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.

BACKGROUND: This study was conducted to develop therapeutic communication skills for nursing students by using video clip.METHODS: The development of therapeutic communication contents were carried out in three steps: The first step is to extract the methods of therapeutic communication described in the case report prepared by a nursing student during mental clinical practice which is highly frequently used and prone to confusion. The second step is to extract cases and create scenarios that reflect the techniques extracted. The third step is to film the developed scenarios with expert advice and then edit it to reflect the content utilization to enhance the efficiency of teaching.RESULTS: Eight video content reflecting therapeutic communication techniques and eight video contents that improperly reflected therapeutic communication, a total of 16 video contents were finally developed.CONCLUSION: The developed video clip based on real error cases in this study can be utilized as an educational contents for nursing students to apply therapeutic communication skills.
Humans ; Students, Nursing

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.

Objective: Bipolar disorder displays a spectrum of manifestations, including manic, hypomanic, depressive, mixed, psychotic, and atypical episodes, contributing to its chronic nature and association with heightened suicide risk. Creating effective pharmacotherapy guidelines is crucial for managing bipolar disorder and reducing its prevalence. Treatment algorithms grounded in science have improved symptom management, but variations in recommended medications arise from research differences, healthcare policies, and cultural nuances globally. Methods: This study compares Korea’s bipolar disorder treatment algorithm with guidelines from the UK, Australia, and an international association. The aim is to uncover disparities in key recommended medications and their underlying factors. Differences in CYP450 genotypes affecting drug metabolism contribute to distinct recommended medications. Variances also stem from diverse guideline development approaches—expert consensus versus metaanalysis results—forming the primary differences between Korea and other countries. Results: Discrepancies remain in international guidelines relying on meta-analyses due to timing and utilized studies. Drug approval speeds further impact medication selection. However, limited high-quality research results are the main cause of guideline variations, hampering consistent treatment conclusions. Conclusion Korea’s unique Delphi-based treatment algorithm stands out. To improve evidence-based recommendations, large-scale studies assessing bipolar disorder treatments for the Korean population are necessary. This foundation will ensure future recommendations are rooted in scientific evidence.