based on the research findings that the satisfaction of psychological needs reduces stress (Neufeld et al., 2020), one can say students will be more successful in reducing their academic stress by satisfying these basic needs. At the same time, university students’ autonomous learning, self-efficacy, grit, and academic self-efficacy levels may also be positively affected by satisfying these three needs. While trying to achieve academic activities, it is important for the students who have passed the theoretical and practical training, who try to pass many staged exams, to see themselves as competent and to reach their goals with determination, in terms of experiencing less stress.

Knowing the coping methods of university students against stress is the first step in developing involvement methods in this context. There is increasing proof of psychological conditions such as depression and stress that university students experience in their educational life, which cause many negative outcomes such as school dropout, burnout, and academic failure (Hunt & Eisenberg, 2010 ; Jiang et al., 2021 ; Thomas & Shanafelt, 2006 ). Turkish university education is a long and challenging process. Reasons like curriculum density, information overload, academic competition, exams, and high-performance expectations cause stress in college students (Dvořáková et al., 2018). Diagnosing stress in college students and learning about the mediating roles are as crucial as developing health-promoting and stress-preventing interventions. The research was conducted on college students who are thought to undergo more intense stress.

In this context, when the studies on psychological need satisfaction and related literature are evaluated together, it is observed that psychological need satisfaction, consisting of autonomy, competence, and relatedness, may increase an individual’s success and academic self-efficacy may decrease academic stress in school, considering that psychological need satisfaction is a component that boosts an individual’s success, lowers their stress, makes them feel competent in achieving success in academic activities, and promotes their learning motivation. With the role of psychological need satisfaction, students’ probability of experiencing success, well-being, and positive emotions escalates, and they go through less stress in the academic field. In this respect, one can say when students’ psychological need satisfaction increases, their academic success also increases, and they will make significant contributions to reducing the stress that can be experienced in the academic environment. At the same time, it has been thought that grit and academic self-efficacy positively affect students’ academic achievement and reduce academic stress. There were numerous research results that highlighted the importance of self-determination theory on academic stress but little has been indicated in a sample of faculty of educational, theology, and medical students together. Therefore, this study aims to determine the mediating role of grit and academic self-efficacy in the relationship between psychological need satisfaction and academic stress in preclinical medical students, educational students, and theology students.

Basic psychological need satisfaction is linked with self-efficacy, and might also affect the evaluation of stress-related appraisals (Travis & Bunde, 2022). Including academic self-efficacy and grit variables might boost academic achievement by hindering stress-related appraisals. There were numerous research results that highlighted the importance of self-determination theory on academic stress but, to our knowledge, little has been indicated in the context of educational, theology, and medical students’ samples together. Since preclinical medical students come across highly intensive academic schedules before clinical practices, overloading academic activities may cause stress-related experiences (Neufeld & Malin, 2019 ). Similarly, education and theology students have been through both academically intense programs and job-related entrance exams. This academic process means for undergraduate students have heavy expectations, a long time to study, and endless exams. Given the academic expectations and program components with the help of satisfaction of autonomy, competence and relatedness may decrease undergraduate students’ academic stress with academic self-efficacy and grit.

The current study contributes to the literature in two ways: First, we report the mediator effect of grit and academic self-efficacy in the relationships between basic psychological need satisfaction and academic stress in a demographically diverse sample of Turkish undergraduates, drawn from a variety of departments, socioeconomic statues, and student classifications. Second, the indirect impact of basic psychological need satisfaction components on academic stress is modeled separately with autonomy, competence, and relatedness components, and a well-established self-regulatory construct such as academic self-efficacy and grit, as distinct constructs, has been relatively understudied in the academic context. A better understanding of the direct and indirect effect of basic psychological need satisfaction on academic stress with cognitive mediators could help undergraduate students and instructors to realize the importance of reducing stress with autonomy, competence, and relatedness components as well as grit and academic self-efficacy. This current study also helps the practitioners who may also design a psychoeducation program to hinder stress with basic psychological need satisfaction components with cognitive constructs such as grit and self-efficacy.

Since psychological need satisfaction has three sub-dimensions, autonomy, competence, and relatedness, and a total score could not be obtained from the scale, a separate model was created for each sub-dimension. For this purpose, the research questions are as follows and the proposed hypothesized model is in Fig.  1 :

How strong is the mediator role of grit and academic self-efficacy in the relationship between autonomy and academic stress?

How strong is the mediator role of grit and academic self-efficacy in the relationship between competence and academic stress?

How strong is the mediator role of grit and academic self-efficacy in the relationship between relatedness and academic stress?

Hypothesized model

Research design

This research was designed in the scope of relational studies. Through serial mediations, it examines the relationships between psychological need satisfaction, grit, academic self-efficacy, and academic stress variables in college students. In relational studies, the direction of the relations between the variables and the relation level is considered. These studies are also carried out to explain human behaviors and predict the possible consequences of these behaviors (McMillan & Schumacher, 2010 ).

Ethical permission

The ethical permission for the study was taken from the Ataturk University Faculty of Medicine Non-Interventional Research Ethics Committee (Date: 30.12.2021, Issue: 09/24). The study was conducted according to the Principles of the Declaration of Helsinki.

Participants

The study was conducted on 995 undergraduate students of the Faculty of Medicine, Faculty of Education, and Faculty of Theology. In sample choosing, a convenient sampling method was used. In the convenient sampling method, the researcher opts for accessible and appropriate individuals for the study (McMillan & Schumacher, 2010 ). But, it restricts the generalization of the study results and representation of sample. To eliminate these biases, we tried to reach different gender, age, city, faculty, university, success, and grade level of students. Participants’ characteristics are given in Table 1 .

Table 1 demonstrates that 526 (54%) of the study group students are female, and 441 (46%) of them are male students. Four hundred four (41.8%) of the students are freshmen, 380 (39.9%) are sophomores, 54 (5.6%) are juniors, and 129 (13.3%) are seniors. The mean average age of the study group was 20.69, and the standard deviation was 2.39. The rates of participations were 73% for the Faculty of Medicine preclinical students (769/1055), 67% for the Faculty of Education (175/262), and 85% for the Faculty of Theology (23/27). Participants were studying at university 1st, 2nd, and 3rd class in 2021–2022 autumn semester for medical students and 1st, 2nd, 3rd, and 4th class in 2021–2022 summer semester for education and theology faculty. The education faculty and the theology faculty students were taking lessons from the researchers’ summer semester class.

A short sociodemographic information form, balance in psychological need satisfaction scale, academic stress scale, brief grit scale, and perceived academic self-efficacy scale were used as data collection tools. In the sociodemographic information form, the students were asked about age, gender, and class information.

Balance in psychological need satisfaction scale

This is a scale of 18 items improved by Sheldon and Hilpert ( 2012 ) adapted to the Turkish version by Kardaş and Yalçın ( 2018 ) and aims to measure individuals’ satisfaction and frustration level psychological needs according to the 5-point Likert system. The analysis results for the scale’s validity demonstrated that both three-dimensional and six-dimensional factor structures were verified in the Turkish sample (three-factor form accordance indices =  χ 2 /sd = 2.92, RMSEA = 0.08, RMR = 0.05, GFI = 0.87, CFI = 0.92, NFI = 0.89, NNFI = 0.91; six-factor form accordance indices =  χ 2 /sd = 1.43, RMSEA = 0.04, RMR = 0.04, GFI = 0.94, CFI = 0.98, NFI = 0.94, NNFI = 0.98).

Since the total score could not be received from the scale, the scale’s reliability was examined according to the sub-dimensions. The research sample determined that the Cronbach alpha reliability coefficient was 0.74 for the autonomy sub-dimension, 0.78 for the competence sub-dimension, and 0.61 for the relatedness sub-dimension. McDonald omega’s credibility was found to be 0.74 for the autonomy sub-dimension, 0.80 for the competence sub-dimension, and 0.63 for the relatedness sub-dimension. It can be stated that the credibility rate of the relatedness sub-dimension of the scale is a little lower than the acceptable limit.

Educational stress scale

It is a 16-item scale improved by Sun et al. ( 2011 ) and adapted to the Turkish version by Celik et al. ( 2014 ) The scale has a five-agent structure: work pressure, workload, grade anxiety, self-expectation, and hopelessness. Scale items are answered and scored according to a 5-point Likert system (1—strongly disagree, 5—strongly agree). The score that can be acquired from the scale is between 16 and 80. Also, points of sub-dimensions can be evaluated, too. Cronbach alpha internal consistency reliability parameter was found to be 0.81 for the whole scale. Celik et al. ( 2014 ) made an adaptation to the Turkish version, and its psychometric features were illustrated. Cronbach alpha rate of the Turkish version of the scale was found to be 0.83 for the whole scale. Results about the scale’s validity showed that it has acceptable accordance indices for the five-agent structure.

Brief grit scale

It is a self-evaluation scale developed by Duckworth and Quinn ( 2009 ) and adapted to Turkish by Sarıçam et al. ( 2016 ) The scale, consisting of 8 items, has a structure of two dimensions, which are (1) consistence of interest and (2) insistence on effort. The themes of the scale are answered (1—Not meant for me, 2—A very little meant for me, 3—A little meant for me, 4—Quite meant for me, 5—Meant for me) and graded according to the 5-point Likert scale.

The Cronbach alpha internal consistency reliability coefficients for the whole scale were found to be 0.82. The Cronbach alpha value of the Turkish scale version was 0.83 for the whole scale. It has been informed that the scale is an acceptable and reliable measuring tool that can evaluate individuals’ grit, determination, persistence, and insistence levels. The confirmatory factor analysis results of the scale revealed that the form accordance indices showed a perfect fit ( χ 2 /sd = 2.06, p = 0.000, RMSEA = 0.046, CFI = 0.95, GFI = 0.94, AGFI = 0.93, SRMR = 0.047).

Perceived academic self-efficacy scale

The perceived academic self-efficacy scale, improved by Jerusalem and Schwarzer ( 1981 ) and adapted to Turkish by Yılmaz et al. ( 2007 ), is a 7-agent scale that evaluates students’ beliefs about finishing an academic work successfully. The Cronbach alpha reliability value of the scale was 0.87 in the original study and 0.79 in the Turkish version. As in the original scale, there are seven items in a single dimension in the Turkish version. Scale items are answered on a 4-point Likert system (fully suited to me, suited to me, very little suited to me, not at all).

Process of data collection

The research was conducted between 10/01/2022–25/01/2022 and 25/07/2022–05/08/2022. Since the pandemic and online education process were still the cases on these dates, the questionnaire form was prepared on Google Forms. After the students were informed about the purpose and scope of the research, they were invited. The questionnaire link was shared on WhatsApp student groups. Volunteerism was the basis for participation in the study. The students were given 2 weeks to complete the questionnaire. Two reminder messages were sent during this period. At the end of the period, the questionnaire was closed for answers.

In online data collection, it is recommended to use attention checks to reduce the bias of participants’ responses to scale items. Similarly, increasing the representativeness of the sample and adding explanatory instructions are among the suggestions (Newman et. al., 2021 ). In the current study, the power of representing the universe was tried to be increased by trying to reach a diverse sample group such as different classes, faculties, universities, regions, and socioeconomic levels. In the first section of the data collection tool, with informed consent, detailed instructions were presented and information was added about the purpose of the research, possible risks, no need for any identity information, and withdrawal options. Then, an attention check has been added for them to read and accept the information. The first question of the questionnaire was “I voluntarily agree to participate in the study.” and it was planned in a way that the participants could continue only when they gave this consent. Thus, the students’ permission was taken online. Those who did not give this first permission could not reach the other questions. The data was collected anonymously. There were not any personal info questions. Each process took 2 weeks to collect the data.

Common method bias

During the data collection phase, the students filled the scales according to self-report. However, during this phase, students may mark incorrectly when filling out the scales due to conditions such as fatigue, distraction, getting approval, or misreading the scale items (Podsakoff et al., 2003 ). This situation is considered a common method bias and negatively affects the validity of the research. To reduce the common method bias in this study, the researchers used Harman’s single factor test. Harman’s single factor test includes collecting all the variables in the research under a single factor and explaining the variables below 50% of the total variance (Harman, 1976 ). In this study, since it was determined that the variables were gathered under a single factor and the explained variance was 21%, it indicated that there was no common method bias problem.

