The Mediating Role of Alexithymia in the Relationship Between Childhood Trauma and Internet Addiction in Adolescents: Emphasizing the Interaction of Person-Affect-Cognition-Execution (I-PACE) Model
Bibliographic record
Abstract
Objective: The present study was conducted with the aim of investigating the mediating role of Alexithymia in the relationship between childhood trauma and internet addiction, with an emphasis on the Interaction of Person-Affect-Cognition-Execution (I-PACE) model in adolescents. Methods and Materials: This study was descriptive-correlational and utilized structural equation modeling. The population consisted of adolescents aged 15 to 18 years on social networks in the year 2023. The sample size was 211 individuals, selected through purposive sampling. Data were collected using the Toronto Alexithymia Scale, Young's Internet Addiction Test, and Bernstein's Childhood Trauma Questionnaire and analyzed using SPSS and AMOS software through path analysis. Findings: The results showed that Alexithymia plays a mediating role in the relationship between childhood trauma and internet addiction in adolescents (P<0.01). Conclusion: Therefore, it is suggested that programs designed and implemented to reduce internet addiction should take into account Alexithymia and aim to repair childhood traumas.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".