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Student Well-Being in Higher Education: A Study Demands–Resources Theory Approach to Academic Stress, Workload, Institutional Support and Resources, and AI Integration

Article Number: e2025557  |  Available Online: November 2025  |  DOI: 10.22521/edupij.2025.19.557

Rawan Khaled Diabat , Mehmet Şükrü Bellibaş

Abstract

Background/purpose. Psychological well-being is a key factor in student success and a priority in global education reform, as reflected in Sustainable Development Goal 3, which promotes Good Health and Well-being. This study examines the factors influencing university students’ perceived well-being in the context of higher education in the United Arab Emirates, a context that has received less attention in higher education research despite significant government investments. Guided by the Study Demands–Resources (SDR) theory, the research examines how academic demands, institutional resources, and experiences with artificial intelligence (AI) relate to student well-being.

Materials/methods. The research used a cross-sectional, quantitative survey, collecting data from 265 university students in the UAE. The study applied descriptive statistics, correlation, and regression analyses to examine the relationships between academic demands, institutional resources, and student well-being.

Results. We found that academic workload acted as a significant demand on students, serving as the strongest predictor of stress and a significant negative predictor of well-being. Conversely, AI use emerged as a key resource, positively predicting student well-being. Other institutional resources, such as lecturer support and growth opportunities, were not significant predictors of well-being or stress. Demographic analysis showed that female students reported significantly higher wellbeing.

Conclusion. Our research showed that higher education institutions should consider AI and workload as key resource and demand factors to affect student wellbeing. As AI emerges as a critical new resource, universities are advised to adopt responsive strategies that integrate AI tools while simultaneously addressing student mental health. This could reduce the perceived workload and stress level and support wellbeing.

Keywords: Student well-being, academic stress, institutional support, SDR theory, AI in education

References

Alaila, R. F., Hamdi, Y. T., Abdullah, M. T., Abdullah, R. M., & Zyoud, S. H. (2024). Assessing mental health among students in the UAE: A cross-sectional study utilizing the DASS-21 scale. Saudi Pharmaceutical Journal, 32(4), 101987. https://doi.org/10.1016/j.jsps.2024.101987

Alalalmeh, S. O., Hegazi, O. E., Shahwan, M., Hassan, N., Alnuaimi, G. R. H., Alaila, R. F., Jairoun, A., Hamdi, Y. T., Abdullah, M. T., Abdullah, R. M., & Zyoud, S. H. (2024). Assessing mental health among students in the UAE: A cross-sectional study utilizing the DASS-21 scale. Saudi Pharmaceutical Journal, 32(4), 101987. https://doi.org/10.1016/j.jsps.2024.101987

Alenezi, M. (2023). Digital learning and digital institution in higher education. Education Sciences, 13(1), 88. https://doi.org/10.3390/educsci13010088

Aljohani, K. A., Almarwani, A. M., Tubaishat, A., Gracia, P. R. B., Natividad, M. J. B., Gamboa, H. M., & Aljohani, M. S. (2023). Nursing and health sciences students’ perspective on the functions of academic advising. SAGE Open Nursing, 9. https://doi.org/10.1177/23779608231172656

Al Marzouqi, A. M., Otim, M. E., Alblooshi, A., Al Marzooqi, S., 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, 15, 1423–1433. https://doi.org/10.2147/PRBM.S365012

Alshamsi, S., Alshamsi, D., Mohammed, K., & Khatib, M. (2025). Global perspectives on AI usage in the education sector: Insights from the UAE education system. International Journal of Technology and Systems. https://doi.org/10.47604/ijts.3221

Al-Shaer, E. A., Aliedan, M. M., Zayed, M. A., Elrayah, M., & Moustafa, M. A. (2024). Mental health and quality of life among university students with disabilities: The moderating role of religiosity and social connectedness. Sustainability, 16(2), 644. https://doi.org/10.3390/su16020644

Areepattamannil, S. (2024). Building a knowledge economy: Higher education as a catalyst for the United Arab Emirates’ visionary growth. Frontiers in Education, 9. https://doi.org/10.3389/feduc.2024.1510421

Badreya, A. (2024). Evaluating the influences on AI adoption in higher education in the UAE: Students' utilization of AI. SEEJPH, XXV(S2), 2932. https://www.seejph.com/index.php/seejph/article/view/2932/1967

Baik, C., Larcombe, W., & Brooker, A. (2019a). Enhancing student mental wellbeing: The role of universities. ERIC. https://files.eric.ed.gov/fulltext/EJ1328924.pdf

