Constructing prediction models and analyzing factors in suicidal ideation using machine learning, focusing on the older population.

ABSTRACT: Suicide among the older population is a significant public health concern in South Korea. As the older individuals have long considered suicide before committing suicide trials, it is important to analyze the suicidal ideation that precedes the suicide attempt for intervention. In this study, six machine learning algorithms were employed to construct a predictive model for suicidal thinking and identify key variables. A traditional logistic regression analysis was supplementarily conducted to test the robustness of the results of machine learning. All analyses were conducted using a hierarchical approach to compare the model fit of each model in both machine learning and logistic regression. Three models were established for analysis. In Model 1, socioeconomic, residential, and health beha

SUBMITTER: Jung HW 

PROVIDER: S-EPMC11262681 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature