Objective: This study investigated mental health issues among higher education students to identify key concepts, topics, and trends over three periods of time: Period 1 (2000-2009), Period 2 (2010-2019), and Period 3 (2020-May 2024). Methods: The study collected 11,732 bibliographic records from Scopus and Web of Science, published between January 2000 and May 2024, and employed textual analysis methods, including keyword co-occurrence analysis, cluster analysis, and topic modeling. Results: In Period 1, general topics related to mental health disorders and treatments were identified. Period 2 showed prominence of well-being and help-seeking, as well as the emergence of digital mental health. Period 3 emphasized the impact of COVID-19 and increased technology usage. Conclusions: Based on the findings, we discussed the significance of the study and practical implications for clinicians and policymakers, as well as methodological implications for researchers. Additionally, the limitations of the study and future research were addressed.
Keywords: Clustering analysis; higher education student; mental health; text mining; topic modeling.