Personality Profiles as Key Drivers of Techno-Eustress for Enhancing Digital Well-Being in Online Learning
DOI:
https://doi.org/10.54855/Keywords:
Personality profiles, techno-eustress, personality traits, IT mindfulness, online learningAbstract
The COVID-19 pandemic's shift to digital education intensified student technostress, impeding engagement. Recent research highlights techno-eustress, positive responses to technological challenges, as a predictor of improved online learning performance. This study examines how personality traits and IT mindfulness enable students to perceive technological demands as stimulating rather than overwhelming. Integrating the Transactional Model of Stress and Coping, Five-Factor Model, and Mindfulness-to-Meaning Theory, we surveyed 79 high-achieving Malaysian university students. Fuzzy-set Qualitative Comparative Analysis (fsQCA) identified four distinct personality profiles associated with techno-eustress. IT mindfulness emerged as universally necessary, enabling reinterpretation of stressors as challenges across all profiles. Findings advance techno-eustress theory by demonstrating that personality configurations shape coping effectiveness and adaptive outcomes. In practice, results inform educators and institutions in designing targeted interventions that leverage personality strengths and cultivate IT mindfulness, empowering students to transform technostress into productive engagement in online learning environments.
References
Agarwal, R., & Prasad, J. (1998). A Conceptual and Operational Definition of Personal Innovativeness in the Domain of Information Technology. Information Systems Research, 9(2), 204-215. https://doi.org/10.1287/isre.9.2.204
Al-Fraihat, D., Joy, M., Masa'deh, R. e., & Sinclair, J. (2020). Evaluating E-learning systems success: An empirical study. Computers in Human Behavior, 102, 67-86. https://doi.org/https://doi.org/10.1016/j.chb.2019.08.004
Audet, É. C., Levine, S. L., Metin, E., Koestner, S., & Barcan, S. (2021). Zooming their way through university: Which Big 5 traits facilitated students' adjustment to online courses during the COVID-19 pandemic. Personality and Individual Differences, 180, 110969. https://doi.org/https://doi.org/10.1016/j.paid.2021.110969
Awang Kader, M. A. R., Abd Aziz, N. N., Mohd Zaki, S., Ishak, M., & Hazudin, S. F. (2022). The Effect of Technostress on Online Learning Behaviour Among Undergraduates. Malaysian Journal of Learning and Instruction, 19(1), 183-211. https://doi.org/10.32890/mjli2022.19.1.7
Ayyagari, R., Grover, V., & Purvis, R. (2011). Technostress: Technological Antecedents and Implications. MIS Quarterly, 35(4), 831-858. https://doi.org/10.2307/41409963
Baruth, O., & Cohen, A. (2023). Personality and satisfaction with online courses: The relation between the Big Five personality traits and satisfaction with online learning activities. Education and Information Technologies, 28(1), 879-904. https://doi.org/10.1007/s10639-022-11199-x
Bhagat, K. K., Wu, L. Y., & Chang, C.-Y. (2019). The impact of personality on students' perceptions towards online learning. Australasian Journal of Educational Technology, 35(4). https://doi.org/10.14742/ajet.4162
Bohane, L., Maguire, N., & Richardson, T. (2017). Resilients, overcontrollers and undercontrollers: A systematic review of the utility of a personality typology method in understanding adult mental health problems. Clinical Psychology Review, 57, 75-92. https://doi.org/https://doi.org/10.1016/j.cpr.2017.07.005
Bossi, F., Zaninotto, F., D’Arcangelo, S., Lattanzi, N., Malizia, A. P., & Ricciardi, E. (2022). Mindfulness-based online intervention increases well-being and decreases stress after Covid-19 lockdown. Scientific Reports, 12(1), 6483. https://doi.org/10.1038/s41598-022-10361-2