Normality analysis

Before proceeding to the mediation analysis, we examined the suitability of the data to the univariate and multivariate normal distribution. Firstly, we calculated the skewness and kurtosis values. It has been noted that the skewness and kurtosis value is between [− 1.5, + 1.5] which is a criterion related to distribution normality (Tabachnick et al., 2007 ). Given that the values of the skewness and kurtosis levels are in the range between − 0.01 and 0.17, it was concluded that the data has univariate normality. In addition, normality of regression errors was the calculated skewness and kurtosis values − 0.01–0.17 respectively. Secondly, in determining the multivariate normality, 28 data that violated the multivariate normality were excluded from the data set. Mardia’s coefficient was calculated below 20, p  < 0.01, for multivariate normality. It is suggested for Mardia’s multivariate kurtosis values of critical ratio that a lower than 10 is an acceptable degree for multivariate normality (Kline, 2015 ). It is considered an acceptable level for multivariate normality with a lower than 20 (Gurbuz, 2016). For the five predictor variables, the Mahalanobis coefficient did not have an outlier value exceeding the p  < 0.01 significance level. After evaluating the multivariate normality of the data set by examining Mahalanobis, tolerance, and variance inflation factor (VIF) values, it was concluded that the data set also has multivariate normality, and an analysis of the data was started to carry out. In determining the relationships between the variables in the data analysis, Pearson product-moment correlation analysis, serial mediation analysis (Hayes, 2017 ), and bootstrap confidence interval methods were used. The analysis process was carried out through SPSS 24, Amos Graphics 22, and SPSS Process 3.5 macros.

The high level of correlation between the variables points to the multicollinearity problem (Kline, 2011). In this context, since the correlations between the variables were observed to be between − 0.31 and 0.61, it was determined that the variables were not highly correlated to form a multicollinearity. Furthermore, the tolerance value should not be less than 10, and the VIF (variance inflation factor) value should not be greater than 10 (Kline, 2011). Tolerance ranges from 0 to 1 and is associated with each independent variable. Although there is not a strict cutoff for tolerance value, Allison ( 1999 ) suggests a tolerance of below 0.40 is cause for concern. Similarly, Weisburd and Britt ( 2013 ) state that anything under 0.20 suggests serious multicollinearity in a model. As it was determined that the tolerance values were between 0.48 and 0.72 and the VIF values were between 1.39 and 2.10, it was concluded that there was no multicollinearity problem.

Validity and reliability of the scales

Confirmatory factor analysis and reliability analyses were conducted to determine that the scales used in the study produced valid and reliable results in the research sample, and the results are given in Table 2 .

When Table 2 is examined, it is seen that the validity and reliability results of the scales used in the study also have valid and reliable results in the research sample of the rankings. Accordingly, when the validity results of the scales are evaluated, it is noticed that their form accordance indices are within acceptable value ranges. According to the reliability results of the rankings, as it was determined that the reliability coefficients of Cronbach alpha and McDonald omega ranged between 0.77 and 0.86, it can be stated that in this research, sample scales produce an adequate amount of valid and reliable results.

Preliminary analysis

Correlation analysis results are given in Table 3 .

When Table 3 is examined, it is seen that there was a negative statistically significant relationship between autonomy ( r  =  − 0.48), competence ( r  =  − 0.41), and relatedness ( r  =  − 0.31), which are the components of psychological need satisfaction and academic stress. There was a positive, statistically significant intermediate relationship among autonomy ( r  = 0.50), competence ( r  = 0.61), relatedness ( r  = 0.40), and grit, and there was a positive, intermediate relationship between autonomy ( r  = 0.38), competence ( r  = 0.55), relatedness ( r  = 0.25), and academic self-efficacy. These findings showed that when autonomy, competence, and relatedness, which are components of psychological need satisfaction, increased, grit and academic self-efficacy also increased, but academic stress decreased, and this relationship was moderate.

Measurement model

Before proceedings of the mediation analysis, we examined the measurement model that has acceptable fit indexes ( χ 2  = 906.87, df  = 109, p  = 0.000, RMSEA = 0.08, CFI = 0.88, GFI = 0.90, SRMR = 0.07). Figure  2 demonstrates the value of observed variables and estimated factor loadings of measurement model. Basic psychological need satisfaction has three components of autonomy, competence, and relatedness; academic stress has five sub-dimensions; grit has two sub-dimensions; and academic self-efficacy consists of seven items. All estimated factor loadings are statistically significant at a level of 0.01.

Mediation analysis results

To test the study’s hypothesis, mediation analysis was made according to Hayes’s ( 2017 ) recommendation of model 6. The hypothesis model was tested with three different comments because the study’s independent variable, psychological need satisfaction, has a three-dimensional structure that needs to be dealt with separately and consists of autonomy, competence, and relatedness. The study’s mediation analysis results are given in Table 4 for the autonomy model, Table 5 for the competence model, and Table 6 for relatedness model.

Autonomy model

As seen in Table 4 , the direct effect of the first component of psychological need satisfaction, autonomy, on academic stress was significant ( B  =  − 0.97, SE = 0.08). The direct effect of autonomy on mediator variable, grit ( B  = 0.60 SE = 0.03) and academic self-efficacy ( B  = 0.21, SE = 0.04), was also proved to be significant. It has been determined that the direct effect of one of the mediator variables, grit on the dependent variable on academic stress ( B  =  − 0.29, SE = 0.07), and the direct effect of the other mediator variable, self-efficacy on the dependent variable academic stress, are also significant ( B  =  − 0.24, SE = 0.07).

Regression analysis based on the bootstrap method was performed to determine if the mediating role of grit and academic self-efficacy in the relationship between autonomy and academic stress is significant. According to the confidence intervals obtained by the bootstrap method, the mediating role of grit and academic self-efficacy between autonomy and academic stress is statistically significant ( B  =  − 0.05, SE = 0.02, 95% CI [− 0.09, − 0.02]). As the bootstrap lower and upper confidence intervals did not include 0, it was seen that the mediation effect was significant.

Figure  3 also indicates a partial mediator role of grit and academic self-efficacy in the relationship between autonomy and academic stress ( B  =  − 0.05, SE = 0.02, 95% CI [− 0.09, − 0.02]). Since the level of the relationship between autonomy and academic stress decreased with the addition of grit and academic self-efficacy to the model, there is a partial mediation of grit and academic self-efficacy in the relationship between autonomy and academic stress.

The mediation analysis result of autonomy model

Competence model

As seen in Table 5 , the direct effect of competence, the second component of psychological need satisfaction, which is the independent variable of the model, on academic stress was significant ( B  =  − 0.70, SE = 0.11). Also, it was determined that the direct effect of competence on mediator variable grit ( B  = 0.76, SE = 0.03) and academic self-efficacy ( B  = 0.49, SE = 0.04) was also significant. It was also noted that both the direct effect of a mediator variable, grit on a dependent variable, academic stress ( B  =  − 0.38, SE = 0.08), and the direct effect ( B  =  − 0.19, SE = 0.08) of a mediator variable, academic self-efficacy on a dependent variable, academic stress, were significant.

Regression analysis based on the bootstrap method was conducted to determine if grit and academic self-efficacy have a significant mediating role in the relationship between competence and academic stress. According to the confidence intervals obtained by the bootstrap method, it was observed that the mediation effect of grit and academic self-efficacy, together with competence and academic stress, was statistically significant ( B  =  − 0.03, SE = 0.02, 95% CI [− 0.07, − 0.00]). Since the bootstrap lower and upper confidence intervals did not include zero, it was seen that the mediation effect was significant.

Figure  4 also indicates a partial mediator role of grit and academic self-efficacy in the relationship between competence and academic stress ( B  =  − 0.03, SE = 0.02, 95% CI [− 0.07, − 0.00]). Since the level of the relationship between competence and academic stress decreased with the addition of grit and academic self-efficacy to the model, there is a partial mediation of grit and academic self-efficacy in the relationship between competence and academic stress.

The mediation analysis result of competence model

Relatedness model

As seen in Table 6 , the third component of psychological need satisfaction, relatedness, an independent variable of the modal, had a significant direct effect on academic stress ( B  =  − 0.59, SE = 0.11). At the same time, it was determined that the direct effect of relatedness on the mediating variables of grit ( B  = 0.60, SE = 0.05) and academic self-efficacy ( B  = 0.10, SE = 0.04) was also significant. The direct effect of grit, one of the mediating variables, on academic stress, a dependent variable ( B  =  − 0.49, SE = 0.08), and the direct effect of academic self-efficacy, another mediator variable, on the dependent variable, academic stress ( B  =  − 0.36, SE = 0.08), were determined to be significant.

To determine if the mediating role of grit and academic self-efficacy in the relationship between relatedness and academic stress is significant, regression analysis, based on the bootstrap method, was conducted. According to the bootstrap confidence intervals, the mediating effect was significant in the relationship between grit, academic self-efficacy, and academic stress ( B  =  − 0.10, SE = 0.02, 95% CI [− 0.15, − 0.05]). As the bootstrap lower and upper confidence intervals did not include zero, the mediation effect was significant.

Figure  5 also indicates a partial mediator role of grit and academic self-efficacy in the relationship between competence and academic stress ( B  =  − 0.10, SE = 0.02, 95% CI [− 0.15, − 0.05]). Since the level of the relationship between relatedness and academic stress decreased with the addition of grit and academic self-efficacy to the model, there is a partial mediation of grit and academic self-efficacy in the relationship between relatedness and academic stress.

The mediation analysis result of relatedness model

Total, direct, and indirect effects

After determining the mediating effect of psychological need satisfaction on academic stress through grit and academic self-efficacy, the total, direct, and indirect effects of the variables on each other were examined. The results of the total, direct, and indirect effects are given in Table 7 .

When Table 7 is examined, it is seen that in the autonomy model, the total effect of autonomy on academic stress ( B  =  − 1.24, SE = 0.07, 95% CI [− 1.39, − 1.10]) and its direct effect ( B  =  − 0.97, SE = 0.08, 95% CI) [− 1.13, − 0.80]) were significant. The total indirect effect of autonomy on academic stress ( B  =  − 0.28, SE = 0.05, 95% CI [− 0.37, − 0.19]) was also seen to be significant. It is seen that the indirect effect of autonomy on academic stress through grit ( B  =  − 0.18, SE = 0.05, 95% CI [− 0.28, − 0.08]) and academic self-efficacy ( B  =  − 0.05, SE = 0.02, 95% CI [− 0.09, − 0.01]) was also significant. In addition, since the standardized total indirect effect value was determined as − 0.11, it is possible to say that grit and academic self-efficacy ( B  =  − 0.05, SE = 0.02, 95% CI [− 0.07, − 0.00]) have a medium mediating effect.

When Table 7 is continued to be examined, it is seen that the total effect of competence on academic stress ( B  =  − 1.11, SE = 0.08, 95% CI [− 1.26, − 0.95]) and its direct effect ( B  =  − 0.69, SE = 0.11, 95% CI [− 0.90, − 0.49]) are significant in the competence model. It is seen that the total indirect ( B  =  − 0.41, SE = 0.08, 95% CI [− 0.57, − 0.26]) effect of competence on academic stress is also significant. It is seen that the effect of competence on academic stress through grit ( B  =  − 0.28, SE = 0.07, 95% CI [− 0.43, − 0.15]) and academic self-efficacy ( B  =  − 0.09, SE = 0.04, 95% CI [− 0.18, − 0.01]) is also significant. At the same time, it is seen that the indirect effect of competence on academic stress through grit and academic self-efficacy ( B  =  − 0.03, SE = 0.02, 95% CI [− 0.07, − 0.00]) is significant. In addition, since the standardized total indirect effect value was determined as − 0.15, it is possible to say that grit and academic self-efficacy have a moderate mediating effect together.

When Table 7 is continued to be examined, it is seen that the total effect of relatedness ( B  =  − 1.01, SE = 0.10, 95% CI [− 1.21, − 0.82]) and the direct effect ( B  =  − 0.59, SE = 0.11, 95% CI [− 0.80, − 0.38]) on academic stress are significant in the relatedness model. It is seen that the total indirect effect ( B  =  − 0.42, SE = 0.06, 95% CI [− 0.54, − 0.32]) of relatedness on academic stress is also significant. It is seen that the indirect effect of relatedness on academic stress through grit ( B  =  − 0.29, SE = 0.06, 95% CI [− 0.41, − 0.19]) and academic self-efficacy ( B  =  − 0.04, SE = 0.02, 95% CI [− 0.08, − 0.00]) is also significant. At the same time, it is seen that the indirect effect of relatedness on academic stress through grit and academic self-efficacy together ( B  =  − 0.10, SE = 0.02, 95% CI [− 0.15, − 0.05]) is significant. In addition, since the standardized total indirect effect value was determined as − 0.13, it is possible to say that grit and academic self-efficacy together have a moderate mediating effect.

