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

•Influential factors of depressive symptoms were investigated among a representative sample of 976 middle-aged and older adults in Singapore.•Our predictors included demographics, socioeconomics, physical well-being, lifestyle, daily activities and loneliness.•Machine learning models were used to id...

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Veröffentlicht in:	Archives of gerontology and geriatrics 2025-02, Vol.129, p.105647, Article 105647
Hauptverfasser:	Tran, Thu, Tan, Yi Zhen, Lin, Sapphire, Zhao, Fang, Ng, Yee Sien, Ma, Dong, Ko, Jeonggil, Balan, Rajesh
Format:	Artikel
Sprache:	eng
Schlagworte:	Activities of Daily Living - psychology Aged Cross-Sectional Studies Depression Depression - diagnosis Depression - epidemiology Depression - psychology Female Humans Life Style Loneliness - psychology Machine Learning Male Middle Aged Prediction model Regression model Risk Factors Socioeconomic Factors Surveys and Questionnaires
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