Brod, C. (1984). Technostress : the human cost of the computer revolution. Addison-Wesley. https://cir.nii.ac.jp/crid/1130282271468676224
Cazan, A.-M., David, L. T., Truța, C., Maican, C. I., Henter, R., Năstasă, L. E., Nummela, N., Vesterinen, O., Rosnes, A. M., Tungland, T., Gudevold, E., Digernes, M., Unz, D., Witter, S., & Pavalache-Ilie, M. (2024). Technostress and time spent online. A cross-cultural comparison for teachers and students [Original Research]. Frontiers in Psychology, Volume 15 - 2024. https://doi.org/10.3389/fpsyg.2024.1377200
Chowdhury, N., Kevorkian, S., Hawn, S. E., Amstadter, A. B., Dick, D., Kendler, K. S., & Berenz, E. C. (2018). Associations between personality and distress tolerance among trauma-exposed young adults. Personality and Individual Differences, 120, 166-170. https://doi.org/https://doi.org/10.1016/j.paid.2017.08.041
Costa, P. T., & McCrae, R. R. (1998). Trait Theories of Personality. In D. F. Barone, M. Hersen, & V. B. Van Hasselt (Eds.), Advanced Personality (pp. 103-121). Springer US. https://doi.org/10.1007/978-1-4419-8580-4_5
De Crescenzo, V., Ribeiro-Soriano, D. E., & Covin, J. G. (2020). Exploring the viability of equity crowdfunding as a fundraising instrument: A configurational analysis of contingency factors that lead to crowdfunding success and failure. Journal of Business Research, 115, 348-356. https://doi.org/https://doi.org/10.1016/j.jbusres.2019.09.051
Devi, V. (2022, 24 April 2022). Address issue of unemployed grads quickly and systematically, says TMJ. The Star. https://www.thestar.com.my/news/nation/2022/04/24/address-issue-of-unemployed-grads-quickly-and-systematically-says-tmj
Farrell, O., & Brunton, J. (2020). A balancing act: a window into online student engagement experiences. International Journal of Educational Technology in Higher Education, 17(1), 25. https://doi.org/10.1186/s41239-020-00199-x
Fiss, P. C. (2011). Building Better Causal Theories: A Fuzzy Set Approach to Typologies in Organization Research. Academy of Management Journal, 54(2), 393-420. https://doi.org/10.5465/amj.2011.60263120
García-Morales, V. J., Garrido-Moreno, A., & Martín-Rojas, R. (2021). The Transformation of Higher Education After the COVID Disruption: Emerging Challenges in an Online Learning Scenario [Mini Review]. Frontiers in Psychology, 12. https://doi.org/10.3389/fpsyg.2021.616059
Garland, E., Farb, N., Goldin, P., & Fredrickson, B. (2015). The Mindfulness-to-Meaning Theory: Extensions, Applications, and Challenges at the Attention–Appraisal–Emotion Interface. Psychological Inquiry, 26(4), 377-387. https://doi.org/10.1080/1047840X.2015.1092493
Garland, E. L., Hanley, A. W., Goldin, P. R., & Gross, J. J. (2017). Testing the mindfulness-to-meaning theory: Evidence for mindful positive emotion regulation from a reanalysis of longitudinal data. PLOS ONE, 12(12), e0187727. https://doi.org/10.1371/journal.pone.0187727
Gramzow, R. H., Sedikides, C., Panter, A. T., Sathy, V., Harris, J., & Insko, C. A. (2004). Patterns of self‐regulation and the Big Five. European Journal of Personality, 18(5), 367-385. https://doi.org/10.1002/per.513
Grant, S., & Langan-Fox, J. (2006). Occupational stress, coping and strain: The combined/interactive effect of the Big Five traits. Personality and Individual Differences, 41(4), 719-732. https://doi.org/https://doi.org/10.1016/j.paid.2006.03.008
Hair, J., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2022). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (3rd Edition ed.). SAGE Publications, Inc.
