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The Burden of University Life: Stress, Anxiety, and Depression in
Undergraduates
Md. Shahadat Hossain*
Lecturer, Department of Psychology, Gopalganj Science and Technology University, Gopalganj-8100, Bangladesh
*Corresponding Author
DOI : https://doi.org/10.51583/IJLTEMAS.2025.14030007
Received: 17 March 2025; Accepted: 21 March 2025; Published: 29 March 2025
Abstract: Mental health concerns among university students have been widely recognized as a growing issue, particularly in
relation to stress, anxiety, and depression. This study examines the burden of stress, anxiety, and depression among undergraduate
students at Gopalganj Science and Technology University, Bangladesh. A cross-sectional survey design was used, with 372
students participating through convenience sampling. The study employed the Bangla version of the Depression Anxiety Stress
Scale-21 (DASS-21) to measure psychological distress. Data were collected using self-reported questionnaires and analyzed using
SPSS (version 27.0). Descriptive statistics were computed, and Pearson’s correlation, independent sample t-tests, one-way
ANOVA, and hierarchical regression analysis were conducted to explore associations and predictive relationships among
variables. Results revealed significant positive correlations between stress, anxiety, and depression. Gender differences were
observed, with female students reporting higher levels of stress, anxiety, and depression compared to males. Additionally, a
significant increase in psychological distress was noted across academic years, with fourth-year students exhibiting the highest
levels of stress, anxiety, and depression. Post-hoc analysis indicated that these differences were particularly pronounced between
first- and fourth-year students. Hierarchical regression analysis demonstrated that stress significantly predicted depression,
accounting for a substantial proportion of the variance. When anxiety was added, the explanatory power increased, highlighting
the combined impact of stress and anxiety on depressive symptoms. These findings underscore the need for targeted mental health
interventions for university students, particularly those in higher academic years and female students. Addressing stress and
anxiety through proactive support strategies could mitigate their impact on depression and enhance students' overall well-being.
Keywords: stress, anxiety, depression, university students, gender differences, academic year
I. Introduction
The evolving dynamics of the higher education environment, marked by escalating competition and intricate academic
expectations, have engendered a notable escalation in the incidence of psychological distress, specifically stress, anxiety, and
depression, among undergraduate student populations (Fauzi et al., 2021). The confluence of rigorous academic curricula,
financial constraints, social pressures, and uncertainties regarding future career prospects collectively contribute to a heightened
vulnerability to mental health challenges within this demographic (Fauzi et al., 2021). Specifically, the transition into tertiary
education represents a critical juncture in the lives of young adults, where a substantial proportion encounters elevated levels of
stress, anxiety, and depression (Parsons et al., 2021; Yang et al., 2022). In fact, a recent study revealed that a significant
percentage of college students, approximately 34.5%, experience considerable stress, while reports from Australia indicate that an
overwhelming majority, around 83.2%, of tertiary education students feel stressed, with 79% reporting anxiety, 66% experiencing
high psychological distress, and over half suffering from sleep disturbances (Parsons et al., 2021).
Amidst these concerns, gender-related disparities in the manifestation and experience of stress, anxiety, and depression among
undergraduates warrant careful consideration. Women, for example, often exhibit a higher prevalence of depression, potentially
attributable to a complex interplay of biological, psychological, and sociocultural factors (Thomas & Segal, 2006). Specifically,
women not only report a higher incidence of daily stressors but also demonstrate a greater likelihood of having a history of
depression, which can amplify the impact of stress on the onset of depressive episodes (Thomas & Segal, 2006). However, some
studies indicate that female students exhibit elevated anxiety and stress scores compared to their male counterparts (Marzouqi et
al., 2022). Female students' unique circumstances and social status render them particularly susceptible to mental health disorders
such as depression and anxiety (Talaie et al., 2024). Research suggests that being female can increase the likelihood of
experiencing mental illnesses by up to four times (Talaie et al., 2024).
