The Modeling of Internet Addiction Based on Identity Styles: The Mediating Role of Alexithymia
Bibliographic record
Abstract
The study aimed to investigate the internet addiction model based on identity styles and mediating role of alexithymia in students. This research was a correlational research based on the structural equation modeling method. The statistical population of this study was all of secondary high school students in Sari. In this study, 361 people were selected by multistage sampling and responded to the Identity Style Scale (Berzonsky,1992), Toronto Alexithymia Scale (Bagby, Taylor & Parker, 1994), and Internet Addiction Scale (Young,1998). The findings showed good model fit and 41% of Internet addiction variance were explained by identity styles and alexithymia. The results of this study highlights the importance of the role of identity as well as the mediating role of alexithymia on students' extreme internet tendencies and has implications for improving mental health.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".