Geun Myun Kim

Purpose: This study evaluated the validity and reliability of therapeutic communication responses generated by GPT-5 by comparing different prompt-engineering strategies and identifying optimal methods for psychiatric nursing education. Methods: A methodological design compared four strategies—Zero-shot, Few-shot, Chain-of-Thought (CoT), and Role-prompt—applied to ten psychiatric nursing communication questions. Fourteen experts with over ten years of combined clinical and educational experience rated 40 anonymized responses using a 4-point scale. Inter-rater reliability was assessed with Fleiss' κ and Krippendorff's ⍺ from 400 repeated outputs. Semantic consistency was examined using cosine similarity. Analyses were conducted in Python. Results: Role-prompt showed the highest content validity (mean=3.54±0.39, S-CVI/Ave=0.95), followed by CoT and Zero-shot. Inter-rater agreement was slight (κ=0.07; ⍺=0.15). Semantic consistency was highest for CoT (0.76±0.12) and Role-prompt (0.75±0.11). A Friedman test indicated significant differences among strategies (x2(3)=11.88, p=.008). Conclusion: Role-prompt yielded the most valid therapeutic responses, while CoT produced the most consistent outputs. These findings support the use of Role-prompt and CoT strategies to enhance the validity and reliability of therapy.

Purpose: Simulation-based education plays a critical role in nursing by allowing students to acquire clinical competencies in a safe and controlled environment. However, current evaluation tools for simulation scenarios often lack standardization, resulting in inconsistencies when assessing the effectiveness of such programs.Methods: This study aimed to develop a comprehensive Nursing Simulation Scenario Evaluation Tool using the Real-Time Delphi method. A panel of 10 experts in nursing and simulation education participated in two rounds of surveys. The evaluation criteria were derived from the International Nursing Association for Clinical Simulation and Learning Standards of Best Practice and relevant literature. Survey items were refined through expert consensus using content validity ratios and coefficient of variation values. The finalized tool was further enhanced with artificial intelligence (AI)–based evaluation capabilities to support objective and systematic assessment. The tool was registered and patented in the Republic of Korea (Korean Intellectual Property Office Registration No. 10-2024-0051234) to acknowledge its innovation and technical merit.Results: The process resulted in an evaluation tool comprising eight key domains and 36 items, covering scenario structure, learning objectives, preparation, script development, debriefing, facilitation, expected outcomes, and scenario validity. A Kendall’s coefficient of concordance of 0.739 indicated strong agreement among the experts.Conclusion: This study successfully developed a standardized and validated tool to improve the reliability and effectiveness of simulation-based education in nursing. The tool addresses a key gap in current educational practices and enhances consistency in evaluating nursing simulation scenarios. Future studies should focus on validating its application across diverse educational environments.

Purpose: This study aimed to identify predictors of health-related quality of life (HRQoL) among adults with multimorbidity using Andersen's behavioral model and to develop a predictive model with a random forest(RF) algorithm.Methods: We conducted a secondary cross-sectional analysis of the 2019-2020 Korea National Health and Nutrition Examination Survey (KNHANES) including 858 adults with two or more chronic conditions. Predictors were grouped as predisposing, enabling, need, and health-behavior factors. HRQoL was measured with the EuroQol five-dimension index (EQ5D) value based on the Korean tariff. Model performance was evaluated using mean absolute error, root mean squared error, and the coefficient of determination. Variable importance and Shapley additive explanations (SHAP) were used for interpretation. Results: The mean HRQoL was 0.90 (standard deviation 0.14). The model achieved a mean absolute error of 0.08 and a coefficient of determination of 0.15. The strongest predictors were subjective health status, days of walking per week, age, monthly income, and private medical insurance; Shapley analyses confirmed their direction and relative influence. Conclusion: Andersen's model provided a coherent framework to interpret determinants of HRQoL in multimorbidity. The findings support routine assessment of subjective health, promotion of walking, and resource linkage for older adults and individuals with limited socioeconomic resources. Interpretable machine learning may aid early risk stratification and tailored nursing interventions.

Purpose: The COVID-19 pandemic significantly impacted clinical practicums for nursing students, especially in mental health nursing, resulting in cancellations due to infection risks. In response, online and VR simulations emerged as appealing alternatives that cater to the preferences of digital-native learners. This study aimed to evaluate a VR-based mental health nursing simulation program.Methods: The study utilized a non-equivalent control group pretest-posttest design and was conducted within nursing education institutions. Fifty-four fourth-year nursing students, who had theoretical knowledge but lacked clinical experience, participated after providing informed consent. The program consisted of six thematic modules that simulated real-world scenarios, and its effectiveness was assessed using repeated measures ANOVA.Results: The findings revealed significant improvements in knowledge related to mental health disorders, learning flow, and overall satisfaction. The program successfully bridged the gap between theoretical and practical learning, enhancing students' skills and confidence in patient interactions and therapeutic nursing interventions.Conclusion: The simulation education program effectively served as a bridge between theoretical learning and practical application, providing students with a valuable educational experience. By improving students' abilities and confidence in engaging with patients and delivering therapeutic nursing interventions, the program demonstrated its potential to connect classroom learning with real-world clinical practice in mental health nursing.

