Abstract
Network analysis was widely used to identify core symptoms, with the aim of providing targets for intervention. Whether targeted treatment based on core symptoms identified by network analysis is superior to the non-targeted treatment remains unknown. We utilize simulation to contrast their effects on the symptom network of mental health. In the simulation, intentional and random attacks represent targeted and non-targeted treatments, respectively. The simulation test was conducted by attacking the symptom network using both random attacks and intentional attacks targeting central nodes, as defined by centrality measures. The results showed that the natural connectivity of the network degraded faster in intentional attacks than in random ones. Additionally, abnormal individuals have higher natural connectivity values than normal individuals. The findings indicated that compare to non-targeted treatment methods, centrality based targeted treatment focusing on core symptoms disrupted the connections between symptoms more quickly, generating better treatment effects.
| Original language | English |
|---|---|
| Pages (from-to) | 29-44 |
| Number of pages | 16 |
| Journal | Journal of Evidence-Based Psychotherapies |
| Volume | 25 |
| Issue number | 1 |
| DOIs | |
| State | Published - 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- invulnerability simulation
- mental health
- network analysis
- symptom network
- targeted treatment
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