Investigating mental wellbeing self-care in higher education using BERTopic modeling

Area of Science:

• Psychology
• Higher Education Studies
• Digital Health

Background:

• Rising mental distress among higher education students necessitates urgent attention.
• Significant gaps exist in help-seeking behaviors within this demographic.
• Students encounter diverse stressors, including academic pressure, career uncertainty, and global issues like climate change.

Purpose of the Study:

• To analyze contemporary triggers of mental distress in students.
• To identify self-care strategies adopted by students during the COVID-19 pandemic.
• To inform the design of future digital mental wellbeing solutions based on student-reported data.

Main Methods:

• An online study involving 810 participants.
• Utilized computational methods for analyzing open-ended qualitative data.
• Focused on data collected during the COVID-19 pandemic.

Main Results:

• Identified prevalent challenges contributing to student mental distress.
• Detailed common self-care strategies employed by students.
• Derived direct implications for the design of mental wellbeing interventions.

Conclusions:

• Findings offer insights into student mental wellbeing needs.
• Technology designers can leverage these insights for creating effective digital support.
• There is a clear need for accessible, student-centered mental wellbeing solutions.