Author
Listed:
- Cephas Mandirahwe
(Faculty of Development Studies, Midlands State University, Zimbabwe)
- Rosemary Guvhu
(epartment of Educational Policy Studies and Leadership, Midlands State University, Zimbabwe)
- Effort Musvutisa
(Department of Science, Technology and Design Education, Midlands State University, Zimbabwe)
Abstract
The accelerated spread of Artificial Intelligence (AI) within higher education institutions such as universities signifies a profound technological advancement with dual implications for sustainable development. While AI promises unique opportunities for youth empowerment, its application demands a critical examination of its effect on student wellbeing. This study investigates the influence of AI-mediated educational processes on university students’ mental health through the lens of the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). Using a convergent parallel mixed-methods design at a selected public university in Zimbabwe, the study combined quantitative data (n=303 students) with qualitative insights from focus group discussions with students and lecturers. Findings showed a inflexible "Hardware Hierarchy," where 85.5% of students recognise the laptop as an vital "academic station" for critical AI confirmation, while mobile-only users experience a "technologically hollowed-out" state. Even though AI is highly cherished for its usefulness among students using tools like ChatGPT AND Google Gemini as "always-on" tutors, it is somewhat linked with adverse mental health outcomes. These manifest as "Turnitin Anxiety," "Temporal Anxieties" connected to computer laboratory access, and ethical panic emanating from a "legal vacuum" in institutional AI policy. Furthermore, qualitative narratives demonstrate "Techno-Exhaustion" among faculty, particularly female lecturers endeavouring to balance domestic work with the rigours of AI-output verification. Overall, the study concludes that the digital divide has evolved from a matter of connectivity to a "Divide in Wellness." It recommends institutional innovation beyond simple technological application and proposes application of robust ethical AI policies and subsidised hardware and WIFI data support to ease psychological risks while promoting resilient human capital development within the Education 5.0 framework.
Suggested Citation
Cephas Mandirahwe & Rosemary Guvhu & Effort Musvutisa, 2026.
"The Digital Divide in Wellness: Unpacking the Effects of Artificial Intelligence on University Student Mental Health,"
International Journal of Latest Technology in Engineering, Management & Applied Science, RSIS International, vol. 15(4), pages 1219-1236, April.
Handle:
RePEc:bjf:ijltem:v:15:y:2026:i:4:a:2406
DOI: 10.51583/IJLTEMAS.2026.150400106
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bjf:ijltem:v:15:y:2026:i:4:a:2406. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Dr. Pawan Verma (email available below). General contact details of provider: https://www.ijltemas.in/ .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.