It is seen that the highest effect on the total and direct effects of the components of psychological need satisfaction on academic stress is autonomy, competence, and relatedness, respectively.

In the autonomy model, grit was found to be significant mediator variable together with academic self-efficacy. The indirect effect of grit is higher than indirect effect of academic self-efficacy. It was observed that the combined effect of grit and academic self-efficacy was less than the indirect effect of grit alone. This finding shows that grit had a strong mediator effect on academic stress in the autonomy model.

In the competence model, it was seen that the total and direct effects of grit and academic self-efficacy were statistically significant. It is seen that the indirect effect of grit is higher than the indirect effect of academic self-efficacy. It has been observed that the combined effect of grit and academic self-efficacy is less than the indirect effect of grit and academic self-efficacy alone. It is seen that the indirect effect of academic self-efficacy in the competence model is higher compared to the autonomy model.

In the relatedness model, on the other hand, the total and direct effects of grit and academic self-efficacy were found to be significant. It is seen that the indirect effect of grit is higher than the indirect effect of academic self-efficacy. It has been observed that the combined effect of grit and academic self-efficacy is less than the indirect effect of grit and academic self-efficacy alone.

Discussion, conclusion, and suggestions

As a result of this research, in which the mediator role of grit and academic self-efficacy in the relationship between psychological need satisfaction and academic stress in students was determined, it is seen that the mediating effect of grit and academic self-efficacy in the relationship between psychological need satisfaction, consisting of autonomy, competence, and relatedness, and academic stress is statistically significant. The research findings were interpreted in line with the positive psychology literature.

The results of the first hypothesis model proposed after this research demonstrated that the mediating role of grit and academic self-efficacy together in the relationship between autonomy and academic stress is statistically significant. That indication from this research supports the other result of the studies conducted before in the literature. Lozano-Jiménez et al. ( 2021 ) discussed the effect of self-determined motivation and group conformity on the life satisfaction of autonomy support and grit in university students, undergraduate and graduate. The study showed that autonomy support and grit in teachers predicted psychological need satisfaction and internal motivation, which also increased group conformity and life satisfaction. A study by Aldrup et al. ( 2017 ) analyzed the mediating role of psychological need satisfaction in the relationship between being exposed to stress and well-being. The results demonstrated that psychological need satisfaction mediates the relationship between exposure to stress and well-being. Jin and Kim ( 2017 ) also introduced that psychological need satisfaction and grit have a significant positive relationship. Jiang et al. ( 2020 ) noted that psychological need satisfaction increases well-being with the help of grit. Jang et al. ( 2019 ) also showed a mediating and regulator effect of grit and daily stress on the relationship between fundamental psychological need satisfaction and academic burnout. Duchatelet and Donche ( 2019 ) put forth that attitude of the teachers who support autonomy increases self-efficacy in students with autonomous motivation. Freire et al. ( 2019 ) worked on the mediating role of self-efficacy between coping with stress and well-being. The results demonstrated that self-efficacy partially mediated the relationship between adaptive coping and stress strategy.

Considering the results, it can be stated that autonomy-supporting behaviors increase an individual’s self-efficacies; when psychological needs are satisfied, academic self-efficacy increases and stress levels are decreased. Therefore, studies in the literature and the current study have a lot in common. This study determined that in case of an increase in autonomy, grit and academic self-efficacy increase, and the mediating effect of grit and academic self-efficacy together is significant between autonomy and academic stress. Now that they choose their learning environment and take more responsibility in their learning process, students may have become more determined about dealing with the problems they face during the learning process. Students, who feel stronger with higher autonomy, may have opted for fighting with difficulties more by taking more responsibility in the learning process. As they overcame numerous obstacles they ran into, their belief in their own efficacy increased, and as a result, they probably had less academic stress. This research also proved that when the students’ autonomy increased, their academic self-efficacy also increased simultaneously, and the mediating role of academic self-efficacy between autonomy and academic stress was found to be significant. Students who take responsibility for the learning process and organize the learning environment could see themselves as more competent academically. As a result of this process, the students could be exposed to less stress.

The results of the second hypothesis model proposed as a result of this research demonstrated that the mediating role of grit and academic self-efficacy in the relationship between competence and academic stress is statistically significant. This finding obtained as a result of the research supports the previous research in the literature. Orkaizagirre‐Gómara et al. ( 2020 ) studied the relationship between nursing students’ perceived competence, self-efficacy, psychological resilience, and stress. Results of the study showed that competence, self-efficacy, and psychological resilience decrease stress levels and increase academic success. Fabelico and Afalla ( 2020 ) analyzed the teachers’ determination and ambition levels and self-efficacy, grit, burnout, and performances. Results showed that characteristics of teachers predict their performance with the help of grit, self-efficacy, and burnout. Jose and Manikandan ( 2019 ) approached the effect of self-efficacy, the working year, and gender on grit in medicine students. Results demonstrated that there is a significant positive relationship between grit and self-efficacy. Xu et al. ( 2021 ) showed a mediating role of self-efficacy and stressful life issues between parental control and a sense of consistency in Chinese adolescents. Zhou et al. ( 2020 ) showed that adolescent school stress decreases when psychological need satisfaction increases. Brando-Garrido et al. ( 2020 ) analyzed academic delaying, perceived competence, coping mechanism, self-respect, and self-efficacy in nursing students. The study showed that there are significant negative relations between academic delaying, perceived competence, coping mechanism, self-respect, and self-efficacy, and perceived competence is the significant predictor of academic delaying. Jeong and Jin ( 2020 ) demonstrated that there is a mediating role of grit in the relationship between fundamental psychological need satisfaction and well-being. Studies, on the whole, show that individuals who consider themselves competent enough go through less stress during the learning process, have higher levels of grit, and have more self-efficacy in academic activities. In this context, when the efficacy level increases, as the individual has control over their environment, they can act more determined in overcoming the obstacles they face. At the same time, students may be more successful in controlling academic stress with higher competence, a component of psychological need satisfaction, and higher self-efficacy.

The results of the third hypothesis model proposed as a result of this research revealed that the mediating role of grit and academic self-efficacy in the relationship between relatedness and academic stress is statistically significant. This indication obtained from the result of the research supports the other studies in a similar context in the literature. The study by Lyrakos ( 2012 ) discovered a significant positive relationship between the stress-coping skills of students and self-efficacy/self-respect. Clark et al. ( 2020 ) showed that students who perceive more social support from their teachers, parents, and peers have higher grit levels. Also, results showed a regulating effect of perceived social support in the relationship between grit and academic success. In a study by Lee et al. ( 2021 ), it was determined that there is a significant positive relationship between social support and school coherence and grit variables in university students attending the nursing department. In Walakira and Kaddu’s ( 2018 ) study, the relationship between social support grit and depression in adolescents was examined. In a study conducted by Lee ( 2017 ), the relationship between academic performance, perceived academic failure, grit, and stress was examined. As a result of the research, it was seen that grit, which consists of the sub-dimensions of interest and determination, is negatively related to stress, and perceived academic failure is positively related to stress. As a result of the longitudinal research by Jumat et al. ( 2020 ) conducted on medical school students, it was revealed that grit is a factor that reduces the burnout of students. In a study by Lan ( 2020 ) on the relationship between peer relationships and grit in early adolescence, it was revealed that when peer relationships increase, grit increases too. Datu ( 2017 ) emphasized that in collectivist cultures, relatedness increases grit. Akbay and Gündüz ( 2020 ) determined a mediating role of self-efficacy, perceived social self-efficacy, and social anxiety in the relationship between peer support in adolescents and autonomy. According to the findings of the study, it was seen that at the same time, as peer support increases, social self-efficacy increases, social anxiety decreases, and as a result, autonomy increases. According to a study by Thornton et al. ( 2020 ), group conformity and positive social relations between students increase academic success and positively affect well-being. Results of this research showed that relatedness increases grit and academic self-efficacy of students and, as a result, decreases academic stress. Similarly, in the present study, it was seen that as the relatedness of medicine students increases, their stress levels decrease, and grit and academic self-efficacy played a mediating role in the relationship between these two variables. As the young people’s social relationships with their teachers, peers, and other individuals increase, their self-confidence increases, which may increase their academic self-efficacy. At the same time, the individual may have shown more grit in academic activities with the effect of positive social ties. As a result, considering their intense education life, their grit and academic self-efficacy may have increased through positive social relations. As a result, the stress levels of the students may have decreased.

Conclusion and suggestions

As a result of this research, it was determined that psychological need satisfaction, which consists of the components of autonomy, competence, and relatedness, has a significant effect on academic stress directly and indirectly through grit and academic self-efficacy. When evaluated in terms of the components of psychological need satisfaction, it was seen that the direct and total effects of academic stress were highest in the autonomy model. In the competence and relatedness model, the total indirect effect was found to be higher than the autonomy model. Accordingly, students’ autonomy explains the academic stress variable, but it has been determined that grit and academic self-efficacy, which are the mediating variables, have a very high indirect effect in the dimensions of competence and relatedness. This finding indicates that grit and academic self-efficacy should also be taken into account, apart from the psychological need satisfaction components, in reducing academic stress.

The current research results showed that grit and academic self-efficacy mediated the relationship between autonomy, competence, and relatedness, which are among the basic psychological need satisfaction and academic stress of preclinical medical students, education faculty, and undergraduate students of theology faculty. These findings reveal the importance of considering constructs such as psychological need satisfaction, perseverance, and academic self-efficacy in preventive studies to reduce and prevent stress for this group, whose education program is intense and who are more likely to be exposed to stress.

As a result of this research that tries to clarify the academic stress in college students with mediating variables, the following suggestions can be made:

This study showed that increasing psychological need satisfaction decreases academic stress and increases grit and academic self-efficacy. Thus, learning environments of departments that have intense academic content and stressful learning conditions can be designed to support students’ autonomy. Classes can be continued with activities that aim to cooperate among students, support competition positively, and make students feel competent. Also, considering that grit is a mediating variable, the motivation of students that increases their determination and makes sure that they can continue without giving up when they face difficulties can be supported. Psychoacademic studies that are thought to increase grit, academic self-efficacy, and motivation levels can be done for that purpose.

Results of the research showed that studies could be designed for the researchers that deal with the mediating and moderating effects of variables such as psychological resilience, hope, optimism, academic well-being, academic strength, and academic procrastination, which are thought to affect academic stress levels of students in future studies. Since this study was carried out only on preclinical medical students, comparative research can be conducted on students in different departments or with students studying in various provinces in future studies. This research was designed as cross-sectional. Longitudinal studies can be completed in future studies.

Limitations

This research has some limitations such as its sampling method and data collection methods. This research was designed in a cross-sectional design and convenient sampling method was used to determine the sample. In the collection of data, online method was used due to the online education in time of COVID-19. In this context, there are some limitations in generalizing the data originating from the method and sample to the population. Although these limitations are tried to be eliminated by including participants with various characteristics as much as possible, generalization limitations can be eliminated by designing probabilistic sampling method and longitudinal studies in future studies. This research was conducted with students studying at three different faculties. In order to increase the generalizability of the results obtained in future studies, it can be examined whether the same model is confirmed in different departments by including different faculties and using a multi-group structural equation model.

Since this research is limited to students’ responses to the scales and uses the quantitative method, variables that cause academic stress can be investigated by using qualitative and mixed methods in future studies. In this study, the mediating effect of grit and academic self-efficacy on the relationship between psychological need satisfaction and academic stress was examined. In this context, academic stress has been tried to be explained only by non-cognitive variables. Its relationship with other variables such as intrinsic motivation, flow experiences, cognitive flexibility, and problem-solving skills that may affect academic stress can be discussed. Experimental research can be designed to reduce academic stress with taking into account grit, academic self-efficacy, and psychological need satisfaction. In this study, it is not known how many categories the stress levels of the students in the sample group are clustered. At the same time, it does not contain information about the stress levels of students at different grade levels. In future research, the change in students’ stress in different years can be determined by latent profile analysis and the number of groups can be determined, and the change over the years can be evaluated with longitudinal studies.

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Çınar-Tanrıverdi, E., Karabacak-Çelik, A. Psychological need satisfaction and academic stress in college students: mediator role of grit and academic self-efficacy. Eur J Psychol Educ 38 , 131–160 (2023). https://doi.org/10.1007/s10212-022-00658-1

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ORIGINAL RESEARCH article

Academic stress and mental well-being in college students: correlations, affected groups, and covid-19.

