Investigating the Relationships between Internet Addiction and Suicidal Ideation in Adolescent Girls
Bibliographic record
Abstract
Objective: Suicidal ideation (SI) signifies a psychiatric crisis, and individuals with SI are at a significantly higher risk of suicide attempts compared to those without. According to previous research, three factors that affect SI in adolescent girls are externalization problems, alexithymia, and perceived social support (PSS). As a result, the present research aimed to examine whether internet addiction (IA) is associated with SI through the mediating roles of PSS, externalizing problems, and alexithymia among adolescent girls in Tehran, Iran. Method: The current correlational study employed a structural equation modeling approach. Model fit indices such as the Chi-square to degrees of freedom ratio (CMIN/DF), normed fit index (NFI), root mean square error of approximation (RMSEA), Tucker-Lewis index (TLI), and goodness-of-fit index (CFI) were reported to assess the model’s adequacy. A total of 441 adolescent girls were selected from high school and between the ages of 11 and 19 using a convenience sampling method. Participants completed the Multidimensional Scale of Perceived Social Support (MSPSS), the Beck Scale for Suicidal Ideation (BSSI), the Cell-Phone Over-Use Scale (COS), the Youth Self-Report (YSR), and the Toronto Alexithymia Scale-20 (TAS-20) in a written manner. Data analysis was done using SPSS 25 and AMOS 22. Results: Results revealed a significant positive correlation between IA and SI (P < 0.001). The study's most significant findings indicate that PSS, externalizing problems, and alexithymia significantly mediate the relationship between SI and IA. The coefficient of determination for the SI variable was 0.33, which means that predictor variables can explain 33% of the variance in SI (IA, PSS, alexithymia, and externalizing problems). Conclusion: IA showed direct and indirect effects on SI. Using these findings, we can elucidate the mechanism of how IA affects individual SI, providing critical information for the development and implementation of targeted strategies and interventions to reduce SI among Iranian adolescent girls. Psychological interventions that address the role of externalizing behaviors, alexithymia, and PSS in adolescents with IA may help reduce SI.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".