A Scoping Review of the Use and Determinants of Social Media Among College Students
Bibliographic record
Abstract
Background/Objectives: Use of social media among college students is ubiquitous. Excessive use of social media has been linked to distractions, reduced academic focus, and poor mental health outcomes such as anxiety and depression. The determinants of social media use among college students are not well understood. Hence, the purpose of this study was to conduct a scoping review on the behavioral, demographic, and psychosocial determinants, explore theoretical frameworks, and suggest evidence-based recommendations. Methods: This scoping review was conducted between January 2024 and May 2025 following PRISMA-ScR guidelines, using MEDLINE (PubMed), CINAHL, and ERIC databases. Peer-reviewed studies were included if they focused on college students (ages 18–30), investigated determinants of social media use, and met predefined inclusion criteria. Results: A total of 22 studies met the inclusion criteria. Studies were conducted in Bangladesh, Canada, China, Egypt, India, Nigeria, Pakistan, Saudi Arabia, Turkey, and the United States, and the majority used cross-sectional designs (n = 20). A consistent finding across the reviewed studies was the strong association between social media overuse and symptoms of depression, anxiety, stress, and emotional dysregulation. Very few theoretical frameworks for understanding the determinants of social media were used. According to the reviewed studies, factors such as fear of missing out, sleep quality, and prolonged social media use consistently emerged as significant predictors of adverse mental health outcomes (p < 0.05). Conclusions: In this study, problematic social media use (PSMU) was linked to increased mental health issues, suggesting that students frequently engage in social comparison and experience feelings of missing out (FoMO), which exacerbate emotional distress. There is a need for integrated approaches in addressing PSMU within educational environments, particularly in fostering healthier digital habits among students. There is a need to conduct more concerted research using longitudinal designs and contemporary theoretical frameworks in this area.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".