• 1 Department of Neurology, Rutgers New Jersey Medical School, Newark, NJ, United States
• 2 Rutgers New Jersey Medical School, Newark, NJ, United States
• 3 Office for Diversity and Community Engagement, Rutgers New Jersey Medical School, Newark, NJ, United States
• 4 Department of Biology, The College of New Jersey, Ewing, NJ, United States

Academic stress may be the single most dominant stress factor that affects the mental well-being of college students. Some groups of students may experience more stress than others, and the coronavirus disease 19 (COVID-19) pandemic could further complicate the stress response. We surveyed 843 college students and evaluated whether academic stress levels affected their mental health, and if so, whether there were specific vulnerable groups by gender, race/ethnicity, year of study, and reaction to the pandemic. Using a combination of scores from the Perception of Academic Stress Scale (PAS) and the Short Warwick-Edinburgh Mental Well-Being Scale (SWEMWBS), we found a significant correlation between worse academic stress and poor mental well-being in all the students, who also reported an exacerbation of stress in response to the pandemic. In addition, SWEMWBS scores revealed the lowest mental health and highest academic stress in non-binary individuals, and the opposite trend was observed for both the measures in men. Furthermore, women and non-binary students reported higher academic stress than men, as indicated by PAS scores. The same pattern held as a reaction to COVID-19-related stress. PAS scores and responses to the pandemic varied by the year of study, but no obvious patterns emerged. These results indicate that academic stress in college is significantly correlated to psychological well-being in the students who responded to this survey. In addition, some groups of college students are more affected by stress than others, and additional resources and support should be provided to them.

Introduction

Late adolescence and emerging adulthood are transitional periods marked by major physiological and psychological changes, including elevated stress ( Hogan and Astone, 1986 ; Arnett, 2000 ; Shanahan, 2000 ; Spear, 2000 ; Scales et al., 2015 ; Romeo et al., 2016 ; Barbayannis et al., 2017 ; Chiang et al., 2019 ; Lally and Valentine-French, 2019 ; Matud et al., 2020 ). This pattern is particularly true for college students. According to a 2015 American College Health Association-National College Health Assessment survey, three in four college students self-reported feeling stressed, while one in five college students reported stress-related suicidal ideation ( Liu, C. H., et al., 2019 ; American Psychological Association, 2020 ). Studies show that a stressor experienced in college may serve as a predictor of mental health diagnoses ( Pedrelli et al., 2015 ; Liu, C. H., et al., 2019 ; Karyotaki et al., 2020 ). Indeed, many mental health disorders, including depression, anxiety, and substance abuse disorder, begin during this period ( Blanco et al., 2008 ; Pedrelli et al., 2015 ; Saleh et al., 2017 ; Reddy et al., 2018 ; Liu, C. H., et al., 2019 ).

Stress experienced by college students is multi-factorial and can be attributed to a variety of contributing factors ( Reddy et al., 2018 ; Karyotaki et al., 2020 ). A growing body of evidence suggests that academic-related stress plays a significant role in college ( Misra and McKean, 2000 ; Dusselier et al., 2005 ; Elias et al., 2011 ; Bedewy and Gabriel, 2015 ; Hj Ramli et al., 2018 ; Reddy et al., 2018 ; Pascoe et al., 2020 ). For instance, as many as 87% of college students surveyed across the United States cited education as their primary source of stress ( American Psychological Association, 2020 ). College students are exposed to novel academic stressors, such as an extensive academic course load, substantial studying, time management, classroom competition, financial concerns, familial pressures, and adapting to a new environment ( Misra and Castillo, 2004 ; Byrd and McKinney, 2012 ; Ekpenyong et al., 2013 ; Bedewy and Gabriel, 2015 ; Ketchen Lipson et al., 2015 ; Pedrelli et al., 2015 ; Reddy et al., 2018 ; Liu, C. H., et al., 2019 ; Freire et al., 2020 ; Karyotaki et al., 2020 ). Academic stress can reduce motivation, hinder academic achievement, and lead to increased college dropout rates ( Pascoe et al., 2020 ).

Academic stress has also been shown to negatively impact mental health in students ( Li and Lin, 2003 ; Eisenberg et al., 2009 ; Green et al., 2021 ). Mental, or psychological, well-being is one of the components of positive mental health, and it includes happiness, life satisfaction, stress management, and psychological functioning ( Ryan and Deci, 2001 ; Tennant et al., 2007 ; Galderisi et al., 2015 ; Trout and Alsandor, 2020 ; Defeyter et al., 2021 ; Green et al., 2021 ). Positive mental health is an understudied but important area that helps paint a more comprehensive picture of overall mental health ( Tennant et al., 2007 ; Margraf et al., 2020 ). Moreover, positive mental health has been shown to be predictive of both negative and positive mental health indicators over time ( Margraf et al., 2020 ). Further exploring the relationship between academic stress and mental well-being is important because poor mental well-being has been shown to affect academic performance in college ( Tennant et al., 2007 ; Eisenberg et al., 2009 ; Freire et al., 2016 ).

Perception of academic stress varies among different groups of college students ( Lee et al., 2021 ). For instance, female college students report experiencing increased stress than their male counterparts ( Misra et al., 2000 ; Eisenberg et al., 2007 ; Evans et al., 2018 ; Lee et al., 2021 ). Male and female students also respond differently to stressors ( Misra et al., 2000 ; Verma et al., 2011 ). Moreover, compared to their cisgender peers, non-binary students report increased stressors and mental health issues ( Budge et al., 2020 ). The academic year of study of the college students has also been shown to impact academic stress levels ( Misra and McKean, 2000 ; Elias et al., 2011 ; Wyatt et al., 2017 ; Liu, C. H., et al., 2019 ; Defeyter et al., 2021 ). While several studies indicate that racial/ethnic minority groups of students, including Black/African American, Hispanic/Latino, and Asian American students, are more likely to experience anxiety, depression, and suicidality than their white peers ( Lesure-Lester and King, 2004 ; Lipson et al., 2018 ; Liu, C. H., et al., 2019 ; Kodish et al., 2022 ), these studies are limited and often report mixed or inconclusive findings ( Liu, C. H., et al., 2019 ; Kodish et al., 2022 ). Therefore, more studies should be conducted to address this gap in research to help identify subgroups that may be disproportionately impacted by academic stress and lower well-being.

The coronavirus disease 19 (COVID-19) pandemic is a major stressor that has led to a mental health crisis ( American Psychological Association, 2020 ; Dong and Bouey, 2020 ). For college students, the COVID-19 pandemic has resulted in significant changes and disruptions to daily life, elevated stress levels, and mental and physical health deterioration ( American Psychological Association, 2020 ; Husky et al., 2020 ; Patsali et al., 2020 ; Son et al., 2020 ; Clabaugh et al., 2021 ; Lee et al., 2021 ; Lopes and Nihei, 2021 ; Yang et al., 2021 ). While any college student is vulnerable to these stressors, these concerns are amplified for members of minority groups ( Salerno et al., 2020 ; Clabaugh et al., 2021 ; McQuaid et al., 2021 ; Prowse et al., 2021 ; Kodish et al., 2022 ). Identifying students at greatest risk provides opportunities to offer support, resources, and mental health services to specific subgroups.

The overall aim of this study was to assess academic stress and mental well-being in a sample of college students. Within this umbrella, we had several goals. First, to determine whether a relationship exists between the two constructs of perceived academic stress, measured by the Perception of Academic Stress Scale (PAS), and mental well-being, measured by the Short Warwick-Edinburgh Mental Well-Being Scale (SWEMWBS), in college students. Second, to identify groups that could experience differential levels of academic stress and mental health. Third, to explore how the perception of the ongoing COVID-19 pandemic affected stress levels. We hypothesized that students who experienced more academic stress would have worse psychological well-being and that certain groups of students would be more impacted by academic- and COVID-19-related stress.

Materials and Methods

Survey instrument.

A survey was developed that included all questions from the Short Warwick-Edinburgh Mental Well-Being ( Tennant et al., 2007 ; Stewart-Brown and Janmohamed, 2008 ) and from the Perception of Academic Stress Scale ( Bedewy and Gabriel, 2015 ). The Short Warwick-Edinburgh Mental Well-Being Scale is a seven-item scale designed to measure mental well-being and positive mental health ( Tennant et al., 2007 ; Fung, 2019 ; Shah et al., 2021 ). The Perception of Academic Stress Scale is an 18-item scale designed to assess sources of academic stress perceived by individuals and measures three main academic stressors: academic expectations, workload and examinations, and academic self-perceptions of students ( Bedewy and Gabriel, 2015 ). These shorter scales were chosen to increase our response and study completion rates ( Kost and de Rosa, 2018 ). Both tools have been shown to be valid and reliable in college students with Likert scale responses ( Tennant et al., 2007 ; Bedewy and Gabriel, 2015 ; Ringdal et al., 2018 ; Fung, 2019 ; Koushede et al., 2019 ). Both the SWEMWBS and PAS scores are a summation of responses to the individual questions in the instruments. For the SWEMWBS questions, a higher score indicates better mental health, and scores range from 7 to 35. Similarly, the PAS questions are phrased such that a higher score indicates lower levels of stress, and scores range from 18 to 90. We augmented the survey with demographic questions (e.g., age, gender, and race/ethnicity) at the beginning of the survey and two yes/no questions and one Likert scale question about the impact of the COVID-19 pandemic at the end of our survey.

Participants for the study were self-reported college students between the ages of 18 and 30 years who resided in the United States, were fluent in English, and had Internet access. Participants were solicited through Prolific ( https://prolific.co ) in October 2021. A total of 1,023 individuals enrolled in the survey. Three individuals did not agree to participate after beginning the survey. Two were not fluent in English. Thirteen individuals indicated that they were not college students. Two were not in the 18–30 age range, and one was located outside of the United States. Of the remaining individuals, 906 were full-time students and 96 were part-time students. Given the skew of the data and potential differences in these populations, we removed the part-time students. Of the 906 full-time students, 58 indicated that they were in their fifth year of college or higher. We understand that not every student completes their undergraduate studies in 4 years, but we did not want to have a mixture of undergraduate and graduate students with no way to differentiate them. Finally, one individual reported their age as a non-number, and four individuals did not answer a question about their response to the COVID-19 pandemic. This yielded a final sample of 843 college students.

Data Analyses

After reviewing the dataset, some variables were removed from consideration due to a lack of consistency (e.g., some students reported annual income for themselves and others reported family income) or heterogeneity that prevented easy categorization (e.g., field of study). We settled on four variables of interest: gender, race/ethnicity, year in school, and response to the COVID-19 pandemic ( Table 1 ). Gender was coded as female, male, or non-binary. Race/ethnicity was coded as white or Caucasian; Black or African American; East Asian; Hispanic, Latino, or of Spanish origin; or other. Other was used for groups that were not well-represented in the sample and included individuals who identified themselves as Middle Eastern, Native American or Alaskan Native, and South Asian, as well as individuals who chose “other” or “prefer not to answer” on the survey. The year of study was coded as one through four, and COVID-19 stress was coded as two groups, no change/neutral response/reduced stress or increased stress.

Table 1 . Characteristics of the participants in the study.

Our first goal was to determine whether there was a relationship between self-reported academic stress and mental health, and we found a significant correlation (see Results section). Given the positive correlation, a multivariate analysis of variance (MANOVA) with a model testing the main effects of gender, race/ethnicity, and year of study was run in SPSS v 26.0. A factorial MANOVA would have been ideal, but our data were drawn from a convenience sample, which did not give equal representation to all groupings, and some combinations of gender, race/ethnicity, and year of study were poorly represented (e.g., a single individual). As such, we determined that it would be better to have a lack of interaction terms as a limitation to the study than to provide potentially spurious results. Finally, we used chi-square analyses to assess the effect of potential differences in the perception of the COVID-19 pandemic on stress levels in general among the groups in each category (gender, race/ethnicity, and year of study).

In terms of internal consistency, Cronbach's alpha was 0.82 for the SMEMWBS and 0.86 for the PAS. A variety of descriptors have been applied to Cronbach's alpha values. That said, 0.7 is often considered a threshold value in terms of acceptable internal consistency, and our values could be considered “high” or “good” ( Taber, 2018 ).

The participants in our study were primarily women (78.5% of respondents; Table 1 ). Participants were not equally distributed among races/ethnicities, with the majority of students selecting white or Caucasian (66.4% of responders; Table 1 ), or years of study, with fewer first-year students than other groups ( Table 1 ).

Students who reported higher academic stress also reported worse mental well-being in general, irrespective of age, gender, race/ethnicity, or year of study. PAS and SWEMWBS scores were significantly correlated ( r = 0.53, p < 0.001; Figure 1 ), indicating that a higher level of perceived academic stress is associated with worse mental well-being in college students within the United States.