Baik, C., Larcombe, W., & Brooker, A. (2019b). How universities can enhance student mental wellbeing: the student perspective. Higher Education Research & Development, 38(4), 674–687. https://doi.org/10.1080/07294360.2019.1576596

Bakker, A. B., & Demerouti, E. (2017). Job demands–resources theory: Taking stock and looking forward. Journal of Occupational Health Psychology, 22(3), 273–285. https://doi.org/10.1037/ocp0000056

Bakker, A. B., & Mostert, K. (2024). Study demands–resources theory: Understanding student well-being in higher education. Educational Psychology Review, 36(3), 1-29. https://doi.org/10.1007/s10648-024-09940-8

Barbayannis, G., Bandari, M., Zheng, X., Baquerizo, H., Pecor, K. W., & Ming, X. (2022). Academic Stress and Mental Well-Being in College Students: Correlations, affected groups, and COVID-19. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.886344

Bayram, N., & Bilgel, N. (2008). The prevalence and socio-demographic correlations of depression, anxiety and stress among a group of university students. Social Psychiatry and Psychiatric Epidemiology, 43, 667–672. https://doi.org/10.1007/s00127-008-0345-x

Bewick, B., Koutsopoulou, G., Miles, J., Slaa, E., & Barkham, M. (2010). Changes in undergraduate students’ psychological well‐being as they progress through university. Studies in Higher Education, 35(6), 633–645. https://doi.org/10.1080/03075070903216643

Brandao De Souza, C., & Jacomuzzi, A. C. (2025). The Role of University Professors’ Emotional Competencies in Students’ Academic and Psychological Well-Being: A Systematic Review. Education Sciences15(7), 882. https://doi.org/10.3390/educsci15070882

Bryant, J., & Welding, L. (2023, February 15). College student mental health statistics. BestColleges. https://www.bestcolleges.com/research/college-student-mental-health-statistics/

Chaudhry, S., Tandon, A., Shinde, S., & Bhattacharya, A. (2024). Student psychological well-being in higher education: The role of internal team environment, institutional, friends and family support and academic engagement. PLOS ONE, 19(1), Article e0297508. https://doi.org/10.1371/journal.pone.0297508

Debolina Halder Adhya, E., Al Bastaki, E. M., Suleymanova, S., Muhammad, N., & Purushothaman, A. (2024). Utilizing open educational practices to support sustainable higher education in the United Arab Emirates. Asian Association of Open Universities Journal, 26(2), 117–134. https://doi.org/10.1108/AAOUJ-07-2023-0086

Dhanabhakyam, M., & Sarath, M. (2022). Psychological wellbeing: A systematic literature review. International Journal of Advanced Research in Science, Communication and Technology, 9(1), 1–8. https://www.ijarsct.co.in

Dollinger, S. J., Leong, F. T. L., & Nagy, D. (2022). Career development and counseling: Putting theory and research to work. Wiley-Blackwell.

Eirene Katsarou. (2021). The effect of computer anxiety and self-efficacy on L2 learners’ self-perceived digital competence and satisfaction in higher education. Journal of Education and eLearning Research, 8(2), 158-172. https://files.eric.ed.gov/fulltext/EJ1300470.pdf

Fowler, D. S. (2023). AI in higher education: Academic integrity, harmony of insights, and recommendations. Journal, 3, 129–143. https://doi.org/10.26034/fr.jehe.2023.4657

Fuller, C., Simmering, M., Atinc, G., Atinc, Y., & Babin, B. (2015). Common methods variance detection in business research. Journal of Business Research. https://doi.org/10.1016/j.jbusres.2015.12.008

Gaad, E., & Almotairi, M. (2013a). Experiences of students with disabilities enrolling in higher education. International Journal of Special Education, 28(2), 1–15. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11736105/

Gaad, E., & Almotairi, M. (2013b). Inclusive higher education in the United Arab Emirates: Will perceived knowledge of inclusive education policies influence attitudes towards learning with peers with disabilities? Frontiers in Education, 6, 793086. https://www.frontiersin.org/articles/10.3389/feduc.2021.793086/full

Garcia-Ruiz, R., Pérez-López, M., & Delgado-Caro, E. (2025). Students’ well-being in higher education: A positive psychology narrative review. Frontiers in Education. https://doi.org/10.3389/feduc.2025.1607364

