The prediction model of suicidal thoughts in Korean adults using Decision Tree Analysis: A nationwide cross-sectional study.
cross_sectional · Level IV
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- Record sourced from PubMed, PMID 31596870.
- Also identified by DOI 10.1371/journal.pone.0223220 and PMC identifier 6785128.
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Abstract
The purpose of this retrospective decisional analysis study is to develop the prediction model of suicidal ideation. We used a Decision Tree Analysis using SPSS 23.0 program to explore predictors of suicide thoughts for 12,015 Korean adults aged 19-98 years. As a result, the most powerful predictor of suicidal ideation was the level of depression. Of people who suspected depression (CESD-11>16), 32.6% experienced suicidal ideation, which is 12 times higher than that of total subjects. The group with the highest rate of suicidal ideation was people who experienced financial difficulties in depression-suspected group and the rate of suicidal thoughts in this group was 56.7%, which was the highest rate. However, in the non-depressive group, the satisfaction of family relationship was the strongest predictor of suicidal ideation. In the non-depressive group, the rate of suicidal thoughts of people with high level of family relationship satisfaction and high level of health satisfaction was 0.6%, which was the lowest rate. The contribution of this study was that it provided the combination of variables to predict the risk groups of adult suicide. This study suggests that researchers and clinicians should consider comprehensively depressive symptoms, family relationships, economic difficulties, and health status to prevent the suicide of adults.
Medical subject headings
- Decision Trees
- Models, Psychological
- Suicidal Ideation