Figure 1 . SWEMWBS and PAS scores for all participants.

Among the subgroups of students, women, non-binary students, and second-year students reported higher academic stress levels and worse mental well-being ( Table 2 ; Figures 2 – 4 ). In addition, the combined measures differed significantly between the groups in each category ( Table 2 ). However, as measured by partial eta squared, the effect sizes were relatively small, given the convention of 0.01 = small, 0.06 = medium, and 0.14 = large differences ( Lakens, 2013 ). As such, there were only two instances in which Tukey's post-hoc tests revealed more than one statistical grouping ( Figures 2 – 4 ). For SWEMWBS score by gender, women were intermediate between men (high) and non-binary individuals (low) and not significantly different from either group ( Figure 2 ). Second-year students had the lowest PAS scores for the year of study, and first-year students had the highest scores. Third- and fourth-year students were intermediate and not statistically different from the other two groups ( Figure 4 ). There were no pairwise differences in academic stress levels or mental well-being among racial/ethnic groups.

Table 2 . Results of the MANOVA.

Figure 2 . SWEMWBS and PAS scores according to gender (mean ± SEM). Different letters for SWEMWBS scores indicate different statistical groupings ( p < 0.05).

Figure 3 . SWEMWBS and PAS scores according to race/ethnicity (mean ± SEM).

Figure 4 . SWEMWBS and PAS scores according to year in college (mean ± SEM). Different letters for PAS scores indicate different statistical groupings ( p < 0.05).

The findings varied among categories in terms of stress responses due to the COVID-19 pandemic ( Table 3 ). For gender, men were less likely than women or non-binary individuals to report increased stress from COVID-19 (χ 2 = 27.98, df = 2, p < 0.001). All racial/ethnic groups responded similarly to the pandemic (χ 2 = 3.41, df = 4, p < 0.49). For the year of study, first-year students were less likely than other cohorts to report increased stress from COVID-19 (χ 2 = 9.38, df = 3, p < 0.03).

Table 3 . Impact of COVID-19 on stress level by gender, race/ethnicity, and year of study.

Our primary findings showed a positive correlation between perceived academic stress and mental well-being in United States college students, suggesting that academic stressors, including academic expectations, workload and grading, and students' academic self-perceptions, are equally important as psychological well-being. Overall, irrespective of gender, race/ethnicity, or year of study, students who reported higher academic stress levels experienced diminished mental well-being. The utilization of well-established scales and a large sample size are strengths of this study. Our results extend and contribute to the existing literature on stress by confirming findings from past studies that reported higher academic stress and lower psychological well-being in college students utilizing the same two scales ( Green et al., 2021 ; Syed, 2021 ). To our knowledge, the majority of other prior studies with similar findings examined different components of stress, studied negative mental health indicators, used different scales or methods, employed smaller sample sizes, or were conducted in different countries ( Li and Lin, 2003 ; American Psychological Association, 2020 ; Husky et al., 2020 ; Pascoe et al., 2020 ; Patsali et al., 2020 ; Clabaugh et al., 2021 ; Lee et al., 2021 ; Lopes and Nihei, 2021 ; Yang et al., 2021 ).

This study also demonstrated that college students are not uniformly impacted by academic stress or pandemic-related stress and that there are significant group-level differences in mental well-being. Specifically, non-binary individuals and second-year students were disproportionately impacted by academic stress. When considering the effects of gender, non-binary students, in comparison to gender-conforming students, reported the highest stress levels and worst psychological well-being. Although there is a paucity of research examining the impact of academic stress in non-binary college students, prior studies have indicated that non-binary adults face adverse mental health outcomes when compared to male and female-identifying individuals ( Thorne et al., 2018 ; Jones et al., 2019 ; Budge et al., 2020 ). Alarmingly, Lipson et al. (2019) found that gender non-conforming college students were two to four times more likely to experience mental health struggles than cisgender students ( Lipson et al., 2019 ). With a growing number of college students in the United States identifying as as non-binary, additional studies could offer invaluable insight into how academic stress affects this population ( Budge et al., 2020 ).

In addition, we found that second-year students reported the most academic-related distress and lowest psychological well-being relative to students in other years of study. We surmise this may be due to this group taking advanced courses, managing heavier academic workloads, and exploring different majors. Other studies support our findings and suggest higher stress levels could be attributed to increased studying and difficulties with time management, as well as having less well-established social support networks and coping mechanisms compared to upperclassmen ( Allen and Hiebert, 1991 ; Misra and McKean, 2000 ; Liu, X et al., 2019 ). Benefiting from their additional experience, upperclassmen may have developed more sophisticated studying skills, formed peer support groups, and identified approaches to better manage their academic stress ( Allen and Hiebert, 1991 ; Misra and McKean, 2000 ). Our findings suggest that colleges should consider offering tailored mental health resources, such as time management and study skill workshops, based on the year of study to improve students' stress levels and psychological well-being ( Liu, X et al., 2019 ).

Although this study reported no significant differences regarding race or ethnicity, this does not indicate that minority groups experienced less academic stress or better mental well-being ( Lee et al., 2021 ). Instead, our results may reflect the low sample size of non-white races/ethnicities, which may not have given enough statistical power to corroborate. In addition, since coping and resilience are important mediators of subjective stress experiences ( Freire et al., 2020 ), we speculate that the lower ratios of stress reported in non-white participants in our study (75 vs. 81) may be because they are more accustomed to adversity and thereby more resilient ( Brown, 2008 ; Acheampong et al., 2019 ). Furthermore, ethnic minority students may face stigma when reporting mental health struggles ( Liu, C. H., et al., 2019 ; Lee et al., 2021 ). For instance, studies showed that Black/African American, Hispanic/Latino, and Asian American students disclose fewer mental health issues than white students ( Liu, C. H., et al., 2019 ; Lee et al., 2021 ). Moreover, the ability to identify stressors and mental health problems may manifest differently culturally for some minority groups ( Huang and Zane, 2016 ; Liu, C. H., et al., 2019 ). Contrary to our findings, other studies cited racial disparities in academic stress levels and mental well-being of students. More specifically, Negga et al. (2007) concluded that African American college students were more susceptible to higher academic stress levels than their white classmates ( Negga et al., 2007 ). Another study reported that minority students experienced greater distress and worse mental health outcomes compared to non-minority students ( Smith et al., 2014 ). Since there may be racial disparities in access to mental health services at the college level, universities, professors, and counselors should offer additional resources to support these students while closely monitoring their psychological well-being ( Lipson et al., 2018 ; Liu, C. H., et al., 2019 ).

While the COVID-19 pandemic increased stress levels in all the students included in our study, women, non-binary students, and upperclassmen were disproportionately affected. An overwhelming body of evidence suggests that the majority of college students experienced increased stress levels and worsening mental health as a result of the pandemic ( Allen and Hiebert, 1991 ; American Psychological Association, 2020 ; Husky et al., 2020 ; Patsali et al., 2020 ; Son et al., 2020 ; Clabaugh et al., 2021 ; Lee et al., 2021 ; Yang et al., 2021 ). Our results also align with prior studies that found similar subgroups of students experience disproportionate pandemic-related distress ( Gao et al., 2020 ; Clabaugh et al., 2021 ; Hunt et al., 2021 ; Jarrett et al., 2021 ; Lee et al., 2021 ; Chen and Lucock, 2022 ). In particular, the differences between female students and their male peers may be the result of different psychological and physiological responses to stress reactivity, which in turn may contribute to different coping mechanisms to stress and the higher rates of stress-related disorders experienced by women ( Misra et al., 2000 ; Kajantie and Phillips, 2006 ; Verma et al., 2011 ; Gao et al., 2020 ; Graves et al., 2021 ). COVID-19 was a secondary consideration in our study and survey design, so the conclusions drawn here are necessarily limited.

The implications of this study are that college students facing increased stress and struggling with mental health issues should receive personalized and specific mental health services, resources, and support. This is particularly true for groups that have been disproportionately impacted by academic stress and stress due to the pandemic. Many students who experience mental health struggles underutilize college services due to cost, stigma, or lack of information ( Cage et al., 2020 ; Lee et al., 2021 ). To raise awareness and destigmatize mental health, colleges can consider distributing confidential validated assessments, such as the PAS and SWEMWBS, in class and teach students to self-score ( Lee et al., 2021 ). These results can be used to understand how academic stress and mental well-being change over time and allow for specific and targeted interventions for vulnerable groups. In addition, teaching students healthy stress management techniques has been shown to improve psychological well-being ( Alborzkouh et al., 2015 ). Moreover, adaptive coping strategies, including social and emotional support, have been found to improve the mental well-being of students, and stress-reduction peer support groups and workshops on campus could be beneficial in reducing stress and improving the self-efficacy of students ( Ruthig et al., 2009 ; Baqutayan, 2011 ; Bedewy and Gabriel, 2015 ; Freire et al., 2020 ; Green et al., 2021 ; Suresh et al., 2021 ). Other interventions that have been effective in improving the coping skills of college students include cognitive-behavioral therapy, mindfulness mediation, and online coping tools ( Kang et al., 2009 ; Regehr et al., 2013 ; Molla Jafar et al., 2015 ; Phang et al., 2015 ; Houston et al., 2017 ; Yusufov et al., 2019 ; Freire et al., 2020 ). Given that resilience has also been shown to help mediate stress and improve mental well-being during the COVID-19 pandemic, interventions focusing on enhancing resilience should be considered ( Surzykiewicz et al., 2021 ; Skalski et al., 2022 ). Telemental health resources across colleges can also be implemented to reduce stigma and improve at-risk students' access to care ( Toscos et al., 2018 ; Hadler et al., 2021 ). University campuses, professors, and counselors should consider focusing on fostering a more equitable and inclusive environment to encourage marginalized students to seek mental health support ( Budge et al., 2020 ).

Limitations

While our study has numerous strengths, including using standardized instruments and a large sample size, this study also has several limitations due to both the methodology and sample. First, the correlational study design precludes making any causal relationships ( Misra and McKean, 2000 ). Thereby, our findings should be taken in the context of academic stress and mental well-being, and recognize that mental health could be caused by other non-academic factors. Second, the PAS comprised only the perception of responses to academic stress, but stress is a multi-factorial response that encompasses both perceptions and coping mechanisms to different stressors, and the magnitude of stress varies with the perception of the degree of uncontrollability, unpredictability, or threat to self ( Miller, 1981 ; Hobfoll and Walfisch, 1984 ; Lazarus and Folkman, 1984 ; Wheaton, 1985 ; Perrewé and Zellars, 1999 ; Schneiderman et al., 2005 ; Bedewy and Gabriel, 2015 ; Schönfeld et al., 2016 ; Reddy et al., 2018 ; Freire et al., 2020 ; Karyotaki et al., 2020 ). Third, the SWEMSBS used in our study and the data only measured positive mental health. Mental health pathways are numerous and complex, and are composed of distinct and interdependent negative and positive indicators that should be considered together ( Margraf et al., 2020 ). Fourth, due to the small effect sizes and unequal representation for different combinations of variables, our analysis for both the PAS and SWEMSBS included only summed-up scales and did not examine group differences in response to the type of academic stressors or individual mental health questions.

An additional limitation is that the participants in our study were a convenience sample. The testing service we used, prolific.co, self-reports a sample bias toward young women of high levels of education (i.e., WEIRD bias) ( Team Prolific, 2018 ). The skew toward this population was observed in our data, as 80% of our participants were women. While we controlled for these factors, the possibility remains that the conclusions we draw for certain groups, such as nonbinary students, ethnic/racial minorities, and men, may not be as statistically powerful as they should be. Moreover, our pre-screening was designed to recruit undergraduate level, English-speaking, 18–30-year-olds who resided in the United States. This resulted in our participant demographics being skewed toward the WEIRD bias that was already inherent in the testing service we used. Future research will aim to be more inclusive of diverse races/ethnicities, sexual orientations, languages, educational backgrounds, socioeconomic backgrounds, and first-generation college students.

Another limitation of our study is the nature of satisficing. Satisficing is a response strategy in which a participant answers a question to satisfy its condition with little regard to the quality or accuracy of the answer ( Roberts et al., 2019 ). Anonymous participants are more likely to satisfice than respondents who answer the question face-to-face ( Krosnick et al., 2002 ). We sought to mitigate satisficing by offering financial incentives to increase response rates and decrease straight-lining, item skipping, total missing items, and non-completion ( Cole et al., 2015 ). Concerns of poor data quality due to surveys offering financial incentives found little evidence to support that claim and may do the opposite ( Cole et al., 2015 ). On the other hand, social desirability bias may have influenced the participant's self-reported responses, although our anonymous survey design aimed to reduce this bias ( Joinson, 1999 ; Kecojevic et al., 2020 ).

