(A) psychological network based SEM of suicide risk

Abstract

Suicide, a significant cause of death in the contemporary world, is a focal point of intense research in public health. Recognizing that suicide is a complex phenomenon influenced by multiple factors, this study utilized psychological networks and structural equation modeling(SEM) to delve into the intricate relationships among various risk factors of suicide. The analysis encompassed a dataset of 128,302 samples, combining The Korea National Investigations of Suicide Decedents (The KNIGHTS Study) data and the Korea Welfare Panel Study (KoWePS) data spanning 2013 to 2017, focusing on suicide and 13 common variables. A comparative assessment between 1) the SEM based on theories and conjecture, 2) the SEM based on the results of Exploratory Factor Analysis, and 3) the SEM based on network results revealed the superiority of the network-based model in terms of both model fit and theoretical validity. Results from the network and structural equation analyses identified depression and suicide attempts as robust predictors of suicide, aligning with findings from prior research. The study also unveiled the mechanism elucidating the impact of gender and latent variables on suicide. In light of these outcomes, the study delves into theoretical implications and offers insights into potential directions for future research.