Analyzing the Rise of Depression Among College Students Through AI and Factor Mapping

This paper investigates the growing issue of depression among college students by using AI-driven analysis and detailed factor mapping. It draws from an extensive dataset that examines various elements, including demographic details, aca- demic workload, and psychological influences. Factors considered in the study include gender, age, living situation, course difficulty, CGPA, academic and job satisfaction, sleep and dietary habits, degree type, study and work hours, financial stress, and family history of mental health concerns. It also addresses how often Students experience severe depression or suicidal thoughts. By examining the relationships between these factors, the study uncovers how academic pressure, financial challenges, unclear career direction, and personal struggles can contribute to mental health issues. It also compares how depression manifests across different fields of study and education levels, highlighting subtle but important differences in students' mental health experiences. The goal is to offer a well-rounded understanding of the factors that contribute to student depression and to provide insights into the emotional and psychological realities faced by students in today's academic environment.