Journal of Korean Academy of Nursing

Yoonju Lee

2 Articles

Influence of Illness Uncertainty on Health Behavior in Individuals with Coronary Artery Disease: A Path Analysis: Hyesun Jeong, Yesul Lee, Jin Sup Park, Yoonju Lee; J Korean Acad Nurs 2024;54(2):162-177. Published online May 31, 2024; DOI: https://doi.org/10.4040/jkan.23136

Purpose
This study aimed to investigate the influence of uncertainty-related factors on the health behavior of individuals with coronary artery disease (CAD) based on Mishel’s uncertainty in illness theory (UIT).
Methods
We conducted a cross-sectional study and path analysis to investigate uncertainty and factors related to health behavior. The study participants were 228 CAD patients who visited the outpatient cardiology department between September 2020 and June 2021. We used SPSS 25.0 and AMOS 25.0 software to analyze the data.
Results
The final model demonstrated a good fit with the data. Eleven of the twelve paths were significant. Uncertainty positively affected danger and negatively affected self-efficacy and opportunity. Danger had a positive effect on perceived risk. Opportunity positively affected social support, self-efficacy, perceived benefit and intention, whereas it negatively affected perceived risk. Social support, self-efficacy, perceived benefit and intention had a positive effect on health behavior. We found that perceived benefit and intention had the most significant direct effects, whereas self-efficacy indirectly affected the relationship between uncertainty and health behavior.
Conclusion
The path model is suitable for predicting the health behavior of CAD patients who experience uncertainty. When patients experience uncertainty, interventions to increase their self-efficacy are required first. Additionally, we need to develop programs that quickly shift to appraisal uncertainty as an opportunity, increase perceived benefits of health behavior, and improve intentions.

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Self-Care, Resilience, and Uncertainty in Patients After Coronary Artery Bypass Graft Surgery
Eun-Hye Park, JiYeon Choi, Phill Ja Kim, Jiyeon Lee
Journal of Cardiovascular Nursing.2025;[Epub] CrossRef
Association between Coping Profiles and Cardiac Health Behavior among Patients with Coronary Artery Disease: A Latent Profile Analysis
Yesul Lee, Yoonju Lee, Jeong Cheon Choe, Hyesun Jeong, Sunyoung Jung
Korean Journal of Adult Nursing.2024; 36(3): 228. CrossRef

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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: Yoonju Lee, Heejin Kim, Yesul Lee, Hyesun Jeong; J Korean Acad Nurs 2021;51(1):40-53. Published online February 28, 2021; DOI: https://doi.org/10.4040/jkan.20207

Abstract PDF

Purpose
The purpose of this study was to develop and compare the prediction model for suicide attempts by Korean adolescents using logistic regression and decision tree analysis. Methods: This study utilized secondary data drawn from the 2019 Youth Health Risk Behavior web-based survey. A total of 20 items were selected as the explanatory variables (5 of sociodemographic characteristics, 10 of health-related behaviors, and 5 of psychosocial characteristics). For data analysis, descriptive statistics and logistic regression with complex samples and decision tree analysis were performed using IBM SPSS ver. 25.0 and Stata ver. 16.0.
Results
A total of 1,731 participants (3.0%) out of 57,303 responded that they had attempted suicide. The most significant predictors of suicide attempts as determined using the logistic regression model were experience of sadness and hopelessness, substance abuse, and violent victimization. Girls who have experience of sadness and hopelessness, and experience of substance abuse have been identified as the most vulnerable group in suicide attempts in the decision tree model.
Conclusion
Experiences of sadness and hopelessness, experiences of substance abuse, and experiences of violent victimization are the common major predictors of suicide attempts in both logistic regression and decision tree models, and the predict rates of both models were similar. We suggest to provide programs considering combination of high-risk predictors for adolescents to prevent suicide attempt.

Citations

Citations to this article as recorded by

Factors Influencing Suicidal Ideation in Female Adolescents With Smartphone Overdependence
Hyeongyeong Yoon
Journal of Pediatric Health Care.2025; 39(2): 225. CrossRef
Public discourse on substance use behavior as a driver of public policy: a scoping review of South Korean academic and official literature
Meekang Sung, Jihye Han, Carrie G. Wade, Vaughan W. Rees
Addiction Research & Theory.2025; 33(4): 312. CrossRef
Risk prediction models for adolescent suicide: A systematic review and meta-analysis
Ruitong Li, Yuchuan Yue, Xujie Gu, Lingling Xiong, Meiqi Luo, Ling Li
Psychiatry Research.2025; 347: 116405. CrossRef
Predictive Performance of Machine Learning for Suicide in Adolescents: Systematic Review and Meta-Analysis
Lingjiang Liu, Zhiyuan Li, Yaxin Hu, Chunyou Li, Shuhan He, Shibei Zhang, Jie Gao, Huaiyi Zhu, Guoping Huang
Journal of Medical Internet Research.2025; 27: e73052. CrossRef
The use of machine learning on administrative and survey data to predict suicidal thoughts and behaviors: a systematic review
Nibene H. Somé, Pardis Noormohammadpour, Shannon Lange
Frontiers in Psychiatry.2024;[Epub] CrossRef
A prediction model for adolescents’ skipping breakfast using the CART algorithm for decision trees: 7th (2016–2018) Korea National Health and Nutrition Examination Survey
Sun A Choi, Sung Suk Chung, Jeong Ok Rho
Journal of Nutrition and Health.2023; 56(3): 300. CrossRef
Development of Prediction Model for Suicide Attempts Using the Korean Youth Health Behavior Web-Based Survey in Korean Middle and High School Students
Younggeun Kim, Sung-Il Woo, Sang Woo Hahn, Yeon Jung Lee, Minjae Kim, Hyeonseo Jin, Jiyeon Kim, Jaeuk Hwang
Journal of Korean Neuropsychiatric Association.2023; 62(3): 95. CrossRef
Effects of Stress on Suicide Behavior among Adolescents: An Analysis of Online Survey Data on Youth Health Behavior Using Propensity Score Matching
Chung Hee Woo, Ju Young Park
Korean Journal of Stress Research.2021; 29(3): 199. CrossRef

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