Problematic Social Media Use in Young Adults: A Mixed Serial–Parallel Mediation Model Involving Alexithymia, Defense Mechanisms, and Fear of Missing Out
Bibliographic record
Abstract
Problematic social media use (PSMU) can have profound and detrimental effects across various domains of life. As a result, scientific investigations into the risk factors associated with this phenomenon can hold substantial practical implications within the clinical and preventive realms. Consistently with this framework, this study aimed to examine the relationship between certain variables and PSMU, with a specific focus on alexithymia, defense mechanisms, and fear of missing out (FoMO). A sample of 340 young adults ( M age = 26.42 years; SD = 3.689) completed an online survey, including the Bergen Social Media Addiction Scale, FoMO scale, 40-Item Defense Style Questionnaire, and 20-Item Toronto Alexithymia Scale. Results showed a statistically significant mixed serial–parallel mediation model. A significant total effect in the association between alexithymia and FoMO emerged. Furthermore, defense mechanisms and FoMO significantly and totally mediated this relationship. These findings have the potential to provide valuable insights in the field of clinical research on PSMU, and can offer practical information for enhancing clinical practice.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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 source (direct Gemma or distilled Codex), 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".