Exploring Cyberaggression and Mental Health Consequences among Adults: An Italian Nationwide Cross-Sectional Study.

Cyberaggression (CyA) embraces a broad spectrum of hostile behaviors through electronic means. This cross-sectional study aimed to evaluate features and outcomes of this phenomenon among Italian adults. A nationwide survey was distributed on social media platforms. Being victim and being perpetrator of CyA were the primary outcomes; positive scores for GAD-2 (generalized anxiety disorder) and PHQ-2 (depressive symptoms) scales were the secondary outcomes. In total, 446 surveys were collected. Considering the primary outcomes, 46.3% and 13.5% reported having been victims and perpetrators of CyA, respectively. Politics, ethnic minority, and sexual orientation were main subjects triggering CyA. A higher likelihood of being cyber-victims was observed for women and the LGBTQA+ group. Women were less likely to be CyA perpetrators. There was an association between being a CyA victim and a CyA perpetrator. A total of 22.4% and 34.0% respondents scored positive for PHQ-2 and GAD-2, respectively. The main mental health consequences after CyA exposure were anger and sadness, whereas sleep alterations and stomach ache were the most experienced psychosomatics symptoms. No significant relationships between PHQ-2/GAD-2 and CyA emerged. CyA also represents a crucial public health issue among Italian adults. Further investigations are needed to better define the phenomenon and to study the potential consequences on mental health.

Resilience or robustness: identifying topological vulnerabilities in rail networks.

Many critical infrastructure systems have network structures and are under stress. Despite their national importance, the complexity of large-scale transport networks means that we do not fully understand their vulnerabilities to cascade failures. The research conducted through this paper examines the interdependent rail networks in Greater London and surrounding commuter area. We focus on the morning commuter hours, where the system is under the most demand stress. There is increasing evidence that the topological shape of the network plays an important role in dynamic cascades. Here, we examine whether the different topological measures of resilience (stability) or robustness (failure) are more appropriate for understanding poor railway performance. The results show that resilience, not robustness, has a strong correlation with the consumer experience statistics. Our results are a way of describing the complexity of cascade dynamics on networks without the involvement of detailed agent-based models, showing that cascade effects are more responsible for poor performance than failures. The network science analysis hints at pathways towards making the network structure more resilient by reducing feedback loops.