Exploring the Impact of Social Media on Anxiety Among University Students in the United Kingdom: Qualitative Study
Bibliographic record
Abstract
BACKGROUND: The rapid surge in social media platforms has significant implications for users' mental health, particularly anxiety. In the case of social media, the impact on mental well-being has been highlighted by multiple stakeholders as a cause for concern. However, there has been limited research into how the association between social media and anxiety arises, specifically among university students-the generation that has seen the introduction and evolution of social media, and currently lives through the medium. Extant systematic literature reviews within this area of research have not yet focused on university students or anxiety, rather predominantly investigating adolescents or generalized mental health symptoms and disorders. Furthermore, there is little to no qualitative data exploring the association between social media and anxiety among university students. OBJECTIVE: The purpose of this study is to conduct a systematic literature review of the existing literature and a qualitative study that aims to develop foundational knowledge around the association of social media and anxiety among university students and enhance extant knowledge and theory. METHODS: A total of 29 semistructured interviews were conducted, comprising 19 male students (65.5%) and 10 female students (34.5%) with a mean age of 21.5 years. All students were undergraduates from 6 universities across the United Kingdom, with most students studying in London (89.7%). Participants were enrolled through a homogenous purposive sampling technique via social media channels, word of mouth, and university faculties. Recruitment was suspended at the point of data saturation. Participants were eligible for the study if they were university students in the United Kingdom and users of social media. RESULTS: Thematic analysis resulted in 8 second-order themes: 3 mediating factors that decrease anxiety levels and 5 factors that increase anxiety levels. Social media decreased anxiety through positive experiences, social connectivity, and escapism. Social media increased anxiety through stress, comparison, fear of missing out, negative experiences, and procrastination. CONCLUSIONS: This qualitative study sheds critical light on how university students perceive how social media affects their anxiety levels. Students revealed that social media did impact their anxiety levels and considered it an important factor in their mental health. Thus, it is essential to educate stakeholders, including students, university counselors, and health care professionals, about the potential impact of social media on students' anxiety levels. Since anxiety is a multifactorial condition, pinpointing the main stressors in a person's life, such as social media use, may help manage these patients more effectively. The current research highlights that there are also many benefits to social media, and uncovering these may help in producing more holistic management plans for anxiety, reflective of the students' social media usage.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".