10.1708/1178.13056
Bibliographic record
Abstract
INTRODUCTION: Internet Addiction Disorder (IAD) is an emerging psychiatric disorder, assimilable to impulse control problems and related to maladaptive use of new networks and social and virtual technologies. AIM: Our study aims to analyze the presence of IAD among adolescents and to study the correlation with social interaction anxiousness. We investigated also the possibility that the Social Network (SN) represent a source of risk for the development of IAD. MATERIALS AND METHODS: The test group was composed of 250 subjects, aged between 14 and 18 years. They were administered: Young's IAT; IAS (Interaction Anxiousness Scale), AAS (Audience Anxiousness Scale) and SISST (Social Interaction Self-Statement Test) to analyze the dimension of social interaction anxiousness. RESULTS: We found a rate of 2% of the IAD. The SN are the most common use of the Net in our sample, but not the most clicked sites by subjects with IAD. It should be noted, finally, a correlation between social interaction anxiety and IAD, but not a significant difference in scores of social anxiousness scales based on the SN use/non-use. CONCLUSIONS: The use of SN intended as single variable doesn't correlate with increased risk for IAD, or for increased social interaction anxiousness. However, if associated with prolonged use of the net for 5-6 hours or more, or concomitant use of chat rooms and/or net gambling, we find a more significant risk of psychopathology. The data presented require further investigations, in order to guide new pathogenetic models and appropriate intervention strategies.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.952 | 0.959 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".