Future Studies

Future studies should replicate our study to validate our results, conduct longitudinal cohort studies to examine well-being and perceived academic stress over time, and aim for a more representative student sample that includes various groups, including diverse races/ethnicities, sexual orientations, socioeconomic backgrounds, languages, educational levels, and first-generation college students. Additionally, these studies should consider examining other non-academic stressors and students' coping mechanisms, both of which contribute to mental health and well-being ( Lazarus and Folkman, 1984 ; Freire et al., 2020 ). Further explorations of negative and other positive indicators of mental health may offer a broader perspective ( Margraf et al., 2020 ). Moreover, future research should consider extending our work by exploring group differences in relation to each factor in the PAS (i.e., academic expectations, workload and examinations, and self-perception of students) and SWEMBS to determine which aspects of academic stress and mental health were most affected and allow for the devising of targeted stress-reduction approaches. Ultimately, we hope our research spurs readers into advocating for greater academic support and access to group-specific mental health resources to reduce the stress levels of college students and improve their mental well-being.

Utilizing two well-established scales, our research found a statistically significant correlation between the perceived academic stress of university students and their mental well-being (i.e., the higher the stress, the worse the well-being). This relationship was most apparent among gender and grade levels. More specifically, non-binary and second-year students experienced greater academic burden and lower psychological well-being. Moreover, women, non-binary students, and upper-level students were disproportionately impacted by stress related to the COVID-19 pandemic.

Studies regarding broad concepts of stress and well-being using a questionnaire are limited, but our study adds value to the understanding of academic stress as a contributor to the overall well-being of college students during this specific point in time (i.e., the COVID-19 pandemic). Competition both for admission to college ( Bound et al., 2009 ) and during college ( Posselt and Lipson, 2016 ) has increased over time. Further, selective American colleges and universities draw applicants from a global pool. As such, it is important to document the dynamics of academic stress with renewed focus. We hope that our study sparks interest in both exploring and funding in-depth and well-designed psychological studies related to stress in colleges in the future.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics Statement

The studies involving human participants were reviewed and approved by Institutional Review Board at Rutgers University. The patients/participants provided their written informed consent to participate in this study.

Author Contributions

GB and MB contributed to conceptualization, study design, IRB application, manuscript drafting, and revision. XZ participated in the conceptualization and design of the questionnaires. HB participated in subject recruitment and questionnaire collection. KP contributed to data analysis, table and figure preparation, manuscript drafting, and revision. XM contributed to conceptualization, study design, IRB application, supervision of the project, manuscript drafting, and revision. All authors contributed to the article and approved the submitted version.

This study was made possible by a generous donation from the Knights of Columbus East Hanover Chapter in New Jersey.

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.

Acknowledgments

The authors wish to thank Shivani Mehta and Varsha Garla for their assistance with the study. We also thank all the participants for their efforts in the completion of the study.

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Keywords: academic stress, well-being, college students, Perception of Academic Stress, Short Warwick-Edinburgh Mental Well-Being Scale, COVID-19

Citation: Barbayannis G, Bandari M, Zheng X, Baquerizo H, Pecor KW and Ming X (2022) Academic Stress and Mental Well-Being in College Students: Correlations, Affected Groups, and COVID-19. Front. Psychol. 13:886344. doi: 10.3389/fpsyg.2022.886344

Received: 28 February 2022; Accepted: 20 April 2022; Published: 23 May 2022.

Reviewed by:

Copyright © 2022 Barbayannis, Bandari, Zheng, Baquerizo, Pecor and Ming. 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: Keith W. Pecor, pecor@tcnj.edu

† These authors have contributed equally to this work and share first authorship

Disclaimer: 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.

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The Impact of Academic Pressure and Peer Support on Adolescents’ Loneliness: A Polynomial Regression and Response Surface Analysis

Zhensong lan.

1 School of Public Administration, Hechi University, Yizhou, Guangxi, 546300, People’s Republic of China

Huaqiang Liu

2 School of Law and Public Administration, Yibin University, Yibin, Sichuan, 644000, People’s Republic of China

3 Yibin Ronghe Social Work Service Center, Yibin, Sichuan, 644000, People’s Republic of China

Xuefang Huang

4 School of Teacher Education, Hechi University, Yizhou, Guangxi, 546300, People’s Republic of China

5 Jiangxi University of Finance and Economics, Nanchang, Jiangxi, 330013, People’s Republic of China

Fafang Deng

6 School of Economics and Management, Beijing University of Technology, Beijing, 100124, People’s Republic of China

To explore the impact of the match between academic pressure and peer support on adolescents’ sense of loneliness and examine whether social connectedness played a mediating role, using a polynomial regression and response surface analysis.

A questionnaire survey was conducted with 1277 adolescents from two cities in Sichuan Province, China, to investigate their academic pressure, peer support, social connectedness, and sense of loneliness.

(1) Adolescents’ sense of loneliness positively correlated with their level of academic pressure and negatively correlated with their degree of peer support. (2) Social connectedness played a mediating role in the relationship between academic pressure, peer support, and sense of loneliness. (3) Adolescents with high academic pressure and low peer support had weaker social connectedness than those with low academic pressure and high peer support. (4) Adolescents with high academic pressure and high peer support had stronger social connectedness than those with low academic pressure and low peer support.

The study revealed the mechanism through which a match (or mismatch) between academic pressure and peer support influenced adolescents’ sense of loneliness and validated the mediating role of social connectedness. The study enriches the developmental theory of adolescent loneliness and provides research experience for future interventions targeting adolescent loneliness.

Introduction

Loneliness is a subjective feeling of social isolation or a perceived lack of contact with others that results in a distressing experience. 1 It is also a significant but underestimated public health risk. 2 Loneliness pervades the entire human lifespan but is most common among adolescents and young people. 3 , 4 Statistics show that nearly 80% of adolescents frequently experience loneliness. 5 The causes of their loneliness include limited familial interaction or increased familial conflict, 6 , 7 hindered development of intimate social relationships, 8 academic maladaptation, 9 and transitions to new environments or roles. 10 , 11 Context development theory suggests that support from friends and parents interact in adolescents’ emotional adaptation, with one form of support compensating for the absence of the other. 12 , 13 Academic pressure also seems to play a role in the increase in adolescent loneliness. 14 This study aims to explore this interaction.

The Relationship Between Academic Pressure and Sense of Loneliness

Academic pressure is defined as stress related to academic performance. 15 Research has shown that the significant increase in loneliness during adolescence is often associated with poor academic performance. 16 One reason is that, in many countries, teachers, and parents place great emphasis on education, making educational expectations one of the main sources of immense pressure on adolescents. 17 There may thus be a positive correlation between academic pressure and loneliness, with high academic pressure leading to higher levels of loneliness, and lonely adolescents feeling a greater academic burden. 14 Although loneliness has been extensively explored as a variable, academic pressure has not received much attention as a factor contributing to a sense of loneliness. However, it has been proven to be a significant variable that should not be overlooked. 14 Previous researches have not much studied on the relationship between academic stress and loneliness among Chinese adolescents. In view of the background that Chinese adolescents generally face greater academic pressure, it is necessary to further examine this relationship.

This study therefore proposes Hypothesis 1: There is a significant positive correlation between academic pressure and a sense of loneliness in adolescents.

The Relationship Between Friend Support and Sense of Loneliness

High-quality friendships are crucial for the well-being of adolescents. 18 Peers and parents are important factors in an individual’s developmental environment, and different types of social relationship can meet different interpersonal needs. 19 Each type of relationship provides essential functions, and a lack of necessary relationship provisions can lead to painful experiences of loneliness. 4 During adolescence, peer relationships in predicting adolescent well-being becomes more prominent. 20 Evidence suggests that a lack of intimate friendships is one of the main causes of adolescent loneliness. 13 In view of the fact that social relationships can meet interpersonal needs and the impact of intimate relationships on adolescents’ loneliness, previous studies have also lacked the relationship between peer support and loneliness. This study attempts to further explore the impact of peer support on adolescents’ loneliness, in order to explore the improvement of adolescents’ peer support to improve their loneliness in the future.

Therefore, this study proposes Hypothesis 2: There is a significant negative correlation between peer support and a sense of loneliness in adolescents.

The Relationship Between Academic Pressure, Friend Support, Social Connectedness, and Sense of Loneliness

Social connectedness refers to an individual’s subjective perception of the intimacy of interpersonal relationships and the cognitive recognition of patterns in these relationships. It reflects an individual’s attachment and commitment to social entities. 20–22 Loneliness occurs when there is a discrepancy between an individual’s expectations and the actual level of interpersonal interactions. It is a subjective experience of perceived unsatisfactory social connectedness and interpersonal relationships, indicating that lonely individuals often experience poor social interactions. 20 , 23 One study found that middle school students with better school connectedness and social connectedness had better mental health outcomes. 24 This suggests that when individuals feel lonely, they may need to enhance their social connectedness and engage in friendly interactions and conversations with others to promote positive emotional experiences and alleviate the distress caused by loneliness. 14

Research has shown that social connectedness is positively correlated with social support and is a protective factor for common psychological distress symptoms such as loneliness, 25 , 26 while a decrease in social support is closely associated with increased feelings of loneliness in adolescents. 27 In addition, scholars have found that higher levels of academic pressure are associated with lower levels of social support. 28 Previous studies focused on the impact of academic stress, peer support or social connection on adolescent loneliness, lacking of research experience to explore how academic stress and peer support work together to affect adolescent loneliness. In addition, peer support is passive support, while social connection is active connection, so it is necessary to explore the mediating role of social connection in it.

Therefore, in order to investigate the mechanisms through which academic pressure and peer support influence feelings of loneliness in adolescents, as well as the mediating role of social connectedness in this mechanism, this study proposes Hypothesis 3: Social connectedness plays a mediating role between the matching effect of “academic pressure-peer relationship” and loneliness in adolescents.

Participants

This study selected adolescents in grades 7 to 12 from four middle schools in L City and Y City, Sichuan Province, China, in January 2023 as participants. Cluster sampling was conducted at the class level with two classes selected from each grade in the four schools, resulting in a total sample of 1320 adolescents. A paper-based questionnaire survey was administered in a group setting. Prior to the administration of the tests, informed consent was obtained from all participants. A total of 1320 questionnaires were distributed; after excluding invalid responses, 1277 valid questionnaires were obtained, accounting for 96.74% of the total. The study was approved by the Human Research Ethics Committee of Yibin University (approval number: 2022042101Y).

In the valid sample, the average age of the adolescents was 14.34 years (SD = 1.72), including 678 (53.1%) males and 599 (46.9%) females. There were 211 (16.5%) students in grade 7, 245 (19.2%) in grade 8, 255 (20.0%) in grade 9, 194 (15.2%) in grade 10, 183 (14.3%) in grade 11, and 189 (14.8%) in grade 12. There were 193 (15.1%) only children and 1084 (84.9%) children with siblings.

Measurements

Academic pressure questionnaire.

This study used the Academic Pressure Questionnaire developed by Wang et al. 29 The questionnaire consists of 35 items covering four dimensions of academic pressure: academic performance pressure, setback pressure, external environmental pressure, and competitive pressure. The behavioral measurement frequency of the participants was scored on a 5-point Likert scale, with (0 = Never, 1 = Occasionally, 2 = Sometimes, 3 = Often, and 4 = Always). After reverse-scoring transformation, higher scores indicated higher levels of academic pressure. In this study, Cronbach’s α for this scale was 0.96, and the KMO and Bartlett’s test values were 0.97, indicating good reliability and validity for the scale.

Child and Adolescent Social Support Scale

This study used the Chinese version of the Child and Adolescent Social Support (CASS) scale, which was revised by Luo, Chen, and Mu. 30 The revised scale consists of five subscales with a total of 60 items. The peer support subscale is a subscale of the CASS scale, consisting of 12 items. The behavioral measurement frequency of the participants was scored on a 5-point Likert scale (0 = Never, 1 = Occasionally, 2 = Sometimes, 3 = Often, and 4 = Always). After reverse-scoring transformation, higher scores indicated lower levels of social support. In this study, Cronbach’s α coefficient for this scale was 0.96, and the KMO and Bartlett’s test values were 0.97, indicating good reliability and validity for the scale.

