Yonsei Med J.
2024 Mar;65(3):137-147. 10.3349/ymj.2023.0129.
The Prediction Model of Non-Suicidal Self-Injury in Psychiatric Patients Using Decision Tree Analysis
- Affiliations
-
- 1Department of Psychiatry, Hanyang University Hospital, Seoul, Korea
- 2Department of Counseling Psychology, Hanyang Cyber University, Seoul, Korea
- 3Department of Psychiatry, College of Medicine and Institute of Mental Health, Hanyang University, Seoul, Korea
- 4Department of Psychology, Yeungnam University, Gyeongsan, Korea
- KMID: 2553354
- DOI: http://doi.org/10.3349/ymj.2023.0129
Abstract
- Purpose
The prevalence rate of non-suicidal self-injury (NSSI) in the clinical population is higher than that in the community sample, necessitating the need to investigate the predicting factors of NSSI in this group. The present study aimed to develop a prediction model of NSSI among psychiatric patients in Korea.
Materials and Methods
Decision tree analysis was conducted on a sample of 224 psychiatric patients. Emotion regulation strategies (rumination, cognitive reappraisal, and expressive suppression), impulsivity, problematic alcohol use, working memory, depressive mood, and gender were included in the model as predictors of NSSI.
Results
Results indicated that rumination, problematic alcohol use, and working memory predicted lifetime NSSI engagement among psychiatric patients. The best predictor of lifetime NSSI engagement was rumination. Specifically, when the level of rumination was high, the level of working memory was lower, and the risk of NSSI was higher. In the case of low levels of rumination, the higher the level of problematic alcohol use, the higher the risk of NSSI. The highest prevalence of lifetime NSSI engagement was found in a subgroup of patients with high levels of rumination and low levels of working memory.
Conclusion
The major contribution of this study is finding a combination of factors to predict the high-risk group of NSSI among psychiatric patients in Korea. This study provides evidence on the effect of rumination, working memory, and problematic alcohol use on NSSI. It is suggested that clinicians and researchers should pay more attention to emotion regulation and related vulnerabilities in preventing and treating NSSI.
- Full Text Links
-
- Actions
-
Cited
- CITED
-
- Close
- Share
-
- Similar articles
-
- Data-Mining-Based Coronary Heart Disease Risk Prediction Model Using Fuzzy Logic and Decision Tree
- Predictors of Protective Factors for Internet Game Addiction in Middle School Students using Data Mining Decision Tree Analysis
- The Prediction Model of Body Image Distortion in Korean Adolescent in the Era of COVID-19 Using Decision Tree Analysis
- Analysis and Prediction of Length of Stay in the Postanesthetia Care Unit
- Comparison of the Prediction Model of Adolescents’ Suicide Attempt Using Logistic Regression and Decision Tree: Secondary Data Analysis of the 2019 Youth Health Risk Behavior Web-Based Survey
