ArticlePloS one2019
The prediction model of suicidal thoughts in Korean adults using Decision Tree Analysis: A nationwide cross-sectional study.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed.
- Predicting suicidal behavior outcomes: an analysis of key factors and machine learning models.BMC psychiatry · 2024Article
- The Longitudinal Association between Multiple Frailty Criteria and Depressive Symptomatology Five Years Later in Older Adults: A Decision Tree Modelling Approach.Journal of clinical medicine · 2024Article
- Examining the use of decision trees in population health surveillance research: an application to youth mental health survey data in the COMPASS study.Health promotion and chronic disease prevention in Canada : research, policy and practice · 2023Article
- Factors associated with suicidal attempts in female patients with mood disorder.Frontiers in public health · 2023Article
- Incidence Trends and Risk Prediction Nomogram for Suicidal Attempts in Patients With Major Depressive Disorder.Frontiers in psychiatry · 2021Article
- Sociological Narrative of Suicidal Behavior Among Older People.Clinical interventions in aging · 2021Article
- Recognizing states of psychological vulnerability to suicidal behavior: a Bayesian network of artificial intelligence applied to a clinical sample.BMC psychiatry · 2020Article
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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.
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