Igwe, J. N., Ugwuanyi, C. S., Ejimonye, J. C., Odionye, N., Metu, I. C., Enebechi, R. I., Eze, K. O., Ikeh, F. E., Okeke, A. O., Nnnadi, E. M., Onuoha, J. C., Ene, C. U., Nwachukwu, V. N., Mbelede, N. G., & Egolum, E. O. (2022). Stress Management Among Science and Social Science Educators Within Open and Distance Learning Centers Using Rational Emotive Behavior Therapy: Implication for Curriculum and Educational Evaluators. Journal of Rational-Emotive & Cognitive-Behavior Therapy, 40(4), 745-766. https://doi.org/10.1007/s10942-021-00430-2
John, O. P., Donahue, E. M., & Kentle, R. L. (1991). The Big Five Inventory--Versions 4a and 54. Berkeley.
Kahwati, L. C., & Kane, H. L. (2018). Qualitative comparative analysis in mixed methods research and evaluation (Vol. 6). Sage Publications.
Kaya, B., Abubakar, A. M., Behravesh, E., Yildiz, H., & Mert, I. S. (2020). Antecedents of innovative performance: Findings from PLS-SEM and fuzzy sets (fsQCA). Journal of Business Research, 114, 278-289. https://doi.org/https://doi.org/10.1016/j.jbusres.2020.04.016
Kropotov, J. D. (2016). Chapter 3.3 - Affective System, Emotions, and Stress. In J. D. Kropotov (Ed.), Functional Neuromarkers for Psychiatry (pp. 207-229). Academic Press. https://doi.org/https://doi.org/10.1016/B978-0-12-410513-3.00013-9
Lazarus, R. S., & Folkman, S. (1984). Stress, appraisal, and coping. Springer publishing company.
Loos, A. T. (2017). The Role of Librarians in Promoting Digital Wellness: A Case Study. Public Services Quarterly, 13(1), 32-40. https://doi.org/10.1080/15228959.2016.1268943
Maier, C., Laumer, S., Wirth, J., & Weitzel, T. (2019). Technostress and the hierarchical levels of personality: a two-wave study with multiple data samples. European Journal of Information Systems, 28(5), 496-522. https://doi.org/10.1080/0960085X.2019.1614739
Malaysian Investment Development Authority. (2021, 8 February 2021). Evolution of e-Learning in the Malaysian Higher Education Institutions. Bernama. https://www.bernama.com/en/thoughts/news.php?id=1928731
McCrae, R. R., & Costa Jr, P. T. (1997). Personality trait structure as a human universal. American Psychologist, 52(5), 509-516. https://doi.org/10.1037/0003-066X.52.5.509
Menon, S. (2021, 12 December 2021). Surveys: Students suffering from emotional distress, poor mental health. The Star. https://www.thestar.com.my/news/education/2021/12/12/surveys-students-suffering-from-emotional-distress-poor-mental-health
Milfont, T. L., & Sibley, C. G. (2012). The big five personality traits and environmental engagement: Associations at the individual and societal level. Journal of Environmental Psychology, 32(2), 187-195. https://doi.org/https://doi.org/10.1016/j.jenvp.2011.12.006
Nascimento, L., Correia, M. F., & Califf, C. B. (2024). Towards a bright side of technostress in higher education teachers: Identifying several antecedents and outcomes of techno-eustress. Technology in Society, 76, 102428. https://doi.org/https://doi.org/10.1016/j.techsoc.2023.102428
Nascimento, L., Correia, M. F., & Califf, C. B. (2025). Techno-eustress under remote work: a longitudinal study in higher education teachers. Education and Information Technologies. https://doi.org/https://doi.org/10.1007/s10639-025-13459-y
Nitzl, C., Sicilia, M., & Steccolini, I. (2024). Personality traits and the use of performance information: enthusiastic and diligent public managers. International Public Management Journal, 1-24. https://doi.org/10.1080/10967494.2024.2323580
O’Hagan, C. (2020, 29 April 2020). 1.3 billion learners are still affected by school or university closures, as educational institutions start reopening around the world, says UNESCO https://en.unesco.org/news/13-billion-learners-are-still-affected-school-university-closures-educational-institutions