Social Connectedness Scale

The Social Connectedness scale, revised by Fan et al, 31 was used to measure the degree of social connectedness. It comprises 20 items across three dimensions: sense of integration, sense of acceptance, and life involvement. Participants rated each item on a five-point Likert scale (0 = never, 1 = occasionally, 2 = sometimes, 3 = often, and 4 = always). After reverse-scoring transformation, the higher the score, the lower the social connectedness. In this study, Cronbach’s α was 0.92, and the KMO and Bartlett’s test values were 0.95, indicating good reliability and validity.

Loneliness Scale

A revised version of the “Adolescent Loneliness Scale” developed by Zou, 32 was used to measure adolescent loneliness. The scale consists of 21 items. Participants were required to rate their agreement with each item. Each item was scored on a 5-point Likert scale (1 = Never, 2 = Occasionally, 3 = Sometimes, 4 = Often, and 5 = Always). After reverse-scoring transformation, higher scores indicated a stronger sense of loneliness. In this study, Cronbach’s α coefficient for this scale was 0.93, and the KMO and Bartlett’s test values were 0.94.

Method of Analysis

The reliability and validity of the questionnaire were assessed using SPSS software (version 23.0; IBM Corp., Armonk, NY, USA). Descriptive statistics and correlation analyses were conducted on the research variables. Polynomial regression and response surface analyses were performed using R language. The important features of the three-dimensional response surface were estimated, and significance tests were conducted. In addition, a three-dimensional response surface graph was plotted.

The polynomial regression analysis was used to test a set of linear and nonlinear equations derived from the regression model. 33 , 34 The independent variables in this model included academic stress (XX) and peer support (HY) as well as their squared and interaction terms. This method of analysis was used to examine the independent, consistency, and differentiation effects (ie, inconsistent effects) of the two independent variables on the dependent variable. The model was constructed using a quadratic polynomial regression as follows: GD = b0 + control variables + b1(XX) + b2(HY) + b3(XX)^2 + b4(XX) × (HY) + b5(HY)^2 + Gender + Age + e. Here, GD represented the dependent variable, XX and HY were the two independent variables, b0 was the intercept, b1–b5 were the non-standard regression coefficients, gender and age were control variables, and e represented the error term. The analysis process in this study mainly involved three steps.

Step 1 involved conducting the polynomial regression analysis. 34 , 35 First, the predictor variables XX and HY were normalized and the ratio of sample consistency or inconsistency in the direction of XX and HY was examined 35 to validate the suitability of the polynomial regression analysis. Second, the control and independent variables XX and HY were entered into the regression equation to test the linear effects of XX and HY on the dependent variable (GD). Finally, the interaction term (XX × HY) and squared terms ((XX)^2 and (HY)^2) were included in the equation to test the curve relationship and interaction effects.

Step 2 involved the construction of a three-dimensional response surface based on the results of the polynomial regression analysis. 33 The regression coefficients (b1–b5) were transformed into parameters (a1–a5) for response surface analysis. 36 The analysis of data features, such as the stationary point of the response surface, (in)consistency lines, and the relationship between the first principal axis and the a1–a5 parameters, was used to interpret the results. 33 , 36

Step 3 involved evaluating the direct and indirect effects of the mediation model between XX and HY in consistent and inconsistent matching pairs using a block variable. 34 , 35 First, the five polynomials (XX, HY, (XX)^2, (XX) × (HY), and (HY)^2) were combined into a block variable. The block variable was then used as the independent variable to test the matching (consistency or inconsistency) of XX–HY and its impact on loneliness (GD) through the social connectedness (SL) hypothesis. The PROCESS plugin in SPSS was used, and bootstrap resampling was performed 5000 times to estimate the 95% confidence interval of the effect values and to test the mediation effect. 37

Descriptive Statistical and Correlation Analyses

The statistical results of the mean, standard deviation, and correlation matrix of each variable are shown in Table 1 using descriptive statistics and correlation analysis. The results showed no significant correlations between sex, age, social connectedness, and loneliness among adolescents (Rs = −0.043 to 0.036, p > 0.05). However, there were significant positive correlations among academic stress (XX), peer support (HY), social connectedness, and loneliness (Rs = 0.314–0.817, p < 0.001). Thus, Hypotheses 1 and 2 were supported. The loneliness score among adolescents in this study was 25.16 ± 16.27, which is at a lower level (with a maximum score of 82.0 points). However, 212 adolescents (16.60%) scored higher than the median score of 42.0.

Descriptive Statistics and Correlation Analysis (N = 1277)

Notes : Statistically significant values ** p < 0.01, and *** p < 0.001; Gender: 0 for Boy and 1 for Girl; XX = academic pressure; HY = peer support; SL = social connectedness; GD= loneliness.

The results showed that the proportion of consistent cases between academic stress (XX) and peer support (HY) was 34.85% (445 participants), the proportion of cases where academic stress (XX) was greater than peer support (HY) was 32.03% (409 participants), and the proportion of cases in which academic stress (XX) was less than peer support (HY) was 33.12% (423 participants). These proportions met the analysis requirements (each category was greater than 10%) and allowed the polynomial regression analysis to be conducted.

The Effect of Academic Pressure–Peer Support Matching on Adolescents’ Social Connectedness

The impact of matching academic stress (XX) with peer support (HY) on adolescents’ social connectedness was examined using polynomial regression and response surface analyses. Table 2 presents the results of the study.

Polynomial Regression Results and Response Surface Analysis (N = 1277)

Notes : Statistically significant values * p < 0.05, ** p < 0.01, and *** p < 0.001; Gender: 0 for Boy and 1 for Girl; SL = social connectedness; GD = loneliness. The regression coefficients in the table are unstandardized regression coefficients. ΔR^2 represents the change in the model’s explanatory power after including the quadratic terms XX^2, XX×HY, and HY^2. R^2 represents the variance explained by the polynomial regression model as a whole. a1 and a2 represent the slope and curvature of the consistent line, respectively, a3 and a4 represent the slope and curvature of the inconsistent line, respectively, and a5 indicates whether the first principal axis of the surface lies on the consistent line.

According to the data in Table 2 , after controlling for gender and age, XX(b1=0.299) and HY(b2=0.524) positively predicted the social connectedness(SL) levels (p < 0.001). The significance of ΔR^2 in the polynomial model increased significantly (p < 0.001), indicating a significant relationship between the independent variables (XX–HY) and the dependent variable (social connectedness, SL) in the opposite direction (“one high and one low”). 38 In addition, the response surface significantly shifted along the inconsistent line (a5 = −0.071, p < 0.01), indicating that the first principal axis representing the response surface did not coincide with the consistent line.

The slope (a1 = 0.823, p < 0.001) and curvature (a2 = 0.053, p < 0.05) along the consistent line (XX = HY) of the response surface indicated that the dependent variable (social connectedness, SL) formed an upward concave surface along the consistency of the independent variable (XX–HY) ( Figure 1 ). In other words, the response surface first decreased along the consistent curve, reached its lowest point near the stationary point, and then increased. Compared to the “low XX–low HY” level of consistency, when the consistency level of the independent variable was “high XX–high HY”, the level of social connectedness (SL) was higher (Z-hat = 23.490, 95% CI [21.829, 25.141]). As higher scores indicate weaker peer support and social connectedness (SL) in adolescents, the social connectedness (SL) of adolescents with strong academic stress (XX) and weak peer support (HY) was weaker than that of adolescents with weak academic stress (XX) and strong peer support (HY).

Response surface analysis of academic pressure (XX) and peer support (HY) matching with social connectedness (SL).

The curvature (a4 = 0.106, p < 0.05) along the inconsistent line (XX = -HY) of the response surface indicates a concave increase from left to right ( Figure 1 ), which means that the consistency of the independent variables (XX and HY) had a negative impact on social connectedness (SL), the lowest value of which occurred within the region where HY > XX. In addition, the slope (a3 = −0.225, P < 0.001) of the inconsistent line suggests a significant difference in the level of social connectedness (SL) owing to the difference in the independent variables. When using the point selection method 39 for calculation, it was found that the level of social connectedness (SL) was lower for “high XX–low HY” than for “low XX–high HY” (Z-hat = −2.768, 95% CI [−5.104, −0.530]). Higher scores indicate weaker peer support(HY) and social connectedness (SL) in adolescents; the social connectedness (SL) of adolescents with strong academic stress (XX) and peer support (HY) was stronger than that of adolescents with weak academic stress (XX) and peer support (HY).

The Effect of Academic Pressure–Peer Support Matching on Adolescents’ Loneliness

The impact of matching academic stress (XX) with peer support (HY) on adolescents’ loneliness was examined using polynomial regression and response surface analyses. Table 2 presents the results of the study.

According to the data in Table 2 , after controlling for gender and age, XX(b1=0.250) and HY(b2=0.445) positively predicted the loneliness(GD) levels (p < 0.001). The significance of ΔR^2 in the polynomial model increased significantly (p < 0.001), indicating a significant relationship between the independent variables (XX–HY) and the dependent variable (loneliness, GD) in the opposite direction (“one high and one low”). 38 In addition, the response surface significantly shifted along the inconsistent line (a5 = −0.071, p < 0.01), indicating that the first principal axis representing the response surface did not coincide with the consistent line.

The slope (a1 = 0.796, p < 0.001) and curvature (a2 = 0.153, p < 0.001) along the consistent line (XX = HY) of the response surface indicated that the dependent variable (loneliness, GD) formed an upward concave surface along the consistency of the independent variable (XX–HY) ( Figure 2 ). Compared to the “low XX–low HY” level of consistency, when the consistency level of the independent variable was “high XX–high HY”, the level of loneliness (GD) was higher (Z-hat=26.435, 95% CI [24.442, 28.495]). As higher scores indicate weaker peer support (HY) and loneliness (GD) in adolescents, the loneliness (GD) of adolescents with strong academic stress (XX) and weak peer support (HY) was weaker than that of adolescents with weak academic stress (XX) and strong peer support (HY).

Response surface analysis of academic pressure (XX) and peer support (HY) matching with loneliness (GD).

The results of slope (a3 =−0.095, P < 0.01) and curvature (a4 = 0.066, P > 0.05) of the response surface along the inconsistency line show that the response surface presents an approximate straight line with lower left and higher right along the inconsistency line (left corner to right corner) ( Figure 2 ). That is to say, the value of loneliness (GD) varies with the degree of differentiation between academic pressure (XX) and peer support (HY). Compared with “low XX–high HY”, the level of loneliness (GD) is higher when “high XX–low HY”. That is, the greater the difference of ‘XX > HY’, the higher the level of loneliness (GD).

Mediating Effect Test

On the basis of the above analysis, we now examine the impact of the block variable (XX–HY) on adolescents’ feelings of loneliness and the mediating effect of social connectedness between the block variable (XX–HY) and adolescents’ feelings of loneliness. As polynomial regression and response surface analysis include sex and age as control variables, this study incorporated them as control variables in the equation. All variables were standardized. As shown in Figure 3 , with gender and age as control variables, the block variable (XX–HY) was the independent variable, social connectedness was the mediating variable, and adolescents’ feelings of loneliness was the dependent variable. The effect of the block variable (XX–HY) on social connectedness was 1.000 (t = 34.36, p < 0.001, 95% CI [0.943, 1.057]); the effect of social connectedness on adolescents’ feelings of loneliness was 0.691 (t = 31.77, p < 0.001, 95% CI [0.648, 0.734]); the total effect of the block variable (XX–HY) on adolescents’ feelings of loneliness was 0.262 (t = 8.36, p < 0.001, 95% CI [0.200, 0.323]); and the direct effect was 0.953 (t = 31.52, p < 0.001, 95% CI [0.894, 1.012]).

Mediating effect of social connectedness between the block variable (academic pressure–peer support) and loneliness among adolescents.

Therefore, social connectedness in adolescents was found to partially mediate the relationship between the block variable (XX–HY) and adolescents’ feelings of loneliness, with a mediation effect size of 72.51%. Hence, Hypothesis 3 is supported.

Due to the emphasis on academic achievement in the Chinese educational environment, adolescents in China generally experience high levels of academic pressure. 17 Moreover, Chinese adolescents face reduced family connections and increased academic pressure. 14 This results confirm that the stronger the academic pressure faced by adolescents, the weaker their social connectedness. 28 This result is consistent with the earlier findings, academic pressures can reduce adolescents’ level of social engagement, 40 and peer support was positively correlated with social connectedness, meaning that the stronger the level of support from friends, the stronger the social connectedness of adolescents.

In this study, academic pressure and peer support had interdependent effects on adolescents’ social connectedness. Furthermore, adolescents with high academic pressure and low peer support had weaker social connectedness than those with low academic pressure and high peer support. Moreover, the degree of adolescent social connectedness showed a concave response surface consistent with academic pressure and peer support. This indicates that, with increasing academic pressure, peer support initially has a weakening effect on the reduction of social connectedness, followed by an additional effect. This finding highlights the importance of considering both academic pressure and peer support and reveals the unique and independent impact of peer support on academic pressure and social connectedness. These results may have practical implications for the implementation of measures and programs to alleviate academic pressure and promote the development of friendships among students.