Gonzo, F. (2023). The impact of digital learning technology on higher education students’ mental health. In Perspectives on enhancing learning experience through digital strategy in higher education. IGI Global. https://doi.org/10.4018/978-1-6684-8282-7.ch005

Hakanen, J. J., Bakker, A. B., & Schaufeli, W. B. (2006). Burnout and work engagement among teachers. Journal of School Psychology, 43(6), 495–513. https://doi.org/10.1016/j.jsp.2005.11.001

He, J., Wang, Q., & Lee, H. (2025). Enhancing online learning engagement: Teacher support, psychological needs satisfaction, and interaction. BMC Psychology, 13, 696. https://doi.org/10.1186/s40359-025-03016-0

Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promise and implications for teaching and learning. https://www.researchgate.net/publication/332180327_Artificial_Intelligence_in_Education_Promise_and_Implications_for_Teaching_and_Learning

Holmes, W., Bialik, M., & Fadel, C. (2021). Artificial intelligence in education: Promises and implications for teaching and learning. OECD Publishing. https://doi.org/10.1787/589b283f-en

Hu, L.-T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1–55. https://doi.org/10.1080/10705519909540118

Subramanian Iyer, S. (2024). Industrial involvement in UAE academic development. https://doi.org/10.13140/RG.2.2.29261.00484

Jagodics, B., & Szabó, É. (2023). Student burnout in higher education: A demand-resource model approach. Trends in Psychology, 31, 757–776. https://doi.org/10.1007/s43076-021-00137-4

Kayyali, M. (2024). Career development in higher education: Best practices and innovations. In B. Christiansen & A. Even (Eds.), Advancing student employability through higher education (pp. 1–19). IGI Global. https://doi.org/10.4018/979-8-3693-0517-1.ch001

Khassawneh, O., Mohammad, T., Ben-Abdallah, R., & Alabidi, S. (2022). The relationship between emotional intelligence and educators’ performance in higher education sector. Behavioral Sciences, 12(12), 511. https://doi.org/10.3390/bs12120511

Klimova, B., & Pikhart, M. (2025). Exploring the effects of artificial intelligence on student and academic well-being in higher education: A mini-review. Frontiers in Psychology, 16, 1498132. https://doi.org/10.3389/fpsyg.2025.1498132

Kohn, J. P., & Frazer, G. H. (1986). An academic stress scale: Identification and rated importance of academic stressors. Psychological Reports, 59(2), 415–426. https://doi.org/10.2466/pr0.1986.59.2.415

Lesener, T., Gusy, B., & Wolter, C. (2024). Study demands–resources theory: Understanding student well-being in higher education. Educational Psychology Review, 36(1), 92. https://doi.org/10.1007/s10648-024-09940-8

Lesener, T., Pleiss, L. S., Gusy, B., & Wolter, C. (2020). The study demands–resources framework: An empirical introduction. International Journal of Environmental Research and Public Health, 17(14), 5183. https://doi.org/10.3390/ijerph17145183

Lizarte Simón, E. J., Gijón Puerta, J., Galván Malagón, M. C., & Khaled Gijón, M. (2024). Influence of Self-Efficacy, Anxiety and Psychological Well-Being on Academic Engagement During University Education. Education Sciences, 14(12), 1367. https://doi.org/10.3390/educsci14121367

Macan, T. H., Shahani, C., Dipboye, R. L., & Phillips, A. P. (1990). College students’ time management: Correlations with academic performance and stress. Journal of Educational Psychology, 82(4), 760–768. https://doi.org/10.1037/0022-0663.82.4.760

Marks, A., Al-Ali, M., Atassi, R., Abualkishik, A., & Rezgui, Y. (2020). Digital transformation in higher education: A framework for maturity assessment. International Journal of Computer Science and Application, 11. https://www.researchgate.net/publication/348364436_Digital_Transformation_in_Higher_Education_A_Framework_for_Maturity_Assessment

Marks, A., Al-Ali, M., Atassi, R., Elkishk, A. A., & Rezgui, Y. (2021). Digital transformation in higher education: Maturity and challenges post COVID-19. In Advances in Intelligent Systems and Computing (pp. 53–70). https://doi.org/10.1007/978-3-030-68285-9_6

Mayyadah Lutfi Abdulwahhab. (2024). The impact of academic workload on the burnout of architecture students. International Journal of Intelligent Systems and Applications in Engineering, 12(22s), 1564. https://www.ijisae.org/index.php/IJISAE/article/view/6702

Misra, R., & McKean, M. (2000). College students’ academic stress and its relation to their anxiety, time management, and leisure satisfaction. American Journal of Health Studies, 16(1), 41–51.