Pappas, I. O., & Woodside, A. G. (2021). Fuzzy-set Qualitative Comparative Analysis (fsQCA): Guidelines for research practice in Information Systems and marketing. International Journal of Information Management, 58, 102310. https://doi.org/https://doi.org/10.1016/j.ijinfomgt.2021.102310
Paunonen, S. V. (1998). Hierarchical organization of personality and prediction of behavior. Journal of Personality and Social Psychology, 74(2), 538-556. https://doi.org/10.1037/0022-3514.74.2.538
Pflügner, K., Maier, C., Mattke, J., & Weitzel, T. (2021). Personality Profiles that Put Users at Risk of Perceiving Technostress. Business & Information Systems Engineering, 63(4), 389-402. https://doi.org/10.1007/s12599-020-00668-7
Postigo, Á., Cuesta, M., García-Cueto, E., Prieto-Díez, F., & Muñiz, J. (2021). General versus specific personality traits for predicting entrepreneurship. Personality and Individual Differences, 182, 111094. https://doi.org/https://doi.org/10.1016/j.paid.2021.111094
Ragin, C. C. (2008). Redesigning social inquiry: Fuzzy sets and beyond. University of Chicago Press.
Ragin, C. C., & Davey, S. (2022). Fuzzy-Set/Qualitative Comparative Analysis 4.0. In Department of Sociology, University of California. https://sites.socsci.uci.edu/~cragin/fsQCA/software.shtml
Ragu-Nathan, T. S., Tarafdar, M., Ragu-Nathan, B. S., & Tu, Q. (2008). The Consequences of Technostress for End Users in Organizations: Conceptual Development and Empirical Validation. Information Systems Research, 19(4), 417-433. https://doi.org/10.1287/isre.1070.0165
Rihoux, B., & Ragin, C. C. (2008). Configurational comparative methods: Qualitative comparative analysis (QCA) and related techniques (Vol. 51). Sage.
Robins, R. W., John, O. P., Caspi, A., Moffitt, T. E., & Stouthamer-Loeber, M. (1996). Resilient, overcontrolled, and undercontrolled boys: Three replicable personality types. Journal of Personality and Social Psychology, 70(1), 157-171. https://doi.org/10.1037/0022-3514.70.1.157
Saleem, F., Chikhaoui, E., & Malik, M. I. (2024). Technostress in students and quality of online learning: role of instructor and university support [Original Research]. Frontiers in Education, 9. https://doi.org/10.3389/feduc.2024.1309642
Schnabel, K., Asendorpf, J. B., & Ostendorf, F. (2002). Replicable types and subtypes of personality: German NEO-PI-R versus NEO-FFI. European Journal of Personality, 16(SpecIssue), S7-S24. https://doi.org/10.1002/per.445
Sharma, S., & Gupta, B. (2022). Investigating the role of technostress, cognitive appraisal and coping strategies on students' learning performance in higher education: a multidimensional transactional theory of stress approach. Information Technology & People, ahead-of-print(ahead-of-print). https://doi.org/10.1108/ITP-06-2021-0505
Shirish, A., Chandra, S., & Srivastava, S. C. (2021). Switching to online learning during COVID-19: Theorizing the role of IT mindfulness and techno eustress for facilitating productivity and creativity in student learning. International Journal of Information Management, 61, 102394. https://doi.org/https://doi.org/10.1016/j.ijinfomgt.2021.102394
Shirish, A., Verstraete, N., & Tantan, O. C. (2023). The impact of ICT characteristics on students’ learning outcomes during COVID-19 lockdown period: The crucial role of techno eustress perception. Human Systems Management, 42, 149-162. https://doi.org/10.3233/HSM-220059
Srivastava, S. C., Chandra, S., & Shirish, A. (2015). Technostress creators and job outcomes: theorising the moderating influence of personality traits. Information Systems Journal, 25(4), 355-401. https://doi.org/https://doi.org/10.1111/isj.12067