Beyond gender differences, the academic year in which a student is enrolled also plays a critical role in influencing stress,
anxiety, and depression levels. Some studies suggesting that first-year and second-year students exhibit higher levels of
depression, anxiety, and stress compared to their more senior peers (Mofatteh, 2020). This heightened vulnerability among
underclassmen may be attributed to the challenges associated with transitioning to a novel academic environment, navigating
unfamiliar social dynamics, and adapting to the rigors of collegiate coursework (Yang et al., 2022). In contrast, research indicates
that final-year students may encounter heightened stress and anxiety levels due to the convergence of academic culmination,
career planning, and the anticipation of entering the professional sphere, necessitating adept adaptation to novel challenges and
responsibilities (Harith et al., 2022). These findings support the fact that as students progress through their academic careers, they
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
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face different stressors and challenges that can affect their mental health (Fauzi et al., 2021; Lee et al., 2021; Radeef & Faisal,
2017).
Given these academic and demographic factors, it becomes essential to understand how stress and anxiety contribute to the
development of depression among undergraduate students. Prospective, longitudinal investigations have consistently revealed that
heightened levels of both stress and anxiety function as salient predictors of subsequent depressive episodes, highlighting the
critical need for proactive identification and management of these psychological vulnerabilities (Lee et al., 2021). Empirical
investigations have consistently demonstrated that heightened levels of both stress and anxiety function as salient predictors of
depressive symptomology within undergraduate populations (Fauzi et al., 2021; Radeef & Faisal, 2017; Wells & Fisher, 2016).
Stress and anxiety are significant predictors of the onset and severity of depressive symptoms, with chronic or unmanaged stress
and anxiety disorders substantially elevating the risk of developing clinical depression (Wells & Fisher, 2016). Specifically, the
escalating demands of academic coursework, coupled with the pervasive anxieties surrounding academic performance and future
career prospects, can precipitate a cascade of negative cognitive and emotional responses, thereby augmenting the risk of
depressive disorders (Fauzi et al., 2021).
Objectives
1. To examine the impact of gender on the mental health challenges faced by students.
2. To explore the impact of gender and academic year on the mental health challenges faced by students.
3. To analyze the predictive role of stress and anxiety in the development of depression among undergraduates.
II. Methodology
Sample
The study included a total of 372 participants from Gopalganj Science and Technology University, Bangladesh. Among them, 205
(55.1%) were female, and 167 (44.9%) were male, with ages ranging between 19 and 25 years (M = 22 years, SD = 2.16), with
academic year 111 were in the first year (29.8%), 85 in the second year (22.8%), 86 in the third year (23.1%), and 90 in the fourth
year (24.2%). The participants were selected using a convenience sampling method.
Study design
A Cross-sectional survey design was used for students.
Measures
Age, gender and academic year were collected as demographic information of the participants. This study utilized three measures,
The Depression Anxiety Stress Scale. The Bangla version of the DASS-21 (Alim et al., 2014) had been developed by Lovibond
et al. (1995) was used. The scale consists of 21 items that are evaluated using a four-point Likert scale, ranging from 0 (did not
apply to me at all) to 3 (applied to me very much). The DASS-21 questionnaire consists of specific items that evaluate depression
(items 3, 5, 10, 13, 16, 17, 21), anxiety (items 2, 4, 7, 9, 15, 19, 20), and stress (items 1, 6, 8, 11, 12, 14, 18). The total score for
each category (depression, anxiety, and stress) should be doubled. In this study the Bangla version Cronbach's alpha for
depression, anxiety, and stress were 0.81, 0.83, and 0.85, respectively. The overall reliability (alpha) was .91.
Procedure
Data was gathered using a self-reported questionnaire that comprised demographic questions and the Depression Anxiety Stress
Scale-21 (DASS-21). Prior to completing the survey, participants received clear instructions. The questionnaires were distributed
in a classroom environment, ensuring that participants had sufficient time to provide their responses.