Mokhtari, F. (2023). Fostering digital literacy in higher education: Benefits, challenges and implications. International Journal of Linguistics Literature & Translation, 6(10), 160–167. https://doi.org/10.32996/ijllt.2023.6.10.19

Olanipekun, E. A. (2015). Assessment of academic workload and its influence on the attitudes of students in NCE in Federal College of Education, Pankshin Chapter 1. Federal College of Education, Pankshin.

Pérez-Jorge, D., Boutaba-Alehyan, M., González-Contreras, A.I. et al. Examining the effects of academic stress on student well-being in higher education. Humanit Soc Sci Commun 12, 449 (2025). https://doi.org/10.1057/s41599-025-04698-y

Pineda, P., & Ashour, S. (2022). Student evaluation of teaching and student-centeredness in the Humboldtian and Emirati tribal traditions of higher education. Higher Education Research & Development, 42(7), 1732–1747. https://doi.org/10.1080/07294360.2022.2156483

Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879

Pointon-Haas, J., Waqar, L., Upsher, R., Foster, J., Byrom, N., & Oates, J. (2023). A systematic review of peer support interventions for student mental health and well-being in higher education. BJPsych open, 10(1), e12. https://doi.org/10.1192/bjo.2023.603

Richardson, Amanda et al. (2012). Thriving or just surviving? Exploring student strategies for a smoother transition to university. A Practice Report. The International Journal of the First Year in Higher Education, 3(2), 87-93. https://doi.org/10.5204/intjfyhe.v3i2.132

Russell, S., & Norvig, P. (2020). Artificial intelligence: A modern approach (4th ed.). Pearson. https://aima.cs.berkeley.edu/

Ryan, R. M., & Deci, E. L. (2017). Self-determination theory: Basic psychological needs in motivation, development, and wellness. Guilford Press.

Scherer, L. A., & Leshner, A. I. (Eds.). (2021). Mental Health, Substance Use, and Wellbeing in Higher Education: Supporting the Whole Student. National Academies Press (US). https://doi.org/10.17226/26015

Schneider, M., & Preckel, F. (2017). Variables associated with achievement in higher education: A systematic review of meta-analyses. Psychological Bulletin, 143(6), 565–600. https://doi.org/10.1037/bul0000098

Selwyn, N., & Facer, K. (2014). The sociology of education and digital technology: Past, present and future. Oxford Review of Education, 40(4), 482–496. https://doi.org/10.1080/03054985.2014.933005

Shwedeh, F., Salloum, S., Aburayya, A., Brihan, F., Elbadawi, M., Alghurabli, Z., & Al-Dabbagh, T. (2024). AI adoption and educational sustainability in higher education in the UAE. In S. Salloum & A. Aburayya (Eds.), Social computing and information science (pp. 1–16). Springer. https://doi.org/10.1007/978-3-031-52280-2_14

Swidan, A., Lee, S. Y., & Romdhane, S. B. (2025). College Students’ Use and Perceptions of AI Tools in the UAE: Motivations, Ethical Concerns and Institutional Guidelines. Education Sciences, 15(4), 461. https://doi.org/10.3390/educsci15040461

Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics (5th ed.). Allyn & Bacon/Pearson Education.

Tennant, R., Hiller, L., Fishwick, R., Platt, S., Joseph, S., Weich, S., Parkinson, J., Secker, J., & Stewart-Brown, S. (2007). The Warwick-Edinburgh Mental Well-being Scale (WEMWBS): Development and UK validation. Health and Quality of Life Outcomes, 5, 63. https://doi.org/10.1186/1477-7525-5-63

Torrey, E. F., & Dailey, L. (2022). What NIMH Should Be Doing. Psychiatric Services, 73(3), 247–248. https://doi.org/10.1176/appi.ps.202100620

UNESCO. (2023). UAE universities play a pivotal role in achieving 2030 sustainable development goals. https://www.unesco.org/en/articles/uae-universities-play-pivotal-role-achieving-2030-sustainable-development-goals?utm

Vieriu, A. M., & Petrea, G. (2025). The Impact of Artificial Intelligence (AI) on Students’ Academic Development. Education Sciences, 15(3), 343. https://doi.org/10.3390/educsci15030343

World Health Organization. (2022). Anxiety disorders. https://www.who.int/news-room/fact-sheets/detail/anxiety-disorders