Identification of High-risk Groups of Suicide from the Depressed Elderly using Decision Tree Analysis
10.12799/jkachn.2019.30.2.130
- Author:
Sehoon HONG
1
;
Dongwon LEE
Author Information
1. Associate Professor, College of Nursing, CHA University, Pocheon, Korea.
- Publication Type:Original Article
- Keywords:
Depression;
Aged;
Suicide;
Decision trees
- MeSH:
Aged;
Decision Trees;
Depression;
Family Characteristics;
Humans;
Korea;
Nutrition Surveys;
Prevalence;
Quality of Life;
Risk Factors;
Sensitivity and Specificity;
Suicidal Ideation;
Suicide
- From:Journal of Korean Academy of Community Health Nursing
2019;30(2):130-140
- CountryRepublic of Korea
- Language:Korean
-
Abstract:
PURPOSE: The aim of this study is to explore levels of suicidal ideation and identify subgroups of high suicidal risk among the depressed elderly in Korea. METHODS: A descriptive cross-sectional design was adopted on secondary data from the 6th (1st year) Korean national health and nutrition examination survey (KNHANES). A total of 239 depressed elders aged 60 or over who participated in the KNHANES. The prevalence of suicidal ideation and its related factors, including sociodemographic, physical, psychological characteristics and quality of life (EQ-5D index) were examined. Descriptive statistics and a decision tree analysis were performed using the SPSS/WIN 23.0 and SPSS Modeler 14.2 programs. RESULTS: Of the depressed elderly, 28.9% had suicidal ideation. Three groups with high suicidal ideation were identified. Predictive factors included perceived stress level, household income level, quality of life and restriction of activity. In the highest risk group were those depressed elderly with moderate and low levels of stress, less than .71 of EQ-5D index and restriction of activity, and 80.0% of these participants had suicidal ideation. The accuracy of the model was 80.8%, its sensitivity 85.9%, and its specificity 68.1%. CONCLUSION: Multi-dimensional intervention should be designed to decrease suicide among the depressed elderly, particularly focusing on subgroups with high risk factors. This research is expected to contribute itself to the policy design and solution building in the future as it suggests policy implications in preventing the suicide of the depressed elderly.
