A Computational Modeling Approach To Examining The Effects Of Environmental Stressors On Suicidal Behavior In Urban Areas

This study utilizes an Agent-Based Modeling (ABM) approach to explore the influence of psychological stressors on suicidal behavior within urban environments. By integrating data from public health records and environmental studies, the model simulates the interactions between individuals and their urban settings, focusing on psychological variables such as perceived burdensomeness, thwarted belongingness, and coping mechanisms. Quantitative analysis from the simulation reveals that individuals experiencing high levels of perceived burdensomeness exhibit a 22.5% increase in suicide rates compared to those with low levels. Similarly, high thwarted belongingness correlates with a 19.8% increase in suicide rates. Notably, the presence of adaptive coping mechanisms leads to a 30% reduction in suicidal ideation, underscoring their protective effect. These findings underscore the critical impact of psychological stressors on suicidal behavior and highlight the potential of interventions that enhance adaptive coping strategies and social support networks. The study advocates for the incorporation of these elements into urban planning and public health policies to effectively mitigate suicide risks in urban populations. Future research directions include conducting longitudinal studies to assess the long-term effects of psychological stressors and expanding the model to include additional variables such as impulsivity and psychiatric disorders. This research contributes valuable insights into the complex dynamics of suicide in urban settings, providing a foundation for more targeted and effective prevention strategies.

A Computational Modeling Approach To Examining The Effects Of Environmental Stressors On Suicidal Behavior In Urban Areas Keywords:

Environmental Stressors , Suicidal Behavior , Urban Areas , Computational Modeling , Mental Health