Statistical analysis
Collected data were statistically analyzed by using SPSS (version 27.0). First of all, we computed the mean, standard deviation,
and range of age for descriptive statistics of the study. Second, to examine the association between stress, anxiety and depression
Pearson’s correlation analysis was conducted. Comparisons of variables between the two groups (male vs female) were analyzed
by independent sample t test. Third, to compare data obtained from four academic year of students, one-way ANOVA and
Bonferroni post hoc tests were conducted. Finally, to calculate predicting effect hierarchical regression analysis was conducted.
Ethical Considerations
Participants were provided with details regarding the study's purpose, their ability to withdraw at any point, and the assurance of
confidentiality in their responses. Prior to participation, written informed consent was obtained. To maintain anonymity, no
personally identifiable information was collected.
III. Results and Discussion
Before applying inferential statistics, the normality of the collected data on internet addiction, self-esteem and depression scores
was checked. Regarding the Shapiro-Wilk and Kolmogorov-Smirnov test, p values are above .05 indicating the variables are
normally distributed (Goodman, 1954). Pearson-product moment correlation revealed significant positive association between all
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three variables. The highest correlation was found between stress and depression (r = .72, p < .01), indicating that higher levels of
stress are strongly associated with greater depressive symptoms. Stress also showed a significant positive correlation with anxiety
(r = .70, p < .01), suggesting that individuals experiencing higher stress levels tend to have increased anxiety. Additionally,
anxiety and depression were significantly correlated (r = .71, p < .01), reflecting the close relationship between these two mental
health variables. These results highlight the strong interconnection among stress, anxiety, and depression.
Table 1 Gender Differences in Stress, Anxiety, and Depression Among University Undergraduates
Female
Male
Variables
M
SD
M
SD
t (370)
p
Cohen's d
Stress
22.17
9.62
17.39
8.04
-5.123
<.001
0.53
Anxiety
17.69
9.79
12.85
7.64
-5.220
<.001
0.54
Depression
20.63
10.15
13.68
6.86
-7.563
<.001
0.79
Table 1 presents gender differences in stress, anxiety, and depression levels among university undergraduates. The results indicate
that females reported significantly higher stress levels (M = 22.17, SD = 9.62) than males (M = 17.39, SD = 8.04), t (370) = -
5.123, p < .001, with a moderate effect size (Cohen’s d = 0.53). Similarly, anxiety levels were significantly higher among females
(M = 17.69, SD = 9.79) compared to males (M = 12.85, SD = 7.64), t (370) = -5.220, p < .001, with a moderate effect size
(Cohen’s d = 0.54). Depression exhibited the largest gender difference, with females scoring significantly higher (M = 20.63, SD
= 10.15) than males (M = 13.68, SD = 6.86), t (370) = -7.563, p < .001, and a large effect size (Cohen’s d = 0.79). The finding that
female students report significantly higher levels of stress, anxiety and depression is consistent with research indicating that
females are more prone to psychological alterations that can result in conditions such as anxiety, insomnia, depression, or post-
traumatic stress disorder (Rodríguez-Besteiro et al., 2021). This observed pattern may be attributed to a complex interplay of
factors, encompassing hormonal influences, differences in coping mechanisms, and differential exposure to social stressors (Wells
& Fisher, 2016). Several theoretical frameworks offer potential explanations for these observed gender differences. From a
biological perspective, hormonal fluctuations associated with the menstrual cycle, pregnancy, and menopause may contribute to
increased vulnerability to mood disorders in women (Wells & Fisher, 2016). From a psychological standpoint, cognitive theories
suggest that women may exhibit distinct cognitive styles characterized by heightened self-criticism, rumination, and negative
attributional biases, which exacerbate the experience of stress, anxiety, and depression. (Thomas & Segal, 2006). Social role
theory posits that societal expectations and gender norms may contribute to differential experiences of stress and emotional
expression between men and women (Wells & Fisher, 2016).
