Factors related to suicidal ideation of schizophrenia patients in China: a study based on decision tree and logistic regression model

Psychol Health Med. 2024 Jan 3:1-15. doi: 10.1080/13548506.2023.2301225. Online ahead of print.

Abstract

This study aimed to investigate the factors associated with suicidal ideation in schizophrenia patients in China using decision tree and logistic regression models. From October 2020 to March 2022, patients with schizophrenia were chosen from Chifeng Anding Hospital and Daqing Third Hospital in Heilongjiang Province. A total of 300 patients with schizophrenia who met the inclusion criteria were investigated by questionnaire. The questionnaire covered general data, suicidal ideation, childhood trauma, social support, depressive symptoms and psychological resilience. Logistic regression analysis revealed that childhood trauma and depressive symptoms were risk factors for suicidal ideation in schizophrenia (OR = 2.330, 95%CI: 1.177 ~ 4.614; OR = 10.619, 95%CI: 5.199 ~ 21.688), while psychological resilience was a protective factor for suicidal ideation in schizophrenia (OR = 0.173, 95%CI: 0.073 ~ 0.409). The results of the decision tree model analysis demonstrated that depressive symptoms, psychological resilience and childhood trauma were influential factors for suicidal ideation in patients with schizophrenia (p < 0.05). The area under the ROC for the logistic regression model and the decision tree model were 0.868 (95% CI: 0.821 ~ 0.916) and 0.863 (95% CI: 0.814 ~ 0.912) respectively, indicating excellent accuracy of the models. Meanwhile, the logistic regression model had a sensitivity of 0.834 and a specificity of 0.743 when the Youden index was at its maximum. The decision tree model had a sensitivity of 0.768 and a specificity of 0.8. Decision trees in combination with logistic regression models are of high value in the study of factors influencing suicidal ideation in schizophrenia patients.

Keywords: Schizophrenia; decision trees; logistic models; suicidal ideation.