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Multimodal Protocol for Assessing Metacognition and Self-Regulation in Adults with Learning Difficulties
Published on: September 27, 2020
Investigating mental wellbeing self-care in higher education using BERTopic modeling
Mahmoud Ali1, Niels van Berkel2, Benjamin Tag3
1University of Oulu, Oulu, Finland. mahmoud.ali@oulu.fi.
Abstract:
Addressing the mental wellbeing of higher education students is urgent, given rising distress rates and significant help-seeking gaps. Students face various life challenges ranging from academic pressure and career concerns to global issues like climate change, all of which may negatively impact their mental wellbeing. While appropriate self-care can mitigate these challenges, understanding the strategies students use independently is key to developing accessible support. This article analyses contemporary triggers for mental distress and the corresponding self-care strategies adopted by students, based on data collected during the COVID-19 pandemic. We then discuss how these findings can inform the design of future digital mental wellbeing solutions. We conducted an online study with 810 participants, utilizing computational methods to analyse open-ended data. We present insights into prevalent challenges and self-care strategies, deriving direct implications for design. Finally, we discuss how technology designers can contribute to effective mental wellbeing solutions based on our findings.
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