Table 2 One-way ANOVA for Stress, Anxiety, and Depression by Academic Year
First Year
Second Year
Third Year
Fourth Year
Variables
M
SD
M
SD
M
SD
M
SD
F(3, 368)
η²
Post-Hoc
Stress
12.32
7.80
18.89
7.64
24.21
5.72
26.58
7.70
75.32***
.38
1<2<3<4
Anxiety
10.74
7.68
15.36
9.17
16.49
7.69
20.62
9.40
23.04***
.16
1<2<3<4
Depression
12.32
8.16
17.29
8.60
19.60
8.32
22.11
9.82
23.09***
.16
1<2<3<4
Note. Homogeneity of variances tested by Levene’s test (p > 0.05). Partial eta-squared (η²) indicates the effect size. ***p < .001
Results of the one-way ANOVA are shown in Table 2. The ANOVA for stress, anxiety, and depression showed significant
differences among academic year groups. For stress, significant differences were found (F (3, 368) = 75.32, p < .001) with a large
effect size (η² = 0.38). Similarly, anxiety (F (3, 368) = 23.04, p < .001) and depression (F (3, 368) = 23.09, p < .001) also
exhibited significant differences, both with large effect sizes (η² = 0.16). Post-Hoc comparisons using Tukey HSD for stress
showed significant differences were found between all academic years except between third- and fourth-year students (p > .001).
The largest mean difference was between first- and fourth-year students (-14.25, p < .001). For anxiety significant differences
were found between first- and all other years (p < .001), as well as between fourth- and third-year students (p < .05). No
significant difference was observed between second- and third-year students (p > .001). For depression significant differences
were found between first- and all other years (p < .001), and between second- and fourth-year students (p < .05). The difference
between third- and fourth-year students was not statistically significant (p > .001). These results indicate a trend of increasing
stress, anxiety, and depression across academic years, with the highest levels reported by fourth-year students. The largest
differences were observed between first- and fourth-year students across all three psychological variables. In similar vein, the
escalating trends of stress, anxiety, and depression observed across successive academic years within the university student
population illuminate the dynamic interplay of factors influencing mental well-being during this critical developmental period
(Yang et al., 2022). The progression from first year to fourth year is marked by increasing academic demands, greater pressures
related to career planning and future prospects, and the culmination of social and personal challenges, all of which contribute to a
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heightened vulnerability to psychological distress (Idaris et al., 2022). This aligns with finding that significant differences in
stress, anxiety, and depression levels across academic years, underscores the dynamic interplay between academic demands,
personal development, and mental health (Mofatteh, 2020). Specifically, first-year students may experience stress and anxiety
related to adjusting to university life, navigating new social environments, and managing academic workloads for the first time,
whereas senior students face heightened stress due to impending graduation, career prospects, and financial concerns (Harith et
al., 2022). Furthermore, the significant differences observed between specific academic years, as revealed by post-hoc
comparisons, emphasize the varying impact of academic milestones and transitional periods on student mental health (Chen et al.,
2022).
Table 3 Hierarchical Regression Analysis Predicting Depression
Variable
B
95% CI
SE B
β
R²
ΔR²
LL
UL
Model 1
.51
.51***
Constant
2.83***
1.22
4.45
0.82
Stress
0.73***
0.66
0.81
0.04
.72***
Model 2
.60
.09***
Constant
2.15**
0.68
3.62
0.75
Stress
0.44***
0.34
0.53
0.05
.43***
Anxiety
0.43***
0.33
0.52
0.05
.41***
Note. CI = confidence interval; LL = lower limit; UL = upper limit. **p < .01, ***p < .001
Table 3 presents the impact of stress and anxiety on depression among participants. In Model 1, the R² value of .51 indicates that
stress alone explained 51% of the variance in depression, with F (1, 370) = 388.14, p < .001. The results show that stress
significantly predicted depression (β = .72, p < .001). In Model 2, the R² value increased to .60, revealing that stress and anxiety
together explained 60% of the variance in depression, with F (2, 369) = 276.39, p < .001. In this model, stress remained a
significant predictor (β = .43, p < .001), while anxiety also significantly predicted depression (β = .41, p < .001). The ΔR² of .09
indicates a 9% increase in variance explained between Models 1 and 2, with ΔF (1, 369) = 80.86, p < .001. Extensive research has
demonstrated the significant relationship between stress, anxiety, and depression. Stress has been identified as a primary predictor
of depressive symptoms, emphasizing its substantial role in influencing mental health outcomes (Barnaby, 2015). Prior studies
confirm that heightened stress levels are strongly associated with increased depression, aligning with well-documented evidence
on stress’s detrimental effects on psychological well-being (Rodgers et al., 2021). Additionally, anxiety has been shown to
contribute uniquely to depression, further enhancing the explanatory power of predictive models (Kircanski et al., 2016). The
interplay between stress and anxiety highlights the multifaceted nature of depression, suggesting that both factors should be
considered in understanding its etiology (Hewitt et al., 1992).
