Computational Modelling of Lifestyle-Driven Mental Health Disorders: Gender-Based Insights

Lifestyle disorders, driven by the mismanagement of daily activities and an inappropriate relationship with the environment, are increasingly leading to severe psychological and physiological consequences. In this study, we investigate the psychological disorders associated with individual lifestyle choices, focusing on gender-based differences. Data was collected through a comprehensive survey, capturing various mental health attributes such as depression, anxiety, and suicidal tendencies, alongside lifestyle parameters including work activities, age, and hereditary factors. This data was then analyzed using mathematical models to predict chronic psychological impacts. Linear regression plots were employed to evaluate the correlation between these mental health attributes and lifestyle parameters for both male and female participants. The findings were further validated using t-values for Pearson's correlation coefficient, providing insights into the gender-specific influences of lifestyle on mental health. These results highlight the importance of computational modelling in understanding and addressing lifestyle-driven mental health disorders, offering sustainable solutions for improved psychological well-being.