Sun, W., Hong, J.-C., Dong, Y., Huang, Y., & Fu, Q. (2023). Self-directed Learning Predicts Online Learning Engagement in Higher Education Mediated by Perceived Value of Knowing Learning Goals. The Asia-Pacific Education Researcher, 32(3), 307-316. https://doi.org/10.1007/s40299-022-00653-6
Sutin, A. R., Costa Jr, P. T., Wethington, E., & Eaton, W. (2010). Turning points and lessons learned: Stressful life events and personality trait development across middle adulthood. Psychology and Aging, 25(3), 524-533. https://doi.org/10.1037/a0018751
Tarafdar, M., Cooper, C. L., & Stich, J.-F. (2017). The technostress trifecta - techno eustress, techno distress and design: Theoretical directions and an agenda for research. Information Systems Journal, 29(1), 6-42. https://doi.org/https://doi.org/10.1111/isj.12169
Tarafdar, M., Pullins, E. B., & Ragu-Nathan, T. S. (2014). Technostress: Negative effect on performance and possible mitigations. Information Systems Journal, 25(2), 103-132. https://doi.org/10.1111/isj.12042
Tariq, Q. (2022, 3 January 2022). Study: Malaysian students burning out online. The Star. https://www.thestar.com.my/tech/tech-news/2022/01/03/study-malaysian-students-burning-out-online
Thatcher, J. B., Wright, R. T., Sun, H., Zagenczyk, T. J., & Klein, R. (2018). Mindfulness in information technology use: definitions, distinctions, and a new measure. MIS Q., 42(3), 831–848. https://doi.org/https://doi.org/10.25300/MISQ/2018/11881
Ul Hassan, M., Murtaza, A., & Rashid, K. (2025). Redefining Higher Education Institutions (HEIs) in the Era of Globalisation and Global Crises: A Proposal for Future Sustainability. European Journal of Education, 60(1), e12822. https://doi.org/https://doi.org/10.1111/ejed.12822
Vollrath, M., & Torgersen, S. (2000). Personality types and coping. Personality and Individual Differences, 29(2), 367-378. https://doi.org/https://doi.org/10.1016/S0191-8869(99)00199-3
Walker, K. A., & Koralesky, K. E. (2021). Student and instructor perceptions of engagement after the rapid online transition of teaching due to COVID-19. Natural Sciences Education, 50(1), e20038. https://doi.org/https://doi.org/10.1002/nse2.20038
Wang, Y., Garland, E. L., & Farb, N. A. S. (2023). An experimental test of the mindfulness-to-meaning theory: Casual pathways between decentering, reappraisal, and well-being. Emotion, 23(8), 2243-2258. https://doi.org/10.1037/emo0001252
Watermeyer, R., Crick, T., Knight, C., & Goodall, J. (2021). COVID-19 and digital disruption in UK universities: afflictions and affordances of emergency online migration. Higher Education, 81(3), 623-641. https://doi.org/10.1007/s10734-020-00561-y
Wei, S., Zhu, F., & Chen, X. (2021). Do stressors stifle or facilitate employees' innovative use of enterprise systems: the moderating role of IT mindfulness. Information Technology & People, 34(3), 955-977. https://doi.org/10.1108/ITP-09-2019-0499
Wu, C., Zhou, Y., Wang, R., Huang, S., & Yuan, Q. (2022). Understanding the Mechanism Between IT Identity, IT Mindfulness and Mobile Health Technology Continuance Intention: An Extended Expectation Confirmation Model. Technological Forecasting and Social Change, 176, 121449. https://doi.org/https://doi.org/10.1016/j.techfore.2021.121449
Zellars, K. L., Perrewé, P. L., Hochwarter, W. A., & Anderson, K. S. (2006). The interactive effects of positive affect and conscientiousness on strain. Journal of Occupational Health Psychology, 11(3), 281-289. https://doi.org/10.1037/1076-8998.11.3.281
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