Network Analysis of Association Between Problematic Social Network Use and Alexithymia in Freshmen
Bibliographic record
Abstract
Objective: Exploring the core and bridge nodes in problematic social network use and alexithymia among freshmen to provide a basis for understanding the relationship and interventions. Methods: A total of 4057 first-year students from four universities in Shandong Province were chosen and surveyed with the Problematic Mobile Social Media Use Assessment Questionnaire and the Toronto Alexithymia Scale (TAS). Network analysis was performed using R to estimate the connections between nodes. Centrality and predictability indicators were used to identify key nodes, with accuracy and stability validation techniques applied. Gender and residence differences in the network structure were also examined. Results: In the problematic social network use network, the nodes with the highest expected influence were P16 (excessive swiping) and P14 (lack of control over phone usage). In the problematic social network use-alexithymia network, cognitive failure had the highest strength (strength = 1.155) and centrality. Difficulty identifying feelings (bridgestrength = 0.32), externally oriented thoughts (bridgestrength = 0.24), and cognitive failure (bridgestrength = 0.19) were key bridge nodes. No significant differences were found in the network structure across gender and residence, though the network was tightly connected. Conclusion: Cognitive failure plays a central role in problematic social network use among freshmen. Difficulty identifying feelings, externally oriented thoughts, and cognitive failure are critical in linking problematic social network use with alexithymia. Plain Language Summary: In a study with over 4000 freshmen from four universities in Shandong Province, researchers examined the link between problematic social media use and alexithymia. The study used the method of network analysis to analyze data. The key findings were that “cognitive failure”—reduced mental processing due to excessive mobile use—is central to problematic social network use. The most significant issues identified were difficulty identifying feelings, engaging in externally oriented thinking, and cognitive failures. These factors are consistent across different genders and residences, indicating a common pattern among freshmen. The results suggest that interventions to reduce excessive social media use and improve emotional awareness should focus on these areas to help alleviate alexithymia symptoms and enhance student well-being. Keywords: problematic social network use, alexithymia, freshmen, network analysis
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".