IV. Conclusion
The findings highlight the intricate relationship between stress, anxiety, and depression among university students. Gender
differences indicate that female students report significantly higher psychological distress compared to males. Additionally,
academic year plays a crucial role, with stress, anxiety, and depression levels increasing progressively from first to fourth year.
Hierarchical regression analysis confirms stress as a primary predictor of depression, with anxiety further contributing to its
variance. These results emphasize the need for targeted interventions to support students' mental health. Future research should
explore additional factors influencing psychological well-being, such as coping mechanisms and social support. Addressing these
concerns can enhance academic success and overall well-being, ensuring a more supportive university environment.
Acknowledgement
The author expresses gratitude towards all those who actively engaged in the study and contributed to the efficient completion of
the research.
References
1. Alim, S. M., Kibria, S. M., Islam, M. J., Uddin, M. Z., Nessa, M., Wahab, M. A., & Islam, M. M. (2014). Translation of
DASS 21 into Bangla and validation among medical students. Bangladesh Journal of Psychiatry, 28(2), 67–70.
2. Barnaby, B. (2015). Clinical handbook of psychological disorders: A step-by-step treatment manual. Occupational
Medicine, 65(9), 766. Oxford University Press. https://doi.org/10.1093/occmed/kqv128
3. Chen, N.-H., Liu, L.-M., Liu, H., Hsieh, C., & Tsai, C.-C. (2022). Psychological distress among first-year health science
students in Taiwan. Heliyon, 8(8). Elsevier BV. https://doi.org/10.1016/j.heliyon.2022.e10121
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
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4. Fauzi, M. F., Anuar, T. S., Teh, L. K., Lim, W. F., James, R. J., Ahmad, R., Mohamed, M., Bakar, S. H. A., Yusof, F. Z.
M., & Salleh, M. Z. (2021). Stress, anxiety and depression among a cohort of health sciences undergraduate students:
The prevalence and risk factors. International Journal of Environmental Research and Public Health, 18(6), 3269.
Multidisciplinary Digital Publishing Institute. https://doi.org/10.3390/ijerph18063269
5. Harith, S., Backhaus, I., Mohbin, N., Ngo, H., & Khoo, S. (2022). Effectiveness of digital mental health interventions for
university students: An umbrella review [Review of Effectiveness of digital mental health interventions for university
students: An umbrella review]. PeerJ, 10. PeerJ, Inc. https://doi.org/10.7717/peerj.13111
6. Hewitt, P. L., Flett, G. L., & Mosher, S. (1992). The Perceived Stress Scale: Factor structure and relation to depression
symptoms in a psychiatric sample. Journal of Psychopathology and Behavioral Assessment, 14(3), 247. Springer
Science+Business Media. https://doi.org/10.1007/bf00962631
7. Idaris, R. M., Shah, N. A., Ong, M. H. A., & Abdullah, S. F. (2022). Exploring the impact of stressors on academic
performance among higher education students. European Proceedings of Multidisciplinary Sciences, 3, 225.