Purpose: To identify factors affecting turnover intention of long-term care hospital nurses.Methods: After receiving permission from nursing managers at 10 nursing hospitals with 100 to 500 beds in three cities in South Korea, nurses who agreed to participate in this study were recruited and a survey was conducted. Final participants included 172 long-term care hospital nurses. Data collection was conducted from January 2, 2024 to April 30, 2024. Questionnaires included job stress, ethical dilemma, burnout, and turnover intention. Statistical analysis was performed using t-test, analysis of variance, Pearson’s correlation coefficient, and multiple regression analysis.Results: Ethical dilemma, job stress, burnout, and turnover intention of long-term care hospital nurses all had significant positive correlations. Age, position, job stress, and burnout were substantial in the turnover intention of long-term care hospital nurses.Conclusion: Findings of this study can be used as primary data for improving the quality of nursing in long-term care hospitals, promoting efficient human resource management, and establishing policies.

Purpose: This study aims to systematically review the literature and conduct a meta-analysis to thoroughly analyze the outcomes of studies on simulation programs in psychiatric nursing.Methods: We conducted an initial search from January 1, 2000, to September 30, 2023, using databases such as PubMed, EMBASE, CINAHL, the Cochrane Library, and Web of Science. A total of 2,571 articles were reviewed based on inclusion and exclusion criteria. We selected 35 articles for systematic literature review and subjected 20 of them to meta-analysis. Data analysis was conducted using descriptive statistics and the Comprehensive Meta-Analysis program.Results: The number of psychiatric nursing simulation programs has increased since 2015. The most common programs used Standard Patients (SP), but studies using Virtual Reality (VR), audio, video, and other methods have recently been reported. The programs addressed various mental health issues, including depression, suicide, violence, alcohol problems, and mood disorders. Overall, considering all the studies, a significant effect was observed with a pooled Hedges’s g value of 0.56 (95% CI: 0.35~0.78; p<.001).Conclusion: These findings highlight the importance of incorporating simulation-based education into nursing curricula to equip professionals with the skills to provide high-quality care to individuals with mental health problems. Further research is needed to explore the long-term benefits of these educational interventions on patient care.

Purpose: The aim of the study was to conduct a systematic review and meta-analysis of nurses’ turnover intention in existing studies.Methods: A literature search was conducted in two rounds. The first round was performed on December 16, 2018. The search period was from January 1, 2008, to December 16, 2018, and involved seven databases: MEDLINE and EMBASE, which are international academic databases, and KoreaMed, KERIS, KISS, KISTI, and KMbase, which are domestic academic databases. The second search round was performed on July 2, 2022. The search period was from 2019 to 2022.Results: Fifty-three variables associated with turnover intention were identified in articles in the first round, with significantly associated work- and organization-related parameters, including burnout, emotional labor, job stress, role conflict, job satisfaction, and organizational commitment. Thirty-eight variables were identified in the second round, with mental and psychological parameters, including mental health and psychological capital, having a more significant influence.Conclusion: The findings of this study can be used to prevent the turnover of hospital nurses and develop strategies for retaining excellent and professional hospital nurses.

Purpose: This study investigates the impact of a Virtual Reality (VR)-based Mental Health Nursing Practice Simulation (MHNPS) on nursing students’ competency in caring for individuals with mental disorders. Nursing students often face fear, anxiety, and helplessness during mental health (MH) rotations, impeding the attainment of learning objectives in the MH nursing practicum. Therefore, innovative strategies offering practice opportunities are crucial for their competence development. Methods: Using a one-group pretest-posttest repeated measures experimental design, 50 nursing students, having completed at least one MH theory course but not yet engaged in MH clinical practicum, were enrolled. Data collection occurred from October 30, 2022, to January 6, 2023. The VR simulation included six modules covering delusion, hallucination, mania, geriatric depression, adolescent depression with suicidal ideation, and obsessive-compulsive disorder. Pre-simulation questionnaires and post-simulation surveys were administered through provided links. Data were analyzed using descriptive statistics and paired t-tests to assess changes over time. Results: Immediate and sustained improvements were observed in mental disorder-related nursing knowledge, communication self-efficacy, critical thinking ability, and MH nursing clinical confidence. Attitudes toward mental illness improved significantly post-intervention (t=− 2.22, p=0.031), while the problem-solving process exhibited significant enhancement six weeks later (t=3.87, p< 0.001). Conclusion: The findings affirm the simulation intervention’s effectiveness in enhancing nursing students’ knowledge, self-efficacy, critical thinking, and confidence in MH nursing practice, with no compromise to patient safety. Integrating simulation into MH nursing practicum narrows the gap between theory and clinical practice, elevates MH care quality, and instills confidence in nursing students as professionals. Despite potential subject selection bias in this single-group pre-post intervention study, the program’s comprehensive impact on knowledge, skills, and attitudes suggests opportunities for expanding psychiatric nursing practice capabilities through subsequent studies. Caution is warranted in interpreting results, but the developed program lays the groundwork for advancing nursing students’ capabilities in psychiatric nursing practice.