Research on the Influencing Factors of Depression and Anxiety Based on Anxiety dataset

This study delves into the complex relationship between depression and anxiety, aiming to elucidate their multifaceted nature and impact. Leveraging a robust dataset, it is conducted a comprehensive analysis to assess the significance of various factors associated with these mental health disorders. Through statistical techniques such as exploratory data analysis (EDA) and predictive modeling such as decision tree model, this paper explored predictors and underlying dynamics. The findings highlighted the importance of demographic, lifestyle, and psychological factors in understanding depression and anxiety. Notably, all variables examined showed significant deviations, emphasizing their relevance. Furthermore, the analysis revealed intricate interactions among factors, emphasizing the nuanced nature of these conditions. This study provides insights for healthcare policies and future research, stressing the need to consider less prominent factors and socio-cultural contexts. By comprehensively understanding the interplay of factors, the author aims to inform more effective interventions and policies in mental health.