The research findings also revealed that the level of social connectedness among adolescents tends to increase in a concave shape from left to right in the mismatch of academic pressure and peer support. This means that consistency between academic pressure and peer support has a negative impact on the level of social connectedness among adolescents. Furthermore, the maximum value of social connectedness among adolescents occurs in the region where peer support is strong and academic pressure is high (HY > XX). In other words, adolescents with high academic pressure and strong peer support have stronger social connectedness than those with low academic pressure and weak peer support. This indirectly indicates that adolescents who face less academic pressure and receive effective peer support have a stronger level of social connectedness, and peer support seems to have a more prominent impact on their social connectedness. Conversely, positive peer support provides adolescents with greater coping resources, enabling them to adapt better to environmental changes 41 and thus improve their academic performance. 42

The Mediating Role of Social Connectedness in the Match Between Academic Pressure and Peer Support and Loneliness

Loneliness is a prominent issue in early adolescence; 3 however, it is currently unclear which factors are closely related to it. Our research findings suggest that social support is closely associated with feelings of loneliness among adolescents. 27 Social support is also closely related to social connectedness, serving as a protective factor against loneliness. 25 , 26 One possible explanation is that adolescents who feel lonely often report lower social skills, and these subjective negative cognitions hinder their behavior in seeking social support and connections because they perceive their functioning in social environments negatively. 43 Research has shown that academic pressure has a unique relationship with feelings of loneliness. 16 Greater academic pressure is associated with stronger feelings of loneliness, and in turn, loneliness negatively affects academic pressure. 14

Furthermore, after examining the multivariate effects of academic pressure and friend support on feelings of loneliness, social connectedness, academic pressure and loneliness were found to be positively correlated. Peer support and social connectedness scores increased, indicating lower levels of peer support and social connectedness among adolescents. This confirms that the higher the level of peer support and social connectedness among adolescents and the greater the academic pressure they face, the stronger their feelings of loneliness.

The results also showed that social connectedness mediated the relationship between academic pressure and peer support matching and feelings of loneliness among adolescents, with a mediation effect size of 72.51%. This indicates that the level of social connectedness among adolescents has a significant mediating effect between the matching of academic pressure and peer support and feelings of loneliness. This study is the first to focus not only on the specific effects of academic pressure, friend support, and social connectedness on feelings of loneliness but also on the associations and differential effects among these factors. Doing so not only confirmed the positive role of more social connections in facilitating friend interactions and communication, and reducing feelings of loneliness 14 but also validated the view that positive social connections are beneficial for the well-being of adolescents who experience loneliness due to increased academic pressure. 24

The main contribution of this study is its use of polynomial regression combined with response surface methodology to reveal the mechanism underlying the joint influence of academic pressure and peer support on social connectedness and feelings of loneliness among adolescents.

Although this study provides new insights, its research design still has some limitations. First, the sampling limitations make it difficult to generalize from the research findings, as the sample size of four secondary schools in two cities is relatively small compared to a national sample. Second, this study focused on junior high and high school students, and it is not known whether the research findings could be replicated. Finally, this was a cross-sectional study, and further longitudinal research data are needed to examine the practical and theoretical effects of social connectedness intervention practices for preventing and intervening in adolescent loneliness.

Acknowledgments

Thanks to the administrators and class teachers of middle schools in Luzhou City and Yibin City, as well as the participants and their parents for their active cooperation, whose help enabled the smooth development of this study.Meanwhile, we would like to thank Yibin University, Hechi University and other institutions for their full support in ethical review, research and coordination.

Funding Statement

This study was funded by the Key Project of Rural Community Governance Research Center of Sichuan Province, China(SQZL2021A02).

Declaration of AI-Assisted Technologies in the Writing Process

During the preparation of this work the author(s) used Chat AI in order to proofread the language. After using this tool, the author(s) reviewed and edited the content as needed and takes full responsibility for the content of the publication.

Data Sharing Statement

All data generated or analysed during this study are included in this published article.

Ethical Approval and Consent to Participate

This study and its research programs were approved by the Ethics Committee of Human Research Ethics Committee of Yibin University, China (2022-04-21-01Y). All methods were carried out in accordance with the Declaration of Helsinki and approved by the aforementioned ethics committee. All participants were informed about the contents of the survey and obtained their consent, as well as the informed consent of the participants’ parents or legal guardians and the class teacher.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

The authors of this study declare no conflict of interest and that the study has not been submitted for publication anywhere else.

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Exploring the Link Between Academic Stress and Mental Health in College Students

College students have experienced unique challenges in adjusting to disruptions associated with the COVID-19 pandemic, such as displacement from the traditional university setting and the abrupt shift to remote learning. 1 Even before the pandemic, however, it was well-known that this population faces substantial stress related to the college experience, including the transition to independent living and changes in peer relationships. In addition, overwhelming academic demands represent a significant source of distress for many college students. 

In a study published in Frontiers in Psychology , Barbayannis et al examined the relationship between perceived levels of academic stress and mental well-being among 843 college students (78.5% women; 66.4% White) in the United States. 2 Scores on the Perception of Academic Stress Scale (PAS) and the Short Warwick-Edinburgh Mental Well-Being Scale (SWEMWBS) were significantly correlated (r=0.53; P <.001) and showed an association between worse academic stress and poor mental well-being in all students surveyed.

Based on SWEMWBS scores, nonbinary students demonstrated the highest levels of academic stress and worst mental health across the sample, while men showed the lowest academic stress levels and highest mental well-being. PAS scores revealed higher levels of both academic stress and COVID-related stress among women and nonbinary students compared to men. 

Second-year college students demonstrated higher academic stress and worse psychological well-being compared to students in other years of study, which may be due in part to “this group taking advanced courses, managing heavier academic workloads, and exploring different majors,” the authors wrote.

According to study co-author Xue Ming, MD, PhD, professor of neurology at Rutgers New Jersey Medical School in Newark, the potential reasons for the observed impact of academic stress on college students’ mental health include “ranking systems, peer pressure, global competition in the job market, and parental and societal demands regarding grades,” among others. “Colleges are perceived by some as a competition stage and less of pure learning environment,” she said. 

These findings align with those from other recent research, including a 2022 study showing that academic stress was a significant predictor of anxiety (β=0.247, t=5.462; P <.001) among college students in China. 3 Other studies have demonstrated links between various sources of stress and the risk for mental health disorders in college students.

In 2020, results of the World Health Organization World Mental Health Surveys International College Student Initiative showed a significant dose-response relationship between the degree of perceived stress in each of 6 life areas (health, finances, family relationships, romantic relationships, work and school relationships, and problems experienced by loved ones) and higher 12-month odds of at least 1 of 6 mental health disorders (major depressive disorder, generalized anxiety disorder, panic disorder, bipolar disorder, drug use disorder, and alcohol use disorder) in first-year college students (n=20,842) from 24 universities in 9 countries. 4

Additionally, estimates of population attributable risk proportions indicated that targeted stress prevention interventions may eliminate up to 80% of the prevalence of the disorders observed in the study. 4

“Awareness is paramount in implementing help for these students,” Dr Xue said. “For those at higher risk, individualized counseling and stress reduction strategies are needed.” Helpful strategies may include peer support groups and training in mindfulness skills. 5

Results of another study published in 2022 suggest that resources aimed at improving time management and self-regulation skills may reduce academic stress in college students , and findings from a 2018 study support the utility of a social-emotional program to improve psychological well-being in this population. 1,6

We interviewed clinical psychologist Jenny C. Yip, PsyD, ABPP, clinical assistant professor of psychiatry at the Keck School of Medicine of the University of Southern California and founder of the Renewed Freedom Center for the treatment of anxiety disorders, to learn more about the effects of academic stress on the mental health of college students and how clinicians, schools, and parents can best support these individuals.

What are believed to be the reasons why academic stress has such as significant impact on college students’ mental health, as found by Barbayannis et al and other researchers?

Dr Yip: Being a student has never been more difficult because of the increased demand for kids to be the most perfect that they can be. Many parents have the expectation that their kids will strive for perfection or will perform perfectly, and that’s just not realistic. Kids know that it’s much more difficult today to get into a university than it’s ever been. There’s more demand and less supply, and therefore, the competition is very anxiety-provoking. On top of that, a lot of kids go into freshman year feeling unprepared to be independent, which has a lot to do with how we’re parenting our children. With helicopter parenting, we’re not giving our children the same opportunities they had in the past to solve their own problems, to find their own solutions. Therefore, they don’t feel capable of doing that on their own when they enter college.    Socially, our kids are also very underprepared to engage with others independently due to the dependence on digital devices to communicate.

What might be the reasons for the greater impact of this stress on nonbinary students and women in particular?

Dr Yip: We are living in a world today where everyone is adjusting to gender neutrality. Someone who is nonbinary will have a taller order of struggle to overcome. Women traditionally have had a glass ceiling. Research has demonstrated that teachers pay more attention to men than women. On top of that, young women who enter college also have the added concern of sexual harassment and assault on campus. For most female students, this is the first time they’re living in a co-ed environment without parental presence for more than just a week or 2 at summer camp. That presents new stressors for those who identify as women.

What are recommendations for mental health professionals to help reduce the impact of academic stress on the mental health of patients who are college students?

Dr Yip: As a mental health professional, I suggest helping the student adjust to independent living. Begin practicing assertive communication so that they can advocate for themselves and problem-solve for the challenges that will come up, whether it’s with their roommates, classmates, or professors. Too often kids today are not advocating for themselves. They’re responding passive-aggressively and avoiding uncomfortable situations. For mental health professionals, the number 1 priority is to help patients practice assertive communication skills to help them feel independent by having agency to speak up for themselves in a way that is conducive to problem solving.

What broader measures are needed to help minimize the effects of academic stress on college students?

Dr Yip: Number 1, parents and schools should start preparing college students for the demand and the transition to college before college even starts. I see a lot of high schools doing that now because of the high attrition rate of incoming freshmen. There are college campuses offering more mental health support than before, but we need to start much earlier than when a student becomes a freshman. Conversations need to be had even before a child starts elementary school. It’s a systemic adjustment.   Mental health adjustments need to be incorporated in colleges, especially with incoming freshmen. It should be mandatory that each incoming student meets with a mental health professional on a regular, consistent basis to evaluate their emotional adjustment. It’s often required for a new college student to meet with a college counselor to be sure they’re taking the coursework that is conducive to them. Why is that not being done with each student’s mental health?

 Jenny C. Yip, PsyD, ABPP is a clinical assistant professor of psychiatry at the Keck School of Medicine of the University of Southern California and founder of the Renewed Freedom Center. Resource http://www.renewedfreedomcenter.com

References:

• von Keyserlingk L, Yamaguchi-Pedroza K, Arum R, Eccles JS. Stress of university students before and after campus closure in response to COVID-19 . J Community Psychol . 2022;50(1):285-301. doi:10.1002/jcop.22561
• Barbayannis G, Bandari M, Zheng X, Baquerizo H, Pecor KW, Ming X. Academic stress and mental well-being in college students: correlations, affected groups, and COVID-19 . Front Psychol . 2022;13:886344. doi:10.3389/fpsyg.2022.886344
• Yang Y, Yang P. Effect of college students’ academic stress on anxiety under the background of the normalization of COVID-19 pandemic: the mediating and moderating effects of psychological capital . Front Psychol . 2022;13:880179. doi:10.3389/fpsyg.2022.880179
• Karyotaki E, Cuijpers P, Albor Y, et al. Sources of stress and their associations with mental disorders among college students: results of the World Health Organization World Mental Health Surveys International College Student Initiative . Front Psychol . 2020;11:1759. doi:10.3389/fpsyg.2020.01759
• Smit B, Stavrulaki E. The efficacy of a mindfulness-based intervention for college students under extremely stressful conditions . 2021;12(12):3086-3100. doi:10.1007/s12671-021-01772-9
• Stocker SL, Gallagher KM. Alleviating anxiety and altering appraisals: social-emotional learning in the college classroom. College Teaching . 2019;67(1):23-35. doi:10.1080/87567555.2018.1515722

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ACADEMIC STRESS AND ACADEMIC PERFORMANCE OF BEEd STUDENTS OF THE COLLEGE OF TEACHER EDUCATION IN OCCIDENTAL MINDORO STATE COLLEGE A THESIS PROPOSAL

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