Exploring key factors influencing depressive symptoms among middle-aged and elderly adult population: A machine learning-based method

• Main Authors: TRAN, Ngoc Doan Thu, TAN, Yi Zhen, LIN, Sapphire, ZHAO, Fang, NG, Yee Sien, MA, Dong, KO, Jeonggil, BALAN, Rajesh Krishna
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2025
• Subjects: Depression; Demographics; socioeconomics; physical well-being; lifestyle; daily activities and loneliness; Machine learning; Prediction model; Regression model; Databases and Information Systems; Gerontology; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/9718; https://ink.library.smu.edu.sg/context/sis_research/article/10718/viewcontent/Depressive_Symptoms_Elderly_av.pdf
• Institution: Singapore Management University

Objective: This paper aims to investigate the key factors, including demographics, socioeconomics, physical wellbeing, lifestyle, daily activities and loneliness that can impact depressive symptoms in the middle-aged and elderly population using machine learning techniques. By identifying the most i...