Addiction Symptom Network of Young Internet Users: Network Analysis

Area of Science:

• Psychiatry
• Behavioral Science
• Network Analysis

Background:

• Internet addiction (IA) is a growing concern due to overuse.
• The Internet Addiction Test (IAT) is widely used, but its symptom interactions and relation to clinical criteria are unclear.

Purpose of the Study:

• To identify core symptoms of IA using network analysis.
• To compare IA symptom networks between addicted and non-addicted individuals.
• To examine the association between IAT and DSM-5 criteria for IA.

Main Methods:

• Network analysis of IAT data from 2845 internet users (aged 14-24).
• Partial correlation with Lasso regularization to identify core symptoms and compare network properties.
• Analysis of symptom networks for DSM-5 criteria and IAT scale.

Main Results:

• Identified core IA symptoms: school/job performance decline, fantasizing about web use, inability to stop, and fear of boredom offline.
• IA group showed stronger links between secrecy/hiding web use compared to non-IA group.
• DSM-5 criteria strongly correlated with specific IAT symptoms, particularly inability to stop and fear of boredom.

Conclusions:

• Significant differences exist in internet use symptom networks between IA and non-IA groups.
• Symptoms like fear of boredom and inability to stop web use are key activators of IA, linked to loss of control.
• Findings clarify IA symptom structure and its relation to clinical diagnostic criteria.