Exploring the links between alexithymia and cognitive emotion regulation strategies in internet addiction: A network analysis model
Bibliographic record
Abstract
Alexithymia and emotion regulation are closely related to internet addiction. However, no research has examined how the different components of alexithymia are associated with cognitive emotion regulation in the context of multi-strategy use in internet addiction. The current study aimed to investigate the relation between alexithymia and cognitive emotion regulation in individuals with internet addiction via network analysis. Participants included 560 students with Young’s Internet Addiction Test scores greater than 50 points; they were also asked to complete the Toronto Alexithymia Scale (TAS-20) and the Cognitive Emotion Regulation Questionnaire (CERQ). The results revealed two bridge nodes emerging within the combined alexithymia and cognitive emotion regulation network model: “catastrophizing” and “externally oriented thoughts.” These findings indicate a more specific relation between alexithymia and cognitive emotion regulation and provide empirical evidence for targeted prevention and targeted interventions for internet addiction.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".