A mixed-methods study of depressive-symptom severity among Thai university students and the underestimated role of social media
Year: 2026
Type: article
Study design: Observational Study
Abstract: Purpose: University students face academic, social, economic, and digital stressors. Social-media use may be under-recognized as a correlate of depressive symptoms because online engagement is often viewed as routine communication, leisure, and academic activity. This study examined factors associated with depressive-symptom severity among Thai university students and explored the mismatch between perceived stressors and the observed association with social-media use. Methods: tests and ordinal logistic regression. A purposive subsample of 12 students participated in semi-structured interviews on social-media routines, online comparison, nighttime use and sleep, coping, social support, and help-seeking. All interviews were audio-recorded and supplemented by contemporaneous field notes. Qualitative data were analyzed thematically and integrated with quantitative findings through joint comparison. Results: Clinically significant depressive symptoms (CES-D ≥ 16) were reported by 49.68% of students. Academic year, major, GPAX, primary source of personal support, and daily social-media use were independently associated with symptom severity. Compared with students using social media >3 h/day, those using it <1 h/day (OR = 0.125, 95% CI: 0.040-0.391) or 1-3 h/day (OR = 0.424, 95% CI: 0.278-0.647) had lower odds of greater symptom severity. Internet/social-media use ranked only fifth among eight perceived stressors (37.01% agreement). Three qualitative themes described social media as an embedded and ambivalent part of student life, psychological effects shaped by patterns and interpretations of use, and distress managed mainly through self-coping and trusted informal support. Conclusion: The key mixed-methods finding was a perception-association mismatch: social-media use was not perceived as a leading stressor yet showed the strongest adjusted association with depressive-symptom severity among the factors examined. These cross-sectional findings do not establish causality but support digital-wellbeing assessment beyond duration alone.
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $2,353
Funder: Rangsit University
OpenAlex ID: W7222007147