https://doi.org/10.15405/epms.2022.10.23
8. Kircanski, K., LeMoult, J., Ordaz, S. J., & Gotlib, I. H. (2016). Investigating the nature of co-occurring depression and
anxiety: Comparing diagnostic and dimensional research approaches [Review of Investigating the nature of co-occurring
depression and anxiety: Comparing diagnostic and dimensional research approaches]. Journal of Affective Disorders,
216, 123. Elsevier BV. https://doi.org/10.1016/j.jad.2016.08.006
9. Lee, J. M., Jeong, H. J., & Kim, S. (2021). Stress, anxiety, and depression among undergraduate students during the
COVID-19 pandemic and their use of mental health services. Innovative Higher Education, 46(5), 519. Springer
Science+Business Media. https://doi.org/10.1007/s10755-021-09552-y
10. Lovibond, S. H., & Lovibond, P. F. (1995). Manual for the Depression Anxiety & Stress Scales (2nd ed.). Sydney:
Psychology Foundation. Retrieved from
https://journals.plos.org/plosone/article/file?type=supplementary&id=info:doi/10.1371/journal.pone.0219193.s004
11. Marzouqi, A. A., Otim, M., Alblooshi, A., Marzooqi, S. A., Talal, M., & Wassim, F. (2022). State of emotional health
disorders of undergraduate students in the United Arab Emirates: A cross-sectional survey. Psychology Research and
Behavior Management, 1423. Dove Medical Press. https://doi.org/10.2147/prbm.s365012
12. Mofatteh, M. (2020). Risk factors associated with stress, anxiety, and depression among university undergraduate
students. AIMS Public Health, 8(1), 36. AIMS Press. https://doi.org/10.3934/publichealth.2021004
13. Parsons, D., Gardner, P., Parry, S., & Smart, S. (2021). Mindfulness-based approaches for managing stress, anxiety and
depression for health students in tertiary education: A scoping review [Review of Mindfulness-based approaches for
managing stress, anxiety and depression for health students in tertiary education: A scoping review]. Mindfulness, 13(1),
1. Springer Science+Business Media. https://doi.org/10.1007/s12671-021-01740-3
14. Radeef, A. S., & Faisal, G. G. (2017). Psychological distress and sources of stressors amongst medical and science
undergraduate students in Malaysia. Makara Journal of Health Research, 21(2). University of Indonesia.
https://doi.org/10.7454/msk.v21i2.6697
15. Rodgers, J., Cuevas, A. G., Williams, D. R., Kawachi, I., & Subramanian, S. V. (2021). The relative contributions of
behavioral, biological, and psychological risk factors in the association between psychosocial stress and all-cause
mortality among middle- and older-aged adults in the USA. GeroScience, 43(2), 655. Springer International Publishing.
https://doi.org/10.1007/s11357-020-00319-5
16. Rodríguez-Besteiro, S., Tornero-Aguilera, J. F., Fernández‐Lucas, J., & Clemente‐Suárez, V. J. (2021). Gender
differences in the COVID-19 pandemic risk perception, psychology, and behaviors of Spanish university students.
International Journal of Environmental Research and Public Health, 18(8), 3908. Multidisciplinary Digital Publishing
Institute. https://doi.org/10.3390/ijerph18083908
17. Talaie, M., Mohammadi, Y., & Raeisoon, M. (2024). The effects of resilience training on mental health among students.
Modern Care Journal, 21(4). https://doi.org/10.5812/mcj-143805
18. Thomas, J. C., & Segal, D. L. (2006). Comprehensive handbook of personality and psychopathology.
19. Wells, A., & Fisher, P. L. (2016). Treating depression: MCT, CBT, and third-wave therapies.
20. Yang, C., Gao, H., Li, Y., Wang, E., Wang, N., & Wang, Q. (2022). Analyzing the role of family support, coping
strategies and social support in improving the mental health of students: Evidence from post COVID-19. Frontiers in
Psychology, 13. Frontiers Media. https://doi.org/10.3389/fpsyg.2022.1064898
